Evaluation of Band Selection for Spectrum-Aided Visual Enhancer (SAVE) for Esophageal Cancer Detection.

IF 3.2 3区 医学 Q2 ONCOLOGY Journal of Cancer Pub Date : 2025-01-01 DOI:10.7150/jca.102759
Yen-Chun Chen, Riya Karmakar, Arvind Mukundan, Chien-Wei Huang, Wei-Chun Weng, Hsiang-Chen Wang
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Abstract

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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食管癌光谱辅助视觉增强器(SAVE)波段选择的评价。
波段选择是降低高光谱图像数据维数的常用方法。利用高谱相关性,提取出若干具有一定意义的重要波段。在医学成像中,窄带成像(NBI)是一种用于内窥镜诊断医学测试的成像技术,其中使用特定蓝色和绿色波长的光来增强粘膜表面某些方面的细节。通过内窥镜中的开关,一个特殊的过滤器被电子激活,从而使用波长为415纳米(蓝色)和540纳米(绿色)的环境光。由于血红蛋白的峰值光吸收发生在这些波长,血管将显得非常暗,从而提高了它们的可见度,并改善了对其他表面结构的识别。与白光成像(WLI)相比,NBI在结合计算机辅助诊断(CAD, intespecc, Hitspectra Intelligent Technology Co.,高雄,台湾)检测癌症图像时具有更高的精度。NBI内窥镜是一种专用设备,可能并非在所有医疗保健环境中都广泛可用。通过利用现有的WLI内窥镜系统和开发算法来模拟NBI成像,医疗机构可以实现类似的诊断功能,而无需额外的昂贵设备。因此,在本研究中,我们开发了一种名为SAVE(光谱辅助视觉增强器)的算法,该算法可以通过奥林巴斯内窥镜的智能波段选择性高光谱成像,从WLI图像中模拟NBI。结果表明,与WLI图像相比,SAVE-NBI图像具有更好的精度和f1评分。
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来源期刊
Journal of Cancer
Journal of Cancer ONCOLOGY-
CiteScore
8.10
自引率
2.60%
发文量
333
审稿时长
12 weeks
期刊介绍: Journal of Cancer is an open access, peer-reviewed journal with broad scope covering all areas of cancer research, especially novel concepts, new methods, new regimens, new therapeutic agents, and alternative approaches for early detection and intervention of cancer. The Journal is supported by an international editorial board consisting of a distinguished team of cancer researchers. Journal of Cancer aims at rapid publication of high quality results in cancer research while maintaining rigorous peer-review process.
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