Publications

  1. Richard D. White, Mutlu Demirer, Vikash Gupta, Ronnie A. Sebro, Frederick M. Kusumoto, Barbaros S. Erdal, Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions, Journal of Medical Imaging 9(5), 054504 (2022), (open access)

  2. Vikash Gupta, Mutlu Demirer, Robert W. Maxwell, Richard D. White, Barbaros Selnur Erdal, A multi-reconstruction study of breast density estimation using Deep Learning, Arxiv, 2022(preprint)

  3. Marcio ABC Rockenbach, Varun Buch, Vikash Gupta, Gopal K Kotecha, Olga Laur, Barbaros S Erdal, Dong Yang, Daguang Xu, Brian B Ghoshhajra, Mona G Flores, Ittai Dayan, Holger Roth, Richard D White, Automatic detection of decreased ejection fraction and left ventricular hypertrophy on 4D cardiac CTA: Use of artificial intelligence with transfer learning to facilitate multi-site operation. Intelligence Based Machines, 2022 (pdf)

  4. Mutlu Demirer, Richard D White, Vikash Gupta, Ronnie A Sebro, Barbaros Selnur Erdal, Cascading Neural Network Methodology for Artificial Intelligence-Assisted Radiographic Detection and Classification of Lead-Less Implanted Electronic Devices within the Chest, 2021 Pre print

  5. Richard D. White, Barbaros S. Erdal, Mutlu Demirer, Vikash Gupta, Matthew T. Bigelow, Engin Dikici, Sema Candemir, Mauricio S. Galizia, Jessica L. Carpenter, Thomas P. O’Donnell, Abdul H. Halabi, Luciano M. Prevedello, Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis During CCTA Evaluation of Chest Pain in the Emergency Department: Preparing an Application for Real-world Use, Journal of Digital Imaging, 2021 [paper]

  6. Vikash Gupta, Clayton Taylor, Sarah Bonnet, Luciano M. Prevedello, Jeffrey Hawley, Richard D White, Mona G Flores, Barbaros Selnur Erdal, Deep Learning-Based Automatic Detection of Poorly Positioned Mammograms to Minimize Patient Return Visits for Repeat Imaging: A Real-World Application. 2020 [preprint]

  7. Vikash Gupta, Holger Roth, Varun Buch, Marcio A.B.C. Rockenbach, Richard D White, Dong Yang, Olga Laur, Brian Ghoshhajra, Ittai Dayan, Daguang Xu, Mona G. Flores, Barbaros Selnur Erdal, Democratizing Artificial Intelligence in Healthcare: A Study of Model Development Across Two Institutions Incorporating Transfer Learning, 2020 [preprint]

  8. Holger R Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, and others, Federated Learning for Breast Density Classification: A Real-World Implementation, MICCAI Workshop on Distributed and Collaborative Learning, 2020

  9. Richard D. White, Barbaros S. Erdal, Mutlu Demirer, Vikash Gupta, Matthew T. Bigelow, Engin Dikici, Sema Candemir, Mauricio S. Galizia, Jessica L. Carpenter, Thomas P. O’Donnell, Abdul H. Halabi, Luciano M. Prevedello, Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis during CCTA Evaluation of Chest-Pain in the Emergency Department: Preparing an Application for Real-World Use. submitted [pdf]

  10. Sema Candemir, Richard D White, Mutlu Demirer, Vikash Gupta, Matthew T Bigelow, Luciano M Prevedello, Barbaros S Erdal, Automated Coronary Artery Atherosclerosis Detection and Weakly Supervised Localization on Coronary CT Angiography with a Deep 3-Dimensional Convolutional Neural Network. Computerized Medical Imaging and Graphics, 2020 [paper]

  11. Vikash Gupta, Mutlu Demirer, Matthew Bigelow, Sarah Yu, Joseph Yu, Luciano Prevedello, Richard D White, Barbaros Erdal, Using Transfer Learning And Class Activation Maps Supporting Detection And Localization of Femoral Fractures of Anteroposterior Radiographs, IEEE International Symposium on Biomedical Imaging (ISBI) 2020. [paper]

