Krishna Nand Keshava Murthy
Graduate Student
Office: 233 Richmond Street, Room 203

I am pursuing my PhD studies in the department of computer engineering at Brown University. I am also working at the Memorial Sloan Kettering Cancer Center, NYC, as an imaging data scientist. My research interests are in computer vision and machine learning as applied to medical image analysis. Some specific projects I have worked on include treatment prediction modeling, medical image segmentation/registration, image classification, anatomical shape modeling, image generative models, and content based image retrieval.


  • Krishna N. Keshavamurthy, Dmitry Dylov, Elena Petre, Steve Solomon, Jeremy Durack: Spectroscopy and Machine Learning Based Rapid Point-of-Care Assessment of Core Needle Cancer Biopsies (in submission, Nature partner journal digital imaging).
  • Krishna N. Keshavamurthy, Pierre Elnajjar, Amin El-Rowmeim, Hao-Hsin Shih, Ian Pan, Kinh Gian Do, Krishna Juluru: Application of Deep Learning Techniques to Characterization of 3D Radiological Datasets - A Pilot Study for Detection of Intravenous Contrast in Breast MRI. (Proc. SPIE medical imaging 2019).
  • Krishna Juluru, Hao-Hsin Shih, Pierre Elnajjar, Amin El-Rowmeim Josef Fox, Eliot Siegel, Krishna Nand Keshava Murthy, Building Blocks for Integrating Image Analysis Algorithms into a Clinical Workflow, (in submission, Journal of digital imaging).
  • Imber BS, Lin AL, Zhang Z, Keshavamurthy KN, Deipolyi AR, Beal K, Cohen MA, Tabar V, DeAngelis LM, Geer EB, Yang TJ, Young RJ, Comparison of radiographic approaches to assess treatment response in pituitary adenomas: is RECIST or RANO good enough?, Journal of the Endocrinal Society, 2019
  • Krishna N. Keshavamurthy, Scott A. Collins, Damian E. Dupuy, Benjamin B. Kimia, Derek Merck: A data driven model for microwave ablation, presented at RSNA conference, 2017.
  • Krishna N. Keshavamurthy, Scott A. Collins, Damian E. Dupuy, Benjamin B. Kimia, Derek Merck: An Accurate Image-Based Metric for Recurrence Prediction after Lung Cancer Ablation, presented at WCIO conference, 2017
  • Krishna N. Keshava, Owen Leary, Lisa H. Merck, Benjamin B. Kimia, Scott A. Collins, David W. Wright, Jason W. Allen, Derek Merck: Machine learning algorithm for automatic detection of CT-identifiable traumatic brain injury lesions. Proc. SPIE 10134, Medical Imaging 2017.
  • Damian E. Dupuy, Krishna N. Keshava, Lakir Patel: Can We Predict Lung Ablation Success by Power and Location Alone? Journal of Vascular and Interventional Radiology 27(9), (2016). Special Issue: Interventional Oncology.
  • Krishna N. Keshavamurthy, Scott A. Collins, Damian E. Dupuy, Benjamin B. Kimia, Derek Merck: Image guided tumor ablation: is it time for a registry? Lessons learned from an international survey, Presentation at Society of Interventional Radiology, 2017.
  • Krishna N. Keshava, Benjamin B. Kimia, Madeleine Cook, Damian E. Dupuy, Scott A. Collins, Derek Merck: A methodology to analyze treatment zone geometry and variability of percutaneous thermal ablation. Proc. SPIE 9326, Energy-based Treatment of Tissue and Assessment VIII, 93260Y (March 11, 2015).
  • David Glidden, Krishna N. Keshava, Madeleine Cook, Scott A. Collins, Garron Deshazer, Grayson Baird, Benjamin B. Kimia, Damian E. Dupuy, Derek Merck: Clinically observed ablation volumes as compared to vendor specified volumes: The emperors new clothes. Presented at the Society of Interventional Radiology (SIR), (2014).
  • Krishna Nand, K., Abugharbieh, R., Hamarneh, G.: Diffusion tensor image processing using complex quaternions, ISBI, pp. 538-541, IEEE (2012)
  • Krishna Nand, K., Abugharbieh, R., Booth, B.G., Hamarneh, G.: Detecting Structure in Diffusion Tensor MR Images. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011. LNCS, vol. 6892, pp. 9097. Springer, Heidelberg (2011).
  • Krishna Nand, K., Sreenivas, T.V.: Two stage iterative Wiener filtering for speech enhancement. In: INTERSPEECH-2008. pp. 175-178.
  • Rao, B.P.C., Thirunavukkarasu, S., Krishna Nand, K., Jayakumar, T., Kalyanasundaram, P., Baldev Raj: Enhancement of magnetic flux Leakage images of defects in carbon steel using Eigen vector based approach. Journal of Non-Destructive Testing and Evaluation 23(1), 35-42 (2008).
  • Krishna Nand, K., Rao, B.P.C., Jayakumar, T., Baldev Raj: Novel wavelet transform based approaches to process eddy current signals from stainless steel cladding tubes. Journal of Non-Destructive Testing and Evaluation (India) 6(10), 41-50 (2007).
  • Krishna Nand, K., Rao, B.P.C., Jayakumar, T., Baldev Raj: A new approach to process magnetic flux leakage images. In: National seminar on Non-Destructive Evaluation 2006.