Regresar

Automatic design of window operators for the segmentation of the prostate gland in magnetic resonance images

Abstract:

W-operators are nonlinear image operators that are translation invariant and locally defined inside a finite spatial window. In this work, we consider the problem of au-tomatic design of W-operators for the segmentation of magnet-ic resonance (MR) volumes as a problem of classifier design. We propose to segment the objects of interest in an MR vol-ume by classifying each pixel of its slices as either part of the objects of interest or background. The classifiers used here are the artificial feed-forward neural networks. The proposed method is applied to the segmentation of the two main regions of the prostate gland: the peripheral zone and the central gland. Performance evaluation was carried out on the volumes of the Prostate-3T collection of the NCI-ISBI 2013 Challenge. The results obtained show the suitability of our approach as a marker detector of the prostate gland.