CN115049721B - Volume measurement method of micron-level biological tissue, volume measurement device, cell number measurement method and computer equipment - Google Patents

Abstract

The invention provides a volume measurement method, a volume measurement device, a cell number measurement method and computer equipment for micron-sized biological tissues, and aims to solve the problem that the volume and the cell number of the micron-sized biological tissues cannot be obtained according to the three-dimensional imaging result of the conventional holographic three-dimensional imaging equipment on a lens-free sheet. The volume measurement method comprises the following steps: establishing a three-dimensional coordinate system; calculating the refractive index distribution of each two-dimensional section by adopting FBPP-LHM algorithm, and splicing to obtain the three-dimensional refractive index distribution of the biological tissue sample, so as to obtain a three-dimensional imaging result; extracting a cuboid space containing a biological tissue sample, dividing the cuboid space into cuboid grids, and calculating the volume of the cuboid grids; obtaining the number S of cuboid grids contained in the biological tissue sample according to the three-dimensional refractive index distribution of the biological tissue sample; multiplying the number S of the cuboid grids by the volume vi of the cuboid grids to obtain the volume V of the biological tissue sample; the cell number of the biological tissue sample is obtained by dividing the volume V of the biological tissue sample by the volume of the individual cells.

Description

Volume measurement method of micron-level biological tissue, volume measurement device, cell number measurement method and computer equipment

Technical Field

The present invention belongs to the technical field of biological tissue measurement, and in particular relates to a volume measurement method, a volume measurement device, a cell quantity measurement method and a computer device for micron-level biological tissue.

Background Art

The volume of micron-sized biological tissues such as organoids and cell clusters and the number of cells they contain are important parameters in the biological tissue culture process. The micron-sized in the present invention generally refers to biological tissues with a size between 3 and 500 microns. A lensless on-chip holographic imaging device is a three-dimensional holographic imaging device, which mainly includes an image sensor, incident light sources with different incident angles, and a computer. When acquiring biological tissue images, the biological tissue sample is placed in the area above the image sensor; the image sensor acquires the image of the biological tissue sample under the illumination of the incident light source with different incident angles; and three-dimensional imaging is performed based on the acquired biological tissue image and using the existing three-dimensional imaging algorithm (for example: optical diffraction tomography algorithm, filtered back projection algorithm or intensity diffraction tomography algorithm) of the computer in the lensless on-chip holographic imaging device. References for lensless on-chip holographic imaging devices can be found in the following literature: [1] Zuo Chao, Sun Jiasong, et al. Lensless phase microscopy and diffraction tomography using LED matrix for multi-angle and multi-wavelength illumination [J]. Optics Express, 201523(11): 14314-14328. [2] Luo Zhenxiang, Liz Bette, et al. Fast compressed lensless tomography for 3D biological cell culture imaging[J]. Optics Express, 202028(18): 26935-26952.

Currently, the only method for measuring the volume and cell number of biological tissues such as organoids is the NoviSight3D cell analysis software launched by Olympus, but this software can only be used in the imaging results of high-resolution optical imaging tools such as confocal microscopes and multiphoton microscopes. Due to the existing 3D imaging algorithms in the computer, it is currently impossible to perform corresponding volume and cell number measurements on the imaging results of lensless on-chip holographic 3D imaging devices.

Summary of the invention

The present invention provides a volume measurement method, a volume measurement device, a cell number measurement method and a computer device for micron-level biological tissue, aiming to solve the problem that the volume and cell number of micron-level biological tissue cannot be obtained based on the three-dimensional imaging results of the existing lensless on-chip holographic three-dimensional imaging device.

In order to solve the above technical problems, the technical solution adopted by the present invention is:

In a first aspect, the present invention provides a method for measuring the volume of a micrometer-level biological tissue, comprising:

receiving a plurality of images of a biological tissue sample acquired by a lensless on-chip holographic 3D imaging device; the lensless on-chip holographic 3D imaging device comprises an image sensor and incident light sources with different incident angles, the biological tissue sample is located in a region above the image sensor; the images are images of the biological tissue sample acquired by the image sensor under illumination of incident light sources with different incident angles;

Establishing a three-dimensional coordinate system including an x-axis, a y-axis, and a z-axis according to the positional relationship among the image sensor, the biological tissue sample, and the incident light source and required for executing the FBPP-LHM algorithm;

According to the position information of the image sensor in the three-dimensional coordinate system, the physical information of the incident light, the refractive index of the medium surrounding the biological tissue sample, and a plurality of images of the biological tissue sample acquired by the image sensor under the illumination of the incident light source at different incident angles, a preset FBPP-LHM algorithm is used to calculate the refractive index distribution of a two-dimensional cross section at every interval dz in the area above the image sensor in the three-dimensional coordinate system, where each two-dimensional cross section is perpendicular to the z-axis of the three-dimensional coordinate system;

splicing the calculated refractive index distributions of the two-dimensional cross sections in each two-dimensional cross section to obtain a three-dimensional refractive index distribution of the biological tissue sample, and obtaining a three-dimensional imaging result of the sample according to the three-dimensional refractive index distribution;

