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Image Processing, Computer Vision, Pattern Recognition, and Graphics

Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention

International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 24, 2010, Proceedings

Editors: Madabhushi, A., Dowling, J.A., Yan, P., Fenster, A., Abolmaesumi, P., Hata, N. (Eds.)

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  • ISBN 978-3-642-15989-3
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About this book

Prostatic adenocarcinoma (CAP) is the second most common malignancy with an estimated 190,000 new cases in the USA in 2010 (Source: American Cancer Society), and is the most frequently diagnosed cancer among men. If CAP is caught early, men have a high, five-year survival rate. Unfortunately there is no standardized ima- based screening protocol for early detection of CAP (unlike for breast cancers). In the USA high levels of prostate-specific antigen (PSA) warrant a trans-rectal ultrasound (TRUS) biopsy to enable histologic confirmation of presence or absence of CAP. With recent rapid developments in multi-parametric radiological imaging te- niques (spectroscopy, dynamic contrast enhanced MR imaging, PET, RF ultrasound), some of these functional and metabolic imaging modalities are allowing for definition of high resolution, multi-modal signatures for prostate cancer in vivo. Distinct com- tational and technological challenges for multi-modal data registration and classifi- tion still remain in leveraging this multi-parametric data for directing therapy and optimizing biopsy. Additionally, with the recent advent of whole slide digital sc- ners, digitized histopathology has become amenable to computerized image analysis. While it is known that outcome of prostate cancer (prognosis) is highly correlated with Gleason grade, pathologists often have difficulty in distinguishing between interme- ate Gleason grades from histopathology. Development of computerized image analysis methods for automated Gleason grading and predicting outcome on histopathology have to confront the significant computational challenges associated with working these very large digitized images.

Table of contents (15 chapters)

Table of contents (15 chapters)
  • Prostate Cancer MR Imaging

    Pages 1-3

    Fütterer, Jurgen J.

  • Computer Aided Detection of Prostate Cancer Using T2, DWI and DCE MRI: Methods and Clinical Applications

    Pages 4-14

    Huisman, Henkjan (et al.)

  • Prostate Cancer Segmentation Using Multispectral Random Walks

    Pages 15-24

    Artan, Yusuf (et al.)

  • Automatic MRI Atlas-Based External Beam Radiation Therapy Treatment Planning for Prostate Cancer

    Pages 25-33

    Dowling, Jason (et al.)

  • An Efficient Inverse-Consistent Diffeomorphic Image Registration Method for Prostate Adaptive Radiotherapy

    Pages 34-41

    Han, Xiao (et al.)

Buy this book

eBook $69.99
price for USA in USD
  • ISBN 978-3-642-15989-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $89.99
price for USA in USD
  • ISBN 978-3-642-15988-6
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Online orders shipping within 2-3 days.
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Bibliographic Information

Bibliographic Information
Book Title
Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention
Book Subtitle
International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 24, 2010, Proceedings
Editors
  • Anant Madabhushi
  • Jason A. Dowling
  • Pingkun Yan
  • Aaron Fenster
  • Purang Abolmaesumi
  • Nobuhiko Hata
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
6367
Copyright
2010
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-15989-3
DOI
10.1007/978-3-642-15989-3
Softcover ISBN
978-3-642-15988-6
Edition Number
1
Number of Pages
X, 146
Number of Illustrations
67 b/w illustrations
Topics