A. G.-UribeJ. ZouM. DuvicV. PrietoL. V. WangTZU-HSUAN CHANG2019-10-312019-10-31201016057422https://scholars.lib.ntu.edu.tw/handle/123456789/429212https://www.scopus.com/inward/record.uri?eid=2-s2.0-77951754051&doi=10.1117%2f12.842781&partnerID=40&md5=ca4761b72d0f843c4a34aa05e2d23565This paper presents the use of spatially resolved oblique-incidence diffuse reflectance spectroscopy for skin cancer diagnosis. Spatio-spectral data from 166 pigmented skin lesions were collected for the wavelength range from 455 to 765 nm. A set of neural network based classifiers separates the pigmented malignant melanomas from the benign and dysplastic subgroups. A total of 110 lesions were used as the training set and 56 lesions were used as the testing set. This classifier performs with an overall 100% sensitivity and 92% specificity for the training set and 100% sensitivity and 88% specificity for the testing set. The second classifier was designed to separate the benign from the dysplastic subgroups. For the second classifier a total of 100 lesions were used as the training set and 51 lesions were used as the testing set. The overall classification rates were 94% and 88% for the training and testing sets respectively. © 2010 Copyright SPIE - The International Society for Optical Engineering.Diffuse reflectance; Melanoma; Skin cancer; Spectroscopy[SDGs]SDG3Classification rates; Diffuse reflectance; Diffuse reflectance spectroscopy; Malignant melanoma; Melanoma; Pigmented skin lesions; Skin cancers; Spatially resolved; Spectral data; Spectroscopic diagnosis; Training and testing; Training sets; Wavelength ranges; Classification (of information); Classifiers; Neural networks; Oncology; Reflection; Skin; Spectroscopy; Dermatologyconference paper10.1117/12.8427812-s2.0-77951754051