CT image blind denoising method based on multiple scales and attention mechanism

Abstract

The invention discloses a CT (Computed Tomography) image blind denoising method based on multiple scales and an attention mechanism. The method specifically comprises the following steps of 1, performing feature fusion; step 2, weight distribution; step 3, de-noising processing is carried out; step 4, comparing and screening; the invention relates to the technical field of image processing. According to the CT image blind denoising method based on the multiple scales and the attention mechanism, the attention mechanism is used for weight redistribution, feature maps with more sufficient key detail feature expression are output, assistance is provided for noise level authentication, effective collection of feature maps of different levels of noise is achieved through sampling processing of the different levels of noise, and the accuracy of denoising of the CT image blind denoising method based on the multiple scales and the attention mechanism is improved. When the CT image to be denoised is denoised, the noise of the corresponding level can be accurately and effectively retrieved, then the denoising model matched with the noise can be selected, the definition of the denoised CT image is ensured, the training burden of the image feature set is effectively reduced in cooperation with the setting of the residual network, and a good guarantee is provided for the denoising robustness of the CT image.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a CT image blind denoising method based on multi-scale and attention mechanism. Background technique [0002] In the process of digitization and transmission, digital images in reality are often affected by the interference of imaging equipment and external environmental noise, which are called noisy images or noisy images. Image denoising refers to the process of reducing noise in digital images. [0003] Most medical CT images are grayscale images with blurred boundaries, noise, and poor contrast. Therefore, traditional feature representation methods are difficult to capture the subtle differences in their features. The same tissue is difficult for different patients, different modalities, and different imaging equipment. There are certain differences in the images, and there may even be differences between different frames of the same modality. [0004] Conventional ...

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Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the present invention provides a CT image blind denoising method based on a multi-scale and attention mechanism, which solves the problem that the determination of different noise levels is relatively simple, the corresponding noise level cannot be effectively identified, and often cannot be accurately determined. Select the corresponding denoising model for denoising processing, resulting in poor denoising effect of the final CT image

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