Relevance feedback measuring method based on the fuzzy region characteristics of medical images

A medical image and fuzzy feature technology, applied in the field of image processing, can solve problems such as the inability to achieve optimal mapping, achieve good segmentation results, and improve the speed of calculation.

Inactive Publication Date: 2009-12-23
SOUTHERN MEDICAL UNIVERSITY
View PDF0 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Some researchers used the AdaBoost method to realize the fuzzy region feature correlation feedback algorithm, but this method can only realize the weight adjustment between different features, but cannot realize the optimal mapping within the feature.

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
  • Relevance feedback measuring method based on the fuzzy region characteristics of medical images
  • Relevance feedback measuring method based on the fuzzy region characteristics of medical images
  • Relevance feedback measuring method based on the fuzzy region characteristics of medical images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] A feedback measurement method based on the classification and recognition of medical image fuzzy area features, such as figure 1 As shown, it specifically includes the following steps:

[0028] Step 1, read in medical images from the hospital PACS system, and use Gaussian filtering to preprocess the input images to reduce the influence of noise on image processing, and then through linear transformation (I-I min )×255 / (I max -I min ) transforms the gray value of all pixels into the range of 0 to 255, where I is the gray value of the image, and I min is the minimum value of image grayscale, I max is the maximum value of image grayscale;

[0029] Step 2, use the EM algorithm of the parameter-restricted Gaussian mixture model to segment all medical images in the medical database, and divide them into several regions, where the parameter-restricted Gaussian mixture model is as follows:

[0030] f ( x | ...

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 relevance feedback measuring method based on the classification and recognition of the fuzzy region characteristics of medical images, comprising the following steps: (1) cutting all medical images which are selected from a medical image database; (2) extracting hard characteristics of each cut region; (3) converting the hard characteristics into fuzzy characteristics which are stored into a character database; (4) selecting one medical image to be compared and extracting fuzzy characteristics of the medical image to be compared , and obtaining the fuzzy similarity of the medical image to be compared and medical images in the characteristic database, arraying the medical images the characteristic database according to the value of the fuzzy similarity, and outputting M images from high value to low value; (5) bringing the fuzzy characteristics of the M once output images into feedback treatment based on the fuzzy similarity to calculate, calculating the similarity of the medical images to be compared and all medical images in the characteristics database again, and outputting N images from high value to low value sequentially. The feedback measuring method can effectively pick needed medical images.

Description

technical field [0001] The invention relates to an image processing method, in particular to a correlation feedback measuring method based on classification and identification of medical image fuzzy area features. Background technique [0002] With the increasingly wide application of medical digital imaging equipment in clinical practice, the technology of electronic medical records and picture archiving communication system (PACS) continues to develop, and a large amount of image data is generated every day in clinical practice (the image data of larger hospitals is more than 10G per day. many). How to effectively organize, manage and output medical images is an urgent problem to be solved. In clinical practice, in the diagnosis of undiagnosed clinical images and in the teaching browsing research, if the diagnosed image with the same content as the lesion image can be found through the output technology, the reliability of clinical diagnosis and data collection will be gr...

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): G06F17/30
Inventor 江少锋冯前进秦安陈武凡
Owner SOUTHERN MEDICAL UNIVERSITY
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