Berkin Bilgic - BRAIN Lab

About me:

I am an Associate Professor in Radiology at Massachusetts General Hospital and Harvard Medical School. I head the BRAIN (Bilgic Reconstruction Acquisition for Imaging Neuroscience) lab at the Martinos Center for Biomedical Imaging.

I am interested in MRI data acquisition and reconstruction, in particular,

  • Parallel imaging and compressed sensing,
  • Fast clinical imaging,
  • Self-supervised machine learning,
  • Quantitative parameter mapping,
  • Diffusion imaging, and
  • Open-source pulse sequence development.

Biography:
  • Associate Professor in Radiology, MGH/Harvard, Nov 2023 -
  • Affiliated Faculty, Health Sciences & Technology, Harvard-MIT, Jun 2018 -
  • Assistant Professor in Radiology, MGH/Harvard, Jun 2019 - Nov 2023
  • Instructor in Radiology, MGH/Harvard, May 2016 - Jun 2019
  • Research Fellow in Radiology, MGH/Harvard, Feb 2013 - May 2016
  • PhD in EECS, MIT, Feb 2010 - Feb 2013
  • SM in EECS, MIT, Sep 2008 - Feb 2010
  • BS in EE, Bogazici University, Sep 2004 - Jun 2008
  • BS in Physics, Bogazici University, Sep 2004 - Jun 2008

Research fellowships in novel acquisition strategies and hardware development for diffusion MRI is open in our groups, effective May 2024. Flyer


News from the ISMRM'24 conference:
News: Abstracts and software from the ISMRM'23 conference:
  • H Yu et al: SubZero: Subspace Zero-Shot MRI Reconstruction, #0829, power pitch Python code on GitHub
  • A Heydari et al: Joint MR T1 and T2* Parameter Mapping with Scan Specific Unsupervised Networks, #1617, digital poster Python code on GitHub
  • IA Vurankaya et al: Self-Supervised Deep Learning Reconstruction for Highly Accelerated Diffusion Imaging, #0831, power pitch Python code on GitHub
  • Y Arefeen et al: Improved T1 and T2 mapping in 3D-QALAS using temporal subspaces and Cramer-Rao-bound flip angle optimization enabled by auto-differentiation, #0671, oral Python code on GitHub
  • X Wang et al: Model-based phase-difference reconstruction for accelerated phase-based T2 mapping, #4960, digital poster BART code on GitHub
  • X Wang et al: An Open-Source Self-navigated Multi-Echo Gradient Echo Acquisition for R2* and QSM mapping using Pulseq and Model-Based Reconstruction, #0420, combined educational & scientific session Matlab code on GitHub
  • Y Jun et al: Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Multiparametric Quantitative MRI Using QALAS, #1105, power pitch Python code on GitHub
  • Y Jun et al: SSL-QALAS: Self-Supervised Learning for Multiparametric Quantitative MRI Using QALAS, #2155, digital poster Python code on GitHub
  • TH Kim et al: Multi-echo MRI Reconstruction with Iteratively Refined Zero-shot Spatio-Temporal Deep Generative Prior, #0828, power pitch Python code on GitHub
  • J Cho et al: VUDU-SAGE: Efficient T2 and T2* Mapping using Joint Reconstruction for Motion-Robust, Distortion-Free, Multi-Shot, Multi-Echo EPI, #2202, digital poster Matlab code on GitHub
  • G Varela-Mattatall et al: Rapid Mesoscale MP2RAGE Imaging at Ultra High Field with Controlled Aliasing, #0539, oral Matlab code on GitLab

Abstracts and software from the Data Sampling and Image Reconstruction workshop, Sedona'23:
  • Y Jun et al: Deep Subspace Reconstruction with Zero-Shot Learning for Multiparametric Quantitative MRI, oral PDF
  • TH Kim et al: Zero-shot Prior Learning of Spatio-temporal Multi-echo/contrast MRI Reconstruction with Iterative Refinement PDF Code
  • G Varela Mattatall et al: Parallel CS-Wave PDF
  • X Wang et al: Model-Based Phase-Difference Reconstruction for Accelerated Phase-Based T2 Mapping PDF
  • J Cho et al: VUDU-SAGE: Efficient T2 and T2* Mapping using Joint Reconstruction for Motion-Robust, Distortion-Free, Multi-Shot, Multi-Echo EPI PDF Code
  • Y Arefeen et al: Improved T1 and T2 mapping in 3D-QALAS using temporal subspaces and flip angle optimization enabled by auto-differentiation PDF
  • X Wang et al: Open-Source Self-navigated Multi-Echo GRE Acquisition for R2* and QSM mapping using Pulseq and Model-Based Reconstruction PDF Code
  • X Wang et al: Model-Based Reconstruction for Joint Estimation of T1, T2 and B0 Inhomogeneity Maps Using Single-Shot Inversion-Recovery Multi-Echo Radial FLASH PDF
Software from the ISMRM'22 conference:
  • Y Arefeen et al: Learning compact latent representations of signal evolution for improved shuffling reconstruction, #0247 Latent shuffling code on Github
  • J Cho et al: Variable Flip, Blip-Up and -Down Undersampling (VUDU) Enables Motion-Robust, Distortion-Free Multi-Shot EPI, #0757 VUDU code on Github
  • J Cho et al: Rapid Quantitative Imaging Using Wave-Encoded Model-Based Deep Learning for Joint Reconstruction, #0435 wave-MoDL code on Github
  • MY Avci et al: Quantifying the uncertainty of neural networks using Monte Carlo dropout for safer and more accurate deep learning based quantitative MRI, #4978 Monte Carlo dropout code on Github
  • A Lin et al: Bayesian sensitivity encoding enables parameter-free, highly accelerated joint multi-contrast reconstruction, #3444 joint Bayesian sensitivity encoding code on Github
  • TH Kim et al: Accelerated MR Parameter Mapping with Scan-specific Unsupervised Networks, #4402 MAPLE code on Github
  • G Varela-Mattatall et al: Rapid CS-Wave MPRAGE acquisition with automated parameter selection, #1604 CS-Wave code on Github
Educational talk from ISMRM'22:
  • Value of multi-contrast techniques (neuro), Wednesday session on Added Value of Sophisticated Multicontrast Techniques recording

  • We continuously seek new research interns at undergraduate, graduate and postdoctoral levels. Please email Berkin for details.


    We gratefully acknowledge our completed or current funding:

    NVIDIA GPU Grant to support machine learning research
    Chinese Scholarship Council (CSC) fellowship: (to Zijing Zhang)
    Office of China Postdoc Council (OCPC) fellowship: (to Zhifeng Chen)
    MIT International Science & Technology Initiatives (MISTI) Grant
    MGH ECOR Formulaic Bridge Funding
    NIH R01 EB028797
    NIH R03 EB031175
    ISMRM Research Exchange Grant Program (to Gabriel Varela-Mattatall)
    NIH R01 EB032378
    NIH T32 EB001680 Neuroimaging training program fellowship: (to Yamin Arefeen)
    JSPS Overseas Research Fellowship: (to Shohei Fujita)
    NIH UG3 EB034875
    Zhejiang University Education Foundation: (to Yuting Cheng)
    Swiss National Science Foundation mobility grant: (to Quentin Uhl)
    NIH R01 EB034757

    Contact Information:

    Berkin

    Building 75
    13th Street
    Charlestown, MA 02129

    E-mail: bbilgic AT mgh.harvard.edu

    Tel: 617-866-8740