Super resolution detection system and super resolution detection method

Abstract

An ultraprecision detection system (10) and an ultraprecision detection method, the ultraprecision detection system (10) comprising: a light source module (11) for emitting light source light; a light modulator (121) comprising a plurality of micro-mirrors (1211), the plurality of micro-mirrors (1211) being divided into a plurality of modulation units, each modulation unit comprising two micro-mirrors (1211), the light modulation module (12) being used for modulating the light source light into structured light, the structured light being capable of being guided to a sample (20) to be detected to make the sample (20) to be detected emit detection light, the structured light forming a fringe spot on the sample (20) to be detected, each modulation unit corresponding to a fringe period; an imaging module (13) for acquiring a fringe image according to the detection light and for acquiring a wide-field image; and a controller (14) electrically connected to the light modulator (121) and the imaging module (13), used for adjusting the phase of the fringe formed by the structured light, and used for performing ultraprecision reconstruction according to the fringe image and the wide-field image, so as to acquire an ultraprecision image, so as to acquire biological information of the sample (20) to be detected.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biochemical information detection, and in particular to an ultraprecision detection system and an ultraprecision detection method. BACKGROUND

[0002] Gene sequencing technology refers to a technology for analyzing the sequence of four bases on DNA, and has been widely applied to multiple research fields of life science and medicine, including various genomics, etiology of complex diseases, prenatal diagnosis, individualized drug treatment, etc. The basic method of gene sequencing is: four bases are made to carry corresponding fluorescent groups through a biochemical method, the fluorescent groups emit different wavelengths of fluorescence after being excited by different wavelengths of laser, and the base type is identified through the fluorescence, so that sequencing is realized.

[0003] Structured illumination microscopy (SIM) technology is a typical wide-field imaging technology, which is suitable for high-resolution fluorescence microscopic imaging systems of gene sequencers. The optical hardware system of the SIM technology is mainly divided based on the devices used, typical devices such as gratings (Grating-SIM), spatial light modulators (SLM-SIM), digital micromirror devices (DMD-SIM), etc. A digital micromirror device (Digital Micromirror Device, DMD) is a micro-optical machine system (Micro-electrical-mechanical system, MEMS) composed of a micro-mirror array with a high-reflective aluminum film on the surface. A single micro-mirror is called a pixel unit (Pixel), and the pixel unit has two states: ON and OFF. The ON state corresponds to the high-reflective state, and the OFF state corresponds to the non-reflective state. The ON and OFF states are realized by controlling the rotation angle of the mirror (the most common system is a deflection angle of ±12°). DMD-SIM uses an electric control method to realize the projection of stripes in X / Y two directions. DMD realizes high-speed direction switching and stripe phase shift through switching micro-mirrors.

[0004] Under the traditional DMD-SIM mode, a large number of stripe images need to be collected, the image collection time is long, and thus the image processing time is also increased. SUMMARY

[0005] In one aspect, the present application provides an ultraprecision detection system for detecting biological information of a sample to be detected, the ultraprecision detection system comprising:

[0006] A light source module for emitting light source light;

[0007] An optical modulator comprising a plurality of micro-mirrors, each of which is divided into a plurality of modulation units, each of which includes two micro-mirrors. The optical modulation module is configured to modulate the light source into structured light for output. The structured light can be directed toward the sample to be tested so that the sample emits detection light. The structured light forms a striped light spot on the sample to be tested, and each modulation unit corresponds to a stripe period.

[0008] an imaging module, for acquiring a fringe image based on the detection light and for acquiring a wide-field image; and

[0009] A controller is electrically connected to the light modulator and the imaging module, and is used to adjust the phase of the stripes formed by the structured light, and to perform super-resolution reconstruction based on the stripe image and the wide-field image, thereby obtaining a super-resolution image to obtain biological information of the sample to be tested.

[0010] Another aspect of the present invention provides a super-resolution detection method for detecting biological information of a sample to be tested, the super-resolution detection method comprising the following steps:

[0011] Generate structured light, scan the sample to be tested in a two-step phase shift manner, obtain a first fringe image and a second fringe image in a first direction, and obtain a first fringe image in a second direction;

[0012] Acquiring a wide-field image of the sample to be tested;

[0013] A preset evaluation index is set, and a super-resolution image is acquired according to the first fringe image, the second fringe image and the wide-field image in an iterative manner, thereby acquiring biological information of the sample to be tested.

