Scale-invariant brain morphometry: application to sulcal depth
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866908662960750592 |
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| author | Dieudonné, Maxime Auzias, Guillaume Lefèvre, Julien |
| author_facet | Dieudonné, Maxime Auzias, Guillaume Lefèvre, Julien |
| contents | The geometry of the human cortex is complex and highly variable, with interactions between brain size, cortical folding, and age well-documented in the literature. However, few studies have explored how global brain size influences morphometry features of the cortical surface derived from anatomical MRI. In this work, we focus on sulcal depth, an imaging phenotype that has gained attention in both basic research and clinical applications. We make key contributions to the field by: 1) providing the first quantitative analysis of the influence of brain size on sulcal depth measurements; 2) introducing a novel, scale-invariant method for sulcal depth estimation based on an original formalization of the problem; 3) presenting a validation framework and sharing our code and benchmark data with the community; and 4) demonstrating the biological relevance of our new sulcal depth measure using a large sample of 1,987 subjects spanning the developmental period from 26 weeks post-conception to adulthood. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_05436 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Scale-invariant brain morphometry: application to sulcal depth Dieudonné, Maxime Auzias, Guillaume Lefèvre, Julien Computer Vision and Pattern Recognition The geometry of the human cortex is complex and highly variable, with interactions between brain size, cortical folding, and age well-documented in the literature. However, few studies have explored how global brain size influences morphometry features of the cortical surface derived from anatomical MRI. In this work, we focus on sulcal depth, an imaging phenotype that has gained attention in both basic research and clinical applications. We make key contributions to the field by: 1) providing the first quantitative analysis of the influence of brain size on sulcal depth measurements; 2) introducing a novel, scale-invariant method for sulcal depth estimation based on an original formalization of the problem; 3) presenting a validation framework and sharing our code and benchmark data with the community; and 4) demonstrating the biological relevance of our new sulcal depth measure using a large sample of 1,987 subjects spanning the developmental period from 26 weeks post-conception to adulthood. |
| title | Scale-invariant brain morphometry: application to sulcal depth |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2501.05436 |