Digital slice rescanning method, apparatus, device, and medium

Abstract

The application discloses a digital slice rescanning method and device, equipment and medium, and the method comprises the following steps: S1, a scanning image of a digital slice is acquired, and the image quality is judged; if the image quality meets preset requirements, S6 is executed; otherwise, S2 is executed; S2, the defect type of the scanning image quality is judged; if the scanning image quality is overall blur, S3 is executed; if the scanning image quality is local blur, S4 is executed; S3, the scanning is re-modeled according to a first preset strategy, the image quality of the re-modeled scanning image is judged, if the image quality meets preset requirements, S6 is executed; otherwise, the defect type of the scanning image quality is judged; if the scanning image quality is still overall blur, S5 is executed; if the scanning image quality is local blur, S4 is executed; S4, the scanning is re-modeled according to a second preset strategy, the image quality of the re-modeled scanning image is judged, if the image quality meets preset requirements, S6 is executed; otherwise, S5 is executed; S5, a quality abnormality prompt is output; S6, the image is archived. The application can automatically judge the defect type of the image and automatically rescans by adopting different strategies.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital slice scanning, in particular to a digital slice rescanning method, device, equipment and medium. BACKGROUND

[0002] After the digital slice scanning device turns the traditional slice scanning into a high-resolution digital picture, the user can view the slice on the computer or mobile device at any time and anywhere, while having the advantages of never fading, easy to save, manage, share, full field of view, and can be zoomed in and out at will. It has been widely used in the fields of pathological diagnosis, teaching training, drug research and scientific research.

[0003] With the popularization of application, the performance of the scanner is getting higher and higher, especially the scanning quality and speed. In order to obtain better image quality, it is required to focus accurately on each field of view, and usually thousands of images of fields of view are needed to be taken for digitalizing a slice, so the focusing mode will affect the scanning speed. Although the traditional focusing on each field of view can obtain better image quality, the speed becomes a bottleneck. Therefore, at present, the method of modeling the focal plane is more used, such as patent 201110283732.2, that is, the focal plane positions of several fields of view of the slice are selected as model points, and the focal plane positions of each field of view in the slice are estimated according to the model points through an algorithm. In this way, when scanning, it is not necessary to move the Z-axis to collect multiple images to calculate the defocus amount, but only needs to drive the Z-axis according to the modeled focal plane position, which significantly improves the speed.

[0004] However, at this time, the problem of image blur often occurs. The conventional method is to find the image quality problem after manual reading, and then to perform rescanning, which needs manual intervention, such as manually selecting model points, manually focusing, and then automatically modeling and scanning, which reduces the efficiency.

[0005] In addition, the patents “CN113256573A-Determination method and device of digital slice quality” and “CN114820510A-Cell pathology image quality evaluation method” evaluate the quality of digital slice images of different microscopic specimens, so that the user can judge whether it is necessary to rescan, which reduces part of the workload, but still needs manual intervention for rescanning. If it is a high-throughput scanner, since there are many slices to be scanned, if there are multiple slices with blur problems, it is also necessary to spend effort to find the corresponding slices, and the efficiency is further reduced.

[0006] Therefore, it is necessary to propose a digital slice rescanning method, which can automatically adjust the scanning strategy when the image quality does not meet the preset requirements, reduce manual identification and intervention, improve the scanning success rate, and as far as possible reduce the rescanning rate. SUMMARY

[0007] The present application aims to solve one of the above technical problems to some extent. To this end, the present application provides a digital slice rescanning method, which reduces the workload of manual review of slices by evaluating the overall blur and local blur of image quality and setting a targeted rescanning strategy, so as to improve the scanning success rate and efficiency.

