{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T15:10:54Z","timestamp":1776525054285,"version":"3.51.2"},"reference-count":54,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T00:00:00Z","timestamp":1743379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Slovenian Research Agency","award":["P2-0065"],"award-info":[{"award-number":["P2-0065"]}]},{"name":"Slovenian Research Agency","award":["P1-0055"],"award-info":[{"award-number":["P1-0055"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>The rising incidence of skin cancer, particularly melanoma, underscores the need for improved diagnostic tools in dermatology. Accurate imaging plays a crucial role in early detection, yet challenges related to color accuracy, image distortion, and resolution persist, leading to diagnostic errors. This study addresses these issues by evaluating color reproduction accuracy across various imaging devices and lighting conditions. Using a ColorChecker test chart, color deviations were measured through Euclidean distances (\u0394E*, \u0394C*), and nonlinear color differences (\u0394E00, \u0394C00), while the color rendering index (CRI) and television lighting consistency index (TLCI) were used to evaluate the influence of light sources on image accuracy. Significant color discrepancies were identified among mobile phones, DSLRs, and mirrorless cameras, with inadequate dermatoscope lighting systems contributing to further inaccuracies. We demonstrate practical applications, including manual camera adjustments, grayscale reference cards, post-processing techniques, and optimized lighting conditions, to improve color accuracy. This study provides applicable solutions for enhancing color accuracy in dermatological imaging, emphasizing the need for standardized calibration techniques and imaging protocols to improve diagnostic reliability, support AI-assisted skin cancer detection, and contribute to high-quality image databases for clinical and automated analysis.<\/jats:p>","DOI":"10.3390\/jimaging11040107","type":"journal-article","created":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T08:48:00Z","timestamp":1743410880000},"page":"107","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Optimizing Digital Image Quality for Improved Skin Cancer Detection"],"prefix":"10.3390","volume":"11","author":[{"given":"Bogdan","family":"Dugonik","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, University of Maribor, Koro\u0161ka Cesta 46, SI-2000 Maribor, Slovenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6351-5541","authenticated-orcid":false,"given":"Marjan","family":"Golob","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Computer Science, University of Maribor, Koro\u0161ka Cesta 46, SI-2000 Maribor, Slovenia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0387-1162","authenticated-orcid":false,"given":"Marko","family":"Marhl","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Maribor, Taborska ulica 8, SI-2000 Maribor, Slovenia"},{"name":"Faculty of Education, University of Maribor, Koro\u0161ka cesta 160, SI-2000 Maribor, Slovenia"},{"name":"Faculty of Natural Sciences and Mathematics, University of Maribor, Koro\u0161ka cesta 160, SI-2000 Maribor, Slovenia"}]},{"given":"Aleksandra","family":"Dugonik","sequence":"additional","affiliation":[{"name":"Department of Dermatology, University Medical Centre Maribor, Ljubljanska Ulica 5, SI-2000 Maribor, Slovenia"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.ejca.2022.04.018","article-title":"European Consensus-Based Interdisciplinary Guideline for Melanoma. 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