Niha G. Beig
Orcid: 0000-0002-1150-5886
According to our database1,
Niha G. Beig
authored at least 12 papers
between 2014 and 2022.
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Bibliography
2022
Radiomic Deformation and Textural Heterogeneity (R-DepTH) Descriptor to Characterize Tumor Field Effect: Application to Survival Prediction in Glioblastoma.
IEEE Trans. Medical Imaging, 2022
Imaging-based histological features are predictive of MET alterations in Non-Small Cell Lung Cancer.
CoRR, 2022
2020
Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Proceedings of the Radiomics and Radiogenomics in Neuro-oncology, 2019
Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
2018
Vascular Network Organization via Hough Transform (VaNgOGH): A Novel Radiomic Biomarker for Diagnosis and Treatment Response.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
2017
Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An Integrated Descriptor for Brain Tumor Prognosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
2014
Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, San Diego, 2014