Clinical Feature Analysis System for Neurodegenerative Disorder Diagnosis
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Solution Overview
Problem
Current methods for detecting and quantifying neurodegenerative disorders like Alzheimer's disease are challenging due to difficulty in early detection and lack of standardization, leading to inconsistent and non-standardized diagnoses, and do not effectively incorporate non-image data for holistic patient assessment.
Innovation Solution
A system and method that access patient image data to identify a region of interest, extract local features, compare them to pre-computed reference data, calculate deviation metrics, and generate visualization maps to standardize diagnosis, incorporating both image and non-image data for a comprehensive approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If statistical deviation methods are used to compare patient data to normal databases, then detection capability is improved, but diagnosis consistency and standardization deteriorate due to subjective expert interpretation
Solution Approach 1:
The patent replaces the mechanical/manual process of expert visual interpretation with an automated computer-based system that performs quantitative comparison between patient data and normal databases, eliminating subjective variability while maintaining detection capability
Solution Approach 2:
The patent transforms qualitative visual assessment into quantitative parameter-based analysis by calculating statistical deviations and presenting them as numerical metrics, enabling objective comparison and standardized diagnosis
2Measurement precision
If comprehensive data analysis is performed to provide holistic patient assessment, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The patent creates a multi-functional system that can analyze various types of medical data (image and non-image) using a unified computational framework, achieving comprehensive assessment while managing complexity through standardized processing methods
Solution Approach 2:
The patent introduces a computer-based intermediary system that processes and integrates multiple data types, serving as a mediator between raw comprehensive data and clinical interpretation, thereby managing complexity while maintaining diagnostic accuracy
Data Source
AI summary
A system and method for analyzing and visualizing a local feature of interest includes access of a clinical image dataset comprising clinical image data acquired from a patient, identification of a region of interest (ROI) from the clinical image dataset, and extraction of at least one local feature corresponding to the ROI. The system and method also include definition of a local feature dataset comprising data representing at least one local feature, access of a pre-computed reference dataset comprising image data representing an expected value of the at least one identified derived characteristic of interest, and comparison of the characteristic dataset to the pre-computed reference dataset. Further, the system and method include calculation of at least one deviation metric from the comparison and output of a visualization of the at least one deviation metric.