Use of Machine Learning Tools for Post-Processing of Digital Dermoscopic Images: a Case Series

Abstract

The use of electronic photographic recording has greatly facilitated the process of photo post-processing. Digital camera-based fixation enables extensive manipulation of captured images, potentially uncovering diagnostically relevant features and improving the visualization of dermoscopic structures. This article aims to illustrate the potential utility of digital image post-processing in selected diagnostic contexts. A series of clinical dermoscopic images are presented, demonstrating pre- and post-processing comparisons, with annotated regions highlighting key diagnostic structures. Digital post-processing may offer diagnostic support in certain cases, particularly when used in conjunction with artificial intelligence and machine learning algorithms, which facilitate analysis with minimal user intervention. However, validation of the diagnostic reliability of post-processed images necessitates multicenter, retrospective comparative studies.