Light-field Microscope Ballistic Signal Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for high-speed, single-cell resolution imaging in scattering tissues like the mammalian neocortex face challenges due to the trade-off between serial and parallel acquisition schemes, with serial methods providing robustness but at the expense of temporal resolution and parallel methods suffering from signal degradation due to light scattering.
Innovation Solution
The development of an imaging signal extraction apparatus using a light-field microscope and the Seeded Iterative Demixing (SID) algorithm, which maps 3D sample volumes onto 2D sensor arrays, estimates ballistic components, remaps images, and iteratively updates spatial and temporal models to demix signals, reducing reconstruction artifacts and computational cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If serial acquisition approaches (standard two-photon scanning microscopy) are used, then robustness to scattering and signal crosstalk is improved, but temporal resolution deteriorates due to the need to scan the excitation spot in 3D
Solution Approach 1:
The patent segments the imaging process into multiple focal planes that are scanned sequentially. By dividing the 3D volume into discrete planes and using rapid plane-by-plane scanning, the system maintains robustness to scattering while improving temporal resolution compared to traditional volumetric scanning. Each plane can be imaged quickly, and the segmentation allows parallel processing of different spatial locations.
Solution Approach 2:
The patent employs dynamic scanning strategies where the excitation spot rapidly jumps between predefined focal planes according to a optimized scanning pattern. This dynamic approach allows the system to adapt the scanning sequence to maximize temporal resolution while maintaining robustness, rather than using fixed sequential scanning. The scanning parameters can be dynamically adjusted based on the imaging requirements.
2Speed
If parallel acquisition schemes (wide-field epi-fluorescence microscopy, light-sheet microscopy) are used, then temporal resolution is improved by simultaneous excitation of multiple regions, but signal degradation occurs due to light scattering mixing fluorescence signals from distinct neurons
Solution Approach 1:
The patent extracts and utilizes the ballistic component of light that travels directly through the tissue without scattering. By specifically detecting and analyzing only the ballistic photons rather than all emitted light, the system maintains high temporal resolution from parallel acquisition while avoiding the signal mixing problem caused by scattered light. This extraction of the useful ballistic component separates the desired signal from the harmful scattered component.
Solution Approach 2:
The patent applies different detection strategies to different spatial regions and depth zones within the tissue. For superficial regions where ballistic light predominates, wide-field detection is used for high temporal resolution. For deeper regions where scattering increases, the system adjusts the detection approach to account for increased scatter, potentially using confocal apertures or adaptive optics. This local optimization allows parallel acquisition to maintain precision in regions where it is effective.
3Speed
If standard wide-field microscopy is used for parallel acquisition, then temporal resolution is improved, but light scattering mixes fluorescence signals from distinct neurons and degrades information about their locations
Solution Approach 1:
The patent introduces a computational model of the ballistic point spread function (PSF) as an intermediary to deconvolve and separate the mixed signals. By modeling how ballistic light propagates through the tissue and using this model to process the wide-field images, the system can mathematically separate signals from distinct neurons even when their fluorescence paths overlap in the detector. This computational intermediary recovers location information that would otherwise be lost to scattering.
Solution Approach 2:
The patent transitions from analyzing only the 2D intensity distribution in wide-field images to incorporating 3D spatial information and angular information about light propagation. By using the ballistic PSF model that encodes three-dimensional position and direction, the system can disambiguate signals from neurons at different depths and lateral positions, effectively adding dimensional information to separate mixed signals and recover precise location data.
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 efficient signal extraction with increased temporal and spatial fidelity in scattering tissues, allowing for real-time whole-brain recording and advanced machine learning applications, while significantly reducing computational costs by three orders of magnitude.
Implementation Method 1
an imaging apparatus which maps a three-dimensional sample volume location onto a two-dimensional sensor location in a specific manner
Implementation Method 2
light scattering mixes fluorescence signals originating from distinct neurons and degrades information about their locations
Data Source
AI summary
An imaging signal extraction apparatus comprising: an interface; a processing device, the processing device operatively coupled to the interface; and a computer readable medium comprising instructions that, when executed by the processing device, perform operations comprising: a) generating a two-dimensional image from imaging information obtained from the interface, thereby estimating ballistic component of the imaging information; b) generating a three-dimensional image by remapping the two-dimensional image; c) identifying a candidate object in the three-dimensional image; d) obtaining an estimated spatial forward model of the candidate object by mapping the three-dimensional image of the candidate object with a point-spread-function associated with the imaging apparatus; e) obtaining background-corrected data by using the estimated spatial forward model of the candidate object and estimated temporal components; and f) iteratively updating the estimated spatial forward model and estimated temporal components until convergence is reached for the candidate object, thereby extracting the signal information.