Unlock instant, AI-driven research and patent intelligence for your innovation.

A large-scale medical image retrieval method based on multi-core hash learning

A medical image, large-scale technology, applied in the field of image processing, can solve the problems of low retrieval speed, high image dimension, large image scale, etc., and achieve the effect of reducing workload, reducing storage space, and small storage capacity

Active Publication Date: 2019-11-12
CHONGQING UNIV OF POSTS & TELECOMM
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The invention proposes a large-scale medical image retrieval method based on multi-core hash learning based on the problems of high image dimension, complex calculation, and the problem of "dimension disaster"; large image scale, low retrieval speed, and large storage capacity.

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
  • A large-scale medical image retrieval method based on multi-core hash learning
  • A large-scale medical image retrieval method based on multi-core hash learning
  • A large-scale medical image retrieval method based on multi-core hash learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] In the present invention, appropriate kernel functions are selected for combination, data are mapped to high-dimensional data space, the problem of linear inseparability is solved, and the problem of "dimension disaster" existing in the operation of high-dimensional feature space is solved by using kernel technology.

[0028] Different kernel functions have their own advantages and disadvantages, different kernel functions exhibit different characteristics, and the performance of the combined kernel functions formed by them will also be different.

[0029] Kernel functions are mainly divided into global kernel functions and local kernel functions. Global kernel functions (such as linear kernel functions) have global characteristics, allowing data points that are far apart to have an impact on the value of the kernel function, while local kernel functions (such as Gaussian kernel functions) are local and only allow data points that are very close Data points have an infl...

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 multi-kernel hash learning-based large-scale medical image retrieval method. The method concretely comprises the steps of: constructing a kernel matrix through fusion of a plurality of different kernel functions; completely converting an image into hash codes by use of the learned hash function, and carrying out compression on the hash codes; solving distances of medical images through hamming distance measurement, sorting according to an ascending order, selecting m images with minimum distances to be returned to a user; optimizing the sorting of the retrieved images again by the user by use of a relevance feedback algorithm until the sorting satisfies the requirement of the user. The method is high in calculation efficiency, rapid in retrieval speed, small in memory space, high in retrieval precision, clear in steps and strong in pertinence, contributes to medical diagnosis of a doctor, reduces the workload of the doctor and improves the working efficiency.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to the realization of large-scale medical image retrieval through hash learning of multi-kernel function fusion. Background technique [0002] Image retrieval technology refers to retrieving matching images or similar images from the image database according to the input image. There are three main aspects of existing technologies: image retrieval technology based on text, image retrieval technology based on content, and retrieval technology combining text and image. The main limitation of text-based technology lies in the subjective tendency and semantic limitations of text annotation. [0003] Content-based image retrieval technology is the mainstream technology of current research, but there are some technical difficulties: (1) There is no universally applicable method that can be applied to various fields of image retrieval; (2) Images are getting larger and more dim...

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 Patents(China)
IPC IPC(8): G06F16/583G06F16/51
CPCG06F16/51G06F16/583
Inventor 曾宪华袁知洪马雪
Owner CHONGQING UNIV OF POSTS & TELECOMM