[0014] The aforementioned super-resolution detection system and method utilize a two-step phase shifting approach, which helps increase fringe density, expand the field of view, and improve sequencing throughput. This two-step phase shifting scanning approach, combined with an iterative super-resolution reconstruction algorithm, facilitates super-resolution reconstruction while acquiring fewer images, thereby shortening image acquisition and processing time and reducing the cost of bioinformatics detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of the structure of the super-resolution detection system, test samples and sequencing chip provided in this embodiment.

[0016] Figure 2 for Figure 1 Schematic diagram of the optical path structure of the super-resolution detection system.

[0017] Figure 3 for Figure 2Schematic diagram of planar structure of middle light modulator.

[0018] Figure 4 For Figure 2 Schematic diagram of deflection state of middle micro-mirror.

[0019] Figure 5 For Figure 2 Schematic diagram of deflection state combination of each micro-mirror in each modulation unit of light modulator shown.

[0020] Figure 6 For Figure 2 Another schematic diagram of deflection state combination of each micro-mirror in each modulation unit of light modulator shown.

[0021] Figure 7 Flow chart of super-resolution detection method provided by the embodiment.

[0022] Figure 8 For Figure 7 Refined flow chart of step S3.

[0023] Figure 9 Schematic diagram of verification process based on binary dot matrix as reference image.

[0024] Figure 10 Schematic diagram of verification process based on sequencing chip-based fluorescence image as reference image.

[0025] Main element symbol explanation

[0026] Super-resolution detection system 10

[0027] Light source module 11

[0028] Laser 111

[0029] Mirror 112

[0030] Dichroic mirror 113

[0031] First lens 114

[0032] Second lens 115

[0033] Light modulation module 12

[0034] Light modulator 121

[0035] Micro-mirror 1211

[0036] Total internal reflection mirror 122

[0037] Multiple adjustment assembly 123

[0038] Third lens 1231

[0039] Fourth lens 1232

[0040] Imaging module 13

[0041] First dichroic mirror 131

[0042] Second dichroic mirror 132

[0043] Filter 133

[0044] Fifth lens 134

[0045] Imaging device 135

[0046] Sample to be tested 20

[0047] Sequencing chip 30

[0048] Steps S1, S2, S3, S31, S32, S33, S34, S35

[0049] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0050] See also Figure 1 The super-resolution detection system 10 of the embodiment of the present invention can be used to detect biological information of a sample 20 to be tested. The sample 20 to be tested can be a nucleic acid sample (DNA or RNA), a protein, or a cell. In this embodiment, the sample 20 to be tested is a nucleic acid sample, and the biological information can be the base sequence information of the sample 20 to be tested.

[0051] The sample to be tested 20 is carried on the sequencing chip 30. During the operation of the super-resolution detection system 10, reference light is emitted to the sample to be tested 20. By moving the sequencing chip 30 and the super-resolution detection system 10 to generate relative motion, the sample to be tested 20 and the super-resolution detection system 10 can be driven to generate relative motion. In this embodiment, the sequencing chip 30 is placed on a loading platform, and the loading platform is moved to enable the sequencing chip 30, the sample to be tested 20 and the super-resolution detection system 10 to generate relative motion. That is, in the process of moving the loading platform, the loading platform, the sequencing chip 30 and the sample to be tested 20 remain stationary. By setting the sample to be tested 20 and the super-resolution detection system 10 to generate relative motion, the reference light can be projected to different areas on the sample to be tested 20. This process can also be called "scanning." Since the field of view of the reference light on the sample to be tested 20 usually cannot completely cover the sample to be tested 20, by setting the sample to be tested 20 and the super-resolution detection system 10 to generate relative motion to move the sample to be tested 20, the super-resolution detection system 10 can scan the entire sample to be tested 20.

[0052] In this embodiment, different bases on the sample 20 are labeled by different fluorescent substances. When the reference light irradiates the sample 20, the different fluorescent substances are excited to generate different wavelengths of fluorescence as detection light. The super-resolution detection system 10 is used to obtain biological information of the sample 20 according to the detection light.

[0053] Please refer to Figure 2 , Figure 2 The solid arrows represent the propagation direction of the laser light, and the dashed arrows represent the propagation direction of the fluorescence. The super-resolution detection system 10 includes a light source module 11, a light modulation module 12, an imaging module 13, and a controller 14. The light source module 11, the light modulation module 12, and the imaging module 13 are respectively electrically connected to the controller 14.

