Multimodal and Multiview Wound Monitoring with Mobile Devices

Author:

Gutierrez EvelynORCID,Castañeda BenjamínORCID,Treuillet SylvieORCID,Hernandez IvanORCID

Abstract

Along with geometric and color indicators, thermography is another valuable source of information for wound monitoring. The interaction of geometry with thermography can provide predictive indicators of wound evolution; however, existing processes are focused on the use of high-cost devices with a static configuration, which restricts the scanning of large surfaces. In this study, we propose the use of commercial devices, such as mobile devices and portable thermography, to integrate information from different wavelengths onto the surface of a 3D model. A handheld acquisition is proposed in which color images are used to create a 3D model by using Structure from Motion (SfM), and thermography is incorporated into the 3D surface through a pose estimation refinement based on optimizing the temperature correlation between multiple views. Thermal and color 3D models were successfully created for six patients with multiple views from a low-cost commercial device. The results show the successful application of the proposed methodology where thermal mapping on 3D models is not limited in the scanning area and can provide consistent information between multiple thermal camera views. Further work will focus on studying the quantitative metrics obtained by the multi-view 3D models created with the proposed methodology.

Funder

Horizon 2020

Publisher

MDPI AG

Subject

Radiology, Nuclear Medicine and imaging,Instrumentation,Atomic and Molecular Physics, and Optics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Registration of thermal 3D models over time using low cost and portable devices;Sixteenth International Conference on Quality Control by Artificial Vision;2023-07-28

2. Generating 3D Bio-Printable Patches Using Wound Segmentation and Reconstruction to Treat Diabetic Foot Ulcers;2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2022-06

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