According to the three-dimensional imaging results, a rectangular space containing the biological tissue sample is extracted in the area where the biological tissue sample is located, and the rectangular space is divided into rectangular grids that correspond to the pixels in each two-dimensional section one by one and have the same number of pixels. The volume vi of each rectangular grid _is :

_vi = p × p × dz;

Where: p is the side length of the pixel, dz is the distance between two adjacent two-dimensional sections;

According to the three-dimensional refractive index distribution of the biological tissue sample, the number of pixels in the rectangular space that are the biological tissue sample pixels is determined; according to the number of pixels in the rectangular space that are the biological tissue sample pixels, the number S of rectangular grids in the biological tissue sample with the same number is obtained;

The volume V of the biological tissue sample is obtained by multiplying the number S of the rectangular grids in the biological tissue sample by the volume v _i of the rectangular grids:

V = S × _vi .

In a further improved solution, the judgment conditions for the pixels of biological tissue samples are:

It is determined whether the refractive index at each pixel exceeds the set refractive index L; if so, the pixel is determined to be a biological tissue sample pixel; if not, the pixel is determined to be not a biological tissue sample pixel.

Based on the above scheme, the surrounding medium of biological tissue samples such as organoids is generally liquid, the refractive index of the biological tissue sample is slightly larger than that of the liquid, and the refractive index of the liquid is close to that of water. The refractive index L is set between the refractive index of the surrounding medium and the refractive index of the organoid; by judging whether the refractive index of the pixel point exceeds the set refractive index, it can be determined whether the pixel point is a pixel point of the biological tissue sample.

In a further improved solution, the refractive index L is set to:

L = _nm + (a _max - _nm ) / 3

Where, _nm is the refractive index of the medium surrounding the biological tissue sample, and a _max is the maximum refractive index in the rectangular space.

Based on the above scheme, on the basis of the refractive index of the medium surrounding the biological tissue sample, the maximum refractive index in the rectangular space and one-third of the interpolated refractive index of the medium surrounding the biological tissue sample are added as the set refractive index to judge the pixel points of the biological tissue sample, with small error and high accuracy.

In a further improved solution, when establishing the three-dimensional coordinate system required for executing the FBPP-LHM algorithm, the plane where the image sensor is located is perpendicular to the z-axis and the center is located on the z-axis;

The position information of the image sensor in the three-dimensional coordinate system is: the distance between the plane where the image sensor is located and the coordinate origin on the z-axis of the three-dimensional coordinate system;

The physical information of the incident light includes: polarization angle, azimuth angle, wavelength and intensity of the incident light.

A further improved solution adopts a preset FBPP-LHM algorithm, and the step of calculating the refractive index distribution of a two-dimensional cross section at each interval dz in the area above the image sensor in the three-dimensional coordinate system includes:

(1) Perform a two-dimensional Fourier transform on the image I _t obtained under the illumination of the t-th LED light to obtain its spectrum and stored in the computer memory; wherein, t = 1, 2, 3 ... N, N represents the total number of incident light sources, and the total number of incident light sources is equal to the number of images;

(2) Define the filter corresponding to the image obtained under the illumination of the tth LED light:

Wherein: k _x , _ky are frequency domain spatial coordinates, _km = 2πn _m /λ, _nm is the refractive index of the medium surrounding the biological tissue sample, λ is the wavelength of the incident light, z ₁ is the cross-sectional distance between the two-dimensional cross section and the coordinate origin on the z axis of the three-dimensional coordinate system, θ ₀ is the polarization angle of the incident light, z ₀ represents the distance between the plane where the image sensor is located and the coordinate origin on the z axis of the three-dimensional coordinate system, represents the azimuth angle of the tth incident light;

(3) Shift the filter in step (2) to obtain the filter In the formula are the wave vectors of the incident light along the k _x and _ky directions respectively:

(4) Multiply the spectrum in step (1) by the filter in step (3) to obtain the filtered spectrum of image I _t :

(5) Add the spectra of all images after filtering I _t and multiply by the constant term Get F:

Where: _a0 is the incident light intensity; i is a complex unit, _KZ0 is the wave vector of the incident light in the frequency domain spatial coordinate z direction;

(6) Perform a two-dimensional inverse Fourier transform on F in step (5) to obtain information f of the cross section of the biological tissue sample at z= _z1 , and then obtain the refractive index n of each pixel point of the cross section of the biological tissue sample at z= _z1 :

(7) Change the value of _z1 and repeat steps (2)-(6) to obtain the refractive index distribution of each two-dimensional cross section.

