title: Automatic detection of follicular regions in H&E images using iterative shape index.
abstract: Follicular Lymphoma (FL) accounts for 20-25% of non-Hodgkin lymphomas in the United States. The first step in grading FL is identifying follicles. Our paper discusses a novel technique to segment follicular regions in H&E stained images. The method is based on three successive steps: (1) region-based segmentation, (2) iterative shape index (concavity index) calculation, (3) and recursive watershed. A novel aspect of this method is the use of iterative Concavity Index (CI) to control the follicular splitting process in recursive watershed. CI takes into consideration the convex hull of the object and the closest area surrounding it. The mean Zijbendos similarity index (ZSI) final segmentation score on fifteen cases was 78.33%, with a standard deviation of 2.83.
authors.affiliation: Department of Biomedical Informatics, Ohio State University, Columbus, OH 43210, USA. Kamel.Boussaid@osumc.edu
authors.forename: K
authors.initials: K
authors.lastname: Belkacem-Boussaid
authors.forename: S
authors.initials: S
authors.lastname: Samsi
authors.forename: G
authors.initials: G
authors.lastname: Lozanski
authors.forename: M N
authors.initials: MN
authors.lastname: Gurcan
mesh_terms: D000465:Algorithms; D003952:Diagnostic Imaging; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008224:Lymphoma, Follicular / Q000473:pathology*; D060787:Neoplasm Grading / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*