This is a practical guide to tomographic image reconstruction with projection data, with strong focus on Computed Tomography (CT) and Positron Emission Tomography (PET). Classic methods such as FBP, ART, SIRT, MLEM and OSEM are presented with modern and compact notation, with the main goal of guiding the reader from the comprehension of the mathematical background through a fast-route to real practice and computer implementation of the algorithms. Accompanied by example data sets, real ready-to-run Python toolsets and scripts and an overview the latest research in the field, this guide will be invaluable for graduate students and early-career researchers and scientists in medical physics and biomedical engineering who are beginners in the field of image reconstruction.

• A top-down guide from theory to practical implementation of PET and CT reconstruction methods, without sacrificing the rigor of mathematical background
• Accompanied by Python source code snippets, suggested exercises, and supplementary ready-to-run examples for readers to download from the CRC Press website
• Ideal for those willing to move their first steps on the real practice of image reconstruction, with modern scientific programming language and toolsets

Contents

Chapter 1: Preliminary notions
Chapter 2: Short guide to Python samples
Chapter 3: Analytical reconstruction algorithms
Chapter 4: Iterative reconstruction algorithms
Chapter 5: Overview of methods for generation of projection data