Abstract: The present disclosure provides a medical imaging system and method. The method may include obtaining a machine learning model and preliminary training data of at least one sample subject. The method may also include generating training input data by processing the preliminary training data, the preliminary training data being superior to the training input data with respect to a data quality parameter. The method may further include determining a trained machine learning model by training the machine learning model based on the training input data and the preliminary training data, the preliminary training data being configured as training target data of the machine learning model.

Abstract: 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.

Abstract: 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.

Abstract: A method for generating image processing models is provided. The method is implemented on a computing device having at least one processor and at least one storage device. The method includes obtaining sample medical images corresponding to a plurality of tracer types; clustering the plurality of tracer types into a plurality of tracer clusters based on the sample medical images, each tracer cluster including one or more tracer types of the plurality of tracer types; for each tracer cluster, generating an image processing model corresponding to the tracer cluster by training an initial image processing model using first sample medical images of the sample medical images, the first sample medical images corresponding to the one or more tracer types in the tracer cluster.

Abstract: 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.

Abstract: The disclosure relates to a multifunctional water-based coating and its preparation method. The coating consists of a surface-grafted flower-ball-shaped nano cuprous oxide, nano lithium silicate, a water-based acrylic emulsion, a wetting agent, a defoaming agent and a dispersing agent. The flower-ball-shaped nano cuprous oxide is etched by introducing a bacterial liquid and is subjected to surface modification by using a silane coupling agent, titanium dioxide, silicon dioxide, etc., so as to improve the performances of the coating layer such as fouling resistance, strength, dispersibility, ageing resistance and insolation resistance. The coating of the disclosure has multiple functions, a wide application range and a long service life, and can be used for surface protection of marine facilities, coastal buildings and coastal steel structures. The materials used are cheap and easy to obtain, have no pollution to the environment, and are suitable for large-scale production.

Abstract: A system and method for image reconstruction are provided. A first region of an object may be determined. The first region may correspond to a first voxel. A second region of the object may be determined. The second region may correspond to a second voxel. Scan data of the object may be acquired. A first regional image may be reconstructed based on the scan data. The reconstruction of the first regional image may include a forward projection on the first voxel and the second voxel and a back projection on the first voxel.

Abstract: 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.

Abstract: 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.

Abstract: The present disclosure provides a system and method for image reconstruction and processing. The method may include obtaining image data of an object acquired by an imaging device. The method may include determining one or more regions of interest (ROIs) of the object. The method may also include determining, based on each ROI of the one or more ROIs, a target portion of the image data corresponding to the ROI among the image data. The method may further include reconstructing, based on the target portion of the image data, one or more images of the ROI.

Abstract: Embodiments of the present disclosure provide an image processing method, a system, an apparatus, and a storage medium thereof. The image processing method may include obtaining a phantom image and a normalization standard and performing a first processing on the phantom image. The method may also include generate a recovery coefficient of the processed phantom image generated by the first processing; determining whether the recovery coefficient satisfies the normalization standard and in response to determining that the recovery coefficient satisfies the normalization standard, obtaining a target processing parameter. The target processing parameter is a processing parameter of the first processing when the recovery coefficient satisfies the normalization standard. The method may further include determining an image processing result by processing an image to be processed based on the target processing parameter.

Abstract: A system and a method for PET imaging may be provided. Scan data of an object collected by a PET scan over a scan time period may be obtained. A plurality of target sets of scan data may be determined from the scan data based on a preset condition. Each of the plurality of target sets of scan data may correspond to a target sub-time period in the scan time period. One or more intermediate images corresponding to one or more sub-time periods different from the plurality of target sub-time periods in the scan time period may be generated based on the plurality of target sets of scan data. A target image sequence of the object may be generated based on the plurality of target sets of scan data and the one or more intermediate images.

Abstract: The present disclosure provides a system and method for image reconstruction and processing. The method may include obtaining image data of an object acquired by an imaging device. The method may include determining one or more regions of interest (ROIs) of the object. The method may also include determining, based on each ROI of the one or more ROIs, a target portion of the image data corresponding to the ROI among the image data. The method may further include reconstructing, based on the target portion of the image data, one or more images of the ROI.

Abstract: Embodiments of the present disclosure provide a medical image processing method, system, and storage medium. The method includes determining a plurality of images of regions of interest (ROIs) based on a first image of a subject; determining a plurality of second images based on the plurality of images of the ROIs and image processing models corresponding to the plurality of images of the ROIs; and performing a fusion operation based on the plurality of second images to obtain a target image.

Abstract: The present disclosure relates to systems and methods for image processing. The methods may include obtaining a first image of a subject; generating a first intermediate image based on the first image, the first intermediate image including feature information of the first image; and generating, based on a weighted fusing of the first intermediate image and at least one reference image, a target image of the subject. The at least one reference image may include at least one of the first image or a second intermediate image associated with the first image, the second intermediate image including lower noise than the first image. In the weighted fusing, different portions of the first intermediate image and/or the at least one reference image have different weights.

Abstract: The present disclosure provides systems and methods for medical imaging. The system may obtain a scout image of a subject lying on a scanning table. The scanning table may include N portions corresponding to N bed positions of a target scan, and an ith portion of the N portions may correspond to an ith bed position of the N bed positions. For the ith bed position, the system may determine one or more body parts of the subject located at the ith portion of the scanning table based on the scout image; and determine at least one scanning parameter or reconstruction parameter corresponding to the ith bed position based on the one or more body parts of the subject.

Abstract: The present disclosure provides a system and method for medical imaging. The method may include obtaining scanning data of a subject acquired using a scanner. The method may also include determining a reconstruction parameter of an objective function based at least in part on the scanning data, wherein the reconstruction parameter includes one or more global components that control an image quality over an entire image to be reconstructed and one or more local components that control the image quality over a portion of the image to be reconstructed. The method may further include generating the image of the subject by reconstructing the scanning data based on the objective function.

Abstract: A system and method for image reconstruction are provided. A first region of an object may be determined. The first region may correspond to a first voxel. A second region of the object may be determined. The second region may correspond to a second voxel. Scan data of the object may be acquired. A first regional image may be reconstructed based on the scan data. The reconstruction of the first regional image may include a forward projection on the first voxel and the second voxel and a back projection on the first voxel.

Abstract: An imaging method may include obtaining original imaging data of an object in a raw-data domain including original time of flight (TOF) information. The method may also include gating the original imaging data into a plurality of data sets in the raw-data domain. The method may also include determining a plurality of motion vector fields based on the plurality of data sets. The method may also include generating corrected imaging data in the raw-data domain by performing motion correction on at least one of the plurality of data sets based on the original TOF information and at least one corresponding MVF of the plurality of MVFs. The method may also include generating one or more target images of the object by performing, based on the corrected imaging data, image reconstruction.