Motion-Compensated MR Image Reconstruction via Segmented Signal Analysis
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Solution Overview
Problem
Current MR imaging techniques face challenges in effectively compensating for motion artifacts, leading to incomplete data utilization and reduced image quality, especially in dynamic contrast enhancement scans, due to difficulties in attributing MR signal data to correct motion states and varying signal-to-noise ratios across different motion bins.
Innovation Solution
The method subdivides the signal acquisition period into short time segments where negligible motion occurs, applying geometric transformations to align and reconstruct MR images across all motion states, allowing for high-quality image reconstruction regardless of motion type or characteristics, and using iterative reconstruction techniques with parallel imaging to refine images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motion compensation is applied using traditional gating or binning techniques, then motion artifacts are reduced, but scan efficiency decreases and patient cooperation is required
Solution Approach 1:
The patent segments the acquired MR signal data into multiple data portions, each associated with a different time segment. This segmentation allows independent processing and motion correction of each data portion, enabling full utilization of acquired data without requiring discarding of out-of-window data, thereby maintaining scan efficiency while reducing motion artifacts
Solution Approach 2:
The patent employs feedback mechanisms where geometric transformations derived from one data portion are applied to correct other data portions. The motion correction process uses information from all acquired data to iteratively refine the correction, creating a self-improving system that maintains high scan efficiency while effectively compensating for motion
2Reliability
If motion binning is used to attribute signal data to motion states, then motion compensation is achieved, but image quality varies due to varying signal-to-noise ratios across bins
Solution Approach 1:
The patent merges information from all data portions across all time segments through iterative reconstruction. Instead of treating motion bins independently with varying signal-to-noise ratios, the method combines all acquired signal data and applies global motion corrections that leverage information from the entire dataset, ensuring consistent image quality across all motion states
Solution Approach 2:
The patent changes the approach from fixed motion binning to dynamic geometric transformations. By deriving and applying geometric transformations that account for actual motion between time segments, the method adapts to varying motion conditions while maintaining consistent image quality, rather than being constrained by fixed bin boundaries with heterogeneous signal-to-noise characteristics
3Measurement precision
If full signal data is utilized for reconstruction, then image quality improves, but motion artifacts increase without proper compensation
Solution Approach 1:
The patent applies preliminary motion correction by deriving geometric transformations between consecutive time segments before performing the final image reconstruction. This preliminary action of correcting for motion in the data portions before combining them allows full utilization of acquired signal data for improved image quality while preventing motion artifacts from degrading the reconstruction
Solution Approach 2:
The patent replaces traditional mechanical gating mechanisms with computational motion correction using geometric transformations. Instead of physically or temporally gating data to exclude motion-affected portions, the method uses mathematical transformations to correct for motion effects, allowing all acquired data to contribute to the final image with motion artifacts eliminated through computation rather than mechanical selection
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the reconstruction of high-resolution, diagnostic-quality MR images that utilize the full acquired signal data, effectively compensating for motion and maintaining image quality across all time segments and motion states, improving scan efficiency and image fidelity.
Implementation Method 1
the body of the patient to be examined is arranged in a strong, uniform magnetic field B0
Implementation Method 2
The magnetic field B0 produces different energy levels for the individual nuclear spins in dependence on the magnetic field strength which can be excited (spin resonance) by application of an electromagnetic alternating field (RF field) of defined frequency (so-called Larmor frequency, or MR frequency)
Implementation Method 3
the magnetization performs a precessional motion about the z-axis. The precessional motion describes a surface of a cone whose angle of aperture is referred to as flip angle
Implementation Method 4
The transverse magnetization and its variation can be detected by means of receiving RF coils which are arranged and oriented within an examination volume of the MR device in such a manner that the variation of the magnetization is measured in the direction perpendicular to the z-axis
Implementation Method 5
In order to realize spatial resolution in the body, time-varying magnetic field gradients extending along the three main axes are superposed on the uniform magnetic field B0, leading to a linear spatial dependency of the spin resonance frequency
Data Source
AI summary
The invention relates to a method of MR imaging of an object (10). It is an object of the invention to enable MR imaging in the presence of motion of the imaged object, wherein full use is made of the acquired MR signal and a high-quality MR image essentially free from motion artefacts is obtained. The method of the invention comprises the steps of: generating MR signals by subjecting the object (10) to an imaging sequence comprising RF pulses and switched magnetic field gradients; acquiring the MR signals as signal data over a given period of time (T); subdividing the period of time into a number of successive time segments (SO, S1, S2, . . . Sn); deriving a geometric transformation (DVF1, DVF2, . . . DVFn) in image space for each pair of consecutive time segments (S0, S1, S2, . . . Sn), which geometric transformation (DVF1, DVF2, . . . DVFn) reflects motion occurring between the two time segments of the respective pair; and reconstructing an MR image from the signal data, wherein a motion compensation is applied according to the derived geometric transformations (DVF1, DVF2, . . . DVFn). Moreover, the invention relates to an MR device (1) and to a computer program for an MR device (1).