Paper Info
Title
Computerized Multiparametric MR image Analysis for Prostate Cancer Aggressiveness-Assessment.
Abstract
We propose an automated method for detecting aggressive prostate cancer(CaP) (Gleason score u003e=7) based on a comprehensive analysis of the lesion and the surrounding normal prostate tissue which has been simultaneously captured in T2-weighted MR images, diffusion-weighted images (DWI) and apparent diffusion coefficient maps (ADC). The proposed methodology was tested on a dataset of 79 patients (40 aggressive, 39 non-aggressive). We evaluated the performance of a wide range of popular quantitative imaging features on the characterization of aggressive versus non-aggressive CaP. We found that a group of 44 discriminative predictors among 1464 quantitative imaging features can be used to produce an area under the ROC curve of 0.73.
Year
Venue
Field
2016
arXiv: Computer Vision and Pattern Recognition
Effective diffusion coefficient,Pattern recognition,Computer science,Artificial intelligence,Quantitative imaging,Prostate,Prostate cancer,Radiology,Area under the roc curve,Discriminative model,Prostate Cancer Aggressiveness
DocType
Volume
Citations 
Journal
abs/1612.00408
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Imon Banerjee14811.45
Lewis Hahn200.34
Geoffrey Sonn332.78
Richard Fan444.36
Daniel L. Rubin51645145.14