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Method, system and equipment for detecting cell stack in microscopic image and medium

A microscopic image and detection method technology, applied in the field of image processing and medical pathological image processing, can solve problems such as uneven tissue smearing in difficult microscopic images, and achieve the effect of improving the intelligence, accuracy and quality of diagnosis

Active Publication Date: 2020-07-03
SHANGHAI XINGMAI INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a detection method, system, equipment and medium for cell stacking in a microscopic image, which is used to solve the problem that it is difficult to smear tissue in a microscopic image in the prior art. Uniformity causes the problem of cell stacking for effective analysis and judgment

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  • Method, system and equipment for detecting cell stack in microscopic image and medium
  • Method, system and equipment for detecting cell stack in microscopic image and medium
  • Method, system and equipment for detecting cell stack in microscopic image and medium

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Embodiment 1

[0044] Such as figure 1 As shown, this embodiment provides a method for detecting cell stacking in a microscopic image, and the method for detecting cell stacking in a microscopic image includes the following steps:

[0045] Step S100, acquiring microscopic pathological images;

[0046] Step S200, calculating at least one image definition feature value of the micropathological image;

[0047] Step S300, judging whether the micropathological image is partially blurred according to the image definition feature value: if not, execute step S600; if yes, continue to execute step S400;

[0048] Step S400, segmenting the micropathological image to obtain a cell area, and detecting the edge definition of the cell area;

[0049] Step S500, judging whether the edge sharpness of the cell region is lower than the sharpness threshold: if not, execute step S600; if yes, continue to execute step S700;

[0050] Step S600, judging that there is no cell stack in the micropathological image; ...

Embodiment 2

[0157] Such as Figure 4 As shown, this embodiment provides a detection system for cell stacking in a microscopic image. The detection system for cell stacking in a microscopic image includes: an image acquisition module, an eigenvalue calculation module, a first judgment module, and a second judgment module .

[0158] In this embodiment, the image acquisition module is used to acquire microscopic pathological images.

[0159] Pathological microscopic images are but not limited to cells or tissues extracted from human lungs, thyroid glands, breasts and other human body parts for pathological microscopic diagnosis, which are made into pathological cell slides and scanned by a digital microscope. The method of obtaining human cell or tissue samples may be obtained through puncture surgery, endoscopy, or other medical means. The sample is generally made into a microscope slide and placed on the stage. In some cases, the sample slide needs to be stained to distinguish the cells ...

Embodiment 3

[0184] Such as Figure 7 As shown, this embodiment also provides an electronic device, the electronic device is but not limited to medical testing equipment, image processing equipment, etc., such as Figure 7 As shown, the electronic device processor 1101 and memory 1102; the memory 1102 is connected to the processor 1101 through a system bus and completes mutual communication, the memory 1102 is used to store computer programs, and the processor 1101 is used to run the computer programs, so that The electronic device implements the method for detecting cell stacks in microscopic images. The method for detecting cell stacks in the microscopic image has been described in detail above, and will not be repeated here.

[0185]The method for detecting cell stacks in microscopic images can be applied to various types of electronic devices. The electronic device is, for example, a controller, specifically an ARM (Advanced RISC Machines) controller, an FPGA (Field Programmable Gate...

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Abstract

The invention provides a method, a system and equipment for detecting cell stacking in a microscopic image and a medium. The method comprises the following steps: acquiring a microscopic pathologicalimage; calculating at least one image definition characteristic value of the micropathology image, and judging whether the micropathology image is partially blurred or not according to the image definition characteristic value: if not, judging that no cell stack exists in the micropathology image; if yes, segmenting the micropathology image to obtain a cell region, detecting the edge definition ofthe cell region and judging whether the edge definition of the cell region is lower than a definition threshold value or not, and if yes, judging that cell stacking exists in the micropathology image; and if not, judging that no cell stack exists in the micropathology image. According to the method, whether partial blurring exists in the microscopic pathology image or not is judged firstly, thenthe cell region is searched continuously, the definition of the internal region of the cell is judged, and the problem of cell stacking caused by uneven tissue smearing in the microscopic image can beeffectively detected.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to the technical field of medical pathological image processing, and specifically relates to a detection method, system, equipment and medium for cell stacking in a microscopic image. Background technique [0002] Image Quality Assessment (IQA), IQA can be divided into subjective assessment and objective assessment from the method. Subjective evaluation is to evaluate the image quality from the subjective perception of people. First, the original reference image and the distorted image are given, and the annotators are asked to rate the distorted image. Generally, the mean subjective score (Mean Opinion Score, MOS) or the mean subjective score difference ( Differential Mean Opinion Score, DMOS) said. Objective evaluation uses mathematical models to give quantitative values, and image processing technology can be used to generate a batch of distorted images, which is easy t...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/13G06T7/11G06K9/62
CPCG06T7/0012G06T7/13G06T7/11G06T2207/10056G06T2207/20081G06T2207/30004G06T2207/30168G06F18/2148G06F18/24
Inventor 叶德贤房劬姜辰希
Owner SHANGHAI XINGMAI INFORMATION TECH CO LTD
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