Abstract: Systems and methods for scan preparation are provided. The systems may obtain a first parameter set of a subject to be scanned by a medical device acquired before a scan is performed on the subject. The first parameter set may relate to a physiological motion of the subject acquired before the scan is performed on the subject. The systems may predict, based on the first parameter set and an estimation model, a second parameter set of the subject. The second parameter set may relate to the physiological motion of the subject. The systems may determine at least one scan parameter for the scan based at least in part on the second parameter set. The systems may cause the medical device to perform the scan on the subject based on the at least one scan parameter.

Abstract: A method for evaluating data to be used to train an object recognition model is to be implemented by a computing device. The computing device stores a plurality of training datasets respectively related to a plurality of images, and each training dataset includes a plurality of entries of training data. The method includes steps of: obtaining, for each image, at least one target area and at least one target property that are related to the image based on the entries of training data; creating, for each image, a training material that includes the image, and the at least one target area and the at least one target property both related to the image; and obtaining at least three object recognition models based on the training materials that are created respectively for the images using at least one machine learning algorithm.

Abstract: The disclosure relates to a system and a method for generating a neural network model for image processing by interacting with at least one client terminal. The method may include receiving via a network, a plurality of first training samples from the at least one client terminal. The method may also include training a first neural network model based on the plurality of first training samples to generate a second neural network model. The method may further include transmitting, via the network, the second neural network model to the at least one client terminal.

Abstract: Systems and methods for scan preparation are provided. The systems may obtain a first parameter set of a subject to be scanned by a medical device acquired before a scan is performed on the subject. The first parameter set may relate to a physiological motion of the subject acquired before the scan is performed on the subject. The systems may predict, based on the first parameter set and an estimation model, a second parameter set of the subject. The second parameter set may relate to the physiological motion of the subject. The systems may determine at least one scan parameter for the scan based at least in part on the second parameter set. The systems may cause the medical device to perform the scan on the subject based on the at least one scan parameter.

Abstract: Systems and methods for a parameter adjustment of a multi-energy computed tomography (CT) device is provided. The systems and methods may obtain, by at least one processor, a parameter set associated with a scan to be performed using a multi-energy CT device. The parameter set may include multiple scanning parameters and multiple reconstruction parameters. The systems and methods may also determine, by the at least one processor, a maximum pitch associated with the scan based on a correlation relationship and the parameter set. The correlation relationship may describe a correlation between a pitch of the multi-energy CT device and the parameter set.

Abstract: The disclosure relates to a system and a method for generating a neural network model for image processing by interacting with at least one client terminal. The method may include receiving via a network, a plurality of first training samples from the at least one client terminal. The method may also include training a first neural network model based on the plurality of first training samples to generate a second neural network model. The method may further include transmitting, via the network, the second neural network model to the at least one client terminal.

Abstract: The present disclosure is related to systems and methods for image processing. The method includes obtaining, from a first image set of a subject acquired at a first time point, a first image; obtaining, from a second image set of the subject acquired at a second time point, a second image, wherein the first image and the second image correspond to a same region of the subject; determining a displacement vector field based on the first image and the second image; and generating a target image based on the displacement vector field, the first image set and the second image set.

Abstract: The present disclosure relates to systems and methods for image generation. The methods may include obtaining projection data generated by a scanner; generating, based on a first weighting function, a first image by back-projecting the projection data, the first image having a first region corresponding to a first part of the object; generating, based on a second weighting function, a second image by back-projecting the projection data, the second image having a second region corresponding to the first part of the object, the second region of the second image presenting a better CT number uniformity than the first region of the first image; and generating a third image based on the first image and the second image.

Abstract: The present disclosure provides methods and systems for image processing. The methods may include obtaining original projection data of a target subject. For each of at least one slice location of the target subject, the methods may include generating a plurality of candidate slice images of the slice location based on a plurality of distance-weight relationships and the original projection data. Each of the plurality of distance-weight relationships may indicate a weight of a portion of the original projection data acquired by the radiation source and a distance from the radiation source to the slice location when acquiring the portion of the original projection data. The methods may further include generating at least one target medical image of the target subject based on the plurality of candidate slice images of each of the at least one slice location.

Abstract: An illuminated keyswitch structure includes a base plate, a drive circuit board under the base plate, a spacer between the drive circuit board and the base plate, and a light-emitting part on the circuit board. The spacer has a through hole communicating with an opening of the base plate in a vertical direction. The sidewall of the through hole is opaque. The light-emitting part is located in the through hole, and falls within a projection of the opening in the vertical direction. The light-emitting part has a top surface that is lower than or equal to a bottom surface of the base plate in the vertical direction. The structure of the illuminated keyswitch structure around the light-emitting part can keep flat by the spacer. The spacer can prevent the light-emitting part from structurally entering the opening, avoiding structural interference between the light-emitting part and other components above the base plate.

