Computer-aided diagnosis: Detection and localization of prostate cancer within the peripheral zone

Yambu Andrik Rampun, Zhili Chen, Paul Malcolm, Bernie Tiddeman, Reyer Zwiggelaar

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

10 Dyfyniadau (Scopus)
304 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

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
Iaith wreiddiolSaesneg
Rhif yr erthygle02745
CyfnodolynInternational Journal for Numerical Methods in Biomedical Engineering
Cyfrol32
Rhif cyhoeddi5
Dyddiad ar-lein cynnar22 Medi 2015
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 27 Ebr 2016

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