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Spatial pattern-driven interpretable model and biological correlates in brain glioblastoma-lymphoma differentiation
Summary Glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) often exhibit overlapping appearances on routine MRI, complicating pre-treatment diagnosis. In 1,109 patients from five centers, we constructed standard-space tumor probabilistic maps and derived atlas-anchored spatial features to augment co...
Deep Learning Pipeline for Automatic Segmentation, Classification, and Molecular Subtyping of Three Pediatric Posterior Fossa Tumors Using T2-Weighted MRI.
BACKGROUND Pediatric posterior fossa tumors vary in malignancy, treatment, and prognosis across tumor types and molecular subtypes, yet noninvasive preoperative differentiation remains challenging. PURPOSE To develop a deep learning (DL) pipeline using T2-weighted (T2w) MR images to automatically segment pediatric po...