NSS Program & Topics
NSS Topics
Authors are invited to submit papers describing their original, unpublished work on one of the topics below:
- Analog and Digital Circuits
- DAQ, Trigger and Front-End Electronics Systems
- AI and Machine Learning for Radiation Detection
- Modeling, Computational Methods, and Data Analysis
- Neutron and Gamma ray Imaging
- Photodetectors
- Organic Scintillators
- Inorganic Scintillators
- Semiconductor and Gaseous Detectors
- Unconventional Detectors
- Nonproliferation, National, and Homeland Security
- Safeguards, treaty verification, contraband detection
- Nuclear and High-Energy Physics, and Astrophysics
- Radiation Damage Effects and Rad-Hard Devices
- Nuclear measurement, dosimetry and reactor applications
The IEEE Nuclear Science Symposium (NSS) brings together the very large and diverse international community of ionizing radiation detector scientists and engineers. We look forward to welcoming you in the beautiful city of Tampa in 2024!
The NSS 2024 program incorporates the latest developments in detector technology and materials, new instrumentation techniques, their implementation in high energy and nuclear physics, astrophysics, accelerators, nuclear security, and many other applications in various types of radiation environments. The program will also include emerging fields and current hot topics in nuclear science instrumentation.
Interdisciplinary state-of-the-art developments will be included in the joint sessions with the MIC and RTSD. Special topic workshops will cover areas of specific interests and short courses will be offered on a variety of traditional and novel topics of interest to the NSS community.
NSS Plenary Sessions
Thea Klaeboe Aarrestad is a fellow at the Institute for Particle Physics and Astrophysics at ETH Zürich. She holds a PhD in Particle Physics from the University of Zürich and has worked as a research fellow at CERN in Geneva before moving to ETH. Her research centers on how Machine Learning can be applied to particle physics problems, especially focusing on using real-time Machine Learning (ML) and anomaly detection for discovering new physics phenomena. She has worked on tools for performing low-power, nanosecond ML inference on field-programmable gate arrays (FPGAs), as well as developing new ML-based methods for collecting and analysing proton collision data at the CERN Large Hadron Collider. She holds several publications in the topics of machine learning and particle physics in journals like Nature Machine Intelligence, PRL and JHEP. She also coordinates the Fast Machine Learning for Science Laboratory and the Targeted Systems Group within the Accelerated AI Algorithms for Data-Driven Discovery (A3D3) Institute.
At the CERN Large Hadron Collider (LHC), real-time event filtering systems must process millions of proton-proton collisions every second on field programmable gate arrays (FPGAs) and perform efficient reconstruction and decision making. Within a few microseconds, over 98% of the collision data must be discarded fast and accurately. As the LHC is upgraded to its high luminosity phase, HL-LHC, these systems must deal with an overwhelming data rate corresponding to 5% of the total internet traffic and will face unprecedented data complexity. In order to ensure data quality is maintained such that meaningful physics analyses can be performed, highly efficient ML algorithms are being utilised for data processing. This has necessitated the development of novel methods and tools for extremely high throughput, ultra low latency inference on specialised hardware.
In this talk, we will discuss how real-time ML is used to process and filter enormous amounts of data in order to improve physics acceptance. We will discuss state-of-the-art techniques for designing and deploying ultrafast ML algorithms on FPGA and ASIC hardware. Finally, we will explore applications of real-time inference in particle physics experiments and beyond.
Nerine Cherepy has been a Research Scientist at Lawrence Livermore National Laboratory since 1998, after earning her PhD at the University of California, Berkeley and completing a postdoctoral and teaching appointment at the University of California, Santa Cruz. She is working on the development of light-emitting materials – single crystals, transparent ceramics, phosphors and plastics – for uses in ionizing radiation detection, imaging screens, lighting and laser optics. She is an SPIE Fellow (2018), a Senior Member of IEEE (2014), serves as an Associate Editor for IEEE TNS (since 2015), and has contributed to three winning R&D 100 awards.
Transparent ceramics are polycrystalline, monolithic, fully-dense optics that offer advantages over single crystals and glasses, as they are amenable to production of high uniformity plates as well as volumetric optics with uniform doping, needed for high performance scintillators. The rugged mechanical properties of transparent ceramics facilitate easy machining and deployment into harsh environments. For lens-coupled radiographic imaging, thin transparent scintillators with low optical scatter are required. Our team developed the bixbyite (Gd,Lu,Eu)2O3, or “GLO,” scintillator, offering high density (9.1 g/cm3) and high light yield for MeV radiography and computed tomography. We have fielded multiple 14” x 14” GLO plates into X-ray CT systems to achieve high efficiency while preserving spatial resolution. Ce-doped Gd garnet transparent ceramics provide the high light yield needed for high energy resolution gamma spectroscopy. The scintillation physics of garnet ceramics may be tuned by controlling the intra-band gap trap state distribution, thereby optimizing the light yield proportionality, pulse duration and afterglow. Recent advances in fabrication and implementation of ceramic scintillators into systems will be described.
Nerine Cherepy
Dr. Nina Lanza is a staff scientist in Space Science and Applications (ISR-1) at Los Alamos National Laboratory. She is the Principal Investigator of the ChemCam instrument onboard the Mars Science Laboratory Curiosity rover and a science team member for the SuperCam instrument onboard the Mars 2020 Perseverance rover. Her current research focuses on understanding the origin and nature of manganese minerals on Mars and how they may serve as potential biosignatures. She is also studying how sound on Mars may help to identify rock coatings, which provide a record of the interaction between rock, atmosphere, water, soil, and potentially life. Dr. Lanza has authored over 60 peer-reviewed publications, including two first-author book chapters. Dr. Lanza has done geologic fieldwork in numerous locations across the world including the Miller Range, Antarctica; Devon and Axel Heiberg islands in the Canadian Arctic; Rio Tinto, Spain; Death Valley, CA; Black Point Lava Flow, AZ; Green River, UT; as well as many sites across New Mexico. Notably, she was a field team member for the Antarctic Search for Meteorites (ANSMET) project during the 2015 – 2016 season, for which she recovered meteorites from remote field locations in Antarctica. She is also a regular contributor on the television series How the Universe Works (The Science Channel). Dr. Lanza was educated at Smith College (AB), Wesleyan University (MA), and the University of New Mexico (PhD). She is thrilled to be living her childhood dream of working on a spaceship.