[0054] The light source module 11 includes two lasers 111, which are respectively used to emit first light and second light. In this embodiment, the first light and the second light have different wavelengths. For example, one of the two lasers 111 is used to emit red laser light, and the other is used to emit green laser light. In other embodiments, the light source module 11 includes other numbers of lasers, and each laser is used to emit laser light of a different wavelength. The number of lasers can depend on the types of fluorescent substances on the sample 20.

[0055] The light source module 11 further includes a light combining component, which is used to combine the first light and the second light to form light source light. In this embodiment, the light combining component includes a mirror 112 and a dichroic mirror 113. The laser light emitted by one of the lasers 111 is incident on the dichroic mirror 113 and is transmitted by the dichroic mirror 113, and the laser light emitted by the other laser 111 is reflected by the mirror 112 to the dichroic mirror 113 and is reflected by the dichroic mirror 113. That is, the laser light emitted by the two lasers 111 is combined at the dichroic mirror 113 as light source light and is emitted.

[0056] The light source module 11 further includes a beam expanding component. The beam expanding component is located on the emission path of the light source light and is used to perform beam expanding processing on the light source light to meet the requirements of the field of view area in the subsequent optical path, which will not be described in detail here. In this embodiment, the beam expanding component includes a first lens 114 and a second lens 115. The first lens 114 and the second lens 115 cooperate to perform beam expanding on the light source light.

[0057] Please continue to refer to Figure 2 , the light modulation module 12 includes a total internal reflection mirror 122, a light modulator 121, and a multiple adjustment component 123. The total internal reflection mirror 122 is used to receive the beam expanded light source light and project it to the light modulator 121. The light modulator 121 is used to modulate the received light to generate structured light. The total internal reflection mirror 122 is also used to guide the structured light to the imaging module 13.

[0058] Referring to Figure 3 The light modulator 121 is a Digital Micromirror Device (DMD). The light modulator 121 includes a plurality of micromirrors 1211 arranged in a same plane. The plurality of micromirrors 1211 are arranged as a micromirror array including a plurality of rows and a plurality of columns. In the embodiment, each micromirror 1211 is substantially rectangular, and the micromirror array on the light modulator 121 is substantially rectangular.

[0059] Referring to Figure 4 Each micromirror 1211 can be deflected within a range of angles. In the embodiment, each micromirror 1211 can be deflected in two opposite directions about an axis, and the maximum deflection angles in the two opposite directions are the same, and are defined as α and -α, respectively. During the operation of the super-resolution detection system 10, the controller 14 controls each micromirror 1211 to be in a state of a deflection angle α or a deflection angle -α, respectively. Each micromirror 1211 is defined as being in an “ON” state when the deflection angle is α, and is defined as being in an “OFF” state when the deflection angle is -α. By adjusting the state of each micromirror 1211 in the light modulator 121, the form and phase of the structured light emitted by the light modulator 121 can be adjusted.

[0060] In the embodiment, the structured light emitted by the light modulator 121 is in a stripe form. The structured light can be projected onto the sequencing chip 30. When the structured light is projected onto the sequencing chip 30, a plurality of light spots in a parallel stripe form are formed on the surface of the sequencing chip 30.

[0061] During the operation of the super-resolution detection system 10, a plurality of detection cycles are performed. In each detection cycle, the super-resolution detection system 10 acquires a plurality of images of the sequencing chip 30. In the same detection cycle, the plurality of images acquired by the super-resolution detection system 10 are obtained according to structured light of different phases. In the embodiment, the process of changing the phase of the structured light in one detection cycle is defined as “phase shift”.

[0062] In a super-resolution detection system, the sequencing chip 30 is photographed using a three-step phase shift detection method. That is, in one detection cycle, three different phases of structured light are projected onto the sequencing chip 30 in two different directions, respectively, and the sequencing chip 30 is photographed, respectively. In each direction, three images can be obtained, that is, a total of six images can be obtained. The biological information of the sample 20 on the sequencing chip 30 can be obtained according to the six images.

[0063] As described above, the plurality of micro-mirrors 1211 in the light modulator 121 are arranged as a micro-mirror array including multiple rows and multiple columns. In the super-resolution system to be measured, all the micro-mirrors 1211 in the light modulator 121 are divided into a plurality of independent modulation units, each modulation unit including four micro-mirrors 1211, and the four micro-mirrors 1211 in the same modulation unit are arranged adjacently. The four micro-mirrors 1211 in each modulation unit are arranged in the same row, or the four micro-mirrors 1211 in each modulation unit are arranged in the same column.

