Department of Medicine - Celiac Disease Center, Columbia University College of Physicians and Surgeons, New York, NY, USA.
Department of Medicine - Celiac Disease Center, Columbia University College of Physicians and Surgeons, New York, NY, USA.
Comput Biol Med. 2019 Mar;106:150-156. doi: 10.1016/j.compbiomed.2018.12.011. Epub 2018 Dec 24.
Videocapsule endoscopy images are useful to detect pathologic alterations, including villous atrophy, in the small intestinal mucosa, which is helpful for diagnosing celiac disease. In prior work, quantitative videocapsule analysis was found useful to classify celiac versus control images. However, the effect of dark/extraneous substances on classification efficacy requires remediation.
For quantitative analysis, data from the Medtronic SB2 and SB3 systems were pooled. Videocapsule images of the distal duodenum/proximal jejunum were acquired from 13 celiac and 13 control patients. Dark regions, extraneous fluids, and air bubbles were mostly removed by utilizing color masking. Two different red-green-blue (RGB) color masks were constructed from 20 to 30 reference pixels obtained from mucosal and from extraneous regions. Each image pixel was accepted or rejected for subsequent analysis based on whether its distance was closest to a mucosal or to an extraneous reference in RGB space. Four images were then randomly selected from each videoclip for processing (52 images from each group). After masking, celiac versus control images were plotted in a three-space consisting of mean and standard deviation in pixel brightness, and surface area remaining after masking. A linear discriminant function was used for classification. The paradigm was repeated with a second random data set for validation.
Masking improved classification of celiac versus control images to nearly 80% accuracy as compared to 70-77% without masking. Celiac disease patients tended to have lesser mean pixel brightness and greater variability in brightness, in accord with prior work, and more masking was needed to remove extraneous features.
Color masking is useful to remove dim/extraneous features from videocapsule images and it results in improved classification/assessment to distinguish celiac with villous atrophy from control videocapsule image. This can be helpful to detect and map regions of pathology, to screen for celiac disease, and to determine the efficacy of a gluten free diet.
视频胶囊内镜图像可用于检测小肠黏膜的病理改变，包括绒毛萎缩，这有助于诊断乳糜泻。在之前的工作中，定量视频胶囊分析被发现有助于对乳糜泻与对照图像进行分类。然而，暗区/外来物质对分类效果的影响需要进行修复。
对于定量分析，将 Medtronic SB2 和 SB3 系统的数据进行了汇总。从 13 例乳糜泻患者和 13 例对照患者的远端十二指肠/近端空肠采集视频胶囊图像。通过利用颜色遮罩，大部分暗区、外来液体和气泡都被去除。从黏膜和外来区域获得 20 到 30 个参考像素，构建了两个不同的红绿蓝（RGB）颜色遮罩。根据图像像素与 RGB 空间中黏膜或外来参考点的距离，接受或拒绝其进行后续分析。然后，从每个视频剪辑中随机选择四个图像进行处理（每组 52 个图像）。遮罩后，将乳糜泻与对照图像绘制在一个由像素亮度的平均值和标准差以及遮罩后剩余表面积组成的三维空间中。使用线性判别函数进行分类。使用第二个随机数据集进行验证，重复该范例。
与不使用遮罩时的 70-77%相比，遮罩将乳糜泻与对照图像的分类提高到近 80%的准确率。乳糜泻患者的平均像素亮度较低，亮度变化较大，这与之前的研究结果一致，并且需要更多的遮罩来去除外来特征。
颜色遮罩可用于从视频胶囊图像中去除暗淡/外来特征，并可提高分类/评估效果，以区分有绒毛萎缩的乳糜泻与对照视频胶囊图像。这有助于检测和绘制病理学区域，筛查乳糜泻，并确定无麸质饮食的疗效。
