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Retinal Vessel Segmentation Based on B-COSFIRE Filters in Fundus Images.

Wenjing Li1, Yalong Xiao2,3, Hangyu Hu4

  • 1Hunan Province People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, China.

Frontiers in Public Health
|September 26, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient B-COSFIRE filter method for retinal vessel segmentation, improving accuracy and speed for diagnosing conditions like diabetic retinopathy and glaucoma.

Keywords:
COSFIREcomputer-aided diagnosismedical image segmentationpostprocessretinal vessel segmentation

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Ophthalmology

Background:

  • Retinal vessel segmentation is crucial for diagnosing pathologies like diabetic retinopathy and glaucoma.
  • Existing methods face challenges in balancing segmentation performance, time efficiency, and distinguishing thin vessels from noise.

Purpose of the Study:

  • To propose an efficient B-COSFIRE filter-based method for accurate retinal vessel segmentation.
  • To address challenges in segmentation performance, speed, and noise differentiation in fundus images.

Main Methods:

  • Utilized Contrast Limited Adaptive Histogram Equalization (CLAHE) for contrast enhancement.
  • Employed B-COSFIRE filters for vessel detection and morphological filters for noise reduction.
  • Applied binary thresholding and connected domain analysis for final vessel segmentation.

Main Results:

  • Achieved high accuracy (e.g., 0.9604 on DRIVE, 0.9558 on STARE) and specificity (e.g., 0.9847 on DRIVE, 0.9705 on STARE).
  • Demonstrated efficient processing time (approx. 12 seconds per image).
  • Successfully distinguished thin vessels from vessel-like noise.

Conclusions:

  • The proposed B-COSFIRE filter method offers an efficient and accurate solution for retinal vessel segmentation.
  • The method shows significant potential for application in computer-aided diagnosis systems for eye diseases.