Elfar Adalsteinsson

About

Elfar Adalsteinsson is the Eaton-Peabody Professor at MIT, with a research focus that includes AI for Healthcare and Life Sciences, Biological and Medical Devices and Systems, Graphics and Vision. His work leverages computational, theoretical, and experimental tools to develop groundbreaking sensors, energy transducers, and new physical substrates for computation, addressing shared challenges facing humanity. As a prominent figure in electrical engineering and artificial intelligence, he contributes to advancing the integration of AI technologies in healthcare and biological systems, fostering innovations that impact medical devices and systems.

Research topics

• Computer Science
• Artificial Intelligence
• Medicine
• Internal medicine
• Cardiology
• Computer vision
• Physics
• Optics
• Biology
• Algorithm

Selected publications

• Nonlinear dipole inversion (NDI) enables robust quantitative susceptibility mapping (QSM)

  NMR in Biomedicine · 2020 · 64 citations

  High-quality Quantitative Susceptibility Mapping (QSM) with Nonlinear Dipole Inversion (NDI) is developed with pre-determined regularization while matching the image quality of state-of-the-art reconstruction techniques and avoiding over-smoothing that these techniques often suffer from. NDI is flexible enough to allow for reconstruction from an arbitrary number of head orientations and outperforms COSMOS even when using as few as 1-direction data. This is made possible by a nonlinear forward-mo…

  DOI

• Placental MRI: Effect of maternal position and uterine contractions on placental BOLD MRI measurements

  Placenta · 2020 · 50 citations

  DOI

• Stochastic‐offset‐enhanced restricted slice excitation and 180° refocusing designs with spatially non‐linear <scp>ΔB₀</scp> shim array fields

  Magnetic Resonance in Medicine · 2023-09-05 · 6 citations

  articleOpen accessSenior author

  Abstract Purpose Developing a general framework with a novel stochastic offset strategy for the design of optimized RF pulses and time‐varying spatially non‐linear ΔB 0 shim array fields for restricted slice excitation and refocusing with refined magnetization profiles within the intervals of the fixed voxels. Methods Our framework uses the decomposition property of the Bloch equations to enable joint design of RF‐pulses and shim array fields for restricted slice excitation and refocusing with a…

  PublisherOA PDFDOI

• Local SAR management strategies to use two‐channel RF shimming for fetal MRI at 3 T

  Magnetic Resonance in Medicine · 2023-11-06 · 3 citations

  articleOpen access

  Abstract Purpose This study evaluates the imaging performance of two‐channel RF‐shimming for fetal MRI at 3 T using four different local specific absorption rate (SAR) management strategies. Methods Due to the ambiguity of safe local SAR levels for fetal MRI, local SAR limits for RF shimming were determined based on either each individual's own SAR levels in standard imaging mode (CP mode) or the maximum SAR level observed across seven pregnant body models in CP mode. Local SAR was constrained e…

  PublisherOA PDFDOI

• Fetal <scp>MRI</scp>: Radiofrequency Safety Assessment at 3 Tesla

  Journal of Magnetic Resonance Imaging · 2025-04-17 · 2 citations

  articleOpen access

  BACKGROUND: 3-T MRI can improve image quality of fetal imaging compared to 1.5-T MRI. However, concerns exist regarding increased local tissue heating at 3-T. PURPOSE: To assess fetal MRI radiofrequency (RF) safety at 3-T by comparing simulated tissue heating to 1.5-T (using constant RF exposure) and by simulating tissue heating at 3-T using RF exposures from clinical fetal examinations. STUDY TYPE: Retrospective. POPULATION: ). FIELD STRENGTH/SEQUENCE: 3-T, 1.5-T, HASTE, VIBE, TRUFISP, EPI, DTI…

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01AG018942

  NIH · $950k · 2005

• Novel MRI Assessment of Placental Structure and Function Throughout Pregnancy

  NIH · $3.6M · 2019–2025

• NIH Grant R01EB007942

  NIH · $1.4M · 2013

Frequent coauthors

• Lawrence L. Wald

  385 shared

• Adolf Pfefferbaum

  SRI International

  242 shared

• Edith V. Sullivan

  Stanford University

  188 shared

• Borjan Gagoski

  150 shared

• Kawin Setsompop

  129 shared

• Polina Golland

  Massachusetts Institute of Technology

  110 shared

• Berkin Bilgic̦

  103 shared

• Junshen Xu

  100 shared

Education

• Ph.D., Electrical Engineering and Computer Science

  Massachusetts Institute of Technology

  2005

• M.S., Electrical Engineering and Computer Science

  Massachusetts Institute of Technology

  2001

• B.S., Computer Science

  University of Iceland

  1998

Similar researchers at Massachusetts Institute of Technology

• Hari Balakrishnanh-104
• Regina Barzilayh-94
• Marc Baldoh-75