Reducing the Impact of Confounding Factors on Skin Cancer Classification via Image Segmentation: Technical Model Study.
Roman Christoph MaronAchim HeklerEva Krieghoff-HenningMax SchmittJustin Gabriel SchlagerJochen Sven UtikalTitus Josef BrinkerPublished in: Journal of medical Internet research (2021)
Image segmentation does not result in overall performance decrease but it causes the beneficial removal of lesion-adjacent confounding factors. Thus, it is a viable option to address the negative impact that confounding factors have on deep learning models in dermatology. However, the segmentation step might introduce new pitfalls, which require further investigations.