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Proceedings Paper

Classification of clinical significance of MRI prostate findings using 3D convolutional neural networks
Author(s): Alireza Mehrtash; Alireza Sedghi; Mohsen Ghafoorian; Mehdi Taghipour; Clare M. Tempany; William M. Wells; Tina Kapur; Parvin Mousavi; Purang Abolmaesumi; Andriy Fedorov
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Paper Abstract

Prostate cancer (PCa) remains a leading cause of cancer mortality among American men. Multi-parametric magnetic resonance imaging (mpMRI) is widely used to assist with detection of PCa and characterization of its aggressiveness. Computer-aided diagnosis (CADx) of PCa in MRI can be used as clinical decision support system to aid radiologists in interpretation and reporting of mpMRI. We report on the development of a convolution neural network (CNN) model to support CADx in PCa based on the appearance of prostate tissue in mpMRI, conducted as part of the SPIE-AAPM-NCI PROSTATEx challenge. The performance of different combinations of mpMRI inputs to CNN was assessed and the best result was achieved using DWI and DCE-MRI modalities together with the zonal information of the finding. On the test set, the model achieved an area under the receiver operating characteristic curve of 0.80.

Paper Details

Date Published: 3 March 2017
PDF: 4 pages
Proc. SPIE 10134, Medical Imaging 2017: Computer-Aided Diagnosis, 101342A (3 March 2017); doi: 10.1117/12.2277123
Show Author Affiliations
Alireza Mehrtash, Brigham and Women's Hospital, Harvard Medical School (United States)
Univ. of British Columbia (Canada)
Alireza Sedghi, Medical Informatics Lab., Queen's Univ. (Canada)
Mohsen Ghafoorian, Brigham and Women's Hospital, Harvard Medical School (United States)
Radboud Univ. Medical Ctr. (Netherlands)
Mehdi Taghipour, Brigham and Women's Hospital, Harvard Medical School (United States)
Clare M. Tempany, Brigham and Women's Hospital, Harvard Medical School (United States)
William M. Wells, Brigham and Women's Hospital, Harvard Medical School (United States)
Tina Kapur, Brigham and Women's Hospital, Harvard Medical School (United States)
Parvin Mousavi, Medical Informatics Lab., Queen's Univ. (Canada)
Purang Abolmaesumi, Univ. of British Columbia (Canada)
Andriy Fedorov, Brigham and Women's Hospital, Harvard Medical School (United States)


Published in SPIE Proceedings Vol. 10134:
Medical Imaging 2017: Computer-Aided Diagnosis
Samuel G. Armato; Nicholas A. Petrick, Editor(s)

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