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Dive into the transformative world of Spectral Photon-Counting Computed Tomography (SPCCT), the groundbreaking technology revolutionizing diagnostic imaging. This book explores the latest advancements in SPCCT systems, revealing their unparalleled precision in detecting chronic, acute, and emergency conditions. Discover the cutting-edge technique of color K-edge imaging, which, combined with innovative contrast agents, may unveil unprecedented diagnostic clarity. From technical breakthroughs to emerging clinical applications, this comprehensive guide charts the future of radiology. A must-read for researchers, clinicians, and imaging enthusiasts eager to harness the potential of SPCCT to redefine medical diagnostics and improve patient outcomes.
Salim Aymeric Si-Mohamed, MD, PhD, is a full professor in medical imaging at the University Claude Bernard Lyon 1 and head of the Cardiovascular and Thoracic Imaging Department at Louis Pradel Hospital in Lyon. Specializing in diagnostic and interventional imaging for cardiovascular and thoracic diseases, he primarily works with cutting-edge CT technology. Dr. Si-Mohamed's experimental research focuses on the development of spectral CT technology, including spectral photon-counting CT and dual-energy CT systems, integrated with novel contrast agents for cardiovascular and thoracic applications. He earned his MD in 2016 and completed his PhD in 2020, with his doctoral research dedicated to the cardiovascular applications of spectral photon-counting CT technology. His groundbreaking work demonstrated the feasibility of color K-edge imaging for cardiovascular imaging, particularly in studying atherosclerosis. Dr. Si-Mohamed is an active member of several national and international research consortia, fostering multidisciplinary collaborations among academic, university, and industry partners. He has authored over 150 publications in leading international journals and conferences, focusing on both experimental and clinical spectral CT imaging. Dr. Si-Mohamed teaches the principles, techniques, and applications of spectral CT, mentoring MSc and PhD students. He is also the holder of an international patent. In 2023, he was awarded an ERC Starting Grant for the KOLOR SPCCT Imaging Project, aimed at advancing comprehensive, one-breath-hold imaging of lung diseases using color K-edge imaging and dedicated contrast agents.
Krzysztof (Kris) Iniewski is a director of detector architecture and applications at Redlen Technologies Inc., a Canon company based in British Columbia, Canada. During his 20 years at Redlen he has managed research and development of highly integrated CZT detector products in medical imaging and security applications. Prior to Redlen Kris hold various management and academic positions at PMC-Sierra, University of Alberta, SFU, UBC and University of Toronto.
Dr. Iniewski has published over 150+ research papers in international journals and conferences. He holds 50+ of pending and granted international patents granted in USA, Canada, EU, France, Germany, and Japan. He wrote and edited over 50 books for Wiley, Cambridge University Press, Mc-Graw Hill, CRC Press and Springer. He is a frequent invited speaker and has consulted for multiple organizations internationally. He can be reached at kris.iniewski@gmail.com.
Chapter 1. Clinical Application of Spectral Photon Counting Computed Tomography.- Chapter 2. Photon Counting CT for cardiac and aortic imaging .- Chapter 3. Lung applications of spectral photon-counting CT (SPCCT).- Chapter 4. Novel contrast agents for SPCCT.- Chapter 5. Clinical Potential of Cadmium Zinc Telluride-based Photon-Counting Computed Tomography for Lung Cancer Imaging.- Chapter 6. Photon-Counting CT in Emergency Radiology.- Chapter 7. Clinical Applications of Photon-Counting CT in Adult and Pediatric Oncology.- Chapter 8. Photon counting breast CT: system requirements, development, current clinical applications, and possible future applications.- Chapter 9. Clinical applications of MARS Spectral Photon Counting CT .- Chapter 10. Photon Counting Computed Tomography: Clinical Applications, Detector Technology and Artificial Intelligence.
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