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Olaf Ronneberger

Showing results (31-40 of 45) with videos related to

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Proceedings of the National Academy of Sciences of the United States of America|November 10, 2010
Inversin relays Frizzled-8 signals to promote proximal pronephros developmentSoeren Lienkamp, Athina Ganner, Christopher Boehlke, et al.
Development (Cambridge, England)|November 5, 2021
Deep learning is widely applicable to phenotyping embryonic development and diseaseThomas Naert, Özgün Çiçek, Paulina Ogar, et al.
Nature Neuroscience|April 18, 2017
A new fate mapping system reveals context-dependent random or clonal expansion of microgliaTuan Leng Tay, Dominic Mai, Jana Dautzenberg, et al.
Nature Methods|February 27, 2019
Author Correction: U-Net: deep learning for cell counting, detection, and morphometryThorsten Falk, Dominic Mai, Robert Bensch, et al.
Nature Methods|December 19, 2018
U-Net: deep learning for cell counting, detection, and morphometryThorsten Falk, Dominic Mai, Robert Bensch, et al.
Medical Image Analysis|September 12, 2016
Gland segmentation in colon histology images: The glas challenge contestKorsuk Sirinukunwattana, Josien P W Pluim, Hao Chen, et al.
Journal of Medical Internet Research|July 13, 2021
Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation StudyStanislav Nikolov, Sam Blackwell, Alexei Zverovitch, et al.
Proteins|October 2, 2021
Applying and improving AlphaFold at CASP14John Jumper, Richard Evans, Alexander Pritzel, et al.
Nature|July 15, 2021
Highly accurate protein structure prediction with AlphaFoldJohn Jumper, Richard Evans, Alexander Pritzel, et al.
Nature|July 22, 2021
Highly accurate protein structure prediction for the human proteomeKathryn Tunyasuvunakool, Jonas Adler, Zachary Wu, et al.
Pageof 5

Showing results (31-40 of 45) with videos related to

Sort By:
Pageof 5
Proceedings of the National Academy of Sciences of the United States of America|November 10, 2010
Inversin relays Frizzled-8 signals to promote proximal pronephros developmentSoeren Lienkamp, Athina Ganner, Christopher Boehlke, et al.
Development (Cambridge, England)|November 5, 2021
Deep learning is widely applicable to phenotyping embryonic development and diseaseThomas Naert, Özgün Çiçek, Paulina Ogar, et al.
Nature Neuroscience|April 18, 2017
A new fate mapping system reveals context-dependent random or clonal expansion of microgliaTuan Leng Tay, Dominic Mai, Jana Dautzenberg, et al.
Nature Methods|February 27, 2019
Author Correction: U-Net: deep learning for cell counting, detection, and morphometryThorsten Falk, Dominic Mai, Robert Bensch, et al.
Nature Methods|December 19, 2018
U-Net: deep learning for cell counting, detection, and morphometryThorsten Falk, Dominic Mai, Robert Bensch, et al.
Medical Image Analysis|September 12, 2016
Gland segmentation in colon histology images: The glas challenge contestKorsuk Sirinukunwattana, Josien P W Pluim, Hao Chen, et al.
Journal of Medical Internet Research|July 13, 2021
Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation StudyStanislav Nikolov, Sam Blackwell, Alexei Zverovitch, et al.
Proteins|October 2, 2021
Applying and improving AlphaFold at CASP14John Jumper, Richard Evans, Alexander Pritzel, et al.
Nature|July 15, 2021
Highly accurate protein structure prediction with AlphaFoldJohn Jumper, Richard Evans, Alexander Pritzel, et al.
Nature|July 22, 2021
Highly accurate protein structure prediction for the human proteomeKathryn Tunyasuvunakool, Jonas Adler, Zachary Wu, et al.
Pageof 5