Video capsule endoscopy (VCE) is increasingly used to decrease discomfort among patients owing to its small size. However, VCE has a major drawback of not having narrow band imaging (NBI) functionality. The current VCE has the traditional white light imaging (WLI) only, which has poor performance in the computer-aided detection (CAD) of different types of cancer compared to NBI. Specific cancers, such as esophageal cancer (EC), do not exhibit any early biomarkers, making their early detection difficult. In most cases, the symptoms are unnoticeable, and EC is diagnosed only in later stages, making its 5-year survival rate below 20% on average. NBI filters provide particular wavelengths that increase the contrast and enhance certain features of the mucosa, thereby enabling early identification of EC. However, VCE does not have a slot for NBI functionality because its size cannot be increased. Hence, NBI image conversion from WLI can presently only be achieved in post-processing. In this study, a complete arithmetic assessment of the decorrelated color space was conducted to generate NBI images from WLI images for VCE of the esophagus. Three parameters, structural similarity index metric (SSIM), entropy, and peak-signal-to-noise ratio (PSNR), were used to assess the simulated NBI images. Results show the good performance of the NBI image reproduction method with SSIM, entropy difference, and PSNR values of 93.215%, 4.360, and 28.064 dB, respectively.
视频胶囊内窥镜（VCE）因其体积小巧，正被越来越多地用于减轻患者的不适。然而，VCE存在一个主要缺点，即不具备窄带成像（NBI）功能。目前的VCE仅配备传统的白光成像（WLI），与NBI相比，在计算机辅助检测（CAD）不同类型癌症方面表现较差。特定癌症，如食管癌（EC），不表现出任何早期生物标志物，这使得其早期检测变得困难。在大多数情况下，症状不明显，EC仅在晚期才被诊断出来，导致其5年生存率平均低于20%。NBI滤镜提供特定波长，可增加对比度并增强黏膜的某些特征，从而实现EC的早期识别。然而，由于尺寸无法增大，VCE没有NBI功能的插槽。因此，目前只能通过后处理从WLI图像转换为NBI图像。在本研究中，对去相关色彩空间进行了完整的算术评估，以从食管VCE的WLI图像生成NBI图像。使用结构相似性指数（SSIM）、熵和峰值信噪比（PSNR）三个参数来评估模拟的NBI图像。结果显示，NBI图像再现方法表现良好，SSIM、熵差和PSNR值分别为93.215%、4.360和28.064 dB。
肿瘤(癌症)患者之家