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公开(公告)号：US09953397B2
公开(公告)日：2018-04-24
申请号：US14478597
申请日：2014-09-05
Applicant: General Electric Company
Inventor： Ek Tsoon Tan , Xiaofeng Liu , Dan Xu
CPC classification number: G06T3/00 , A61B5/055 , G06T5/006 , G06T7/32 , G06T2207/10088
Abstract: A method implemented using at least one processor includes receiving a target image and a reference image. The target image is a distorted magnetic resonance image and the reference image is an undistorted magnetic resonance image. The method further includes selecting an image registration method for registering the target image to the reference image, wherein the image registration method uses an image transformation. The method further includes performing image registration of the target image with the reference image, wherein the image registration provides a plurality of optimized parameters of the image transformation. The method also includes generating a corrected image based on the target image and the plurality of optimized parameters of the image transformation.
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2.发明申请COMPUTER-AIDED LESION DETECTION AND TRACK PLANNING FOR MRI-GUIDED BREAST BIOPSY 有权计算机辅助检查和跟踪计划用于MRI引导生物学公开(公告)号：US20160228104A1
公开(公告)日：2016-08-11
申请号：US14618316
申请日：2015-02-10
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Ileana Hancu , Robert David Darrow , Eric William Fiveland , Xiaofeng Liu
CPC classification number: A61B10/0233 , A61B5/0555 , A61B5/4312 , A61B5/742 , A61B2576/02
Abstract: The system and method of the invention pertains to an MR-guided breast biopsy procedure, specifically as to quickly identifying the biopsy location. More particularly, the system utilizes a diagnostic imaging modality such as magnetic resonance imaging (MRI) to locate one or more lesions in a human breast. Non-rigid registration between uncompressed screening images (where the lesion has been previously identified) and the compressed biopsy images enables easier identification of the biopsy site, hence shortening the biopsy procedure.
Abstract translation: 本发明的系统和方法涉及MR指导的乳腺活检程序，具体地涉及快速识别活检位置。 更具体地，系统利用诸如磁共振成像（MRI）的诊断成像模式来定位人乳房中的一个或多个损伤。 未压缩筛选图像（其中已经识别出病变）与压缩的活检图像之间的非刚性配准使得能够更容易地识别活检部位，从而缩短活检程序。
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公开(公告)号：US20160071269A1
公开(公告)日：2016-03-10
申请号：US14478597
申请日：2014-09-05
Applicant: General Electric Company
Inventor： Ek Tsoon Tan , Xiaofeng Liu , Dan Xu
CPC classification number: G06T3/00 , A61B5/055 , G06T5/006 , G06T7/32 , G06T2207/10088
Abstract: A method implemented using at least one processor includes receiving a target image and a reference image. The target image is a distorted magnetic resonance image and the reference image is an undistorted magnetic resonance image. The method further includes selecting an image registration method for registering the target image to the reference image, wherein the image registration method uses an image transformation. The method further includes performing image registration of the target image with the reference image, wherein the image registration provides a plurality of optimized parameters of the image transformation. The method also includes generating a corrected image based on the target image and the plurality of optimized parameters of the image transformation.
Abstract translation: 使用至少一个处理器实现的方法包括接收目标图像和参考图像。 目标图像是失真的磁共振图像，参考图像是未失真的磁共振图像。 该方法还包括选择用于将目标图像登记到参考图像的图像配准方法，其中图像配准方法使用图像变换。 该方法还包括用参考图像执行目标图像的图像配准，其中图像配准提供图像变换的多个优化参数。 该方法还包括基于目标图像和图像变换的多个优化参数生成校正图像。
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公开(公告)号：US09974521B2
公开(公告)日：2018-05-22
申请号：US14618316
申请日：2015-02-10
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Ileana Hancu , Robert David Darrow , Eric William Fiveland , Xiaofeng Liu
CPC classification number: A61B10/0233 , A61B5/0555 , A61B5/4312 , A61B5/742 , A61B2576/02
Abstract: The system and method of the invention pertains to an MR-guided breast biopsy procedure, specifically as to quickly identifying the biopsy location. More particularly, the system utilizes a diagnostic imaging modality such as magnetic resonance imaging (MRI) to locate one or more lesions in a human breast. Non-rigid registration between uncompressed screening images (where the lesion has been previously identified) and the compressed biopsy images enables easier identification of the biopsy site, hence shortening the biopsy procedure.
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Patent Agency Ranking
5.发明授权公开(公告)号：US09349186B2
公开(公告)日：2016-05-24
申请号：US14177414
申请日：2014-02-11
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Xiaofeng Liu , John Frederick Schenck , Ek Tsoon Tan , Albert Amos Montillo
CPC classification number: G06T7/0081 , G06T7/11 , G06T7/143 , G06T7/149 , G06T7/174 , G06T2200/04 , G06T2207/10072 , G06T2207/20076 , G06T2207/20128 , G06T2207/30016
Abstract: The system and method of the invention combines target image intensity into a maximum likelihood estimate (MLE) framework as in STAPLE to take advantage of both intensity-based segmentation and statistical label fusion based on atlas consensus and performance level, abbreviated iSTAPLE. The MLE framework is then solved using a modified expectation-maximization algorithm to simultaneously estimate the intensity profiles of structures of interest as well as the true segmentation and atlas performance level. The iSTAPLE greatly extends the use of atlases such that the target image need not have the same image contrast and intensity range as the atlas images.
