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Frederik Maes

Frederik Maes

D-Index & Metrics

Computer Science

D-Index
60
Citations
26377
World Ranking
3161
National Ranking
29

Overview

Frederik Maes is affiliated with KU Leuven in Belgium and has a publication record focused primarily on Medicine, with a particular emphasis on Radiology, Nuclear Medicine and Imaging. Their research spans multiple subfields including Molecular Biology, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, and Oncology.

Their work extensively covers topics related to Radiomics and Machine Learning in Medical Imaging, Colorectal Cancer Screening and Detection, Advanced Neural Network Applications, and Advanced Radiotherapy Techniques. Other notable topics in their research portfolio include Muscle Physiology and Disorders, COVID-19 diagnosis using AI, and Advanced MRI Techniques and Applications.

Frederik Maes has contributed publications to a variety of scientific venues, frequently appearing in:

  • Endoscopy
  • Gastrointestinal Endoscopy
  • Radiotherapy and Oncology
  • Neuromuscular Disorders
  • arXiv (Cornell University)

Among the recent published papers linked to Frederik Maes, the following are noteworthy:

  • Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index (2020), IEEE Transactions on Medical Imaging
  • Lipid availability determines fate of skeletal progenitor cells via SOX9 (2020), Nature
  • Interobserver variability in organ at risk delineation in head and neck cancer (2021), Radiation Oncology
  • Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty (2022), Frontiers in Robotics and AI
  • icobrain ms 5.1: Combining unsupervised and supervised approaches for improving the detection of multiple sclerosis lesions (2021), NeuroImage Clinical

Frederik Maes collaborates regularly with several researchers, including:

  • Tom Eelbode
  • Raf Bisschops
  • Pieter Sinonquel
  • Siri Willems
  • Kristl G. Claeys

Best Publications

  • Multimodality image registration by maximization of mutual information

    F. Maes;A. Collignon;D. Vandermeulen;G. Marchal

  • Automated multi-moda lity image registration based on information theory

    Andre M.F. Collignon;Frederik Maes;D. Delaere;Dirk Vandermeulen

  • Automated model-based tissue classification of MR images of the brain

    K. Van Leemput;F. Maes;D. Vandermeulen;P. Suetens

  • Comparison and Evaluation of Retrospective Intermodality Brain Image Registration Techniques

    West J;Fitzpatrick Jm;Wang My;Dawant Bm

  • Multi-modality image registration by maximization of mutual information

    F. Maes;A. Collignon;D. Vandermeulen;G. Marchal

  • Automated model-based bias field correction of MR images of the brain

    K. Van Leemput;F. Maes;D. Vandermeulen;P. Suetens

  • Medical image registration using mutual information

    F. Maes;D. Vandermeulen;P. Suetens

  • Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information.

    Frederik Maes;Dirk Vandermeulen;Paul Suetens

  • Automated segmentation of multiple sclerosis lesions by model outlier detection

    K. Van Leemput;F. Maes;D. Vandermeulen;A. Colchester

  • ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

    Oskar Maier;Bjoern H. Menze;Janina von der Gablentz;Levin Häni

  • Comparison and evaluation of retrospective intermodality image registration techniques

    Jay B. West;J. Michael Fitzpatrick;Matthew Yang Wang;Benoit M. Dawant

  • Multi-modality image registration by maximization of mutual information

    Frederik Maes;Dirk Vandermeulen;Paul Suetens

  • A unifying framework for partial volume segmentation of brain MR images

    K. Van Leemput;F. Maes;D. Vandermeulen;P. Suetens

  • Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index

    Tom Eelbode;Jeroen Bertels;Maxim Berman;Dirk Vandermeulen

  • Nonrigid Image Registration Using Conditional Mutual Information

    D. Loeckx;P. Slagmolen;F. Maes;D. Vandermeulen

  • A viscous fluid model for multimodal non-rigid image registration using mutual information

    Emiliano D'Agostino;Frederik Maes;Dirk Vandermeulen;Paul Suetens

  • Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice

    Jeroen Bertels;Tom Eelbode;Maxim Berman;Dirk Vandermeulen

  • Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations. I. Methodology and validation on normal subjects

    B.M. Dawant;S.L. Hartmann;J.-P. Thirion;F. Maes

  • Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images

    Saurabh Jain;Diana M. Sima;Annemie Ribbens;Melissa Cambron

  • Automated multi-modality image registration based on information theory

    André Collignon;Frederik Maes;Dominique Delaere;Dirk Vandermeulen

  • Multi-modal volume registration by maximization of mutual information

    Frederik Maes;Andre M.F. Collignon;Dirk Vandermeulen;Guy Marchal

  • Clinical relevance of fully automated multimodality image registration by maximization of mutual information

    Frederik Maes;Dirk Vandermeulen;Guy Marchal;Paul Suetens

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