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Dr. Nagesh Subbanna

Assistant Professor, Center for Wireless Networks & Applications (Amrita WNA), Amritapuri

Qualification: Ph.D
nageshks@am.amrita.edu
Research Interest: Biomedical Imaging, Computational Linguistics, Time Frequency Analysis

Bio

Dr. Nagesh Subbanna currently serves as an Assistant Professor at the Center for Wireless Networks & Applications, Amrita Vishwa Vidyapeetham, Amritapuri.

Work Experience

  1. Research Assistant, Department of Electrical Engineering, IISc December 2001 – January 2003
    The project was undertaken under the guidance of Prof. Y. V. Venkatesh between December 2001 and January 2003. We worked on the classification of satellite images and removing speckle noise in satellite images.
  2. Project Associate in the Department of Bioinformatics, Indian Institute of Science 2007 – July 2008
  3. Post Doctoral Fellow at the Department of Radiology in University of Pennsylvania February 2016 – February 2017
  4. Lead Computer Scientist in Sigtuple Technologies March 2017-July 201
  5. Post Doctoral Fellow at the Department of Biomedical Engineering in the University of Calgary August 2017 – April 2021

Nagesh Subbanna translated and published the book titled “Abhinava Shankara – Shree Shree Sacchidanandendra Swami Saraswati” by Hemalatha Shamanna to English.

Publications

Journal Article

Year : 2021

An analysis of the vulnerability of two common deep learning based medical image segmentation techniques to model inversion attacks

Cite this Research Publication : N. K. Subbanna, M. Wilms, A. Tuladhar, and N. D. Forkert, “An analysis of the vulnerability of two common deep learning based medical image segmentation techniques to model inversion attacks”, Sensors 2021, 21, 3874. DOI: https://doi.org/10.3390/s21113874

Publisher : Sensors 2021, 21, 3874

Year : 2020

Supervised machine learning tools: a tutorial for clinicians

Cite this Research Publication : Lucas Lo Vercio, Kimberly Amador, Jordan J Bannister, Sebastian Crites, Alejandro Gutierrez, M Ethan MacDonald, Jasmine Moore, Pauline Mouches, Deepthi Rajashekar, Serena Schimert, Nagesh Subbanna, Anup Tuladhar, Nanjia Wang, Matthias Wilms, Anthony Winder, Nils D Forkert, "Supervised machine learning tools: a tutorial for clinicians", accepted for publication at Journal of Neural Engineering (invited paper), 2020. DOI: 10.1088/1741-2552/abbff2

Publisher : Journal of Neural Engineering

Year : 2019

Stroke lesion segmentation in FLAIR MRI datasets using Customised Markov Random Fields

Cite this Research Publication : N. K. Subbanna, D. Rajashekhar, B. Cheng, G. Thomalla, J. Fiehler, T. Arbel, and N. D. Forkert, “Stroke lesion segmentation in FLAIR MRI datasets using Customised Markov Random Fields”, Frontiers in Neurology, May 2019, https://doi.org/10.3389/fneur.2019.00541

Publisher : Frontiers in Neurology

Year : 2015

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

Cite this Research Publication : Bjoern H. Menze,corresponding author Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elizabeth Gerstner, Marc-André Weber, Tal Arbel, Brian B. Avants, Nicholas Ayache, Patricia Buendia, D. Louis Collins, Nicolas Cordier, Jason J. Corso, Antonio Criminisi, Tilak Das, Hervé Delingette, Çağatay Demiralp, Christopher R. Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan M. Iftekharuddin, Raj Jena, Nigel M. John, Ender Konukoglu, Danial Lashkari, José António Mariz, Raphael Meier, Sérgio Pereira, Doina Precup, Stephen J. Price, Tammy Riklin Raviv, Syed M. S. Reza, Michael Ryan, Duygu Sarikaya, Lawrence Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos A. Silva, Nuno Sousa, Nagesh K. Subbanna, Gabor Szekely, Thomas J. Taylor, Owen M. Thomas, Nicholas J. Tustison, Gozde Unal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, and Koen Van Leemput, “The Multimodal Brain TumourImage Segmentation Benchmark: (BRATS)''. IEEE Transactions onMedical Imaging, Vol. 34(10): 1993-2024, October 2015.

