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

Method and system for recognizing force line by using neural network, storage medium and electronic equipment

A neural network and recognition technology, applied in the field of medical technology related to the Ming Dynasty, can solve problems such as patient lesions and surgical failures

Active Publication Date: 2021-12-31
LANCET ROBOTICS CO LTD
View PDF15 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

If the calibration of the force line is inaccurate, it may cause the patient to cause lesions again during the postoperative recovery process, and even lead to the complete failure of the entire operation

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
  • Method and system for recognizing force line by using neural network, storage medium and electronic equipment
  • Method and system for recognizing force line by using neural network, storage medium and electronic equipment
  • Method and system for recognizing force line by using neural network, storage medium and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] Exemplary embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The exemplary embodiments described below and illustrated in the accompanying drawings are intended to teach the principles of the invention and enable those skilled in the art to implement and use the invention in a number of different environments and for a number of different applications. Therefore, the protection scope of the present invention is defined by the appended claims, and the exemplary embodiments are not intended and should not be considered as a limiting description of the protection scope of the present invention.

[0022] refer to Figure 9 According to the present invention, there is provided a method and system for segmenting femur and tibia images using deep learning and determining the position of force lines according to medical definitions on this basis, so as to improve the accuracy of subsequent operations. The specific...

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 method and a system for assisting in recognizing a force line by using a neural network, which can be used for detecting the force line before and after an operation, assisting the operation and knowing the postoperative recovery condition. The method comprises the steps that CT file sequence rows are combined into a complete three-dimensional image, then slicing is carried out on a coronal plane to obtain a first image, the first image is input into a first multi-classification segmentation neural network based on unet and using a softmax activation function to carry out different classification on a femoral and a tibia, and therefore, a femoral model and a tibia model are segmented at one time; and a femoral head center point on the femoral model is searched by using a second segmentation neural network to determine the force line, wherein other key physiological points, namely a femoral knee joint center point, a tibia knee joint center point and a tibia ankle joint center point, are calculated based on the point cloud. The first image is subjected to a bilinear quantization process such that downward quantization can also be performed while upward interpolation is performed by a bilinear interpolation.

Description

technical field [0001] The present invention relates to the field of medical technology, that is, the field of computer-aided planning technology for joint replacement and the technical field of medical image data processing. More specifically, it involves a method based on image reconstruction, deep learning, and numerical algorithms to calibrate the line of force, especially redesigning a different deep learning marking scheme based on the coronal plane. Background technique [0002] With the rapid development of modern society, all walks of life have begun to have an inseparable connection with the IT industry, and the same is true for the medical industry. Determining the position of the force line is very important in assisted knee arthroplasty by surgical robot, which can determine the success of the operation and the postoperative recovery status of the patient. If the calibration of the force line is not accurate, it may cause the patient to re-introduce the lesion ...

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): G06T7/00G06T17/00G06K9/62G06N3/04A61B34/10A61B34/30
CPCG06T7/0012G06T17/00A61B34/10A61B34/30G06T2207/10081G06T2207/30008A61B2034/101A61B2034/107A61B2034/105G06N3/045G06F18/2431
Inventor 黄志俊刘金勇钱坤范昕
Owner LANCET ROBOTICS CO LTD
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