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It is also a critical target for interventions such as deep brain stimulation and serves as an important biomarker in clinical trials, including those investigating remyelination therapies. Despite extensive research on corpus callosum segmentation, few publicly available tools provide a comprehensive and automated analysis pipeline. To address this gap, we present FastSurfer-CC, an efficient and fully automated framework for corpus callosum morphometry. FastSurfer-CC automatically identifies mid-sagittal slices, segments the corpus callosum and fornix, localizes the anterior and posterior commissures to standardize head positioning, generates thickness profiles and subdivisions, and extracts eight shape metrics for statistical analysis. We demonstrate that FastSurfer-CC outperforms existing specialized tools across the individual tasks. Moreover, our method reveals statistically significant differences between Huntington\u2019s disease patients and healthy controls that are not detected by the current state-of-the-art.<\/jats:p>","DOI":"10.1162\/imag.a.1221","type":"journal-article","created":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T20:02:06Z","timestamp":1775592126000},"update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":0,"title":["FastSurfer-CC: A robust, accurate, and comprehensive framework for corpus callosum morphometry"],"prefix":"10.1162","volume":"4","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-1645-7609","authenticated-orcid":false,"given":"Clemens","family":"Pollak","sequence":"first","affiliation":[{"name":"AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kersten","family":"Diers","sequence":"additional","affiliation":[{"name":"AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Santiago","family":"Estrada","sequence":"additional","affiliation":[{"name":"AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"K\u00fcgler","sequence":"additional","affiliation":[{"name":"AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Martin","family":"Reuter","sequence":"additional","affiliation":[{"name":"AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany"},{"name":"A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States"},{"name":"Department of Radiology, Harvard Medical School, Boston, MA, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","published-online":{"date-parts":[[2026,5,8]]},"reference":[{"key":"2026050815550723800_IMAG.a.1221-b1","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1007\/s12021-014-9236-3","article-title":"Software pipeline for midsagittal corpus callosum thickness profile processing: Automated segmentation, manual editor, thickness profile generator, group-wise statistical comparison and results display","volume":"12","author":"Adamson","year":"2014","journal-title":"Neuroinformatics"},{"issue":"12","key":"2026050815550723800_IMAG.a.1221-b2","doi-asserted-by":"crossref","first-page":"2131","DOI":"10.1002\/hbm.21174","article-title":"Thickness profile generation for the corpus callosum using Laplace\u2019s equation","volume":"32","author":"Adamson","year":"2011","journal-title":"Human Brain Mapping"},{"key":"2026050815550723800_IMAG.a.1221-b3","article-title":"Automated segmentation of corpus callosum in MRI scans: Application to tracking Alzheimer\u2019s disease progression. 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