Computational pathology: Challenges and promises for tissue analysis

Computerized Medical Imaging and Graphics

Volumn 35, Issue 7-8, 2011, Pages 515-530

  Fuchs, Thomas J ^a   Buhmann, Joachim M ^a  

^a ETH ZURICH   (Switzerland)

Author keywords

Cancer research; Computational pathology; Machine learning; Medical imaging; Survival statistics; Whole slide imaging

Indexed keywords

CANCER RESEARCH; COMPUTATIONAL PATHOLOGY; MACHINE-LEARNING; SURVIVAL STATISTICS; WHOLE SLIDE IMAGING;

GENE EXPRESSION; INFORMATION SCIENCE; LEARNING SYSTEMS; MEDICAL IMAGING; MOLECULAR BIOLOGY; PATHOLOGY; TISSUE;

DISEASES;

ALGORITHM; BIOMEDICAL ENGINEERING; CANCER RESEARCH; CANCER SURVIVAL; CELL NUCLEUS; CLASSIFICATION; CLEAR CELL CARCINOMA; COMPUTATIONAL PATHOLOGY; COMPUTER PROGRAM; CYTOLOGY; FLUORESCENCE MICROSCOPY; GOLD STANDARD; HISTOLOGY; HUMAN; IMAGING; IMMUNOHISTOCHEMISTRY; KIDNEY CARCINOMA; MACHINE LEARNING; PATHOLOGIST; PATHOLOGY; PRIORITY JOURNAL; REVIEW; TISSUE MICROARRAY; WHOLE SLIDE IMAGING;

ALGORITHMS; AUTOMATION; DIAGNOSTIC IMAGING; GENOMICS; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NEOPLASMS; PATHOLOGY, CLINICAL; PROGNOSIS; PROTEOMICS; SOFTWARE DESIGN; SURVIVAL ANALYSIS;

EID: 80052324279     PISSN: 08956111     EISSN: 18790771     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2011.02.006     Document Type: Review

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