World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
136
Citations
173390
World Ranking
220
National Ranking
142

Medicine

D-Index
136
Citations
173661
World Ranking
1925
National Ranking
1093

Overview

Bruce Fischl is affiliated with Harvard University in the United States. Their research primarily spans the field of Medicine, with a focus on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering, Cognitive Neuroscience, and Biophysics. The main topics of their work include:

  • Advanced Neuroimaging Techniques and Applications
  • Advanced MRI Techniques and Applications
  • Functional Brain Connectivity Studies
  • Medical Image Segmentation Techniques
  • Optical Coherence Tomography Applications
  • Medical Imaging Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging

Bruce Fischl has contributed to various frequent publication venues, notably:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • NeuroImage
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Alzheimer's & Dementia

Some of the recent research papers authored or co-authored by Bruce Fischl include:

  • FastSurfer - A fast and accurate deep learning based neuroimaging pipeline (2020, NeuroImage)
  • SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining (2023, Medical Image Analysis)
  • Infant FreeSurfer: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0-2 years (2020, NeuroImage)
  • SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry (2023, Science Advances)
  • Test-retest reliability of FreeSurfer automated hippocampal subfield segmentation within and across scanners (2020, NeuroImage)

Bruce Fischl has collaborated extensively with several researchers, including the following frequent co-authors:

  • Adrian V. Dalca
  • Juan Eugenio Iglesias
  • Brian L. Edlow
  • Jean C. Augustinack
  • Yaël Balbastre

Best Publications

  • An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

    Rahul S. Desikan;Florent Ségonne;Bruce Fischl;Bruce Fischl;Brian T. Quinn

  • Cortical surface-based analysis. I. Segmentation and surface reconstruction

    Anders M. Dale;Bruce Fischl;Martin I. Sereno

  • The organization of the human cerebral cortex estimated by intrinsic functional connectivity

    B. T. Thomas Yeo;Fenna M. Krienen;Jorge Sepulcre;Jorge Sepulcre;Mert R. Sabuncu;Mert R. Sabuncu

  • Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

    Bruce Fischl;David H. Salat;Evelina Busa;Marilyn Albert

  • FreeSurfer

    Unknown

  • Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System

    Bruce Fischl;Martin I. Sereno;Anders M. Dale

  • Measuring the thickness of the human cerebral cortex from magnetic resonance images

    Bruce Fischl;Anders M. Dale

  • The minimal preprocessing pipelines for the Human Connectome Project.

    Matthew F. Glasser;Stamatios N. Sotiropoulos;J. Anthony Wilson;Timothy S. Coalson

  • Automatically Parcellating the Human Cerebral Cortex

    Bruce Fischl;André van der Kouwe;Christophe Destrieux;Eric Halgren

  • Accurate and robust brain image alignment using boundary-based registration.

    Douglas N. Greve;Bruce Fischl

  • High-resolution intersubject averaging and a coordinate system for the cortical surface.

    Bruce Fischl;Martin I. Sereno;Roger B.H. Tootell;Anders M. Dale

  • Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature

    Christophe Destrieux;Bruce Fischl;Bruce Fischl;Anders M. Dale;Eric Halgren

  • Meditation experience is associated with increased cortical thickness

    Sara W. Lazar;Catherine E. Kerr;Rachel H. Wasserman;Jeremy R. Gray

  • A Hybrid Approach to the Skull Stripping Problem in MRI

    Florent Ségonne;Anders M. Dale;Evelina Busa;Maureen Glessner

  • Within-Subject Template Estimation for Unbiased Longitudinal Image Analysis

    Martin Reuter;Nicholas J. Schmansky;H. Diana Rosas;Bruce Fischl;Bruce Fischl

  • Sequence-independent segmentation of magnetic resonance images.

    Bruce Fischl;Bruce Fischl;David H. Salat;André J.W. van der Kouwe;Nikos Makris

  • Thinning of the cerebral cortex in aging

    David H. Salat;Randy L. Buckner;Randy L. Buckner;Abraham Z. Snyder;Douglas N. Greve

  • Dynamic Statistical Parametric Mapping: Combining fMRI and MEG for High-Resolution Imaging of Cortical Activity

    Anders M. Dale;Arthur K. Liu;Bruce R. Fischl;Randy L. Buckner

  • Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex

    B. Fischl;A. Liu;A.M. Dale

  • Mechanisms of migraine aura revealed by functional MRI in human visual cortex

    Nouchine Hadjikhani;Margarita Sanchez del Rio;Ona Wu;Denis Schwartz

  • Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer.

    Xiao Han;Jorge Jovicich;David Salat;Andre van der Kouwe

Frequent Co-Authors

Anders M. Dale
Anders M. Dale J. Craig Venter Institute
David H. Salat
David H. Salat Harvard University
Douglas N. Greve
Douglas N. Greve Harvard University
Randy L. Buckner
Randy L. Buckner Harvard University
André J. W. van der Kouwe
André J. W. van der Kouwe Harvard University
Jean C. Augustinack
Jean C. Augustinack Harvard University
Martin Reuter
Martin Reuter University of Bonn
Lawrence L. Wald
Lawrence L. Wald Harvard University
William S. Kremen
William S. Kremen University of California, San Diego

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