Mars has long captured our imaginations as a potential home for past, present, and future life. Current tools now allow for these questions to be addressed scientifically. There are two NASA-led rovers, Curiosity and Perseverance, currently exploring the surface of Mars that seek to answer these questions in different ways. Curiosity has been exploring the martian surface for the past 12 Earth years, while Perseverance landed almost four Earth years ago. Each rover is equipped with an instrument payload designed to answer fundamental questions about martian geology, climate, habitability, and the possibility for past life. While Mars and Earth have had very different histories and evolutionary paths, our deep and evolving knowledge of Earth provides us with critical context in which to interpret data returned from Mars. In this talk, we will discuss ongoing work from both rover missions, including plans for returning geologic samples from Mars to Earth for the very first time.
Nina Lanza
MIC Program & Topics
The IEEE Medical Imaging Conference (MIC)
The IEEE Medical Imaging Conference (MIC) is a leading international scientific meeting to discuss the latest physics, engineering, and mathematical innovations in medical imaging with a particular focus on applications of ionizing radiation.
Medical imaging is a continuously growing field where technical advances in detectors, instrumentation, computational methods, and integrated systems pave the way towards advances in clinical detection, diagnosis, treatment, and monitoring as well as clinical research into the underlying mechanisms of disease and treatment. In recent years, there has been increased interest in applications of machine learning, AI, and other rapidly emerging areas of research, and innovations in these areas continue to play an increasing role in medical imaging.
MIC is an opportunity for students, post-doctoral fellows, and junior and senior researchers from around the world to come together to share their new ideas and results of innovations and scientific endeavors.
The scientific program of the MIC consists of oral and poster sessions, plenary sessions, and a student award session. Regular sessions will be complemented by Short Courses and specialized workshops covering timely topics in medical imaging and therapy.
MIC Topics
Authors are invited to submit papers describing their original, unpublished work on one of the topics below:
- New radiation detector technologies for medical imaging
- Simulation and modeling of medical imaging systems
- Total-body, whole-body, and multi-modality clinical emission systems
- High resolution imaging systems (organ-dedicated, small animal systems)
- X-ray imaging systems (CT, spectral CT, photo-counting CT)
- Tomographic reconstruction techniques
- Quantitative imaging
- Kinetic Modeling
- Signal and image processing, image assessment, standardization
- Applications in brain and body
- Emerging applications, new concepts (e.g., self-collimation in SPECT)
- Imaging in particle therapy and image-guided interventions
RTSD Program & Topics
Room Temperature Semiconductor Detector Conference (RTSD)
The Room Temperature Semiconductor Detector Conference (RTSD) represents the largest forum of scientists and engineers developing compound semiconductor radiation detectors and imaging arrays operable at room temperature.
Room-temperature semiconductor radiation detectors are finding increasing applications in such diverse fields as medicine, homeland security, radiography, astrophysics and environmental monitoring. The objective of this conference is to provide a forum for discussion of the state of the art for room-temperature-operating detector technology based on compound semiconductors, including materials improvement, material and device characterizations, fabrication, electronic readout, system development and applications. To provide a comprehensive review, oral and poster presentations representing a broad spectrum of research and development activities emphasizing compound semiconductor detectors or imaging devices are sought.
RTSD Topics
Authors are invited to submit papers describing their original, unpublished work on one of the topics below:
- Compound Semiconductor Materials for Radiation Detection
- Organic and Perovskite Materials for Radiation Detection
- Crystal Growth, Materials and Defect Characterization
- Properties of Electrical Contacts and Device Fabrication Technology
- Radiation Damage, Long-Term Stability and Environmental Effects
- Pixel, Strip, Frisch-Grid and Discrete Semiconductor Detectors
- Detector/ASIC Hybridization, Interconnects and Electronics
- Scintillator/Semiconductor Array Hybrids
- Compound Semiconductor Neutron Detectors
- 3D Photon Tracking Detectors and Image Reconstruction Technology
- Use of AI/ML tools for Analysis of Detector Signals and Decision Making
- Spectrometer Systems for Homeland Security, Nuclear Inspections, Safeguards, Portal Monitoring, and Other Uses
- Imaging Systems based on Compound Semiconductor Detectors for Medical, Astrophysics, Non-Destructive Testing, Cargo Monitoring, Environmental Monitoring and Other Uses
Short Courses
Please note that this is a two-day course!
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Course title: |
Radiation Detection and Measurement (2024) |
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Course organizer: |
David K. Wehe, University of Michigan, USA |
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Date/time/venue: |
Saturday, 26 Oct. – 8:30 am – 5:00 pm – Venue: tba Sunday, 27 Oct. – 8:30 am – 5:00 pm – Venue: tba |
Instructors:
- Jarek Glodo, Radiation Monitoring Devices, Inc., USA
- Robert Redus, Amptek, Inc., USA
- David Wehe, University of Michigan, USA
- Florian Brunbauer, CERN, Switzerland
- Lothar Strueder, PNSensor GmbH, Germany
- Shaun Clarke, University of Michigan, USA
- Zhong He, University of Michigan, USA
Course Description
This 2-day course provides an overall review of the basic principles that underlie the operation of all major types of instruments used in the detection and spectroscopy of charged particles, gamma rays, and other forms of ionizing radiation. Examples of both established applications and recent developments are drawn from areas including particle physics, nuclear medicine, homeland security, and general radiation spectroscopy. Emphasis is on understanding the fundamental processes that govern the operation of radiation detectors, rather than on operational details that are unique to specific commercial instruments. This course does not cover radiation dosimetry nor health physics instrumentation. The level of presentation is best suited to those with some prior background in ionizing radiation interaction mechanisms. Those with prior experience in radiation measurements would benefit from discovering concepts and applications outside their experience base. A complete set of course notes is provided to registrants, and a recent copy of Radiation Detection and Measurement by G. F. Knoll is highly recommended.
Course Outline
I. Fundamental Concepts in Ionizing Radiation Detection
II. Gas-Filled Detectors
III. Scintillation Detectors
IV. Semiconductor Detectors
V. Analog and Digital Electronics for Radiation Measurements
VI. Pulse Shape Discrimination and Multi-modality Sensing
VII. Recent Detector Developments and Summary
Instructors’ Biographies
ROBERT REDUS is a Member of the IEEE and is the Chief Scientist and Director of Engineering at Amptek, an Ametek company in Bedford, MA. He has spent over thirty years designing instruments for radiation detection and measurement, for many applications and many customers. These include X-ray spectroscopy, gamma-ray spectroscopy using compound semiconductors, scintillators, and HPGe detectors, and space radiation measurements.
