Methods and apparatus for medical image reconstruction using machine learning based processes

Abstract

Machine learning based systems and methods for improving attenuation and scatter correction and for estimating organ volume in medical images are disclosed. In some embodiments, a co-modality image, a non-attenuated corrected nuclear image, and an x-ray image are received. A first machine learning process is applied to the co-modality image to generate location data identifying feature locations. Further, a second machine learning process is applied to the non-attenuated corrected nuclear image, the x-ray image, and the location data to generate a segmentation mask. In addition, at least a third machine learning process is applied to the segmentation mask, the co-modality image, the non-attenuated corrected nuclear image, and the x-ray image to generate a plurality of synthetic images. Moreover, at least a fourth machine learning process is applied to the plurality of synthetic images to generate a final synthetic image.