In a second aspect, the present invention provides a device for measuring the volume of micrometer-level biological tissue, comprising:

An image receiving module receives a plurality of images of a biological tissue sample acquired by a lensless on-chip holographic 3D imaging device; the lensless on-chip holographic 3D imaging device comprises an image sensor and incident light sources with different incident angles, and the biological tissue sample is located in an area above the image sensor; the images are images of the biological tissue sample acquired by the image sensor under illumination of incident light sources with different incident angles;

A three-dimensional coordinate system establishment module: a three-dimensional coordinate system including an x-axis, a y-axis and a z-axis is established according to the positional relationship among the image sensor, the biological tissue sample and the incident light source and required for executing the FBPP-LHM algorithm;

A two-dimensional cross-sectional refractive index distribution calculation module: based on the position information of the image sensor in the three-dimensional coordinate system, the physical information of the incident light, the refractive index of the medium surrounding the biological tissue sample, and a plurality of images of the biological tissue sample acquired by the image sensor under illumination of incident light sources at different incident angles, a preset FBPP-LHM algorithm is used to calculate the refractive index distribution of a two-dimensional cross section at each interval dz in the area above the image sensor in the three-dimensional coordinate system, where each two-dimensional cross section is perpendicular to the z-axis of the three-dimensional coordinate system;

Three-dimensional imaging module: splicing the calculated refractive index distributions of the two-dimensional cross sections to obtain the three-dimensional refractive index distribution of the biological tissue sample, and obtaining the three-dimensional imaging result of the sample according to the three-dimensional refractive index distribution;

Rectangular grid volume calculation module: According to the three-dimensional imaging results, the rectangular space containing the biological tissue sample is extracted in the area where the biological tissue sample is located, and the rectangular space is divided into rectangular grids that correspond to the pixels in each two-dimensional section one by one and have the same number of pixels. The volume of each rectangular grid, vi _{, is} :

_vi = p × p × dz;

Where: p is the side length of the pixel, dz is the distance between two adjacent two-dimensional sections;

Rectangular grid number acquisition module: according to the three-dimensional refractive index distribution of the biological tissue sample, determine the number of pixels in the rectangular space that are biological tissue sample pixels; according to the number of pixels in the rectangular space that are biological tissue sample pixels, obtain the number S of rectangular grids in the biological tissue sample with the same number;

Biological tissue sample volume calculation module: multiply the number S of rectangular grids in the biological tissue sample by the volume v _i of the rectangular grid to obtain the volume V of the biological tissue sample:

V = S × _vi .

In a further improved solution, the judgment conditions for the pixels of biological tissue samples are:

It is determined whether the refractive index at each pixel exceeds the set refractive index L; if so, the pixel is determined to be a biological tissue sample pixel; if not, the pixel is determined to be not a biological tissue sample pixel.

In a further improved solution, the refractive index L is set to:

L = _nm + (a _max - _nm ) / 3

Where, _nm is the refractive index of the medium surrounding the biological tissue sample, and a _max is the maximum refractive index in the rectangular space.

In a third aspect, the present invention provides a method for measuring the number of cells in micrometer-level biological tissues, wherein the calculation formula for the number of cells M is:

M＝V/v

In the formula: v is the volume of a single cell, and V is the volume of the biological tissue measured by any one of the micrometer-level biological tissue volume measurement methods described in the first aspect.

Since the volume v of a single cell in biological tissues such as organoids is usually the same size, the volume of a single cell can be calculated as long as the volume of the biological tissue is measured by the volume measurement method of micron-level biological tissue in the first aspect, which makes the calculation more convenient.

In a fourth aspect, the present invention provides a computer device comprising a memory and a processor in communication connection, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to implement the steps of a method for measuring the volume of micrometer-level biological tissue as described in any one of the first aspects.

The beneficial effects of the present invention are:

The first aspect of the present invention provides a method for measuring the volume of micron-level biological tissues. The refractive index of each pixel point in each two-dimensional section is calculated by the FBPP-LHM algorithm, and the three-dimensional refractive index distribution of the biological tissue sample is obtained by splicing the refractive index of each pixel point in each two-dimensional section, thereby obtaining a three-dimensional imaging result of the biological tissue; according to the three-dimensional imaging result, a rectangular space containing the biological tissue sample is extracted in the area where the biological tissue sample is located, and the rectangular space is divided into rectangular grids that correspond to the pixel points one by one and have the same number as the pixel points, and the volume of a single rectangular grid is calculated according to the area of the pixel points and the spacing between two adjacent two-dimensional sections; according to the three-dimensional refractive index distribution of the biological tissue sample, the number of pixel points of the biological tissue sample and the number of rectangular grids can be obtained; by multiplying the number of rectangular grids by the volume of the rectangular grids, the volume of the biological tissue sample can be obtained.

