Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images
This addresses the difficulty for non-expert clinicians in diagnosing ileus by providing an intuitive visualization tool, though it is incremental as it builds on existing segmentation methods.
This paper tackles the problem of visualizing intestines and stenosed parts for ileus diagnosis from 3D CT images, using a 3D U-Net with weak annotation to segment regions and color them based on distance, resulting in intuitive identification of stenosed parts as endpoints in experiments.
This paper presents a visualization method of intestine (the small and large intestines) regions and their stenosed parts caused by ileus from CT volumes. Since it is difficult for non-expert clinicians to find stenosed parts, the intestine and its stenosed parts should be visualized intuitively. Furthermore, the intestine regions of ileus cases are quite hard to be segmented. The proposed method segments intestine regions by 3D FCN (3D U-Net). Intestine regions are quite difficult to be segmented in ileus cases since the inside the intestine is filled with fluids. These fluids have similar intensities with intestinal wall on 3D CT volumes. We segment the intestine regions by using 3D U-Net trained by a weak annotation approach. Weak-annotation makes possible to train the 3D U-Net with small manually-traced label images of the intestine. This avoids us to prepare many annotation labels of the intestine that has long and winding shape. Each intestine segment is volume-rendered and colored based on the distance from its endpoint in volume rendering. Stenosed parts (disjoint points of an intestine segment) can be easily identified on such visualization. In the experiments, we showed that stenosed parts were intuitively visualized as endpoints of segmented regions, which are colored by red or blue.