DICODerma: A practical approach for metadata management of images in dermatology

TL;DR

This paper introduces DICODerma, a practical tool and approach for managing dermatology images with DICOM standards, aiming to enhance metadata handling and standard adoption in dermatological imaging.

Contribution

It presents a novel, practical solution and open-source tools for integrating dermatologists' workflows with DICOM standards for image metadata management.

Findings

Enables tagging, searching, and organizing dermatology images.

Facilitates conversion of clinical images to DICOM format.

Aims to improve standard adoption in dermatology.

Abstract

Clinical images are vital for diagnosing and monitoring skin diseases, and their importance has increased with the growing popularity of machine learning. Lack of standards has stifled innovation in dermatological imaging, unlike other image-intensive specialties such as radiology. We investigate the meta-requirements for utilizing the popular DICOM standard for metadata management of images in dermatology. We propose practical design solutions and provide open-source tools to integrate dermatologists' workflow with enterprise imaging systems. Using the tool, dermatologists can tag, search, organize and convert clinical images to the DICOM format. We believe that our less disruptive approach will improve the adoption of standards in the specialty.