Open AccessVisible near-infrared hyperspectral imaging and supervised classification for the detection of small intestinal necrosis tissue in vivo
Author(s) -
lechao zhang,
Danfei Huang,
Xiaojing Chen,
Li Zhu,
xiaoqing chen,
zhonghao xie,
Guangzao Huang,
junzhao gao,
Wen Shi,
Guihua Cui
Publication year - 2022
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.470202
Subject(s) - hyperspectral imaging , artificial intelligence , pathology , computer science , support vector machine , tissue sample , pattern recognition (psychology) , medicine , biomedical engineering
Complete recognition of necrotic areas during small bowel tissue resection remains challenging due to the lack of optimal intraoperative aid identification techniques. This research utilizes hyperspectral imaging techniques to automatically distinguish normal and necrotic areas of small intestinal tissue. Sample data were obtained from the animal model of small intestinal tissue of eight Japanese large-eared white rabbits developed by experienced physicians. A spectral library of normal and necrotic regions of small intestinal tissue was created and processed using six different supervised classification algorithms. The results show that hyperspectral imaging combined with supervised classification algorithms can be a suitable technique to automatically distinguish between normal and necrotic areas of small intestinal tissue. This new technique could aid physicians in objectively identify normal and necrotic areas of small intestinal tissue.