Computed tomography aortic aneurysm auxiliary diagnosis method based on deep learning

A technology of tomography and deep learning, applied in computer-aided medical procedures, neural learning methods, medical automated diagnosis, etc., to achieve good diagnostic capabilities, enhance film reading and decision-making capabilities, and improve overall strength

Active Publication Date: 2021-08-06
JILIN UNIV
View PDF15 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Previous studies have ignored the problem that t

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Computed tomography aortic aneurysm auxiliary diagnosis method based on deep learning
  • Computed tomography aortic aneurysm auxiliary diagnosis method based on deep learning
  • Computed tomography aortic aneurysm auxiliary diagnosis method based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0041] The auxiliary diagnosis method of computerized tomography aortic aneurysm based on deep learning includes the following steps: Step 1: Data collection, firstly, a plurality of ordinary CT scans with aorta are collected retrospectively from the hospital area, and the data are continuous Acquisition, including diagnostic imaging reports and examinations, all acquired images are in DICOM format, including information such as the age, gender, and multiple CT parameters of the patient. In the clinical workflow, the postoperative situation of the aortic stent will be determined by the receiving department In this case, radiologists will pay more attention to the risk of aortic disease in these groups, so that the possibility of missed diagnosis is relatively small. In order to ensure that the aorta of all study subjects is clearly visible on CT scans, In order to more effectively evaluate the effectiveness of auxiliary diagnostic tools, the following data inclusion and exclusi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the technical field of aortic aneurysm auxiliary diagnosis, and particularly relates to a deep learning-based computed tomography aortic aneurysm auxiliary diagnosis method, which comprises the following steps of: 1, data acquisition: firstly, retrospectively collecting a plurality of common CT scans with aorta from a hospital area of a hospital; 2, data processing: dividing the data into three data sets: a training set, an internal test set and an external test set; and 3, establishing a model, constructing an auxiliary diagnosis tool by using an Attention-Unet convolutional neural network, evaluating the risk, detection sensitivity, specificity and accuracy of the aortic aneurysm in a test set by using the auxiliary diagnosis tool. The method is reasonable in design and has good diagnosis capability on aortic aneurysm; when the method is used in combination with radiologists, the film reading and decision-making capabilities of the radiologists can be remarkably enhanced, and the overall strength of imaging departments is improved. Therefore, the performance of the advanced technology proves that the non-invasive, cheap and convenient method has the potential of clinical tests.

Description

technical field [0001] The invention relates to the technical field of auxiliary diagnosis of aortic aneurysm, in particular to an auxiliary diagnosis method of computerized tomography based on deep learning for aortic aneurysm. Background technique [0002] The aorta is the largest artery in the body. Due to the important position of the aorta in the human body, diseases related to it often endanger the lives of patients. With the development and popularization of imaging diagnostic equipment such as computed tomography (CT), the number of aortic aneurysm cases discovered has increased significantly in recent years, which has attracted the attention of clinicians. Aortic aneurysms mainly include abdominal aortic aneurysm (AAA), thoracic aortic aneurysm confined to the thoracic cavity, and thoracoabdominal aortic aneurysm (TAAA), which grow in both the thoracic and abdominal cavities to account for 5 of all aortic aneurysms. %the following. It has been reported that 50% o...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G16H50/20G16H15/00G06T7/00G06T7/62G06N3/04G06N3/08
CPCG16H50/20G16H15/00G06T7/0012G06T7/62G06N3/08G06T2207/10081G06T2207/20081G06T2207/20084G06T2207/30101G06N3/045
Inventor 黄萨陈鹏李佳明刘威武韩林
Owner JILIN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap