Segmentation method for cerebral blood vessels from MRA using hysteresis

Georgia Kenyon, Stephan Lau, Michael A. Chappell, Mark Jenkinson
3/9/2023
eess.IVcs.CVcs.LG

No official code found. Best implementation: georgiakenyon/Segmentation-method-for-cerebral-blood-vessels-from-MRA-using-hysteresis (5 stars, last commit 2024-12-02).

Abstract

Segmentation of cerebral blood vessels from Magnetic Resonance Imaging (MRI) is an open problem that could be solved with deep learning (DL). However, annotated data for training is often scarce. Due to the absence of open-source tools, we aim to develop a classical segmentation method that generates vessel ground truth from Magnetic Resonance Angiography for DL training of segmentation across a variety of modalities. The method combines size-specific Hessian filters, hysteresis thresholding and connected component correction. The optimal choice of processing steps was evaluated with a blinded scoring by a clinician using 24 3D images. The results show that all method steps are necessary to produce the highest (14.2/15) vessel segmentation quality score. Omitting the connected component correction caused the largest quality loss. The method, which is available on GitHub, can be used to train DL models for vessel segmentation.

View on arXivView PDF

Code Implementations(1)

georgiakenyon/Segmentation-method-for-cerebral-blood-vessels-from-MRA-using-hysteresisCommunity100%

Segmentation method for cerebral blood vessels from MRA using hysteresis

50PythonFeb 7, 20231 years ago

Similar Papers

Simulation-Based Segmentation of Blood Vessels in Cerebral 3D OCTA Images

87% match2024

SMILE-UHURA Challenge -- Small Vessel Segmentation at Mesoscopic Scale from Ultra-High Resolution 7T Magnetic Resonance Angiograms

86% match2024

Robust automatic brain vessel segmentation in 3D CTA scans using dynamic 4D-CTA data

85% match1 repo72026

A label-free and data-free training strategy for vasculature segmentation in serial sectioning OCT data

85% match2024

SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using Maximum Intensity Projection as Loss

85% match1 repo22024

Multi-Domain Brain Vessel Segmentation Through Feature Disentanglement

84% match1 repo112025

Cite this paper

@article{kenyon2023segmentation,
  title  = {Segmentation method for cerebral blood vessels from MRA using hysteresis},
  author = {Georgia Kenyon and Stephan Lau and Michael A. Chappell and Mark Jenkinson},
  year   = {2023},
  eprint = {2303.05113},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.05113v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2303.05113.svg)](https://codeofpaper.com/paper/2303.05113)

Discussion