Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Rib fracture image detection method based on small sample deep learning

A deep learning and rib fracture technology, applied in the field of rib fracture image detection, can solve the unseen problems of deep learning in rib fracture detection and achieve the effect of reducing demand

Pending Publication Date: 2021-03-16
NEIJIANG NORMAL UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] However, there is no application of deep learning in rib fracture detection in the above research results

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
  • Rib fracture image detection method based on small sample deep learning
  • Rib fracture image detection method based on small sample deep learning
  • Rib fracture image detection method based on small sample deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] Slight rib fractures are easy to be ignored. To solve this problem, the present invention proposes a deep learning model for image detection of rib fractures based on the YOLO-v3 model and using transfer learning methods to process small samples. This method uses a small amount of labeled rib CT images as the data of the input layer, performs transfer learning based on the fine-tuned Yolo-v3 model, and finally conducts deep learning training. The model needs to deal with fewer samples and has a wider range of applications in practice. The final experiment shows that the method requires fewer iterations and obtains high accuracy, thereby improving the accuracy of rib fracture image detection and providing a good basis for doctors' diagnosis.

[0021] Below in conjunction with accompanying drawing, the method of the present invention is described in detail as follows:

[0022] Such as figure 1 As shown, a rib fracture image detection method based on small-sample deep le...

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 discloses a rib fracture image detection method based on small sample deep learning. The method comprises the following steps: step 1, marking a collected rib fracture CT image; 2, performing feature extraction by adopting a YOLOv3 model; 3, carrying out transfer learning on the extracted feature vectors; and 4, carrying out deep learning training. Compared with the prior art, the method has the positive effects that a YOLOv3 model is provided, small samples are processed by means of a transfer learning method, and a deep learning model for rib fracture image detection is established. According to the method, few rib CT images are used as data of an input layer for deep learning training, the obtained effective rate is high, and therefore a small sample deep learning model can be established, and a good basis is provided for diagnosis of doctors.

Description

technical field [0001] The invention discloses a rib fracture image detection method based on small-sample deep learning. Background technique [0002] Rib fracture is one of the common traumas, and its diagnosis mainly depends on imaging examination. Clinical imaging methods for rib fractures mainly include DR examination and multi-slice spiral CT examination. DR is currently the preferred method for the examination of chest injuries. It is widely used in the routine examination of rib fractures due to its low cost, simple operation, and low radiation dose. The missed diagnosis rate is high. Multi-slice spiral CT transverse or oblique scanning is also applied to the diagnosis of rib fractures. However, due to the large number of ribs and the irregular shape, CT examination has defects such as inaccurate counting and limited scope. The 2D and 3D reconstructions of SCT and MSCT have been widely used in the diagnosis of bone diseases, including the diagnosis of rib fractur...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06N3/08G06T2207/20081G06T2207/20084G06T2207/10081G06T2207/30008G06V2201/03G06N3/045G06F18/253
Inventor 李甫孔花吴开腾陈泓杏余文春张莉周丹李季
Owner NEIJIANG NORMAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com