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Discrimination between normal and necrotic small intestinal tissue using hyperspectral imaging and unsupervised classification.
Zhang, Lechao; Huang, Danfei; Chen, Xiaojing; Zhu, Libin; Xie, Zhonghao; Chen, Xiaoqing; Cui, Guihua; Zhou, Yao; Huang, Guangzao; Shi, Wen.
Afiliación
  • Zhang L; College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China.
  • Huang D; Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China.
  • Chen X; College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China.
  • Zhu L; Zhongshan Research Institute, Changchun University of Science and Technology, Zhongshan, China.
  • Xie Z; College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China.
  • Chen X; Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, China.
  • Cui G; College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China.
  • Zhou Y; Pediatric General Surgery, The Second Hospital of Wenzhou Medical University, Wenzhou, China.
  • Huang G; College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, China.
  • Shi W; College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun, China.
J Biophotonics ; 16(7): e202300020, 2023 07.
Article en En | MEDLINE | ID: mdl-36966458
ABSTRACT
Objective and automatic clinical discrimination of normal and necrotic sites of small intestinal tissue remains challenging. In this study, hyperspectral imaging (HSI) and unsupervised classification techniques were used to distinguish normal and necrotic sites of small intestinal tissues. Small intestinal tissue hyperspectral images of eight Japanese large-eared white rabbits were acquired using a visible near-infrared hyperspectral camera, and K-means and density peaks (DP) clustering algorithms were used to differentiate between normal and necrotic tissue. The three cases in this study showed that the average clustering purity of the DP clustering algorithm reached 92.07% when the two band combinations of 500-622 and 700-858 nm were selected. The results of this study suggest that HSI and DP clustering can assist physicians in distinguishing between normal and necrotic sites in the small intestine in vivo.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Algoritmos / Imágenes Hiperespectrales Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: J Biophotonics Asunto de la revista: BIOFISICA Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Algoritmos / Imágenes Hiperespectrales Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: J Biophotonics Asunto de la revista: BIOFISICA Año: 2023 Tipo del documento: Article País de afiliación: China