World's Best Scientists 2026 revealed!

Overview

Mads Nielsen is affiliated with the University of Copenhagen in Denmark and has contributed extensively to the fields of Medicine and Computer Science. Their research primarily focuses on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Epidemiology, and Health Informatics.

The scientist's work encompasses several main topics, including:

  • Radiomics and Machine Learning in Medical Imaging
  • AI in cancer detection
  • COVID-19 diagnosis using AI
  • Domain Adaptation and Few-Shot Learning
  • Artificial Intelligence in Healthcare and Education
  • Machine Learning in Healthcare
  • Dementia and Cognitive Impairment Research

Mads Nielsen has published research in a variety of venues, frequently appearing in:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Scientific Reports
  • Radiology
  • SSRN Electronic Journal

Selected recent papers authored or coauthored by Mads Nielsen include:

  • An Artificial Intelligence-based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload, 2022, Radiology
  • Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients, 2021, Scientific Reports
  • The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up, 2021, The Journal of Machine Learning for Biomedical Imaging
  • Position paper on COVID-19 imaging and AI: From the clinical needs and technological challenges to initial AI solutions at the lab and national level towards a new era for AI in healthcare, 2020, Medical Image Analysis
  • Impact of adding breast density to breast cancer risk models: A systematic review, 2020, European Journal of Radiology

Mads Nielsen has collaborated with several frequent coauthors, notably:

  • Mostafa Mehdipour Ghazi
  • Aasa Feragen
  • Anders Nymark Christensen
  • Martin G. Tolsgaard
  • Martin Lillholm

In addition to research articles, Nielsen has contributed to book publications, including a title published by Springer Science+Business Media:

  • Information Processing in Medical Imaging, 2021

Best Publications

  • Proceedings European Conference on Computer Vision 2002

    Anders Heyden;Gunnar Sparr;Mads Nielsen;Peter Johansen

  • Computer Vision - Eccv 2002

    Anders Heyden;Gunnar Sparr;Mads Nielsen;Peter Johansen

  • Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network

    Adhish Prasoon;Kersten Petersen;Christian Igel;François Lauze

  • Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring

    Michiel Kallenberg;Kersten Petersen;Mads Nielsen;Andrew Y. Ng

  • Scale-space theories in computer vision

    Mads Nielsen;Peter Johansen;Ole Fogh Olsen;Joachim Weickert

  • Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

    Esther E. Bron;Marion Smits;Wiesje M. van der Flier;Hugo Vrenken

  • Gaussian Scale-Space Theory

    Jon Sporring;Luc Florack;Mads Nielsen;Peter Johansen

  • Early detection of Alzheimer's disease using MRI hippocampal texture

    Lauge Sørensen;Christian Igel;Naja Liv Hansen;Merete Osler

  • Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry

    Lauge Sørensen;Christian Igel;Akshay Pai;Ioana Balas

  • Eye typing using Markov and active appearance models

    D.W. Hansen;J.P. Hansen;M. Nielsen;A.S. Johansen

  • Regularization, Scale-Space, and Edge Detection Filters

    Mads Nielsen;Luc Florack;Rachid Deriche

  • Texture-Based Analysis of COPD: A Data-Driven Approach

    L. Sorensen;M. Nielsen;Pechin Lo;H. Ashraf

  • Automatic segmentation of high- and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative.

    Erik B. Dam;Martin Lillholm;Joselene Marques;Mads Nielsen

  • Manifold valued statistics, exact principal, geodesic analysis and the effect of linear, approximations

    Stefan Sommer;François Lauze;Søren Hauberg;Mads Nielsen

  • Modeling and off-design performance of a 1 kWe HT-PEMFC (high temperature-proton exchange membrane fuel cell)-based residential micro-CHP (combined-heat-and-power) system for Danish single-family households

    Alexandros Arsalis;Mads Pagh Nielsen;Søren Knudsen Kær

  • Training recurrent neural networks robust to incomplete data: Application to Alzheimer's disease progression modeling.

    Mostafa Mehdipour Ghazi;Mads Nielsen;Akshay Pai;M Jorge Cardoso

  • Mass preserving image registration for lung CT.

    Vladlena Gorbunova;Jon Sporring;Pechin Lo;Martine Loeve

  • Quantitative vertebral morphometry using neighbor-conditional shape models

    Marleen de Bruijne;Michael T. Lund;László B. Tankó;Paola C. Pettersen

  • The Intrinsic Structure of Optic Flow Incorporating Measurement Duality

    Luc Florack;Wiro Niessen;Mads Nielsen

  • Non-rigid registration by geometry-constrained diffusion

    Per Rønsholt Andresen;Mads Nielsen

Frequent Co-Authors

Marleen de Bruijne
Marleen de Bruijne Erasmus University Rotterdam
Søren Knudsen Kær
Søren Knudsen Kær Aalborg University
Christian Igel
Christian Igel University of Copenhagen
Marco Loog
Marco Loog Radboud University
Sebastien Ourselin
Sebastien Ourselin King's College London
Marc Modat
Marc Modat King's College London
Xavier Pennec
Xavier Pennec French Institute for Research in Computer Science and Automation - INRIA
Brian Elmegaard
Brian Elmegaard Technical University of Denmark
Nico Karssemeijer
Nico Karssemeijer Radboud University
Wiro J. Niessen
Wiro J. Niessen Erasmus University Rotterdam

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