Publisher : IEEE Transactions on Medical Imaging.

Year : 2015

Bayesian Multiple Sclerosis Lesion Classification based on Modelling Regional Intensity Variability and Local Neighbourhood Information

Cite this Research Publication : R. Harmouche, N. K. Subbanna, D. L. Collins, D. L. Arnold, and T. Arbel, “Bayesian Multiple Sclerosis Lesion Classification based on Modelling Regional Intensity Variability and Local Neighbourhood Information”, IEEE Transactions on Biomedical Engg. Vol. 62(5): 1281-1292, May 2015.

Publisher : IEEE Transactions on Biomedical Engineering.

Year : 2011

Evaluating intensity normalization on MRIs of human brain with multiple sclerosis

Cite this Research Publication : M. Shah, Y. Xiao, N. K. Subbanna, S. J. Francis, D. L. Collins, D. L. Arnold, and T. Arbel, “Evaluating intensity normalization on MRIs of human brain with multiple sclerosis”, Medical Image Analysis, Vol. 15(2): 267-282 (2011), DOI: 10.1016/j.media.2010.12.003

Publisher : Medical Image Analysis.

Year : 2008

Macromolecular sequence analysis using multiwindow Gabor Representations

Cite this Research Publication : N. K. Subbanna and Y. Y. Zeevi, "Macromolecular Sequence Analysis using Multiwindow Gabor Representations", Signal Processing, 88(4), pp. 877-890, April 2008, (Invited Paper).

Publisher : Signal Processing.

Year : 2007

Existence Conditions for Discrete Noncanonical Multiwindow Gabor Schemes

Cite this Research Publication : N. K. Subbanna and Y. Y. Zeevi, "Existence Conditions for Non-Canonical Discrete Multiwindow Gabor Frames", IEEE Transactions on Signal Processing, Vol. 55(10), pp. 5113-5117, October 2007. DOI: 10.1109/TSP.2007.896100

Publisher : IEEE Transactions on Signal Processing

Year : 2007

A Unified Approach to Gabor Windows

Cite this Research Publication : E. Matusiak, T. Werther, Y. C. Eldar, and N. K. Subbanna, "A Unified Approach to Gabor Windows", IEEE Transactions on Signal Processing, Vol. 55(5-1), pp. 1758-1768, May 2007. DOI: 10.1109/TSP.2006.890908

Publisher : IEEE Transactions on Signal Processing

Year : 2005

Dual Gabor frames: theory and computational aspects

Cite this Research Publication : T. Werther, Y. C. Eldar, and N. K. Subbanna, "Dual Gabor Frames: Theory and Computational Aspects", IEEE Transactions on Signal Processing, Vol. 53(11), pp. 4147-4158, November 2005. DOI: 10.1109/TSP.2005.857049

Publisher : IEEE Transactions on Signal Processing

Conference Paper

Year : 2024

Automated Quantification of Mammographic Density in Craniocaudal Oblique-View Radiographs

Cite this Research Publication : K.Athira,J.Lekshmi,D.K.Vijayakumar,and N.K.Subbanna,``Automated Quantification of Mammographic Density in Craniocaudal
Oblique-View Radiographs’’, accepted for publication at 9th IEEE conference on convergence in technology (I2CT 2024)

Year : 2023

Atlas based breast registration and segmentation in the Medio lateral Obliqueand Craniocaudal views

Cite this Research Publication : K.Athira,J.Dharmarajan,D.K.Vijayakumar,and N.K. Subbanna, ``Atlas based breast registration and segmentation in the Medio lateral Obliqueand Craniocaudal views’’, in 2nd International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT 2023)

