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A review on MR vascular image processing: skeleton versus nonskeleton approaches: part II
Jasjit S Suri1, Kecheng Liu, Laura Reden
1Philips Medical Systems, Inc., Cleveland, OH 44143, USA.
Summary
This review explores vascular segmentation techniques from magnetic resonance angiography (MRA). It details direct and indirect methods, discussing their algorithms, pros, cons, and clinical relevance for future advancements.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Computer Vision
Background:
- Vascular segmentation from medical images is crucial for diagnosis and treatment planning.
- Magnetic Resonance Angiography (MRA) is a key imaging modality for visualizing vasculature.
- Advances in MRA necessitate sophisticated segmentation algorithms.
Purpose of the Study:
- To provide a comprehensive review of current vascular segmentation techniques applied to MRA data.
- To analyze both direct (non-skeleton) and indirect (skeleton-based) segmentation methods.
- To discuss the clinical implications and future directions in vascular segmentation.
Main Methods:
- Detailed review of eight direct-based vascular segmentation techniques, including mathematical foundations and algorithms.
- Discussion of three indirect-based vascular segmentation techniques, covering their mathematical underpinnings and algorithms.
- Comparative analysis of skeleton versus non-skeleton based segmentation approaches.
Main Results:
- Comprehensive overview of the state-of-the-art in MRA-based vascular segmentation.
- Detailed pros and cons analysis for each presented segmentation technique.
- Identification of current challenges and emerging trends in the field.
Conclusions:
- Vascular segmentation from MRA is a rapidly evolving field with diverse algorithmic approaches.
- Both direct and indirect methods offer unique advantages and face specific challenges.
- Future research should focus on improving accuracy, efficiency, and clinical integration of these techniques.