Satish Viswanath, PhD

Assistant Professor
Department of Biomedical Engineering
School of Medicine
Case School of Engineering
Assistant Professor
Department of Radiology
School of Medicine
Member
Cancer Imaging Program
Case Comprehensive Cancer Center

Research Information

Research Projects

The primary focus of my lab is developing novel medical image analysis and machine learning tools for imaging data, through spatial correlation and cross-linking against pathology or molecular data.

Applications of our tools are being examined in:

  1. Decision support for treatment (e.g. choice of therapy)
  2. Targeting therapeutic procedures (e.g. guiding ablation, radiotherapy, surgery)
  3. Biological quantitation for treatment response characterization in vivo

This multi-disciplinary, multi-pronged approach is being applied to colorectal, renal, and prostate cancers, as well as digestive diseases.

Publications

View All Publications

Viswanath, S+, Tiwari P+, Lee, G+, Madabhushi, A, “Dimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases”. BMC Med Imaging. 2017 Jan 5;17(1):2. (+joint first authors) [PMID: 28056889, PMCID: PMC5217665]

Antunes, J, Viswanath, S, Rusu, M, Valls, L, Hoimes, C, Avril, N, Madabhushi, A, “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): 155-162, 2016 [PMID: 27084432, PMCID: PMC4833889]

Antunes J., Prasanna P., Madabhushi A., Tiwari P., Viswanath S. (2017) RADIomic Spatial TexturAl descripTor (RADISTAT): Characterizing Intra-tumoral Heterogeneity for Response and Outcome Prediction. In: Descoteaux M., Maier-Hein L., Franz A., Jannin P., Collins D., Duchesne S. (eds) Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017. MICCAI 2017. Lecture Notes in Computer Science, vol 10434. Springer, Cham