Year : 2023

A survey of the various techniques used for breast segmentation from mammogram

Cite this Research Publication : K.Athira,J.Dharmarajan,D.K.Vijayakumar, and N. K. Subbanna, ``A survey of the various techniques used for breast segmentation from mammogram’’,in International Conference On Distributed Computing And Electrical Circuits And Electronics 2023

Year : 2022

Estimation of Breast Density from Human mammograms using U-Nets

Cite this Research Publication : Y.Saikumar,J.P.Dharmarajan,S.S.Karve,D.K. Vijayakumar,andN.K.Subbanna,``Estimation of Breast Density from Human mammograms using U-Nets’’, in proceedings of the 6th International Conference on Computing, Communication, Control and Automation (ICCUBEA-2022)

Publisher : IEEE

Year : 2021

Understanding Privacy Risks in Typical Deep Learning Models for Medical Image Analysis

Cite this Research Publication : N. K. Subbanna, A. Tuladhar, M. Wilms, and N. D. Forkert, "Understanding Privacy Risks in Typical Deep Learning Models for Medical Image Analysis", Accepted for Publication at SPIE 2020, San Diego, February 2021.

Publisher : Proceedings Volume 11601, Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications

Year : 2019

Morphology-based estimation of disease duration in multiple sclerosis patients using T1-weighted MRI datasets

Cite this Research Publication : N. K. Subbanna, A. Rauscher, D. Li, A. Traboulsee, G. B. Pike, N. D. Forkert, "Morphology-based estimation of disease duration in multiple sclerosis patients using T1-weighted MRI datasets", Computer Aided Radiology and Surgery, Rennes, June 18-21, 2019.

Publisher : Computer Aided Radiology and Surgery.

Year : 2018

Novel Techniques for MS Lesion Segmentation Algorithm Evaluation

Cite this Research Publication : I. Oguz, A. Carass, D. L. Pham, S. Roy, N. K. Subbanna, P. A. Calabresi, P. A. Yushkevich, R. T. Shinohara, J. L. Prince, "Novel Techniques for MS Lesion Segmentation Algorithm Evaluation", Multiple Sclerosis Journal, Vol. 24: pp. 72-73 (ACTRIMS Presentation), 2018.

Publisher : Multiple Sclerosis Journal.

Year : 2017

Dice Overlap Measures for Objects of Unknown Number: Application to Lesion Segmentation

Cite this Research Publication : I. Oguz, A. Carass, D. L. Pham, S. Roy, N. K. Subbanna, P. A. Calabresi, P. A. Yushkevich, R. T. Shinohara, J. L. Prince, "Dice Overlap Measures for Objects of Unknown Number: Application to Lesion Segmentation", International MICCAI Brain Lesion Workshop, pp. 3-14, MICCAI 2017. doi: 10.1007/978-3-319-75238-9_1

Publisher : International MICCAI Brain Lesion Workshop.

Year : 2017

Multiple Sclerosis Lesion Segmentation Using Joint Label Fusion

Cite this Research Publication : M. Dong, I. Oguz, N. K. Subbanna, P. Calabresi, R. T. Shinohara, and P. Yuskhevich, “Multiple Sclerosis Lesion Segmentation Using Joint Label Fusion”, Patch Based Techniques in Medical Imaging, MICCAI 2017.

