HybridVel

HybridVel computes blood velocity from space-time vascular images using Sobel filtering and an iterative Radon transform to quantify red blood cell (RBC) streak angles for fMRI and vascular imaging analysis.

Key Features:

• Hybrid Image Filtering: Applies a Sobel filter as a pre-processing step to enhance contrast and reduce noise in images containing red blood cell (RBC) streaks.
• Iterative Radon Transform: Uses iterative application of the Radon transform to convert space-time streak angles into quantitative blood velocity measurements.
• Trade-off Management: Balances measurement precision and processing speed via the iterative approach, achieving approximately an order of magnitude acceleration relative to conventional Radon-based methods while improving precision.
• Robustness Against Artifacts: Mitigates effects of low image contrast, imaging depth limitations, acquisition speed constraints, and movement artifacts encountered in large mammals.
• No A Priori Angle Information Required: Operates without pre-existing angle information and accepts space-time images from line-scan imaging or reconstructed full-frame, time-lapse vasculature images.

Scientific Applications:

• Hemodynamic mapping in fMRI: Quantifies vessel-specific blood velocity to support interpretation of hemodynamic signals associated with neural activity in fMRI studies.
• Cardiovascular research: Measures blood flow dynamics in individual vessels for studies of vascular physiology and pathology.
• Vascular imaging analysis across modalities: Processes space-time line-scan and reconstructed time-lapse vasculature images to enable precise vascular imaging analysis across imaging modalities.

Methodology:

Pre-processes images with a Sobel filter to enhance RBC streaks, constructs space-time images containing RBC streaks, and applies an iterative Radon transform that maps streak angles to velocity without requiring a priori angle information; the iterative scheme improves precision and speeds processing by approximately an order of magnitude and includes measures to mitigate low contrast, imaging depth limitations, acquisition speed constraints, and movement artifacts.