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Prostate Cancer Imaging. An Engineering and Clinical Perspective

ISBN: 9781032652412
ISBN: 9781032652412
Διαστάσεις 25 × 18 cm



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This book covers novel strategies and state of the art approaches for automated non-invasive systems for early prostate cancer diagnosis.  Prostate cancer is the most frequently diagnosed malignancy after skin cancer and the second leading cause of cancer related male deaths in the USA after lung cancer. However, early detection of prostate cancer increases chances of patients’ survival. Generally, The CAD systems analyze the prostate images in three steps: (i) prostate segmentation; (ii) Prostate description or feature extraction; and (iii) classification of the prostate status.

  • 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.






1. History of Imaging for Prostate Cancer

Sutchin R. Patel

2. Transrectal Ultrasound (TRUS)-Guided Prostate Biopsy: Historical Perspective and Contemporary Clinical Application

Jennifer Fantasia, Dragan Golijanin, and Boris Gershman

3. Current Active Surveillance Protocol for Prostate Cancer

Scott Greenberg and Jennifer Yates

4. Prostate MRI

J. Pereira, Gyan Pareek, and D. Grand

5. Current Role and Evolution of MRI Fusion Biopsy for Prostate Cancer

Danielle Velez, Joseph Brito, and Joseph Renzulli II

6. Current Role of Focal Therapy for Prostate Cancer

H. Abraham Chiang and George E. Haleblian

7. High-Intensity Focused Ultrasound (HIFU)

Rutveej Patel and Sammy Elsamra

8. Current Role of Cryotherapy in the Treatment of Prostate Cancer

Adnan Dervishi and Murali K. Ankem

9. Transperineal Mapping of the Prostate for Biopsy Strategies

Daniel Kaplon and Winston Barzell

10. Computer-Aided Diagnosis Systems for Prostate Cancer Detection: Challenges and Methodologies

Guillaume Lemaître, Robert Martí, and Fabrice Meriaudeau

11. Early Diagnosis and Staging of Prostate Cancer Using Magnetic Resonance Imaging: State of the Art and Perspectives

Ruba Alkadi, Fatma Taher, Ayman El-Baz, and Naoufel Werghi

12. A DCE-MRI-Based Noninvasive CAD System for Prostate Cancer Diagnosis

F. Khalifa, A. Shalaby, Mohamed Abou El-Ghar, Jasjit S. Suri, and A. El-Baz

13. Prostate Segmentation from DW-MRI Using Level-Set Guided by Nonnegative Matrix Factorization

Islam Reda, Patrick McClure, Ahmed Shalaby, Mohammed Elmogy, Ahmed Aboulfotouh, Mohamed Abou El-Ghar, Moumen El-Melegy, Jasjit S. Suri, and Ayman El-Baz

14. Automated Prostate Image Recognition and Segmentation

Ke Yan, Xiuying Wang, Jinman Kim, Changyang Li, Dagan Feng, and Mohamed Khadra

15. Precision Imaging of Prostate Cancer: Computer-Aided Detection and Their Clinical Applications

Baowei Fei

16. Computer-Aided Diagnosis of Prostate Magnetic Resonance Imaging: From Bench to Bedside

Valentina Giannini, Simone Mazzetti, Filippo Russo, and Daniele Regge

17. Magnetic Resonance Imaging in the Detection of Prostate Cancer

Timothy D. McClure, Daniel Margolis, and Peter N. Schlegel

18. Diagnosing Prostate Cancer Based on Deep Learning with a Stacked Nonnegativity Constraint Autoencoder

Islam Reda, Ahmed Shalaby, Mohammed Elmogy, Ahmed Aboulfotouh, Mohamed Abou El-Ghar, Adel Elmagharaby, and Ayman El-Baz

19. MRI Imaging of Seminal Vesicle Invasion (SVI) in Prostate Adenocarcinoma

Samuel A. Gold, Graham R. Hale, Kareem N. Rayn, Vladimir Valera, Jonathan B. Bloom, and Peter A. Pinto