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4k medical image processing method

A medical image and processing method technology, applied in the field of image processing, can solve the problems of slow processing speed and poor noise reduction effect, and achieve the effect of ensuring processing speed and improving computing efficiency

Active Publication Date: 2022-07-12
THE AFFILIATED HOSPITAL OF QINGDAO UNIV
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  • Claims
  • Application Information

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Problems solved by technology

[0007] Aiming at the technical problems of slow processing speed and poor noise reduction effect in the prior art for 4K ultra-high-definition medical image processing, the present invention proposes a 4K medical image processing method, which can solve the above problems

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  • 4k medical image processing method

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Embodiment 1

[0049] This embodiment proposes a 4K medical image processing method, such as figure 2 shown, including:

[0050] Obtain a medical image frame of a preset type. For the original image obtained in this step, see image 3 shown;

[0051] A dividing step, dividing the medical image frame into several sub-images;

[0052] Perform gradient calculation on the sub-images in parallel to obtain the gradient matrix of each sub-image;

[0053] combining the gradient matrices of all sub-images into a total gradient matrix according to the positions of the sub-images in the original medical image frame;

[0054]The secondary segmentation step is to perform gradient feature analysis on the total gradient matrix, and divide the medical image frame into several regions according to the analysis results. The schematic diagram of this step can be found in Figure 4 As shown, it is divided into several regions such as A, B, C, and D according to the gradient feature;

[0055] Perform filte...

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Abstract

The invention discloses a 4K medical image processing method, which includes: acquiring a medical image frame of a preset type; dividing the medical image frame into several sub-images in one segmentation step; calculating the gradient of the sub-images in parallel to obtain the gradient of each sub-image Matrix; the gradient matrices of all sub-images are combined into a total gradient matrix according to the position of the sub-images in the medical image frame; in the secondary segmentation step, the gradient feature analysis is performed on the total gradient matrix, and the medical image frame is divided into several parts according to the analysis results. Each area is filtered and noise-reduced in parallel to obtain a processed image. The 4K medical image processing method of the present invention improves computing efficiency by means of parallel computing. Especially for the processing of ultra-high-definition medical image frames, the processing speed is guaranteed. It can also prevent edge information from being filtered out during filtering, and can retain more detailed features of medical image frames.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular, relates to a 4K medical image processing method. Background technique [0002] With the advent of the era of intelligence, the performance of most medical products is also developing in the direction of intelligence, and the role of medical-grade images is becoming more and more obvious. It is an indispensable device for minimally invasive surgery and medical endoscopic systems because of the difficulty of surgery and the improvement of the success rate of surgery. [0003] Medical-grade images use 4K resolution, which belongs to ultra-high-definition resolution, and can obtain internal tissue images of the human body or a certain part of the human body in a non-invasive manner. It contains the following two relatively independent research directions: medical imaging and medical image processing. The former refers to the process of image formation, including research...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06T5/00
CPCG06T7/11G06T2207/20021G06T2207/20032G06T5/70
Inventor 于腾波马金龙王德勇赵海波陈进利卢罗宗时春峰
Owner THE AFFILIATED HOSPITAL OF QINGDAO UNIV