Publisher : Patch Based Techniques in Medical Imaging, MICCAI 2017

Year : 2017

Lesion Detection, Segmentation and Prediction in Multiple Sclerosis Clinical Trials

Cite this Research Publication : Andrew Doyle, Colm Elliott, Zahra Karimaghaloo, Nagesh Subbanna, Douglas L. Arnold, Tal Arbel, "Lesion Detection, Segmentation and Prediction in Multiple Sclerosis Clinical Trials", Third International Workshop, BrainLes 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, pp.15-28. (Invited Talk)

Publisher : Third International Workshop, BrainLes 2017

Year : 2015

IMaGe: Iterative Multilevel Probabilistic Graphical Model for Detection and Segmentation of Multiple Sclerosis Lesions in Brain MRI

Cite this Research Publication : N.K. Subbanna, D. Precup, D.L. Arnold, and T. Arbel, “IMaGE: Iterative Multilevel Probabilistic Graphical Model for Detection and Segmentation of Multiple Sclerosis Lesions in Brain MRI”, in Proceedings of Information Processing for Medical Imaging (IPMI), 2015. (Acceptance Rate in IPMI 2015: 31%) DOI: 10.1007/978-3-319-19992-4_40

Publisher : Proceedings of Information Processing for Medical Imaging (IPMI) .

Year : 2014

Iterative Multilevel MRF Leveraging Context and Voxel Information for Brain Tumour Segmentation in MRI

Cite this Research Publication : N. K. Subbanna, D. Precup and T. Arbel, "Iterative Multilevel MRF Leveraging Context and Voxel Information for Brain Tumour Segmentation in MRI", Accepted to the 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), June 2014. (Acceptance Rate in CVPR 2014: 29.7%)

Publisher : 2014 IEEE Conference on Computer Vision and Pattern Recognition

Year : 2013

Hierarchical Probabilistic Segmentation of Brain Tumours in MRI

Cite this Research Publication : N. K. Subbanna, D. Precup, D. L. Collins and T. Arbel, ``Hierarchical Probabilistic Segmentation of brain tumours in MRI'' in Proceedings of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI '13), Nagoya, Japan, Sept. 2013, Lecture Notes in Computer Science, Springer, Vol. 8149, pp. 751-758. (Acceptance Rate in MICCAI 2013: 32%)

Publisher : Proceedings of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI '13), Nagoya, Japan, Sept. 2013, Lecture Notes in Computer Science, Springer.

Year : 2012

Probabilistic Gabor and Markov Random Fields Segmentation of Brain Tumours in MRI Volumes

Cite this Research Publication : N. K. Subbanna, V. Fonov, D. L. Collins, and T. Arbel, "Probabilistic Gabor and Markov Random Fields Segmentation of Brain Tumours in MRI Volumes", in Proceedings of the Workshop on Multimodal Brain Tumor Segmentation Challenge (BraTS 2012) held in conjunction with the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI '12), Nice, France, October 2012. (Oral Presentation)

Publisher : Proceedings of the Workshop on Multimodal Brain Tumor Segmentation Challenge (BraTS 2012) held in conjunction with the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI '12)

Year : 2011

Adapted MRF Segmentation of MS Lesions Using Local Contextual Information

Cite this Research Publication : N. K. Subbanna, S. J. Francis, D. Precup, D. L. Collins, D. L. Arnold, and T. Arbel, "Adapted MRF Segmentation of MS Lesions Using Local Contextual Information", in Medical Image Understanding and Analysis (MIUA 2011), July 14-15, London.

Publisher : Medical Image Understanding and Analysis

Year : 2009

MS Lesion Segmentation using Markov Random Fields

Cite this Research Publication : N. K. Subbanna, M. Shah, S. J. Francis, S. Narayanan, D. L. Collins, D. L. Arnold, and T. Arbel, "MS Lesion Segmentation using Markov Random Fields'', in Proceedings of the MICCAI Workshop on Medical Image Analysis on Multiple Sclerosis (Segmentation and Validation Issues) 2009 (MIAMS09), pp. 15-26, September 2009, London.

Publisher : Proceedings of the MICCAI Workshop on Medical Image Analysis on Multiple Sclerosis (Segmentation and Validation Issues) 2009 (MIAMS09)

Year : 2008

Capturing Metabolite Flow in Biological Systems through Kinetic Radio-tracer simulations

Cite this Research Publication : N. K. Subbanna, J. P. Bhat, Y. Y. Zeevi, and N. R. Chandra, ``Capturing Metabolite Flow in Biological Systems through Kinetic Radio-tracer simulations'', in Proceedings of the 9th International Conference on Systems Biology, Gothenburg, Sweden, August 2008.

