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公开(公告)号：US11717233B2
公开(公告)日：2023-08-08
申请号：US16947149
申请日：2020-07-21
发明人： Florin-Cristian Ghesu , Siqi Liu , Awais Mansoor , Sasa Grbic , Sebastian Vogt , Dorin Comaniciu , Ruhan Sa , Zhoubing Xu
IPC分类号： A61B5/00 , G06T7/62 , G06T7/11 , G16H50/20 , G16H30/40 , A61B6/03 , A61B6/00 , G06T7/00 , G06F18/214
CPC分类号： A61B5/7275 , A61B5/7267 , A61B6/032 , A61B6/50 , G06F18/214 , G06T7/0012 , G06T7/11 , G06T7/62 , G16H30/40 , G16H50/20 , G06T2207/10081 , G06T2207/10116 , G06T2207/20081 , G06T2207/20084 , G06T2207/20221 , G06T2207/30061 , G06V2201/031
摘要： Systems and methods for assessing a disease are provided. An input medical image in a first modality is received. Lungs are segmented from the input medical image using a trained lung segmentation network and abnormality patterns associated with the disease are segmented from the input medical image using a trained abnormality pattern segmentation network. The trained lung segmentation network and the trained abnormality pattern segmentation network are trained based on 1) synthesized images in the first modality generated from training images in a second modality and 2) target segmentation masks for the synthesized images generated from training segmentation masks for the training images. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality patterns.
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公开(公告)号：US20210256716A1
公开(公告)日：2021-08-19
申请号：US17175125
申请日：2021-02-12
摘要： A method, computer system, and a computer-readable medium for registering one or more structures to a desired orientation for planning and guidance for surgery is provided. The method includes in a preoperative stage, obtaining one or more 3D models of one or more structures from one or more CT images using an image processing segmentation technique or a manual segmentation technique; in the preoperative stage, registering the one or more structures to a template that is adapted to an alternating registration for a patient-specific shape and pose for a desired reduction and corresponding reduction transformations; in an intraoperative stage, mapping the one or more structures to one or more radiographs via a 3D-2D registration that iteratively optimizes a similarity metric between acquired and simulated radiographs; and in the intraoperative stage, providing an output that is representative of a radiograph or a 3D tomographic representation to provide guidance to a user.
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公开(公告)号：US20200035363A1
公开(公告)日：2020-01-30
申请号：US16046007
申请日：2018-07-26
发明人： Sebastian Vogt , Thomas Mertelmeier
摘要： A system and method includes acquisition of one or more images of each of a plurality of bodies, each of the images associated with an acquisition time, determination, for each body, of a future health status of the body, the future health status of the body being a health status of the body at a time after the acquisition time of the one or more images of the body, and training of an artificial neural network to output a predicted health status, the training based on the one or more images and determined future health status of each body.
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公开(公告)号：US20220292742A1
公开(公告)日：2022-09-15
申请号：US17249735
申请日：2021-03-11
发明人： Boris Mailhe , Florin-Cristian Ghesu , Siqi Liu , Sasa Grbic , Sebastian Vogt , Dorin Comaniciu , Awais Mansoor , Sebastien Piat , Steffen Kappler , Ludwig Ritschl
摘要： Systems and methods for generating a synthetic image are provided. An input medical image in a first modality is received. A synthetic image in a second modality is generated from the input medical image. The synthetic image is upsampled to increase a resolution of the synthetic image. An output image is generated to simulate image processing of the upsampled synthetic image. The output image is output.
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公开(公告)号：US11908047B2
公开(公告)日：2024-02-20
申请号：US17249735
申请日：2021-03-11
发明人： Boris Mailhe , Florin-Cristian Ghesu , Siqi Liu , Sasa Grbic , Sebastian Vogt , Dorin Comaniciu , Awais Mansoor , Sebastien Piat , Steffen Kappler , Ludwig Ritschl
CPC分类号： G06T11/008 , G06T3/4053 , G06T7/0012 , G06T7/11 , G06T2207/10081 , G06T2207/20081 , G06T2207/20084 , G06T2211/408 , G16H30/40
摘要： Systems and methods for generating a synthetic image are provided. An input medical image in a first modality is received. A synthetic image in a second modality is generated from the input medical image. The synthetic image is upsampled to increase a resolution of the synthetic image. An output image is generated to simulate image processing of the upsampled synthetic image. The output image is output.
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公开(公告)号：US11669984B2
公开(公告)日：2023-06-06
申请号：US17175125
申请日：2021-02-12
CPC分类号： G06T7/344 , A61B34/10 , G06T7/11 , G06T7/337 , G06T17/00 , G06T19/20 , A61B34/20 , A61B2034/102 , A61B2034/105 , A61B2090/367 , A61B2090/3762 , G06T2207/10081 , G06T2207/10124 , G06T2207/30008 , G06T2210/41 , G06T2219/2004
摘要： A method, computer system, and a computer-readable medium for registering one or more structures to a desired orientation for planning and guidance for surgery is provided. The method includes in a preoperative stage, obtaining one or more 3D models of one or more structures from one or more CT images using an image processing segmentation technique or a manual segmentation technique; in the preoperative stage, registering the one or more structures to a template that is adapted to an alternating registration for a patient-specific shape and pose for a desired reduction and corresponding reduction transformations; in an intraoperative stage, mapping the one or more structures to one or more radiographs via a 3D-2D registration that iteratively optimizes a similarity metric between acquired and simulated radiographs; and in the intraoperative stage, providing an output that is representative of a radiograph or a 3D tomographic representation to provide guidance to a user.
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公开(公告)号：US20220022818A1
公开(公告)日：2022-01-27
申请号：US16947149
申请日：2020-07-21
发明人： Florin-Cristian Ghesu , Siqi Liu , Awais Mansoor , Sasa Grbic , Sebastian Vogt , Dorin Comaniciu , Ruhan Sa , Zhoubing Xu
IPC分类号： A61B5/00 , G06T7/11 , G06T7/00 , G06K9/62 , G06T7/62 , G16H30/40 , G16H50/20 , A61B6/03 , A61B6/00
摘要： Systems and methods for assessing a disease are provided. An input medical image in a first modality is received. Lungs are segmented from the input medical image using a trained lung segmentation network and abnormality patterns associated with the disease are segmented from the input medical image using a trained abnormality pattern segmentation network. The trained lung segmentation network and the trained abnormality pattern segmentation network are trained based on 1) synthesized images in the first modality generated from training images in a second modality and 2) target segmentation masks for the synthesized images generated from training segmentation masks for the training images. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality patterns.
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