Cell segmentation, tracking, and mitosis detection using temporal context

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3749 LNCS, Issue , 2005, Pages 302-309

  Yang, Fuxing ^a   Mackey, Michael A ^b   Ianzini, Fiorenza ^b,c   Gallardo, Greg ^a   Sonka, Milan ^a  

^a IA United States   (United States)

^b UNIVERSITY OF IOWA   (United States)

^c UNIVERSITY OF IOWA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ERROR ANALYSIS; IMAGE SEGMENTATION; MEDICAL IMAGING; PROBLEM SOLVING; TUMORS;

CELL TRACKING; LARGE SCALE DIGITAL CELL ANALYSIS SYSTEM (LSDCAS); MITOSIS;

CELLS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CELL COUNT; CELL MOTION; CELL NUCLEUS; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; GLIOMA; HUMAN; IMAGE CYTOMETRY; IMAGE ENHANCEMENT; METHODOLOGY; MITOSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; TIME; TUMOR CELL LINE; ULTRASTRUCTURE; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CELL COUNT; CELL LINE, TUMOR; CELL MOVEMENT; CELL NUCLEUS; GLIOMA; HUMANS; IMAGE CYTOMETRY; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MITOSIS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TIME FACTORS;

EID: 33744790029     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11566465_38     Document Type: Conference Paper

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