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公开(公告)号：US20200043204A1
公开(公告)日：2020-02-06
申请号：US16056111
申请日：2018-08-06
Applicant: General Electric Company
Inventor： Lin Fu , Sathish Ramani , Jie Tang , Bruno Kristiaan Bernard De Man , Jed Douglas Pack , Jiang Hsieh , Ge Wang
Abstract: The present disclosure relates to image reconstruction with favorable properties in terms of noise reduction, spatial resolution, detail preservation and computational complexity. The disclosed techniques may include some or all of: a first-pass reconstruction, a simplified datafit term, and/or a deep learning denoiser. In various implementations, the disclosed technique is portable to different CT platforms, such as by incorporating a first-pass reconstruction step.
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公开(公告)号：US20180197317A1
公开(公告)日：2018-07-12
申请号：US15400763
申请日：2017-01-06
Applicant: General Electric Company
Inventor： Lishui Cheng , Bruno Kristiaan Bernard De Man , Sheshadri Thiruvenkadam , Sangtae Ahn , Lin Fu , Hao Lai
CPC classification number: G06N3/08 , G06N3/0454 , G06T11/006 , G06T2211/421 , G06T2211/424
Abstract: The present discussion relates to the use of deep learning techniques to accelerate iterative reconstruction of images, such as CT, PET, and MR images. The present approach utilizes deep learning techniques so as to provide a better initialization to one or more steps of the numerical iterative reconstruction algorithm by learning a trajectory of convergence from estimates at different convergence status so that it can reach the maximum or minimum of a cost function faster.
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公开(公告)号：US09953440B2
公开(公告)日：2018-04-24
申请号：US14597896
申请日：2015-01-15
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Lin Fu , Bruno Kristiaan Bernard DeMan , Jed Douglas Pack
IPC: G06T11/00
CPC classification number: G06T11/006 , G06T2211/421 , G06T2211/424 , G06T2211/432
Abstract: The present approaches relate to frequency-split iterative reconstruction approaches. In some embodiment, such approaches provide for the combination of the low frequency components of an analytical reconstruction (e.g., a filtered back projection) and the high frequency components of an iterative reconstruction. In certain embodiments, frequency-split iterative reconstruction is used for generating region of interest images.
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公开(公告)号：US09406154B2
公开(公告)日：2016-08-02
申请号：US13918656
申请日：2013-06-14
Inventor： Lin Fu , Madison Gray McGaffin , Zhou Yu , Jean-Baptiste Thibault , Sathish Ramani , Jeffrey Allen Fessler , Bruno Kristiaan Bernard De Man , Debashish Pal
IPC: G06T11/00
CPC classification number: G06T11/006 , G06T2211/424
Abstract: The use of the channelized preconditioners in iterative reconstruction is disclosed. In certain embodiments, different channels correspond to different frequency sub-bands and the output of the different channels can be combined to update an image estimate used in the iterative reconstruction process. While individual channels may be relatively simple, the combined channels can represent complex spatial variant operations. The use of channelized preconditioners allows empirical adjustment of individual channels.
Abstract translation: 公开了在迭代重建中使用信道化预处理器。 在某些实施例中，不同的信道对应于不同的频率子带，并且可以组合不同信道的输出以更新在迭代重建过程中使用的图像估计。 虽然单个通道可能相对简单，但组合通道可以表示复杂的空间变体操作。 通道化预处理器的使用允许对各个通道进行实证调整。
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公开(公告)号：US20140140599A1
公开(公告)日：2014-05-22
申请号：US14045816
申请日：2013-10-04
Inventor： Donghwan Kim , Sathish Ramani , Jeffrey A. Fessler , Lin Fu , Bruno Kristiaan Bernard De Man
IPC: G06T7/00
CPC classification number: G06T11/006 , G06T2211/424
Abstract: Methods, systems, and non-transitory computer readable media for image reconstruction are presented. Measured data corresponding to a subject is received. A preliminary image update in a particular iteration is determined based on one or more image variables computed using at least a subset of the measured data in the particular iteration. Additionally, at least one momentum term is determined based on the one or more image variables computed in the particular iteration and/or one or more further image variables computed in one or more iterations preceding the particular iteration. Further, a subsequent image update is determined using the preliminary image update and the momentum term. The preliminary image update and/or the subsequent image update are iteratively computed for a plurality of iterations until one or more termination criteria are satisfied.
