Prabhakar Rajiah

Publications

Alilou, M., Prasanna, P., Bera, K., Gupta, A., Rajiah, P., Yang, M., Jacono, F., Velcheti, V., Gilkeson, R., Linden, P., & Madabhushi, A. (2021). A Novel Nodule Edge Sharpness Radiomic Biomarker Improves Performance of Lung-RADS for Distinguishing Adenocarcinomas from Granulomas on Non-Contrast CT Scans. Cancers, 13 (11), 2781.
Khorrami, M., Bera, K., Thawani, R., Rajiah, P., Gupta, A., Fu, P., Linden, P., Pennell, N., Jacono, F., Gilkeson, R., Velchetii, V., & Madabhushi, A. (2021). Distinguishing granulomas from adenocarcinomas by integrating stable and discriminating radiomic features on non-contrast computed tomography scans. European Journal of Cancer, 148 , 146 - 158.
Khorrami, M., Bera, K., Leo, P., Vaidya, P., Patil, P., Thawani, R., Velu, P., Rajiah, P., Alilou, M., Choi, H., Feldman, M., Gilkeson, R., Linden, P., Fu, P., Pass, H., Velcheti, V., & Madabhushi, A. (2020). Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study. Lung Cancer, 142 , 90-97.
Vaidya, P., Bera, K., Gupta, A., WAng, X., Corredor-Prada, G., Fu, P., Beig, N., Prasanna, P., Patil, P., Velu, P., Rajiah, P., Gilkeson, R., Feldman, M., Choi, H., Velcheti, V., & Madabhushi, A. (2020). CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction. The Lancet Digital Health, 2 (3), e116-e128.
Khorrami, M., Bera, K., Leo, P., Vaidya, P., Patil, P., Thawani, R., Velu, P., Rajiah, P., Alilou, M., Choi, H., & Others, H. (2020). Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study. Lung Cancer, 142 , 90--97.
Khorrami, M., Khunger, M., Zagouras, A., Patil, P., Thawani, R., Bera, K., Rajiah, P., Fu, P., Velcheti, V., & Madabhushi, A. (2019). Combination of Peri- and Intratumoral Radiomic Features on Baseline CT Scans Predicts Response to Chemotherapy in Lung Adenocarcinoma. Radiology: Artificial Intelligence, 1 (2).
Beig, N., Khorrami, M., Alilou, M., Prasanna, P., Braman, N., Orooji, M., Rakshit, S., Bera, K., Rajiah, P., Ginsberg, J., Donatelli, C., Thawani, R., Yang, M., Jacono, F., Tiwari, P., Velcheti, V., Gilkeson, R., Linden, P., & Madabhushi, A. (2019). Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas. Radiology, 290 (3), 783-792.
Alilou, M., Orooji, M., Beig, N., Prasanna, P., Rajiah, P., Donatelli, C., Velcheti, V., Rakshit, S., Yang, M., Jacono, F., Gilkeson, R., Linden, P., & Madabhushi, A. (2018). Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas. Scientific Reports, 8 (1).
Orooji, M., Alilou, M., Rakshit, S., Beig, N., Khorrami, M., Rajiah, P., Thawani, R., Ginsberg, J., Donatelli, C., Yang, M., Jacono, F., Gilkeson, R., Velcheti, V., Linden, P., & Madabhushi, A. (2018). Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography. Journal of Medical Imaging, 5 (2).
Zhou, X., Rosenthal, N., Parikh, S., Okere, I., Rajiah, P., Wilson, D. L., & Bezerra, H. L. (2013). A Novel Porcine Model of Acute Myocardial Ischemia Guided by FFR for Accuracy of Dynamic CT Myocardial Perfusion Imaging Study. Circulation, 128 (22 Supplement), A17885.