Breast ultrasonic image multi-classification system and method based on cross correlation characteristics

An ultrasound image and classification system technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problems of artifact signal-to-noise ratio, low diagnostic results, and low image quality

Active Publication Date: 2017-11-17
NORTHEASTERN UNIV
View PDF5 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, medical ultrasound images are coherent images. Compared with mammography X-ray images, CT, and MRI, there are still de

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
  • Breast ultrasonic image multi-classification system and method based on cross correlation characteristics
  • Breast ultrasonic image multi-classification system and method based on cross correlation characteristics
  • Breast ultrasonic image multi-classification system and method based on cross correlation characteristics

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] The system and method for multiple classification of breast ultrasound images based on cross-correlation features of the present invention will be described with reference to the accompanying drawings.

[0047] Such as figure 1Shown is the structural block diagram of the breast ultrasound image multiple classification system based on cross-correlation features of the present invention, the classification system includes: ultrasound image preprocessing unit 1, region of interest extraction unit 2, internal cross-correlation density feature extraction unit 3, traditional feature Extraction unit 4 and multi-class classification unit.

[0048] Ultrasound image preprocessing unit 1 is used for the original mammary gland ultrasound image set (P 1 ,P 2 ...,P n Each image in ) is enhanced and denoised. The region of interest extracting unit 2 utilizes the region growth segmentation method to extract the lesion region in each image after denoising processing as the region of...

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 provides a breast ultrasonic image multi-classification system and method based on cross correlation characteristics. The system comprises an ultrasonic image preprocessing unit; an interest area extraction unit used for extracting an image of an interest area; an internal cross correlation density feature extraction unit used for extracting an internal cross correlation density characteristic value of an interest image; a conventional feature extraction unit used for extracting a plurality of conventional characteristic values of the interest area image; and a multi-classification unit used for training classifiers, inputting an internal cross correlation density characteristic value vector and conventional characteristic vectors to three trained classifiers for classification, and regarding the category with the most prediction as a final classification result. According to the classification method, the internal cross correlation density characteristic based on the interest area is additionally provided, the auxiliary diagnosis effect of a breast ultrasonic computer can be effectively improved, the classification category of galactocele which is the benign lesion is added, and the requirement of a breast ultrasonic computer auxiliary system by doctors is further met.

Description

technical field [0001] The invention belongs to the technical field of post-processing of medical images, and in particular relates to a system and method for multiple classification of breast ultrasound images based on cross-correlation features. Background technique [0002] Breast disease is one of the more common diseases in modern women, and breast cancer is a common female malignant tumor. In terms of incidence, breast cancer ranks first among female malignant tumors in Europe and the United States, and ranks second in China. It has become an important disease that affects women's physical and mental health. Regarding the differentiation of benign and malignant breast masses, imaging methods undoubtedly play an important role. Imaging examinations such as mammography, CT, MRI, and ultrasound all have an important impact on the diagnosis and differentiation of breast masses. Among them, with the update of equipment and the development of technology, more and more atten...

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): G06K9/62G06T5/00G06T7/00G06T7/11
CPCG06T5/002G06T7/0012G06T7/11G06T2207/10132G06T2207/20036G06T2207/20081G06T2207/20104G06T2207/30068G06F18/2321G06F18/2431
Inventor 王之琼高小松曲璐渲黄玉坤赵越
Owner NORTHEASTERN 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