JAREK GLODO is Senior Scientist and Team Leader at Radiation Monitoring Devices, Inc. His research areas of interest include novel scintillation materials for high resolution gamma-ray spectroscopy including CeBr3, LuI3:Ce and SrI2:Eu and dual mode scintillators such as Cs2LiYCl6:Ce, Cs2LiLaBr 6:Ce and Cs2LiLa(Br,Cl)6:Ce for combined detection of gamma-rays and neutrons. He has also worked in the areas of ceramic scintillators including garnets and silicates, and organic crystalline and plastic scintillators for neutron detection.
FLORIAN BRUNBAUER is working on the development of novel gaseous detectors. Florian is a Fellow in the CERN Gaseous Detector Development (GDD) group. Florian joined CERN with a focus on optical readout of MicroPattern Gaseous Detectors (MPGDs). He explored applications of scintillation light readout for GEM detectors in TPCs, beam monitoring applications and radiation imaging. He is working on precise timing detectors based on the Picosec Micromegas concept as well as exploring novel MPGD technologies.
LOTHAR STRUEDER is the scientific director of PNSensor GmbH and professor at the University of Siegen. He earned his Ph.D. in Experimental Physics at the TU Munich in 1988. His interests include position-, energy-, and time-resolving detectors for photons and particles. He is author or co-author of more than 300 technical and scientific publications. He has been issued 13 worldwide patents in scientific instrumentation.
DAVID WEHE is Professor of Nuclear Engineering and Radiological Sciences at University of Michigan. He worked at the Oak Ridge National Laboratory as a Wigner Fellow, and served as Director of the Michigan Phoenix Memorial Project, which included the 2-MW Ford Nuclear Reactor. His teaching and research have focused on applied radiation measurements, as an editor for Nuclear Instruments and Methods in Physics Research, and general chair of the SORMA international conference.
SHAUN CLARKE has almost two decades of experience performing radiation detection measurements and Monte Carlo modeling at Michigan. He has organized and performed numerous experimental campaigns involving measurements of special nuclear material with organic scintillation detectors and state-of-art digital electronics. His current interests are active interrogation systems for nuclear nonproliferation, safeguards, and treaty verification applications.
ZHONG HE invented the 3D-readout technique which forms the basis of room-temperature semiconductor operation, enabling excellent energy resolution and gamma-ray imaging with a single CdZnTe crystal. Prof. He founded H3D Inc., and is known for his work with position-sensitive room-temperature semiconductor radiation imaging detectors, low-noise charge sensitive application specific integrated circuitries, and gamma-ray image reconstruction.
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Course title: |
Front-End Electronics for Radiation Detectors |
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Course organizer: |
Gianluigi De Geronimo |
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Date/time/venue: |
Saturday, 26 Oct. – 8:00 am – 6:10 pm – Venue: tba |
Instructors:
• Gianluigi De Geronimo, University of Michigan, Stony Brook University, and DG Circuits, USA
• Lodovico Ratti, Institute for Nuclear Physics (INFN), Italy
• Yuefeng Zhu, University of Michigan, USA
Course Description
Successful front-end electronics developments are the result of a close collaboration between electronics engineers and a broad range of detector, data acquisition, and system-level specialists. Conceived by three experienced instructors, this one-day Course aims at providing participants with the fundamental concepts needed to understand front-end design and facilitate communications and collaborations. The first section of the Course introduces less experienced circuit designers, physicists, and other detector specialists to the fundamentals of low-noise front-end circuit design. This year students are required to bring their laptop with pre-installed software (information will be provided) since they will interactively participate with the instructor in examples of noise analysis and front-end electronics design and simulation. The second section of the Course deepens into two selected subjects of broad interest to our community: radiation tolerance and digital signal processing.
Course Outline
Fundamentals Part 1 – Gianluigi De Geronimo (Coordinator)
• Noise sources and equivalent noise charge
• Noise analysis in frequency and time domain
• Interactive noise analysis, design and simulations
Fundamentals Part 2 – Gianluigi De Geronimo
• Charge amplifier design
• Filter design
• Mixed-signal circuits
• Interactive noise analysis, design and simulations
Radiation Tolerance – Lodovico Ratti
• Introduction: radiation environments and radiation sources
• Ionizing radiation effects on MOSFET transistors
• Ionizing radiation effects: from low to extreme doses
• Ionizing radiation effects: from bulk CMOS to finFETs
• Rad-tolerant design strategies
• Effect of bulk damage on the dark count rate in CMOS SPADs
Digital Signal Processing – Yuefeng Zhu
• Fundamentals: sampling theory, time and frequency domain analysis, Fourier transform
• Advanced topics: noise analysis, digital filtering, curve fitting, pulse shape discrimination, principal component analysis
• Case study: CdZnTe signal processing
Instructors’ Biographies
GIANLUIGI DE GERONIMO received his M.S. and Ph.D. from the Electronics and Communications Department of Milan Polytechnic, Italy, in 1993 and 1997 respectively. In September 1997 he joined the Instrumentation Division of Brookhaven National Laboratory in NY where he specialized in the design of low-noise integrated circuits for ionizing radiation detectors growing from assistant scientist to tenured and head of microelectronics. He developed several front-end ASICs for a wide range of applications in medical imaging, space, security, defense, and physics research. Dr. De Geronimo has co-authored over 150 scientific publications and two book chapters and is recipient of the 2008 BNL Science and Technology Award, 2009, 2011, and 2014 R&D 100 Award, 2012 CSIRO Award, 2012 Battelle Inventor of the Year Award, 2018 IEEE LI Section Charles Hirsch Award. He is currently a research scientist and professor with the University of Michigan, professor with the Stony Brook University, consultant, and editor for IEEE Transactions on Nuclear Science.
LODOVICO RATTI (M’ 2000, SM’2013) is full professor of electronics with the University of Pavia, Department of Electrical, Computer and Biomedical Engineering, Italy. His main expertise is in the field of front-end electronics for highly segmented radiation detectors and monolithic sensors, in particular based on CMOS processes, and of ionizing radiation effects, bulk damage and noise characterization in microelectronic devices and circuits. The target applications are in the area of high energy physics, astrophysics and photon science experiments. Lodovico Ratti is a member of the Radiation Instrumentation Steering Committee (RISC) of the Nuclear and Plasma Science Society (NPSS) and Chair of the Nuclear and Plasma Sciences (NPS) Italy Chapter. He is a technology research fellow with the Italian Institute for Nuclear Physics (INFN). He is author or co-author of 300 among papers published in peer-reviewed journals or conference proceedings, works presented at international conferences and book chapters, and editor for IEEE Transactions on Nuclear Science, Frontiers in Physics and MDPI Electronics.
