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Automatic brain segmentation in Time-of-Flight MRA images
Nils Daniel Forkert1, D Säring, J Fiehler
1Department of Medical Informatics, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. n.forkert@uke.uni-hamburg.de
Methods of Information in Medicine
|August 22, 2009
Summary
This study presents a new method for automatically segmenting brain tissue in 3D Time-of-Flight (TOF) MRA images. The technique improves visualization of cerebral vasculature, aiding in the assessment of stroke risk from vascular malformations.
Area of Science:
- Medical Imaging
- Neuroscience
- Radiology
Background:
- Cerebral vascular malformations pose a stroke risk influenced by individual anatomy.
- 3D Time-of-Flight (TOF) Magnetic Resonance Angiography (MRA) is crucial for assessing vascular anatomy.
- TOF images present challenges in vasculature segmentation and visualization.
Purpose of the Study:
- To develop a robust method for segmenting brain tissue in TOF MRA images.
- To overcome limitations of current TOF image analysis for cerebral vasculature.
- To enhance automatic segmentation and direct volume rendering of the cerebral vascular system.
Main Methods:
- Preprocessing of TOF MRA data.
- Region growing for segmenting low-intensity tissues surrounding the brain.
- Graph-based contour extraction using extracted brain border points.
- Non-linear registration for outlier correction via consistency checks.
Main Results:
- Quantitative validation on 18 clinical datasets achieved a mean Dice coefficient of 0.989.
- Successfully included 99.56% of vessel voxels on average.
- Outperformed three common brain segmentation tools, achieving results within inter-observer variability.
Conclusions:
- The proposed method enables robust and automatic brain tissue segmentation in TOF images.
- Significantly improves automatic segmentation and direct volume rendering of the cerebral vascular system.
- Facilitates better understanding of vascular anatomy for stroke risk assessment.
