Satish Viswanath

Assistant Professor, Biomedical Engineering
develops novel medical image analysis and machine learning tools for targeting and evaluating interventions
Office: 523D Wickenden Phone Number: (216) 368-3888 Email: satish.viswanath@case.edu

Patents Received

Publications

Eck, B., Chirra, P., Muchhala, A., Hall, S., Bera, K., Tiwari, P., Madabhushi, A., Seiberlich, N., & Viswanath, S. E. (2021). Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions In Vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters. Journal of Magnetic Resonance Imaging (JMRI).
Sadri, A., Janowczyk, A., Zhou, R., Verma, R., Beig, N., Antunes, J., Madabhushi, A., Tiwari, P., & Viswanath, S. E. (2020). Technical Note: MRQy — An open-source tool for quality control of MR imaging data. Medical Physics, 47 (12), 6029-6038.
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.
Penzias, G., Singanamalli, A., Elliott, R., Gollamudi, J., Shih, N., Feldman, M., Stricker, P., Delprado, W., Tiwari, S., B�hm, M., Haynes, A., Ponsky, L., Fu, P., Tiwari, P., Viswanath, S. E., & Madabhushi, A. E. (2018). Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings. PLoS ONE, 13 (8).
Antunes, J., Selvam, A., Bera, K., Brady, J., Willis, J., Paspulati, R., Madabhushi, A., Delaney, C., & Viswanath, S. E. (2018). 857 - Machine Learning Analysis of the Whole Rectal Wall on Post-Neoadjuvant Chemoradiation MRI may offer Accurate Identifiction of Rectal Cancer Patients Needing more Aggressive Follow-Up or Surgery. Gastroenterology, 154 (6).
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.
Antunes, J., Viswanath, S. E., Brady, J. E., Crawshaw, B. E., Ros, P. E., Steele, S. E., Delaney, C. E., Paspulati, R. E., Willis, J. E., & Madabhushi, A. E. (2018). Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging. Academic Radiology.
Kim, J., Bennett, N., Devita, M., Chahar, S., Viswanath, S. E., Lee, H. E., Jung, H. E., Shao, P. E., Childers, E. E., Liu, C. E., Kulesa, A. E., Garcia, B. E., Becker, M. E., Hwang, W. E., Madabhushi, A. E., Verzi, M. E., & Moghe, P. E. (2017). Optical High Content Nanoscopy of Epigenetic Marks Decodes Phenotypic Divergence in Stem Cells.. Scientific reports, 7 , 39406.
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).
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).
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).
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.
Penzias, G., Janowczyk, A., Singanamalli, A., Rusu, M., Shih, N., Feldman, M., Stricker, P., Delprado, W., Tiwari, S., Böhm, M., Haynes, A., Ponsky, L., Viswanath, S. E., & Madabhushi, A. E. (2016). AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments.. Scientific reports, 6 , 29906.
Penzias, G., Janowczyk, A., Singanamalli, A., Rusu, M., Shih, N., Feldman, M., Stricker, P., Delprado, W., Tiwari, S., Böhm, M., Haynes, A., Ponsky, L., Viswanath, S. E., & Madabhushi, A. E. (2016). AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments. Scientific Reports, 6
Antunes, J., Viswanath, S. E., Rusu, M. E., Valls, L. E., Hoimes, C. E., Avril, N. E., & Madabhushi, A. E. (2016). Radiomics Analysis on FLT-PET/MRI for Characterization of Early Treatment Response in Renal Cell Carcinoma: A Proof-of-Concept Study.. Translational oncology, 9 (2), 155-62.
Antunes, J., Viswanath, S. E., Rusu, M. E., Valls, L. E., Hoimes, C. E., Avril, N. E., & Madabhushi, A. E. (2016). Radiomics Analysis on FLT-PET/MRI for Characterization of Early Treatment Response in Renal Cell Carcinoma: A Proof-of-Concept Study. Translational Oncology [19365233], 9 (2), 155-162.
Cohn, H., Lu, C., Paspulati, R., Katz, J., Madabhushi, A., Stein, S., Cominelli, F., Viswanath, S. E., & Dave, M. E. (2016). Tu1966 A Machine-Learning Based Risk Score to Predict Response to Therapy in Crohn's Disease via Baseline MRE. Gastroenterology [00165085], 150 (4).
Penzias, G., Janowczyk, A., Singanamalli, A., Rusu, M., Shih, N., Feldman, M., Stricker, P., Delprado, W., Tiwari, S., Böhm, M., Haynes, A., Ponsky, L., Viswanath, S. E., & Madabhushi, A. E. (2016). AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments. Scientific Reports [20452322], 6
Basavanhally, A., Viswanath, S. E., & Madabhushi, A. E. (2015). Predicting classifier performance with limited training data: applications to computer-aided diagnosis in breast and prostate cancer.. PloS one, 10 (5), e0117900.
Basavanhally, A., Viswanath, S. E., & Madabhushi, A. E. (2015). Predicting Classifier Performance With Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer. PLOS ONE.
Ginsburg, S., Viswanath, S. E., Bloch, B. E., Rofsky, N. E., Genega, E. E., Lenkinski, R. E., & Madabhushi, A. E. (2015). Novel PCA-VIP scheme for ranking MRI protocols and identifying computer-extracted MRI measurements associated with central gland and peripheral zone prostate tumors.. Journal of magnetic resonance imaging : JMRI, 41 (5), 1383-93.
