Active Contour for Overlap Resolution using Watershed BASED initialization (ACOReW): Applications to histopathology

Abstract

In recent years, shape based active contours have emerged as a natural solution to overlap resolution. However, most of these shape-based methods are limited to finding and resolving one object overlap per scene and require user intervention for model initialization. In this paper, we present a novel synergistic segmentation scheme called Active Contour for Overlap Resolution using Watershed (ACOReW). ACOReW combines shape priors with boundary and region-based active contours in a level set formulation with a watershed scheme for model initialization for identifying and resolving multiple object overlaps in an image scene. The energy functional for the variational active contour model is composed of three complimentary terms (a) a shape model which constrains the active contour to a pre-defined shape, (b) boundary based term which directs the active contour model to the image gradient, and (c) a third term driving the shape prior and the active contour towards a homogeneous intensity region. In this paper we show an application of ACOReW in the context of segmenting nuclear and glandular structures on prostate and breast cancer histopathology. The results of qualitative and quantitative evaluation on 100 prostate and 14 breast cancer histology images reveals that ACOReW outperforms two state of the art segmentation schemes (Geodesic Active Contour (GAC) and Rousson's shape based model) and resolves up to 92% of overlapping/occluded lymphocytes and nuclei on prostate and breast cancer histology images.