Optical Flow Calculation for DSA Vascular Fluid Motion Quantification
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Solution Overview
Problem
Current methods for quantifying vascular fluid motions, such as CT perfusion, MR perfusion, and Doppler ultrasound, face limitations like high radiation exposure, long image acquisition times, and poor spatial-temporal resolution, particularly in fast-changing flow situations, while Digital Subtraction Angiography (DSA) lacks robustness in computation cost and accuracy.
Innovation Solution
A method combining a temporally extended variant of the Horn-Schunck approach with the Lucas-Kanade approach non-linearly in a spatiotemporal multiresolution scheme to calculate optical flow fields between DSA images, using a CLG energy function that incorporates Gaussian smoothing and successive over-relaxation for accurate displacement estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT perfusion or MR perfusion is used to measure arteriovenous flow, then measurement accuracy is improved, but image acquisition time increases significantly
Solution Approach 1:
The patent extracts the essential flow information from DSA images by applying optical flow algorithms that compute displacement vectors between consecutive frames. This extracts velocity and flow quantification data without requiring the lengthy acquisition times of CT or MR perfusion, resolving the contradiction between measurement accuracy and acquisition time
Solution Approach 2:
The patent replaces the mechanical/physical imaging systems (CT scanners, MR scanners) with a computational approach using optical flow algorithms. This substitution maintains flow measurement capability while dramatically reducing acquisition time by using existing DSA temporal sequences rather than dedicated perfusion imaging protocols
2Loss of time
If Doppler ultrasound is used for vessel flow quantification, then acquisition time is reduced, but spatial resolution deteriorates due to skull attenuation
Solution Approach 1:
The patent introduces optical flow computation as an intermediary processing step that operates on DSA images. This intermediary approach bypasses the skull attenuation problem of Doppler ultrasound by using X-ray based DSA images that can penetrate the skull, while still achieving rapid flow quantification through efficient optical flow algorithms
3Object-affected harmful factors
If PC-MRI is used for flow quantification, then radiation exposure is reduced, but spatial-temporal resolution is insufficient for fast-changing flows
Solution Approach 1:
The patent changes the temporal sampling parameters by utilizing the high temporal resolution inherent in DSA imaging sequences. By applying optical flow algorithms to these high-frame-rate DSA sequences, the method achieves superior spatial-temporal resolution for capturing fast-changing vascular flows while avoiding radiation concerns through post-processing of already-acquired images
4Measurement precision
If conventional DSA with gray scale analysis is used, then spatial resolution is maintained, but computational robustness and accuracy for flow quantification are insufficient
Solution Approach 1:
The patent creates a composite approach by combining conventional DSA imaging with optical flow computation. This composite method maintains the high spatial resolution of DSA while adding computational robustness through the optical flow framework that handles intensity variations, noise, and complex flow patterns more reliably than simple gray scale analysis
5Measurement precision
If Horn-Schunck or Lucas-Kanade optical flow methods are used, then flow quantification capability is improved, but computation cost increases due to large displacement errors
Solution Approach 1:
The patent segments the computation into multiple resolution levels using a pyramid approach. By processing images at progressively finer resolutions, the method reduces computational cost at coarse levels while maintaining accuracy at fine levels, effectively dividing the computational burden to avoid the high cost of full-resolution processing
Solution Approach 2:
The patent adds the resolution level dimension to the computation by implementing a multiresolution pyramid scheme. This dimensional extension allows the algorithm to work efficiently at lower resolutions and progressively refine results, reducing overall computation cost while maintaining the flow quantification capability of optical flow methods
Data Source
AI summary
Disclosed is a method and an apparatus for quantifying vascular fluid motions from digital subtraction angiography (DSA) images, comprising: calculating an optical flow field between two temporal consecutive DSA images; and estimating a displacement of blood or tissue between the two temporal consecutive DSA images from the calculated optical flow field, wherein the optical flow field is calculated by solving a minimization problem of a CLG energy function, wherein the CLG energy function combines the temporally extended variant of Horn-Schunck approach with Lucas-Kanade approach non-linearly in spatiotemporal approach. The present disclosure provides a new optical flow solution significantly reducing the computation cost with a high robustness for quantifying vascular fluid motions from DSA.