Trained FIL model
收藏DataCite Commons2023-03-14 更新2024-07-28 收录
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https://figshare.com/articles/dataset/Trained_FIL_model/17143370
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资源简介：
The FIL model was trained on all 15 training subjects (fil15) from the MICCAI Challenge dataset, using a minimally informative, but proper Wishart prior, with <i>v</i><sub>0</sub>=1.0. An augmentation search radius of 3 voxels was used with a Gaussian weighting standard deviation of 2.0 voxels. Patch sizes were 4x4x4 voxels, and four outer iterations were used for model training. Up to <i>K</i>=24 basis functions were available to encode each patch. This file is the result.<br>A second model was trained on all 30 subjects (fil30) from the MICCAI Challenge dataset (35 scans, with repeat scans given a weighting of 0.5). Augmentation search radius was 2 voxels, with a Gaussian weighting standard deviation of 1.5 voxels. Other parameters remained the same as for fil15.<br>
提供机构：
figshare
创建时间：
2021-12-08