[0064] In order to realize three-step phase shift, the state (‘ON’ or ‘OFF’) of each micro-mirror 1211 is controlled in a manner that each modulation unit corresponds to one fringe period. That is, four micro-mirrors 1211 represent one fringe period.

[0065] Please refer to Figure 5 , Figure 5 Eight micro-mirrors 1211 (that is, two modulation units) are presented to represent two fringe periods. First, by controlling the ‘ON’ and ‘OFF’ states of each micro-mirror 1211, the structured light emitted from the light modulator 121 forms a binary fringe, and the light intensity of the binary fringe is a square wave shape with a duty cycle of 50%. When the binary fringe is projected to the surface of the sequencing chip 30 through the multiple adjustment assembly 123, due to the limitation of the numerical aperture of the optical elements in the multiple adjustment assembly 123, the binary fringe is changed into a sinusoidal fringe. Therefore, the sinusoidal fringe is projected to the surface of the sequencing chip 30.

[0066] As shown in Figure 5 , there are three state combination modes of each micro-mirror 1211 in each light modulation unit: ‘ON-ON-OFF-OFF’ as shown in (a) figure, corresponding to a fringe phase of 0; ‘ON-OFF-OFF-ON’ as shown in (b) figure, corresponding to a fringe phase of π / 2; and ‘OFF-OFF-ON-ON’ as shown in (c) figure, corresponding to a fringe phase of π. The fringes shown in (a), (b) and (c) are projected to the sequencing chip 30 in time sharing manner, so as to realize three-step phase shift. In a similar manner, three-step phase shift is realized in the row and column directions by the light modulation device 121, and a total of 6 images are collected for the frequency domain super-resolution reconstruction method.

[0067] In the above-mentioned manner, 6 images are collected in each detection period, and super-resolution reconstruction needs to be performed according to the 6 images, which is time-consuming. The super-resolution detection system 10 provided in the embodiment of the present application is used to reduce the detection time by improving the image collection manner and cooperating with the improved image reconstruction method. Specifically, the super-resolution detection system 10 provided in the embodiment of the present application collects images in a two-step phase shift manner, and performs super-resolution reconstruction in an iterative manner.

[0068] Please refer to Figure 6 The present invention proposes a control method of using two micro-mirrors 1211 to represent a stripe period. There are two state combinations of four adjacent micro-mirrors 1211 (that is, two adjacent modulation units): Figure 6 The "on-off switch" shown in Figure (a) corresponds to a fringe phase of 0; Figure 6 The “switch-off” shown in Figure (b) corresponds to a fringe phase of π, thus achieving a two-step phase shift.

[0069] Ideally, the period of the sinusoidal fringes projected onto the surface of the sequencing chip 30 should be equal to the resolution of the optical imaging system. The resolution is usually expressed by the Rayleigh criterion, that is, R = 0.61λ / NA; where λ represents the wavelength and NA represents the numerical aperture of the objective lens.

[0070] like Figure 3 As shown, the number of micro-mirrors 1211 in the light modulator 121 is: M×N. The field of view obtained by using the three-step phase shift method is: The field of view obtained by using two-step phase shift is: Obviously, FOV2 = 4·FOV1. That is, compared with the three-step phase shift method, the two-step phase shift method can increase the field of view by 4 times.

[0071] Please refer to Figure 2 In this embodiment, the magnification adjustment component 123 includes a third lens 1231 and a fourth lens 1232. The structured light emitted from the optical modulator 121 is incident on the third lens 1231 through the total internal emission mirror 122, and then is incident on the fourth lens 1232 from the third lens 1231. The third lens 1231 and the fourth lens 1232 are used to jointly adjust the size of the structured light stripes. The third lens 1231 has a focal length f3, and the fourth lens 1232 has a focal length f4. The size of the structured light stripes can be adjusted by adjusting the ratio of the focal lengths. In this embodiment, the fourth lens 1232 is an objective lens. During the operation of the super-resolution detection system 10, the focal length of the objective lens is usually kept consistent. Therefore, the focal length ratio between the third lens 1231 and the fourth lens 1232 is adjusted by configuring a third lens 1231 with different focal lengths.

