Speckle-Illumination Eye Imaging for Pupil-Limited Resolution
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Solution Overview
Problem
Current retinal imaging technologies are limited by the attainable size of the eye's pupil, which constrains the numerical aperture and lateral resolution, making it difficult to image critical retinal structures in vivo.
Innovation Solution
The use of non-uniform illumination patterns, specifically speckle illumination, combined with computational reconstruction algorithms, allows for high-resolution imaging of the ocular fundus by overcoming the limitations of the pupil's numerical aperture, enabling super-resolution imaging and aberration correction without the need for precise calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional uniform illumination is used, then the imaging system is simple to operate, but the lateral resolution is limited by the pupil size
Solution Approach 1:
The illumination is divided into multiple discrete spots arranged in patterns (e.g., hexagonal, square) rather than uniform continuous illumination. This segmentation allows the system to achieve super-resolution by combining information from multiple spot positions, effectively overcoming the diffraction limit imposed by the small pupil size while maintaining a relatively simple optical implementation.
Solution Approach 2:
The illumination pattern is dynamically moved or scanned across the sample plane in a systematic manner. By capturing images at multiple positions and combining them computationally, the system achieves enhanced lateral resolution beyond what is possible with static illumination, resolving the contradiction between resolution and complexity.
2Measurement precision
If the pupil size is increased to improve resolution, then lateral resolution improves, but the depth of field decreases
Solution Approach 1:
The system transitions from relying solely on optical parameters (pupil size) to achieve resolution improvement to incorporating the temporal dimension through multi-position illumination scanning. By moving the illumination pattern across multiple positions and combining the data computationally, the system achieves super-resolution without requiring a large physical aperture, thereby maintaining adequate depth of field.
3Measurement precision
If adaptive optics is used to correct aberrations, then imaging quality improves, but the system complexity and calibration requirements increase
Solution Approach 1:
The system uses the sample itself (or a reference sample) to characterize and correct optical aberrations through the measured intensity variations in the speckle patterns. This self-calibration approach eliminates the need for complex external wavefront sensors and manual alignment procedures, reducing system complexity while maintaining high imaging quality.
Solution Approach 2:
The system implements an iterative feedback loop where the measured intensity patterns are used to update the aberration correction parameters, which are then applied to improve subsequent measurements. This feedback mechanism enables automatic aberration correction without requiring complex manual calibration procedures.
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
This approach achieves up to double the resolution of conventional methods, revealing previously inaccessible retinal details and correcting aberrations, facilitating early diagnosis and therapeutic strategies for severe vision-disabling conditions like AMD and glaucoma.
Implementation Method 1
a light source to generate one or multiple non-uniform illumination patterns on an ocular fundus
Implementation Method 2
a detector array to extract data representative of backscattering from the object
Data Source
AI summary
Systems and methods are provided for imaging and characterizing objects including the eye using non-uniform or speckle illumination patterns. According to the present technology, a method for characterizing at least a portion of an object may include generating, using at least one light source, one or multiple non-uniform illumination patterns on an object. The method may also include detecting, using a detector, backscattered light from the object in response to the generating. The method may further include extracting, using the detector, data representative of the backscattered light. The method may also include processing, using a processing unit, the data representative of the backscattered light to create one or more images of at least a portion of the object.