title: Iterative thresholding for segmentation of cells from noisy images.
abstract: We introduce an iterative thresholding algorithm for the segmentation of cells from noisy cell images. The thresholding image, which is initially a constant, changes iteratively with both the previous segmentation and image local activity. Experimental results for both synthesized and real cell images are provided to demonstrate the performance of the algorithm.
authors.affiliation: Department of Pathology, Box 1194, Mount Sinai School of Medicine, One Gustave L. Levy Place, New York, NY 10029, USA. hwu@msvax.mssm.edu
authors.forename: H S
authors.initials: HS
authors.lastname: Wu
authors.forename: J
authors.initials: J
authors.lastname: Barba
authors.forename: J
authors.initials: J
authors.lastname: Gil
mesh_terms: D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008853:Microscopy / Q000379:methods*; D009130:Muscle, Smooth / Q000166:cytology*; D010336:Pathology / Q000379:methods*