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Classification method, apparatus and device, and storage medium

A classification method and target classification technology, applied in the field of data processing, can solve the problems of segmentation error, target part classification influence, loss of detail information, etc.

Pending Publication Date: 2020-12-18
SHENZHEN INST OF ADVANCED TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above-mentioned reconstructed image has the problem of blurring, resulting in the loss of some detailed information, and this lost information is very important for the classification of target parts in the later stage
In addition, the segmentation of the region of interest on the image will often lead to segmentation errors, which will eventually affect the classification of the target part.

Method used

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  • Classification method, apparatus and device, and storage medium
  • Classification method, apparatus and device, and storage medium
  • Classification method, apparatus and device, and storage medium

Examples

Experimental program
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Embodiment 1

[0023] figure 1 It is a flowchart of a classification method provided by Embodiment 1 of the present invention. This embodiment is applicable to the case of classifying target parts based on magnetic resonance technology. This method can be performed by a classification device, specifically through the classification device. implemented in software and / or hardware. Such as figure 1 As shown, the method of this embodiment specifically includes:

[0024] S110. Acquire magnetic resonance K-space data corresponding to the current target site of the subject.

[0025] The basic principle of magnetic resonance imaging is: put the object to be scanned into a magnetic field, and generate an excitation magnetic field by applying radio frequency pulses, so that the hydrogen protons in the target part of the object to be scanned resonate and produce energy level transitions. After stopping the application of radio frequency pulses, The resonant hydrogen protons will release energy and ...

Embodiment 2

[0035] figure 2 It is a flowchart of a classification method provided by Embodiment 2 of the present invention. In this embodiment, on the basis of the above-mentioned embodiments, before inputting the magnetic resonance K-space data into the trained target classification model, it may also include: matching the magnetic resonance K-space data with zero padding or data retention. The matrix size of the first matrix is ​​adjusted to a preset size to obtain a second matrix that can be processed by the classification model, and the data corresponding to the second matrix is ​​used as the magnetic resonance K-space data input to the target classification model. Further, the optional data retention method is starting from the center data of the first matrix, and sequentially retaining the data in the rows and columns from the inside to the outside, wherein, if the rows and columns of the first matrix are both odd numbers, then the first matrix The central data of is one, if the r...

Embodiment 3

[0064] image 3 It is a structural schematic diagram of a sorting device in Embodiment 3 of the present invention. Such as image 3 As shown, the device of this embodiment includes:

[0065] A magnetic resonance K-space data acquisition module 310, configured to acquire magnetic resonance K-space data corresponding to the target part of the current subject;

[0066] The classification module 320 is configured to input the magnetic resonance K-space data into the trained target classification model to obtain the first classification result corresponding to the target part, wherein the target classification model includes a classification model trained based on supervised learning .

[0067] A classification device provided in this embodiment uses the magnetic resonance K-space data acquisition module to obtain the magnetic resonance K-space data corresponding to the target part of the current subject, and uses the classification module to input the magnetic resonance K-space...

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Abstract

The embodiment of the invention discloses a classification method apparatus and device, and a storage medium, and the method comprises the steps: obtaining magnetic resonance K space data corresponding to a target part of a current detected body; and inputting the magnetic resonance K space data into a trained target classification model to obtain a first classification result corresponding to thetarget part, with the target classification model comprising a classification model trained based on a supervised learning mode. According to the technical scheme of the embodiment of the invention,the classification accuracy of the target part is improved.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of data processing, and in particular to a classification method, device, equipment and storage medium. Background technique [0002] Medical magnetic resonance is more and more used in clinical examination due to its ability to provide a variety of contrast information, good soft tissue imaging capabilities, and no ionizing radiation. [0003] The current process of using magnetic resonance data to classify target parts is as follows: image preprocessing; region of interest segmentation; feature extraction, selection and classification. Among them, preprocessing refers to correcting image distortion caused by noise or motion artifacts, normalizing the image, denoising and increasing contrast, etc. to enhance the display quality of the image; after preprocessing, image segmentation is performed, and the sense The region of interest is separated from the background or surrounding ti...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06V2201/03G06F18/24G06F18/214G06F18/00
Inventor 梁栋朱燕杰程静刘新郑海荣
Owner SHENZHEN INST OF ADVANCED TECH