Abstract: The present disclosure relates to systems and methods for image generation. The methods may include obtaining projection data generated by a scanner; generating, based on a first weighting function, a first image by back-projecting the projection data, the first image having a first region corresponding to a first part of the object; generating, based on a second weighting function, a second image by back-projecting the projection data, the second image having a second region corresponding to the first part of the object, the second region of the second image presenting a better CT number uniformity than the first region of the first image; and generating a third image based on the first image and the second image.

Abstract: The disclosure relates to a system and a method for generating a neural network model for image processing by interacting with at least one client terminal. The method may include receiving via a network, a plurality of first training samples from the at least one client terminal. The method may also include training a first neural network model based on the plurality of first training samples to generate a second neural network model. The method may further include transmitting, via the network, the second neural network model to the at least one client terminal.

Abstract: A method may include obtaining first image data relating to a region of interest (ROI) of a first subject. The first image data corresponding to a first equivalent dose level may be acquired by a first device. The method may also include obtaining a model for denoising relating to the first image data and determining second image data corresponding to an equivalent dose level higher than the first equivalent dose level based on the first image data and the model for denoising. In some embodiments, the method may further include determining information relating to the ROI of the first subject based on the second image data and ecording the information relating to the ROI of the first subject.

Abstract: The disclosure relates to a system and a method for generating a neural network model for image processing by interacting with at least one client terminal. The method may include receiving via a network, a plurality of first training samples from the at least one client terminal. The method may also include training a first neural network model based on the plurality of first training samples to generate a second neural network model. The method may further include transmitting, via the network, the second neural network model to the at least one client terminal.

Abstract: The embodiment of the present disclosure discloses a method and a system for image acquisition, image quality evaluation, and medical image acquisition. The image acquisition method comprises obtaining an image of a target subject; obtaining, based on one or more evaluation models, one or more scores related to one or more evaluation indexes of the image; obtaining a quality evaluation result of the image based on the one or more scores related to the one or more evaluation indexes; and determining one or more acquisition parameters based on the quality evaluation result.

Abstract: An illuminated keyswitch structure with an illuminating module includes a base plate, a drive circuit board under the base plate, a spacer between the drive circuit board and the base plate, and a light-emitting part on the circuit board. The spacer has a through hole communicating with an opening of the base plate in a vertical direction. The light-emitting part is located in the through hole, and falls within a projection of the opening in the vertical direction. The light-emitting part has a top surface that is lower than or equal to a bottom surface of the base plate in the vertical direction. The structure of the illuminated keyswitch structure around the light-emitting part can keep flat by the spacer. The spacer can prevent the light-emitting part from structurally entering the opening, avoiding structural interference between the light-emitting part and other components above the base plate.

Abstract: A method may include obtaining first image data relating to a region of interest (ROI) of a first subject. The first image data corresponding to a first equivalent dose level may be acquired by a first device. The method may also include obtaining a model for denoising relating to the first image data and determining second image data corresponding to an equivalent dose level higher than the first equivalent dose level based on the first image data and the model for denoising. In some embodiments, the method may further include determining information relating to the ROI of the first subject based on the second image data and recording the information relating to the ROI of the first subject.

Abstract: A method may include obtaining first image data relating to a region of interest (ROI) of a first subject. The first image data corresponding to a first equivalent dose level may be acquired by a first device. The method may also include obtaining a model for denoising relating to the first image data and determining second image data corresponding to an equivalent dose level higher than the first equivalent dose level based on the first image data and the model for denoising. In some embodiments, the method may further include determining information relating to the ROI of the first subject based on the second image data and recording the information relating to the ROI of the first subject.

Abstract: The embodiments of the present disclosure disclose methods and systems for determining a ring artifact. The method for determining the ring artifact may include: obtaining an original image; mapping a plurality of pixels in the original image to a polar coordinate image; determining a protection region in the polar coordinate image; obtaining a smooth image by smoothing at least one region in the polar coordinate image other than the protection region; generating a residual image based on the polar coordinate image and the smooth image; determining a location of the ring artifact in the original image based on the residual image. In the present disclosure, the original image may be mapped to a trapezoidal region or a triangular region in the polar coordinate image, and the gradient angle image may be used for image processing, which may reduce the influence of noise. An accurate location of the ring artifact may be determined, and information for imaging device detection and air correction may be provided.

Abstract: An illuminated keyswitch structure with an illuminating module includes a base plate, a drive circuit board under the base plate, a spacer between the drive circuit board and the base plate, and a light-emitting part on the circuit board. The spacer has a through hole communicating with an opening of the base plate in a vertical direction. The light-emitting part is located in the through hole, and falls within a projection of the opening in the vertical direction. The light-emitting part has a top surface that is lower than or equal to a bottom surface of the base plate in the vertical direction. The structure of the illuminated keyswitch structure around the light-emitting part can keep flat by the spacer. The spacer can prevent the light-emitting part from structurally entering the opening, avoiding structural interference between the light-emitting part and other components above the base plate.