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公开(公告)号：US11468558B2
公开(公告)日：2022-10-11
申请号：US16158093
申请日：2018-10-11
发明人： Michael Abramoff , Gwenole Quellec
摘要： A method of identifying an object of interest can comprise obtaining first samples of an intensity distribution of one or more object of interest, obtaining second samples of an intensity distribution of confounder objects, transforming the first and second samples into an appropriate first space, performing dimension reduction on the transformed first and second samples, whereby the dimension reduction of the transformed first and second samples generates an object detector, transforming one or more of the digital images into the first space, performing dimension reduction on the transformed digital images, whereby the dimension reduction of the transformed digital images generates one or more reduced images, classifying one or more pixels of the one or more reduced images based on a comparison with the object detector, and identifying one or more objects of interest from the classified pixels.
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2.发明授权公开(公告)号：US09545196B2
公开(公告)日：2017-01-17
申请号：US14397756
申请日：2013-03-15
发明人： Michael Abramoff , Milan Sonka
CPC分类号： G06T7/0016 , A61B3/0025 , A61B3/102 , A61B3/1225 , G06T2207/10101 , G06T2207/30041
摘要： Systems and methods for assessing glaucoma loss using optical coherence topography. One method according to an aspect comprises receiving optical coherence image data and assessing functional glaucoma damage from retinal optical coherence image data. In an aspect, the systems and methods can map regions and layers of the eye to determine structural characteristics to compare to functional characteristics.
摘要翻译： 使用光学相干形貌评估青光眼损失的系统和方法。 根据一个方面的一种方法包括接收光学相干图像数据并从视网膜光学相干图像数据评估功能性青光眼损伤。 在一方面，系统和方法可以映射眼睛的区域和层以确定与功能特征相比较的结构特征。
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3.发明授权公开(公告)号：US11288808B2
公开(公告)日：2022-03-29
申请号：US16985896
申请日：2020-08-05
发明人： Michael Abramoff , Xiaodong Wu
摘要： Disclosed are systems and methods for image segmentation using convolutional networks. Image data comprising an image hypervolume can be received. The image hypervolume can be provided to a trained convolutional neural network (CNN). The CNN can output a segmentation of the image hypervolume.
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公开(公告)号：US10354384B2
公开(公告)日：2019-07-16
申请号：US15371925
申请日：2016-12-07
发明人： Michael Abramoff , Milan Sonka
摘要： Systems and methods for assessing glaucoma loss using optical coherence topography. One method according to an aspect comprises receiving optical coherence image data and assessing functional glaucoma damage from retinal optical coherence image data. In an aspect, the systems and methods can map regions and layers of the eye to determine structural characteristics to compare to functional characteristics.
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公开(公告)号：US20170236282A1
公开(公告)日：2017-08-17
申请号：US15371925
申请日：2016-12-07
发明人： Michael Abramoff , Milan Sonka
CPC分类号： G06T7/0016 , A61B3/0025 , A61B3/102 , A61B3/1225 , G06T2207/10101 , G06T2207/30041
摘要： Systems and methods for assessing glaucoma loss using optical coherence topography. One method according to an aspect comprises receiving optical coherence image data and assessing functional glaucoma damage from retinal optical coherence image data. In an aspect, the systems and methods can map regions and layers of the eye to determine structural characteristics to compare to functional characteristics.
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公开(公告)号：US20190295257A1
公开(公告)日：2019-09-26
申请号：US16440480
申请日：2019-06-13
发明人： Michael Abramoff , Milan Sonka
摘要： Systems and methods for assessing glaucoma loss using optical coherence topography. One method according to an aspect comprises receiving optical coherence image data and assessing functional glaucoma damage from retinal optical coherence image data. In an aspect, the systems and methods can map regions and layers of the eye to determine structural characteristics to compare to functional characteristics.
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7.发明申请公开(公告)号：US20180108139A1
公开(公告)日：2018-04-19
申请号：US15788509
申请日：2017-10-19
发明人： Michael Abramoff , Xiaodong Wu
CPC分类号： G06T7/11 , G06N3/0445 , G06N3/0454 , G06N3/084 , G06T2200/04 , G06T2207/10072 , G06T2207/10136 , G06T2207/20081 , G06T2207/20084 , G06T2207/20124
摘要： Disclosed are systems and methods for image segmentation using convolutional networks. Image data comprising an image hypervolume can be received. The image hypervolume can be provided to a trained convolutional neural network (CNN). The CNN can output a segmentation of the image hypervolume.
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公开(公告)号：US20240104741A1
公开(公告)日：2024-03-28
申请号：US18522805
申请日：2023-11-29
发明人： Michael Abramoff , Milan Sonka
CPC分类号： G06T7/0016 , A61B3/0025 , A61B3/102 , A61B3/1225 , G06T2207/10101 , G06T2207/30041
摘要： Systems and methods for assessing glaucoma loss using optical coherence topography. One method according to an aspect comprises receiving optical coherence image data and assessing functional glaucoma damage from retinal optical coherence image data. In an aspect, the systems and methods can map regions and layers of the eye to determine structural characteristics to compare to functional characteristics.
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公开(公告)号：US11935235B2
公开(公告)日：2024-03-19
申请号：US17901582
申请日：2022-09-01
发明人： Michael Abramoff , Gwenole Quellec
CPC分类号： G06T7/0012 , G06F18/00 , G06T7/75 , G06V40/193 , G06T2207/10024 , G06T2207/20081 , G06T2207/30041 , G06T2207/30096 , G06V2201/03
摘要： A method of identifying an object of interest can comprise obtaining first samples of an intensity distribution of one or more object of interest, obtaining second samples of an intensity distribution of confounder objects, transforming the first and second samples into an appropriate first space, performing dimension reduction on the transformed first and second samples, whereby the dimension reduction of the transformed first and second samples generates an object detector, transforming one or more of the digital images into the first space, performing dimension reduction on the transformed digital images, whereby the dimension reduction of the transformed digital images generates one or more reduced images, classifying one or more pixels of the one or more reduced images based on a comparison with the object detector, and identifying one or more objects of interest from the classified pixels.
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10.发明申请Methods And Systems For Determining Optimal Features For Classifying Patterns Or Objects In Images 审中-公开用于确定图像中图案或物体分类的最佳特征的方法和系统公开(公告)号：US20130108131A1
公开(公告)日：2013-05-02
申请号：US13692652
申请日：2012-12-03
发明人： Michael Abramoff , Stephen Russell
CPC分类号： G06K9/66 , G06K9/6231 , G06K9/6277 , G06T7/0014
摘要： Provided are methods for determining optimal features for classifying patterns or objects. Also provided are methods for image analysis. Further provided are methods for image searching.
摘要翻译： 提供了用于确定用于对图案或对象进行分类的最佳特征的方法。 还提供了图像分析的方法。 进一步提供图像搜索的方法。
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