Soumya Ghose

Publications

Atta-Fosu, T., LaBarbara, M., Ghose, S., Schoenhagen, P., Saliba, W., Tchou, P., Lindsay, B., Desai, M., Kwon, D., Chung, M., & Madabhushi, A. (2021). A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT. BMC Medical Imaging, 21 (1), 45.
Prasanna, P., Mitra, J., Beig, N., Nayate, A., Patel, S., Ghose, S., Thawani, R., Partovi, S., Madabhushi, A., & Tiwari, P. (2019). Mass Effect Deformation Heterogeneity (MEDH) on Gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility study. Scientific Reports, 9 (1).
Shiradkar, R., Ghose, S., Jambor, I., Taimen, P., Ettala, O., Purysko, A., & Madabhushi, A. (2018). Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings. Journal of Magnetic Resonance Imaging, 48 (6), 1626-1636.
Algohary, A., Viswanath, S. E., Shiradkar, R. E., Ghose, S. E., Pahwa, S. E., Moses, D. E., Jambor, I. E., Shnier, R. E., Böhm, M. E., Haynes, A. E., Brenner, P. E., Delprado, W. E., Thompson, J. E., Pulbrock, M. E., Purysko, A. E., Verma, S. E., Ponsky, L. E., Stricker, P. E., & Madabhushi, A. E. (2018). Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings. Journal of Magnetic Resonance Imaging, 48 (3), 818-828.
Shiradkar, R., Ghose, S., Jambor, I., Taimen, P., Ettala, O., Purysko, A., & Madabhushi, A. (2018). Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings: Prostate Cancer Recurrence Prediction. Journal of Magnetic Resonance Imaging.
Algohary, A., Viswanath, S. E., Shiradkar, R. E., Ghose, S. E., Pahwa, S. E., Moses, D. E., Jambor, I. E., Shnier, R. E., B�hm, M. E., Haynes, A. E., Brenner, P. E., Delprado, W. E., Thompson, J. E., Pulbrock, M. E., Purysko, A. E., Verma, S. E., Ponsky, L. E., Stricker, P. E., & Madabhushi, A. E. (2018). Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings: Radiomics Categorizes PCa Patients on AS. Journal of Magnetic Resonance Imaging.
Thawani, R., McLane, M., Beig, N., Ghose, S., Prasanna, P., Velcheti, V., & Madabhushi, A. (2018). Radiomics and radiogenomics in lung cancer: A review for the clinician. Lung Cancer, 115 , 34-41.
Ghose, S., Shiradkar, R., Rusu, M., Mitra, J., Thawani, R., Feldman, M., Gupta, A., Purysko, A., Ponsky, L., & Madabhushi, A. (2017). Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings. Scientific Reports, 7 (1).
Madabhushi, A., Ghose, S., Shiradkar, R., & Rajat, T. (2017). Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings. Scientific Reports, 7 (1), 15829.
Shiradkar, R., Ghose, S., Villani, R., Ben-Levi, E., Rastinehad, A., & Madabhushi, A. (2017). PD65-08 DISTINGUISHING LOW VERSUS HIGH RISK PROSTATE CANCER LESIONS USING RADIOMIC FEATURES DERIVED FROM MULTI-PARAMETRIC MAGNETIC RESONANCE IMAGING (MRI). The Journal of Urology, 197 (4).