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Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 24, 2010, Proceedings /

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 i...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Madabhushi, Anant (Editor ), Dowling, Jason (Editor ), Yan, Pingkun (Editor ), Fenster, Aaron (Editor ), Abolmaesumi, Purang (Editor ), Hata, Nobuhiko (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 6367
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Prostate Cancer MR Imaging
  • Computer Aided Detection of Prostate Cancer Using T2, DWI and DCE MRI: Methods and Clinical Applications
  • Prostate Cancer Segmentation Using Multispectral Random Walks
  • Automatic MRI Atlas-Based External Beam Radiation Therapy Treatment Planning for Prostate Cancer
  • An Efficient Inverse-Consistent Diffeomorphic Image Registration Method for Prostate Adaptive Radiotherapy
  • Atlas Based Segmentation and Mapping of Organs at Risk from Planning CT for the Development of Voxel-Wise Predictive Models of Toxicity in Prostate Radiotherapy
  • Realtime TRUS/MRI Fusion Targeted-Biopsy for Prostate Cancer: A Clinical Demonstration of Increased Positive Biopsy Rates
  • HistoCAD: Machine Facilitated Quantitative Histoimaging with Computer Assisted Diagnosis
  • Registration of In Vivo Prostate Magnetic Resonance Images to Digital Histopathology Images
  • High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies
  • Automated Analysis of PIN-4 Stained Prostate Needle Biopsies
  • Augmented Reality Image Guidance in Minimally Invasive Prostatectomy
  • Texture Guided Active Appearance Model Propagation for Prostate Segmentation
  • Novel Stochastic Framework for Accurate Segmentation of Prostate in Dynamic Contrast Enhanced MRI
  • Boundary Delineation in Prostate Imaging Using Active Contour Segmentation Method with Interactively Defined Object Regions.