[0008] Specifically, the digital slice rescanning method comprises the following steps:

[0009] S1, acquiring a scanning image of a digital slice, judging the image quality, if it meets the preset requirements, executing S6, otherwise, executing S2;

[0010] S2, determining the defect type of the scanning image quality, if it is overall blur, executing S3; if it is local blur, executing S4;

[0011] S3, re-modeling scanning according to a first preset strategy, judging the image quality of the re-modeled scanning image, if it meets the preset requirements, executing S6; otherwise, determining the defect type of the scanning image quality, if it is still overall blur, executing S5, if it is local blur, executing S4;

[0012] S4, re-modeling scanning according to a second preset strategy, judging the image quality of the re-modeled scanning image, if it meets the preset requirements, executing S6; otherwise, executing S5.

[0013] S5, outputting a quality abnormality prompt;

[0014] S6, image archiving.

[0015] Further, in S2, the number of blurred fields of view is acquired, if the number of blurred fields of view is less than a blur evaluation threshold, it is determined to be local blur; otherwise, it is determined to be overall blur.

[0016] Further, in S3, the first preset strategy comprises judging whether the focal plane position of the model point is higher than the reference position by a first position threshold, if yes, setting the upper limit of the focusing range of the model point as the difference between the focal plane position of the original model point and the first position threshold; if no, setting the upper and lower limits of the docking range of the model point as the reference position plus and minus a second position threshold;

[0017] Further, in S4, the second preset strategy comprises:

[0018] S41, judging the severity of local blur, if it is severe blur, executing S42, otherwise, executing S43;

[0019] S42, identifying tissue regions and coverslip regions, judging whether there is a tissue region outside the coverslip region, if yes, executing step S43; if no, executing step S45;

[0020] S43, limit the scanning area to the tissue area within the coverslip area, re-model the scanning, judge the image quality, if it meets the preset requirement, execute S6, otherwise, execute S44;

[0021] S44, judge the severity of the local blur, if it is serious blur, execute S5, if it is slight blur, execute S45;

[0022] S45, on the basis of the original model points, add model points in the blurred area, re-model the scanning, judge the image quality of the re-modeled scanning, if it meets the preset requirement, execute S6, otherwise, execute S5.

[0023] Preferably, in S45, before executing S5, it further comprises S46: query the number of blurred fields of view, if the number of blurred fields of view is not less than a number threshold, adopt the stop-and-go mode to automatically focus on each field of view; or adopt the extended depth of field mode to scan.

[0024] Further, obtain a focus factor, if the value of the focus factor is less than a first focus threshold, determine that it is serious blur; if the value of the focus factor is greater than or equal to the first focus threshold but less than a second focus threshold, determine that it is slight blur.

[0025] Further, in the process of scanning the digital slice, S1-S6 are synchronously executed.

[0026] The application further discloses a slice scanning device, comprising:

[0027] an obtaining module, configured to obtain a scanning image of a digital slice;

[0028] an evaluating module, configured to evaluate the quality of the scanning image, and determine whether the defect type of the scanning image is overall blur or local blur if the scanning image has a defect;

[0029] a correcting module, configured to execute a re-scanning action according to the evaluation result of the evaluating module, according to a first preset strategy and / or a second preset strategy, and feed back the re-scanning result to the evaluating module for determining whether to continue correcting or archiving;

[0030] an archiving module, configured to end the scanning process at the current time and store the scanning image when a qualified scanning image is obtained.

[0031] The application further discloses a slice scanning device, comprising a processor and a memory, wherein the memory stores computer executable instructions capable of being executed by the processor, and the processor executes the computer executable instructions to realize the method as described above.

[0032] The application further discloses a computer readable storage medium, which stores computer executable instructions, and the computer executable instructions cause a processor to implement the method as described above when the computer executable instructions are invoked and executed by the processor.

[0033] Based on the digital slice rescan method provided in the application, the scanning image of the digital slice can be automatically evaluated, and the image defect type is judged, and the non-exception condition does not need manual intervention, and the rescan action is automatically performed, so that the labor input is reduced.

[0034] Based on the execution logic of the digital slice rescan method provided in the application, the unnecessary rescan action can be reduced, and the rescan rate is significantly reduced.

