Development and clinical validation of a novel photography‐based skin pigmentation evaluation system: a comparison with the calculated consensus of dermatologists

Abstract

This pigmentation evaluation system can reproduce the physicians' consensus, suggesting that this system can support the dermatologists' objective evaluation of pigmentation.

Identification of cecum time-location in a colonoscopy video by deep learning analysis of colonoscope movement

“…In our colonoscopy video, a 0.5 s period yielded optimal results. As the standard setting, observing the colonoscopy video at a speed of 0.7 times to avoid misreading directions, participation of five fellow doctors, and selecting values more than three made the accuracy of the gold standard more reliable (Cho et al, 2016; Fallah & Niakan Kalhori, 2017; Cho et al, 2017)…”

Development and clinical validation of a novel photography‐based skin erythema evaluation system: a comparison with the calculated consensus of dermatologists

“…. An algorithm developed in a previous study for detecting pigmentation was modified to detect erythema. To detect only erythema, irrespective of pigmentary changes, channel mixing was used .…”

“…The green channel was primarily used in the channel mixing algorithm after bilateral filtering and discriminate equalization. Bilateral filtering was performed to reduce noise , and discriminate equalization was performed to classify the pixels of the images based on intensity values . In the channel mixing, discriminate equalization was applied to the green channel instead of the L* channel.…”

“…We devised a new consensus parameter, the clinical consensus area of erythema (CCAE), for this purpose. Previously, we developed a similar parameter called the clinical consensus area of pigmentation (CCAP), which summarized five dermatologists’ clinical judgements and degree of consensus on pigmentation . In this study, five dermatologists evaluated areas of erythema in the same photographs.…”

“…Thus, new devices are needed that can provide a consistent photographic environment over multiple measurements and evaluate a sufficiently wide field to perform objective and quantitative assessments conveniently. Previously, our group developed such a system for use in pigmentation measurement . In this study, we designed a novel system that acquires high‐quality photographs from three different viewpoints for quantitatively measuring erythema using a dermatologists’ algorithm.…”