title: Computer-aided diagnosis: detection and localization of prostate cancer within the peripheral zone.
abstract: We propose a methodology for prostate cancer detection and localization within the peripheral zone based on combining multiple segmentation techniques. We extract four image features using Gaussian and median filters. Subsequently, we use each image feature separately to generate binary segmentations. Finally, we take the intersection of all four binary segmentations, incorporating a model of the peripheral zone, and perform erosion to remove small false-positive regions. The initial evaluation of this method is based on 275 MRI images from 37 patients, and 86% of the slices were classified correctly with 87% and 86% sensitivity and specificity achieved, respectively. This paper makes two contributions: firstly, a novel computer-aided diagnosis approach, which is based on combining multiple segmentation techniques using only a small number of simple image features, and secondly, the development of the proposed method and its application in prostate cancer detection and localization using a single MRI modality with the results comparable with the state-of-the-art multimodality and advanced computer vision methods in the literature. Copyright © 2015 John Wiley & Sons, Ltd.
authors: Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, UK.
authors: Andrik
authors: A
authors: Rampun
authors: Information and Control Engineering Faculty, Shenyang Jianzhu University, Liaoning, 110168, China.
authors: Zhili
authors: Z
authors: Chen
authors: Department of Radiology, Norfolk Norwich University Hospital, Norwich, NR4 7UY, UK.
authors: Paul
authors: P
authors: Malcolm
authors: Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, UK.
authors: Bernie
authors: B
authors: Tiddeman
authors: Department of Computer Science, Aberystwyth University, Aberystwyth, SY23 3DB, UK.
authors: Reyer
authors: R
authors: Zwiggelaar
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011467:Prostate / Q000000981:diagnostic imaging; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging*
keywords: MRI; prostate cancer detection; prostate cancer localization