Research on application of spectral imaging technology in determining on thermal burn degree

作者
Yongquan Luo,Li Xian Huang,Junjie Yang,Zhixue Shen,Dayong Zhang,Jun Wu
出处
期刊:Proceedings of SPIE [SPIE]
卷期号:8512: 85120S-85120S 被引量:2
标识
DOI:10.1117/12.928348
摘要

Thermal injuries are a serious medical problem in the China. The accurate determination of burn degree is difficult for scatheless diagnose and a precondition of treating burn wounds. Multi-spectral photographic analysis is expected to play an important role in determining burn wound degree, the Liquid Crystal Tunable Filter has a capability of selecting the observing wavelength instaneously with high spectral resolution and excellent imaging quality in visible and near-infrared spectrum band. Taking advantage of this filter, we have developed a LCTF imaging spectrometer prototype instrument at visible wavelength bands for burn wound diagnose. In this paper, spectral analysis experiments were first performed on KUNMING mice and burn injury patients to find the characteristic reflective spectral curves at 400nm-1800nm, the imaging spectrometer prototype instrument using LCTFs which are sensitive to radiation in 420nm-750nmwavelength bands was built based on spectral analysis results. The spectral imaging experiments on burn injury patients have verified the excellent properties of the prototype instrument, including high quality spectral images with spectral resolution of less than 7nm and continuous selection of the output wavelength. The burn areas of patients were marked with different colors which represents as different burn degree and the spectral imaging system has thus been proven to have the ability to classify the burn areas through comparing their reflective spectral curves with characteristic spectrum of the different burn degree in spectral database in the future. Finally, the application of the LCTF imaging spectrometer to burn wound diagnose are summarized based on the results of spectral imaging experiments on burn injuries.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
深情安青应助mimi采纳,获得10
2秒前
真实的火车完成签到,获得积分10
5秒前
kk627完成签到,获得积分10
5秒前
LewisAlien发布了新的文献求助10
5秒前
DD完成签到 ,获得积分10
6秒前
7秒前
Hou完成签到,获得积分20
7秒前
Hello应助雪原白鹿采纳,获得10
8秒前
daydayup完成签到,获得积分10
10秒前
英俊的铭应助个性的语蓉采纳,获得10
10秒前
ninini完成签到 ,获得积分10
11秒前
11秒前
14秒前
douglas完成签到,获得积分10
14秒前
16秒前
ninini关注了科研通微信公众号
16秒前
18秒前
18秒前
所所应助研友_LXOvq8采纳,获得10
18秒前
dfsdgyu发布了新的文献求助10
19秒前
zzs发布了新的文献求助10
20秒前
缪连虎发布了新的文献求助10
21秒前
乐观的鞋子完成签到,获得积分10
22秒前
22秒前
默默完成签到,获得积分10
23秒前
24秒前
24秒前
小阮应助Maximuszhao采纳,获得10
25秒前
25秒前
25秒前
风趣的烤鸡完成签到,获得积分10
26秒前
26秒前
希zi发布了新的文献求助10
28秒前
yjh123应助123采纳,获得20
30秒前
宁宁发布了新的文献求助10
30秒前
Hello应助ay采纳,获得20
31秒前
xiaoxiao发布了新的文献求助10
31秒前
31秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Römisch-Germanische Forschungen 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Green Fire Retardants for Polymeric Materials 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7614653
求助须知:如何正确求助?哪些是违规求助? 9189999
关于积分的说明 19690853
捐赠科研通 7187421
什么是DOI,文献DOI怎么找? 3271178
关于科研通互助平台的介绍 2434506
邀请新用户注册赠送积分活动 2266167