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Tim Scherr

Showing results (1-10 of 10) with videos related to

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Plos One|September 7, 2021
A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correctionKatharina Löffler, Tim Scherr, Ralf Mikut
Plos One|December 8, 2020
Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategyTim Scherr, Katharina Löffler, Moritz Böhland, et al.
Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry|March 7, 2020
Segregation of Dispersed Silica Nanoparticles in Microfluidic Water-in-Oil Droplets: A Kinetic StudySahana Sheshachala, Maximilian Grösche, Tim Scherr, et al.
Bioinformatics (Oxford, England)|June 27, 2020
BeadNet: deep learning-based bead detection and counting in low-resolution microscopy imagesTim Scherr, Karolin Streule, Andreas Bartschat, et al.
Plos One|September 22, 2021
Machine learning methods for automated classification of tumors with papillary thyroid carcinoma-like nuclei: A quantitative analysisMoritz Böhland, Lars Tharun, Tim Scherr, et al.
Plos One|November 29, 2022
microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentationTim Scherr, Johannes Seiffarth, Bastian Wollenhaupt, et al.
Klinische Monatsblatter Fur Augenheilkunde|November 1, 2019
[Digital Image Processing and Deep Neural Networks in Ophthalmology - Current Trends]Andreas Bartschat, Stephan Allgeier, Sebastian Bohn, et al.
Plos Genetics|June 20, 2020
Pax6 organizes the anterior eye segment by guiding two distinct neural crest wavesMasanari Takamiya, Johannes Stegmaier, Andrei Yu Kobitski, et al.
Medical Image Analysis|December 29, 2023
CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and countingSimon Graham, Quoc Dang Vu, Mostafa Jahanifar, et al.
Nature Methods|May 18, 2023
The Cell Tracking Challenge: 10 years of objective benchmarkingMartin Maška, Vladimír Ulman, Pablo Delgado-Rodriguez, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Plos One|September 7, 2021
A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correctionKatharina Löffler, Tim Scherr, Ralf Mikut
Plos One|December 8, 2020
Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategyTim Scherr, Katharina Löffler, Moritz Böhland, et al.
Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry|March 7, 2020
Segregation of Dispersed Silica Nanoparticles in Microfluidic Water-in-Oil Droplets: A Kinetic StudySahana Sheshachala, Maximilian Grösche, Tim Scherr, et al.
Bioinformatics (Oxford, England)|June 27, 2020
BeadNet: deep learning-based bead detection and counting in low-resolution microscopy imagesTim Scherr, Karolin Streule, Andreas Bartschat, et al.
Plos One|September 22, 2021
Machine learning methods for automated classification of tumors with papillary thyroid carcinoma-like nuclei: A quantitative analysisMoritz Böhland, Lars Tharun, Tim Scherr, et al.
Plos One|November 29, 2022
microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentationTim Scherr, Johannes Seiffarth, Bastian Wollenhaupt, et al.
Klinische Monatsblatter Fur Augenheilkunde|November 1, 2019
[Digital Image Processing and Deep Neural Networks in Ophthalmology - Current Trends]Andreas Bartschat, Stephan Allgeier, Sebastian Bohn, et al.
Plos Genetics|June 20, 2020
Pax6 organizes the anterior eye segment by guiding two distinct neural crest wavesMasanari Takamiya, Johannes Stegmaier, Andrei Yu Kobitski, et al.
Medical Image Analysis|December 29, 2023
CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and countingSimon Graham, Quoc Dang Vu, Mostafa Jahanifar, et al.
Nature Methods|May 18, 2023
The Cell Tracking Challenge: 10 years of objective benchmarkingMartin Maška, Vladimír Ulman, Pablo Delgado-Rodriguez, et al.
Pageof 1