Holographic Tomography for Non-Invasive Cell Imaging
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Solution Overview
Problem
Current methods for high-resolution imaging of microscopic biological specimens, such as living cells, face limitations due to the transparent nature of cells and the constraints of optical systems, which hinder non-invasive imaging without damaging the specimens, and existing techniques like holographic microscopy suffer from inferior lateral resolution compared to intensity-based imaging systems.
Innovation Solution
The method involves characterizing and imaging microscopic biological specimens using quantitative multi-dimensional data, particularly 3D or 4D refractive index distributions, through techniques like holographic tomography and digital staining, which allows for the extraction and visualization of refractive index data, enabling improved resolution and non-invasive analysis without markers or sample preparation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If holographic microscopy is used to image living cells, then non-invasive imaging is achieved, but lateral resolution is inferior
Solution Approach 1:
The patent transitions from 2D intensity-based imaging to 3D refractive index distribution imaging by adding the optical path length dimension. This enables quantitative tomographic reconstruction that provides both high resolution and non-invasive imaging of living cells through holographic techniques combined with computational algorithms.
Solution Approach 2:
The patent replaces traditional mechanical staining or fixation methods with optical field-based holographic imaging. By using coherent light and computational algorithms to extract refractive index information, the system achieves non-invasive characterization without physical manipulation or damaging staining procedures.
2Measurement precision
If intensity-based imaging is used, then lateral resolution is improved, but non-invasive imaging of living cells is compromised
Solution Approach 1:
The patent changes the imaging parameter from intensity to refractive index distribution. By measuring the phase and amplitude of the optical field and computing the refractive index map through holographic tomography, the system achieves high resolution without the need for damaging intensity-based staining or fixation methods.
Solution Approach 2:
The patent introduces the refractive index distribution as an intermediary parameter that bridges the gap between resolution and non-invasive imaging. This physical property can be measured through holography without damaging the specimen, while providing sufficient contrast and resolution for detailed analysis of living cells.
3Measurement precision
If conventional microscopy is used, then imaging is achieved, but resolution is limited by diffraction
Solution Approach 1:
The patent performs preliminary computational algorithms during the imaging process itself rather than as post-processing. By incorporating deconvolution and tomographic reconstruction into the holographic imaging workflow, the system achieves super-resolution without requiring complex additional optical components.
Solution Approach 2:
The patent creates a multi-functional imaging system that simultaneously provides high resolution, quantitative measurement, and non-invasive imaging capability. The holographic microscope integrates multiple functions including phase imaging, amplitude imaging, and computational tomography into a single system, reducing overall complexity compared to multiple separate systems.
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 precise characterization and visualization of microscopic objects by generating high-resolution images of biological specimens' refractive index distributions, facilitating advanced analysis and understanding of cellular structures and processes without harming the specimens, improving resolution beyond traditional limits.
Implementation Method 1
holographic microscopy, suffers from inferior lateral resolution compared to intensity based imaging systems
Implementation Method 2
light propagating in the far field
Implementation Method 3
the physical refractive index of the sample is obtained in a three dimensional (3D) distribution
Implementation Method 4
The coherent transfer function (CTF), which is the Fourier transform of the complex valued amplitude point-spread function (APSF)
Implementation Method 5
Deconvolution methods may improve general image quality by deblurring, enhancing optical sectioning capability, or improving resolution
Implementation Method 6
Light enters a microscope objective (MO) within a cone that intercepts the microscope objective's pupil
Implementation Method 7
The spectrum appears multiplied by a complex function called the coherent transfer function (CTF), which is the Fourier transform of the complex valued amplitude point-spread function (APSF)
Implementation Method 8
The autocorrelation of the coherent transfer function is the Fourier transform of the point spread function and is commonly denominated optical transfer function (OTF)
Data Source
AI summary
A microscopic object characterization system comprises a computer system, a microscope with a computing unit connected to the computer system, and an object characterization program executable in the computer system configured to receive refractive index data representing at least a spatial distribution of measured values of refractive index (RI) or values correlated to refractive index of the microscopic object. The object characterization program is operable to execute an algorithm applying a plurality of transformations on the refractive index data. The transformations generate a distribution of two or more parameters used to characterize features of the microscopic object. The computer system further comprises a feedback interface configured for connection to one or more data servers in a network computing system, via a global communications network such as the internet, and configured to receive feedback data from the data servers for processing by the object characterization program to calibrate, refine or enhance a characterization of the features.