Method and system for identifying and processing noise tag in medical image

Abstract

The invention belongs to the technical field of medical images, and discloses a method for identifying and processing a noise label in a medical image map, which comprises a noise label identification and noise processing method, and the noise identification part comprises the following specific operation steps: S1, determining the size of a shot picture, and converting the size of the picture into the size of a standard drawing through picture scanning; according to the method, an image scanning and recognition means is mainly adopted for noise recognition, the whole content is divided into a plurality of small blocks, one point is randomly selected from each small block for recognition sampling, and equipment judges the overall condition in a mode of combining region division and internal random points; in the part, internal random point imaging information can be obtained by utilizing an established snowflake point noise mathematical model, the accuracy degree of the obtained internal random point imaging information is proved by further combining a noise distribution probability model, and the current equipment scanning effect is judged by utilizing noise point information.

Description

technical field [0001] The invention belongs to the technical field of medical imaging, in particular to a method and system for identifying and processing noise labels in medical imaging images. Background technique [0002] Image noise refers to unnecessary or redundant interference information existing in image data, similar to snowflakes on old-fashioned TV screens. The existence of noise seriously affects the quality of the image. Image noise can be simply understood as the noise on the image. "Grainy", the more obvious the "grainy", the stronger the noise of the image, such as Figure 4 On the surface, we can clearly see that the noise in the right image is higher than that in the left image, the “graininess” in the right image is heavier, and the image is blurred. Noise will cause CT to be unable to distinguish the lesion, so this part will affect the subsequent use, which is not conducive to the correct judgment of the doctor. [0003] Existing medical imaging equip...

AI Technical Summary

Problems solved by technology

[0002] Image noise refers to the unnecessary or redundant interference information existing in the image data, similar to the snowflakes on the old-fashioned TV screen, the existence of noise seriously affects the quality of the image, and the noise of the image can be simply understood as the noise on the image. "Graininess", the more obvious the "graininess" is, the stronger the noise of the image, such as Figure 4 As shown on the surface, we can clearly see that the noise of the right image is higher than that of the left image. The right image has a heavier "graininess" and the image is blurred. Noise will cause CT to be unable to distinguish this lesion, so this part will affect the subsequent use, which is not conducive to the doctor's correct judgment

[0003] Existing medical imaging equipment basically has noise when it is used, but because of the difference between the reason and the actual work, the situation of noise generation is also different. For example, the patient's body thickness will obviously affect the scanning recognition. Different equipment has different implementation standards. In the existing technology, the causes of noise in most medical imaging images are summarized. The only thing that is lacking is targeted adjustment. At this time, it is subject to experience and actual conditions. Unclear impact, medical staff will inevitably have some disadvantages when using it

Images