The present invention relates to an improved method and system for simulating and constructing original actual Magnetic Resonance Images MRI from first modality of a patient to second modality, wherein the system is configured to receive an input MRI image taken in first modality, pre-process the input MRI image, send the processed image to a Convolutional Neural Network (CNN), and obtain the new constructed MRI images in second modality that are identical at the pixel level to the actual image as captured by the MRI machines.
FIELD OF THE INVENTION
The present invention generally relates to automated analysis (i.e. simulating and constructing) of medical images i.e. Magnetic Resonance Images (MRI), Computed Tomography (CT) images, Ultrasound Images, Positron Emission Tomography Images, Single-Photon Emission Computed Tomography Images are the like. More particularly, the present invention relates to an improved method and system for simulating and constructing original actual Magnetic Resonance Images MRI from first modality of a patient to second modality.
The study of the human body and its connection to human activities has been of interest to scientists for centuries. Medical imaging methods have been developed to allow a visualization of the human body in recent years. Magnetic Resonance Imaging (MRI) is such a technique that provides a noninvasive way to view the structure of the human body.
The subject invention provides improved method and system for simulating and constructing actual MRI images in second modality from a source or actual MRI image of a patient taken in first modality.
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