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公开(公告)号：US20230016982A1
公开(公告)日：2023-01-19
申请号：US17373917
申请日：2021-07-13
发明人： Andrew Crispin Graham , Julian Matthew Foxall , James Vradenburg Miller , Walter V. Dixon , Vijay Shirsat
摘要： A method for inspecting an object includes determining guide image data of the object from a determined orientation, the guide image data including a guide image pixel array and a pixel property for at least one guide image pixel in the guide image pixel array. The method also includes receiving inspection image data indicative of an inspection image and associating the inspection image data with the guide image data with a processor of a computing device. Additionally, the method includes determining a property of the object based on the guide image data and the associated inspection image data.
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公开(公告)号：US20230018458A1
公开(公告)日：2023-01-19
申请号：US17373920
申请日：2021-07-13
发明人： Andrew Crispin Graham , Julian Matthew Foxall , James Vradenburg Miller , Walter V. Dixon , Vijay Shirsat
摘要： A method for inspecting an object includes receiving or determining inspection image data, the inspection image data including an inspection image pixel array with at least one inspection image pixel in the inspection image pixel array having a pixel property associated therewith. The method includes receiving via a processor a user input associated with a continuous segment of inspection image pixels in the inspection image pixel array. The method includes determining a property of the object based on the pixel properties associated with the continuous segment of inspection image pixels in the inspection image pixel array.
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公开(公告)号：US20240314447A1
公开(公告)日：2024-09-19
申请号：US18141493
申请日：2023-05-01
发明人： Vamshi Krishna Reddy Kommareddy , Biswajit Medhi , Andrew Crispin Graham , Walter V. Dixon , James Vradenburg Miller
CPC分类号： H04N23/74 , H04N23/6812 , H04N23/6845 , H04N23/73 , H04N23/689
摘要： A pulse illumination imaging system is provided. The system includes an image sensor, a light source, and a controller. The image sensor includes a plurality of light sensitive pixel elements that are activatable for a designated exposure time to capture one or more images. The controller is configured to determine an activation time to activate the image sensor based on motion of a target element relative to the image sensor; activate the image sensor at the activation time; and activate the light source during the exposure time of the image sensor to produce a pulse having a preconfigured time duration that is less than the exposure time of the image sensor.
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公开(公告)号：US20230018554A1
公开(公告)日：2023-01-19
申请号：US17373925
申请日：2021-07-13
发明人： Andrew Crispin Graham , Julian Matthew Foxall , James Vradenburg Miller , Walter V. Dixon , Vijay Shirsat
摘要： A method for inspecting an object includes determining a first inspection package that includes a first inspection image of the object and a first designation. The method includes determining data indicative of a second inspection package that includes a second inspection image of the object and a second designation. The method includes determining a first property of the object based on the first inspection image of the object, one or more properties maps of the object, and the first designation. The method includes determining a second property of the object based on the second inspection image of the object, the one or more properties maps of the object, and the second designation. The method includes displaying the first property and the second property or displaying data indicative of a comparison of the first property with the second property.
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公开(公告)号：US11869192B2
公开(公告)日：2024-01-09
申请号：US17091725
申请日：2020-11-06
发明人： Mohammed Yousefhussien , Arpit Jain , James Vradenburg Miller , Achalesh Kumar , Walter V Dixon, III
IPC分类号： G06T7/11 , G06T17/05 , G06Q10/06 , G06Q10/0631 , G06Q10/0639 , G06V20/10 , G06V10/764 , G06V10/82 , G06N3/04 , G06N3/08
CPC分类号： G06T7/11 , G06Q10/06312 , G06Q10/06315 , G06Q10/06393 , G06T17/05 , G06V10/764 , G06V10/82 , G06V20/188 , G06N3/04 , G06N3/08 , G06T2207/10032 , G06T2207/30188
摘要： According to some embodiments, a system and method are provided comprising a vegetation module to receive image data from an image source; a memory for storing program instructions; a vegetation processor, coupled to the memory, and in communication with the vegetation module, and operative to execute program instructions to: receive image data; estimate a vegetation segmentation mask; generate at least one of a 3D point cloud and a 2.5D Digital Surface Model based on the received image data; estimate a relief surface using a digital terrain model; generate a vegetation masked digital surface model based on the digital terrain model, the vegetation segmentation mask and at least one of the 3D point cloud and the 2.5D DSM; generate a canopy height model based on the generated vegetation masked digital surface model; and generate at least one analysis with an analysis module, wherein the analysis module receives the generated canopy height model prior to execution of the analysis module, and wherein the analysis module uses the generated canopy height model in the generation of the at least one analysis. Numerous other aspects are provided.
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公开(公告)号：US10964017B2
公开(公告)日：2021-03-30
申请号：US16192551
申请日：2018-11-15
发明人： Jed Douglas Pack , Peter Michael Edic , Xin Wang , Xia Li , Prem Venugopal , James Vradenburg Miller
摘要： The present disclosure relates to training one or more neural networks for vascular vessel assessment using synthetic image data for which ground-truth data is known. In certain implementations, the synthetic image data may be based in part, or derived from, clinical image data for which ground-truth data is not known or available. Neural networks trained in this manner may be used to perform one or more of vessel segmentation, decalcification, Hounsfield unit scoring, and/or estimation of a hemodynamic parameter.
