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Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer
The clinical signs and symptoms of esophageal cancer (EC) are often not discernible until the intermediate or advanced phases. The detection of EC in advanced stages significantly decreases the survival rate to below 20%. This study conducts a comparative analysis of the efficacy of several imaging...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665456/ https://www.ncbi.nlm.nih.gov/pubmed/37993660 http://dx.doi.org/10.1038/s41598-023-47833-y |
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author | Yang, Kai-Yao Mukundan, Arvind Tsao, Yu-Ming Shi, Xian-Hong Huang, Chien-Wei Wang, Hsiang-Chen |
author_facet | Yang, Kai-Yao Mukundan, Arvind Tsao, Yu-Ming Shi, Xian-Hong Huang, Chien-Wei Wang, Hsiang-Chen |
author_sort | Yang, Kai-Yao |
collection | PubMed |
description | The clinical signs and symptoms of esophageal cancer (EC) are often not discernible until the intermediate or advanced phases. The detection of EC in advanced stages significantly decreases the survival rate to below 20%. This study conducts a comparative analysis of the efficacy of several imaging techniques, including white light image (WLI), narrowband imaging (NBI), cycle-consistent adversarial network simulated narrowband image (CNBI), and hyperspectral imaging simulated narrowband image (HNBI), in the early detection of esophageal cancer (EC). In conjunction with Kaohsiung Armed Forces General Hospital, a dataset consisting of 1000 EC pictures was used, including 500 images captured using WLI and 500 images captured using NBI. The CycleGAN model was used to generate the CNBI dataset. Additionally, a novel method for HSI imaging was created with the objective of generating HNBI pictures. The evaluation of the efficacy of these four picture types in early detection of EC was conducted using three indicators: CIEDE2000, entropy, and the structural similarity index measure (SSIM). Results of the CIEDE2000, entropy, and SSIM analyses suggest that using CycleGAN to generate CNBI images and HSI model for creating HNBI images is superior in detecting early esophageal cancer compared to the use of conventional WLI and NBI techniques. |
format | Online Article Text |
id | pubmed-10665456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106654562023-11-22 Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer Yang, Kai-Yao Mukundan, Arvind Tsao, Yu-Ming Shi, Xian-Hong Huang, Chien-Wei Wang, Hsiang-Chen Sci Rep Article The clinical signs and symptoms of esophageal cancer (EC) are often not discernible until the intermediate or advanced phases. The detection of EC in advanced stages significantly decreases the survival rate to below 20%. This study conducts a comparative analysis of the efficacy of several imaging techniques, including white light image (WLI), narrowband imaging (NBI), cycle-consistent adversarial network simulated narrowband image (CNBI), and hyperspectral imaging simulated narrowband image (HNBI), in the early detection of esophageal cancer (EC). In conjunction with Kaohsiung Armed Forces General Hospital, a dataset consisting of 1000 EC pictures was used, including 500 images captured using WLI and 500 images captured using NBI. The CycleGAN model was used to generate the CNBI dataset. Additionally, a novel method for HSI imaging was created with the objective of generating HNBI pictures. The evaluation of the efficacy of these four picture types in early detection of EC was conducted using three indicators: CIEDE2000, entropy, and the structural similarity index measure (SSIM). Results of the CIEDE2000, entropy, and SSIM analyses suggest that using CycleGAN to generate CNBI images and HSI model for creating HNBI images is superior in detecting early esophageal cancer compared to the use of conventional WLI and NBI techniques. Nature Publishing Group UK 2023-11-22 /pmc/articles/PMC10665456/ /pubmed/37993660 http://dx.doi.org/10.1038/s41598-023-47833-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Yang, Kai-Yao Mukundan, Arvind Tsao, Yu-Ming Shi, Xian-Hong Huang, Chien-Wei Wang, Hsiang-Chen Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer |
title | Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer |
title_full | Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer |
title_fullStr | Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer |
title_full_unstemmed | Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer |
title_short | Assessment of hyperspectral imaging and CycleGAN-simulated narrowband techniques to detect early esophageal cancer |
title_sort | assessment of hyperspectral imaging and cyclegan-simulated narrowband techniques to detect early esophageal cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665456/ https://www.ncbi.nlm.nih.gov/pubmed/37993660 http://dx.doi.org/10.1038/s41598-023-47833-y |
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