Prostate Cancer Imaging. An Engineering and Clinical Perspective

Concurrent Segmentation of the Prostate on MRI and Ct via Linked Statistical Shape Models for Radiotherapy Planning. Segmentation of the Prostate in MR Images by Atlas Matching. Unsurpervised 3D Prostate Segmentation Based on Diffusion- Weighted Imaging MRI using Active Contour Models with a Shapr Prior. A New 3D Automatic Segmentation Framework for Accurate Segmentation of Prostate from DCE-MRI. Automated Prostate Segmentation in Whole-Body MRI Scans for Epidemilogical Studies. Segmentation of Prostate Boundaries from Ultasound Images Using Statistical Shape Model. Segmentation of Volumetric Prostate MRI Data Using Hybrid 2D=3D Shape Modeling. A Multi-Model Prostate Segmentation Scheme by Combining Spectral Clustering and Active Shape Models. Automated Segmentation of the Prostate in 3D MR Images. A Diffusion-Weighted Imaging Based Dianostic System for Early Detection of Prostate Cancer. Integrating Structural and Functional Imaging for Computer Assisted Detection. Automated Computer-Aided Detection of Abnormalities in Prostate MRI.Automated Computer-Aeded Detection of Prostate Cancer Based on Multi-Parametric Magnetic Resonance Image Analysis. Computer-Aided Diagnosis of Prostate Cancer in the Peripheral Zone Using Multi-Parametric MRI.

This will be a comprehensive overview of the latest research, technologies and innovations in minimally invasive imaging of the prostate gland and prostate cancer imaging. A major focus will be 3D image segmentation along with computer-aided-diagnosis techniques for prostate cancer. Also featured are automated segmentation methods featuring ultrasound and MRI techniques. A number of the authors are world-class experts in the field ranging from the US, Europe, and Asia.

Features

• Explores all of the latest research and developments in state-of-the art imaging of the prostate from world class experts.
• Contains a comprehensive overview of 2D/3D Shape Modeling for MRI data.
• Presents a detailed examination of automated segmentation of the prostate in 3D imaging.
• Examines Computer-Aided-Diagnosis through automated techniques.
• There will be extensive references at the end of each chapter to enhance further study.

Editor(s) Bio

Ayman El-Baz is a Professor in the Department of Bioegineering at the University of Louisville. His interest is in the field of bioimaging modeling and CAD systems in 2d/3D imaging. He has earned multple awards for his work related to novel image analysis techniques for lung cancer and autism diagnosis. Dr. El-Baz has published more than 300 technical articles.

Gyan Pareek, MD is Director of the Minimally Invasive Urology Institute and Director of the Kidney Stone Center at The Miriam Hospital. He is also an Associate Professor of Surgery (Urology) at The Warren Alpert Medical School of Brown University. He is board certified in urology and a Fellow of the American College of Surgeons. He was a part of the team that performed the first robotic prostatechomy in the state of Rhode Island. He is President of the Rhode Island Urological Society.

Dr Jasit Suri is a noted researcher and innovator in medical imaging as well as being a Fellow of the American Institute of Medical and Biological Engineering (AIMBE). He has published over 500 peer reviewed articles which includes 100 patents, 15 trademarks and 35 books. He has won over 50 awards during his career.