JOURNAL ARTICLE

Wound detection and reconstruction using RGB-D camera

Abstract

The advent of inexpensive RGB-D sensors pioneered by the original Kinect sensor, has paved the way for a lot of innovations in computer and robot vision applications. In this article, we propose a system which uses the new Kinect 2 sensor in a medical application for the purpose of detection and 3D reconstruction of chronic wounds. Wound detection is based on a per block classification of wound tissue using color histograms and the nearest neighbor approach. The 3D reconstruction is similar to KinectFusion where ICP is used for determining the rigid body transformation, color enhanced TSDF is applied for scene fusion, while the marching cubes algorithm is used for creating a surface mesh. The entire system is implemented in CUDA which enables real-time operation. The end result of the developed system is a precise 3D colored model which can be used for determining a correct therapy and treatment of chronic wounds.

Keywords:
Computer vision Artificial intelligence RGB color model Computer science Marching cubes Histogram Block (permutation group theory) CUDA Computer graphics (images) Image (mathematics) Mathematics Visualization

Metrics

8
Cited By
1.26
FWCI (Field Weighted Citation Impact)
19
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Diabetic Foot Ulcer Assessment and Management
Health Sciences →  Medicine →  Endocrinology, Diabetes and Metabolism
3D Surveying and Cultural Heritage
Physical Sciences →  Earth and Planetary Sciences →  Geology
Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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