3D Image Reconstruction for CT and PET: A Practical Guide with Python

This book is a comprehensive guide to tomographic image reconstruction with projection data, focusing on Computed Tomography (CT) and Positron Emission Tomography (PET). It presents classic methods such as FBP, ART, SIRT, MLEM, and OSEM with modern and compact notation, guiding the reader from mathematical understanding to practical implementation. Accompanied by example data sets, real-ready-to-run Python toolsets, and scripts, it is invaluable for graduate students, early-career researchers, and scientists in medical physics and biomedical engineering.

Format: Paperback / softback
Length: 134 pages
Publication date: 29 April 2022
Publisher: Taylor & Francis Ltd

This comprehensive guide provides a practical approach to tomographic image reconstruction with projection data, with a strong focus on Computed Tomography (CT) and Positron Emission Tomography (PET). It presents classic methods such as FBP, ART, SIRT, MLEM, and OSEM in a modern and compact notation, with the main objective of guiding readers from understanding the mathematical background to rapidly implementing algorithms in practice and computer implementation.

Accompanied by example data sets, real ready-to-run Python toolsets, and scripts, this guide offers valuable insights for graduate students, early-career researchers, and scientists in medical physics and biomedical engineering who are beginners in the field of image reconstruction.

The author, Daniele Panetta, is a researcher at the Institute of Clinical Physiology of the Italian National Research Council (CNR-IFC) in Pisa. He holds an MSc degree in Physics and a specialisation diploma in Health Physics from the University of Pisa. Prior to joining CNR-IFC, he worked at the Department of Physics E. Fermi of the University of Pisa, where he focused on tomographic image reconstruction for small animal imaging micro-CT instrumentation.

This guide is designed to bridge the gap between theory and practical implementation, ensuring that readers have a solid foundation in the mathematical aspects while also providing practical guidance for applying reconstruction algorithms in real-world scenarios. With its modern scientific programming language and toolsets, it is an ideal resource for those who are eager to embark on their journey into the realm of image reconstruction.

Dimension: 216 x 138 (mm)
ISBN-13: 9780367539818