Medical ultrasonic image denoising method based on statistical model

Abstract

The invention provides a medical ultrasonic image denoising method based on a statistical model. The medical ultrasonic image denoising method comprises the following steps that step 1) a medical ultrasonic image model is established; step 2) wavelet decomposition is performed on an image after logarithmic transformation obtained in the first step so that four frequency domains (LL1, LH1, HL1 and HH1) are obtained; wavelet decomposition is continuously performed on the low frequency domain LL1 and then four frequency domains (LL2, LH2, HL2 and HH2) are obtained; and then the step is repeated until the maximum number J of layers of decomposition; step 3) threshold method contraction processing is performed on the wavelet coefficient of the high frequency part (LHj, HLj and HHj, j=1,2,...,J) of each layer; step 4) filtering processing is performed on the wavelet coefficient in the low frequency part (LLJ) of the last layer by utilizing a guidance filter; and step 5) wavelet inverse transformation processing is performed so that a denoised medical ultrasonic image is obtained.

Description

technical field [0001] The invention is applied in the field of medical image denoising. Background technique [0002] In the field of medical imaging, imaging technologies such as ultrasound imaging, CT, and MRI have been applied in medical clinical diagnosis. The application of ultrasonic diagnosis as a diagnostic technique in medical diagnosis began with the advent of gray-scale ultrasound in 1972. Especially in recent years, ultrasonic diagnosis has been widely used in medical clinical diagnosis, mainly because: [0003] 1) Ultrasound is non-ionizing radiation, which is harmless to the human body and can visually display the morphology and structure of human organs and tissues; [0004] 2) Ultrasound has a high resolution ability for human soft tissue; [0005] 3) It can observe the functional activities of human organs in real time; [0006] 4) Ultrasonic imaging equipment is easy to operate, easy to use, and cheap. [0007] Therefore, ultrasound imaging technology ...

AI Technical Summary

Problems solved by technology

[0016] (2) In the field of medical image denoising, traditional methods are in full bloom, but these methods are not perfect, mainly in the loss of image details while denoising

[0019] (5) In terms of practical application, due to the limitation of hospital resources, especially the number of patients manually diagnosed by doctors every day cannot meet the needs of the entire social class, that is, there are many patients and few doctors.

Among the latest denoising methods, many iterative methods have emerged as the times require. Although they have strong denoising capabilities, they are often based on a large number of iterations, and the corresponding calculation time will be relatively long. Suitable for real-time imaging systems

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