| Autor: |
Lechao Zhang, Yao Zhou, Danfei Huang, Libin Zhu, Xiaoqing Chen, Zhonghao Xie, Guihua Cui, Guangzao Huang, Shujat Ali, Xiaojing Chen |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Photonics, Vol 10, Iss 7, p 708 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2304-6732 |
| DOI: |
10.3390/photonics10070708 |
| Popis: |
Obtaining adequate resection margins in small intestinal necrotic tissue remains challenging due to the lack of intraoperative feedback. Here, we used hyperspectral imaging (HSI), an imaging technique for objective identification, combined with deep learning methods for automated small intestine tissue classification. As part of a prospective experimental study, we recorded hyperspectral datasets of small intestine biopsies from seven white rabbits. Based on the differences in the spectral characteristics of normal and ischemic necrotic small intestinal tissues in the wavelength range of 400–1000 nm, we applied deep learning techniques to objectively distinguish between these two types of tissues. The results showed that three-dimensional convolutional neural networks were more effective in extracting both spectral and spatial features of small intestine tissue hyperspectral data for classification. The combination of a deep learning model and HSI provided a new idea for the objective identification of ischemic necrotic tissue in the small intestine. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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