Ophthalmologic Imaging Device With Pupil-Based Face Support Detection
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Solution Overview
Problem
In ophthalmologic devices, improper face support by the chin rest can lead to inaccuracies or failures in acquiring ocular characteristics due to face movement during measurement, such as blurring in fundus photographic images, which existing auto-alignment technologies cannot adequately address.
Innovation Solution
An ophthalmologic device with a face supporting unit that includes a pupil image detecting unit to determine proper face support by repeatedly acquiring anterior ocular segment images from multiple cameras, estimating pupil image presence ranges, and adjusting the face support mechanism if necessary, ensuring accurate and reliable ocular characteristic acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If auto-alignment is performed with high accuracy, then positioning precision is improved, but face support stability is not ensured, leading to measurement failure
Solution Approach 1:
The system performs preliminary face support determination before auto-alignment by detecting pupil images in anterior ocular segment images. This preliminary check ensures the face is properly supported on the chin rest before proceeding to measurement, preventing measurement failure due to face movement.
Solution Approach 2:
The system continuously monitors pupil image position in repeated anterior ocular segment images to determine face support status. This feedback mechanism allows the system to verify whether the face remains stable during measurement and adjust or reinitiate measurement if face movement is detected.
2Productivity
If face support is not properly verified, then measurement speed is maintained, but image quality deteriorates due to blurring and flare
Solution Approach 1:
The system performs preliminary detection of pupil images in anterior ocular segment images to verify face support before initiating fundus photography. This preliminary verification prevents poor image quality caused by face movement during the actual measurement, ensuring only properly supported faces proceed to imaging.
Solution Approach 2:
The system replaces mechanical face support verification methods with optical detection using cameras to capture anterior ocular segment images and analyze pupil position. This substitution provides reliable face support verification without adding mechanical complexity to the measurement system.
3Measurement precision
If multiple cameras are used for repeated imaging, then face support determination accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses the existing anterior ocular segment imaging cameras for dual purposes: both face support determination and routine measurement. This multi-functionality avoids adding separate dedicated cameras for face support verification, reducing overall device complexity while maintaining determination accuracy.
Solution Approach 2:
The system segments the measurement process into distinct phases: face support determination phase using anterior ocular segment images, and measurement phase using fundus images. This segmentation allows specialized processing for each phase, improving accuracy without requiring a single complex integrated system.
Data Source
AI summary
Provided are an ophthalmologic device and a method of controlling the same capable of accurately and reliably acquiring ocular characteristics of a subject eye. The ophthalmologic device includes: a face supporting unit configured to support a face of an examinee; an anterior ocular segment image acquiring unit configured to repeatedly acquire an anterior ocular segment image of the subject eye of the face supported by the face supporting unit; a pupil image detecting unit configured to detect a pupil image of the subject eye for each anterior ocular segment image based on the anterior ocular segment image repeatedly acquired by the anterior ocular segment image acquiring unit; and a determining unit configured to determine whether or not the face is properly supported by the face supporting unit based on a result of detection of the pupil image for each anterior ocular segment image by the pupil image detecting unit.