[0035] Based on the execution logic of the digital slice rescan method provided in the application, the scanning, evaluation and correction can be performed simultaneously in the scanning process of the digital slice, and the evaluation and rescan do not have to wait for the completion of the scanning of the whole slice, so that the efficiency is further improved. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 It is a step schematic diagram of the digital slice rescan method of the application;

[0037] Figure 2 It is a flow schematic diagram of the digital slice rescan method of the application;

[0038] Figure 3 It is a schematic diagram of a slice scanning device of the application;

[0039] Figure 4 It is a schematic diagram of a slice scanning device of the application. DETAILED DESCRIPTION

[0040] The embodiments of the application are described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are intended to explain the application, and cannot be understood as a limitation of the application.

[0041] The application provides a digital slice rescan method, and the core scheme thereof is to give different rescan strategies according to different defect types of an image after it is found that the image quality is problematic, so that the success rate and efficiency of scanning are improved.

[0042] Please refer to Figure 1 and Figure 2 As shown in the figures, the digital slice rescan method comprises the following steps:

[0043] S1, acquire a scanning image of a digital slice, judge the image quality, if it meets the preset requirements, execute S6 to archive the image. Otherwise, execute S2 to further judge the defect type.

[0044] Wherein, the image quality is evaluated based on machine learning or artificial intelligence method, to determine whether it meets the preset requirements.

[0045] S2, judge the defect type of the scanning image quality, if it is overall blur, execute S3; if it is local blur, execute S4.

[0046] Wherein, based on the field of view image obtained during scanning, it is distinguished whether it is partial field of view blur (referred to as local blur in this application) or overall digital slice blur (referred to as overall blur in this application). The blur judgment of a single field of view can use edge algorithm to obtain focus factor, if the value of focus factor is less than the second focus threshold, it is judged as blur. The number of blurred fields of view is judged to determine whether it is local blur or overall blur. A blur evaluation threshold is preset, if the number of blurred fields of view is less than the blur evaluation threshold, it is judged as local blur; otherwise, it is judged as overall blur.

[0047] S3, re-model the scanning according to the first preset strategy, judge the image quality of the scanning image after re-modeling, if it meets the preset requirements, execute S6; otherwise, judge the defect type of the scanning image quality, if it is still overall blur, execute S5, if it is local blur, execute S4.

[0048] Specifically, in one example, the first preset strategy includes judging whether the focal plane position of the model point is higher than the reference position by a first position threshold, if yes, setting the upper limit of the focusing range of the model point as the difference between the focal plane position of the original model point and the first position threshold; if no, setting the upper and lower limits of the focusing range of the model point as the reference position plus and minus a second position threshold. Wherein, the first position threshold is determined according to the cover glass thickness, with the average position of the focal plane of the last several scanning successful slices as the reference position. The second position threshold is determined according to the focusing range of the autofocus.

[0049] When the overall blur in the digital slice is detected, it is likely that the dust or impurities on the cover glass are focused on, and the focal plane position of this case will have a larger difference from the normal focal plane position, mainly caused by the cover glass caused by the optical path difference.

[0050] In a 170um thickness cover glass example, assuming that the Z axis adjustment is the objective lens height, the normal focal plane position is recorded as 0um, if the focal plane is focused on the cover glass surface, the focal plane needs to be raised by about 122um, which can be judged according to this feature.

[0051] If the thickness deviation of the same batch of glass slides is not large, the average position of the focal plane of the last several successfully scanned slices can be combined as a reference position. If the focal plane model position of the current blurred specimen is about 100 um higher than the reference position, it can be judged that the focus is on the cover glass. The upper limit of the focusing range of the model point is set to the original model point focal plane minus 100 um before rescan. Refocus modeling and scanning are performed. If neither is within the range of 100 um (i.e. the original model point focal plane minus 100 um, then modeling is not successful), the upper and lower limits of the focusing range of the model point are set to the focal plane position of the last successfully scanned specimen + / - 40 um (+ / - 40 um is the range of automatic focusing, and automatic focusing is performed within this range). Refocus modeling and scanning are performed.

