An Image Processing Method Based on Adaptive Fast Iterative Shrinkage Threshold Algorithm

An iterative shrinkage threshold and image processing technology, applied in the field of image processing, can solve the problem of inapplicable iterative process, and achieve the effect of less error points, more local details, and accurate reconstruction

Inactive Publication Date: 2021-04-13
NANJING MEDICAL UNIV
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Problems solved by technology

[0006] However, the above algorithm is based on the fact that the shrinkage factor has been reduced by a fixed step in iterations, which does not apply to the entire iteration process

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  • An Image Processing Method Based on Adaptive Fast Iterative Shrinkage Threshold Algorithm
  • An Image Processing Method Based on Adaptive Fast Iterative Shrinkage Threshold Algorithm
  • An Image Processing Method Based on Adaptive Fast Iterative Shrinkage Threshold Algorithm

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Embodiment 1

[0100] Different MR images of various parts of the human body, including MR images of the human head, blood vessels, and knee joints, are used as experimental images. The MR images used for testing were acquired on a 1.5T Philips Achieva magnetic resonance at Jiangsu Provincial People's Hospital using an 8-channel receiver coil with gradient echo sequences with the following parameters in Table 1.

[0101] In this embodiment, q=2 in formula (25), in this application, use three parameters to be used for evaluating reconstruction quality: mean square error (MSE), peak signal-to-noise ratio (PSNR) structured similarity (SSIM) . MSE reflects the degree of difference between the estimated value and the original value. PSNR represents the ratio of the maximum possible power of the signal to the noise power. SSIM is a measure of the similarity of two images from brightness, contrast and structural information. Compared with PSNR, it is more in line with human visual characteristic...

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Abstract

The invention discloses an image processing method based on an adaptive fast iterative shrinkage threshold algorithm, which includes eight steps to reconstruct the original image. Compared with the existing three algorithms, the images obtained by this method can show more local details and clearer outlines; produce fewer error points and provide more accurate reconstruction; the convergence speed is fast, and it has a comparative advantage. Other methods have higher iteration efficiency; it has stability for image reconstruction of different parts.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an image processing method based on an adaptive fast iterative shrinkage threshold algorithm. Background technique [0002] Magnetic resonance (MR) imaging is a safe, fast and accurate image acquisition technique. It has the advantages of multiple directions, parameters and modes, and is harmless to the human body. It can display anatomical and functional information of human tissue. MR imaging has a wide range of applications. However, the scanning time of MR imaging is long, the scanning speed is slow, and the image may be blurred due to the movement of organs, which cannot provide dynamic real-time images and navigation. Therefore, the shortcomings of MR imaging limit the promotion of functional imaging and cause additional pain to users. [0003] To this end, technicians in this field have done in-depth research and proposed the theory of compressed sensing: when the sampl...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/10088G06T2207/20056
Inventor 王伟吴小玲姚庆强朱松盛周宇轩刘宾
Owner NANJING MEDICAL UNIV
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