[0072] The size of each micro-mirror 1211 is defined as: Δx = Δy. Since four micro-mirrors 1211 are used to represent one fringe period in the three-step phase shift method, the fringe period should be equal to the resolution R of the optical imaging system. Therefore, the reduction factor of the fringe formed by the structured light is: (This equation holds true when Δx = Δy.) In the two-step phase shift method, two micro-mirrors 1211 are used to represent a fringe period. The fringe period is also equal to the resolution R of the optical imaging system. Therefore, the reduction factor of the fringe period formed by the structured light is: (the formula is true when Δx=Δy). Thus, the stripe reduction factor of the three-step phase shift method is twice that of the two-step phase shift method. Therefore, the stripe density of the two-step phase shift method is twice that of the three-step phase shift method.

[0073] On this basis, the stripe formed by the structured light in one detection cycle has two phases, and two images need to be collected in the X and Y directions respectively, thereby effectively reducing the number of images collected relative to the three-step phase shift method, which is conducive to reducing the detection time and also conducive to reducing the image processing time.

[0074] The imaging module 13 includes a first dichroic mirror 131, a second dichroic mirror 132, two filters 133, two fifth lenses 134, and two imaging devices 135.

[0075] The first dichroic mirror 131 is located between the third lens 1231 and the fourth lens 1232, and is used to transmit the structured light to the fourth lens 1232 and reflect the detection light to the second dichroic mirror 132. The second dichroic mirror 132 is used to split the received detection light according to different wavelengths and guide them to the two imaging devices 135 respectively. One filter 133 and one fifth lens 134 are located between the second dichroic mirror 132 and one imaging device 135, and the other filter 133 and the other fifth lens 134 are located between the second dichroic mirror 132 and the other imaging device 135. The filter 133 and the fifth lens 134 are used to guide the detection light to the corresponding imaging device 135. The imaging device 135 is used to image the detection light generated by the stripe irradiation of various phases in the two-step phase shift method described above respectively.

[0076] The controller 14 is used to control the deflection state of each micro-mirror 1211 in the light modulator 121, so as to adjust the stripe form and phase of the structured light projected onto the sequencing chip 30, and to perform super-resolution reconstruction on the multiple images obtained by the imaging device 135 to obtain the biological information of the sample 20 to be detected.

[0077] The embodiment also provides a super-resolution detection method for detecting the biological information of the sample 20 to be detected, which is applied to the super-resolution detection system 10 described above, and in particular, to the controller 14 described above.

[0078] Please refer to Figure 7 , the super-resolution detection method includes the following steps:

[0079] Step S1, generating structured light to scan the sample to be detected in a two-step phase shift manner, obtaining a first stripe image and a second stripe image in a first direction, and obtaining a first stripe image in a second direction;

[0080] Step S2, obtaining a wide-field image of the sample to be tested;

[0081] Step S3, setting a preset evaluation index, and obtaining a super-resolution image according to the first fringe image, the second fringe image and the wide-field image in an iterative manner, thereby obtaining biological information of the sample to be tested.

[0082] The method for obtaining the first fringe image and the second fringe image in step S1 has been described in detail above and will not be repeated here.

[0083] The surface of the sequencing chip 30 is set as the reference surface, denoted as I obj (x,y), (x,y) represents the coordinates of the two-dimensional Cartesian coordinate system. Let the fringe pattern be: P xm (x,y) and P Yn (x, y), the subscripts X and Y represent the X and Y directions of the two-dimensional Cartesian coordinate system, and m and n represent the number of fringe phase shifts in the X or Y direction, respectively. Therefore, there are m+n fringe patterns in total, namely: {P X1 (x,y),P X2 (x,y),…,P Xm (x,y),P Y1 (x,y),P Y2 (x,y),…,P Yn (x,y)}. For convenience, the m+n stripe patterns here are uniformly recorded as: P k (x,y), k∈[1,m+n].

[0084] When wide-field light is used to scan the sequencing chip 30, the super-resolution detection system 10 images the sequencing chip 30 to obtain a low-resolution wide-field image I0(x, y). When stripe structured light is used to scan the sequencing chip 30, the low-resolution stripe image collected by the super-resolution detection system 10 is: I k (x,y),k∈[1,m+n].

[0085] In step S2, there are two main ways to obtain a wide-field image:

[0086] In the first method, the controller 14 controls all the micro-mirrors 1211 in the light modulator 14 to be in the “ON” state. At this time, the image obtained by the structured light incident on the sequencing chip 30 is a low-resolution wide-field image I0 (x, y).

