Speckle Illumination Imaging for Pupil-Limited Retinal 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 speckle illumination patterns, combined with computational reconstruction algorithms, allows for high-resolution imaging of the ocular fundus by overcoming the NA limitations through trans-pupillary or trans-scleral illumination, and processing backscattered light to generate detailed images.
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 a pattern across the pupil plane, rather than using uniform continuous illumination. This segmentation allows each spot to contribute to high-resolution imaging while collectively covering the full aperture, thereby improving lateral resolution without requiring a larger physical pupil.
Solution Approach 2:
Different regions of the pupil are illuminated with different intensities and positions according to a specific pattern (e.g., annular or multi-spot pattern). This local variation in illumination quality enables optimization of the point spread function and improves lateral resolution at the image plane while maintaining system simplicity.
2Measurement precision
If the pupil size is increased to improve resolution, then the lateral resolution improves, but the eye's anatomical constraints prevent further enlargement
Solution Approach 1:
The solution moves from relying solely on the physical dimension of the pupil area to utilizing the spatial distribution pattern of illumination spots across the pupil plane. By arranging multiple illumination spots in specific patterns (radial, annular, or grid patterns), the system effectively utilizes the two-dimensional pupil area more efficiently, achieving higher resolution than would be possible with a single large aperture or simple uniform illumination.
3Measurement precision
If multiple illumination patterns are used to achieve super-resolution, then the imaging resolution improves, but the acquisition time increases
Solution Approach 1:
Multiple illumination patterns are acquired in a periodic sequence, with each pattern providing complementary information. The patterns are cycled through repeatedly, and computational algorithms combine these periodic acquisitions to reconstruct super-resolution images. This periodic approach allows for efficient data collection while maintaining relatively short acquisition times compared to non-periodic methods.
Solution Approach 2:
The system pre-calculates and stores the expected point spread functions and reconstruction matrices for each illumination pattern before actual imaging. This preliminary preparation allows for rapid processing of the acquired images without requiring complex real-time computations, thereby reducing the overall acquisition time while still achieving super-resolution.
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 enables super-resolution imaging of the ocular fundus, revealing otherwise inaccessible retinal details and characterizing aberrations, facilitating earlier disease diagnosis and therapeutic strategies for vision-preserving treatments.
Implementation Method 1
The use of non-uniform speckle illumination patterns, combined with computational reconstruction algorithms, allows for high-resolution imaging of the ocular fundus by overcoming the NA limitations through trans-pupillary or trans-scleral illumination
Implementation Method 2
detecting, using a detector, backscattered light from the object in response to the generating
Implementation Method 3
detecting, using a detector, backscattered light 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.