Lensless Imaging via Sample Translation and Computational Reconstruction
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Solution Overview
Problem
Conventional microscopy systems face challenges in achieving high spatial resolution and a wide field of view simultaneously, often requiring bulky and expensive optical lenses, which limits their applicability and cost-effectiveness.
Innovation Solution
The development of lensless imaging systems that utilize translated speckle illumination, pattern modulation, phase modulation, and wavelength-encoded mask modulation to achieve super-resolution imaging without the need for optical lenses, allowing for compact, portable, and cost-effective setups that can process multiple images to recover complex sample profiles based on positional shifts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional microscope systems use high numerical aperture lenses to achieve high spatial resolution, then resolution is improved, but the system becomes bulky and expensive
Solution Approach 1:
The patent removes the objective lens and tube lens from the conventional microscope system, extracting the imaging function to a computational algorithm that processes intensity measurements to recover complex profiles. This eliminates the bulky optical components while achieving super-resolution through translation-based diffraction modulation.
Solution Approach 2:
The patent replaces the mechanical/optical lens system with a computational approach. Instead of using physical lenses to focus light, the system uses a translation mechanism to modulate diffraction patterns and employs algorithms to reconstruct complex profiles from intensity measurements, substituting mechanical optics with computational imaging.
2Measurement precision
If conventional microscope systems use high numerical aperture lenses to achieve high spatial resolution, then resolution is improved, but the field of view is limited
Solution Approach 1:
The patent introduces dynamic translation of the sample or mask to modulate the diffraction pattern. By translating the sample through a range of positions, the system captures multiple intensity measurements that encode different spatial frequency information, enabling super-resolution reconstruction with an extended field of view that is not limited by lens numerical aperture.
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
These systems achieve high spatial resolution and large field of view, surpassing diffraction-limited resolutions, and are suitable for applications in digital pathology and other imaging modalities, providing quantitative absorption and phase contrast, while being compact and cost-effective, making them suitable for point-of-care settings.
Implementation Method 1
an imaging system includes a sample mount for holding a sample to be imaged, a light source configured to emit a light beam to be incident on the sample
Implementation Method 2
a translation mechanism coupled to the sample mount and configured to scan the sample to a plurality of sample positions in a plane substantially perpendicular to an optical axis of the imaging system
Implementation Method 3
a mask positioned downstream from the sample along the optical axis
Implementation Method 4
an image sensor positioned downstream from the mask along the optical axis. The image sensor is configured to acquire a plurality of images as the sample is translated to the plurality of sample positions
Implementation Method 5
a processor configured to process the plurality of images to recover a complex profile of the sample based on positional shifts extracted from the plurality of images
Data Source
AI summary
An imaging system includes a sample mount for holding a sample to be imaged, a light source configured to emit a light beam to be incident on the sample, a translation mechanism coupled to the sample mount and configured to scan the sample to a plurality of sample positions in a plane substantially perpendicular to an optical axis of the imaging system, a mask positioned downstream from the sample along the optical axis, and an image sensor positioned downstream from the mask along the optical axis. The image sensor is configured to acquire a plurality of images as the sample is translated to the plurality of sample positions. Each respective image corresponds to a respective sample position. The imaging system further includes a processor configured to process the plurality of images to recover a complex profile of the sample based on positional shifts extracted from the plurality of images.