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公开(公告)号：EP3794548A1
公开(公告)日：2021-03-24
申请号：EP19724456.9
申请日：2019-05-14
发明人： BREDNO, Joerg , LORSAKUL, Auranuch
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公开(公告)号：EP3552179B1
公开(公告)日：2021-03-10
申请号：EP17829947.5
申请日：2017-12-08
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公开(公告)号：EP3759685A1
公开(公告)日：2021-01-06
申请号：EP19710957.2
申请日：2019-03-01
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公开(公告)号：EP3703007A3
公开(公告)日：2020-10-28
申请号：EP20159613.7
申请日：2020-02-26
发明人： Lou, Bin , Odry, Benjamin
摘要： Brain tumor or other tissue classification and/or segmentation is provided based on from multi-parametric MRI. MRI spectroscopy, such as in combination with structural and/or diffusion MRI measurements, are used to classify. A machine-learned model or classifier distinguishes between the types of tissue in response to input of the multi-parametric MRI. To deal with limited training data for tumors, a patch-based system may be used. To better assist physicians in interpreting results, a confidence map may be generated using the machine-learned classifier.
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公开(公告)号：EP3683767A1
公开(公告)日：2020-07-22
申请号：EP19151746.5
申请日：2019-01-15
摘要： An image analysis method and device is for detecting failure or error in an image segmentation procedure. The method comprises comparing (14) segmentation outcomes for two or more images, representative of a particular anatomical region at different respective time points, and identifying a degree of consistency or deviation between them. Based on this derived consistency or deviation measure, a measure of accuracy of the segmentation procedure is determined (16).
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公开(公告)号：EP3682420A1
公开(公告)日：2020-07-22
申请号：EP18905184.0
申请日：2018-02-06
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公开(公告)号：EP3281174B1
公开(公告)日：2020-03-25
申请号：EP16718084.3
申请日：2016-04-06
发明人： BOON, Cathy, L. , LI, Zheng
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