Systems and methods for deep learning-based image reconstruction

    公开(公告)号:US10679384B2

    公开(公告)日:2020-06-09

    申请号:US15720632

    申请日:2017-09-29

    Abstract: Methods and systems for deep learning based image reconstruction are disclosed herein. An example method includes receiving a set of imaging projections data, identifying a voxel to reconstruct, receiving a trained regression model, and reconstructing the voxel. The voxel is reconstructed by: projecting the voxel on each imaging projection in the set of imaging projections according to an acquisition geometry, extracting adjacent pixels around each projected voxel, feeding the regression model with the extracted adjacent pixel data to produce a reconstructed value of the voxel, and repeating the reconstruction for each voxel to be reconstructed to produce a reconstructed image.

    Systems and methods for deep learning-based image reconstruction

    公开(公告)号:US11580677B2

    公开(公告)日:2023-02-14

    申请号:US16806727

    申请日:2020-03-02

    Abstract: Methods and systems for deep learning based image reconstruction are disclosed herein. An example method includes receiving a set of imaging projections data, identifying a voxel to reconstruct, receiving a trained regression model, and reconstructing the voxel. The voxel is reconstructed by: projecting the voxel on each imaging projection in the set of imaging projections according to an acquisition geometry, extracting adjacent pixels around each projected voxel, feeding the regression model with the extracted adjacent pixel data to produce a reconstructed value of the voxel, and repeating the reconstruction for each voxel to be reconstructed to produce a reconstructed image.

    System and method for imaging biopsy samples obtained from a patient

    公开(公告)号:US10827989B2

    公开(公告)日:2020-11-10

    申请号:US15385046

    申请日:2016-12-20

    Abstract: A system for imaging biopsy samples obtained from a patient includes: a radiation source; a radiation detector having a surface that defines a first imaging region, a second imaging region, and a third imaging region; and a collimator having a body defining an opening and selectively adjustable between a first imaging position and a second imaging position. The first imaging position allows radiation rays to pass from the radiation source, through the opening, and into the second imaging region while restricting the radiation rays from passing into the first imaging region when the radiation source is in a first scanning position. The second imaging position allows radiation rays to pass from the radiation source, through the opening, and into the third imaging region while restricting the radiation rays from passing into the first imaging region when the radiation source is in a second scanning position.

    Apparatus and method for mammographic breast compression

    公开(公告)号:US10695010B2

    公开(公告)日:2020-06-30

    申请号:US16108891

    申请日:2018-08-22

    Abstract: A mammography apparatus includes a support plate for supporting a breast of a patient, a compression plate movable toward and away from the support plate for compressing the breast against the support plate, and a controller configured to control movement of the compression plate toward and away from the support plate. The controller is configured to adjust at least one of a rate of compression and a pressure applied to the breast based on a measurement of at least one of a diastolic pressure and a systolic pressure of the patient taken during at least one of a compression phase and a clamping phase of the mammography apparatus.

    Clinical task-based processing of images

    公开(公告)号:US10755454B2

    公开(公告)日:2020-08-25

    申请号:US15852076

    申请日:2017-12-22

    Abstract: An imaging system, such as a DBT system, is provided that is capable of providing processing of an image from initial generation/reconstruction of the image through the review of the image by a radiologist or other practitioner that produces images optimized for the particular task/process performed using the images. The task/review that the radiologist is performing on the processed or reconstructed image can be modeled with regard to the initial generation of the processed or reconstructed images from the raw images or the model considerations can be retroactively applied and back propagated through the image processing performed by the system. These modeling considerations that can take the form of an indicator of clinical performance is/are used by the system to optimize and produce an image(s) that best represents the items in the image necessary for an accurate diagnosis of the patient when reviewed by the radiologist.

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