Automated detection of periventricular veins on 7 T brain MRI

Hugo J. Kuijf*, Willem H. Bouvy, Jaco J M Zwanenburg, Max A. Viergever, Geert Jan Biessels, Koen L. Vincken

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Cerebral small vessel disease is common in elderly persons and a leading cause of cognitive decline, dementia, and acute stroke. With the introduction of ultra-high field strength 7.0T MRI, it is possible to visualize small vessels in the brain. In this work, a proof-of-principle study is conducted to assess the feasibility of automatically detecting periventricular veins. Periventricular veins are organized in a fan-pattern and drain venous blood from the brain towards the caudate vein of Schlesinger, which is situated along the lateral ventricles. Just outside this vein, a region-of-interest (ROI) through which all periventricular veins must cross is defined. Within this ROI, a combination of the vesselness filter, tubular tracking, and hysteresis thresholding is applied to locate periventricular veins. All detected locations were evaluated by an expert human observer. The results showed a positive predictive value of 88% and a sensitivity of 95% for detecting periventricular veins. The proposed method shows good results in detecting periventricular veins in the brain on 7.0T MR images. Compared to previous works, that only use a 1D or 2D ROI and limited image processing, our work presents a more comprehensive definition of the ROI, advanced image processing techniques to detect periventricular veins, and a quantitative analysis of the performance. The results of this proof-of-principle study are promising and will be used to assess periventricular veins on 7.0T brain MRI.

Original languageEnglish
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
PublisherSPIE
Volume9413
ISBN (Print)9781628415032
DOIs
Publication statusPublished - 2015
EventMedical Imaging 2015: Image Processing - Orlando, United States
Duration: 24 Feb 201526 Feb 2015

Conference

ConferenceMedical Imaging 2015: Image Processing
Country/TerritoryUnited States
CityOrlando
Period24/02/1526/02/15

Keywords

  • quantitative image analysis
  • segmentation methodologies

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