Integration and Optimization of a 3D Scanning-Based Wound Coverage System with AI-Driven Boundary Detection

DOI

10.2991/978-94-6239-823-8_12How to use a DOI?

Keywords

3D scanning; pressure ulcers; wound segmentation; artificial intelligence; wound assessment

Abstract

Accurate characterization of the geometric and surface properties of pressure ulcers is important for supporting therapeutic decisions and wound coverage planning. Three-dimensional scanning technologies provide new possibilities for capturing wound geometry in a digital form and enable more detailed spatial analysis than traditional two-dimensional approaches. Despite these advances, practical application remains challenging, particularly with respect to system integration, usability, and extensibility of the complete processing pipeline in real-world environments. This study presents the integration and optimization of a wound coverage system, building on processing components developed in earlier stages of the research. The pipeline integrates steps from 3D data capture to wound coverage planning and combines manual user interaction with automated algorithmic procedures. An essential aspect of the present work is the incorporation of artificial intelligence methods into the workflow, with a particular focus on automatic wound boundary detection for subsequent geometric evaluation and coverage planning. A modular system architecture forms a central design principle, allowing individual functional units to be developed, tested, replaced, or extended independently while maintaining consistent data flow. Compared with the initial wound coverage baseline version, the integrated system introduces consolidated functional units, increased automation, AI-supported boundary detection, and targeted improvements to the graphical user interface. The current implementation demonstrates the feasibility of combining these components within a functional research prototype. Further technical and clinical validation is required, with future development focusing on improved automation, expanded AI integration, and enhanced clinical applicability.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Szabina Molnár-Zékány
PY  - 2026
DA  - 2026/11/04
TI  - Integration and Optimization of a 3D Scanning-Based Wound Coverage System with AI-Driven Boundary Detection
BT  - Proceedings of the Innovation in Engineering Education 2026 Conference (IEE 2026)
PB  - Atlantis Press
SP  - 134
EP  - 144
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6239-823-8_12
DO  - 10.2991/978-94-6239-823-8_12
ID  - Molnár-Zékány2026
ER  -