V-Net: Fully convolutional neural networks for volumetric medical image segmentation

Proceedings - 2016 4th International Conference on 3D Vision, 3DV 2016

Volumn , Issue , 2016, Pages 565-571

  Milletari, Fausto ^a   Navab, Nassir ^a   Ahmadi, Seyed Ahmad ^b  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b UNIVERSITY OF MUNICH   (Germany)

Author keywords

convolutional neural networks; Deep learning; machine learning; prostate; segmentation

Indexed keywords

CONVOLUTION; DEEP LEARNING; DEEP NEURAL NETWORKS; IMAGE SEGMENTATION; LEARNING SYSTEMS; LINEAR TRANSFORMATIONS; MATHEMATICAL TRANSFORMATIONS; MEDICAL IMAGING; MEDICAL PROBLEMS; NEURAL NETWORKS; UROLOGY;

3D IMAGE SEGMENTATION; CLINICAL PRACTICES; CONVOLUTIONAL NEURAL NETWORK; EXPERIMENTAL EVALUATION; HISTOGRAM MATCHING; NON-LINEAR TRANSFORMATIONS; OBJECTIVE FUNCTIONS; PROSTATE;

MEDICAL IMAGE PROCESSING;

EID: 85011298810     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/3DV.2016.79     Document Type: Conference Paper

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