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Automatic segmentation of vessels from angiogram sequences using adaptive feature transformation.

Ying-Che Tsai1, Hsi-Jian Lee2, Michael Yu-Chih Chen3

  • 1Institute of Medical Science, Tzu Chi University, Hualien, Taiwan, ROC.

Computers in Biology and Medicine
|May 13, 2015
PubMed
Summary

This study presents an automated method for segmenting vessels in angiogram sequences. The technique achieves high accuracy in extracting high-contrast images and precise vessel segmentation, aiding medical image analysis.

Keywords:
Feature transformationMultiscale Hessian-basedVessel segmentationX-ray angiograms

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Computational Biology

Background:

  • Accurate vessel segmentation from angiogram sequences is crucial for diagnosing and monitoring cardiovascular diseases.
  • Traditional methods often struggle with low contrast and non-uniform intensity distributions in X-ray angiograms.

Purpose of the Study:

  • To develop an efficient and automated method for segmenting vessels from angiogram sequences.
  • To improve the accuracy and robustness of vessel segmentation in challenging angiographic images.

Main Methods:

  • Automatic extraction of high-contrast angiograms based on vessel intensity distribution.
  • Application of multiscale Hessian-based filtering with an adaptive feature transformation function to enhance vesselness.
  • Utilizing connected component labeling for final vessel extraction, addressing complex backgrounds.

Main Results:

  • Achieved 98% accuracy in automatically selecting high-contrast angiograms.
  • Demonstrated 96.3% accuracy and a Kappa value of 81.8% for vessel segmentation.
  • Experimental results validated by a cardiologist, confirming accurate and automatic vessel segmentation.

Conclusions:

  • The proposed method effectively overcomes challenges in X-ray angiograms, including low contrast and non-uniform intensity.
  • The automated approach provides accurate vessel segmentation, suitable for clinical applications.
  • This technique offers a reliable tool for quantitative analysis of vascular structures.