The present invention is mainly applied to lensless on-chip holographic imaging devices, and provides a new three-dimensional imaging method for lensless on-chip holographic imaging devices. Based on the three-dimensional imaging method, volume measurement of micron-level biological tissues and measurement of cell numbers can be completed.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

FIG1 is a schematic flow chart of a method for measuring the volume of micrometer-level biological tissues in the present invention.

FIG. 2 is a schematic diagram of a three-dimensional coordinate system in the present invention.

FIG. 3 is a schematic diagram of a rectangular space containing organoids.

FIG. 4 is a logical schematic diagram of a device for measuring the volume of biological tissue at the micrometer level.

DETAILED DESCRIPTION

The technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work belong to the protection scope of the present invention.

Embodiment 1:

Referring to FIG. 1 , the present invention provides a method for measuring the volume of a micrometer-level biological tissue, comprising:

S100, receiving a plurality of images of a biological tissue sample acquired by a lensless on-chip holographic 3D imaging device; the lensless on-chip holographic 3D imaging device comprises an image sensor and incident light sources with different incident angles, the biological tissue sample is located in a region above the image sensor; the images are images of the biological tissue sample acquired by the image sensor under illumination of incident light sources with different incident angles;

The characteristics of lensless on-chip holographic 3D imaging devices include: (1) The biological tissue sample is very close to the CMOS sensor (image sensor), usually about 1 mm (generally between 0.1 mm and 4 mm); hence it is called "on-chip" holography, where "chip" refers to the CMOS sensor chip. (2) The distance between the light source and the biological tissue sample is much greater than the distance between the sample and the CMOS sensor, so the light reaching the sample can be approximately considered as parallel light. (3) The light source illuminates the sample from multiple different angles.

S200, establishing a three-dimensional coordinate system including an x-axis, a y-axis and a z-axis and required for executing the FBPP-LHM algorithm according to the positional relationship among the image sensor, the biological tissue sample and the incident light source;

S300. Based on the position information of the image sensor in the three-dimensional coordinate system, the physical information of the incident light, the refractive index of the medium surrounding the biological tissue sample, and a plurality of images of the biological tissue sample acquired by the image sensor under illumination of incident light sources at different incident angles, a preset FBPP-LHM algorithm is used to calculate the refractive index distribution of a two-dimensional section at every interval dz in the area above the image sensor in the three-dimensional coordinate system, where each two-dimensional section is perpendicular to the z-axis of the three-dimensional coordinate system; wherein the refractive index distribution information of the two-dimensional section includes the refractive index value of each pixel point on each two-dimensional section.

S400, splicing the calculated refractive index distributions of the two-dimensional cross sections in each two-dimensional cross section to obtain a three-dimensional refractive index distribution of the biological tissue sample, and obtaining a three-dimensional imaging result of the sample according to the three-dimensional refractive index distribution;

S500, according to the three-dimensional imaging result, extract a cuboid space containing the biological tissue sample in the area where the biological tissue sample is located, and divide the cuboid space into cuboid grids which correspond to the pixels in each two-dimensional section one by one and have the same number as the pixels, and the volume vi of each cuboid grid _is :

_vi = p × p × dz;

Where: p is the side length of the pixel, dz is the distance between two adjacent two-dimensional sections;

For example, the pixel size of a CMOS sensor (image sensor) is p=1.4um; the spacing between adjacent layers is dz=2.8um; the volume of the rectangular grid (volume element) is _vi =p×p×dz=1.4×1.4×2.8= ^5.488um3 ; the volume of the rectangular grid can be known by simply calculating how many rectangular grids the biological tissue contains.

S600, judging the number of pixels in the rectangular space that are the biological tissue sample pixels according to the three-dimensional refractive index distribution of the biological tissue sample; obtaining the number S of rectangular grids in the biological tissue sample with the same number according to the number of pixels in the rectangular space that are the biological tissue sample pixels;

S700, multiply the number S of rectangular grids in the biological tissue sample by the volume v _i of the rectangular grids to obtain the volume V of the biological tissue sample:

V = S × _vi .

Taking the organoid in Figure 3 as an example, where p = 1.4um, dz = 2.8um, the volume of the organoid is 9.88×10 ⁶ um ³ calculated by the above method. The volume of a single cell in the organoid biological tissue sample is 300um ³ , so it can be obtained that the organoid contains m = 9.88×10 ⁶ /300um ³ ≈ 3.3×10 ⁴ cells.

On the basis of the above scheme, in step S600, the judgment condition of the biological tissue sample pixel is:

It is determined whether the refractive index at each pixel exceeds the set refractive index L; if so, the pixel is determined to be a biological tissue sample pixel; if not, the pixel is determined to be not a biological tissue sample pixel.

