CT angiography image classification method suitable for Lee's artificial liver treatment

An angiography and artificial liver technology, applied in the field of medical image recognition, can solve problems such as limiting the efficiency of Lee's artificial liver treatment, critical illness, etc., and achieve the effect of improving prediction ability, reducing the influence of interference factors, and ensuring the effect of classification

Pending Publication Date: 2022-07-29
ZHEJIANG UNIV
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Problems solved by technology

Among them, patients with liver failure are often in critical condition and the disease progresses rapidly, and doctors need to spend a lot of time artificiall...

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  • CT angiography image classification method suitable for Lee's artificial liver treatment
  • CT angiography image classification method suitable for Lee's artificial liver treatment
  • CT angiography image classification method suitable for Lee's artificial liver treatment

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Embodiment 1

[0038] Embodiment 1. The CT angiography image segmentation method suitable for Lee's artificial liver treatment, as shown in the appendix Figure 1-7 shown, including the following steps:

[0039] S1, data collection and preprocessing

[0040] The data collection and construction of CT angiography related to liver failure in the study were carried out. The data collection was mainly obtained through the cooperation of relevant medical units in Zhejiang Province. These data were obtained from the liver CT image data of the desensitized patients in the hospital. All patient image data were converted into JPG format image format, and the converted patient image data in JPG format were manually classified and marked by medical experts according to whether they were suitable for Li's artificial liver treatment. The specific data set information is shown in Table 1 below:

[0041]Table 1. Data set of CT angiography images

[0042] data set CT angiography images n...

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Abstract

The invention discloses a CT angiography image segmentation method suitable for Lee's artificial liver treatment, and the method comprises the steps: obtaining a liver CT angiography image, carrying out the data enhancement processing of the liver CT angiography image in an upper computer, inputting an obtained image into a CT angiography image segmentation network, and obtaining a two-dimensional segmentation result image and a classification result; the CT angiography image segmentation network comprises a UNet + + image segmentation network and a ResNet-Att image classification network; the ResNet-Att image classification network comprises a prediction network based on ResNet 50-base, and an improved Attention self-attention module is added into the prediction network. The CT angiography image segmentation method suitable for the Lee's artificial liver treatment can be effectively used for segmenting and classifying the CT images of the liver of the patient.

Description

technical field [0001] The invention relates to the field of medical image recognition, in particular to a CT angiography image classification method suitable for Lee's artificial liver treatment. Background technique [0002] Liver failure refers to the liver failure syndrome in which massive or sub-mass necrosis occurs in the liver in a short period of time caused by a variety of pathogenic factors. Due to large or sub-large necrosis in the liver, the disease develops very rapidly, and the fatality rate of liver failure is as high as 70%. At present, the treatment methods of liver failure mainly include comprehensive medical treatment and Li's artificial liver treatment. Li's artificial liver mainly uses the regeneration ability of liver cells and external equipment, including mechanical, physicochemical or biological devices, to remove harmful substances produced by liver failure while supplementing the essential components of the human body, stabilizing the internal env...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/10G06V10/764G06K9/62G06N3/04G06N3/08A61B6/00A61B6/03
CPCG06T7/0012G06T7/10G06N3/084A61B6/032A61B6/5211A61B6/504G06T2207/10081G06T2207/20081G06T2207/20084G06T2207/30101G06N3/045G06F18/24
Inventor 金心宇张杰龚善超
Owner ZHEJIANG UNIV
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