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This project is for the evaluation of brain vessels from TOF MRA data using a quantitative method, telling possible effects of aging on brain vessels. Two possible perspectives are extracting features from topology of vessels and voxel intensity of the vessel area in the image.
Two approaches for evaluation
From the topology perspective, vessel areas need to be segmented first, then convert the vessel areas to tree-like structures. After that, several features can be calculated, such as total voxel of vessels in the brain, length of branches, number of end points in tree, proportion of main branch and small end branch, etc. The richness and intricacy of vessels are essential in evaluating brain health.
From the image intensity perspective, gray scale of each voxel in TOF is somehow related to flow speed of blood according to the imaging principle. Absolute value of voxels in image need to be normalized to be useful in further analysis. The normalized data is then used in telling relative speed of blood flow compared among patients. Speed value is another important index to reflect health of brain vessels.
Vessel aging may appear in different regions of brain on different scales. Brain regions need to be divided to have a better understanding of which part of brain vessel is more likely to change during aging. A method based on determining "Order" is used to separate vessels into four groups.
A total of 162 TOF MRA image sets with patients ranged from 57 to 85 years old are acquired. Use statistical method to identify the underlying regulations of features in each part of brain through aging.
Detailed key points:
1. Acquire sets of 3D TOF MRA data.
2. Segment vessel in 3D TOF MRA data.
Validate through rotated MIP images
3. Find a quantitative method to evaluate vessels in each region of the brain.
4. Find a normalized method to evaluate blood flow speed in TOF MRI image.
Two reference points normalization
6. Analyze features to make assumption on possible effect of vessel aging.