Specifically, the refractive index L is set to:

L = _nm + (a _max - _nm ) / 3

Where, _nm is the refractive index of the medium surrounding the biological tissue sample, and a _max is the maximum refractive index in the rectangular space.

Among them, the refractive index L is set to be between the refractive index of the surrounding medium of the biological tissue sample and the refractive index of the biological tissue sample; the surrounding medium of the biological tissue sample is liquid and the refractive index of the liquid is close to the refractive index of water 1.33, so _nm is taken as 1.33; generally, on the basis of the refractive index of the surrounding medium of the biological tissue sample, the maximum value of the refractive index in the rectangular space and one-third of the interpolation of the refractive index of the surrounding medium of the biological tissue sample are added as the set refractive index to judge the pixel points of the biological tissue sample, with small error and high accuracy.

Specifically, it is determined whether the refractive index at each pixel point exceeds the set refractive index L; if it exceeds, the pixel point is determined to be a biological tissue sample pixel point, and the value of the biological tissue sample pixel point is set to 1; if it does not exceed, the pixel point is determined to be not a biological tissue sample pixel point, and the value of the biological tissue sample pixel point is set to 0; and the number of biological tissue sample pixel points whose values are set to 1 is counted.

Referring to FIG. 2 , based on the above solution, in step S200 , when establishing the three-dimensional coordinate system required for executing the FBPP-LHM algorithm, the plane where the image sensor is located is perpendicular to the z-axis, and the center is located on the z-axis;

The position information of the image sensor in the three-dimensional coordinate system is determined as follows: the distance z ₀ between the plane where the image sensor is located and the origin of the coordinate system on the z axis of the three-dimensional coordinate system.

The physical information of the incident light includes: polarization angle, azimuth, wavelength and intensity of the incident light, and _S0 is the direction of the incident light.

Based on the above scheme, the calculation result of the FBPP-LHM algorithm is the three-dimensional refractive index distribution of the biological tissue sample. The preset FBPP-LHM algorithm is inspired by the filter back propagation method (Filter Back Propagation, FBPP), which is a filtered back propagation algorithm based on a lensless holographic hardware structure (Filtered Back-Propagation Algorithm Based on Lensless Holographic Microscope).

Using the preset FBPP-LHM algorithm, in the area above the image sensor in the three-dimensional coordinate system, when calculating the refractive index distribution of a two-dimensional cross section at each interval dz, the calculation of the refractive index distribution of each two-dimensional cross section is obtained by the following formula:

The specific calculation process includes:

(1) Perform a two-dimensional Fourier transform on the image I _t obtained under the illumination of the t-th LED light to obtain its spectrum and stored in the computer memory; wherein, t = 1, 2, 3 ... N, N represents the total number of incident light sources, and the total number of incident light sources is equal to the number of images;

(2) Define the filter corresponding to the image obtained under the illumination of the tth LED light:

Wherein: k _x , _ky are frequency domain spatial coordinates, _km = 2πn _m /λ, _nm is the refractive index of the medium surrounding the biological tissue sample, λ is the wavelength of the incident light, z ₁ is the cross-sectional distance between the two-dimensional cross section and the coordinate origin on the z axis of the three-dimensional coordinate system, θ ₀ is the polarization angle of the incident light, z ₀ represents the distance between the plane where the image sensor is located and the coordinate origin on the z axis of the three-dimensional coordinate system, represents the azimuth angle of the tth incident light;

(3) Shift the filter in step (2) to obtain the filter In the formula are the wave vectors of the incident light along the k _x and _ky directions respectively:

(4) Multiply the spectrum in step (1) by the filter in step (3) to obtain the filtered spectrum of image I _t :

(5) Add the spectra of all images after filtering I _t and multiply by the constant term Get F:

Where: _a0 is the incident light intensity; i is a complex unit, _KZ0 is the wave vector of the incident light in the frequency domain spatial coordinate z direction;

(6) Perform a two-dimensional inverse Fourier transform on F in step (5) to obtain information f of the cross section of the biological tissue sample at z= _z1 , and then obtain the refractive index n of each pixel point of the cross section of the biological tissue sample at z= _z1 :

(7) Change the value of _z1 and repeat steps (2)-(6) to obtain the refractive index distribution of each two-dimensional cross section.

