CT Image Reconstruction Method Based on MRI

Abstract

The invention discloses an MRI-based CT image reconstruction method, comprising the following steps: 1) using a deep learning network to reconstruct the MRI, training the deep learning network, obtaining under-sampled k-space data of an object to be measured, and converting the object to be measured The undersampled k-space data is input to the trained deep learning network to obtain the online MRI of the object to be measured; 2) using a bidirectional generative adversarial network to reconstruct a CT image from the MRI. The present invention has the following advantages: (1) MRI imaging speed is fast; (2) has a wide range of applications, can be used for lung imaging, and can also be used for imaging other parts of the human body; (3) CT images are obtained by MRI reconstruction, avoiding the need for CT (4) The reconstructed CT images can also be used for radiotherapy planning and PET attenuation correction.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to an MRI-based CT image reconstruction method. Background technique [0002] COVID-19 is highly contagious and has a high fatality rate. Early detection, early diagnosis, early treatment, and early isolation are currently the most effective means of prevention and treatment. Compared with various limitations of nucleic acid examination, CT (computed tomography) examination is timely, accurate, fast, with a high positive rate, and the extent of lung lesions is closely related to clinical symptoms. Therefore, it has become the main reference for early screening and diagnosis of patients with new coronavirus pneumonia in accordance with. According to the diagnosis and treatment plan for novel coronavirus pneumonia (Trial Sixth Edition), multiple small patchy shadows and interstitial changes appeared in the early stage of new coronary pneumonia, especially in the extr...

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