Shanghai United Imaging Intelligence Co., Ltd.

Shanghai United Imaging Healthcare Co., Ltd.

Chen Xi

Yang Lyu

Shuhui Chen

The present disclosure relates to systems and methods for image processing. The systems may acquire imaging data. The systems may generate multiple intermediate images based on the imaging data by performing image optimization of multiple image optimization dimensions using a plurality of trained machine learning models. The systems may generate a target image based on the intermediate images.

Systems and methods for image processing

The present disclosure provides a system and method for image reconstruction. The method may include obtaining training samples, the training samples including at least one sample first image generated based on a first tracer, at least one reference first image each of which corresponds to one of the at least one sample first image and has a higher image quality than the corresponding sample first image, at least one sample second image generated based on a second tracer different from the first tracer, and at least one reference second image each of which corresponds to one of the at least one sample second images and has a higher image quality than the corresponding sample second image; and generating a trained image processing model by training a preliminary model using the training samples.

System for image correction in PET is provided. The system may acquire a PET image and a CT image of a subject. The system may generate, based on the PET image and the CT image, an attenuation-corrected PET image of the subject by application of an attenuation correction model. The attenuation correction model may be a trained cascaded neural network including a trained first model and at least one trained second model downstream to the trained first model. During the application of the attenuation correction model, an input of each of the at least one trained second model may include the PET image, the CT image, and an output image of a previous trained model that is upstream and connected to the trained second model.

Systems and methods for image correction in positron emission tomography

The present disclosure provides a system for image reconstruction. The system may obtain an initial image of a subject. The initial image may be generated based on scan data of the subject that is collected by an imaging device. The system may also generate a gradient image associated with the initial image. The system may further generate a target image of the subject by applying an image reconstruction model based on the initial image and the gradient image. The target image may have a higher image quality than the initial image.

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Shanghai, China

Chen Xi