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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2507.07010 |
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| _version_ | 1866915379733856256 |
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| author | Li, Zhiyuan Schilling, Kurt G. Landman, Bennett A. |
| author_facet | Li, Zhiyuan Schilling, Kurt G. Landman, Bennett A. |
| contents | Historically, functional magnetic resonance imaging (fMRI) of the brain has focused primarily on gray matter, particularly the cortical gray matter and associated nuclei. However, recent work has demonstrated that functional activity in white matter also plays a meaningful role in both cognition and learning. In previous work, we introduced the High Angular Resolution Functional Imaging (HARFI) pipeline, which demonstrated both local and global patterns of functional correlation in white matter. Notably, HARFI enabled exploration of asymmetric voxel-wise correlation using odd-order spherical harmonics. Although the original implementation of HARFI was released via GitHub, adoption was limited due to the technical complexity of running the source code. In this work, we present a robust and efficient containerized version of the HARFI pipeline, enabling seamless execution across multiple public datasets. Our goal is to facilitate broader and deeper exploration of functional white matter architecture, especially through the lens of high angular resolution functional correlations. The key innovation of this work is the containerized implementation, which we have made available under a permissive open-source license to support reproducible and accessible research practices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_07010 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust Containerization of the High Angular Resolution Functional Imaging (HARFI) Pipeline Li, Zhiyuan Schilling, Kurt G. Landman, Bennett A. Medical Physics Software Engineering Historically, functional magnetic resonance imaging (fMRI) of the brain has focused primarily on gray matter, particularly the cortical gray matter and associated nuclei. However, recent work has demonstrated that functional activity in white matter also plays a meaningful role in both cognition and learning. In previous work, we introduced the High Angular Resolution Functional Imaging (HARFI) pipeline, which demonstrated both local and global patterns of functional correlation in white matter. Notably, HARFI enabled exploration of asymmetric voxel-wise correlation using odd-order spherical harmonics. Although the original implementation of HARFI was released via GitHub, adoption was limited due to the technical complexity of running the source code. In this work, we present a robust and efficient containerized version of the HARFI pipeline, enabling seamless execution across multiple public datasets. Our goal is to facilitate broader and deeper exploration of functional white matter architecture, especially through the lens of high angular resolution functional correlations. The key innovation of this work is the containerized implementation, which we have made available under a permissive open-source license to support reproducible and accessible research practices. |
| title | Robust Containerization of the High Angular Resolution Functional Imaging (HARFI) Pipeline |
| topic | Medical Physics Software Engineering |
| url | https://arxiv.org/abs/2507.07010 |