Evaluation of Band Selection for Spectrum-Aided Visual Enhancer (SAVE) for Esophageal Cancer Detection Article Swipe
Yen-Chun Chen
,
Riya Karmakar
,
Arvind Mukundan
,
Chien‐Wei Huang
,
Wei‐Chun Weng
,
Hsiang‐Chen Wang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.7150/jca.102759
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.7150/jca.102759
Band selection is a common approach to reduce the data dimensionality of hyperspectral imagery. It extracts several bands of importance in some sense by taking advantage of high spectral correlation. In medical imaging, narrow-band imaging (NBI) is an imaging technique for endoscopic diagnostic medical tests, where light of specific blue and green wavelengths is used to enhance the detail of certain aspects of the surface of the mucosa. A special filter is electronically activated by a switch in the endoscope leading to the use of ambient light of wavelengths of 415 nm (blue) and 540 nm (green). Because the peak light absorption of hemoglobin occurs at these wavelengths, blood vessels will appear very dark, allowing for their improved visibility and in the improved identification of other surface structures. NBI when compared with the white-light imaging (WLI) have proven to have better precision when combined with computer-aided diagnosis (CAD, Intespec C, Hitspectra Intelligent Technology Co., Kaohsiung, Taiwan) in detecting cancerous images. NBI endoscopes are specialized equipment that may not be widely available in all healthcare settings. By leveraging existing WLI endoscopic systems and developing algorithms to simulate NBI imaging, healthcare facilities can achieve similar di-agnostic capabilities without the need for additional costly equipment. Therefore, in this study, algorithm known as the SAVE (spectrum-aided visual enhancer) has been developed which can simulate NBI from the WLI images through an intelligent band-selective hyperspectral imaging for Olympus endoscope. The results suggested that the SAVE-NBI images had a better precision and F1-score than the WLI images.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7150/jca.102759
- OA Status
- gold
- Cited By
- 9
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4405256059Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.7150/jca.102759Digital Object Identifier
- Title
-
Evaluation of Band Selection for Spectrum-Aided Visual Enhancer (SAVE) for Esophageal Cancer DetectionWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-11Full publication date if available
- Authors
-
Yen-Chun Chen, Riya Karmakar, Arvind Mukundan, Chien‐Wei Huang, Wei‐Chun Weng, Hsiang‐Chen WangList of authors in order
- Landing page
-
https://doi.org/10.7150/jca.102759Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.7150/jca.102759Direct OA link when available
- Concepts
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Esophageal cancer, Selection (genetic algorithm), Enhancer, Computer science, Cancer, Artificial intelligence, Computational biology, Medicine, Biology, Internal medicine, Genetics, Gene, Transcription factorTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
- Citations by year (recent)
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2025: 9Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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