Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. - Sukanya Iyer; Marwa Ismail; Benita Tamrazi; Ashley Margol; Ruchika Verma; Ramon Correa; Prateek Prasanna; Niha G. Beig; Kaustav Bera; Volodymyr Statsevych; Alexander R. Judkins; Anant Madabhushi; et al. (Computer-Aided Diagnosis, 2019)

Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma. - Ruchika Verma; Ramon Correa; Virginia B. Hill; Niha G. Beig; Abdelkader Mahammedi; Anant Madabhushi; Pallavi Tiwari (Computer-Aided Diagnosis, 2019)

"Lesion-habitat" radiomics to distinguish radiation necrosis from tumor recurrence on post-treatment MRI in metastatic brain tumors. - Ramon Correa; Qiu Lei; Jonathan Chen; Johnathan Zeng; Jennifer Yu; Pallavi Tiwari (Computer-Aided Diagnosis, 2020)

Spatial-And-Context Aware (SpACe) "Virtual Biopsy" Radiogenomic Maps to Target Tumor Mutational Status on Structural MRI. - Marwa Ismail; Ramon Correa; Kaustav Bera; Ruchika Verma; Anas Saeed Bamashmos; Niha G. Beig; Jacob Antunes; Prateek Prasanna; Volodymyr Statsevych; Manmeet Ahluwalia; Pallavi Tiwari (MICCAI (2), 2020)

Can tumor location on pre-treatment MRI predict likelihood of pseudo-progression versus tumor recurrence in Glioblastoma? A feasibility study. - Marwa Ismail; Virginia B. Hill; Volodymyr Statsevych; Evan Mason; Ramon Correa; Prateek Prasanna; Gagandeep Singh; Kaustav Bera; Rajat Thawani; Anant Madabhushi; Manmeet Ahluwalia; Pallavi Tiwari (CoRR, 2020)

Can Tumor Location on Pre-treatment MRI Predict Likelihood of Pseudo-Progression vs. Tumor Recurrence in Glioblastoma? - A Feasibility Study. - Marwa Ismail; Virginia B. Hill; Volodymyr Statsevych; Evan Mason; Ramon Correa; Prateek Prasanna; Gagandeep Singh; Kaustav Bera; Rajat Thawani; Manmeet Ahluwalia; Anant Madabhushi; Pallavi Tiwari (Frontiers Comput. Neurosci., 2020)

Reading Race: AI Recognises Patient's Racial Identity In Medical Images. - Imon Banerjee; Ananth Reddy Bhimireddy; John L. Burns; Leo Anthony Celi; Li-Ching Chen; Ramon Correa; Natalie Dullerud; Marzyeh Ghassemi; Shih-Cheng Huang; Po-Chih Kuo; Matthew P. Lungren; Lyle J. Palmer; et al. (CoRR, 2021)

Two-step adversarial debiasing with partial learning - medical image case-studies. - Ramon Correa; Jiwoong Jason Jeong; Bhavik N. Patel; Hari Trivedi; Judy W. Gichoya; Imon Banerjee (CoRR, 2021)

A radiomics approach to distinguish non-contrast enhancing tumor from vasogenic edema on multi-parametric pre-treatment MRI scans for glioblastoma tumors. - Ipsa Yadav; Marwa Ismail; Volodymyr Statsevych; Virginia B. Hill; Ramon Correa; Manmeet Ahluwalia; Pallavi Tiwari (Computer-Aided Diagnosis, 2022)

Networking Research Innovations for Telesurgery: A Systematic Review. - Pradeeban Kathiravelu; Elhadj Benkhelifa; Zachary Zaiman; Matthew Wang; Ramon Correa; Luís Veiga; Imon Banerjee; Hari Trivedi; Saptarshi Purkayastha; Judy Gichoya; Babak Mahmoudi (SDS, 2022)

The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.5M Screening and Diagnostic Mammograms. - Jiwoong Jason Jeong; Brianna L. Vey; Ananth Reddy Bhimireddy; Thomas Kim; Thiago Santos; Ramon Correa; Raman Dutt; Marina Mosunjac; Gabriela Oprea-Ilies; Geoffrey H. Smith; Minjae Woo; Christopher R. McAdams; et al. (CoRR, 2022)

Efficient adversarial debiasing with concept activation vector - Medical image case-studies. - Ramon Correa; Khushbu Pahwa; Bhavik N. Patel; Celine M. Vachon; Judy W. Gichoya; Imon Banerjee (J. Biomed. Informatics, 2024)