Abstract translation: 本发明的系统和方法将目标图像强度与STAPLE中的最大似然估计（MLE）框架相结合，以利用基于图集共识和性能水平（简称为iSTAPLE）的基于强度的分割和统计标签融合。 然后使用修改的期望最大化算法来解决MLE框架，以同时估计感兴趣的结构的强度分布以及真实的分段和图谱性能水平。 iSTAPLE大大扩展了地图集的使用，使得目标图像不需要具有与图集图像相同的图像对比度和强度范围。
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公开(公告)号：US09208572B2
公开(公告)日：2015-12-08
申请号：US14032877
申请日：2013-09-20
Applicant: General Electric Company
Inventor： Xiaofeng Liu , Albert Montillo , Ek Tsoon Tan , John F. Schenck
CPC classification number: G06T7/0089 , G06T7/11 , G06T7/149 , G06T2207/10088 , G06T2207/20128 , G06T2207/30016
Abstract: Systems and methods for image segmentation using a deformable atlas are provided. One method includes obtaining one or more target images, obtaining one or more propagated label probabilities for the one or more target images, and segmenting the one or more target images using a cost function of a deformable atlas model. The method further includes identifying segmented structures within the one or more target images based on the segmented one or more target images.
Abstract translation: 提供了使用可变形图案的图像分割的系统和方法。 一种方法包括获得一个或多个目标图像，为一个或多个目标图像获得一个或多个传播的标签概率，以及使用可变形图集模型的成本函数对一个或多个目标图像进行分割。 该方法还包括基于分割的一个或多个目标图像来识别所述一个或多个目标图像内的分段结构。
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7.发明申请公开(公告)号：US20140226889A1
公开(公告)日：2014-08-14
申请号：US14177414
申请日：2014-02-11
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Xiaofeng Liu , John Frederick Schenck , Ek Tsoon Tan , Albert Amos Montillo
IPC: G06T7/00
CPC classification number: G06T7/0081 , G06T7/11 , G06T7/143 , G06T7/149 , G06T7/174 , G06T2200/04 , G06T2207/10072 , G06T2207/20076 , G06T2207/20128 , G06T2207/30016
Abstract: The system and method of the invention combines target image intensity into a maximum likelihood estimate (MLE) framework as in STAPLE to take advantage of both intensity-based segmentation and statistical label fusion based on atlas consensus and performance level, abbreviated iSTAPLE. The MLE framework is then solved using a modified expectation-maximization algorithm to simultaneously estimate the intensity profiles of structures of interest as well as the true segmentation and atlas performance level. The iSTAPLE greatly extends the use of atlases such that the target image need not have the same image contrast and intensity range as the atlas images.
Abstract translation: 本发明的系统和方法将目标图像强度与STAPLE中的最大似然估计（MLE）框架相结合，以利用基于图集共识和性能水平（简称为iSTAPLE）的基于强度的分割和统计标签融合。 然后使用修改的期望最大化算法来解决MLE框架，以同时估计感兴趣的结构的强度分布以及真实的分段和图谱性能水平。 iSTAPLE大大扩展了地图集的使用，使得目标图像不需要具有与图集图像相同的图像对比度和强度范围。
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公开(公告)号：US20160228068A1
公开(公告)日：2016-08-11
申请号：US14618707
申请日：2015-02-10
Applicant: General Electric Company
Inventor： Ileana Hancu , Robert David Darrow , Eric William Fiveland , Xiaofeng Liu
CPC classification number: A61B5/7271 , A61B5/055 , A61B5/4312 , A61B5/742 , A61B10/0041 , A61B10/0233
Abstract: The system and method of the invention pertains to an MR-guided breast biopsy procedure, specifically as to quality control and assurance following a breast biopsy procedure. Following automated lesion segmentation in a first post-contrast biopsy image, with the biopsy location segmented out of last biopsy series, a quantitative assessment is performed at the end of the procedure to highlight the volume of tissue taken out and the percentage (%) lesion fraction in the extracted tissue. This provides confirmation to the clinician that the appropriate target tissue was identified and sampled during the procedure.
Abstract translation: 本发明的系统和方法涉及MR指导的乳腺活检程序，具体涉及乳腺活检程序之后的质量控制和保证。 在第一次造影后活检图像中的自动化损伤分割之后，将活检位置从最后活检系列分割出来，在手术结束时进行定量评估，以突出取出的组织体积和百分比（％）病变 提取组织中的分数。 这为临床医生提供了在手术过程中鉴定和采样适当的靶组织的确认。
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公开(公告)号：US20150086096A1
公开(公告)日：2015-03-26
申请号：US14032877
申请日：2013-09-20
Applicant: General Electric Company
Inventor： Xiaofeng Liu , Albert Montillo , Ek Tsoon Tan , John F. Schenck
IPC: G06T7/00
CPC classification number: G06T7/0089 , G06T7/11 , G06T7/149 , G06T2207/10088 , G06T2207/20128 , G06T2207/30016
Abstract: Systems and methods for image segmentation using a deformable atlas are provided. One method includes obtaining one or more target images, obtaining one or more propagated label probabilities for the one or more target images, and segmenting the one or more target images using a cost function of a deformable atlas model. The method further includes identifying segmented structures within the one or more target images based on the segmented one or more target images.
Abstract translation: 提供了使用可变形图案的图像分割的系统和方法。 一种方法包括获得一个或多个目标图像，为一个或多个目标图像获得一个或多个传播的标签概率，以及使用可变形图集模型的成本函数对一个或多个目标图像进行分割。 该方法还包括基于分割的一个或多个目标图像来识别所述一个或多个目标图像内的分段结构。
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