YUEFENG ZHU received his Ph.D. from the department of Nuclear Engineering and Radiological Sciences of the University of Michigan, Ann Arbor, USA. After graduation, he stayed at the University of Michigan as an associate research scientist. His main interest is room-temperature semiconductor radiation detectors, including CdZnTe, HgI2, TlBr, perovskite etc. In the past decades, he has been working on readout system design for digitizer AISCs, calibration and reconstruction algorithm development for pixelated semiconductor detectors, radiation imaging based on pixelated detectors, digital signal processing methods for digitizer ASICs etc.
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Course title: |
Modern and Emerging AI for Radiation Detection |
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Course organizer: |
James Ghawaly |
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Date/time/venue: |
Sunday, 27 Oct. – 8:30 am – 5:00 pm – Venue: tba |
Instructors:
• Dr. James Ghawaly Jr., Louisiana State University, Computer Science and Engineering, USA
• Dr. Miltos Alamaniotis, University of Texas San Antonio, Electrical and Computer Engineering, USA
Abstract
This short course introduces the application of cutting-edge artificial intelligence methodologies for radioactive source detection and identification. Designed for graduate students and professionals in nuclear engineering, physics, and related STEM fields, the curriculum will cover fundamental AI concepts, foundational AI models, and machine learning techniques applied to radiation detection technologies. Participants will gain practical insights through case studies involving neural networks, deep learning models, and anomaly detection systems that improve the accuracy and efficiency of detecting and identifying radioactive sources in low signal-to-noise ratio settings. By the end of this course, attendees will possess a strong understanding of potential AI technologies, enabling them to start applying these innovations to enhance radiation detection systems in their respective fields.
Course Outline
Instructors’ Biographies
DR. JAMES GHAWALY is an Assistant Professor of Computer Science & Engineering at Louisiana State University (LSU), where he researches modern and emerging machine learning techniques, with applications to national security. He also holds joint appointments with the LSU Center for Computation and Technology (CCT) and the LSU Office of Academic Affairs (OAA). Prior to LSU, he was a staff research data scientist at Oak Ridge National Laboratory (ORNL). In the past 5 years, he has led over $2m in research efforts to develop deep learning and neuromorphic computing approaches for national security challenges, sponsored by DOE NNSA, DHS CWMD, DTRA, and other federal government agencies. Dr. Ghawaly has developed deep learning approaches to signature detection in low signal-to-noise ratio sensor data streams, multimodal data fusion algorithms (imagery, LiDAR, text, time series sensor data) for object detection and characterization, LLMs for cybersecurity applications, and multimodal contrastive learning approaches for object similarity detection. At LSU, he teaches a course on large language models (LLMs) for undergraduate upperclassman and is developing a graduate-level deep learning course focusing on LLMs.
DR. MILTOS ALAMANIOTIS is Associate professor and the GreenStar Endowed Fellow in Energy in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio (UTSA). Before joining UTSA, he worked as a researcher at Purdue University. He received his BS in Electrical and Computer Engineering from the University of Thessaly, 2005, and MS and PhD in Nuclear Engineering with an emphasis in Applied Artificial Intelligence from Purdue University in 2010 and 2012, respectively. His interdisciplinary research focuses on the development of Artificial Intelligence and machine learning approaches applied to intelligent energy systems, nuclear power systems, and nuclear security to detect hidden radioactive materials. He has published over two hundred (200) research papers in scientific journals, books and proceedings of international conferences. He serves as Associate Editor in the International journal on Artificial Intelligence Tools, Internet of Things (Elsevier), and as Program Chair in IEEE International Tools with Artificial Intelligence 2018 and 2020. He had worked as an external researcher at Argonne National Laboratory (Illinois, USA) from 2010 to 2012, as visiting researcher in the Energy and Power Systems group at Oak Ridge National Laboratory (Tennessee, USA) in May 2016, and at the Nevada National Security Laboratory (USA). He is the recipient of the Distinguished Alumnus Award of the Department of Electrical and Computer Engineering. University of Thessaly in July 2017, and the Presidential Award for Distinguished Research Achievements at UTSA in 2022. In 2023, the National Academy of Engineering included him in the “top-notch 100 Early Career Engineers in USA” for the 2023 Frontiers-of-Engineering Symposium.
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Course title: |
PET Kinetic Modeling and Parametric Imaging |
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Course organizer: |
Guobao Wang, Marc Normandin |
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Date/time/venue: |
Monday, 28 Oct. – 8:30 am – 5:00 pm – Venue: tba |
Instructors:
• Marc Normandin, Yale University
• Guobao Wang, UC Davis
Course Description
Dynamic PET imaging with tracer kinetic modeling can provide images of physiologically important parameters that have the advantages of creating higher lesion contrast, being quantitative, and allowing single tracer multiparametric imaging as compared to standard static images. Conventionally, dynamic PET parametric imaging was hampered by limited scanner sensitivity and axial field-of-view. State-of-the-art commercial PET scanners now have achieved unprecedented sensitivity and also enabled simultaneous dynamic imaging of the entire body. It is becoming increasingly feasible to exploit kinetic modeling and parametric imaging for various clinical applications. This course will provide an overview of the basics of PET tracer kinetic modeling and parametric imaging and clinical applications. It will also cover recent advances in total-body PET kinetic modeling. The intended audience is anyone who would like to gain a better understanding of PET kinetic modeling and parametric imaging.
Course Outline
• Basics of dynamic PET quantification
• Compartment modeling
• Graphical and linearized models
• Reference-tissue modeling methods
• Direct estimation of kinetic parameters
• Brain applications
• Oncological and cardiac applications
• Total-body PET kinetic modeling
• Applications of total-body PET kinetic modeling
Prerequisites for this course: Basic understanding of PET physics and mathematics.
Instructors’ Biographies
MARC D. NORMANDIN is an Associate Professor at Yale Medical School. Dr. Normandin’s work spans a variety of laboratory and medical imaging techniques toward the development and application of noninvasive physiological measurement technologies and assessment of therapeutic interventions. To that end, he utilizes pharmacokinetic analysis techniques, radiosynthetic/analytic procedures, and molecular biology assays to characterize biological processes in cell culture, tissue samples, and in vivo imaging in animals and human subjects. He is a recognized worldwide as a leader in molecular imaging, especially quantitative methodology for PET and MRI, and serves the scientific community through teaching locally and internationally in the acclaimed PET Pharmacokinetics Course held annually as a satellite to the NeuroReceptor Mapping and BrainPET conferences.