  12. Joseph S Yu, Sarah M. Yu, Barbaros S. Erdal, Mutlu Demirer, Vikash Gupta, Matthew Bigelow, A. Salvador, T. Rink, S.S. Lenobel, Luciano M. Prevedello, Richard D. White, Detection and localisation of hip fractures on anteroposterior radiographs with artificial intelligence: proof of concept, Clinical Radiology 2019 [paper]

  13. Demirer, Mutlu, Sema Candemir, Matthew Bigelow, Sarah Yu, Vikash Gupta, Luciano M. Prevedello, Richard D. White, Joseph S. Yu, Rainer Grimmer, Michael Wels, Andreas Wimmer, Abdul H. Halabi, Alvin Ihsani, Thomas P. O’Donnell, and Barbaros S. Erdal, A user interface for optimizing radiologist engagement in image-data curation for artificial intelligence, Radiology: Artificial Intelligence, 2019. [paper]

  14. Vikash Gupta, Mutlu Demirer, Matthew Bigelow, Kevin J. Little, Sema Candemir, Luciano M. Prevedello, Richard D. White, Thomas P. O’Donnell, Michael Wels, Barbaros S. Erdal. Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning, Journal of Digital Imaging 2019 [paper]

  15. Vikash Gupta, Sophia I. Thomopoulos, Conor Corbin, Faisal M. Rashid, Paul M. Thompson, FiberNET 2.0: An automatic neural network based tool for clustering white matter fibers in the brain, ISBI 2018 [bioarxiv version]

  16. Mark S. Shiroishi, Vikash Gupta, Bavrina Bigjahan, Steven Y. Cen, Faisal Rashid, Darryl H. Hwang, Alexander Lerner, Orest B. Boyko, Chia-Shang Jason Liu, Meng Law, Paul M. Thompson, Neda Jahanshad, Brain cortical structural differences between non-central nervous system cancer patients treated with and without chemotherapy compared to non-cancer controls: a cross-sectional pilot MRI study using clinically-indicated scans, 13th International Conference on Medical Information Processing and Analysis (SIPAIM) 2017

  17. Mark Shiroshi, Vikash Gupta, Joshua Faskowitz, Paul Thompson, Neda Jahanshad and others, Towards accurate automated brain morphometry using contrast-enhanced T1-weighted scans a pilot study, Society for Neurosciences, 2017

  18. Vikash Gupta, Sophia I. Thomopoulos, Faisal M. Rashid, Paul M. Thompson, FiberNET: An ensembled deep learning framework for clustering white matter fibers, MICCAI 2017 [paper] [poster]

  19. Vikash Gupta, Gautam Prasad and Paul Thompson, Clustering white matter fibers using support vector machines: A volumetric conformal mapping approach, 12th International Conference on Medical Information Processing and Analysis (SIPAIM) 2016

  20. Vikash Gupta, Gautam Prasad and Paul Thompson, A volumetric conformal mapping approach for spectral clustering of white matter fibers, Spectral and Shape Analysis in Medical Imaging (SESAMI), MICCAI 2016

  21. Vikash Gupta, Gregoire Malandain, Nicholas Ayache, Xavier Pennec. A framework for creating population specific multimodal brain atlas using clinical T1 and diffusion tensor images, Workshop on Computational Diffusion MRI at MICCAI, 2015 [paper]

  22. Vikash Gupta, Nicholas Ayache, Xavier Pennec, Improving DTI resolution from a single clinical acquisition: a statistical approach using spatial prior. Medical Image Computing and Computer Assisted Intervention 2013 (MICCAI), volume 8151 of Lecture Notes in Computer Science - LNCS, Nagoya, Japon, pages 477-484, 2013. Springer

  23. Vikash Gupta, Hari Kr. Voruganti, Bhaskar Dasgupta, Domain Mapping for Volumetric Parameterization using Harmonic Functions. Computer Aided Design and Application, volume 11, pages 426-435, June, 2013

