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- W2471631844 abstract "Stroke is a common cause of sudden death and disability worldwide. In clinical practice, brain magnetic resonance (MR) scans are used to assess the stroke lesion presence. In this work, we have built a fully automatic stroke lesion segmentation system using 3D brain magnetic resonance (MR) data. The system contains a 3D registration framework and a 3D multi-random forest model trained from the data provided by the Ischemic Stroke Lesion Segmentation (ISLES) challenge of the 18th International Conference on Medical Image Computing and Computer Assisted Intervention. The preliminary test results show that the presented system is capable to detect stroke lesion from 3D brain MRI data." @default.
- W2471631844 created "2016-07-22" @default.
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- W2471631844 date "2016-01-01" @default.
- W2471631844 modified "2023-09-27" @default.
- W2471631844 title "Stroke Lesion Segmentation of 3D Brain MRI Using Multiple Random Forests and 3D Registration" @default.
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- W2471631844 doi "https://doi.org/10.1007/978-3-319-30858-6_19" @default.
- W2471631844 hasPublicationYear "2016" @default.
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