-
公开(公告)号：US10748040B2
公开(公告)日：2020-08-18
申请号：US16193828
申请日：2018-11-16
IPC分类号： G06K9/00 , B41M5/00 , G06K9/62 , G06T7/00 , G06K9/66 , G16H30/20 , G16B25/00 , G16B40/00 , G16B20/00 , G06K9/46 , G16B40/20
摘要： Glioblastoma multiforme (GBM) is the most aggressive type of brain cancer. It is critical to determine the most effective patient-specific treatment quickly. Exemplary embodiments use a data-driven approach to extracting brain tumor information from data obtain from Whole Slide Image that is uploaded through an interface. Exemplary embodiments generate the following information about a glioblastoma tumor from a brain biopsy slide using neural networks: annotated areas of relevant tissues, molecular subtype, and expression status of an important gene and include three steps: the segmentation of tumor features; prediction of molecular subtype; and prediction of gene methylation status from a WSI.
-
公开(公告)号：US11416716B2
公开(公告)日：2022-08-16
申请号：US16934293
申请日：2020-07-21
IPC分类号： G06K9/00 , B41M5/00 , G06K9/62 , G06T7/00 , G16H30/20 , G16B25/00 , G16B40/00 , G16B20/00 , G16B40/20 , G06V10/44 , G06V20/69 , G06V30/194
摘要： Cancer can be an aggressive disease. It is critical to determine the most effective patient-specific treatment quickly. Exemplary embodiments use a data-driven approach to extracting tumor information from data obtain from Whole Slide Image that is uploaded through an interface. Exemplary embodiments generate the following information about a tumor from a biopsy slide using neural networks: annotated areas of relevant tissues, molecular subtype, and expression status of an important gene and include three steps: the segmentation of tumor features; prediction of molecular subtype; and prediction of gene methylation status from a WSI.
-
公开(公告)号：US20200349399A1
公开(公告)日：2020-11-05
申请号：US16934293
申请日：2020-07-21
IPC分类号： G06K9/62 , G06T7/00 , G06K9/66 , G16H30/20 , G16B25/00 , G16B40/00 , G16B20/00 , G06K9/46 , G06K9/00 , G16B40/20
摘要： Cancer can be an aggressive disease. It is critical to determine the most effective patient-specific treatment quickly. Exemplary embodiments use a data-driven approach to extracting tumor information from data obtain from Whole Slide Image that is uploaded through an interface. Exemplary embodiments generate the following information about a tumor from a biopsy slide using neural networks: annotated areas of relevant tissues, molecular subtype, and expression status of an important gene and include three steps: the segmentation of tumor features; prediction of molecular subtype; and prediction of gene methylation status from a WSI.
-
-
搜索结果
3 条记录 (耗时 0.011 秒)