Embodiment 2:

Referring to FIG. 4 , this embodiment provides a volume measurement device for micrometer-level biological tissues, comprising:

An image receiving module receives a plurality of images of a biological tissue sample acquired by a lensless on-chip holographic 3D imaging device; the lensless on-chip holographic 3D imaging device comprises an image sensor and incident light sources with different incident angles, and the biological tissue sample is located in an area above the image sensor; the images are images of the biological tissue sample acquired by the image sensor under illumination of incident light sources with different incident angles;

A three-dimensional coordinate system establishment module: a three-dimensional coordinate system including an x-axis, a y-axis and a z-axis is established according to the positional relationship among the image sensor, the biological tissue sample and the incident light source and required for executing the FBPP-LHM algorithm;

A two-dimensional cross-sectional refractive index distribution calculation module: based on the position information of the image sensor in the three-dimensional coordinate system, the physical information of the incident light, the refractive index of the medium surrounding the biological tissue sample, and a plurality of images of the biological tissue sample acquired by the image sensor under illumination of incident light sources at different incident angles, a preset FBPP-LHM algorithm is used to calculate the refractive index distribution of a two-dimensional cross section at each interval dz in the area above the image sensor in the three-dimensional coordinate system, where each two-dimensional cross section is perpendicular to the z-axis of the three-dimensional coordinate system;

Three-dimensional imaging module: splicing the calculated refractive index distributions of the two-dimensional cross sections to obtain the three-dimensional refractive index distribution of the biological tissue sample, and obtaining the three-dimensional imaging result of the sample according to the three-dimensional refractive index distribution;

Rectangular grid volume calculation module: According to the three-dimensional imaging results, the rectangular space containing the biological tissue sample is extracted in the area where the biological tissue sample is located, and the rectangular space is divided into rectangular grids that correspond to the pixels in each two-dimensional section one by one and have the same number of pixels. The volume of each rectangular grid, vi _{, is} :

_vi = p × p × dz;

Where: p is the side length of the pixel, dz is the distance between two adjacent two-dimensional sections;

Rectangular grid number acquisition module: according to the three-dimensional refractive index distribution of the biological tissue sample, determine the number of pixels in the rectangular space that are biological tissue sample pixels; according to the number of pixels in the rectangular space that are biological tissue sample pixels, obtain the number S of rectangular grids in the biological tissue sample with the same number;

Biological tissue sample volume calculation module: multiply the number S of rectangular grids in the biological tissue sample by the volume v _i of the rectangular grid to obtain the volume V of the biological tissue sample:

V = S × _vi .

Among them, the judgment conditions of biological tissue sample pixels are:

It is determined whether the refractive index at each pixel exceeds the set refractive index L; if so, the pixel is determined to be a biological tissue sample pixel; if not, the pixel is determined to be not a biological tissue sample pixel.

Wherein, the set refractive index L is:

L = _nm + (a _max - _nm ) / 3

Where, _nm is the refractive index of the medium surrounding the biological tissue sample, and a _max is the maximum refractive index in the rectangular space.

In a third aspect, the present invention provides a method for measuring the number of cells in micrometer-level biological tissues, wherein the calculation formula for the number of cells M is:

M＝V/v

In the formula: v is the volume of a single cell, and V is the volume of the biological tissue measured by any one of the micrometer-level biological tissue volume measurement methods described in the first aspect.

Since the volume of a single cell in biological tissues such as organoids is usually within a smaller range, v is the average value obtained based on the volumes of several cells measured in advance. Therefore, as long as the volume of the biological tissue is measured by the volume measurement method of micron-level biological tissue in the first aspect, the number of single cells can be calculated, and the calculation is relatively convenient.

Embodiment 4:

This embodiment provides a computer device, including a memory and a processor that are communicatively connected, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to implement the steps of a method for measuring the volume of a micrometer-level biological tissue as described in any one of the first embodiments.

By way of specific example, the memory may include, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a flash memory (Flash Memory), a first-in first-out memory (FIFO) and/or a first-in last-out memory (FILO); the processor may be limited to a microprocessor of the STM32F105 series; in addition, the computer device may also include, but is not limited to, a power module, a display screen and other necessary components.

The working process, working details and technical effects of the aforementioned computer device provided in this embodiment can be referred to any one of the micrometer-level biological tissue volume measurement methods in the above embodiment 1, and will not be described in detail here.

The present invention is not limited to the above-mentioned optional implementation modes. Anyone can derive other various forms of products under the inspiration of the present invention. However, no matter what changes are made in the shape or structure, all technical solutions that fall within the scope defined by the claims of the present invention fall within the protection scope of the present invention.

