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Light field microscopic three-dimensional reconstruction method and device based on deep learning algorithm

A technology of light field microscopy and deep learning, applied in the fields of computational photography, computational optics, computer vision and computer graphics, can solve problems such as difficult measurement, reconstruction speed limit, reconstruction algorithm to be improved, etc., to achieve less artifacts , high-resolution effects

Active Publication Date: 2021-06-11
TSINGHUA UNIV
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Problems solved by technology

[0003] Although light field microscopy technology has the ability to quickly obtain three-dimensional information of samples, there are some inherent problems in its commonly used reconstruction algorithm - three-dimensional deconvolution algorithm, which seriously limits the expansion of the application range of light field microscopy.
First, in order to achieve accurate results, the fitting method needs to have a more accurate estimate of the point spread function, but this is difficult to measure in experiments
Second, the 3D deconvolution algorithm based on maximum likelihood estimation often requires a large number of iterative steps to achieve a better convergence effect, which limits the reconstruction speed
Third, due to the physical limitation of the resolution at the focal plane, traditional methods cannot effectively solve this problem
In addition, due to the ill-conditioned nature of the problem, 3D deconvolution algorithms often cause unpredictable noise
In summary, it can be found that although light field microscopy has significant advantages in some aspects compared with other 3D imaging methods, its reconstruction algorithm still needs to be improved.

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  • Light field microscopic three-dimensional reconstruction method and device based on deep learning algorithm
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  • Light field microscopic three-dimensional reconstruction method and device based on deep learning algorithm

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Embodiment Construction

[0041] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0042]The method and device for three-dimensional reconstruction of light field microscopy based on deep learning algorithm according to the embodiments of the present invention will be described below with reference to the accompanying drawings. rebuild method.

[0043] figure 1 It is a flowchart of a light field microscopic three-dimensional reconstruction method based on a deep learning algorithm according to an embodiment of the present invention.

[0044] Such as figure 1 As shown, the light field microscopic three-dimens...

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Abstract

The invention discloses a light-field microscope three-dimensional reconstruction method and device based on a deep learning algorithm, wherein the method comprises: building a light-field microscope imaging system; obtaining the point diffusion of the imaging system by simulating the light-field microscope imaging system function; generate a simulated sample volume distribution data set; generate a simulated light field data set through the point spread function and the corresponding sample data, and correct the possible noise and background model; build a deep convolutional neural network to simulate the light field data As the input of the network, the simulated sample body distribution data is used as the output of the network, and the network is trained according to the microscopic sample design loss function; after the model training is completed, the light field microscopic data to be reconstructed is input into the model for testing. Obtain the predicted value of the corresponding sample body distribution data. The method can achieve fast, high-resolution, and less artifact three-dimensional reconstruction of light field data while maintaining the advantage of the light field for fast collection of three-dimensional information.

Description

technical field [0001] The present invention relates to technical fields such as computational optics, computational photography, computer vision and computer graphics, and in particular to a light field microscopic three-dimensional reconstruction method and device based on a deep learning algorithm. Background technique [0002] The development of life science and medical technology has put forward higher requirements for 3D fast volume imaging technology. In this case, light field microscopy has become a method that has attracted much attention due to its characteristics of obtaining both spatial and angular information of the sample. Since the light field can quickly obtain the three-dimensional information of the sample, it has become a general solution to the fast imaging problem. After being introduced into optical microscopy, light-field microscopy plays an increasingly important role in bio-optical imaging problems such as three-dimensional imaging problems such as...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T17/00G06N3/04G06N3/08G06N3/063
CPCG06T17/00G06N3/08G06N3/065G06N3/045
Inventor 戴琼海乔晖李晓煦
Owner TSINGHUA UNIV
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