Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images

Hirohisa Oda; Kohei Nishio; Takayuki Kitasaka; Hizuru Amano; Aitaro Takimoto; Hiroo Uchida; Kojiro Suzuki; Hayato Itoh; Masahiro Oda; Kensaku Mori

doi:10.1117/12.2548910

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16 March 2020 Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images

Hirohisa Oda, Kohei Nishio, Takayuki Kitasaka, Hizuru Amano, Aitaro Takimoto, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, Kensaku Mori

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Proceedings Volume 11314, Medical Imaging 2020: Computer-Aided Diagnosis; 1131434 (2020) https://doi.org/10.1117/12.2548910
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

This paper presents a visualization method of intestine (the small and large intestine) 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 liquids. These liquids 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.

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Hirohisa Oda, Kohei Nishio, Takayuki Kitasaka, Hizuru Amano, Aitaro Takimoto, Hiroo Uchida, Kojiro Suzuki, Hayato Itoh, Masahiro Oda, and Kensaku Mori "Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images", Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 1131434 (16 March 2020); https://doi.org/10.1117/12.2548910

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