-
公开(公告)号：US20200237332A1
公开(公告)日：2020-07-30
申请号：US16256843
申请日：2019-01-24
Applicant: General Electric Company
Inventor： Dejun Wang , Srikrishnan V , Gireesha Rao , Katelyn Rose Nye , Nasir Ahmed Desai , Arun Kumar Chandrashekarappa , Huanzhong Li
Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.
-
公开(公告)号：US20140294276A1
公开(公告)日：2014-10-02
申请号：US13852781
申请日：2013-03-28
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Qi Song , Srikrishnan V , Roshni Rustom Bhagalia , Biqul Das
IPC: G06T7/00
CPC classification number: G06T7/0046 , G06K9/621 , G06K2009/366 , G06K2209/051 , G06T7/0012 , G06T7/75 , G06T2207/10072 , G06T2207/10136 , G06T2207/20081 , G06T2207/30004
Abstract: A hierarchical multi-object active appearance model (AAM) framework is disclosed for processing image data, such as localizer or scout image data. In accordance with this approach, a hierarchical arrangement of models (e.g., a model pyramid) maybe employed where a global or parent model that encodes relationships across multiple co-located structures is used to obtain an initial, coarse fit. Subsequent processing by child sub-models add more detail and flexibility to the overall fit.
Abstract translation: 公开了一种用于处理诸如定位器或侦察图像数据的图像数据的分级多对象主动外观模型（AAM）框架。 根据这种方法，可以使用模型（例如，模型金字塔）的分层布置，其中使用编码跨多个同位置结构的关系的全局或父模型来获得初始粗匹配。 儿童子模型的后续处理增加了整体配合的更多细节和灵活性。
-
公开(公告)号：US09355454B2
公开(公告)日：2016-05-31
申请号：US13852781
申请日：2013-03-28
Applicant: General Electric Company
Inventor： Qi Song , Srikrishnan V , Roshni Rustom Bhagalia , Bipul Das
CPC classification number: G06T7/0046 , G06K9/621 , G06K2009/366 , G06K2209/051 , G06T7/0012 , G06T7/75 , G06T2207/10072 , G06T2207/10136 , G06T2207/20081 , G06T2207/30004
Abstract: A hierarchical multi-object active appearance model (AAM) framework is disclosed for processing image data, such as localizer or scout image data. In accordance with this approach, a hierarchical arrangement of models (e.g., a model pyramid) maybe employed where a global or parent model that encodes relationships across multiple co-located structures is used to obtain an initial, coarse fit. Subsequent processing by child sub-models add more detail and flexibility to the overall fit.
Abstract translation: 公开了一种用于处理诸如定位器或侦察图像数据的图像数据的分级多对象主动外观模型（AAM）框架。 根据这种方法，可以使用模型（例如，模型金字塔）的分层布置，其中使用编码跨多个同位置结构的关系的全局或父模型来获得初始粗匹配。 儿童子模型的后续处理增加了整体配合的更多细节和灵活性。
-
-
Search Results
3
records
(took 0.012 seconds)
