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Related Experiment Video

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Scale-space for empty catheter segmentation in PCI fluoroscopic images.

Ketan Bacchuwar1,2, Jean Cousty3, Régis Vaillant4

  • 1GE-Healthcare, 78530, Buc, France. ketan.bacchuwar@esiee.fr.

International Journal of Computer Assisted Radiology and Surgery
|May 24, 2017
PubMed
Summary

We developed a novel method using structural scale-space to automatically segment empty guiding catheters in X-ray fluoroscopy images. This technique improves Percutaneous Coronary Intervention (PCI) procedure modeling by accurately identifying catheter positions.

Keywords:
Guiding catheterMathematical morphologyModeling interventional processesPercutaneous coronary interventionSegmentation

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Interventional Cardiology

Background:

  • Guiding catheter segmentation is crucial for Percutaneous Coronary Intervention (PCI) procedure modeling.
  • Empty guiding catheters present challenges due to low contrast and disconnected edges in fluoroscopic images.

Purpose of the Study:

  • To present a novel method for segmenting empty guiding catheters in X-ray fluoroscopic images.
  • To facilitate accurate PCI procedure modeling through reliable catheter segmentation.

Main Methods:

  • Utilized level-set scale-space and min-tree to extract curve blobs.
  • Developed a novel structural scale-space hierarchy based on curve blobs.
  • Identified the deep connected component maximizing empty catheter likelihood for segmentation.

Main Results:

  • Evaluated on 1250 fluoroscopic images from 6 patients.
  • Achieved mean precision of 80.48% and recall of 63.04%.
  • Demonstrated very good qualitative and quantitative segmentation performance.

Conclusions:

  • A novel structural scale-space effectively segments sparse empty catheters in X-ray images.
  • Fully-automatic segmentation is a vital preliminary step for PCI modeling.
  • Aids in tracking interventional tools during PCI procedures.