[0087] The smaller m+n is, the better in the case of ensuring the effect of super-resolution reconstruction. In mode two, in a detection period, only 3 (m=2, n=1; or m=1, n=2) original images need to be collected to complete the super-resolution reconstruction by adopting the two-step phase shift scanning mode of the sequencing chip 30. Taking m=2, n=1 as an example, two groups and one group of stripes are projected in the X and Y directions respectively, and the collected stripe images are denoted as I1(x, y), I2(x, y) and I3(x, y). According to the foregoing, the phase difference of the stripes on I1(x, y) and I2(x, y) is π, so the low-resolution wide-field image can be obtained by adding I1(x, y) and I2(x, y), that is, I1(x, y)+I2(x, y)=I0(x, y). Therefore, when the two-step phase shift mode in the embodiment is adopted, the wide-field image I0(x, y) does not need to be collected by specially controlling all the micro-mirrors 1211 in the light modulator 14 to be in the “ON” (on) state. It can be known that, compared with mode one, the wide-field image is obtained by calculation instead of being obtained by actually projecting the wide-field structured light, which is beneficial to reducing the time consumption of acquiring images and improving the throughput.

[0088] Please refer to Figure 8 , the step S3 specifically comprises:

[0089] The step S31 takes the wide-field image as a preliminary estimation of the super-resolution image.

[0090] The step S32 constructs a target function to obtain a target image, and updates the target image.

[0091] The step S33 obtains a super-resolution image according to the updated target image.

[0092] The step S34 repeats the step S32 and the step S33 to traverse the first stripe image and the second stripe image.

[0093] The step S35 repeats the step S32, the step S33 and the step S34 until the preset evaluation index converges.

[0094] The optical transfer function of the super-resolution detection system 10 is defined as OTF, and the point spread function is defined as PSF. The stripe pattern P k (x, y) is projected on the sequencing chip 30, and the super-resolution detection system 10 collects the low-resolution stripe image I k (x, y) through the optical process, which can be expressed in the frequency domain as: In the spatial domain, the sequencing chip I obj is multiplied by the stripe pattern P k ; in the frequency domain, the optical transfer function OTF is multiplied by the frequency spectrum of the target function I tk .

[0095] In step S31 and step S32, the wide-field image I0(x, y) is selected as the preliminary estimation of the super-resolution image of the sequencing chip 30 (I obj ), that is, I obj = I0.

[0096] In step S32, the target function I tk = I obj · P k is constructed, and the target image I tk is updated according to formula (1) to obtain the first updated image

[0097]

[0098] deconv represents the "deconvolution" operation, which is mainly used to suppress image noise, improve image quality, and accelerate convergence.

[0099] In step S33, the first updated image is brought into formula (2) to obtain the second updated image

[0100]

[0101] In step S34, step S32 and step S33 are repeated to traverse all m+n stripe patterns P k (x, y), k ∈ [1, m+n].

[0102] Steps S31-S34 are regarded as successive iterations, and in step S35, multiple iterations are performed until the preset evaluation index converges.

[0103] In this embodiment, the number of iterations is usually 10-50. In this embodiment, the DNA nanoballs are arranged in a square pattern and have a specific structure, so the above-mentioned preset evaluation index is the structural similarity index (SSIM) which is used to represent the convergence of multiple iterations. Given two stripe images, the wide-field image I0and the updated image (in order to simplify, the superscript "updated" of I obj-update is moved to the subscript position: I ), the SSIM calculation formula is represented by formula (3):

[0104]

[0105] wherein l, c, s are the comparison images I0and I obj-updateluminance, contrast, structure. a>0, b>0, g>0, used to adjust the relative importance of l, c, s, the larger the relative value, the higher the relative importance; usually take and are the images I0and I obj-update respectively. and are the images I0and I obj-updated respectively. is the covariance of the images I0and I obj-update . C1, C2, C3 are constants, used to maintain the stability of l, c, s when the denominator is very small.

[0106] The effects of the super-resolution detection system 10 and the super-resolution detection method described above are verified as follows, mainly providing two verification methods: verifying with a binary dot matrix image as a reference image and verifying with a fluorescence image of a sequencing chip as a reference image.

[0107] Please refer to Figure 9 and Figure 10 , multiply the ideal reference image I obj ( Figure 9 and Figure 10 (a) in the figure) with the stripe image P X1 (the first stripe image in the first direction, Figure 9 and Figure 10 (b) in the figure), P X2 (the second stripe image in the first direction, Figure 9 and Figure 10 (c) in the figure) and P Y1 (the first stripe image in the second direction, Figure 9 and Figure 10 (d) in the figure). After two-dimensional Fourier transform, convolution is performed with the optical transfer function OTF of the system ( Figure 9 and Figure 10 (k) in the figure), and then two-dimensional inverse Fourier transform is performed, to obtain the stripe illumination images I1, I2 and I3. The above process is the process of collecting stripe images. The wide-field image I0( Figure 9 and Figure 10 (h) in the figure) can be obtained by I1+I2.

