Principal Investigator: Pallavi Tiwari, PhD

Academic Advisor: Anant Madabhushi, PhD

Department of Biomedical Engineering, Case Western Reserve University

Principal Investigator: Jayaram Udupa, PhD

Department of Radiology, Perelman School of Medicine, University of Pennsylvania. 

M.S in Medical Image Processing and software (CGPA 9.4/10)

B.S in Medical Electronics. (First Class with Distinction)


Languages            :  R, Python (scikit, pandas), MATLAB (advanced)

Deep Learning      : Tensor Flow (beginner), keras


EECS 440 Machine Learning / (Case Western Reserve University)

CBIO 453 Cell Biology / (Case Western Reserve University)

EBME 401 Biomedical Instrumentation and Signal Analysis / (Case Western Reserve University)

Teaching Assistant CWRU EBME358: Biomedical Signals and Systems Laboratory (Fall 2017) /  (Case Western Reserve University)

Teaching Assistant CWRU EBME360 : Principles of Biomedical Instrumentation (Spring 2018) /  (Case Western Reserve University)

Computer Networks / (Manipal University, India)

Database Programming in Java / ( Manipal University, India)

Data Mining / ( Manipal University, India)



  • Radiogenomic characterization of response to chemo-radiation therapy in Glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. Niha Beig, Prateek Prasanna, Virginia Hill, Ruchika Verma, Vinay Varadan, Anant Madabhushi, and Pallavi Tiwari. SPIE, Medical Imaging: Computer-Aided Diagnosis (2019).
  • Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. Sukanya Iyer, Marwa Ismail, Benita Tamrazi,Ramon Correa, Prateek Prasanna, Niha Beig, Ruchika Verma, Kaustav Bera, Volodymyr Statsevych Ashley Margol, Alexander Judkins, Anant Madabhushi, and Pallavi Tiwari. SPIE, Medical Imaging: Computer-Aided Diagnosis (2019).
  • Radiomics of the lesion habitat on pre-treatment MRI to predict response to chemo-radiation therapy in Glioblastoma. Ruchika Verma, Ramon Correa, Virginia Hill, Niha Beig, Abdelkar Mahammedi, Anant Madabhushi, Pallavi Tiwari. SPIE, Medical Imaging: Computer-Aided Diagnosis (2019).
  • Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma. Niha Beig, Jay Patel, Prateek Prasanna, Sasan Partovi, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari. Proc. SPIE 10134, Medical Imaging: Computer-Aided Diagnosis (2017). doi:10.1117/12.2255694
  • Vascular Network organization via Hough transform (VaNgOGH): A novel radiomic biomarker for diagnosis and treatment response. Nathaniel Braman, Prateek Prasanna, Niha Beig, Mehdi Alilou, Anant Madabhushi. Medical Image Computing and Computer Assisted Intervention (MICCAI 2018). In Press
  • Radiographic-Deformation and Textural Heterogeneity (r-DepTH): An integrated descriptor for brain tumor prognosis. Prateek Prasanna, Jhimli Mitra, Niha Beig, Sasan Partovi, Gagan Singh, M Pinho, Anant Madabhushi, Pallavi Tiwari. Medical Image Computing and Computer Assisted Intervention (MICCAI 2017)
  • Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models. Monica M. S. Matsumoto, Niha Beig, Jayaram K. Udupa, Steven Archer, Drew A. Torigian. Proc. of SPIE Vol. 9035 90350J-1





