Precise Cerebrovascular Segmentation

Document Type

Conference Proceeding

Source of Publication

Proceedings - International Conference on Image Processing, ICIP

Publication Date

10-1-2020

Abstract

© 2020 IEEE. Analyzing cerebrovascular changes using Time-of-Flight Magnetic Resonance Angiography (ToF-MRA) images can detect the presence of serious diseases and track their progress, e.g., hypertension. Such analysis requires accurate segmentation of the vasculature from the surroundings, which motivated us to propose a fully automated cerebral vasculature segmentation approach based on extracting both prior and current appearance features that capture the appearance of macro and micro-vessels. The appearance prior is modeled with a novel translation and rotation invariant Markov-Gibbs Random Field (MGRF) of voxel intensities with pairwise interaction analytically identified from a set of training data sets, while the current appearance is represented with a marginal probability distribution of voxel intensities by using a Linear Combination of Discrete Gaussians (LCDG) whose parameters are estimated by a modified Expectation-Maximization (EM) algorithm. The proposed approach was validated on 190 data sets using three metrics, which revealed high accuracy compared to existing approaches.

ISBN

9781728163956

ISSN

1522-4880

Publisher

IEEE

Volume

2020-October

First Page

394

Last Page

397

Disciplines

Medicine and Health Sciences

Keywords

and MGRF, Brain Vascular System, MRA

Scopus ID

85098646805

Indexed in Scopus

yes

Open Access

no

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