APPARATUS, METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM FOR IMPROVING IMAGE QUALITY OF A MEDICAL IMAGE VOLUME

    公开(公告)号:US20230011759A1

    公开(公告)日:2023-01-12

    申请号:US17369596

    申请日:2021-07-07

    Abstract: An apparatus, method, and computer-readable medium for improving image quality of a medical volume. In an embodiment, the apparatus includes processing circuitry configured to receive a reconstructed input image volume from X-ray projection data corresponding to a three-dimensional region of an object to be examined, apply a pseudo-three-dimensional neural network (P3DNN) to the reconstructed input image volume, the application of the pseudo-three-dimensional neural network including generating, for the reconstructed input image volume, a plurality of three-dimensional image datasets representing a different anatomical plane of the reconstructed input image volume, applying at least one convolutional filter to each of a sagittal plane dataset, a transverse plane dataset, and a coronal plane dataset, and concatenating results of the applied at least one convolutional filter to generate an intermediate output image volume, and generate, based on the application of the P3DNN, an output image volume corresponding to the three-dimensional region of the object.

    METHOD AND APPARATUS FOR COMPUTED TOMOGRAPHY (CT) AND MATERIAL DECOMPOSITION WITH PILE-UP CORRECTION CALIBRATED USING REAL PULSE PILEUP EFFECT AND DETECTOR RESPONSE

    公开(公告)号:US20200323508A1

    公开(公告)日:2020-10-15

    申请号:US16915722

    申请日:2020-06-29

    Abstract: An apparatus and method are described using a forward model to correct pulse pileup in spectrally resolved X-ray projection data from photon-counting detectors (PCDs). To calibrate the forward model, which represents each order of pileup using a respective pileup response matrix (PRM), an optimization search determines the elements of the PRMs that optimize an objective function measuring agreement between the spectra of recorded counts affected by pulse pileup and the estimated counts generated using forward model of pulse pileup. The spectrum of the recorded counts in the projection data is corrected using the calibrated forward model, by determining an argument value that optimizes the objective function, the argument being either a corrected X-ray spectrum or the projection lengths of a material decomposition. Images for material components of the material decomposition are then reconstructed using the corrected projection data.

    FOUR-DIMENSIONAL MOTION ESTIMATION AND COMPENSATION BY USING FEATURE RECONSTRUCTION

    公开(公告)号:US20250157100A1

    公开(公告)日:2025-05-15

    申请号:US18509385

    申请日:2023-11-15

    Abstract: A medical image processing method includes obtaining a set of projection data acquired in a computed tomography (CT) scan of a three-dimensional region of an object to be examined; generating for each time point of a plurality of time points of the CT scan based on a part of the obtained set of projection data corresponding to the time point, a pair of feature maps for estimating motion at the time point so as to generate a plurality of pairs of feature maps, each feature map representing a feature of an image reconstructed from the part of the obtained set of projection data; estimating, based on the generated plurality of pairs of feature maps, a four-dimensional motion field; and reconstructing, based on the estimated four-dimensional motion field and the obtained set of projection data, a CT image of the object.

    INFORMATION PROCESSING METHOD, MEDICAL IMAGE DIAGNOSTIC APPARATUS, AND INFORMATION PROCESSING SYSTEM

    公开(公告)号:US20220139006A1

    公开(公告)日:2022-05-05

    申请号:US17577689

    申请日:2022-01-18

    Abstract: An information processing method of an embodiment is a processing method of information acquired by imaging performed by a medical image diagnostic apparatus, the information processing method includes the steps of: acquiring noise data by imaging a phantom using a medical imaging apparatus; based on first subject projection data acquired by the imaging performed by a medical image diagnostic modality of a same kind as the medical image diagnostic apparatus and the noise data, acquiring synthesized subject data in which noise based on the noise data is added to the first subject projection data; and acquiring a noise reduction processing model by machine learning using the synthesized subject data and second subject projection data acquired by the imaging performed by the medical image diagnostic modality.

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