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

Initial sketch based stomach CT (Computed Tomography) image lymph node detection system

A technology for CT images and lymph nodes, applied in the field of image processing, can solve the problems of high false alarm rate of lymph nodes, long use time, and inaccurate location of lymph node boundaries, so as to achieve accurate extraction, improve processing speed, and reduce false alarm rate.

Active Publication Date: 2016-03-16
XIDIAN UNIV
View PDF4 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is based on the grayscale features of the pixels in the CT image, so it takes a long time, and because the shape of the lymph node is similar to an ellipse, the boundary location of the lymph node is not particularly accurate, and the false alarm rate in the finally detected lymph node high

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
  • Initial sketch based stomach CT (Computed Tomography) image lymph node detection system
  • Initial sketch based stomach CT (Computed Tomography) image lymph node detection system
  • Initial sketch based stomach CT (Computed Tomography) image lymph node detection system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] The technical scheme of the present invention and effect are described in detail below in conjunction with accompanying drawing:

[0046] refer to figure 1 , the detection system of the present invention includes: a gray value statistics module 1, a sketch line preprocessing module 2, an adaptive window determination module 3 based on the sketch line, a suspected lymph node image block sequence extraction module 4, and a lymph node detection based on row and column cut images Module 5, Low Rank Decomposition Module 6, Centroid Tracking Module 7, Sketch Line Labeling Module 8. in:

[0047] The gray value statistical module 1 is used to divide each pair of CT images in the original CT sequence diagram into four categories by the otsu classification algorithm, and count the gray value range of each class respectively, according to the gray value from small to The largest order is the gray value range of the background, the gray value range of the fat, the gray value rang...

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

PropertyMeasurementUnit
Angleaaaaaaaaaa
Login to View More

Abstract

The present invention discloses an initial sketch based stomach CT (Computed Tomography) image lymph node detection system. The detection system comprises eight functional modules: a gray-scale value statistic module collects statistics of gray-scale values of pixel points in a CT image; a sketch line pre-processing module performs pre-processing on sketch lines; a sketch line based adaptive window determining module is an adaptive window for extracting the sketch lines; a suspected lymph node image block sequence extracting module extracts an image block sequence based on the sketch lines and the adaptive window; a line-row sectional drawing based lymph node detection module tracks and determines a suspected lymph node, the image block sequence of which is greater than 11*11; a low rank decomposition module and a centroid tracking module track and determine a suspected lymph node, the image block sequence of which is not greater than 11*11; and a sketch line marking module marks the sketch lines enclosed by the tracked suspected lymph nodes as processed. According to the initial sketch based stomach CT image lymph node detection system provided by the present invention, sketch information of the CT image is used, so that the lymph node detection speed is improved and the false alarm rate is reduced, and the system cab be applicable to medical image processing.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an image detection system, which can be used for lymph node detection and auxiliary diagnosis of medical images. Background technique [0002] Due to the good visual properties of CT images, CT images have been widely used in the medical field. In the medical diagnosis of CT images, doctors find pathogens by observing a series of two-dimensional slice images, that is, the current analysis of CT image information mainly relies on doctors' own experience. However, with the rapid development of medical imaging technology, the number of CT images taken for each person is increasing day by day. Relying solely on doctors to process these images will lead to an increase in the workload of doctors. With the rapid development of computer technology and image processing technology, the information in CT images can be processed by computer, so that doctors do not need to spend a l...

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): G06T7/00G06T7/60
CPCG06T7/0012G06T2207/10081G06T2207/20012G06T2207/30092
Inventor 刘芳李婷婷王敏焦李成郝红侠尚荣华马文萍马晶晶
Owner XIDIAN UNIV
Features
  • Generate Ideas
  • 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