Isotropic MRI Imaging via Multi-Plane Data Fusion
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Solution Overview
Problem
Current 3D MRI scanning techniques suffer from low resolution in one dimension, leading to limitations in 3D image analysis and visualization, increased partial volume effects, and missed boundaries due to scanning resolution and orientation issues.
Innovation Solution
The method involves performing multiple MRI scans in different planes and merging them to create an isotropic or near-isotropic data volume, where gray values are interpolated to achieve higher resolution in all three dimensions, reducing partial volume effects and improving tissue segmentation and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional 3D MRI scanning techniques are used, then the imaging speed and coverage are improved, but the resolution in one dimension deteriorates leading to partial volume effects and missed boundaries
Solution Approach 1:
The patent acquires MRI data in multiple orientations (e.g., axial, coronal, sagittal planes) and combines them to create an isotropic 3D volume. This multi-dimensional approach ensures high resolution in all three spatial dimensions by leveraging the strength of each orientation, eliminating the need to compromise resolution in any single dimension for the sake of imaging speed.
2Area of stationary object
If conventional 3D MRI scanning techniques are used, then the imaging coverage is improved, but the manufacturing precision of isotropic image data deteriorates
Solution Approach 1:
The patent merges multiple 2D MRI scans taken in different planes and orientations to construct a single isotropic 3D volume. By combining data from multiple acquisitions with different coverage areas and orientations, the method achieves both comprehensive imaging coverage and uniform isotropic resolution throughout the entire volume, avoiding the trade-off between coverage and precision.
3Productivity
If conventional 3D MRI scanning techniques are used, then the scanning efficiency is improved, but the detection precision of boundaries and structures deteriorates
Solution Approach 1:
By acquiring and combining data from multiple orientations, the patent creates isotropic voxels that provide equal resolution in all directions. This enables accurate boundary detection and structural measurement in any plane through the 3D volume, eliminating the directional resolution limitations of conventional anisotropic scanning while maintaining scanning efficiency.
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 enhances the accuracy of 3D image analysis and tissue segmentation by providing high-resolution images in all directions, reducing partial volume effects and improving the detection of boundaries, thereby facilitating more precise diagnostic and treatment strategies.
Implementation Method 1
Via radio frequency (RF) magnetic field (B1) excitation and manipulations, selected magnetic dipoles in the subject that are otherwise aligned with the main magnetic field are tipped to excite magnetic resonance. The resonance is typically manipulated to induce detectable magnetic resonance echoes from a selected region of the subject.
Implementation Method 2
In imaging, the echoes are spatially encoded via magnetic gradients set up in the main magnetic field.
Data Source
AI summary
In accordance with the present invention there is provided methods for generating an isotropic or near-isotropic three-dimensional images from two-dimensional images. In accordance with the present invention the method includes, obtaining a first image of a body part in a first plane, wherein the first image generates a first image data volume; obtaining a second image of the body part in a second plane, wherein the second image generates a second image data volume; and combining the first and second image data volumes to form a resultant image data volume, wherein the resultant image data volume is isotropic or near-isotropic.