RGB-D Camera-Based Automatic Wound-Measurement System-Reference-Cited by-同舟云学术

RGB-D Camera-Based Automatic Wound-Measurement System

Published:2023 Issue: Volume:72 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zhang Peng¹^ORCID,Zhang Yichen¹^ORCID,Li Qiang¹^ORCID

Affiliation:

1. Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, and the MoE Key Laboratory for Biomedical Photonics, Collaborative Innovation Center for Biomedical Engineering, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Science Fund for Creative Research Group of China

Director Fund of WNLO

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10097754.pdf?arnumber=10097754

Reference47 articles.

1. Wound intensity correction and segmentation with convolutional neural networks

2. HarDNet-MSEG: A simple encoder–decoder polyp segmentation neural network that achieves over 0.9 mean dice and 86 FPS;huang;arXiv 2101 07172,2021

3. A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks;wang;Proc 37th Annu Int Conf IEEE Eng Med Biol Soc (EMBC),2015

4. Detection, Reconstruction and Segmentation of Chronic Wounds Using Kinect v2 Sensor

5. Convolutional neural networks for wound detection: the role of artificial intelligence in wound care

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