Saliency-Enhanced Content-Based Image Retrieval for Diagnosis Support in Dermatology Consultation: Reader Study.

Background: Previous research studies have demonstrated that medical content image retrieval can play an important role by assisting dermatologists in skin lesion diagnosis. However, current state-of-the-art approaches have not been adopted in routine consultation, partly due to the lack of interpretability limiting trust by clinical users.

Objective: This study developed a new image retrieval architecture for polarized or dermoscopic imaging guided by interpretable saliency maps.

Suspicious Skin Lesion Detection in Wide-Field Body Images using Deep Learning Outlier Detection.

During consultation dermatologists have to address hundreds of lesions in a limited amount of time. They will not only evaluate the single lesion of interest but more importantly the context of it. Visually comparing the similarity of the majority of lesions within the same patient provides a strong indication for lesions with significantly differing aspects.