Abstract translation: 提出了用于图像重建的方法，系统和非暂时性计算机可读介质。 接收与被摄体对应的测量数据。 基于在特定迭代中使用至少一个测量数据的子集计算的一个或多个图像变量来确定特定迭代中的初步图像更新。 另外，基于在特定迭代中计算的一个或多个图像变量和/或在特定迭代之前的一个或多个迭代中计算的一个或多个另外的图像变量来确定至少一个动量项。 此外，使用初步图像更新和动量项来确定随后的图像更新。 对多个迭代迭代地计算初步图像更新和/或后续图像更新，直到满足一个或多个终止标准。
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Patent Agency Ranking
公开(公告)号：US20190180481A1
公开(公告)日：2019-06-13
申请号：US15840953
申请日：2017-12-13
Applicant: General Electric Company , Purdue University , Notre Dame University
Inventor： Lin Fu , Jean-Baptiste Thibault , Somesh Srivastava , Charles A. Bouman, Jr. , Donghye Ye , Amirkoushyar Ziabari , Ken Sauer
Abstract: An iterative reconstruction approach is provided that allows the use of differing weights in pixels or larger sub-regions in the reconstructed image. By way of example, the relative significance of each projection measurement may be determined based on both the measurement position and the location of the reconstructed pixel. Computationally, the significance of each projection based on these two factors is represented by a weight factor employed in the algorithmic computation.
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公开(公告)号：US20170215818A1
公开(公告)日：2017-08-03
申请号：US15014847
申请日：2016-02-03
Applicant: General Electric Company
Inventor： Bruno Kristiaan Bernard De Man , Lin Fu , Mark Alan Frontera
CPC classification number: A61B6/025 , A61B6/027 , A61B6/032 , A61B6/5205
Abstract: A high-resolution imaging approach is described. The described approach includes use of a small focal spot size and positioning of the patient offset from the center of the imaging volume. The off-center displacement is combined with a small focal spot size and with modified image reconstruction methods to provide high intrinsic spatial resolution without hardware changes to the imaging system.
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公开(公告)号：US20200232938A1
公开(公告)日：2020-07-23
申请号：US16745836
申请日：2020-01-17
Applicant: General Electric Company
Inventor： Paul Francis Fitzgerald , John Scott Price , William Robert Ross , Mingye Wu , Lin Fu , Michelle Brault , Bruno Kristiaan Bernard De Man , Xin Li
IPC: G01N23/046 , G06T7/00 , G06T11/00
Abstract: The present disclosure relates to the design of phantoms configurable using one or more inserts and to their use in generating images that may be used to compare image quality between different imaging systems. Such phantoms may have a modular design with inserts that may be exchanged one for another within a phantom body.
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公开(公告)号：US10679385B1
公开(公告)日：2020-06-09
申请号：US16221606
申请日：2018-12-17
Applicant: General Electric Company
Inventor： Brian David Yanoff , Mingye Wu , Lin Fu , Peter Michael Edic , Xue Rui , Geng Fu , Yannan Jin , Fredrik Gronberg
Abstract: A method for imaging an object to be reconstructed includes acquiring projection data corresponding to the object. Furthermore, the method includes generating a measured sinogram based on the acquired projection data and formulating a forward model, where the forward model is representative of a characteristic of the imaging system. In addition, the method includes generating an estimated sinogram based on an estimated image of the object and the forward model and formulating a statistical model based on at least one of pile-up characteristics and dead time characteristics of a detector of the imaging system. Moreover, the method includes determining an update corresponding to the estimated image based on the statistical model, the measured sinogram, and the estimated sinogram and updating the estimated image based on the determined update to generate an updated image of the object. Additionally, the method includes outputting a final image of the object.
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公开(公告)号：US20180197314A1
公开(公告)日：2018-07-12
申请号：US15400782
申请日：2017-01-06
Applicant: General Electric Company
Inventor： Bruno Kristiaan Bernard De Man , Lin Fu
IPC: G06T11/00
CPC classification number: G06T11/006
Abstract: The present disclosure relates to the use of a hierarchical tomographic reconstruction approach that employs data representations in intermediate steps are between a full line integral and a voxel (e.g., an intermediate line integral). Each of the steps is progressively more local in nature and therefore has computational advantages and is also amenable to a deep learning solution using trained neural networks. The proposed hierarchical structure provides a mechanism to divide a large-scale inverse problem into a series of smaller-scale problems.
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