OCT Image Processing for Eye Tissue Shape Specification
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Solution Overview
Problem
Current ophthalmologic apparatuses face challenges in acquiring tomographic images of the eye with high reproducibility due to misalignment issues during optical coherence tomography (OCT) measurements, which affect the accuracy of refractive power measurement, especially in peripheral visual fields.
Innovation Solution
An ophthalmologic information processing apparatus that analyzes OCT images to specify the true shape of eye tissues by separating high and low sensitivity components, reducing alignment errors and enabling precise calculation of refractive power in peripheral regions using an eyeball model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional OCT measurement is performed without alignment correction, then the measurement process is simple, but the measurement precision deteriorates due to misalignment errors affecting tomographic image quality
Solution Approach 1:
The system performs preliminary alignment correction by acquiring reference tomographic images at multiple positions and calculating a transformation matrix before the actual measurement. This preliminary action eliminates misalignment errors in advance, allowing simple subsequent measurements to achieve high precision without requiring complex real-time alignment mechanisms during the main measurement process.
Solution Approach 2:
The invention introduces a transformation matrix as an intermediary element that bridges the reference images and measurement images. This mathematical intermediary enables automatic alignment correction by transforming measurement images based on the pre-calculated matrix, achieving high measurement precision without requiring complex mechanical alignment systems.
2Measurement precision
If alignment correction using multiple reference frames is implemented, then measurement precision improves, but the processing time and complexity increase
Solution Approach 1:
The system performs the time-consuming alignment correction and transformation matrix calculation as a preliminary action before actual measurements. Although this initial processing takes time, it enables all subsequent measurements to be completed quickly with high precision, reducing the overall time loss for repeated measurements.
Solution Approach 2:
The invention creates a transformed copy of the measurement image using the calculated transformation matrix. This copied and corrected image can be processed and analyzed without requiring repeated alignment operations, saving processing time while maintaining measurement precision.
3Measurement precision
If transformation matrix correction is applied to OCT scan parameters, then the accuracy of peripheral refractive power measurement improves, but the device complexity increases
Solution Approach 1:
The transformation matrix serves as a mathematical intermediary that corrects scan parameters automatically. Instead of requiring complex hardware modifications to the OCT system, the patent uses software-based image transformation to achieve accurate peripheral refractive power measurements, thereby improving precision without significantly increasing device complexity.
Solution Approach 2:
The invention replaces potential mechanical alignment systems with computational image transformation. By using software-based correction of scan parameters through transformation matrices, the system achieves high measurement accuracy without requiring complex mechanical adjustment mechanisms.
Data Source
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AI summary
An ophthalmologic information processing apparatus includes an acquisition unit, a tissue specifying unit, and a specifying unit. The acquisition unit is configured to acquire a tomographic image of a subject's eye formed based on scan data acquired using an optical system for performing optical coherence tomography on the subject's eye. The tissue specifying unit is configured to acquire first shape data representing shape of a tissue of the subject's eye by performing segmentation processing on the tomographic image. The specifying unit is configured to specify a low sensitivity component having a small variation with respect to a change in a position of the optical system with respect to the subject's eye from the first shape data, and to obtain second shape data representing shape of the tissue based on the specified low sensitivity component.