DocumentCode
3505968
Title
Active Contour for Overlap Resolution using Watershed BASED initialization (ACOReW): Applications to histopathology
Author
Ali, Sahirzeeshan ; Madabhushi, Anant
Author_Institution
Electr. & Comput. Eng., Rutgers Univ., Piscataway, NJ, USA
fYear
2011
fDate
March 30 2011-April 2 2011
Firstpage
614
Lastpage
617
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.
Keywords
biological tissues; cancer; image registration; medical image processing; ACOReW scheme; Geodesic Active Contour; Rousson´s shape based model; active contour; breast cancer; glandular structure segmentation; histopathology; lymphocyte; model initialization; nuclear structure segmentation; overlap resolution; prostate cancer; synergistic segmentation scheme; watershed based initialization; Active contours; Breast cancer; Context; Image segmentation; Level set; Mathematical model; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location
Chicago, IL
ISSN
1945-7928
Print_ISBN
978-1-4244-4127-3
Electronic_ISBN
1945-7928
Type
conf
DOI
10.1109/ISBI.2011.5872482
Filename
5872482
Link To Document