Curvature integration in a 5D kernel for extracting vessel connections in retinal images

S. Abbasi-Sureshjani, M. Favali, G. Citti, A. Sarti, B.M. ter Haar Romeny

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)
138 Downloads (Pure)

Abstract

Tree-like structures such as retinal images are widely studied in computer-aided diagnosis systems for large-scale screening programs. Despite several segmentation and tracking methods proposed in the literature, there still exist several limitations specifically when two or more curvilinear structures cross or bifurcate, or in the presence of interrupted lines or highly curved blood vessels. In this paper, we propose a novel approach based on multi-orientation scores augmented with a contextual affinity matrix, which both are inspired by the geometry of the primary visual cortex (V1) and their contextual connections. The connectivity is described with a five-dimensional kernel obtained as the fundamental solution of the Fokker-Planck equation modelling the cortical connectivity in the lifted space of positions, orientations, curvatures and intensity. It is further used in a self-tuning spectral clustering step to identify the main perceptual units in the stimuli. The proposed method has been validated on several easy and challenging structures in a set of artificial images and actual retinal patches. Supported by quantitative and qualitative results, the method is capable of overcoming the limitations of current state-of-the-art techniques.
Original languageEnglish
Article number8063447
Pages (from-to)606-621
Number of pages16
JournalIEEE Transactions on Image Processing
Volume27
Issue number2
DOIs
Publication statusPublished - Feb 2018

Keywords

  • Retina
  • Junctions
  • Biomedical imaging
  • Blood vessels
  • Mathematical model
  • Visualization
  • Brain modeling
  • Primary visual cortex
  • Contextual affinity matrix
  • Perceptual grouping
  • Retinal image analysis
  • Spectral clustering
  • Curvature
  • Humans
  • Retinal Vessels/diagnostic imaging
  • Algorithms
  • Image Processing, Computer-Assisted/methods
  • Phantoms, Imaging
  • Retina/diagnostic imaging
  • Cluster Analysis

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