Chen Yen-Chun, Karmakar Riya, Mukundan Arvind, Huang Chien-Wei, Weng Wei-Chun, Wang Hsiang-Chen
Department of Gastroenterology, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No. 2, Minsheng Road, Dalin, Chiayi, 62247 Taiwan.
School of Medicine, Tzuchi University, No.701, Sec. 3, Zhongyang Rd. Hualien 97004, Taiwan.
J Cancer. 2025 Jan 1;16(2):470-478. doi: 10.7150/jca.102759. eCollection 2025.
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.
波段选择是降低高光谱图像数据维度的常用方法。它利用高光谱相关性在某种意义上提取几个重要波段。在医学成像中,窄带成像(NBI)是一种用于内镜诊断医学检查的成像技术,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。一种特殊的滤光片通过内镜中的开关进行电子激活,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处,血管会显得非常暗,从而提高其可见性并改善对其他表面结构的识别。与白光成像(WLI)相比,NBI在与计算机辅助诊断(CAD,Intespec C,Hitspectra智能技术公司,台湾高雄)结合检测癌性图像时已被证明具有更高的精度。NBI内镜是专门设备,可能并非在所有医疗环境中都广泛可用。通过利用现有的WLI内镜系统并开发算法来模拟NBI成像,医疗机构无需额外的昂贵设备即可实现类似的诊断能力。因此,在本研究中,已开发出一种名为SAVE(光谱辅助视觉增强器)的算法,它可以通过针对奥林巴斯内镜的智能波段选择高光谱成像从WLI图像模拟NBI。结果表明,SAVE-NBI图像比WLI图像具有更高的精度和F1分数。