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公开(公告)号：US20150164605A1
公开(公告)日：2015-06-18
申请号：US14106091
申请日：2013-12-13
CPC分类号： A61B8/466 , A61B1/00009 , A61B1/04 , A61B5/0035 , A61B5/0044 , A61B5/0066 , A61B5/0073 , A61B5/055 , A61B5/4887 , A61B6/032 , A61B6/037 , A61B6/466 , A61B6/5205 , A61B6/5252 , A61B8/0841 , A61B8/085 , A61B8/12 , A61B8/5207 , A61B8/523 , A61B18/12 , A61B34/20 , A61B90/37 , A61B2017/00243 , A61B2034/105 , A61B2576/00 , A61B2576/023 , A61N7/02 , G06T7/73 , G06T19/20 , G06T2207/10076 , G06T2207/30048 , G06T2210/41 , G06T2219/2016 , G06T2219/2021
摘要： Methods and systems for imaging a subject are presented. A series of volumetric images corresponding to a volume of interest in the subject is received during an interventional procedure. One or more of anatomical structures in at least one volumetric image selected from the series of volumetric images are detected. Detecting the anatomical structures includes determining an originally acquired view of the anatomical structures in the selected volumetric image. An optimal view of the anatomical structures is determined for performing a desired imaging task during the interventional procedure. The detected anatomical structures are automatically reoriented to transform the originally acquired view of the detected anatomical structures into a reoriented view. One or more obstructing structures are automatically removed from the reoriented view to generate the optimal view of the detected anatomical structures. The selected volumetric image including the optimal view of the detected anatomical structures is displayed in real-time.
摘要翻译： 介绍了成像对象的方法和系统。 在介入手术期间接收与受试者感兴趣体积相对应的一系列体积图像。 检测从一系列体积图像中选择的至少一个体积图像中的一个或多个解剖结构。 检测解剖结构包括确定所选择的体积图像中的解剖结构的原始获取的视图。 确定解剖结构的最佳视图，用于在介入手术期间执行所需的成像任务。 检测到的解剖结构自动地重新定向以将检测到的解剖结构的原始获取的视图变换为重新定向的视图。 一个或多个阻挡结构自动从重新定向的视图中移除，以产生检测到的解剖结构的最佳视图。 包括检测到的解剖结构的最佳视图的所选体积图像被实时显示。
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公开(公告)号：US20240331128A1
公开(公告)日：2024-10-03
申请号：US18194109
申请日：2023-03-31
发明人： John Karigiannis , Shaopeng Liu , James Vradenburg Miller , Peihong Zhu , David Cantin , Jonathan R. Hootman
IPC分类号： G06T7/00 , G01N21/91 , G06N3/045 , G06N3/0464
CPC分类号： G06T7/0004 , G01N21/91 , G06N3/045 , G06N3/0464 , G06T2207/20081 , G06T2207/20084 , G06T2207/30164
摘要： A control circuit can access inspection results from an inspection of a first component and then input those inspection results to a first machine learning model. The inspection results include potential wear indications. By one approach, that first machine learning model is trained using a training corpus that includes inspection results for previously inspected components that are at least similar to the first component. The first machine learning model can output assessment information that, by one approach, identifies some of the potential wear indications as being relevant. By one approach, the aforementioned assessment information may be input a second machine learning model that is trained using a training corpus that includes historical results from previous inspections of the same first component and wherein the second machine learning model outputs prediction information regarding whether a repeated physical processing of the first component will yield a particular result.
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公开(公告)号：US20240029407A1
公开(公告)日：2024-01-25
申请号：US17871247
申请日：2022-07-22
IPC分类号： G06V10/774 , G06T15/10
CPC分类号： G06V10/774 , G06T15/10
摘要： A control circuit accesses three-dimensional image information for a given three-dimensional object. The control circuit accesses a selection corresponding to a feature of the three-dimensional object, and then automatically generates a plurality of synthetic images of the three-dimensional object as a function of the three-dimensional and the selection of the aforementioned feature. By one approach, these synthetic images include supplemental visual emphasis corresponding to the aforementioned feature. The generated plurality of synthetic images can then be used as a training corpus when training a machine learning model.
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公开(公告)号：US10448915B2
公开(公告)日：2019-10-22
申请号：US15633819
申请日：2017-06-27
发明人： Bruno Kristiaan Bernard De Man , Jed Douglas Pack , Eri Haneda , Sathish Ramani , Jiang Hsieh , James Vradenburg Miller , Peter Michael Edic
摘要： A method for characterizing anatomical features includes receiving scanned data and image data corresponding to a subject. The scanned data comprises sinogram data. The method further includes identifying a first region in an image of the image data corresponding to a region of interest. The method also includes determining a second region in the scanned data. The second region corresponds to the first region. The method further includes identifying a sinogram trace corresponding to the region of interest. The sinogram trace comprises sinogram data present within the second region. The method includes determining a data feature of the subject based on the sinogram trace and a deep learning network. The method also includes determining a diagnostic condition corresponding to a medical condition of the subject based on the data feature.
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