Computerized Medical Diagnosis of Melanocytic Lesions based on the ABCD approach

dc.creatorBareiro Paniagua,Laura Raquel
dc.creatorLeguizamón Correa,Deysi Natalia
dc.creatorPinto-Roa,Diego P.
dc.creatorVázquez Noguera,José Luis
dc.creatorSalgueiro Toledo,Lizza A
dc.date2016-08-01
dc.date.accessioned2023-09-25T18:36:00Z
dc.date.available2023-09-25T18:36:00Z
dc.identifierhttp://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002016000200006
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8838832
dc.descriptionMelanoma is a type of skin cancer and is caused by the uncontrolled growth of atypical melanocytes. In recent decades, computer aided diagnosis is used to support medical professionals; however, there is still no globally accepted tool. In this context, similar to state-of-the-art we propose a system that receives a dermatoscopy image and provides a diagnostic if the lesion is benign or malignant. This tool is composed with next modules: Preprocessing, Segmentation, Feature Extraction, and Classification. Preprocessing involves the removal of hairs. Segmentation is to isolate the lesion. Feature extraction is considering the ABCD dermoscopy rule. The classification is performed by the Support Vector Machine. Experimental evidence indicates that the proposal has 90.63 % accuracy, 95 % sensitivity, and 83.33 % specificity on a data-set of 104 dermatoscopy images. These results are favorable considering the performance of diagnosis by traditional progress in the area of dermatology
dc.formattext/html
dc.languageen
dc.publisherCentro Latinoamericano de Estudios en Informática
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceCLEI Electronic Journal v.19 n.2 2016
dc.subjectMelanoma
dc.subjectAutomatic Diagnosis
dc.subjectImage Processing
dc.subjectMachine Learning
dc.titleComputerized Medical Diagnosis of Melanocytic Lesions based on the ABCD approach
dc.typeinfo:eu-repo/semantics/article


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