World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
9573
World Ranking
5895
National Ranking
2665

Overview

Marc Niethammer is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research is primarily situated at the intersection of computer science and medicine, with notable contributions encompassing fields such as computer vision, medical imaging, and artificial intelligence.

The scientist has a significant publication record, with 135 works categorized under computer science and 104 within medicine. Their subfields of study include:

  • Computer Vision and Pattern Recognition
  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Biomedical Engineering
  • Rheumatology

Topics commonly addressed in their research involve:

  • Medical Image Segmentation Techniques
  • Radiomics and Machine Learning in Medical Imaging
  • Medical Imaging and Analysis
  • AI in cancer detection
  • Medical Imaging Techniques and Applications
  • Advanced Neuroimaging Techniques and Applications
  • Advanced Neural Network Applications

Marc Niethammer's publication venues frequently include:

  • arXiv (Cornell University)
  • UNC Libraries
  • Lecture Notes in Computer Science
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Medical Image Analysis

Some recent papers authored in collaboration with others showcase their work across various aspects of image analysis and deep learning:

  • "Robust and Generalizable Visual Representation Learning via Random Convolutions," 2020, arXiv (Cornell University)
  • "Quicksilver: Fast predictive image registration - A deep learning approach," 2020, UNC Libraries
  • "Differential Role for Hippocampal Subfields in Alzheimer's Disease Progression Revealed with Deep Learning," 2021, Cerebral Cortex
  • "Deep-learning-based image registration and automatic segmentation of organs-at-risk in cone-beam CT scans from high-dose radiation treatment of pancreatic cancer," 2021, Medical Physics
  • "Accurate Point Cloud Registration with Robust Optimal Transport," 2021, arXiv (Cornell University)

Marc Niethammer collaborates frequently with coauthors including Roland Kwitt, Hastings Greer, Martin Styner, Raúl San Jośe Estépar, and Stephen Aylward. The number of joint publications with these collaborators ranges from 13 to 21, reflecting ongoing collaborative research efforts.

Best Publications

  • A method for normalizing histology slides for quantitative analysis

    Marc Macenko;Marc Niethammer;J. S. Marron;David Borland

  • Quicksilver: Fast predictive image registration – A deep learning approach

    Xiao Yang;Roland Kwitt;Martin Styner;Marc Niethammer

  • Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging

    Emilie Gerardin;Gaël Chételat;Marie Chupin;Rémi Cuingnet

  • Time-frequency representations of Lamb waves.

    Marc Niethammer;Laurence J. Jacobs;Jianmin Qu;Jacek Jarzynski

  • Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

    Heather D. Couture;Lindsay A. Williams;Joseph Geradts;Sarah J. Nyante

  • Laplace-Beltrami eigenvalues and topological features of eigenfunctions for statistical shape analysis

    Martin Reuter;Franz-Erich Wolter;Martha Shenton;Marc Niethammer

  • Fast Global Labeling for Real-Time Stereo Using Multiple Plane Sweeps.

    Christopher Zach;David Gallup;Jan Michael Frahm;Marc Niethammer

  • The power of correlative microscopy: multi-modal, multi-scale, multi-dimensional.

    Jeffrey Caplan;Marc Niethammer;Russell M Taylor;Kirk J Czymmek;Kirk J Czymmek

  • Restoration of DWI Data Using a Rician LMMSE Estimator

    S. Aja-Fernandez;M. Niethammer;M. Kubicki;M.E. Shenton

  • Geodesic regression for image time-series

    Marc Niethammer;Yang Huang;François-Xavier Vialard

  • Deep Learning with Topological Signatures

    Christoph D. Hofer;Roland Kwitt;Marc Niethammer;Andreas Uhl

  • Scene Parsing with Object Instances and Occlusion Ordering

    Joseph Tighe;Marc Niethammer;Svetlana Lazebnik

  • DeepAtlas: Joint Semi-supervised Learning of Image Registration and Segmentation

    Zhenlin Xu;Marc Niethammer

  • Fast Predictive Image Registration

    Xiao Yang;Roland Kwitt;Marc Niethammer

  • AGA: Attribute-Guided Augmentation

    Mandar Dixit;Roland Kwitt;Marc Niethammer;Nuno Vasconcelos

  • Time-frequency representation of Lamb waves using the reassigned spectrogram

    Marc Niethammer;Laurence J. Jacobs;Jianmin Qu;Jacek Jarzynski

  • Networks for Joint Affine and Non-Parametric Image Registration

    Zhengyang Shen;Xu Han;Zhenlin Xu;Marc Niethammer

  • Automatic atlas-based three-label cartilage segmentation from MR knee images

    Liang Shan;Christopher Zach;Cecil Charles;Marc Niethammer

  • Robust and Generalizable Visual Representation Learning via Random Convolutions

    Zhenlin Xu;Deyi Liu;Junlin Yang;Colin Raffel

  • LQG-obstacles: Feedback control with collision avoidance for mobile robots with motion and sensing uncertainty

    Jur van den Berg;David Wilkie;Stephen J. Guy;Marc Niethammer

  • Global medical shape analysis using the Laplace-Beltrami spectrum

    Marc Niethammer;Martin Reuter;Franz-Erich Wolter;Sylvain Bouix

Frequent Co-Authors

Allen Tannenbaum
Allen Tannenbaum Stony Brook University
James Stephen Marron
James Stephen Marron University of North Carolina at Chapel Hill
Martha E. Shenton
Martha E. Shenton Harvard University
Christopher Zach
Christopher Zach Chalmers University of Technology
Sylvain Bouix
Sylvain Bouix Harvard Medical School
Carl-Fredrik Westin
Carl-Fredrik Westin Brigham and Women's Hospital
Peter J. Mucha
Peter J. Mucha Dartmouth College
Kirk J. Czymmek
Kirk J. Czymmek Donald Danforth Plant Science Center
Stephen M. Pizer
Stephen M. Pizer University of North Carolina at Chapel Hill

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