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J Bidgoli1, A Ahmadian, S Akhlaghpor

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Summary

This study introduces an efficient automated method for segmenting colonic walls in CT scans using half-sized data. The approach minimizes errors, enabling accurate colon lumen extraction for analysis.

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Area of Science:

  • Medical Imaging
  • Computer-Aided Diagnosis
  • Gastrointestinal Radiology

Background:

  • Automated segmentation of colonic walls in volumetric CT data is crucial for accurate analysis.
  • Existing methods can be time-consuming, necessitating efficient approaches.
  • Accurate extraction of the colon lumen is vital for diagnosing various conditions.

Purpose of the Study:

  • To develop an efficient, fully automated method for colonic wall segmentation in half-sized volumetric CT data.
  • To improve the speed and accuracy of colon lumen extraction and analysis.
  • To minimize leakage errors during segmentation.

Main Methods:

  • Anatomical-oriented approach using half-sized volumetric CT data.
  • Utilized global and local histograms of Contrast Enhanced Fluids (CEF) for adaptive thresholding.
  • Generated binary masks and employed a restricted dilation operation for seed generation and region growing.

Main Results:

  • Successfully segmented colonic walls in half-sized CT data efficiently.
  • The method extracted the entire colon lumen, including areas submerged by CEF.
  • Validation demonstrated minimized leakage to extra-colonic regions.

Conclusions:

  • The proposed method offers an efficient and automated solution for colonic wall segmentation.
  • This technique can serve as a preliminary stage for multi-stage colon lumen extraction and analysis.
  • The approach enhances accuracy and reduces processing time for CT-based colon analysis.