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

Marian Voloshynovych; Tetiana Boychuk; Iryna Blaha; Oleksandr Berezkin; Natalia Matkovska; Volodymyr Voloshynovych

doi:10.5114/dr.2025.152310

eISSN: 2084-9893
ISSN: 0033-2526

Dermatology Review/Przegląd Dermatologiczny

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1/2025
vol. 112

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abstract:

Case report

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

Marian Voloshynovych

^{1, 2}

,

Tetiana Boychuk

²

,

Iryna Blaha

^{1, 2}

,

Oleksandr Berezkin

³

,

Natalia Matkovska

⁴

,

Volodymyr Voloshynovych

⁵

Department of Dermatology and Venereology, Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine
Lux Skin, Ivano-Frankivsk, Ukraine
Bogomolets dermpathlab, Kyiv, Ukraine
Department of Therapy, Family and Emergency Medicine of Postgraduate Education, Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine
Department of Forensic Medicine, Medical and Pharmaceutical Law, Ivano-Frankivsk National Medical University, Ivano-Frankivsk, Ukraine

Dermatol Rev/Przegl Dermatol 2025, 112, 59-63

DOI: https://doi.org/10.5114/dr.2025.152310

Online publish date: 2025/05/20

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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.

keywords:

diagnostic imaging, dermoscopy, machine learning, image enhancement, skin neoplasms

Indeks osobowy

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

Marian Voloshynovych 1, 2 , Tetiana Boychuk 2 , Iryna Blaha 1, 2 , Oleksandr Berezkin 3 , Natalia Matkovska 4 , Volodymyr Voloshynovych 5

diagnostic imaging, dermoscopy, machine learning, image enhancement, skin neoplasms

Marian Voloshynovych

^{1, 2}

,

Tetiana Boychuk

²

,

Iryna Blaha

^{1, 2}

,

Oleksandr Berezkin

³

,

Natalia Matkovska

⁴

,

Volodymyr Voloshynovych

⁵