  24. Furui Wang, Milind Shastri, Christopher Jones, Vikash Gupta, Christian Osswald, Xuan Kang, Derek Kamper, Nilanjan Sarkar. Design and Control of an Actuated Thumb Exoskeleton for Hand Rehabilitation following Stroke. IEEE International Conference on Robotics and Automation, Shanghai, China., pages 3688-3693, May, 2011

  25. Hari K. Voruganti, Vikash Gupta, Bhaskar Dasgupta, Volumetric Parameterization of 3D non-convex shapes. Seventh International Conference on Curves and Surfaces 2010, Avignon, France.

  26. Hari K. Voruganti, Vikash Gupta, Bhaskar Dasgupta, Domain Mapping for Spherical Parametriza- tion using Harmonic Function Theory,IISc Centenary-International Conference on Advances in Mechanical Engineering (IC-ICAME), 2008, Bangalore, India.

  27. Vikash Gupta, Ashish Singla, Bhaskar Dasgupta, Anjali Kulkarni, Design and development of an 8-R snake-like manipulator, IISc Centenary-International Conference on Advances in Mechanical Engineering (IC-ICAME), 2008, Bangalore, India.

Abstracts:

  1. Conor Corbin, Vikash Gupta, Talia M. Nir, Julio E. Villalon, Faisal Rashid, Sophia I. Thomopoulos, Neda Jahanshad, Paul M. Thompson. White Matter Changes in Parkinson's Disease Mapped with a Novel Tract Mapping Algorithm, American Academy of Neurology 2018, Los Angeles, CA. (link)

  2. Mark Shiroishi, Vikash Gupta, Joshua Faskowitz, Bavrina Bigjahan, Steven Cen, Faisal Rashid, Darryl Hwang, Alexander Lerner, Orest Boyko, Chia-Shang Jason Liu, Meng Law, Paul Thompson, Neda Jahanshad (2018). The ENIGMA Cancer and Chemotherapy Working Group and Cancer-Related Cognitive Impairment, American Academy of Neurology 2018, Los Angeles, CA.

  3. Vikash Gupta, Sophia I. Thomopoulos, Conor K. Corbin, Faisal M. Rashid, Paul M. Thompson, FiberNet 2.0: A robust white matter classifier, Medical Imaging meets NIPS, med-NIPS 2017 [paper]

  4. Fabrizio Pizzagalli, Vikash Gupta, Joshua Faskowitz, Peter Kochunov, Paul Thompson, Neda Jahanashad, Local exploration of human brain folding, Organization for Human Brain Mapping, 2017 [paper]

  5. Faisal Rashid, Vikash Gupta, Paul Thompson, FiberNet: A deep learning framework for clustering white matter tracts in the brain, Organization for Human Brain Mapping, 2017

  6. Vikash Gupta, Marc Harrison, Gautam Prasad, Paul Thompson, Multimodal analysis of Alzheimers disease using diffusion and anatomic MRI, Organization for Human Brain Mapping, 2016


Invited Talks

    • Real World Applications and examples of AI in Medical Imaging, Guest Lecture at Applied Machine Learning Course @ Northwestern University,, 2019

    • Building Tools for AI Research in Medical Imaging, Featured Speaker, NVIDIA GTC 2018, Washington DC

    • Developing a coordinate system for the brain and classification of white matter fibers: A Deep Learning Approach, at Children’s Hospital Los Angeles, April 2017.

    • Diffusion tensor imaging of the brain: Towards quantitative clinical tools, at IBM Medical Sieve Team, San Jose, December 2016.

    • Statistical Analysis of diffusion tensor images for understanding HIV effects on white matter tracts, at Deutsches Zentrum fr Neurodegenerative Erkrankungen (German Center for Neurodegenerative diseases), October, 2014.

    • Towards Higher Resolution Analysis of Clinical Brain Diffusion Images. 1st International Symposium on Deep Brain Connectomics, 2012 Clermont-Ferrand, France.