Shanghai United Imaging Healthcare Co., Ltd.

Yuhang Shi

Hui Liu

Zheng Zhang

Tuoyu Cao

Tingrong Shi

Xinyuan Xia

Jiaxu Zheng

Yang Xin

Guobin Li

Qiang He

Lingzhi Hu

Jie Lu

Guoguang Zhao

Lixiang Hu

Jun'an Zheng

Yanxia Chen

The present disclosure directs to a system and method for automated positioning of a subject. The method may include obtaining a scout image of a subject when the subject is positioned at a first position in an apparatus. The method may also include determining location information of a reference structure of the subject based on the scout image. The method may also include determining an offset between the first position of the subject relative to a characteristic point of the apparatus according to the location information of the reference structure. The method may further include moving the subject to a second position based on the offset. The method may still further include performing, using the apparatus, a procedure relating to a target structure of the subject located at the second position.

System and method for medical imaging

A method may include obtaining an image of an object; obtaining a target artifact identification model; determining target artifact feature information by inputting the image into the target artifact identification model, the target artifact feature information indicating a feature of one or more artifacts in the image; obtaining a target artifact extent determination model; determining target artifact extent indication information by inputting the image and the target artifact feature information into the target artifact extent determination model, the target artifact extent indication information indicating an influence extent of the one or more artifacts on an image quality of the image; in response to determining that the influence extent is greater than or equal to the extent threshold, outputting a notice of the one or more artifacts of the image.

Systems and methods for image processing

The present disclosure provides a system and method for image data acquisition. The method may include acquiring physiological data of a subject. The physiological data may correspond to a motion of the subject over time. The method may include obtaining a trained machine learning model configured to detect feature data represented in the physiological data. The method may include determining, based on the physiological data, an output result of the trained machine learning model that is generated based on the feature data. The method may include acquiring, based on the output result, image data of the subject using an imaging device.

Systems and methods for image data acquisition

A method for controlling a medical device may be provided. The method may include obtaining, via one or more cameras, first data regarding a first motion of a subject in an examination space of the medical device. The method may include obtaining, via one or more radars, second data regarding a second motion of the subject. The method may further include generating, based on the first data and the second data, a control signal for controlling the medical device to scan at least a part of the subject.

Systems and methods for controlling imaging

A method for magnetic resonance imaging (MRI) may include obtaining a magnetic resonance (MR) image of a subject, wherein the MR image may be acquired based on a first MRI device and include at least one region of interest (ROI) of the subject. The method may also include selecting, based on the MR image and an ROI determination model, a portion of a main magnetic field generated by the first MRI device. The selected portion of the main magnetic field may correspond to the at least one ROI. The method may also include performing a magnetic field homogenization operation on the selected portion of the main magnetic field.

Systems and methods for magnetic resonance imaging

The present disclosure relates to systems and methods for evaluating a medical image. The systems and methods may obtain the medical image. The systems and methods may extract a feature of the medical image. The feature may include a histogram of oriented gradients (HOG) feature of the medical image. The systems and methods may determine a degree to which an artifact in the medical image affects recognition of a tissue feature by inputting the feature of the medical image to a determination model.

Systems and methods for evaluating medical image

The present disclosure relates to systems and methods for determining a motion of an object during imaging. The systems and methods may cause a light emission device to project a structured light onto the object, and cause a light reception device to detect light resulting from the structured light as projected onto the object and generate a plurality of measured images of the structured light based on the detected light. The systems and methods may further determine the motion of the object based on the plurality of measured images of the structured light and a reference image of the structured light.

Systems and methods for determining motion of an object in imaging

The present disclosure provides a system and method for image generation. The method may include obtaining a first image of a first modality including a complete representation of a subject, obtaining a second image of a second modality including a partial representation of the subject, obtaining a trained machine learning model, generating an synthesized second image including a complete representation of the subject using the trained machine learning model based on the first image and the second image.

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Shanghai, China

Yuhang Shi