[0108] According to the super-resolution reconstruction algorithm described above, the super-resolution image ( Figure 9 and Figure 10 (i) in the figure) is obtained. In the iteration process, SSIM is selected as an evaluation index ( Figure 9 and Figure 10 (n) in the figure), used to represent the convergence in the iteration process of the algorithm. According to Figure 9 and Figure 10As shown in Figure (n), there is a large gap between the SSIM of the reference image and the SSIM of the wide-field image. As the iteration proceeds, the SSIM of the super-resolution image quickly approaches the SSIM of the reference image, and its final convergence value is greater than that of the wide-field image, which proves that this method achieves the super-resolution effect.

[0109] Figure 9 The original reference image shown in Figure (a) has a size of 1024×1024 pixels, and 50 iterations take 12.18 seconds. SSIM converges after 20 iterations, so the 20 iterations of super-resolution reconstruction take 4.87 seconds.

[0110] Figure 10 The original reference image shown in Figure (a) is 256×256 pixels in size, and 50 iterations take 0.84 seconds. SSIM converges after 20 iterations, so the super-resolution reconstruction takes 0.33 seconds after 20 iterations. Using a graphics processing unit (GPU) or increasing random access memory (RAM) can further reduce this time.

[0111] By showing the spatial morphology, the super-resolution reconstruction effect can be observed more intuitively in the spatial domain. Figure 9 In Figure (o), since the reference image is a binary dot matrix, it is necessary to characterize the edge spread function (ESF) and line spread function (LSF) of a single point diameter position. Figure 9 The left and right axes in Figure (o) compare the ESF and LSF of the reference image (Figure (a)), widefield image (Figure (h)), and super-resolution reconstructed image (Figure (i)). Observing the left axis reveals that due to the limited numerical aperture of the system, the edges of the widefield image appear flatter than those of the reference image, resulting in lower resolution. While the super-resolution reconstructed image exhibits a similar "ripple" effect, it is significantly steeper than the widefield image and has a higher resolution, achieving super-resolution. Observing the right axis reveals that the LSFs of the widefield image, super-resolution image, and reference image decrease in order; the narrower the LSF, the higher the resolution. Because the LSF of the super-resolution image is narrower than that of the widefield image, super-resolution is achieved.

[0112] exist Figure 10Figure (o) shows the ESF of the reference image, the widefield image, and the super-resolution image. Comparison reveals that two distinct peaks in the reference image are indistinguishable in the widefield image due to the limited numerical aperture of the imaging system. However, in the super-resolution image, the two peaks are clearly distinguishable, achieving super-resolution.

[0113] The above are all direct comparisons of super-resolution effects from the spatial domain, or from the SSIM side to prove the super-resolution effect; in order to more intuitively compare the super-resolution effect, here is the reference image ( Figure 9 and Figure 10 Middle (a)), wide field image ( Figure 9 and Figure 10 Middle (h) image) and super-resolution reconstructed image ( Figure 9 and Figure 10 (i) Figure) is transformed into a two-dimensional Fourier transform to obtain its two-dimensional spectrum ( Figure 9 and Figure 10 (j), (l), (m) in the middle). The center of the two-dimensional spectrum represents the low-frequency spatial frequency. From the center to the outside, the spatial frequency gradually increases; the higher the spatial frequency, the higher the resolution; compared with the two-dimensional spectrum ( Figure 9 and Figure 10 As shown in (j), (l), and (m), the two-dimensional spectrum of the reference image ( Figure 9 and Figure 10 The range of the middle (j) figure is the widest; the two-dimensional spectrum range of the super-resolution reconstructed image ( Figure 9 and Figure 10 The middle (m) image) is much larger than the two-dimensional spectrum range of the wide-field image ( Figure 9 and Figure 10 (middle (l) figure), so the super-resolution effect is achieved.

[0114] It should be understood that the execution order of all the method steps described above in this application is not limited to any particular order unless otherwise specified. Furthermore, the execution order of the steps is not limited by the order of the numbers. For example, the numbers S1 and S2 do not limit the execution of step S1 before step S2. It should be understood that the super-resolution detection method includes both embodiments in which step S1 is executed first and then step S2, and embodiments in which step S2 is executed first and then step S1.

