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Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study.

, , , , , , , , , , , and . Frontiers Comput. Neurosci., (2020)

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Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109500B. SPIE, (2019)Networking Research Innovations for Telesurgery: A Systematic Review., , , , , , , , , and 1 other author(s). SDS, page 1-8. IEEE, (2022)Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI., , , , , , , , , and 1 other author(s). MICCAI (2), volume 12262 of Lecture Notes in Computer Science, page 305-314. Springer, (2020)Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study., , , , , , , , , and 2 other author(s). Frontiers Comput. Neurosci., (2020)Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI., , , , , , , , , and 3 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109501E. SPIE, (2019)A radiomics approach to distinguish non-contrast enhancing tumor from vasogenic edema on multi-parametric pre-treatment MRI scans for glioblastoma tumors., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 12033 of SPIE Proceedings, SPIE, (2022)"Lesion-habitat" radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumors., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Knowledge Management Model Supported by Social Networks. Case: University-Enterprise., , and . KMO, page 361-373. Springer, (2013)Adversarial Debiasing techniques towards 'fair' skin lesion classification., , and . NER, page 1-4. IEEE, (2023)