20 March 2015 Automated detection of periventricular veins on 7 T brain MRI
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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.
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Hugo J. Kuijf, Hugo J. Kuijf, Willem H. Bouvy, Willem H. Bouvy, Jaco J. M. Zwanenburg, Jaco J. M. Zwanenburg, Max A. Viergever, Max A. Viergever, Geert Jan Biessels, Geert Jan Biessels, Koen L. Vincken, Koen L. Vincken, } "Automated detection of periventricular veins on 7 T brain MRI", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94132T (20 March 2015); doi: 10.1117/12.2080952; https://doi.org/10.1117/12.2080952
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