Shankar, E., Kanwal, R., Goel, A., Yang, X., Shukla, S., MacLennan, G., Fu, P., Madabhushi, A., Ramakrishnan, P., & Gupta, S.(2017).Abstract 1080: Targeting the PI3K-Akt and NF-?B pathways as a combination therapy in blocking prostate cancer progression.Cancer Research,77(13 Supplement),1080-1080.
Velcheti, V., Alilou, M., Khunger, M., Thawani, R., & Madabhushi, A.(2017).Changes in Computer Extracted Features of Vessel Tortuosity on CT Scans Post-Treatment in Responders Compared to Non-Responders for NonSmall Cell Lung Cancer on Immunotherapy.Journal of Thoracic Oncology,12(8).
Shankar, E., Kanwal, R., Goel, A., Yang, X., Shukla, S., MacLennan, G., Fu, P., Liu, H., Madabhushi, A., & Gupta, S.(2017).PD33-02 PROSTATE CANCER AGGRESSIVENESS IS MEDIATED BY AKT AND NF-?B SIGNALING PATHWAYS: A SYSTEMS BIOLOGY APPROACH.The Journal of Urology,197(4).
Li, L., Pahwa, S., Penzias, G., Rusu, M., Gollamudi, J., Viswanath, S. E., & Madabhushi, A. E.(2017).Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation.Scientific Reports,7(1).
Ghose, S., Shiradkar, R., Rusu, M., Mitra, J., Thawani, R., Feldman, M., Gupta, A., Purysko, A., Ponsky, L., & Madabhushi, A.(2017).Field effect induced organ distension (FOrge) features predicting biochemical recurrence from pre-treatment prostate MRI.,10434 LNCS, 442-449.
Xue, Z., Monaco, J., Sparks, R., & Madabhushi, A.(2017).Connecting Markov random fields and active contour models: application to gland segmentation and classification.Journal of Medical Imaging,4(2).
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).
Bektik, E., Dennis, A., Prasanna, P., Madabhushi, A., & Fu, J.(2017).Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes.PLoS ONE,12(8).
Wang, H., Viswanath, S. E., & Madabhushi, A. E.(2017).Discriminative Scale Learning (DiScrn): Applications to Prostate Cancer Detection from MRI and Needle Biopsies.Scientific Reports,7(1).
Singanamalli, A., Wang, H., & Madabhushi, A.(2017).Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features.Scientific Reports,7(1).
Beig, N., Correa, R., Thawani, R., Prasanna, P., Badve, C., Gold, D., Madabhushi, A., DeBlank, P., & Tiwari, P.(2017).MEDU-48. MRI TEXTURAL FEATURES CAN DIFFERENTIATE PEDIATRIC POSTERIOR FOSSA TUMORS.Neuro-Oncology,19(suppl_4),iv47-iv47.
WAng, X., Janowczyk, A., Zhou, Y., Thawani, R., Fu, P., Schalper, K., Velcheti, V., & Madabhushi, A.(2017).Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images.Scientific Reports,7(1).
Ginsburg, S., Algohary, A., Pahwa, S., Gulani, V., Ponsky, L., Aronen, H., Boström, P., Böhm, M., Haynes, A., Brenner, P., Delprado, W., Thompson, J., Pulbrock, M., Taimen, P., Villani, R., Stricker, P., Rastinehad, A., Jambor, I., & Madabhushi, A.(2016).Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study..Journal of magnetic resonance imaging : JMRI.
Tiwari, P., Prasanna, P., Wolansky, L., Pinho, M., Cohen, M., Nayate, A., Gupta, A., Singh, G., Hatanpaa, K., Sloan, A., Rogers, L., & Madabhushi, A.(2016).Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study..AJNR. American journal of neuroradiology,37(12),2231-2236.
Prasanna, P., Tiwari, P., & Madabhushi, A.(2016).Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor..Scientific reports,6, 37241.
Shiradkar, R., Podder, T., Algohary, A., Viswanath, S. E., Ellison, C. E., & Madabhushi, A. E.(2016).Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI..Radiation oncology (London, England),11(1),148.
Shiradkar, R., Podder, T., Algohary, A., Viswanath, S. E., Ellis, R. E., & Madabhushi, A. E.(2016).Radiomics based targeted radiotherapy planning (Rad-TRaP): A computational framework for prostate cancer treatment planning with MRI.Radiation Oncology,11(1).
Prasanna, P., Patel, J., Partovi, S., Madabhushi, A., & Tiwari, P.(2016).Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings..European radiology.
Madabhushi, A., & Lee, G.(2016).Image analysis and machine learning in digital pathology: Challenges and opportunities..Medical image analysis,33, 170-5.
De Leon, A., Lee, G., Shih, N., Elliott, R., Feldman, M., & Madabhushi, A.(2016).Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images..Journal of medical imaging (Bellingham, Wash.),3(4),047502.
