Tendency Discrimination Device Using MRI Brain Analysis
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Solution Overview
Problem
Current systems for determining personality and learning tendencies rely heavily on subjective judgment and lack objective correlation with brain morphology and function, particularly in relation to MRI technology.
Innovation Solution
A device and method using MRI-derived anatomical and diffusion weighted images to calculate gray matter volume and diffusion anisotropy for specific brain regions, employing machine learning to generate a discriminator that outputs a tendency index relevant to behavior sustainability, enabling objective discrimination of learning tendencies and adaptive task execution assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If written tests and subjective judgment are used to determine personality and learning tendencies, then the system can operate with simple equipment, but the objectivity and reliability of the discrimination result deteriorates
Solution Approach 1:
The patent replaces subjective human judgment with objective MRI imaging technology and automated image processing systems. The mechanical/technical system (MRI scanner, image processing software) substitutes for the human evaluator's subjective assessment, providing reliable, repeatable, and quantifiable measurements of brain morphology that objectively correlate with personality tendencies.
Solution Approach 2:
The patent introduces brain imaging data as an intermediary between the subject and the tendency discrimination. Instead of directly observing behavior or using self-report questionnaires, the system uses MRI images of brain structure as an intermediate measure that correlates with personality tendencies, providing an objective bridge to psychological characteristics.
2Measurement precision
If MRI technology is used to measure brain morphology and function, then the objectivity and measurement precision of tendency discrimination improves, but the device complexity and cost increases
Solution Approach 1:
The patent segments the brain into specific regions of interest (frontal lobe, temporal lobe, parietal lobe, occipital lobe) and analyzes each region's gray matter volume separately. This segmentation allows precise measurement of localized brain structures without requiring analysis of the entire brain, reducing computational complexity while maintaining measurement precision.
Solution Approach 2:
The patent focuses on measuring gray matter volume in specific local brain regions rather than using whole-brain averages. By concentrating on particular areas (frontal, temporal, parietal, occipital lobes) and their specific structural characteristics, the system achieves high measurement precision for psychologically relevant brain structures.
3Reliability
If diffusion tensor imaging is used to visualize white matter tracts and diffusion anisotropy, then the reliability of brain function assessment improves, but the imaging time and processing complexity increases
Solution Approach 1:
The patent applies partial action by focusing DTI analysis on specific white matter tracts and regions rather than performing complete diffusion imaging of the entire brain. The system selectively measures diffusion anisotropy in areas most relevant to personality assessment, reducing imaging time while maintaining reliable assessment of brain function.
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
Enables objective discrimination of personality and learning tendencies, providing tailored task execution procedures based on brain data, improving learning outcomes by matching instruction methods with individual brain characteristics.
Implementation Method 1
Magnetic resonance imaging (MRI) is an imaging technique of magnetically exciting, by using RF signals at the Larmor frequency, the nuclear spin of a test object located in a static magnetic field, and recomposing an image from MR signals generated by the excitation
Implementation Method 2
The DTI images that the water-molecule diffusion direction is mainly restricted by the axis cylinder and myelin sheath of the nervous system, by using the MRI technology
Data Source
AI summary
A tendency discrimination device includes a discriminator to objectively discriminate a tendency of a person to be tested, based on brain information obtained by magnetic resonance imaging (MRI). In the generation of the discriminator, a gray matter volume and a diffusion anisotropy degree are calculated for a frontal pole of each of multiple test subjects as a region of interest, and machine learning is performed on the relationship of the information obtained by classifying results of a test for discriminating the tendencies of the multiple test subjects, to gray matter volumes and diffusion anisotropy degrees obtained by MRI for each of the multiple test subjects.