Department of Electrical Engineering and Computer Sciences (EECS)
I am a postdoc in the Department of Electrical Engineering and Computer Sciences (EECS) at UC Berkeley. I have the pleasure of being co-advised by Prof. Michael (Miki) Lustig (UC Berkeley) and Prof. Shreyas Vasanawala (Stanford). I work with their collaborative groups on developing MRI reconstruction methods for rapid dynamic MRI scans. My research leverages Machine Learning, physics-based modeling and computational imaging.
In 2015-2019 I was a PhD student at the Technion - Israel Institute of Technology. I spent joyful years in the lab of my PhD advisor Prof. Haim Azhari, where I developed sparsity-based methods for MR image reconstruction.
I am an advocate of reproducible research - all my papers have open-source code packages (see links below). I'm also the 2021-2023 Trainee Representative of the ISMRM Reproducible Research Study Group (RRSG) Governing Committee.
New! This work was highlighted in a PNAS commentary article.
This work received a Magna cum Laude Award at the ISMRM 2021 Annual Meeting. Here is the git repo.
BladeNet: Dynamic Abdominal MRI using PROPELLER and Deep Learning
ISMRM 2022 abstract: #0684
New! My abstract was accepted for an oral presentation at the ISMRM conference in London: Wed, May 11, at 15:20, in room S11 (Breakout B) - New/Deep Machine Learning Techniques session.
This work introduces a new method for rapid dynamic (temporal) abdominal MRI with high spatio-temporal resolution and built-in motion correction.
CORE-Deblur is a Parallel Imaging Compressed Sensing (PI-CS) method.
Our paper introduced the concept of MR image reconstruction by deblurring using Compressed Sensing (CS), and showed that CORE-Deblur can expedite CS computations: the number of required iterations is reduced by a factor of 10.
My activities in the upcoming ISMRM 2022 conference in London:
I will give an oral presentation titled: "BladeNet: Rapid PROPELLER Acquisition and Reconstruction for High spatio-temporal Resolution Abdominal MRI". Abstract #0684. Session: New Deep/Machine Learning Techniques. Thursday, May 12, 14:45-16:45.
I organized the MR-Pub II competition for open code - submissions are welcome! Deadline: May 2.
I organized the Reproducible Research Study Group (RRSG) Member Initiated Symposium (MIS), titled: "The Reproducibility Crisis - Perspectives from Funders, Researchers and Journal Editors".
I will moderate the following sessions:
Software tutorials for the whole community: introduction & panel discussion. May 9, 8:00-9:00. Details here.
Software tutorials for the whole community: software tools I & II. May 10, 8:00-9:00. Details here.
(RRSG) Member Initiated Symposium (MIS), titled: "The Reproducibility Crisis - Perspectives from Funders, Researchers and Journal Editors". May 10, 16:45-18:15.
Deep Learning image reconstruction, May 11, 2022. Details here.
April 2022: My work was highlighted in a PNAS commentary article.
April 2022: I am a co-guest editor of the Bioengineering journal (IF ~4.7) special issue: "AI in MRI: Frontiers and Applications". Submissions are welcome! Deadline: May 20, 2022.
March 2022: I gave a talk in the BAIR Visual Computing Workshop. Title: "Data Crimes: The Risk in Naïve Training of Medical AI Algorithms".
March 2022: I am co-organizing the 2nd MR Pub competition for open science, together with the ISMRM RRSG committee. Details soon!
Feb 2022: Three abstracts (1 first-authored and 2 co-authored) were accepted to ISMRM'22:
Shimron et al., "BladeNet: Rapid PROPELLER Acquisition and Reconstruction for High spatio-temporal Resolution Abdominal MRI".
Waddington, Shimron, Hindley, Koonjoo, Rosen, "Accelerating Ultra-Low Field MRI with Compressed Sensing". This work is part of my collaboration with the group of Prof. Matthew Rosen (MGH, Harvard).
Wang et al., "Rigorous Uncertainty Estimation for MRI Reconstruction" - collaboration between our lab and Jitendra Malik's group.
December 2021: I gave a talk about Data Crimes at the MRI Together conference (Dec 15, 2021).
October 2021: I was named as an Emerging Investigator at the Imaging Elevated: Utah Symposium for Emerging Investigators.
Prof. Jon Tamir, Electrical and Computer Engineering Department (ECE), UT Austin.
Prof. Matthew Rosen, Martinos Center for Biomedical Imaging, Harvard.
Dr. David Waddington - The University of Sydney
Prof. Martin Uecker, Department of Diagnostic and Interventional Radiology, University Medical Center Göttingen.
Prof. William Grissom, Biomedical Engineering Department, Vanderbilt University, TN.
Prof. Andrew Webb, Leiden University Medical Center (LUMC), Leiden, The Netherlands.
Ke Wang, PhD candidate at UC Berkeley's Electrical Engineering and Computer Sciences (EECS) Department
Jerry (Boyuan) Ma
(c) website copyright Efrat Barak Shimron, 2022