[0052] After scanning, if it is still judged that the whole is blurred, it is prompted that there is a scanning quality problem. If it is judged that it is locally blurred, the processing method for local blur is used.

[0053] S4, re-modeling and scanning according to the second preset strategy, judging the image quality of the re-modeled and scanned image, if it meets the preset requirement, executing S6; otherwise, executing S5.

[0054] The second preset strategy includes:

[0055] S41, judging the severity of local blur, if it is serious blur, executing S42, otherwise, executing S43.

[0056] In the case where it has been determined to be blurred (i.e. the focusing factor is less than the second focusing threshold), at this time, the severity is still judged by the focusing factor. If the focusing factor is less than the first focusing threshold, it is determined to be serious blur. If the value of the focusing factor is greater than or equal to the first focusing threshold but less than the second focusing threshold, it is determined to be slight blur. That is, the focusing factor is used as an index to evaluate the blur degree, and two different values of the first focusing threshold and the second focusing threshold are set to judge the blur degree.

[0057] S42, identifying the tissue area and the cover glass area, judging whether there is a tissue area outside the cover glass area, if yes, executing step S43; if no, executing step S45;

[0058] That is, when there is local blur, first determine the severity of local blur, if there is a serious blur field, the great possibility is to focus on the tissue area outside the cover glass (caused by non-standard preparation), due to the cover glass optical path difference, the tissue focal position outside the cover glass will be lower than that inside by about 58 um, and the depth of field of the commonly used objective is about 1 um, which will bring serious blur, at this time, the image algorithm can be used to identify the tissue area and the cover glass area respectively, to determine whether the tissue area is all under the cover glass, if not, only the tissue area under the cover glass is taken as the scanning area, and the model is rebuilt and scanned.

[0059] S43, limit the scanning area to the tissue area within the cover glass area, rebuild the model and scan, determine the image quality, if it meets the preset requirements, execute S6, otherwise, execute S44.

[0060] That is, after limiting the scanning area and rebuilding the model and scanning, if the quality obtained still does not meet the image quality requirements, further determination is needed whether it is still serious blur or has turned to slight blur.

[0061] S44, determine the severity of local blur, if it is serious blur, execute S5, if it is slight blur, execute S45.

[0062] At this time, if it is still serious blur, a scanning quality problem is prompted, and an abnormal quality prompt is output.

[0063] S45, on the basis of the original model points, additional model points are added in the blurred area, the model is rebuilt and scanned, and the image quality of the scanned image after rebuilding the model is determined, if it meets the preset requirements, execute S6; otherwise, execute S5.

[0064] That is, if it is a slight blur field, more model points are set in the blurred area on the basis of the original model points, the model is rebuilt and scanned. For example, if only one field is blurred, one more model point is set at that place, if two consecutive fields are blurred, two more model points are preferably set at that place, if three or more consecutive fields are blurred, at least three more model points are preferably set at that place, and then refocus and rebuild the model and rescan. If the image quality output at this time meets the preset requirements, the image is archived; if the image still has many fields blurred, an abnormal prompt can be output.

[0065] As a preferred embodiment, before S5 is executed to output the abnormality prompt in S45, it can further include S46. That is, the number of blurred fields of view is queried, if the number of blurred fields of view is not less than a number threshold, a walk-stop mode is adopted, and automatic focusing is performed for each field of view; or, an extended depth of field mode is adopted to perform scanning. The extended depth of field mode is to divide the field of view image into blocks, typically into 2*2 or 3*3, and then calculate the focusing factor for each block in turn, for the case that the focal plane difference in the same field of view is large.

[0066] After S46 is executed, the image quality is evaluated again, if there is still unacceptable image blur (for example, the number threshold is 10, when the number of image blur is ≥10), S5 is executed to output the abnormality prompt.

[0067] S5, outputting a quality abnormality prompt.

[0068] At this time, the abnormality prompt is output, and manual intervention or other measures are taken.

[0069] S6, image archiving.

[0070] If the image quality meets the preset requirement, the corresponding image is archived.

