World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
64
Citations
17340
World Ranking
2590
National Ranking
112

Research.com Recognitions

  • 2013 - Fellow of Alfred P. Sloan Foundation

Overview

Andreas Maier is affiliated with the University of Erlangen-Nuremberg in Germany. Their research spans several interdisciplinary fields including Medicine, Computer Science, and Engineering, with a significant focus on subfields such as Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, and Pulmonary and Respiratory Medicine.

The main topics covered in their work include Medical Imaging Techniques and Applications, Advanced X-ray and CT Imaging, Radiomics and Machine Learning in Medical Imaging, AI in cancer detection, Medical Image Segmentation Techniques, Advanced MRI Techniques and Applications, and Retinal Imaging and Analysis.

Recent publications by Andreas Maier include:

  • "A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging", 2020, Medical Image Analysis
  • "Mitosis domain generalization in histopathology images - The MIDOG challenge", 2022, Medical Image Analysis
  • "Noise reduction in optical coherence tomography images using a deep neural network with perceptually-sensitive loss function", 2020, Biomedical Optics Express
  • "Benchmarking ChatGPT-4 on a radiation oncology in-training exam and Red Journal Gray Zone cases: potentials and challenges for ai-assisted medical education and decision making in radiation oncology", 2023, Frontiers in Oncology
  • "Deepfilternet: A Low Complexity Speech Enhancement Framework for Full-Band Audio Based On Deep Filtering", 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Frequent co-authors who have collaborated extensively with Andreas Maier are:

  • Vincent Christlein
  • Katharina Breininger
  • Marc Aubreville
  • Mareike Thies
  • Yixing Huang

Their work has been published across various specialized venues, including:

  • arXiv (Cornell University)
  • Scientific Reports
  • Zenodo (CERN European Organization for Nuclear Research)
  • 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
  • e-Journal of Nondestructive Testing

Andreas Maier has contributed to numerous book publications. Notable publishers include Springer Nature, with titles such as "Bildverarbeitung für die Medizin 2020" (2020), "Bildverarbeitung für die Medizin 2022" (2022), "Bildverarbeitung für die Medizin 2023" (2023), and "Bildverarbeitung für die Medizin 2024" (2024). Additionally, they have published "Machine Learning for Medical Image Reconstruction" (2022) with Springer Science+Business Media and "Auditory Perception and Phantom Perception in Brains, Minds and Machines" (2023) with Frontiers Media.

Among the awards received, Andreas Maier was named a Fellow of the Alfred P. Sloan Foundation in 2013.

Best Publications

  • Robust Vessel Segmentation in Fundus Images

    Attila Budai;Rüdiger Bock;Andreas K. Maier;Joachim Hornegger

  • A gentle introduction to deep learning in medical image processing

    Andreas K. Maier;Christopher Syben;Tobias Lasser;Christian Riess

  • Automatic classification of defective photovoltaic module cells in electroluminescence images

    Sergiu Deitsch;Vincent Christlein;Stephan Berger;Claudia Buerhop-Lutz

  • A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging.

    Zhaohan Xiong;Qing Xia;Zhiqiang Hu;Ning Huang

  • Multi-Scale Deep Reinforcement Learning for Real-Time 3D-Landmark Detection in CT Scans

    Florin-Cristian Ghesu;Bogdan Georgescu;Yefeng Zheng;Sasa Grbic

  • Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning.

    Marc Aubreville;Christian Knipfer;Christian Knipfer;Nicolai Oetter;Christian Jaremenko

  • Learning with Known Operators reduces Maximum Training Error Bounds.

    Andreas K. Maier;Christopher Syben;Bernhard Stimpel;Tobias Würfl

  • Deep Learning Computed Tomography: Learning Projection-Domain Weights From Image Domain in Limited Angle Problems

    Tobias Wurfl;Mathis Hoffmann;Vincent Christlein;Katharina Breininger

  • PEAKS - A system for the automatic evaluation of voice and speech disorders

    A. Maier;T. Haderlein;U. Eysholdt;F. Rosanowski

  • Robust Non-rigid Registration Through Agent-Based Action Learning

    Julian Krebs;Julian Krebs;Tommaso Mansi;Hervé Delingette;Li Zhang

  • Learning to Recognize Abnormalities in Chest X-Rays with Location-Aware Dense Networks

    Sebastian Gündel;Sasa Grbic;Bogdan Georgescu;Siqi Liu

  • Deep Learning Computed Tomography

    Tobias Würfl;Florin C. Ghesu;Vincent Christlein;Andreas K. Maier

  • Towards More Reality in the Recognition of Emotional Speech

    B. Schuller;D. Seppi;A. Batliner;A. Maier

  • CONRAD—A software framework for cone-beam imaging in radiology

    Andreas Maier;Hannes G. Hofmann;Martin Berger;Peter Fischer

  • Age and gender recognition for telephone applications based on GMM supervectors and support vector machines

    T. Bocklet;A. Maier;J.G. Bauer;F. Burkhardt

  • Segmentation of photovoltaic module cells in uncalibrated electroluminescence images

    Sergiu Deitsch;Claudia Buerhop-Lutz;Evgenii Sovetkin;Ansgar Steland

  • Evaluation of speech intelligibility for children with cleft lip and palate by means of automatic speech recognition

    Maria Schuster;Andreas Maier;Tino Haderlein;Emeka Nkenke

  • TOWARD QUANTITATIVE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY: Visualizing Blood Flow Speeds in Ocular Pathology Using Variable Interscan Time Analysis

    Stefan B. Ploner;Eric M. Moult;WooJhon Choi;Nadia K. Waheed

  • Classification of breast cancer histology images using transfer learning

    Sulaiman Vesal;Nishant Ravikumar;AmirAbbas Davari;Stephan Ellmann

  • Decoding Sources of Energy Variability in a Laser-Plasma Accelerator

    Andreas R. Maier;Niels M. Delbos;Timo Eichner;Lars Hübner

  • Automatic CAD-RADS Scoring Using Deep Learning

    Felix Denzinger;Michael Wels;Katharina Breininger;Mehmet A. Gülsün

  • Writer Identification Using GMM Supervectors and Exemplar-SVMs

    Vincent Christlein;David Bernecker;Florian Hönig;Andreas K. Maier

Frequent Co-Authors

Joachim Hornegger
Joachim Hornegger University of Erlangen-Nuremberg
Rebecca Fahrig
Rebecca Fahrig Siemens Healthcare (United States)
Elmar Nöth
Elmar Nöth University of Erlangen-Nuremberg
Stefan Steidl
Stefan Steidl MorphoSys (Germany)
Xiaolin Huang
Xiaolin Huang Shanghai Jiao Tong University
Gisela Anton
Gisela Anton University of Erlangen-Nuremberg
Nassir Navab
Nassir Navab Technical University of Munich
Silke Christiansen
Silke Christiansen Fraunhofer Society
Dorin Comaniciu
Dorin Comaniciu Siemens (United States)

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