Workshop Program

Octobor 17 (Sunday) Afternoon, 2021, on Zoom. Accepted papers are here [ LCI Papers ] .

All planned time are based on Eastern Daylight Time (EDT), UTC - 04:00

• • • 17:00: Opening and Welcome

    • 17:10 - 17:40: Invited Talk by Rebecca Willett . Title: Deep Equilibrium Architectures for Inverse Problems in Imaging

• • • 17:40 – 18:10 : Invited Talk by Jeffrey A. Fessler. Title: Joint Optimization of Learning-Based Image Reconstruction and Sampling for MRI

    • 18:10 – 18:25 : Q & A + Panel Discussion 1

• • [ Video Recordings ] - First Half Invited Talks

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• • • 18:25 – 19:10 : Parallel Contributed Talk 1 (2 breakout rooms)

    • Session A (Breakout Room 1):

      • How to cheat with metrics in single-image HDR reconstruction Gabriel Eilertsen (Linköping University)*; Saghi Hajisharif (Linkoping University); Param Hanji (University of Cambridge); Apostolia Tsirikoglou (Linköping University ); Rafal Mantiuk (Univ. Cambridge); Jonas Unger (Linköpings universitet)

      • Joint Reconstruction and Calibration Using Regularization by Denoising with Application to Computed Tomography Mingyang Xie (Washington University in St. Louis); Jiaming Liu (Washington University in St. Louis)*; Yu Sun (Washington University in St. Louis); Weijie Gan (Washington University in St. Louis); Brendt Wohlberg (Los Alamos National Laboratory); Ulugbek S. Kamilov (Washington University in St. Louis)

      • What Does Your Computational Imaging Algorithm Not Know?: A Plug-and-Play Model Quantifying Model Uncertainty Canberk Ekmekci (University of Rochester)*; Mujdat Cetin (University of Rochester)

      • [ Video Recording ] - Session A

• Session B (Breakout Room 2):

  • Photon-Limited Object Detection using Non-local Feature Matching and Knowledge Distillation Chengxi Li (Purdue University)*; Xiangyu Qu (Purdue University); Abhiram Gnanasambandam (Purdue University); Omar A Elgendy (Gigajot Technology, Inc); Jiaju Ma (Gigajot Technology); Stanley Chan (Purdue University, USA)

  • SS-JIRCS: Self-Supervised Joint Image Reconstruction and Coil Sensitivity Calibration in Parallel MRI without Ground Truth Weijie Gan (Washington University in St. Louis)*; Yuyang Hu (Washington University in St. Louis); Cihat Eldeniz (Washington University in St. Louis); Jiaming Liu (Washington University in St. Louis); Yasheng Chen (Washington University in St. Louis); Hongyu An (Washington University, St. Louis); Ulugbek S. Kamilov (Washington University in St. Louis)

  • Thermal Image Processing via Physics-Inspired Deep Networks Vishwanath Saragadam (Rice University)*; Akshat Dave (Rice University); Ashok Veeraraghavan (Rice University); Richard Baraniuk (Rice University)

  • [ Video Recording ] - Session B

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• • • 19:10-19:30: 20-min Break

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• • • 19:30 - 20:00: Invited Talk by Zhizhen Zhao. Title: An Adversarial Learning Approach for Unknown View Tomography

    • 20:00 - 20:30: Invited Talk by Laura Waller. Title: Computational 3D fluorescence microscopy

    • 20:30 – 20:45 : Q & A + Panel Discussion 2

• • [ Video Recordings ] - Second Half Invited Talks

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• • • 20:45 – 21:35 : Parallel Contributed Talk 2 (2 breakout rooms)

    • Session C (Breakout Room 1):

      • CryoPoseNet: End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data Youssef Nashed (SLAC National Accelerator Laboratory); Frédéric Poitevin (Stanford)*; Harshit Gupta (SLAC National Accelerator Laboratory); Geoffrey Woollard (University of Toronto); Michael Kagan (SLAC / Stanford); Chun Hong Yoon (SLAC national accelerator laboratory); Daniel Ratner (Stanford University )

      • Fast Unsupervised MRI Reconstruction Without Fully-Sampled Ground Truth Data Using Generative Adversarial Networks Elizabeth Cole (Stanford University)*; Frank Ong (Stanford University); Shreyas Vasanawala (Stanford University); John Pauly (Stanford University)

      • Inference of Black Hole Fluid-Dynamics from Sparse Interferometric Measurements Aviad Levis (Caltech)*; Daeyoung Lee (University of Illinois at Urbana-Champaign); Joel Tropp (Caltech); Charles Gammie ( University of Illinois at Urbana-Champaign); Katherine Bouman (Caltech)

      • Deep Radio Interferometric Imaging with POLISH Liam Connor (California Institute of Technology)*

• [ Video Recording ] - Session C

• Session D (Breakout Room 2):

  • K-space refinement in deep learning MR reconstruction via regularizing scan specific SPIRiT-based self consistency Kanghyun Ryu (Stanford University)*; Cagan Alkan (Stanford University); Chanyeol Choi (Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT)); Ikbeom Jang (Massachusetts General Hospital); Shreyas Vasanawala (Stanford University)

  • Compressed Classification from Learned Measurements Robiulhossain Mdrafi (Mississippi State University)*; Ali C Gurbuz (Mississippi State University)

  • Adaptive Local Neighborhood-based Networks for MR Image Reconstruction from Undersampled Data Shijun Liang (michigan state university); Ashwin Sreevatsa (University of Michigan); Anish Lahiri (University of Michigan); Saiprasad Ravishankar (Michigan State University)*

• [ Video Recording ] - Session D

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21:45: Closing of the LCI Workshop