Automatic detection of basal cell carcinoma using telangiectasia analysis in dermoscopy skin lesion images

Skin Research and Technology

Volumn 17, Issue 3, 2011, Pages 278-287

  Cheng, Beibei ^a   Erdos, David ^a   Stanley, Ronald J ^a   Stoecker, William V ^b   Calcara, David A ^b   Gómez, David D ^c  

^a University of Missouri Rolla   (United States)

^b Stoecker and Associates   (United States)

^c UNIVERSITAT POMPEU FABRA   (Spain)

Author keywords

Basal cell carcinoma; Dermoscopy; Image analysis; Neural network; Telangiectasia; Vessels

Indexed keywords

AUTOMATIC DETECTION; BASAL CELL CARCINOMA; BENIGN LESION; CLINICAL PRACTICES; DATA SETS; DERMOSCOPY; DIAGNOSTIC ACCURACY; IMAGE ANALYSIS TECHNIQUES; LOCAL COLOR; NEURAL NETWORK CLASSIFIER; NOISE FILTERS; PRIMARY SCREEN; SKIN LESION; SKIN LESION IMAGES; TELANGIECTASIA; VESSEL-LIKE STRUCTURES; VESSELS;

CRYSTAL STRUCTURE; DERMATOLOGY; IMAGE ANALYSIS; NEURAL NETWORKS;

BLOOD VESSELS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BASAL CELL CARCINOMA; BENIGN SKIN TUMOR; DIAGNOSTIC ACCURACY; DIFFERENTIAL DIAGNOSIS; EPILUMINESCENCE MICROSCOPY; EXPERT SYSTEM; HUMAN; IMAGE ANALYSIS; SKIN BLOOD VESSEL; SKIN EXAMINATION; TELANGIECTASIA;

BASAL CELL CARCINOMA; DERMOSCOPY; IMAGE ANALYSIS; NEURAL NETWORK; TELANGIECTASIA; VESSELS;

ALGORITHMS; CARCINOMA, BASAL CELL; DERMOSCOPY; FLORIDA; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MISSOURI; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SKIN NEOPLASMS; TELANGIECTASIS;

EID: 79960322710     PISSN: 0909752X     EISSN: 16000846     Source Type: Journal    
DOI: 10.1111/j.1600-0846.2010.00494.x     Document Type: Article

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