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D-Index & Metrics

Computer Science

D-Index
48
Citations
16524
World Ranking
6028
National Ranking
2711

Overview

Dzung L. Pham is affiliated with the Henry M. Jackson Foundation in the United States and has a significant body of research focused primarily in the field of Medicine, with an emphasis on Radiology, Nuclear Medicine and Imaging, Epidemiology, Computer Vision and Pattern Recognition, Neurology, and Pulmonary and Respiratory Medicine.

The scientist's work extensively covers topics including Traumatic Brain Injury Research, Advanced MRI Techniques and Applications, Trauma-related Neurovascular Disturbances, Automotive and Human Injury Biomechanics, Multiple Sclerosis Research Studies, and Advanced Image Processing and Neuroimaging Techniques.

Dzung L. Pham has published numerous papers in various respected venues. Some of the recent publications include:

  • Neurofilament light as a biomarker in traumatic brain injury, 2020, Neurology
  • Time course and diagnostic utility of NfL, tau, GFAP, and UCH-L1 in subacute and chronic TBI, 2020, Neurology
  • Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis, 2020, Scientific Reports
  • SMORE: A Self-Supervised Anti-Aliasing and Super-Resolution Algorithm for MRI Using Deep Learning, 2020, IEEE Transactions on Medical Imaging
  • Brain and blood biomarkers of tauopathy and neuronal injury in humans and rats with neurobehavioral syndromes following blast exposure, 2020, Molecular Psychiatry

Publications frequently appear in venues such as arXiv (Cornell University), Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition, Lecture Notes in Computer Science, Neurology, and bioRxiv (Cold Spring Harbor Laboratory).

Frequent collaborators include:

  • Jerry L. Prince
  • John A. Butman
  • Aaron Carass
  • Samuel W. Remedios
  • Yi-Yu Chou

The scientist's research demonstrates integration of advanced imaging methodologies, biomarker studies, and computational techniques to investigate neurological injury and disease. Their contributions encompass both clinical and technical aspects of medical imaging, particularly focusing on traumatic brain injury and related neurobiological processes.

Best Publications

  • Current methods in medical image segmentation.

    Dzung L. Pham;Chenyang Xu;Jerry L. Prince

  • Longitudinal Magnetic Resonance Imaging Studies of Older Adults: A Shrinking Brain

    Susan M. Resnick;Dzung L. Pham;Michael A. Kraut;Alan B. Zonderman

  • Adaptive fuzzy segmentation of magnetic resonance images

    D.L. Pham;J.L. Prince

  • An adaptive fuzzy C -means algorithm for image segmentation in the presence of intensity inhomogeneities

    Dzung L. Pham;Jerry L. Prince

  • A Survey of Current Methods in Medical Image Segmentation

    Dzung L. Pham;Chenyang Xu;Jerry L. Prince

  • Image Segmentation Using Deformable Models

    Dzung L. Pham;Chenyang Xu;Jerry L. Prince

  • Spatial Models for Fuzzy Clustering

    Dzung L. Pham

  • Statistical normalization techniques for magnetic resonance imaging

    Russell T. Shinohara;Elizabeth M. Sweeney;Jeff Goldsmith;Navid Shiee

  • A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions.

    Navid Shiee;Pierre Louis Bazin;Arzu Ozturk;Daniel S. Reich

  • Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.

    Aaron Carass;Snehashis Roy;Amod Jog;Jennifer L. Cuzzocreo

  • An image-processing system for qualitative and quantitative volumetric analysis of brain images.

    Alberto F. Goldszal;Christos Davatzikos;Dzung L. Pham;Dzung L. Pham;Michelle X.H. Yan

  • Reconstruction of the human cerebral cortex from magnetic resonance images

    C. Xu;D.L. Pham;M.E. Rettmann;D.N. Yu

  • CRUISE: cortical reconstruction using implicit surface evolution.

    Xiao Han;Dzung L. Pham;Duygu Tosun;Maryam E. Rettmann

  • DeepHarmony: A deep learning approach to contrast harmonization across scanner changes.

    Blake E. Dewey;Blake E. Dewey;Can Zhao;Jacob C. Reinhold;Aaron Carass

  • Random forest regression for magnetic resonance image synthesis.

    Amod Jog;Aaron Carass;Snehashis Roy;Dzung L. Pham

  • Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis

    Aaron Carass;Snehashis Roy;Adrian Gherman;Jacob C. Reinhold

  • SMORE: A Self-Supervised Anti-Aliasing and Super-Resolution Algorithm for MRI Using Deep Learning

    Can Zhao;Blake E. Dewey;Dzung L. Pham;Peter A. Calabresi

  • Fuzzy clustering with spatial constraints

    D.L. Pham

  • Topology-Preserving Tissue Classification of Magnetic Resonance Brain Images

    P.-L. Bazin;D.L. Pham

  • The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

    Blake C. Lucas;Blake C. Lucas;John A. Bogovic;Aaron Carass;Pierre Louis Bazin

  • Volumetric Neuroimage Analysis Extensions for the MIPAV Software Package

    Pierre Louis Bazin;Jennifer L. Cuzzocreo;Michael A. Yassa;William Gandler

  • Homeomorphic brain image segmentation with topological and statistical atlases

    Pierre Louis Bazin;Dzung L. Pham

Frequent Co-Authors

Jerry L. Prince
Jerry L. Prince Johns Hopkins University
Pierre-Louis Bazin
Pierre-Louis Bazin University of Amsterdam
Aaron Carass
Aaron Carass Johns Hopkins University
Chenyang Xu
Chenyang Xu Princeton University
Russell T. Shinohara
Russell T. Shinohara University of Pennsylvania
Susan M. Resnick
Susan M. Resnick National Institutes of Health
Philip V. Bayly
Philip V. Bayly Washington University in St. Louis
Bennett A. Landman
Bennett A. Landman Vanderbilt University
Kaj Blennow
Kaj Blennow University of Gothenburg
Christos Davatzikos
Christos Davatzikos University of Pennsylvania

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