This study presents a method to identify early esophageal cancer within endoscope using hyperspectral imaging technology. The research samples are three kinds of endoscopic images including white light endoscopic, chromoendoscopic, and narrow-band endoscopic images with different stages of pathological changes (normal, dysplasia, dysplasia - esophageal cancer, and esophageal cancer). Research is divided into two parts: first, we analysis the reflectance spectra of endoscopic images with different stages to know the spectral responses by pathological changes. Second, we identified early cancerous lesion of esophagus by principal component analysis (PCA) of the reflectance spectra of endoscopic images. The results of this study show that the identification of early cancerous lesion is possible achieve from three kinds of images. In which the spectral characteristics of NBI endoscopy images of a gray area than those without the existence of the problem the first two, and the trend is very clear. Therefore, if simply to reflect differences in the degree of spectral identification, chromoendoscopic images are suitable samples. The best identification of early esophageal cancer is using the NBI endoscopic images. Based on the results, the use of hyperspectral imaging technology in the early endoscopic esophageal cancer lesion image recognition helps clinicians quickly diagnose. We hope for the future to have a relatively large amount of endoscopic image by establishing a hyperspectral imaging database system developed in this study, so the clinician can take this repository more efficiently preliminary diagnosis.
Shih-Wei Huang, Shih-Hua Chen, Weichung Chen, I-Chen Wu, Ming Tsang Wu, Chie-Tong Kuo, and Hsiang-Chen Wang, "Identification of early cancerous lesion of esophagus with endoscopic images by hyperspectral image technique
(Conference Presentation)," Proc. SPIE 9701, Multimodal Biomedical Imaging XI, 97010G (Presented at SPIE BiOS: February 13, 2016; Published: 26 April 2016); https://doi.org/10.1117/12.2211989.4848643184001.
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