GUOBAO WANG is an Associate Professor in the Department of Radiology, University of California Davis Health. He is a recipient of NIH/NIBIB Trailblazer Award and NIH/NCI Paul Calabresi Clinical Oncology K12 Research Scholar. His primary research interest is in the theory and practice of PET parametric imaging. The research in his laboratory commonly integrates multidimensional (e.g., dynamic) PET data acquisition with the design of advanced computational imaging algorithms to derive quantitative parametric imaging biomarkers for assessing human diseases. In close collaboration with clinicians, his group is actively pursuing novel clinical translation of PET/CT parametric imaging in various diseases, including metastatic cancer, fatty liver disease, and heart disease. Dr. Wang is an Associate Editor for the journal IEEE Transactions on Radiation in Plasma and Medical Sciences.
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Course title: |
Medical Image Reconstruction and Processing with AI |
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Course organizer: |
Joyita Dutta, Arman Rahmim |
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Date/time/venue: |
Monday, 28 Oct. – 8:30 am – 5:00 pm – Venue: tba |
Instructors:
• Joyita Dutta
• Arman Rahmim
• Quanzheng Li
• Tyler Bradshaw
Course Description
This course delves into the cutting-edge techniques of medical imaging reconstruction and processing, with a focus on molecular imaging modalities, especially PET. Participants will explore how Artificial Intelligence (AI) revolutionizes reconstruction and processing tasks, enhancing image quality, diagnostic accuracy, and clinical utility. Through a combination of theoretical knowledge, practical demonstrations, and hands-on exercises, participants will gain proficiency in leveraging AI for advanced image reconstruction and processing in molecular imaging.
Course Outline
• Overview of molecular imaging modalities (PET, SPECT, MRI, etc.)
• Reconstruction background – MLEM, OSEM, MAP
• Quantitative corrections background – motion and attenuation correction
• Processing background – Denoising, deblurring
• Basics and core principles of AI and machine learning
• Convolutional Neural Networks (CNN), Encoder-Decoder Networks, Recurrent Neural Networks (RNN), Transformer Networks, Diffusion Models, Foundation and Large-Language Models
• Data preparation and augmentation, Model training and parameter tuning
• Generalizability, reproducibility, transparency
• AI-Based Image Reconstruction Techniques
• End-to-end reconstruction
• AI-based regularizers
• Quantitative Corrections
• Motion correction
• Attenuation correction
• AI-Based Image Enhancement
• Denoising
• Resolution recovery
• Clinical Applications and Emerging Directions
• AI for oncology
• AI for RPT and dosimetry
• AI for neuroimaging
• AI for cardiac imaging
• Hands-On Workshop
• AI-based reconstruction demo
• AI-based denoising and super-resolution demo
• Future Perspectives and Challenges
• Ethical considerations and regulatory aspects of AI in medical imaging
• Addressing challenges and overcoming barriers to widespread adoption
Prerequisites:
• Linear algebra basics
• Probability and statistics basics
• Python programming basics
Instructors’ Biographies
DR. JOYITA DUTTA is a tenured Professor in the Department of Biomedical Engineering at the University of Massachusetts Amherst. She received her B.Tech. (Honors) from the Indian Institute of Technology (IIT) Kharagpur and M.S. and Ph.D. from the University of Southern California. She directs the Biomedical Imaging and Data Science Laboratory (BIDSLab) at UMass Amherst, which develops signal processing and artificial intelligence (AI) techniques for image, graph, and time-series datasets. Her scientific contributions include the development of a broad range of tools for medical image enhancement and reconstruction with a focus on multimodality information integration. Her current research interests include developing AI approaches for the diagnosis and prognosis of Alzheimer’s disease. Dr. Dutta was the recipient of the 2016 Tracy Lynn Faber Memorial Award from the Society of Nuclear Medicine and Molecular Imaging (SNMMI) and the 2016 Bruce Hasegawa Young Investigator Medical Imaging Science Award from the IEEE. As a postdoc/junior faculty, she received an SNMMI Young Investigator Award, the 2013 SNMMI Mitzi & William Blahd MD Pilot Research Grant, the 2013 American Lung Association Senior Research Training Fellowship, and an NIH K01 Career Development Award. Her research is supported by multiple grants, including active NIH R01, R21, and R03 grants held as PI. Dr. Dutta has served as a member of the SNMMI AI Task Force and the Program Chair for the 2022 IEEE Medical Imaging Conference in Milan, Italy. She is currently the President of the SNMMI Physics, Instrumentation and Data Sciences Council (PIDSC). Her trainees at BIDSLab have been awarded prestigious extramural training grants from the SNMMI, IEEE, APS, and AAUW.
ARMAN RAHMIM is a Professor of Radiology, Physics, and Biomedical Engineering at the University of British Columbia (UBC) and a Distinguished Scientist and Provincial Medical Imaging Physicist at BC Cancer. He earned his MSc in condensed matter physics and PhD in medical imaging physics at UBC. After completing his PhD, he joined Johns Hopkins University (JHU) to lead the high-resolution brain PET imaging physics program and conduct research in Radiology and Electrical Engineering. In 2018, he returned to Vancouver to continue his research in molecular imaging and therapy. Dr. Rahmim has published a book, over 200 journal articles, and delivered more than 120 invited lectures worldwide. He has been a principal or co-investigator on various grants for quantitative imaging and personalized therapies. He received the Young Scientist Award from the AAPM in 2016 and the Presidential Distinguished Service Award from SNMMI in 2022. He has served as Vice President (2017-18) and President (2018-19) of the SNMMI’s Physics, Instrumentation and Data Sciences Council (PIDSC), and currently chairs the SNMMI Artificial Intelligence (AI) Task Force (2020-) and the SNMMI Dosimetry-AI working group (2022).
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Course title: |
Hybrid imaging SPECT/CT, PET/CT, PET/MR |
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Course organizer: |
Chi Liu, Chao Ma |
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Date/time/venue: |
Tuesday, 29 Oct. – 8:30 am – 5:00 pm – Venue: tba |
Instructors:
• Chi Liu
• Chao Ma
• Thibault Marin
Course Summary
This one-day course covers the physical aspects of PET, SPECT, CT, and MR (basic principles, instrumentation, requirements for integration). Basics of SPECT, CT, PET and MR physics and instrumentation as they pertain to SPECT/CT, PET/CT, PET/MR are discussed in detail. An overview of a wide range of detector technologies, from Anger cameras to state-of-the-art PET/MR systems is provided.
The basic principles of image reconstruction are discussed for each imaging modality, followed by advanced topics such as constrained image reconstruction and denoising methods with an emphasis on the state-of-the-art deep learning methods. Challenges specific to hybrid imaging physics, including attenuation correction, motion compensation, partial volume correction, and geometry integration, are discussed.
