Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification-Reference-Cited by-同舟云学术

Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification

Published:2017-03-30 Issue:15 Volume:33 Page:2424-2426
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Arganda-Carreras Ignacio¹²³,Kaynig Verena⁴,Rueden Curtis⁵,Eliceiri Kevin W⁵,Schindelin Johannes⁵,Cardona Albert⁶,Sebastian Seung H⁷

Affiliation:

1. Ikerbasque, Basque Foundation for Science, Bilbao, Spain

2. Computer Science and Artificial Intelligence Department, Basque Country University, San Sebastian, Spain

3. Donostia International Physics Center, San Sebastian, Spain

4. Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

5. Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI, USA

6. Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA, USA

7. Neuroscience Institute and Computer Science Department, Princeton University, NJ, USA

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/33/15/2424/25157856/btx180.pdf

Reference7 articles.

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2. Improved structure, function and compatibility for cellprofiler: modular high-throughput image analysis software;Kamentsky;Bioinformatics,2011

3. Collaborative analysis of multi-gigapixel imaging data using cytomine;Marée;Bioinformatics,2016

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