Claims (10)

1. A method for measuring the volume of micron-scale biological tissue, comprising: receiving a plurality of images of a biological tissue sample acquired by a lensless on-chip holographic 3D imaging device; the lensless on-chip holographic 3D imaging device comprises an image sensor and incident light sources with different incident angles, the biological tissue sample is located in a region above the image sensor; the images are images of the biological tissue sample acquired by the image sensor under illumination of incident light sources with different incident angles; According to the positional relationship among the image sensor, the biological tissue sample and the incident light source, a three-dimensional coordinate system including the x-axis, the y-axis and the z-axis is established and required for executing the FBPP-LHM algorithm; According to the position information of the image sensor in the three-dimensional coordinate system, the physical information of the incident light, the refractive index of the medium surrounding the biological tissue sample and several images of the biological tissue sample acquired by the image sensor under the illumination of the incident light source at different incident angles, a preset FBPP-LHM algorithm is used to calculate the refractive index distribution of a two-dimensional cross section at each interval dz in the area above the image sensor in the three-dimensional coordinate system: S1, perform a two-dimensional Fourier transform on each image at different angles to obtain the spectrum of the corresponding image; S2, determine the filter corresponding to the image according to the illumination angle of each image; S3, shift the corresponding filter according to the illumination angle of the image; S4, multiply the shifted filter by the spectrum of the image to complete the filtering of the image; S5, superimpose the filtered spectra of all the images, and perform an inverse Fourier transform to obtain the refractive index distribution of a cross section; repeat steps S1-S5 to calculate the refractive index distribution of each cross section with an interval of dz; Each two-dimensional section is perpendicular to the z-axis of the three-dimensional coordinate system; splicing the calculated refractive index distributions of the two-dimensional cross sections in each two-dimensional cross section to obtain a three-dimensional refractive index distribution of the biological tissue sample, and obtaining a three-dimensional imaging result of the sample according to the three-dimensional refractive index distribution; According to the three-dimensional imaging results, a rectangular space containing the biological tissue sample is extracted in the area where the biological tissue sample is located, and the rectangular space is divided into rectangular grids that correspond one-to-one to the pixel points in each two-dimensional section and have the same number of pixel points. The volume vi of each rectangular grid _is : _vi = p × p × dz; Where: p is the side length of the pixel, dz is the distance between two adjacent two-dimensional sections; According to the three-dimensional refractive index distribution of the biological tissue sample, the number of pixels in the rectangular space that are the biological tissue sample pixels is determined; according to the number of pixels in the rectangular space that are the biological tissue sample pixels, the number S of rectangular grids in the biological tissue sample with the same number is obtained; The volume V of the biological tissue sample is obtained by multiplying the number S of the rectangular grids in the biological tissue sample by the volume v _i of the rectangular grids: V = S × _vi . 2. The method for measuring the volume of a micron-level biological tissue according to claim 1, wherein the judgment condition of the pixel point of the biological tissue sample is: It is determined whether the refractive index at each pixel exceeds the set refractive index L; if so, the pixel is determined to be a biological tissue sample pixel; if not, the pixel is determined to be not a biological tissue sample pixel. 3. The method for measuring the volume of micron-level biological tissue according to claim 2, wherein the set refractive index L is: L = _nm + (a _max - _nm ) / 3 Where, _nm is the refractive index of the medium surrounding the biological tissue sample, and a _max is the maximum refractive index in the rectangular space. 4. A method for measuring the volume of a micron-level biological tissue according to claim 1, characterized in that: when establishing the three-dimensional coordinate system required for executing the FBPP-LHM algorithm, the plane where the image sensor is located is perpendicular to the z-axis, and the center is located on the z-axis; The position information of the image sensor in the three-dimensional coordinate system is: the distance between the plane where the image sensor is located and the coordinate origin on the z-axis of the three-dimensional coordinate system; The physical information of the incident light includes: polarization angle, azimuth angle, wavelength and intensity of the incident light. 5. A method for measuring the volume of micron-level biological tissue according to claim 4, characterized in that, using a preset FBPP-LHM algorithm, the step of calculating the refractive index distribution of a two-dimensional cross section at each interval dz in the area above the image sensor in the three-dimensional coordinate system comprises: (1) Perform a two-dimensional Fourier transform on the image It obtained under the illumination of the tth LED light to obtain its spectrum and stored in the computer memory; wherein, t = 1, 2, 3 ... N, N represents the total number of incident light sources, and the total number of incident light sources is equal to the number of images; (2) Define the filter corresponding to the image obtained under the illumination of the tth LED light: Wherein: k _x , _ky are frequency domain spatial coordinates, _km = 2πn _m /λ, _nm is the refractive index of the medium surrounding the biological tissue sample, λ is the wavelength of the incident light, z ₁ is the cross-sectional distance between the two-dimensional cross section and the coordinate origin on the z axis of the three-dimensional coordinate system, θ ₀ is the polarization angle of the incident light, z ₀ represents the distance between the plane where the image sensor is located and