mlsanityData to 14 Oct 2026

Graph-Based Small Bowel Path Tracking with Cylindrical Constraints

arXiv 2207.14436 ↗First posted 29 Jul 2022cs.CV eess.IVcited by 0

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Abstract (arXiv)

We present a new graph-based method for small bowel path tracking based on cylindrical constraints. A distinctive characteristic of the small bowel compared to other organs is the contact between parts of itself along its course, which makes the path tracking difficult together with the indistinct appearance of the wall. It causes the tracked path to easily cross over the walls when relying on low-level features like the wall detection. To circumvent this, a series of cylinders that are fitted along the course of the small bowel are used to guide the tracking to more reliable directions. It is implemented as soft constraints using a new cost function. The proposed method is evaluated against ground-truth paths that are all connected from start to end of the small bowel for 10 abdominal CT scans. The proposed method showed clear improvements compared to the baseline method in tracking the path without making an error. Improvements of 6.6% and 17.0%, in terms of the tracked length, were observed for two different settings related to the small bowel segmentation.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 20 references that are in the map. First posted on arXiv 29 Jul 2022.

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References · 5

  1. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,476
  2. 2021Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representationcited by 11
  3. 2020Deep Small Bowel Segmentation with Cylindrical Topological Constraintscited by 6
  4. 2021A Graph-theoretic Algorithm for Small Bowel Path Tracking in CT Scanscited by 3
  5. 2020Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT imagescited by 2

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