BACKGROUND: It is often difficult to differentiate early melanoma from benign pigmented lesions of similar clinical appearance. OBJECTIVE: Our purpose was to develop a computer image analysis system that has the potential for use as an adjunct to the clinical distinction of melanoma from less serious pigmented lesions. METHODS: The system, consisting of a hand-held device incorporating a color video camera and color frame grabber mounted in a microcomputer, was used in a pigmented lesion clinic. Analysis software extracted features relevant to the size, color, shape, and boundary of each lesion, and these features were correlated with clinical and histologic characteristics on which standard diagnoses of skin tumors are based. For discriminant analysis based on image analysis measurements, equal prior probabilities were assigned to two specified diagnostic groups, namely melanoma and "other pigmented lesions," most of which were melanocytic nevi. RESULTS: In a 20-month period, video images of 164 unselected pigmented lesions for which complete diagnostic data were available were successfully captured using the camera. Sixteen of 18 melanomas, and 89% of pigmented lesions overall, were correctly classified by the image analysis system, compared with 83% based on clinical gradings of lesion characteristics. CONCLUSION: Computer image analysis has the potential to provide a valuable diagnostic aid that could enable clinicians to make highly sensitive and specific diagnoses of early, curable melanoma.
BACKGROUND: It is often difficult to differentiate early melanoma from benign pigmented lesions of similar clinical appearance. OBJECTIVE: Our purpose was to develop a computer image analysis system that has the potential for use as an adjunct to the clinical distinction of melanoma from less serious pigmented lesions. METHODS: The system, consisting of a hand-held device incorporating a color video camera and color frame grabber mounted in a microcomputer, was used in a pigmented lesion clinic. Analysis software extracted features relevant to the size, color, shape, and boundary of each lesion, and these features were correlated with clinical and histologic characteristics on which standard diagnoses of skin tumors are based. For discriminant analysis based on image analysis measurements, equal prior probabilities were assigned to two specified diagnostic groups, namely melanoma and "other pigmented lesions," most of which were melanocytic nevi. RESULTS: In a 20-month period, video images of 164 unselected pigmented lesions for which complete diagnostic data were available were successfully captured using the camera. Sixteen of 18 melanomas, and 89% of pigmented lesions overall, were correctly classified by the image analysis system, compared with 83% based on clinical gradings of lesion characteristics. CONCLUSION: Computer image analysis has the potential to provide a valuable diagnostic aid that could enable clinicians to make highly sensitive and specific diagnoses of early, curable melanoma.
Authors: R Joe Stanley; William V Stoecker; Randy H Moss; Harold S Rabinovitz; Armand B Cognetta; Giuseppe Argenziano; H Peter Soyer Journal: Skin Res Technol Date: 2008-11 Impact factor: 2.365
Authors: R Joe Stanley; Randy Hays Moss; William Van Stoecker; Chetna Aggarwal Journal: Comput Med Imaging Graph Date: 2003 Sep-Oct Impact factor: 4.790