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 problems such as unsuitable iterative process, and achieve the effect of less error points, more local details, and accurate reconstruction
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[0101] 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.
[0102] 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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