Course Outline
tba
Instructors’ Biographies
CHAO MA is an Assistant Professor in the Department of Radiology and Biomedical Imaging at Yale University. He is a Junior Fellow of the International Society of Magnetic Resonance in Medicine (ISMRM). His primary research interests are MR spectroscopy/spectroscopic imaging, cardiac MRI, MR RF pulse design, and quantitative PET/MR.
CHI LIU is a Professor in the Department of Radiology and Biomedical Imaging, and the Department of Biomedical Engineering, of Yale University. He is a board-certified Nuclear Medicine physicist by the American Board of Science in Nuclear Medicine. His lab is currently funded by multiple NIH grants. His current research focuses on quantitative oncological and cardiac PET/CT and SPECT/CT imaging, including deep learning algorithms, reconstruction algorithms, data corrections, dynamic imaging, and translational imaging.
THIBAULT MARIN is an Assistant Professor in the Department of Radiology and Biomedical Imaging at Yale University, where he specializes in advancing algorithms for quantitative imaging in PET and MRI. His research in positron emission tomography (PET) encompasses the creation of innovative image reconstruction techniques designed for next-generation scanners, as well as the development of direct estimation methods that integrate image reconstruction with kinetic modeling. His work on magnetic resonance (MR) imaging focuses on harnessing subspace and manifold learning approaches to enhance cardiac MRI. His research also explores deep learning applications for model-based image denoising, parametric mapping, and image segmentation.
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Course title: |
Dosimetry in radiopharmaceutical therapy, from basics to advanced |
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Course organizer: |
Georges El Fakhri, Julia Brosch-Lenz, Emilie Roncali |
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Date/time/venue: |
Tuesday, 29 Oct. – 8:30 am – 5:00 pm – Venue: tba |
Instructors:
• Georges El Fakhri
• Julia Brosch-Lenz
• Emilie Roncali
Course Description
Dosimetry in radiopharmaceutical therapy plays a crucial role in determining the effective and safe administration of radiopharmaceuticals to patients. This course aims to provide a comprehensive understanding of dosimetry principles, methodologies, and applications in the context of radiopharmaceutical therapy. Starting from foundational concepts, the course progresses to cover advanced topics.
Course Outline
• Overview of radiopharmaceuticals
• Basic principles of radiopharmaceutical therapy
• Introduction to dosimetry and its significance in therapy
• Basic radiation dosimetry principles
• Radionuclide selection criteria
• Patient-specific dosimetry considerations
• Methods for patient dosimetry estimation
• Factors influencing patient dosimetry calculations
• Dosimetry challenges and solutions in targeted radionuclide therapy (TRT)
• Monte Carlo simulation in dosimetry
• Image-based dosimetry methods
• Personalized dosimetry approaches
• Practical demonstrations of dosimetry calculations
• Discussion of real-world dosimetry challenges and solutions
• Future/emerging technologies
Prerequisites:
• Basic knowledge of radiation physics and biology
• Familiarity with medical imaging modalities and radiopharmaceuticals
Instructors’ Biographies
DR. EMILIE RONCALI is an Associate Professor in the Departments of Biomedical Engineering and Radiology at UC Davis. She received her Ph.D. in Biomedical Engineering from the Ecole Centrale de Paris, France before joining Dr. Simon Cherry’s group at UC Davis for her postdoctoral training. Dr. Roncali’s research involves molecular imaging and therapy, with an emphasis on quantitative dosimetry for radiopharmaceutical therapy and multiscale modeling. Dr. Roncali currently focuses her simulation developments on personalized dosimetry for liver transarterial embolization, where microspheres are injected in the liver artery to target liver tumors with radiation or chemotherapy. Dr. Roncali is a member of two working groups for the National Cancer Institute (NCI) and of the SNMMI AI Dosimetry taskforce to develop new dosimetry methods for radiopharmaceutical therapy with the goal of improving treatment planning and optimizing radiopharmaceutical therapy clinical trials. Her contributions to women in medical imaging sciences have been recognized in 2022 with the Faber award from the Society of Nuclear Medicine and Molecular Imaging (SNMMI).
DR. JULIA BROSCH-LENZ is a passionate medical physicist from Germany with strong interest in dosimetry to provide patients with optimum treatment. Her educational background includes a Bachelor (B.Sc.), a Master (M.Sc.), and a Doctoral (Dr.rer.nat.) degree in Medical Physics from Ludwig Maximilian University of Munich, Germany, where she gained comprehensive knowledge in radiation therapy, diagnostic imaging, radiation safety, and dosimetry. She has more than six years of clinical experience working as a medical physicist expert, which provided her with valuable insights into the clinical routine of nuclear medicine imaging and therapy.
Dr. Brosch-Lenz’s research focuses on image-based dosimetry for internal radionuclide therapies towards accurate, reproducible, and practical absorbed dose estimation at the organ, voxel- and microscopic level. She is a steering committee member of the special interest group on radionuclide internal dosimetry of the European Federation of Organisations for Medical Physics (EFOMP), where she further leads a focus group on Voxel S Values. She is an active member of task and project groups of the American Association of Physics in Medicine (AAPM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), and the European Association of Nuclear Medicine (EANM). In 2024, her work towards identifying global variabilities in absorbed doses was recognized with the award for Nuclear Medicine Therapies by the German Society of Nuclear Medicine.
DR. GEORGES EL FAKHRI iis the endowed Elizabeth Mears and House Jameson Professor of Radiology & Biomedical Imaging, Yale School of Medicine, and Director of the Yale PET Center, and Vice-Chair of Scientific Research in the Department of Radiology & Biomedical Imaging. Dr El Fakhri is an internationally recognized expert in quantitative molecular imaging (SPECT, PET-CT, and PET-MR) especially as it pertains to quantitative imaging, pharmacokinetic modeling, and probing pathophysiology in brain, cardiac, and oncologic PET/CT/MR. He has authored or co-authored over 300 papers and mentored over 120 students, post-docs and faculty. He has been a chartered member of many NIH study sections pertaining to Medical Imaging and Radiotherapy as well as DOD, DOE and other Foundations. He has received many awards and honors, including the Mark Tetalman Award and the E.J. Hoffman Award from the Society of Nuclear Medicine and Molecular Imaging and the Dana Foundation Brain and Immuno-Imaging Award. He was elected Fellow to the SNMMI, AAPM and IEEE for “contributions to biological imaging”.
Workshops
Workshop 1: Digital SiPM and SPAD based sensors
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Date: |
Sunday, 27 Oct., 2024 |
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Time: |
08:30 am – 06:00 pm |
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Room: |
tba |
Description
Analog SiPMs, now in use across-the-board, digital SiPMs, and SPAD-based devices see increased development activity with the potential of improving photon counting systems.
