High-throughput biomarker segmentation on ovarian cancer tissue microarrays via hierarchical normalized cuts

IEEE Transactions on Biomedical Engineering

Volumn 59, Issue 5, 2012, Pages 1240-1252

  Janowczyk, Andrew ^a,b   Chandran, Sharat ^a   Singh, Rajendra ^c   Sasaroli, Dimitra ^d   Coukos, George ^d   Feldman, Michael D ^d   Madabhushi, Anant ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

^b RUTGERS UNIVERSITY   (United States)

^c QUEST DIAGNOSTICS NICHOLS INSTITUTE   (United States)

^d UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Biomarker discovery; hierarchical normalized cuts (HNCuts); high throughput; mean shift; multivariate histology; normalized cuts; segmentation; tissue microarray (TMA)

Indexed keywords

BIO-MARKER DISCOVERY; HIGH-THROUGHPUT; MEAN SHIFT; NORMALIZED CUTS; TISSUE MICROARRAYS;

ALGORITHMS; BIOINFORMATICS; DATA STRUCTURES; DISEASES; MICROARRAYS; PIXELS; TISSUE;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; CANCER TISSUE; CLASSIFIER; CONTROLLED STUDY; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; HIERARCHICAL NORMALIZED CUT; HUMAN; IMAGE ANALYSIS; OUTCOME ASSESSMENT; OVARY CANCER; PREDICTIVE VALUE; SENSITIVITY ANALYSIS; TISSUE MICROARRAY;

ALGORITHMS; FEMALE; HIGH-THROUGHPUT SCREENING ASSAYS; HISTOCYTOCHEMISTRY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; NEOVASCULARIZATION, PATHOLOGIC; OVARIAN NEOPLASMS; TISSUE ARRAY ANALYSIS; TUMOR MARKERS, BIOLOGICAL;

EID: 84860372492     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2011.2179546     Document Type: Article

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