Written by an interdisciplinary team of medical doctors, computer scientists, physicists, engineers, and mathematicians, Correction Techniques in Emission Tomography presents various correction methods used in emission tomography to generate and enhance images. It discusses the techniques from a computer science, mathematics, and physics viewpoint.
The book gives a comprehensive overview of correction techniques at different levels of the data processing workflow. It covers nuclear medicine imaging, hybrid emission tomography (PET-CT, SPECT-CT, PET-MRI, PET-ultrasound), and optical imaging (fluorescence molecular tomography). It illustrates basic principles as well as recent advances, such as model-based iterative algorithms and 4D methods. An important aspect of the book is on new and sophisticated motion correction techniques in PET imaging. These techniques enable high-resolution, high-quality images, leading to better imaging analysis and image-based diagnostics.
Reflecting state-of-the-art research, this volume explores the range of problems that occur in emission tomography. It looks at how the resulting images are affected and presents practical compensation methods to overcome the problems and improve the images.
Table of Contents
Introduction. BACKGROUND: Biomedical Applications of Emission Tomography. PET Image Reconstruction. CORRECTIONS TECHNIQUES IN PET AND SPECT: Basics of PET and SPECT Imaging. Corrections for Physical Factors. Corrections for Scanner Related Factors. Image Processing Techniques in Emission Tomography. Motion Correction in Emission Tomography. Combined Correction and Reconstruction Methods. RECENT DEVELOPMENTS: Introduction into Hybrid Tomographic Imaging. MR-Based Attenuation Correction for PET/MR. Optical Imaging. Index.
Mohammad Dawood is a researcher at the European Institute for Molecular Imaging. He earned a PhD in computer science from the University of Münster. His research interests include motion correction and tumor segmentation in medical imaging as well as biometrics and pattern analysis in image analysis.
Xiaoyi Jiang is a professor at the University of Münster and a scientist at the European Institute for Molecular Imaging. An IEEE senior member and an IAPR fellow, he earned a PhD in computer science from the University of Bern. His research areas include medical imaging analysis, pattern recognition, and computer vision.
Klaus Schäfers is head of the technology group at the European Institute for Molecular Imaging. He earned a PhD in medical physics from the University of Münster. His research interests include quantitative PET, motion detection and correction, high-resolution PET, multimodal molecular imaging techniques, and molecular imaging information in radiation therapy planning.