Accurate and Robust Segmentation of the Clinical Target Volume for Prostate Brachytherapy
Authors:
- 13 September 2018
- book chapter
- Published by Springer Nature
- p. 531-539
Abstract
No abstract availableKeywords
This publication has 7 references indexed in Scilit:
- Densely Connected Convolutional Networks2017
- U-Net: Convolutional Networks for Biomedical Image Segmentation2015
- Rotationally resliced 3D prostate TRUS segmentation using convex optimization with shape priorsMedical Physics, 2015
- Sparse Subspace Clustering: Algorithm, Theory, and ApplicationsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2013
- Adaptively Learning Local Shape Statistics for Prostate Segmentation in UltrasoundIEEE Transactions on Biomedical Engineering, 2010
- Permanent prostate brachytherapy preplanned technique: The modern Seattle method step-by-step and dosimetric outcomesBrachytherapy, 2009
- Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble AccuracyMachine Learning, 2003