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RESEARCH PRODUCT
Melanoma-Nevus Discrimination Based on Image Statistics in Few Spectral Channels
Ints MednieksDainis JakovelsAivars LorencsJuris Sinica-sinavskissubject
0301 basic medicineNevi and melanomasContextual image classificationImage classificationmelanoma detection.Multispectral imageSpectral bandsbiomedical optical imagingmedicine.disease01 natural sciencesThresholdingStandard deviation010104 statistics & probability03 medical and health sciences030104 developmental biologyCutaneous melanomaStatisticsmultispectral imagingmedicineNevus0101 mathematicsElectrical and Electronic EngineeringMathematicsdescription
The purpose of this paper is to offer a method for discrimination of cutaneous melanoma from benign nevus, founded on analysis of skin lesion image. At the core of method is calculation of mean and standard deviation of pixel optical density values for a few narrow spectral bands. Calculated values are compared with discriminating thresholds derived from a set of images of benign nevi and melanomas with known diagnosis. Classification is done applying weighted majority rule to results of thresholding. Verification against the available multispectral images of 32 melanomas and 94 benign nevi has shown that the method using three spectral bands provided zero false negative and four false positive melanoma detections. The proposed classifier is characterized by high sensitivity and specificity concerning statistical point estimates whereas its possible technical implementation is fairly simple. The proposed method may be instrumental for designing low cost diagnostic equipment to be used in primary care that is important for early detection of cutaneous melanoma. DOI: http://dx.doi.org/10.5755/j01.eie.22.2.12173
year | journal | country | edition | language |
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2016-04-13 | Elektronika ir Elektrotechnika |