Publisher : Proceedings of the 9th International Conference on Systems Biology, Gothenburg, Sweden.

Year : 2007

An Efficient Analysis of Protein Conformation Using Sequence Representations in Combined Space

Cite this Research Publication : N. K. Subbanna, Y. Y. Zeevi, and N. Lotan, "An Efficient Analysis of Protein Conformation Using Sequence Representations in Combined Space", in Proceedings of 21st Symposium of the Protein Society, July 2007.

Publisher : Proceedings of 21st Symposium of the Protein Society

Year : 2006

Image Representations Using Non-Canonical Discrete Multiwindow Gabor Frames

Cite this Research Publication : N. K. Subbanna, and Y. Y. Zeevi, "Image Representations Using Non-Canonical Discrete Multiwindow Gabor Frames", in Proceedings of the 3rd International conference on Visual Information Engineering, Bangalore, India (VIE 2006), September 2006.

Publisher : Proceedings of the 3rd International conference on Visual Information Engineering

Year : 2005

An Efficient Analysis Technique for DNA Sequences Using Multiwindow Gabor Representations

Cite this Research Publication : N. K. Subbanna, and Y. Y. Zeevi, "An Efficient Analysis Technique for DNA Sequences Using Multiwindow Gabor Representations", in Proceedings of the 13th European Signal Processing Conference, Antalya, Turkey (EUSIPCO 05), September 2005 (One of the Ten Best Student Papers of the Conference).

Publisher : Proceedings of the 13th European Signal Processing Conference

Year : 2005

Indexing of Macromolecules Using Multiwindow Gabor Representations

Cite this Research Publication : N. K. Subbanna, Y. Y. Zeevi, “Indexing of Macromolecules Using Multiwindow Gabor Representations”, in Proceedings of 4th International Workshop on Content Based Multimedia Indexing, Riga, Latvia (CBMI 05), June 2005.

Publisher : Proceedings of 4th International Workshop on Content Based Multimedia Indexing, Riga, Latvia (CBMI 05).

Year : 2005

Oversampling of the Generalised Multiwindow Gabor Space

Cite this Research Publication : N. K. Subbanna, Y. C. Eldar, and Y. Y. Zeevi, “Oversampling of the Generalised Multiwindow Gabor Space”, in Proceedings of the 6th International Workshop on Sampling Theory and Applications, Samsun, Turkey (SampTA 05), July 2005.

Publisher : Proceedings of the 6th International Workshop on Sampling Theory and Applications

Year : 2004

Efficient Gabor expansion using non minimal dual Gabor windows

Cite this Research Publication : N. K. Subbanna, and Y. C. Eldar, “Efficient Gabor Expansion Using Non-Minimal Dual Gabor Windows”, in the Proceedings of the 11th International Conference on Electronics, Circuits, and Systems, Tel-Aviv, Israel (ICECS 2004), December 2004. DOI: 10.1109/ICECS.2004.1399764

Publisher : Proceedings of the 11th International Conference on Electronics, Circuits, and Systems, Tel-Aviv, Israel (ICECS 2004)

Year : 2004

A Fast Algorithm for Calculating the Dual Gabor Window with Integer Oversampling

Cite this Research Publication : N. K. Subbanna, and Y. C. Eldar, “A Fast Algorithm for Calculating the Dual Gabor Window with Integer Oversampling", in Proceedings of the 23rd IEEE Convention of Electrical and Electronic Engineers in Israel, Herziliya, Israel (IEEEI 2004), September 2004.

Publisher : Proceedings of the 23rd IEEE Convention of Electrical and Electronic Engineers in Israel, Herziliya, Israel (IEEEI 2004).

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