  1. Beig, N, Hill, V, Prasanna, P, Varadan, V, Madabhushi, A, and Tiwari, P,“Support vector machine (SVM) classifier based approach for prediction of chemo-radiation therapy response in grade 4 brain tumors on pre-treatment MRI scans”, The 13th Women in Machine Learning (WiML) Workshop, 2018. Montreal, Quebec, Canada.
  2. Beig, N, Ismail, M, Madabhushi, A, Ahluwalia, M, Tiwari, P, “Probabilistic Atlases of Pre-Treatment MRI Reveal Hemispheric and Lobe-Specific Spatial Distributions across Molecular Sub-Types of Diffuse Gliomas”, Proceedings of the Radiological Society of North America Annual Meeting, 2018. Chicago, IL, USA.
  3. Beig, N,  Prasanna,P,  Verma,R, Hill,V, Varadan,V, Madabhushi,A, and Tiwari,P, “Radiomic features of Glioblastoma on pre-treatment Gd-T1w MRI are predictive of response to chemo-radiation therapy and associated with AKT and apoptosis pathways”, Proceedings of the Journal of Neuro-Oncology, 2018.  New Orleans, Louisiana, USA.
  4. Beig, N, Braman,N, Prasanna,P, Varadan,V, Madabhushi,A, and Tiwari,P, “Radiogenomic analysis of Glioblastoma reveals textural features from MRI that correlate with genomic immune score and are also predictive of chemo-radiation treatment response”, Proceedings of the Journal of Neuro-Oncology, 2018.  New Orleans, Louisiana, USA.
  5. Braman,N, Prasanna,P, Singh,S, Beig,N, et al.,“Intratumoral and peritumoral MRI signatures of HER2-enriched subtype also predict pathological response to neoadjuvant chemotherapy in HER2+ breast cancers”, San Antonio Breast Cancer Symposium, 2017. San Antonio, TX, USA
  6. Braman,N, Prasanna,P, Singh,S, Beig,N, et al.,“ Radiogenomic analysis of HER2+ breast cancer reveals MRI features correlated with genomic immune index are predictive of neoadjuvant chemotherapy response”, San Antonio Breast Cancer Symposium, 2017. San Antonio, TX, USA
  7. Prasanna P, Mitra J, Beig N, Partovi S, Singh G, Pinho M, Madabhushi A, Tiwari P. “Structural deformation field on T1w MRI in healthy brain parenchyma is associated with overall survival in treatment-naïve glioblastoma multiforme”, Society for Neuro-Oncology 2017. San Francisco, CA, USA
  8. Braman, N, Prasanna, P, Singh, S, Beig, N, Plecha, DM, Gilmore, H, Harris, L, Etesami, M, Bates, D,Gallagher, K, Bloch, N, Varadan, V, Madabhushi, A, ” Texture Entropy Features at 1 Centimeter Outside HER2+ Breast Cancer Lesions Predict Response-Associated Molecular Subtypes on DCE-MRI,” Proceedings of Radiologic Society of North America (RSNA) 2017. Chicago, IL, USA
  9. Beig,N , Correa,R , Thawani,R , Prasanna,P , Badve,C , Gold,D , deBlank,P , Madabhushi,A , and Tiwari,P. “MRI textural features can differentiate pediatric posterior fossa tumors”, SNO Pediatric Neuro-Oncology Basic and Translational Research Conference, 2017. New York City, NY, USA
  10. Beig,N , Correa,R , Prasanna,P , Mitra,J , Nayate,A , Madabhushi,A , and Tiwari,P. “Radiogenomic analysis of distinct tumor sub-compartments on T2 and FLAIR predict distinct molecular subtypes in Lower Grade Gliomas”, The International Society for Magnetic Resonance in Medicine (ISMRM), 2017. Honolulu, HI, USA
  11. Beig,N, Correa,R, Prasanna,P, Mitra,J, Nayate,A, Madabhushi,A, Tiwari,P. ”Predicting IDH mutation status on routine treatment-naïve MRI using radiogenomic features from peritumoral brain parenchyma”, Proceedings Of The Society For Neuro-Oncology, 2016. Scottsdale, AZ, USA
  12. Beig,N , Orooji,M, Rajiah,P , Rakshit,S , Yang,M , Jacono,F , Prasanna,P , Tiwari,P , Velcheti,V ,Gilkeson,R, Linden,P, Madabhushi,A, “Radiomic Features of the Perinodular Habitat on Non-contrast Lung CT Discriminates Adenocarcinoma from Granulomas”, Proceedings of the Radiologic Society of North America, 2016. Chicago, IL, USA
  13. Rakshit,S , Orooji,M , Beig,N , Rajiah,P , Yang,M , Jacono,F , Velcheti,V ,Gilkeson,R, Linden,P , Madabhushi,A, “Evaluation of radiomic features on baseline CT scan to predict clinical benefit for pemetrexed based chemotherapy in metastatic lung adenocarcinoma.” American Society of Clinical Oncology Annual Meeting, 2016. Chicago, IL, USA
  14. Orooji,M , Rakshit,S , Alilou,M, Beig,N , Rajiah,P , Yang,M , Jacono,F , Velcheti,V, Gilkeson,R, Linden,P , Madabhushi,A , “Computerized textural analysis of lung CT to enable quantification of tumor infiltrating lymphocytes in NSCLC.” American Society of Clinical Oncology Annual Meeting, 2016. Chicago, IL, USA

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Niha Beig on ResearchGate