[0071] It should be understood that the present application can execute S1-S6 synchronously in the process of scanning the digital slice. That is, it can evaluate and correct the scanning strategy while scanning, without waiting for the whole slice to be scanned to evaluate, so as to further improve the efficiency. Then, at each time, if the image quality at the current time meets the preset requirement, the corresponding image is archived, and the scanning and evaluation actions at the next time are executed.

[0072] Please refer to Figure 3 The present application also discloses a slice scanning device, which comprises an acquisition module, an evaluation module, a correction module, a prompt module and an archiving module

[0073] The acquisition module is used to acquire the scanning image of the digital slice. When the scanning-evaluating strategy is adopted, the acquisition mode is real-time acquisition, without waiting for the whole digital slice to be scanned.

[0074] The evaluation module is used to evaluate the quality of the scanning image, if the scanning image has defects, to determine whether the defect type is overall blur or local blur, and further determine the blur degree of the local blur, that is, whether it is slight blur or serious blur.

[0075] The correction module is used to execute the re-scanning action according to the evaluation result of the evaluation module, according to the first preset strategy and / or the second preset strategy, and feed back the re-scanning result to the evaluation module for the evaluation module to determine whether to continue to correct or to archive. That is, if the evaluation module evaluates that the image quality meets the preset requirement, the track is archived, otherwise, the correction and evaluation confirmation are continued according to the blur type and degree.

[0076] The prompting module is configured to prompt abnormal information when the abnormality that cannot be overcome after the re-scanning action performed by the correction module occurs in the scanned image.

[0077] The archiving module is configured to end the scanning process at the current time and store the scanned image when the qualified scanned image is obtained.

[0078] It should be understood that, for the device embodiment, since it basically corresponds to the method embodiment, the relevant part can be referred to the part of the method embodiment. The device embodiment described above is only illustrative, wherein the modules described as separate components can or can not be physically separated, and the components displayed as modules can or can not be physical modules, i.e., can be located in one place or distributed to multiple modules. Part or all of the modules can be selected to achieve the purpose of the present disclosure according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0079] Accordingly, please refer to Figure 4 The present application also discloses a slice scanning device, comprising a processor and a memory, the memory stores computer executable instructions capable of being executed by the processor, and the processor executes the computer executable instructions to realize the method as described above.

[0080] Accordingly, the present application also discloses a computer readable storage medium, the computer readable storage medium stores computer executable instructions, and the computer executable instructions, when called and executed by a processor, prompt the processor to realize the method as described above.

[0081] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device, equipment and medium described above can refer to the corresponding process in the foregoing method embodiment, which will not be described here.

[0082] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. Computer-usable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to: phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0083] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, devices, and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0084] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0085] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operation steps are performed on the computer or other programmable devices to generate a computer-implemented process, thus the instructions executed on the computer or other programmable devices provide a process for implementing the functions specified in the flowchart Figure 1 one or more flows and / or blocks Figure 1 one or more blocks or several blocks.

[0086] It should be noted that the use of any of the terms "first", "second" or the like does not indicate any order, quantity or importance, but is used to distinguish one element from another. The terms "comprises", "comprising", "includes", "including" or "contains", "containing" are inclusive, i.e. they indicate that the elements specified after the word "comprises", "comprising", "includes", "including", "contains" or "containing" are not exhaustive, but can be supplemented by other elements. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The word "one" does not exclude the presence of more than one element or quantity. The terms "primarily", "mainly", "essentially" or the like indicate that the feature or feature group concerned is essential for the invention, but that the invention can also be implemented without this feature or feature group. The use of the word "if" does not indicate any preference.

[0087] Although the preferred embodiments of the application have been described, those skilled in the art will be able to make additional changes and modifications without departing from the spirit and scope of the application. Therefore, the appended claims are intended to cover all such changes and modifications that fall within the scope of the application.

[0088] Obviously, many modifications and variations of the present application are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

[0089] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative expressions of the above terms should not be understood as necessarily referring to the same embodiment or example. Also, the specific features, structures, materials or characteristics described can be combined in any suitable manner in one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples without contradiction.

