Multi-dimensional Parameter Space Exploration for Streamline-specific Tractography
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909282829598720 |
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| author | Vink, Ruben Vilanova, Anna Chamberland, Maxime |
| author_facet | Vink, Ruben Vilanova, Anna Chamberland, Maxime |
| contents | One of the unspoken challenges of tractography is choosing the right parameters for a given dataset or bundle. In order to tackle this challenge, we explore the multi-dimensional parameter space of tractography using streamline-specific parameters (SSP). We 1) validate a state-of-the-art probabilistic tracking method using per-streamline parameters on synthetic data, and 2) show how we can gain insights into the parameter space by focusing on streamline acceptance using real-world data. We demonstrate the potential added value of SSP to the current state of tractography by showing how SSP can be used to reveal patterns in the parameter space. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_05056 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multi-dimensional Parameter Space Exploration for Streamline-specific Tractography Vink, Ruben Vilanova, Anna Chamberland, Maxime Image and Video Processing Computer Vision and Pattern Recognition One of the unspoken challenges of tractography is choosing the right parameters for a given dataset or bundle. In order to tackle this challenge, we explore the multi-dimensional parameter space of tractography using streamline-specific parameters (SSP). We 1) validate a state-of-the-art probabilistic tracking method using per-streamline parameters on synthetic data, and 2) show how we can gain insights into the parameter space by focusing on streamline acceptance using real-world data. We demonstrate the potential added value of SSP to the current state of tractography by showing how SSP can be used to reveal patterns in the parameter space. |
| title | Multi-dimensional Parameter Space Exploration for Streamline-specific Tractography |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2408.05056 |