Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique
碩士 === 國立中正大學 === 機電光工程研究所 === 103 === 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 im...
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ndltd-TW-103CCU004900042019-05-15T22:07:57Z http://ndltd.ncl.edu.tw/handle/8a8z6v Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique 應用多頻譜影像技術於內視鏡影像辨識食道早期癌變病灶之研究 Shih-Hua Chen 陳世華 碩士 國立中正大學 機電光工程研究所 103 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. 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. 王祥辰 2015 學位論文 ; thesis 61 zh-TW |
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碩士 === 國立中正大學 === 機電光工程研究所 === 103 === 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. 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.
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author2 |
王祥辰 |
author_facet |
王祥辰 Shih-Hua Chen 陳世華 |
author |
Shih-Hua Chen 陳世華 |
spellingShingle |
Shih-Hua Chen 陳世華 Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique |
author_sort |
Shih-Hua Chen |
title |
Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique |
title_short |
Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique |
title_full |
Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique |
title_fullStr |
Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique |
title_full_unstemmed |
Identification of Early Cancerous Lesion of Esophagus with Endoscopic Images by Multispectral Image Technique |
title_sort |
identification of early cancerous lesion of esophagus with endoscopic images by multispectral image technique |
publishDate |
2015 |
url |
http://ndltd.ncl.edu.tw/handle/8a8z6v |
work_keys_str_mv |
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1719124771464019968 |