AI Ophthalmic Robot for Comprehensive Eye Disease Screening
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Solution Overview
Problem
Current artificial intelligence eye disease screening systems are limited in their ability to intelligently screen for diseases of the whole eye, from the ocular anterior segment to the ocular posterior segment, and require professional personnel to operate, making them inefficient and inaccessible in regions lacking ophthalmologists.
Innovation Solution
An artificial intelligence eye disease screening and diagnostic system based on an ophthalmic robot, utilizing a deep learning algorithm like DenseNet121, which enables the robot to perform comprehensive eye disease screening and diagnosis, automatically focus on different parts of the eye, perform optometry, and detect corneal curvature without professional operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an artificial intelligence eye disease screening system is developed to screen for fundus lesions or ocular surface diseases, then the diagnostic capability for specific eye regions is improved, but the system cannot screen for diseases of the whole eye from the ocular anterior segment to the ocular posterior segment
Solution Approach 1:
The patent integrates multiple imaging modules (anterior segment imaging module and fundus imaging module) into a single automated ophthalmic imaging system that can perform comprehensive screening of the entire eye, including the ocular anterior segment, ocular surface, and ocular posterior segment, making the system universal for all eye region diagnostics
2Measurement precision
If an artificial intelligence eye disease screening system is developed, then the diagnostic capability is improved, but the device still requires professional personnel to operate
Solution Approach 1:
The system incorporates automated eye positioning analysis, automatic focus adjustment, and intelligent image quality monitoring that enable the device to perform comprehensive eye screening without requiring professional ophthalmologist operation, making it accessible for use by non-specialist personnel in regions lacking ophthalmologists
3Measurement precision
If manual examination by an ophthalmologist using a slit lamp or an ophthalmoscope is used, then the diagnostic accuracy is maintained, but the screening process is time-consuming and inefficient
Solution Approach 1:
The patent replaces the manual mechanical examination process with an automated robotic system that uses deep learning algorithms (DenseNet121) for image analysis, enabling the system to automatically capture, analyze, and diagnose eye diseases across all segments, thereby maintaining diagnostic accuracy comparable to ophthalmologists while dramatically improving screening efficiency and productivity
Data Source
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AI summary
An artificial intelligence eye disease screening and diagnostic system based on an ophthalmic robot, comprising a human eye positioning analysis module, an image information collection module, an AI picture quality monitoring module, an eye disease analysis and diagnosis module, a data storage management module, and an execution control module. The system can replace ophthalmologists to perform eye disease diagnosis tasks in regions lacking ophthalmologists, and assists the ophthalmologists in eye disease screening and diagnosis in large hospitals with a large number of patients, thus improving diagnosis efficiency.