Ginsburg, S., Viswanath, S. E., Bloch, B. E., Genega, E. E., Lenkinski, R. E., Rofsky, N. E., & Madabhushi, A. E. (2015). A Novel PCA-VIP Scheme for Ranking MRI Protocols and Identifying Computer Extracted MRI Measurements Associated with Central Gland and Peripheral Zone Prostate Tumors. Journal of Magnetic Resonance Imaging.
Ginsburg, S., Viswanath, S. E., Bloch, B. E., Rofsky, N. E., Genega, E. E., Lenkinski, R. E., & Madabhushi, A. E. (2015). Novel PCA-VIP Scheme for Ranking MRI Protocols and Identifying Computer-Extracted MRI Measurements Associated With Central Gland and Peripheral Zone Prostate Tumors. JOURNAL OF MAGNETIC RESONANCE IMAGING, 41 (5), 1383-1393.
Viswanath, S. E., Toth, R. E., Rusu, M. E., Sperling, D. E., Lepor, H. E., Futterer, J. E., & Madabhushi, A. E. (2014). Identifying Quantitative <i>In Vivo</i> Multi-Parametric MRI Features For Treatment Related Changes after Laser Interstitial Thermal Therapy of Prostate Cancer.. Neurocomputing, 144 , 13-23.
Litjens, G., Huisman, H., Elliott, R., Shih, N., Feldman, M., Viswanath, S. E., Futterer, J. E., Bomers, J. E., & Madabhushi, A. E. (2014). Quantitative identification of MRI features of prostate cancer response following laser ablation and radical prostatectomy. Journal of Medical Imaging.
Litjens, G., Huisman, H., Elliott, R., Shih, N., Feldman, M., Viswanath, S. E., Futterer, J. E., Bomers, J. E., & Madabhushi, A. E. (2014). Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomy.. Journal of medical imaging (Bellingham, Wash.), 1 (3), 035001.
Madabhushi, A., Litjens, G., Huisman, H., Elliott, R., Shin, N., Feldman, M., Viswanath, S. E., Futterer, J. E., & Bomers, J. E. (2014). Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomy. Journal of Medical Imaging, 1 (3), 9 pages.
Viswanath, S. E., Toth, R. E., Rusu, M. E., Sperling, D. E., Lepor, H. E., Futterer, J. E., & Madabhushi, A. E. (2014). Identifying Quantitative In Vivo Multi-Parametric MRI Features For Treatment Related Changes after Laser Interstitial Thermal Therapy of Prostate Cancer. Neurocomputing.
Viswanath, S. E., Toth, R. E., Rusu, M. E., Sperling, D. E., Lepor, H. E., Futterer, J. E., & Madabhushi, A. E. (2013). Quantitative Evaluation of Treatment Related Changes on Multi-Parametric MRI after Laser Interstitial Thermal Therapy of Prostate Cancer.. Proceedings of SPIE--the International Society for Optical Engineering, 8671 , 86711F.
Viswanath, S. E., Bloch, B. E., Chappelow, J. E., Toth, R. E., Rofsky, N. E., Genega, E. E., Lenkinski, R. E., & Madabhushi, A. E. (2012). Central gland and peripheral zone prostate tumors have significantly different quantitative imaging signatures on 3 Tesla endorectal, in vivo T2-weighted MR imagery.. Journal of magnetic resonance imaging : JMRI, 36 (1), 213-24.
Tiwari, P., Viswanath, S. E., Kurhanewicz, J. E., Sridharan, A. E., & Madabhushi, A. E. (2012). Multimodal wavelet embedding representation for data combination (MaWERiC): integrating magnetic resonance imaging and spectroscopy for prostate cancer detection.. NMR in biomedicine, 25 (4), 607-19.
Viswanath, S. E., & Madabhushi, A. E. (2012). Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data.. BMC bioinformatics, 13 , 26.
Viswanath, S. E., Bloch, B. E., Chappelow, J. E., Patel, P. E., Rofsky, N. E., Lenkinski, R. E., Genega, E. E., & Madabhushi, A. E. (2011). Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE): Detecting Prostate Cancer on Multi-Parametric MRI.. Proceedings of SPIE--the International Society for Optical Engineering, 7963 , 79630U.
Viswanath, S. E., Tiwari, P. E., Chappelow, J. E., Toth, R. E., Kurhanewicz, J. E., & Madabhushi, A. E. (2011). CADOnc<sup>©</sup>: An Integrated Toolkit For Evaluating Radiation Therapy Related Changes In The Prostate Using Multiparametric MRI.. Proceedings. IEEE International Symposium on Biomedical Imaging, 2011 , 2095-2098.
Palumbo, D., Yee, B., O'Dea, P., Leedy, S., Viswanath, S. E., & Madabhushi, A. E. (2011). Interplay between bias field correction, intensity standardization, and noise filtering for T2-weighted MRI.. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011 , 5080-3.
Viswanath, S. E., Bloch, B. E., Rosen, M. E., Chappelow, J. E., Toth, R. E., Rofsky, N. E., Lenkinski, R. E., Genega, E. E., Kalyanpur, A. E., & Madabhushi, A. E. (2009). Integrating Structural and Functional Imaging for Computer Assisted Detection of Prostate Cancer on Multi-Protocol <i>In Vivo</i> 3 Tesla MRI.. Proceedings of SPIE--the International Society for Optical Engineering, 7260 , 72603I.
Viswanath, S. E., Bloch, B. E., Genega, E. E., Rofsky, N. E., Lenkinski, R. E., Chappelow, J. E., Toth, R. E., & Madabhushi, A. E. (2008). A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 11 (Pt 1), 662-9.