A fully automatic random walker segmentation for skin lesions in a supervised setting

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

Volumn 5762 LNCS, Issue PART 2, 2009, Pages 1108-1115

  Wighton, Paul ^a,b,c   Sadeghi, Maryam ^a,c   Lee, Tim K ^a,b,c   Atkins, M Stella ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c BRITISH COLUMBIA CANCER RESEARCH CENTRE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC METHOD; F-MEASURE; LOW CONTRAST; MANUAL SEGMENTATION; RANDOM WALKERS; SEED POINT; SKIN LESION; STATISTICAL PATTERN RECOGNITION; TRAINING SETS;

DERMATOLOGY; PATTERN RECOGNITION;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COLORIMETRY; COMPUTER ASSISTED DIAGNOSIS; EPILUMINESCENCE MICROSCOPY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SKIN; SKIN DISEASE; STATISTICAL ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COLORIMETRY; DATA INTERPRETATION, STATISTICAL; DERMOSCOPY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SKIN; SKIN DISEASES;

EID: 79960476121     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_134     Document Type: Conference Paper

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