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Titlebook: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; Third International Alessandro Crimi,Spyridon Bakas,Mauricio

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发表于 2025-3-21 17:10:47 | 显示全部楼层 |阅读模式
期刊全称Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
期刊简称Third International
影响因子2023Alessandro Crimi,Spyridon Bakas,Mauricio Reyes
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; Third International  Alessandro Crimi,Spyridon Bakas,Mauricio
影响因子.This book constitutes revised selected papers from the Third International MICCAI Brainlesion Workshop, BrainLes 2017, as well as the International Multimodal Brain Tumor Segmentation, BraTS, and White Matter Hyperintensities, WMH, segmentation challenges, which were held jointly at the Medical Image computing for Computer Assisted Intervention Conference, MICCAI, in Quebec City, Canada, in September 2017. ..The 40 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections named: brain lesion image analysis; brain tumor image segmentation; and ischemic stroke lesion image segmentation..
Pindex Conference proceedings 2018
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发表于 2025-3-21 20:32:16 | 显示全部楼层
0302-9743 this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections named: brain lesion image analysis; brain tumor image segmentation; and ischemic stroke lesion image segmentation..978-3-319-75237-2978-3-319-75238-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
发表于 2025-3-22 02:28:23 | 显示全部楼层
Mechanisms and Ways of Macrophage Deliveryre we propose a new set of evaluation techniques that offer new insights into the behavior of segmentation algorithms. We illustrate these techniques with a case study comparing two popular multiple sclerosis (MS) lesion segmentation algorithms: OASIS and LesionTOADS.
发表于 2025-3-22 06:53:50 | 显示全部楼层
Kylie B. R. Belchamber,Louise E. Donnelly who underwent brain gliomas resection. By using landmark-based mean target registration errors (TRE) for evaluation, our technique has achieved a result of 2.32 ± 0.68 mm from the initial 5.13 ± 2.78 mm.
发表于 2025-3-22 12:23:46 | 显示全部楼层
Regulation of Macrophage Productional time of patients. The proposed deep learning frameworks was evaluated on BraTS 17 validation set and achieved competing results for tumor segmentation While Dice scores of 0.88, 0.75 0.71 were achieved for whole tumor, enhancing tumor and tumor core, respectively, an accuracy of 0.55 was obtained for survival prediction.
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发表于 2025-3-22 18:32:18 | 显示全部楼层
Dice Overlap Measures for Objects of Unknown Number: Application to Lesion Segmentationre we propose a new set of evaluation techniques that offer new insights into the behavior of segmentation algorithms. We illustrate these techniques with a case study comparing two popular multiple sclerosis (MS) lesion segmentation algorithms: OASIS and LesionTOADS.
发表于 2025-3-22 23:28:44 | 显示全部楼层
MARCEL (Inter-Modality Affine Registration with CorrELation Ratio): An Application for Brain Shift C who underwent brain gliomas resection. By using landmark-based mean target registration errors (TRE) for evaluation, our technique has achieved a result of 2.32 ± 0.68 mm from the initial 5.13 ± 2.78 mm.
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