Abstract: The present disclosure provides a system and method for CT image reconstruction. The method may include combining an analytic image reconstruction technique with an iterative reconstruction algorithm of CT images. The image reconstruction may be performed on or near a region of interest.

Abstract: A system and method for image correction is provided. The method includes: receiving an original image; pre-correcting the original image; generating correction data based on the original image and the pre-corrected image; weighting the original image and the pre-corrected image based on the correction data; and generating a corrected image based on the weighting.

Abstract: The present disclosure provides a system and method for CT image reconstruction. The method may include combining an analytic image reconstruction technique with an iterative reconstruction algorithm of CT images. The image reconstruction may be performed on or near a region of interest.

Abstract: The disclosure relates to systems and methods for iterative reconstruction. Raw data detected from a plurality of angles by an imaging device may be obtained. A first seed image may be generated by performing a filtered back projection on the raw data. A first air mask may be determined by performing a minimum value back projection (BP) on the raw data. One or more images may be reconstructed by performing an iterative reconstruction based on the first seed image, the first air mask, and the raw data.

Abstract: A system and method for image correction is provided. The method includes: receiving an original image; pre-correcting the original image; generating correction data based on the original image and the pre-corrected image; weighting the original image and the pre-corrected image based on the correction data; and generating a corrected image based on the weighting.

Abstract: The present disclosure relates to a system, method and storage medium for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data is received, a plurality of iterations may be implemented. During each iteration, a first voxel value relating to a first voxel in an image is calculated; at least a portion of a second voxel may be continuously changed with respect to at least a portion of the first voxel value; the image may be transformed to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; a projection error may be obtained based on the estimated projection and the raw data; and the image may be corrected or updated based on the projection error.

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 present disclosure relates to a system, method and storage medium for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data is received, a plurality of iterations may be implemented. During each iteration, a first voxel value relating to a first voxel in an image is calculated; at least a portion of a second voxel may be continuously changed with respect to at least a portion of the first voxel value; the image may be transformed to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; a projection error may be obtained based on the estimated projection and the raw data; and the image may be corrected or updated based on the projection error.

Abstract: In one aspect, present invention provides a recombinant mutant human factor VIII having increased expression and/or secretion as compared to wild-type factor VIII. In certain embodiments, the recombinant factor VIII includes one or more amino acid substitution(s) selected from the group consisting of I86, Y105, A108, D115, Q117, F129, G132, H134, M147 and L152. In other aspects, the present invention provides FVIII encoding nucleic acids, FVIII-expression vectors, as well as methods of using the modified FVIII genes in the treatment of FVIII deficiencies, such as hemophilia A.

Abstract: The present disclosure relates to a system, method and storage medium for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data is received, a plurality of iterations may be implemented. During each iteration, a first voxel value relating to a first voxel in an image is calculated; at least a portion of a second voxel may be continuously changed with respect to at least a portion of the first voxel value; the image may be transformed to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; a projection error may be obtained based on the estimated projection and the raw data; and the image may be corrected or updated based on the projection error.

Abstract: The present disclosure relates to methods, systems, and non-transitory computer readable mediums for reconstructing an image. Image data may be obtained, wherein the image data may be generated by a detector array. A weighting window may be determined based on at least one parameter relating to the detector array. A first set of data may be determined based on the image data and the weighting window. An objective function associated with a target image may be determined based on the first set of data, wherein the objective function may include a first model, the first model may represent a difference between the target image and the first set of data, and the first model may be identified based on the first set of data. The target image may be reconstructed by performing a plurality of iterations based on the objective function.

Abstract: The present disclosure provides a system and method for CT image reconstruction. The method may include combining an analytic image reconstruction technique with an iterative reconstruction algorithm of CT images. The image reconstruction may be performed on or near a region of interest.

Abstract: The present disclosure relates to a system, method and storage medium for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data is received, a plurality of iterations may be implemented. During each iteration, a first voxel value relating to a first voxel in an image is calculated; at least a portion of a second voxel may be continuously changed with respect to at least a portion of the first voxel value; the image may be transformed to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; a projection error may be obtained based on the estimated projection and the raw data; and the image may be corrected or updated based on the projection error.

Abstract: The present disclosure provides a system and method for CT image reconstruction. The method may include combining an analytic image reconstruction technique with an iterative reconstruction algorithm of CT images. The image reconstruction may be performed on or near a region of interest.

Abstract: The present disclosure provides a system and method for CT image reconstruction. The method may include combining an analytic image reconstruction technique with an iterative reconstruction algorithm of CT images. The image reconstruction may be performed on or near a region of interest.

Abstract: A system and method for image correction is provided. The method includes: receiving an original image; pre-correcting the original image; generating correction data based on the original image and the pre-corrected image; weighting the original image and the pre-corrected image based on the correction data; and generating a corrected image based on the weighting.

Abstract: The present disclosure relates to a system, method and storage medium for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data is received, a plurality of iterations may be implemented. During each iteration, a first voxel value relating to a first voxel in an image is calculated; at least a portion of a second voxel may be continuously changed with respect to at least a portion of the first voxel value; the image may be transformed to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; a projection error may be obtained based on the estimated projection and the raw data; and the image may be corrected or updated based on the projection error.

Abstract: Compositions and methods are provided for the diagnosis and treatment of thrombotic thrombocytopenic purpura (TTP), stroke and myocardial infarction.