Abstract: Systems and methods for determining at least one scanning parameter for a scanning by an imaging device (110) are provided. The methods may include obtaining a scout image of at least one portion of a subject (502), and determining, in the scout image, a region of interest (ROI) corresponding to the at least one portion of the subject (504). The methods may further include determining, based on the ROI, the at least one scanning parameter associated with the at least one portion of the subject for performing the scanning by the imaging device (506). Systems and methods for evaluating a scanning parameter are further provided. The methods may include determining a scanning parameter associated with the ROI (1606) and obtaining a reference scanning parameter associated with the ROI (1608). The methods may further include determining whether the scanning parameter needs to be adjusted by comparing the scanning parameter and the reference scanning parameter (1610).

Abstract: The disclosure relates to systems and methods for image processing. A trained deep learning model may be determined. An input image may be acquired. A processing result may be generated by processing the input image based on the trained deep learning model. The trained deep learning model may be obtained according to a process including: acquiring a preliminary deep learning model; acquiring a sample image; generating a plurality of sub-images based on the sample image; and training the preliminary deep learning model based on the plurality of sub-images to obtain the trained deep learning model.

Abstract: The disclosure relates to systems and methods for image processing. A trained deep learning model may be determined. An input image may be acquired. A processing result may be generated by processing the input image based on the trained deep learning model. The trained deep learning model may be obtained according to a process including: acquiring a preliminary deep learning model; acquiring a sample image; generating a plurality of sub-images based on the sample image; and training the preliminary deep learning model based on the plurality of sub-images to obtain the trained deep learning model.

Abstract: The disclosure relates to systems and methods for image processing. A trained deep learning model may be determined. An input image may be acquired. A processing result may be generated by processing the input image based on the trained deep learning model. The trained deep learning model may be obtained according to a process including: acquiring a preliminary deep learning model; acquiring a sample image; generating a plurality of sub-images based on the sample image; and training the preliminary deep learning model based on the plurality of sub-images to obtain the trained deep learning model.

Abstract: Systems and methods for determining at least one scanning parameter for a scanning by an imaging device (110) are provided. The methods may include obtaining a scout image of at least one portion of a subject (502), and determining, in the scout image, a region of interest (ROI) corresponding to the at least one portion of the subject (504). The methods may further include determining, based on the ROI, the at least one scanning parameter associated with the at least one portion of the subject for performing the scanning by the imaging device (506). Systems and methods for evaluating a scanning parameter are further provided. The methods may include determining a scanning parameter associated with the ROI (1606) and obtaining a reference scanning parameter associated with the ROI (1608). The methods may further include determining whether the scanning parameter needs to be adjusted by comparing the scanning parameter and the reference scanning parameter (1610).

Abstract: The disclosure relates to systems and methods for image processing. A trained deep learning model may be determined. An input image may be acquired. A processing result may be generated by processing the input image based on the trained deep learning model. The trained deep learning model may be obtained according to a process including: acquiring a preliminary deep learning model; acquiring a sample image; generating a plurality of sub-images based on the sample image; and training the preliminary deep learning model based on the plurality of sub-images to obtain the trained deep learning model.

Abstract: A method and system for image processing is provided. The technique includes acquiring data related to the processing, performing a pre-processing of the data, performing a segmentation of a subject, performing a post-processing of the result of the segmentation and managing storage of the data. The post-process includes a calibrating and a rendering of the data.

Abstract: A method and system for image processing is provided. The technique includes acquiring data related to the processing, performing a pre-processing of the data, performing a segmentation of a subject, performing a post-processing of the result of the segmentation and managing storage of the data. The post-process includes a calibrating and a rendering of the data.