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Related Experiment Video

Updated: May 24, 2026

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
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An automatic method for renal cortex segmentation on CT images: evaluation on kidney donors.

Xinjian Chen1, Ronald M Summers, Monique Cho

  • 1Radiology and Imaging Sciences Department, National Institutes of Health Clinical Center, Building 10, Room 1C515, Bethesda, MD 20892-1182, USA.

Academic Radiology
|February 21, 2012
PubMed
Summary

An automated method accurately segments renal cortex on CT scans, reducing analysis time. This technology confirms renal cortex volume increases after kidney donation, improving donor assessment.

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Area of Science:

  • Medical Imaging
  • Nephrology
  • Radiology

Background:

  • Accurate renal cortex segmentation is crucial for assessing kidney health in donors.
  • Manual segmentation is time-consuming and subjective.

Purpose of the Study:

  • To develop and validate an automated method for renal cortex segmentation on contrast-enhanced abdominal CT images.
  • To track renal cortex volume changes post-donation.

Main Methods:

  • A 3D automated segmentation algorithm was developed and validated using a leave-one-out strategy on 37 CT datasets.
  • Comparison with manual segmentation by two experts using linear regression and Bland-Altman analysis.
  • Calculation of true-positive and false-positive volume fractions and cortex volume changes.

Main Results:

  • The automated method showed strong correlation with manual segmentation (Pearson's r > 0.91) and agreeable results via Bland-Altman plots.
  • Mean renal cortex volume increase of 35.1% was observed post-donation (P < .01).
  • Segmentation accuracy: 90.15% true-positive, 0.85% false-positive volume fractions. Time reduced from 20 to 2 minutes.

Conclusions:

  • The automated method is accurate, efficient, and a viable replacement for manual segmentation.
  • Computerized measurement confirms renal cortex volume increases after kidney donation.