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Olaf Ronneberger

Olaf Ronneberger

D-Index & Metrics

Computer Science

D-Index
45
Citations
158004
World Ranking
6960
National Ranking
335

Overview

Olaf Ronneberger is affiliated with the University of Freiburg in Germany. Their research primarily focuses on Biochemistry, Genetics and Molecular Biology, with a particular emphasis on Molecular Biology, Materials Chemistry, Artificial Intelligence, Computer Vision and Pattern Recognition, and Biophysics.

The main topics Ronneberger has worked on include Protein Structure and Dynamics, Machine Learning in Bioinformatics, Enzyme Structure and Function, Advanced Neural Network Applications, Cell Image Analysis Techniques, Advanced Electron Microscopy Techniques and Applications, and Genetic and Kidney Cyst Diseases.

Ronneberger has contributed to several notable recent publications. Among these are:

  • Highly accurate protein structure prediction with AlphaFold, 2021, Nature
  • Accurate structure prediction of biomolecular interactions with AlphaFold 3, 2024, Nature
  • Protein complex prediction with AlphaFold-Multimer, 2021, bioRxiv (Cold Spring Harbor Laboratory)
  • Highly accurate protein structure prediction for the human proteome, 2021, Nature
  • The Medical Segmentation Decathlon, 2022, Nature Communications

Ronneberger's publications have appeared frequently in high-impact venues, including:

  • Nature
  • Nature Communications
  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Dagstuhl Research Online Publication Server

The scientist has worked in collaboration with several frequent co-authors, such as:

  • Pushmeet Kohli
  • John Jumper
  • K Taki
  • Alexander Pritzel
  • Tim Green

Best Publications

  • U-Net: Convolutional Networks for Biomedical Image Segmentation

    Olaf Ronneberger;Philipp Fischer;Thomas Brox

  • Highly accurate protein structure prediction with AlphaFold

    John M. Jumper;Richard O. Evans;Alexander Pritzel;Tim Green

  • 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

    Özgün Çiçek;Ahmed Abdulkadir;Ahmed Abdulkadir;Soeren S. Lienkamp;Thomas Brox

  • Protein complex prediction with AlphaFold-Multimer

    Richard Evans;Michael O'Neill;Alexander Pritzel;Natasha Antropova

  • Highly accurate protein structure prediction for the human proteome

    Kathryn Tunyasuvunakool;Jonas Adler;Zachary Wu;Tim Green

  • Clinically applicable deep learning for diagnosis and referral in retinal disease

    Jeffrey De Fauw;Joseph R. Ledsam;Bernardino Romera-Paredes;Stanislav Nikolov

  • U-Net: deep learning for cell counting, detection, and morphometry

    Thorsten Falk;Dominic Mai;Robert Bensch;Özgün Çiçek

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • Gland segmentation in colon histology images: The GlaS challenge contest

    Korsuk Sirinukunwattana;Josien P.W. Pluim;Hao Chen;Xiaojuan Qi

  • A large annotated medical image dataset for the development and evaluation of segmentation algorithms

    Amber L. Simpson;Michela Antonelli;Spyridon Bakas;Michel Bilello

  • An objective comparison of cell-tracking algorithms

    Vladimír Ulman;Martin Maška;Klas E G Magnusson;Olaf Ronneberger

  • Applying and improving AlphaFold at CASP14

    John Jumper;Richard Evans;Alexander Pritzel;Tim Green

  • 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

  • A benchmark for comparison of dental radiography analysis algorithms

    Ching-Wei Wang;Cheng-Ta Huang;Jia-Hong Lee;Chung-Hsing Li

  • A Probabilistic U-Net for Segmentation of Ambiguous Images

    Simon A. A. Kohl;Bernardino Romera-Paredes;Clemens Meyer;Jeffrey De Fauw

  • Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

    Stanislav Nikolov;Sam Blackwell;Ruheena Mendes;Jeffrey De Fauw

  • Micro-Raman spectroscopic identification of bacterial cells of the genus Staphylococcus and dependence on their cultivation conditions

    M. Harz;P. Rösch;K. Peschke;Olaf Ronneberger

  • Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study

    Stanislav Nikolov;Sam Blackwell;Alexei Zverovitch;Ruheena Mendes

  • Rotation-Invariant HOG Descriptors Using Fourier Analysis in Polar and Spherical Coordinates

    Kun Liu;Henrik Skibbe;Thorsten Schmidt;Thomas Blein

  • XuvTools: free, fast and reliable stitching of large 3D datasets.

    M. Emmenlauer;Olaf Ronneberger;A. Ponti;P. Schwarb

  • Contrastive Training for Improved Out-of-Distribution Detection.

    Jim Winkens;Rudy Bunel;Abhijit Guha Roy;Robert Stanforth

Frequent Co-Authors

Hans Burkhardt
Hans Burkhardt University of Freiburg
Thomas Brox
Thomas Brox University of Freiburg
Klaus Palme
Klaus Palme University of Freiburg
Wolfgang Driever
Wolfgang Driever University of Freiburg
Roland Nitschke
Roland Nitschke University of Freiburg
Pushmeet Kohli
Pushmeet Kohli DeepMind (United Kingdom)
Demis Hassabis
Demis Hassabis Google (United States)
Andrew W. Senior
Andrew W. Senior Google (United States)
Geraint Rees
Geraint Rees University College London
Klaus H. Maier-Hein
Klaus H. Maier-Hein German Cancer Research Center

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