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Pulmonary embolism detection system, medium and electronic equipment

A detection system and pulmonary embolism technology, applied in the field of medical detection, can solve the problems of easy misdiagnosis, inaccurate results, and low execution efficiency, and achieve the effects of enhancing extraction ability, preventing overfitting, and improving accuracy.

Active Publication Date: 2021-05-25
SHAN DONG MSUN HEALTH TECH GRP CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The inventor found that due to the low incidence of pulmonary embolism, most hospitals still rely on doctors to observe, which is less efficient and prone to misdiagnosis; and the increasing incidence of pulmonary embolism makes doctors overwhelmed, and the traditional machine learning algorithm , the execution efficiency is low and the results are not accurate enough, which cannot meet the needs of auxiliary diagnosis

Method used

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  • Pulmonary embolism detection system, medium and electronic equipment
  • Pulmonary embolism detection system, medium and electronic equipment
  • Pulmonary embolism detection system, medium and electronic equipment

Examples

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Embodiment 1

[0039] Such as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Figure 6 and Figure 7 As shown, Embodiment 1 of the present disclosure provides a pulmonary embolism detection system, comprising:

[0040] The data acquisition module is configured to: acquire CT image data and perform preprocessing;

[0041] The detection and judgment module is configured to: input the preprocessed CT image data into a preset EfficientNetB5 neural network to obtain a pulmonary embolism recognition result.

[0042] Specifically, include the following:

[0043] S1: Select the CT data with pulmonary embolism lesions, and expert doctors will carry out the data labeling work, and save the labels of each CT image in csv format, where 0 indicates normal CT images, and 1 indicates CT images containing pulmonary embolism lesions.

[0044] S2: After the preliminary labeling is completed, another group of expert doctors will review the preliminary labeling data. If the conclusion is cons...

Embodiment 2

[0058] Embodiment 2 of the present disclosure provides a computer-readable storage medium on which a program is stored, and when the program is executed by a processor, the following steps are implemented:

[0059] Acquire CT image data and perform preprocessing

[0060] Input the preprocessed CT image data into the preset EfficientNetB5 neural network to obtain the recognition result of pulmonary embolism;

[0061] Among them, the end add layers of adjacent blocks in the EfficientNetB5 neural network are skipped and connected, and the features output by each block include the features extracted in the previous block.

[0062] The detailed steps are the same as the working method of the system provided in Embodiment 1, and will not be repeated here.

Embodiment 3

[0064] Embodiment 3 of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and operable on the processor, and the processor implements the following steps when executing the program:

[0065] Acquire CT image data and perform preprocessing

[0066] Input the preprocessed CT image data into the preset EfficientNetB5 neural network to obtain the recognition result of pulmonary embolism;

[0067] Among them, the end add layers of adjacent blocks in the EfficientNetB5 neural network are skipped and connected, and the features output by each block include the features extracted in the previous block.

[0068] The detailed steps are the same as the working method of the system provided in Embodiment 1, and will not be repeated here.

[0069] Those skilled in the art should understand that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Accordingly, the...

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Abstract

The invention provides a pulmonary embolism detection system, a medium and electronic equipment, and the system comprises a data obtaining module which is configured to obtain CT image data and carry out preprocessing; a detection and judgment module configured to input the preprocessed CT image data into a preset OfficientNetB5 neural network to obtain a pulmonary embolism recognition result; wherein the end add layers of the adjacent blocks in the OfficientNetB5 neural network are connected in a jumping manner, and the features output by each block comprise the features extracted from the previous block, Whether the input CT image is a pulmonary embolism lesion or not can be automatically judged more accurately, and the fine-grained feature extraction capability of the model is improved.

Description

technical field [0001] The present disclosure relates to the technical field of medical detection, in particular to a pulmonary embolism detection system, media and electronic equipment. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] With the advancement of society and the development of science and technology, the application of medical imaging in disease diagnosis is becoming more and more extensive, and lung CT scanning is a vital part of medical imaging. Since lung CT images are usually high-definition images, and the shadow of pulmonary embolism usually only accounts for a small part of the CT image and the starting point does not necessarily appear in the first few images, this has caused great difficulties for doctors to quickly and accurately judge pulmonary embolism. little difficulty. Timely treatment is of great significanc...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06N3/04G06N3/08
CPCG06T7/0012G06N3/084G06T2207/10081G06T2207/20081G06T2207/20084G06T2207/30061G06T2207/30204G06N3/048
Inventor 樊昭磊吴军张嵩颜世舵王剑孙钊
Owner SHAN DONG MSUN HEALTH TECH GRP CO LTD
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