the coordinate origin on the z axis of the three-dimensional coordinate system, represents the azimuth angle of the tth incident light; (3) Shift the filter in step (2) to obtain the filter In the formula are the wave vectors of the incident light along the k _x and _ky directions respectively: (4) Multiply the spectrum in step (1) by the filter in step (3) to obtain the spectrum of the image It after filtering: (5) Add the spectra of all images after filtering I _t and multiply by the constant term Get F: Where: _a0 is the incident light intensity; i is a complex unit, _KZ0 is the wave vector of the incident light in the frequency domain spatial coordinate z direction; (6) Perform a two-dimensional inverse Fourier transform on F in step (5) to obtain information f of the cross section of the biological tissue sample at z= _z1 , and then obtain the refractive index n of each pixel point of the cross section of the biological tissue sample at z= _z1 : (7) Change the value of _z1 and repeat steps (2)-(6) to obtain the refractive index distribution of each two-dimensional cross section. 6. A device for measuring the volume of micrometer-level biological tissue, comprising: An image receiving module receives a plurality of images of a biological tissue sample acquired by a lensless on-chip holographic 3D imaging device; the lensless on-chip holographic 3D imaging device comprises an image sensor and incident light sources with different incident angles, and the biological tissue sample is located in an area above the image sensor; the images are images of the biological tissue sample acquired by the image sensor under illumination of incident light sources with different incident angles; Three-dimensional coordinate system establishment module: establishes a three-dimensional coordinate system including x-axis, y-axis and z-axis according to the positional relationship among the image sensor, biological tissue sample and incident light source and is required to execute the FBPP-LHM algorithm; Two-dimensional cross-sectional refractive index distribution calculation module: according to the position information of the image sensor in the three-dimensional coordinate system, the physical information of the incident light, the refractive index of the medium surrounding the biological tissue sample and several images of the biological tissue sample acquired by the image sensor under the illumination of the incident light source at different incident angles, a preset FBPP-LHM algorithm is used to calculate the refractive index distribution of a two-dimensional cross section at each interval dz in the area above the image sensor in the three-dimensional coordinate system: S1, perform a two-dimensional Fourier transform on each image at different angles to obtain the spectrum of the corresponding image; S2, determine the filter corresponding to the image according to the illumination angle of each image; S3, shift the corresponding filter according to the illumination angle of the image; S4, multiply the shifted filter by the spectrum of the image to complete the filtering of the image; S5, superimpose the filtered spectra of all the images, and perform inverse Fourier transform to obtain the refractive index distribution of a cross section; repeat steps S1-S5 to calculate the refractive index distribution of each cross section with an interval of dz; Each two-dimensional section is perpendicular to the z-axis of the three-dimensional coordinate system; Three-dimensional imaging module: splicing the calculated refractive index distributions of the two-dimensional cross sections to obtain the three-dimensional refractive index distribution of the biological tissue sample, and obtaining the three-dimensional imaging result of the sample according to the three-dimensional refractive index distribution; Rectangular grid volume calculation module: According to the three-dimensional imaging results, the rectangular space containing the biological tissue sample is extracted in the area where the biological tissue sample is located, and the rectangular space is divided into rectangular grids that correspond to the pixels in each two-dimensional section one by one and have the same number of pixels. The volume of each rectangular grid, vi _{, is} : _vi = p × p × dz; Where: p is the side length of the pixel, dz is the distance between two adjacent two-dimensional sections; Rectangular grid number acquisition module: according to the three-dimensional refractive index distribution of the biological tissue sample, determine the number of pixels in the rectangular space that are biological tissue sample pixels; according to the number of pixels in the rectangular space that are biological tissue sample pixels, obtain the number S of rectangular grids in the biological tissue sample with the same number; Biological tissue sample volume calculation module: multiply the number S of rectangular grids in the biological tissue sample by the volume v _i of the rectangular grid to obtain the volume V of the biological tissue sample: V = S × _vi . 7. The device for measuring the volume of micrometer-level biological tissue according to claim 6, wherein the judgment condition of the pixel point of the biological tissue sample is: It is determined whether the refractive index at each pixel exceeds the set refractive index L; if so, the pixel is determined to be a biological tissue sample pixel; if not, the pixel is determined to be not a biological tissue sample pixel. 8. The device for measuring the volume of micron-level biological tissue according to claim 7, wherein the set refractive index L is: L = _nm + (a _max - _nm ) / 3 Where, _nm is the refractive index of the medium surrounding the biological tissue sample, and a _max is the maximum refractive index in the rectangular space. 9. A method for measuring the number of cells in micron-scale biological tissues, characterized in that the calculation formula of the number of cells M is: M＝V/v In the formula: v is the volume of a single cell, and V is the volume of the biological tissue measured by the method for measuring the volume of micrometer-level biological tissue according to any one of claims 1 to 5. 10. A computer device, characterized in that it comprises a memory and a processor in communication connection, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to implement the steps of a method for measuring the volume of micrometer-level biological tissue according to any one of claims 1 to 5.