This workshop is structured in two parts: the morning session will be dedicated to tutorials on the basics of SPAD-based sensors from the structure and behaviour of the photodiodes (sensitivity, correlated noise, crosstalk…) with a focus on the characteristics of digitally readout SPADs, to the various sensing, quenching, and readout electronics techniques. Examples of embedded signal processing will also be reviewed. This first part of the workshop aims to introduce the technology to highly qualified personnel (HQPs) and researchers interested in using these next generation devices.
In the second part of the workshop (afternoon), we will hear developers of digital SiPM and SPAD based devices present their technology proposals aimed at applications in the realm of the NSS MIC RTSD conference. This part is meant to be as inclusive as possible, ranging from academic institutions, government laboratories, to commercial foundries. As most recent scientific advances will be communicated in the various sessions of the conference, this workshop is intended to be a forum offering a comprehensive view on development plans and timelines, and to highlight the applications addressed in collaborations, projects, and networks of researchers. The goal is to keep present and future stakeholders informed on the development of these technologies.
Organizer
Developers and stakeholders are welcome to submit communication to us by email.
- Serge Charlebois, Université de Sherbrooke
- Catherine Pepin, Université de Sherbrooke
Workshop 2: 1st NPSS Climate Workshop on Nuclear and Plasma Solutions for Energy and Society
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Date: |
Sunday, 27 Oct. , 2024 |
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Time: |
9:00 am - 5:00 pm |
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Room: |
tba |
Motivation
Workshop Structure
The workshop will span over 1 days divided into four sessions:
- Understanding Climate Change:
An introductory session covering the basics of climate change and its impact. - Science and Applications of Nuclear Fusion and Nuclear Fission:
to expose participants to the science and application of nuclear technology and the key role they could play for energy sustainability, together with action plans to identify opportunities for collective action with other communities. - Science and Applications of Plasma and Accelerators technologies and solutions:
to discuss with participants the science and applicazion of plasma science and accelerators technologies and their applications to energy and society, together with action plans to identify opportunities for collective action with other communities. - Science and Applications of Ultra Low Power Electronics, Big Data and Simulation:
to identify how low power electronics could change the IoT and remote monitoring and how big data and simulation could help defining future strategies in Climate Monitoring and Adaptation.
Contact
Cinzia DaVià, University of Manchester
on behalf of the NPSS Climate Change Initiative
Workshop 3: Edge computing for real-time imaging, reconstruction, and applications
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Date: |
Sunday, 27 Oct. , 2024 |
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Time: |
tba |
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Room: |
tba |
Description
The interdisciplinary field of real-time imaging and related applications is rapidly growing requiring low latency processing of the image data generated by high throughput devices such as large image sensors or particle counting devices. Making image sensors ‘smart’, in terms of automated data processing in real time, is a must in many applications, and is often a desired feature. Artificial intelligence/machine learning (AI/ML) is not only good for post-processing of image data but also for real-time enhancement of image sensors and measurements in situ and operando, also known as ‘edge computing’. Holistic combinations of edge computing with image sensors such as CMOS, LGADs, and other imaging hardware lead to ‘smart or intelligent imaging’.
This one-day workshop within IEEE MIC/NSS/RTSD 2024 aims to foster dialog on the state-of-the-art and future perspectives on real-time imaging methods, tomographic reconstruction algorithms, and smart image sensor hardware that innovatively use edge computing. Applications include physics experiments, compressed sensing, medical imaging and other real-time, data-driven applications. Topics of interest include but are not limited to the following:
- AI/ML-enhanced sensors and front-end circuits for real-time processing of image data;
- AI/ML deployment on DAQ systems for real-time analysis of data;
- Novel architectures for distributed computing combining diverse hardware (CPU, GPU, FPGA, ASIC) with AI/ML algorithms and augmented domain knowledge;
- AI/ML for sparse imaging using CMOS and other sensors;
- Uncertainty quantification, error corrections and data enhancement for imaging modalities and other applications;
- Theoretical foundations to accelerate AI/ML on hardware and facilitate sensor integration; and
- Digital twin applications and other related topics.
Experts
- Zhehui (Jeph) Wang, LANL
- Audrey Corbeil Therrien, U. Sherbrooke
- Lorenzo Fabris, ORNL
Workshop 4: Ultra-low-dose PET imaging
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Date: |
Tuesday, 29 Oct. , 2024 |
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Time: |
2:00 pm - 6:00 pm |
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Room: |
tba |
Description
The workshop comprises two parts: the first part will review recent advancements in ultra-low-dose PET imaging, and the second part will feature an open challenge, inviting the public to contribute to the development of ultra-low-dose PET imaging technologies. This challenge aims to build on the success of our previous challenge by establishing a benchmark dataset to address the technical hurdles of ultra-low-dose imaging on total-body PET. This year’s challenge will incorporate a broader and more diverse dataset acquired on two commercial total-body PET systems, uExplorer (United Imaging) and Biograph ision Quadra (Siemens Healthineers), to solidify the trust in methodological developments and enhance the clinical translational potential of the outcomes.
Experts
- Kuangyu Shi, Dept. Nuclear Medicine, University of Bern, Switzerland
- Rui Guo, Dept. Nuclear Medicine, Ruijin Hospital, Shanghai Jiaotong University, China
- Christoph Clement, Dept. Nuclear Medicine, University of Bern, Switzerland
- Hanzhong Wang, Dept. Nuclear Medicine, Ruijin Hospital, Shanghai Jiaotong University, China
- Axel Rominger, Dept. Nuclear Medicine, University of Bern, Switzerland
- Biao Li, Nuclear Medicine, Ruijin Hospital, Shanghai Jiaotong University, China
Workshop 5: PET Rapid Image Reconstruction
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Date: |
Saturday, 2 Nov. , 2024 |
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Time: |
2:00 pm - 6:00 pm |
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Room: |
tba |
Description
Recently, several advanced image reconstruction methods have been developed exploiting improved optimisation methods, machine learning and more powerful computer hardware. In tandem, the problem setting is becoming increasingly challenging, due to larger size of the measured data, multi-sequence/model data and applications in a high-noise context. In this workshop our invited experts will present recent advances in image reconstruction, covering developments in CT, MRI and PET. Currently confirmed speakers are Prof. J. Fessler and Prof. A. Reader. This will be followed by an overview of the PET Rapid Image Reconstruction Challenge (github.com/SyneRBI/PETRIC) which will have concluded before the conference. Finally, the top scoring teams will present their work and we will announce the winners of PETRIC.
