Efficient globally optimal segmentation of cells in fluorescence microscopy images using level sets and convex energy functionals

Medical Image Analysis

Volumn 16, Issue 7, 2012, Pages 1436-1444

  Bergeest, Jan Philip ^a   Rohr, Karl ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Active contours; Cell segmentation; Convex optimization; Level sets

Indexed keywords

ACTIVE CONTOURS; CELL FUNCTIONS; CELL NUCLEUS; CELL SEGMENTATION; CELL TYPES; ENERGY FUNCTIONALS; FLUORESCENCE MICROSCOPY IMAGES; FUNCTIONALS; GLOBAL SOLUTIONS; HIGH-THROUGHPUT; LEVEL SET; LOCAL MINIMUMS; OPTIMAL SEGMENTATION; PROTEIN EXPRESSIONS; QUANTITATIVE COMPARISON; SEGMENTATION RESULTS;

CELLS; CONVEX OPTIMIZATION; CYTOLOGY; FLUORESCENCE MICROSCOPY;

IMAGE SEGMENTATION;

ANIMAL CELL; ARTICLE; CELL NUCLEUS; CELL TYPE; COMPUTER ANALYSIS; CONTROLLED STUDY; ENERGY; FLUORESCENCE MICROSCOPY; HUMAN; HUMAN CELL; IMAGE ANALYSIS; MOUSE; NONHUMAN; PERFORMANCE; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELL TRACKING; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY, FLUORESCENCE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84866436561     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2012.05.012     Document Type: Article

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