Automatic diagnosis of melanoma using hyperspectral data and GoogLeNet.
Ginji HiranoMitsutaka NemotoYuichi KimuraYoshio KiyoharaHiroshi KogaNaoya YamazakiGustav ChristensenChristian IngvarKari NielsenAtsushi NakamuraTakayuki SotaTakashi NagaokaPublished in: Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) (2020)
The system was evaluated by 5-fold cross-validation, and the results indicate sensitivity, specificity, and accuracy of 69.1%, 75.7%, and 72.7% without data augmentation, 72.3%, 81.2%, and 77.2% with data augmentation, respectively. In future work, it is intended to improve the Mini Network and to increase the number of lesions.