title: Semi-automated color segmentation of anatomical tissue.
abstract: We propose a semi-automated region-based color segmentation algorithm to extract anatomical structures, including soft tissues, in the color anatomy slices of the Visible Human data. Our approach is based on repeatedly dividing an image into regions using Voronoi diagrams and classifying the regions based on experimental classification statistics. The user has the option of reclassifying regions in order to improve the final boundary. Our results indicate that the algorithm can find accurate outlines in a small number of iterations and that manual interaction can markedly improve the outline. This approach can be extended to 3D color segmentation.
authors.affiliation: Department of Computer Science, Columbia University and Office of Scholarly Resources, College of Physicians and Surgeons of Columbia University, 701 W. 168th St., HHHSC 201, 10032, New York, NY, USA. ci42@columbia.edu
authors.forename: C
authors.initials: C
authors.lastname: Imelińska
authors.forename: M S
authors.initials: MS
authors.lastname: Downes
authors.forename: W
authors.initials: W
authors.lastname: Yuan
mesh_terms: D000465:Algorithms; D019412:Anatomy, Cross-Sectional; D001331:Automation; D003116:Color; D003196:Computer Graphics; D006801:Humans