Abstract: In an example, a method and apparatus for obtaining an image mask is provided. After a magnitude image and a phase image of a to-be-processed image is obtained, magnitude coherent data of each pixel point in the magnitude image and phase coherent data of each pixel point in the phase image may be calculated. Then, a binarization threshold processing may be performed on the magnitude coherent data of each pixel point in the magnitude image to obtain a magnitude image mask. A binarization threshold processing may be performed on the phase coherent data of each pixel point in the phase image to obtain a phase image mask. In this way, an image mask of the to-be-processed image may be obtained by using the magnitude image mask and the phase image mask.

Abstract: Methods and apparatus, including computer programs encoded on a computer storage medium, for image reconstruction are provided. According to an example of the methods, an image reconstruction may be performed to generate a first set of reconstructed data with a first set of projection data comprising a plurality of first projection data each corresponding to a respective projection angle of a plurality of projection angles. A second set of projection data comprising second projection data for each projection angle may be generated with the first set of reconstructed data. The first set of projection data may be corrected based on a shifting distance between the first projection data and the second projection data for each projection angle. Then, a second set of reconstructed data may be generated with the corrected first set of projection data, and a reconstructed image may be generated according to the second set of reconstructed data.

Abstract: Methods and apparatus, including computer programs encoded on a computer storage medium, for image reconstruction are provided. The methods include: accessing a first set of projection data including a plurality of first projection data each corresponding to a respective projection angle of a plurality of projection angles, generating a first set of reconstructed data by image reconstruction with the first set of projection data, generating a second set of projection data comprising a plurality of second projection data each corresponding to a respective projection angle by projection calculation with the first set of reconstructed data, generating a third set of projection data by optimizing the first set of projection data based on a correlation between respective first projection data and respective second projection data corresponding to each projection angle, and generating a second set of reconstructed data by image reconstruction with the third set of projection data.

Abstract: A method of processing Magnetic Resonance Imaging (MRI) data is provided. According to an example of the method, after a set of MRI data of a subject is obtained by an MRI system, interpolation may be performed on real parts and imaginary parts of the set of MRI data, respectively, to obtain real part interpolation results and imaginary part interpolation results. Interpolation is performed on amplitudes of the set of MRI data to obtain amplitude interpolation results. Target interpolation results are determined with the real part interpolation results, the imaginary part interpolation results and the amplitude interpolation results. Then, an MRI image of the subject is reconstructed with the target interpolation results.

Abstract: Methods and apparatus, including computer programs encoded on a computer storage medium, for image reconstruction are provided. According to an example of the methods, an image reconstruction may be performed to generate a first set of reconstructed data with a first set of projection data comprising a plurality of first projection data each corresponding to a respective projection angle of a plurality of projection angles. A second set of projection data comprising second projection data for each projection angle may be generated with the first set of reconstructed data. The first set of projection data may be corrected based on a shifting distance between the first projection data and the second projection data for each projection angle. Then, a second set of reconstructed data may be generated with the corrected first set of projection data, and a reconstructed image may be generated according to the second set of reconstructed data.

Abstract: Methods and apparatus, including computer programs encoded on a computer storage medium, for image reconstruction are provided. The methods include: accessing a first set of projection data including a plurality of first projection data each corresponding to a respective projection angle of a plurality of projection angles, generating a first set of reconstructed data by image reconstruction with the first set of projection data, generating a second set of projection data comprising a plurality of second projection data each corresponding to a respective projection angle by projection calculation with the first set of reconstructed data, generating a third set of projection data by optimizing the first set of projection data based on a correlation between respective first projection data and respective second projection data corresponding to each projection angle, and generating a second set of reconstructed data by image reconstruction with the third set of projection data.

Abstract: In an example, a method and apparatus for obtaining an image mask is provided. After a magnitude image and a phase image of a to-be-processed image is obtained, magnitude coherent data of each pixel point in the magnitude image and phase coherent data of each pixel point in the phase image may be calculated. Then, a binarization threshold processing may be performed on the magnitude coherent data of each pixel point in the magnitude image to obtain a magnitude image mask. A binarization threshold processing may be performed on the phase coherent data of each pixel point in the phase image to obtain a phase image mask. In this way, an image mask of the to-be-processed image may be obtained by using the magnitude image mask and the phase image mask.