Experts
- Charalampos Tsoumpas
- Christoph Kolbitsch
- Matthias Ehrhardt
- Kris Thielemans
Special Events
“Scientific Communication Skills for Scientists Speaking English as an Additional Language”
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Date: |
Monday, 28 Oct. ,2024 |
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Time: |
12:00 pm - 2:00 pm |
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Location: |
tba |
Scientists who speak English as an Additional Language often face challenges in scholarly communication, even though they may be outstanding writers or speakers in their native language. Moreover, such challenges may be poorly understood by mentors or colleagues, and little support is available for accelerating learning of scholarly English. This 2-hour hands-on workshop will provide strategies for making development of scientific English skills more effective and efficient. We will cover techniques for expressing the essence of a research project clearly and concisely, whether in written or spoken form, navigating professional conversations about research, using summary and paraphrase skillfully, using AI tools responsibly for writing and speaking, minimizing difficulties with accent, and more.
Lunch will be provided and so registration is required to attend the event. Space is limited and we encourage early registration.
Speaker
CARRIE CAMERON, PhD, is associate professor in the Dept. of Behavioral Science at the Univ. of Texas MD Anderson Cancer Center and serves as PI/PD on the on the “Scientific Communication Advances Research Excellence” (R25 GM125640-06, ‘SCOARE’) faculty mentor-training program. She also serves as PI/PD of the NIH Diversity Programs Consortium U01 award “Building a Diverse Biomedical Workforce Through Communication Across Difference” (U01 GM132219, G Unguez, multi-PI) which investigates the role of learning to communicate across difference in developing science identity and reinforcing STEM career intention. Trained as a linguist, her research focuses on the role of communication skills (both scholarly and lay) in development of research careers and acculturation into the research environment.
“RISC Forum at Tampa NSS/MIC/RTSD”
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Date: |
Wednesday, 30 Oct. ,2024 |
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Time: |
12:15 pm - 1:45 pm |
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Location: |
tba |
This forum is an initiative to identify the Next-Generation of RISC volunteers and implement means for increasing opportunities for a representation of students, mid-career, and underrepresented groups.
The opportunities are across several areas related to organizing and managing RISC conference and events e.g. abstract reviewing, session chairs, plenary speakers, organizing committee members, nomination for technical awards and RISC elected positions. The program would include:- Introduction by the RISC committee members with supportive presence of experienced NPSS members. – Questions and feedback from the floor This forum is open to anyone interested in getting involved with organizing a NPSS-RISC event.
Lunch will be provided and so registration is required to attend the event. Space is limited and we encourage early registration.
Women in Engineering (WIE) Luncheon
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Date: |
Thursday, 31 Oct. ,2024 |
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Time: |
12:15 pm – 1:45 pm |
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Room: |
tba |
Dear WIE supporters,
We are delighted to announce the IEEE NPSS WIE Luncheon at the NSS MIC RTSD in Tampa on the 31st of October 2024!
For many of us, one of the most difficult things to do is to talk openly and proudly of our achievements. In particular, women and other under-represented groups often struggle with self promotion, yet this is a skill that is crucial not only in academia, but for the vast majority of fields.
This year, we propose a workshop to boost confidence, recognise your unique worth, acknowledge the value of your contributions, learn more about the importance of self-promotion in our careers, and develop self-promotion skills. This workshop is meant for everyone, from students just starting to build their CV to experienced researchers looking to improve their mentorship skills. Join us in a celebration of your accomplishments!
Please book your ticket during the registration to guarantee your participation in this unique workshop. While the entrance will be free, the number of participants will be limited and only granted by your early registration.
We are looking forward to welcoming you!!
Organizer
- Audrey Corbeil Therrien, U. Sherbrooke
GATE User Meeting
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Date: |
Thursday, 31 Oct. ,2024 |
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Time: |
12:15 pm – 1:45 pm |
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Room: |
tba |
Description
The GATE toolkit has been in the research landscape for almost 20 years. This open-source software is designed to help researchers and engineers to perform a large range of Monte Carlo simulations in the medical physics field: PET, SPECT, Compton Camera, CT, CBCT (Cone-Beam CT) and radiation therapies.
The first publication on PET and SPECT developments has been published in 2004, the evolution towards radiation therapy in 2011, some extensions to other dosimetry applications in 2014 and, more recently in 2021, a specific topic for emission tomography imaging. A third long-term project has started, aiming to completely rethink the way the simulations are described by the user. It has been decided to investigate whether simulations can be directly described in Python instead of macro files. GATE 10 is currently showing the feasibility of such an approach. The mechanism is based on the Geant4 python binding thanks to pybind11 that exposes to Python a fraction of the Geant4 API.
The first public release of this approach will be proposed in September 2024. We encourage our community of users to participate in our annual workshop, the objectives will be to better understand the latest innovative applications in the field of imaging, to identify certain limits and to propose solutions adapted to the improvement of simulation practices.
Organizer
- Lydia Maigne, University of Clermont Auvergne
STIR Users’ & Developers’ Meeting
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Date: |
Thursday, 31 Oct. ,2024 |
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Time: |
6:30 pm - 8:30 pm |
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Room: |
tba |
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Submission deadline: |
1. September 2024 |
Description
STIR is Open Source software for use in tomographic imaging. Its aim is to provide a Multi-Platform Object-Oriented framework for all data manipulations in tomographic imaging. The emphasis is on image reconstruction in emission tomography (PET and SPECT). During the annual meeting experienced users and developers will present their recent work with STIR with technical emphasis on software and algorithmic development. Additional time will be allowed for discussion between the speakers and the audience. If interested in presenting contact the chairs before the 1st of September.
For up-to-date information please always check STIR website:
Chairs
- Daniel Deidda, National Physical Laboratory
- Nikos Efthymiou, Harvard Medical School
- Charalampos Tsoumpas, University of Groningen
- Kris Thielemans, University College London
CASToR Meeting
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Date: |
Friday, 1 Nov. ,2024 |
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Time: |
12:30 pm - 2:00 pm |
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Room: |
tba |
CASToR is an open-source multi-platform project for 4D emission (PET and SPECT) and transmission (CT) tomographic reconstruction. This platform is a scalable software providing both basic iterative image reconstruction features for “standard” users and advanced tools for specialists in the reconstruction field, to develop, incorporate and assess their own methods in image reconstruction through the implementation of new classes. More information can be found in the CASToR website:
The aim of this meeting is to provide interested users the opportunity to talk about their developments with CASToR. CASToR current and future developments will be also presented. Additional time will be allowed for discussion between the developers and the audience. If interested in presenting your work in the meeting, please contact the organizers below, before the 1st of October.
The inscription fee includes a lunchbox.
- Dimitris Visvikis
- Thibaut Merlin
- Simon Stute
