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1. Fast, Sequence Adaptive Parcellation of Brain MR Using Parametric Models NSTL国家科技图书文献中心

Oula Puonti | Juan Eugenio Iglesia...... - 《Medical image computing and computer-assisted intervention--MICCAI 2013 : Part I /》 - International Conference on Medical Image Computing and Computer-Assisted Intervention - 2013, - 727～734 - 共8页

摘要： method obtains* state-of-the-art segmentation* | . Compared to the* non-parametric, multi-atlas segmentation | brain parcellation using the type of generative* | , while retaining all the* benefits of generative* | -valued intensities) MR data. We have validated our

关键词： obtains state-of-the-art;;the non-parametric;;MR data

NSTL主题词： Fasting | Parametric statistics | Parametric | Self tuning | Sequences | Cerebrum

2. Fast, Sequence Adaptive Parcellation of Brain MR Using Parametric Models NSTL国家科技图书文献中心

Oula Puonti | Juan Eugenio Iglesia...... - 《Medical image computing and computer-assisted intervention - MICCAI 2013, part 1: 16th International conference on medical imaging computing and computer-assisted intervention (MICCAI 2013), September 22-26, 2013, Nagoya, Japan》 - International conference on medical imaging computing and computer-assisted intervention - 2013, - 727～734 - 共8页

摘要： method obtains* state-of-the-art segmentation* | . Compared to the* non-parametric, multi-atlas segmentation | brain parcellation using the type of generative* | , while retaining all the* benefits of generative* | -valued intensities) MR data. We have validated our

NSTL主题词： Fasting | Parametric statistics | Parametric | Self tuning | Cerebrum

3. Fast, Sequence Adaptive Parcellation of Brain MR Using Parametric Models NSTL国家科技图书文献中心

Oula Puonti | Juan Eugenio Iglesia...... - 《Medical image computing and computer-assisted intervention - MICCAI 2013: 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, p.I》 - International Conference on Medical Image Computing and Computer-Assisted Intervention - 2013, - 727～734 - 共8页

摘要： method obtains* state-of-the-art segmentation* | . Compared to the* non-parametric, multi-atlas segmentation | brain parcellation using the type of generative* | , while retaining all the* benefits of generative* | -valued intensities) MR data. We have validated our

NSTL主题词： Fasting | Parametric statistics | Parametric | Self tuning | Cerebrum

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obtains state-of-the-art;;the non-parametric;;MR data

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