Image compression method for medical image storage

A medical image and image compression technology, applied in the field of image processing, can solve the problems of insufficient intelligence and low efficiency of medical image compression, and achieve the effect of intelligent methods

Active Publication Date: 2022-05-24
中国医学科学院阜外医院深圳医院
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The present invention provides an image compression method for medical image storage to solve the problems of

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  • Image compression method for medical image storage
  • Image compression method for medical image storage
  • Image compression method for medical image storage

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Embodiment Construction

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0044] An embodiment of an image compression method for medical image storage of the present invention, such as figure 1 shown, including:

[0045] Step 1: Collecting medical images, and extracting regions of interest of the medical images;

[0046] The purpose of this step is to obtain the core area of ​​the medical image, the area of ​​interest in medical treatment.

[0047] Among them, the method of extracting the region of inte...

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Abstract

The invention relates to the field of image processing, in particular to an image compression method for medical image storage, which comprises the following steps of: acquiring a medical image, extracting a region of interest, obtaining adjacency according to the gray difference and variance of each edge pixel point of the region of interest and eight neighborhood pixel points of the region of interest; edge pixel points needing to be expanded are determined according to an adjacency threshold value, external expansion is carried out through continuous iteration, an expanded area is obtained, the combined variance of the expanded area and the combined variance of the residual area are obtained through the gray values of the pixel points of the interested area, the pixel points of the expanded area and the pixel points of the residual area, and a random area in the residual area is determined; wavelet coefficients of random regions in the region of interest, the expanded region and the remaining regions and other regions in the remaining regions are obtained through the mask algorithm, embedded zero-tree wavelet coding is carried out in sequence, image compression is completed, and the method is intelligent and efficient.

Description

technical field [0001] The present application relates to the field of image processing, in particular to an image compression method for medical image storage. Background technique [0002] A large number of people seek medical treatment in a hospital, and a large number of medical images are often generated. Such a large number of medical images have very high requirements for data compression, transmission and preservation. Massive medical image storage often becomes one of the problems that hospitals urgently need to solve. The quality of image storage is related to the personal health of patients, so how to improve the storage efficiency under the premise of ensuring the quality of the relevant data is one of the problems that continue to be solved. [0003] The current research on related technologies is mostly aimed at improving the overall image compression method, or the related compression method based on template matching. The degree of intelligence is not strong ...

Claims

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Application Information

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IPC IPC(8): H04N19/182H04N19/63
CPCH04N19/182H04N19/63
Inventor 石瑀韩桂圆刘黎香
Owner 中国医学科学院阜外医院深圳医院
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