Sayantan Bhadra

According to our database, Sayantan Bhadra authored at least 13 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Subcutaneous edema segmentation on abdominal CT using multi-class labels and iterative annotation.

Sayantan Bhadra, Jianfei Liu, Ronald M. Summers

Int. J. Comput. Assist. Radiol. Surg., January, 2025

A unified approach to medical image segmentation by leveraging mixed supervision and self and transfer learning (MIST).

Jianfei Liu, Sayantan Bhadra, Omid Shafaat, Pritam Mukherjee, Christopher Parnell, Ronald M. Summers

Comput. Medical Imaging Graph., 2025

2024

Improved subcutaneous edema segmentation on abdominal CT using a generated adipose tissue density prior.

Jianfei Liu, Omid Shafaat, Sayantan Bhadra, Christopher Parnell, Ayden Harris, Ronald M. Summers

Int. J. Comput. Assist. Radiol. Surg., March, 2024

2022

Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems.

Sayantan Bhadra, Umberto Villa, Mark A. Anastasio

CoRR, 2022

2021

On Hallucinations in Tomographic Image Reconstruction.

Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio

IEEE Trans. Medical Imaging, 2021

Compressible Latent-Space Invertible Networks for Generative Model-Constrained Image Reconstruction.

Varun A. Kelkar, Sayantan Bhadra, Mark A. Anastasio

IEEE Trans. Computational Imaging, 2021

Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio

CoRR, 2021

Advancing the AmbientGAN for learning stochastic object models.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio

Proceedings of the Medical Imaging 2021: Image Perception, 2021

Assessing regularization in tomographic imaging via hallucinations in the null space.

Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, Mark A. Anastasio

Proceedings of the Medical Imaging 2021: Image Perception, 2021

2020

Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio

CoRR, 2020

Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks.

Sayantan Bhadra, Weimin Zhou, Mark A. Anastasio

CoRR, 2020

Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio

Proceedings of the Medical Imaging 2020: Image Perception, 2020

2019

Learning stochastic object model from noisy imaging measurements using AmbientGANs.

Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Mark A. Anastasio

Proceedings of the Medical Imaging 2019: Image Perception, 2019