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Ramon Correa

Researcher at Case Western Reserve University

Publications -  20
Citations -  278

Ramon Correa is an academic researcher from Case Western Reserve University. The author has contributed to research in topics: Population & Enhancing Lesion. The author has an hindex of 5, co-authored 16 publications receiving 160 citations.

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Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma

TL;DR: It is hypothesized that radiomic texture descriptors can capture tumor heterogeneity manifested as a result of molecular variations in tumor hypoxia, on routine treatment naïve MRI, and these imaging based texture surrogate markers of Hypoxia can discriminate GBM patients as short-term (STS), mid- term (MTS), and long-term survivors (LTS).
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Shape Features of the Lesion Habitat to Differentiate Brain Tumor Progression from Pseudoprogression on Routine Multiparametric MRI: A Multisite Study.

TL;DR: The preliminary results suggest that 3D shape attributes from the lesion habitat can differentially express across pseudoprogression and tumor progression and could be used to distinguish these radiographically similar pathologies.
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Reproducibility analysis of multi-institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset

TL;DR: This work addresses two critical challenges with regard to developing robust radiomic approaches: the lack of availability of reliable segmentation labels for GBM tumor sub-compartments, and identifying "reproducible" radiomic features that are robust to segmentation variability across readers/sites.
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Tumor Habitat-derived Radiomic Features at Pretreatment MRI That Are Prognostic for Progression-free Survival in Glioblastoma Are Associated with Key Morphologic Attributes at Histopathologic Examination: A Feasibility Study.

TL;DR: Preliminary findings demonstrated significant associations of prognostic radiomic features with disease-specific histologic attributes in glioblastoma, with implications for risk-stratifying patients with GBM for personalized treatment decisions.