I am a Ph.D candidate in Computer Science and Engineering at the Washington University in St. Louis. Currently, I am a visiting scholar at the University of Illinois at Urbana-Champaign in the Computational Imaging Science Laboratory supervised by Prof. Mark A. Anastasio. My research focuses on investigating deep learning (DL) methods for image reconstruction guided by theoretical principles of image formation, with applications in medical imaging. Before joining my Ph.D program, I completed my B.E. degree in Electronics and Telecommunication Engineering from Jadavpur University in 2016.

News

• Paper on finding multiple data-consistent solutions of ill-posed tomographic imaging problems with a style-based GAN available on arXiv 2022 (preprint)
• Paper on learning stochastic object models with advanced AmbientGANs published in SPIE Journal of Medical Imaging 2022 (paper)
• Research on hallucinations in medical imaging highlighted in IEEE Spectrum: Medical Image AIs Need a Good “Hallucination Map”
• Featured in research news by the Beckman Institute: Investigating medical imaging hallucinations
• Paper defining hallucinations in ill-posed imaging inverse problems published in IEEE Transactions on Medical Imaging 2021 under the Second Special Issue on Machine Learning for Image Reconstruction (paper)
• Paper on improved generative-model constrained image reconstruction with invertible neural networks published in IEEE Transactions on Computational Imaging 2021 (paper)

Research

• Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems
  arXiv (2022)
  Sayantan Bhadra, Umberto Villa, Mark A. Anastasio
  [preprint] [code]

• Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks
  Journal of Medical Imaging (2022)
  Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
  [paper] [project]

• On hallucinations in tomographic image reconstruction
  IEEE Transactions on Medical Imaging (2021)
  Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio
  [paper] [code] [project]

• Compressible latent-space invertible networks for generative model-constrained image reconstruction
  IEEE Transactions on Computational Imaging (2021)
  Varun A. Kelkar, Sayantan Bhadra, Mark A. Anastasio
  [paper] [project]

• Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks
  SPIE Medical Imaging (2020)
  Sayantan Bhadra, Weimin Zhou, Mark A. Anastasio
  [proceeding] [project]

• Full-view 3D imaging system for functional and anatomical screening of the breast
  SPIE Photonics West BiOS (2018)
  (with TomoWave Laboratories and MD Anderson Cancer Center)
  A. Oraevsky, R. Su, H. Nguyen, J. Moore, Y. Lou, S. Bhadra, L. Forte, M.A. Anastasio, W. Yang
  [proceeding]

• Real-time low-field cardiac MRI using an integrated MRI-guided radiotherapy system
  ISMRM (2018)
  (with WashU Radiation Oncology and ViewRay)
  H.M. Gach, S. Bhadra, A.N. Curcuru, R. Nana, C.G. Robinson, P.S. Cuculich, S. Mutic, M.A. Anastasio
  [proceeding]