Author:
Dorit S. Hochbaum
Affiliation:
UC Berkeley, United States
Keyword(s):
Array-CGH, Comparative Genomics, Arabidopsis Ecotypes, Hidden Markov Model(HMM).
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
Abstract:
This paper describes a utilization of a very efficient polynomial time algorithm, discovered by Hochbaum (2001), for segmentation tool through Markov Random Fields. The tool allows flexible choice of input parameters, controlling the output within an interactive tool with dynamic features and easily modified parameters.