A fully automated imaging-native framework (CranioTrace) that transforms routine neuroimaging into standardized, population-referenced markers of cranial development, providing a foundation for imaging-based growth charting, integrated skull– brain phenotyping, and precise assessment of neurodevelopment.
P. Mattisson, A. Mandal, M. Gardner et al.· bioRxiv· 0 citations
Clinical brain MRIs from pediatric health systems represent a viable resource for modeling early neurodevelopmental trajectories and studying neurodevelopmental risk in real-world populations, and a robust segmentation approach tailored to early-life clinical MRIs with variable orientation, resolution, and contrast is...
E. Levitis, H. Tregidgo, D. Zimmerman et al.· medRxiv· 0 citations
Accurate prediction of tumor recurrence in brain tumor patients following surgery is essential for optimizing adjuvant therapy, response assessment, and surveillance regimen. While MRI remains the gold standard for surveillance, integrating patient-specific clinical context may inform recurrence prediction. Traditional...
D. Tak, D. Sreedhar, H. Aerts et al.· medRxiv· 0 citations
Training DMG segmentation models with post-treatment scans substantially improves performance in longitudinal clinical trial imaging, enabling more accurate volumetric tracking and response assessment.
John Zielke, F. Mussa, A. Zapaishchykova et al.· AJNR. American journal of ne...· 0 citations
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