Image segmentation is often described as partitioning an image into a finite number of
semantically non-overlapping regions. In medical applications, it is a fundamental process in …

Abstract Accurate segmentation of 2-D, 3-D, and 4-D medical images to isolate anatomical
objects of interest for analysis is essential in almost any computer-aided diagnosis system or …

Deep learning networks have recently been shown to outperform other segmentation
methods on various public, medical-image challenge datasets, particularly on metrics …

We report here on recent developments and advances in pore-scale X-ray tomographic
imaging of subsurface porous media. Our particular focus is on immiscible multi-phase fluid …

In this paper, we propose a natural framework that allows any region-based segmentation
energy to be re-formulated in a local way. We consider local rather than global image …

This paper addresses the problem of image segmentation by means of active contours,
whose evolution is driven by the gradient flow derived from an energy functional that is …

Defect detection and classification of ceramic tile surface defects occurred in firing units are
usually performed by human observations in most factories. In this paper, an automatic …

We propose and analyze a nonparametric region-based active contour model for
segmenting cluttered scenes. The proposed model is unsupervised and assumes pixel …

We address the issue of textured image segmentation in the context of the Gabor feature
space of images. Gabor filters tuned to a set of orientations, scales and frequencies are …

We present a novel algorithm for segmentation of natural images that harnesses the
principle of minimum description length (MDL). Our method is based on observations that a …