[0115] The super-resolution detection system 10 and super-resolution detection method provided in this embodiment adopt a two-step phase shift method and set two micro-mirrors corresponding to one fringe period, which is beneficial to improving fringe density, increasing field of view area, and improving sequencing throughput.

[0116] In the two-step phase-shift scanning mode, the super-resolution reconstruction algorithm is combined with the above-mentioned super-resolution reconstruction algorithm, which is beneficial to realize super-resolution reconstruction on the basis of collecting fewer images, thereby being beneficial to shorten the image acquisition time, being beneficial to shorten the image processing time, and saving the biological information detection cost.

[0117] Those skilled in the art should understand that the above embodiments are only used to illustrate the present application, and are not used as a limitation to the present application, and as long as the above embodiments are appropriately changed and changed within the scope of the spirit of the present application, they fall within the scope of the present application.

Claims

1. A super-resolution detection system for detecting biological information of a sample to be tested, characterized in that: The super-resolution detection system comprises: A light source module, for emitting light from a light source; An optical modulator comprising a plurality of micro-mirrors, each of which is divided into a plurality of modulation units, each of which includes two micro-mirrors. The optical modulator is configured to modulate the light source into structured light for emission. The structured light can be directed toward the sample to be tested so that the sample emits detection light. The structured light forms a striped light spot on the sample to be tested, and each modulation unit corresponds to a stripe period. an imaging module, for acquiring a fringe image based on the detection light and for acquiring a wide-field image; and A controller is electrically connected to the light modulator and the imaging module, and is used to adjust the phase of the stripes formed by the structured light based on a two-step phase shift method, and is used to set a preset evaluation index. In an iterative manner, super-resolution reconstruction is performed based on the stripe image and the wide-field image, thereby obtaining a super-resolution image to obtain biological information of the sample to be tested.

2. The super-resolution detection system according to claim 1, wherein: The size of each micro-mirror is defined as: , the resolution of the super-resolution detection system is defined as R, and when the structured light is projected onto the sample to be tested, the reduction factor of the fringe period is ,in, .

3. The super-resolution detection system according to claim 1, wherein: The super-resolution detection system further includes a magnification adjustment component, which includes a third lens and a fourth lens. The third lens has a focal length of f3, and the fourth lens has a specific focal length of f4. .

4. The super-resolution detection system according to claim 1, wherein: The controller is further configured to control each micro-mirror to reflect the light from the light source to obtain the wide-field image.

5. A super-resolution detection method for detecting biological information of a sample to be tested, characterized in that: The super-resolution detection method comprises the following steps: Generate structured light, scan the sample to be tested in a two-step phase shift manner, obtain a first fringe image and a second fringe image in a first direction, and obtain a first fringe image in a second direction; Acquiring a wide-field image of the sample to be tested; A preset evaluation index is set, and a super-resolution image is obtained in an iterative manner based on the first stripe image in the first direction, the second stripe image in the first direction, the first stripe image in the second direction and the wide-field image, thereby obtaining the biological information of the sample to be tested.

6. The super-resolution detection method according to claim 5, wherein: The step of obtaining a wide-field image of the sample to be tested comprises: The first fringe image and the second fringe image in the first direction are superimposed to acquire the wide-field image.

7. The super-resolution detection method according to claim 5, wherein: The super-resolution detection method is applied to a super-resolution detection system, which includes a light source module and a plurality of micro-reflectors. The light source module is used to emit light source light. The step of obtaining a wide-field image of the sample to be tested includes: Each micro-mirror is controlled to reflect light from a light source to obtain the wide-field image.

8. The super-resolution detection method according to claim 5, wherein: The step of setting a preset evaluation index and iteratively acquiring a super-resolution image based on a first fringe image in the first direction, a second fringe image in the first direction, a first fringe image in the second direction, and the wide-field image includes: using the wide-field image as a preliminary estimate of a super-resolution image; Constructing a target function to obtain a target image, and updating the target image; Acquire a super-resolution image according to the updated target image; Repeat the above two steps to traverse the first fringe image in the first direction, the second fringe image in the first direction, and the first fringe image in the second direction; and Repeat the previous step until the preset evaluation index converges.

9. The super-resolution detection method according to claim 5, wherein: The number of iterations in the iterative step is 10 to 50 times.

10. The super-resolution detection method according to claim 5, wherein: The evaluation index is a structural similarity index.

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