{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T17:13:28Z","timestamp":1790961208252,"version":"4.1.0"},"reference-count":20,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T00:00:00Z","timestamp":1741046400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Hippocampal segmentation is essential in neuroimaging for evaluating conditions like Alzheimer\u2019s dementia and mesial temporal sclerosis, where small volume changes can significantly impact normative percentiles. However, inaccurate segmentation is common due to the inclusion of non-hippocampal structures such as choroid plexus and cerebrospinal fluid (CSF), leading to volumetric overestimation and confounding of functional analyses. Current methods of assessment largely rely on virtual or manual ground truth labels, which can fail to capture these inaccuracies. To address this shortcoming, this study introduces a more direct voxel intensity-based method of segmentation assessment. Using paired precontrast and postcontrast T1-weighted MRIs, hippocampal segmentations were refined by adding marginal gray matter and removing marginal CSF and enhancement to determine a total required correction volume. Six segmentation algorithms\u2014e2dhipseg, HippMapp3r, hippodeep, AssemblyNet, FastSurfer, and QuickNat\u2014were implemented and compared. HippMapp3r and e2dhipseg, followed closely by hippodeep, exhibited the least total correction volumes, indicating superior accuracy. Dedicated hippocampal segmentation algorithms outperformed whole-brain methods.<\/jats:p>","DOI":"10.3390\/bioengineering12030258","type":"journal-article","created":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T07:47:37Z","timestamp":1741074457000},"page":"258","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Intensity-Based Assessment of Hippocampal Segmentation Algorithms Using Paired Precontrast and Postcontrast MRI"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0350-184X","authenticated-orcid":false,"given":"Justin","family":"Cramer","sequence":"first","affiliation":[{"name":"Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leslie","family":"Baxter","sequence":"additional","affiliation":[{"name":"Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harrison","family":"Lang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathon","family":"Parker","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alicia","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0949-0736","authenticated-orcid":false,"given":"Nicholas","family":"Matthees","sequence":"additional","affiliation":[{"name":"Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7145-833X","authenticated-orcid":false,"given":"Ichiro","family":"Ikuta","sequence":"additional","affiliation":[{"name":"Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6241-735X","authenticated-orcid":false,"given":"Yalin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computing and Augmented Intelligence, Arizona State University, 699 S Mill Ave, Tempe, AZ 85281, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxiang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Radiology, Mayo Clinic Arizona, 5711 E Mayo Blvd, Phoenix, AZ 85054, 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