Supercharge Your Innovation With Domain-Expert AI Agents!

MKL-SVM-PSO algorithm-based lung nodule image processing method

An MKL-SVM, pulmonary nodule technology, applied in the field of pulmonary nodule image processing based on the MKL-SVM-PSO algorithm, can solve the problems of long search time, large amount of calculation, difficult to form an online identification algorithm, etc. Global optimal solution, the effect of fast average fitness value

Active Publication Date: 2017-10-10
CHANGCHUN UNIV OF TECH +1
View PDF8 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The existing technology has the disadvantages of large amount of calculation, long time for parameter search, poor real-time performance, and it is not easy to form an online recognition algorithm

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
  • MKL-SVM-PSO algorithm-based lung nodule image processing method
  • MKL-SVM-PSO algorithm-based lung nodule image processing method
  • MKL-SVM-PSO algorithm-based lung nodule image processing method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0038] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0039] The present invention provides a kind of pulmonary nodule image processing method based on MKL-SVM-PSO algorithm, see figure 1 ,include:

[0040] S100: Extract a region of interest from the image of a pulmonary nodule, perform feature selection on the region of interest, and obtain a data sample;

[0041] Specifically, this embodiment further explains the region of interest (ROI): in machine vision and image processing, the image to be processed is drawn in the form of a box, circle, ellipse, irregular polygon, etc. The processed area is called region of interest, ROI. In the field of image processing, a region of interest (ROI) is an image region selected from an image, and this region is the focus of image analysis. Circle ...

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 an MKL-SVM-PSO algorithm-based lung nodule image processing method. The method comprises the steps of extracting a region of interest out of a lung nodule image, performing feature selection for the region of interest, and obtaining a data sample, wherein the data sample comprises a training set for optimizing parameters and a test set for testing models; subjecting the training set of the data sample to optimization treatment based on the MKL-SVM-PSO algorithm so as to obtain an optimal parameter set, and establishing an MKL-SVM mathematical model; applying the optimal parameter set to the MKL-SVM mathematical model for recognition and calculation so as to obtain a recognition result of a lung nodule. Based on the method, the optimal parameter set of the MKL-SVM algorithm can be quickly and accurately searched, and the optimal parameter set is applied to the recognition of the lung nodule. Meanwhile, the PSO algorithm is introduced to the MKL-SVM algorithm and is applied to the benign and malignant identification of the lung nodule.

Description

technical field [0001] The present invention relates to the field, in particular to a method for processing images of pulmonary nodules based on the MKL-SVM-PSO algorithm. Background technique [0002] Pulmonary nodules usually refer to round-like dense opacities in the lungs with a diameter not greater than 3 cm, which is also an early manifestation of lung cancer on lung CT images. Computed tomography (CT) technology is an important means to detect early pulmonary nodules. According to the CT manifestations of pulmonary nodules, they can be divided into solid nodules (such as solitary nodules, adherent pulmonary nodules, adherent vascular nodules), ground glass nodules, and cavitary nodules. [0003] Lung computer-aided detection (Computer Aided Detection, CAD) system is the application of machine vision technology, which can reduce the visual fatigue of radiologists caused by super-loaded film reading, and reduce the possibility of misjudgment or missed detection. Auxil...

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): G06T7/00G06K9/32G06K9/62
CPCG06T7/0012G06T2207/30064G06T2207/20081G06T2207/10081G06V10/25G06F18/2411
Inventor 李阳张丽娟赵庆东侯阿临刘丽伟王宏志祝志川田颖
Owner CHANGCHUN UNIV OF TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com