[0090] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and are not to be construed as limiting the present application, and that variations, modifications, substitutions and changes can be made by those skilled in the art without departing from the scope of the present application.

Claims

1. A method of digital rescan of a slice, characterized in that, Comprising: S1, acquiring a scanning image of a digital slice, judging the image quality, if it meets the preset requirement, executing S6, otherwise, executing S2; S2, judging the defect type of the scanning image quality, if it is overall blur, executing S3; if it is local blur, executing S4; S3, remodeling the scanning according to the first preset strategy, judging the image quality of the remodeled scanning image, if it meets the preset requirement, executing S6; otherwise, judging the defect type of the scanning image quality, if it is still overall blur, executing S5, if it is local blur, executing S4; S4, remodeling the scanning according to the second preset strategy, judging the image quality of the remodeled scanning image, if it meets the preset requirement, executing S6; otherwise, executing S5; S5, outputting a quality abnormality prompt; S6, image archiving; In S3, the first preset strategy comprises judging whether the focal plane position of the model point is higher than the reference position by a first position threshold value, if yes, setting the upper limit of the focusing range of the model point as the difference between the focal plane position of the original model point and the first position threshold value; If no, setting the upper and lower limits of the docking range of the model point as the reference position plus and minus a second position threshold value, the second position threshold value being smaller than the first position threshold value.

2. The digital slice rescan method of claim 1, wherein: In S2, the number of blurred fields of view is acquired, if the number of blurred fields of view is less than a blur evaluation threshold value, it is determined to be local blur; otherwise, it is determined to be overall blur.

3. The digital slice rescan method of claim 1, wherein, In S4, the second preset strategy comprises: S41, judging the severity of the local blur, if it is severe blur, executing S42, otherwise, executing S43; S42, identifying the tissue area and the cover glass area, judging whether there is a tissue area outside the cover glass area, if yes, executing step S43; if no, executing step S45; S43, limiting the scanning area to the tissue area within the cover glass area, remodeling the scanning, judging the image quality, if it meets the preset requirement, executing S6, otherwise, executing S44; S44, judging the severity of the local blur, if it is severe blur, executing S5, if it is slight blur, executing S45; S45, on the basis of the original model point, adding a model point in the blurred area, remodeling the scanning, judging the image quality of the remodeled scanning image, if it meets the preset requirement, executing S6; otherwise, executing S5.

4. The digital slice rescanning method of claim 3, wherein, In S45, before executing S5, it further comprises S46: querying the number of blurred fields of view, if the number of blurred fields of view is greater than a preset value, adopting a stop-and-go mode to automatically focus on each field of view; Or, adopting an extended depth of field mode to scan.

5. The digital slice rescanning method of claim 3, wherein: Acquiring a focus factor, if the value of the focus factor is less than a first focus threshold value, it is determined to be severe blur; if the value of the focus factor is greater than or equal to the first focus threshold value, but less than a second focus threshold value, it is determined to be slight blur.

6. The digital slice rescanning method of claim 1, wherein: In the process of scanning the digital slice, S1-S6 are executed synchronously.

7. A slice scanning apparatus for carrying out the method according to any one of claims 1 to 6, characterized in that Comprising: An acquisition module, configured to acquire a scanning image of a digital slice; An evaluation module is configured to evaluate the quality of the scanned image, and determine whether the defect of the scanned image is a global blur or a local blur; A correction module is configured to perform a re-scanning action according to a first preset strategy and / or a second preset strategy based on the evaluation result of the evaluation module, and feed back the result of the re-scanning to the evaluation module for determining whether to continue the correction or to archive; An archiving module is configured to end the scanning process at the current time and store the scanned image when a qualified scanned image is obtained.

8. A slice scanning apparatus characterized by: A processor and a memory are included, the memory stores computer executable instructions which can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer readable storage medium stores computer executable instructions, and the computer executable instructions, when invoked and executed by a processor, cause the processor to implement the method according to any one of claims 1 to 6.

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