D-Index & Metrics Best Publications

Olaf Ronneberger

University of Freiburg
Germany

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 38 Citations 55,677 110 World Ranking 6198 National Ranking 290

Overview

What is he best known for?

The fields of study Olaf Ronneberger is best known for:

Gene
Neuron
Operating system

His Artificial intelligence study frequently draws parallels with other fields, such as Pattern recognition (psychology). He connects Machine learning with Data science in his research. His study deals with a combination of Data science and Machine learning. Many of his studies on Segmentation apply to Image segmentation as well. Olaf Ronneberger conducts interdisciplinary study in the fields of Image segmentation and Computer vision through his research. His Computer vision study frequently links to adjacent areas such as Segmentation. Olaf Ronneberger integrates many fields in his works, including Gene and Computational biology. Olaf Ronneberger undertakes multidisciplinary studies into Computational biology and Biochemistry in his work. Olaf Ronneberger combines Biochemistry and Protein structure in his studies.

His most cited work include:

U-Net: Convolutional Networks for Biomedical Image Segmentation (25475 citations)
Highly accurate protein structure prediction with AlphaFold (9640 citations)
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation (2119 citations)

What are the main themes of his work throughout his whole career to date

While working on this project, Olaf Ronneberger studies both Artificial intelligence and Algorithm. His work often combines Algorithm and Artificial intelligence studies. Segmentation is often connected to Image segmentation in his work. His Image segmentation study often links to related topics such as Segmentation. Borrowing concepts from Biochemistry, he weaves in ideas under Gene. His study deals with a combination of Biochemistry and Gene. His research links Image (mathematics) with Computer vision. His Image (mathematics) study frequently draws connections to other fields, such as Computer vision. Machine learning and Deep learning are two areas of study in which he engages in interdisciplinary work.

Olaf Ronneberger most often published in these fields:

Artificial intelligence (67.53%)
Pattern recognition (psychology) (37.66%)
Segmentation (28.57%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger;Philipp Fischer;Thomas Brox.
medical image computing and computer assisted intervention (2015)

38557 Citations

Highly accurate protein structure prediction with AlphaFold

John M. Jumper;Richard O. Evans;Alexander Pritzel;Tim Green.
Nature (2021)

5474 Citations

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

Özgün Çiçek;Ahmed Abdulkadir;Ahmed Abdulkadir;Soeren S. Lienkamp;Thomas Brox.
medical image computing and computer assisted intervention (2016)

2910 Citations

Clinically applicable deep learning for diagnosis and referral in retinal disease

Jeffrey De Fauw;Joseph R. Ledsam;Bernardino Romera-Paredes;Stanislav Nikolov.
Nature Medicine (2018)

1456 Citations

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

Thorsten Falk;Dominic Mai;Robert Bensch;Özgün Çiçek.
Nature Methods (2019)

920 Citations

Highly accurate protein structure prediction for the human proteome

Kathryn Tunyasuvunakool;Jonas Adler;Zachary Wu;Tim Green.
Nature (2021)

766 Citations

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

Amber L. Simpson;Michela Antonelli;Spyridon Bakas;Michel Bilello.
arXiv: Computer Vision and Pattern Recognition (2019)

498 Citations

Gland segmentation in colon histology images: The GlaS challenge contest

Korsuk Sirinukunwattana;Josien P.W. Pluim;Hao Chen;Xiaojuan Qi.
Medical Image Analysis (2017)

422 Citations

A new fate mapping system reveals context-dependent random or clonal expansion of microglia

Tuan Leng Tay;Dominic Mai;Jana Dautzenberg;Francisco Fernández-Klett.
Nature Neuroscience (2017)

411 Citations

An objective comparison of cell-tracking algorithms

Vladimír Ulman;Martin Maška;Klas E G Magnusson;Olaf Ronneberger.
Nature Methods (2017)

361 Citations

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Olaf Ronneberger

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Overview

What is he best known for?

The fields of study Olaf Ronneberger is best known for:

His most cited work include:

What are the main themes of his work throughout his whole career to date

Olaf Ronneberger most often published in these fields:

Best Publications

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