Deep Learning in Image Cytometry: A Review-Reference-Cited by-同舟云学术

Deep Learning in Image Cytometry: A Review

Published:2018-12-19 Issue:4 Volume:95 Page:366-380
ISSN:1552-4922
Container-title:Cytometry Part A
language:en
Short-container-title:Cytometry

Author:

Gupta Anindya¹^ORCID,Harrison Philip J.²^ORCID,Wieslander Håkan¹^ORCID,Pielawski Nicolas¹^ORCID,Kartasalo Kimmo³⁴^ORCID,Partel Gabriele¹^ORCID,Solorzano Leslie¹^ORCID,Suveer Amit¹^ORCID,Klemm Anna H.¹⁵^ORCID,Spjuth Ola²^ORCID,Sintorn Ida‐Maria¹^ORCID,Wählby Carolina¹⁵^ORCID

Affiliation:

1. Centre for Image AnalysisUppsala University Uppsala 75124 Sweden

2. Department of Pharmaceutical BiosciencesUppsala University Uppsala 75124 Sweden

3. Faculty of Medicine and Life SciencesUniversity of Tampere Tampere 33014 Finland

4. Faculty of Biomedical Sciences and EngineeringTampere University of Technology Tampere 33720 Finland

5. BioImage Informatics Facility of SciLifeLab Uppsala 75124 Sweden

Funder

H2020 European Research Council

Stiftelsen för Strategisk Forskning

Vetenskapsrådet

Publisher

Wiley

Subject

Cell Biology,Histology,Pathology and Forensic Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cyto.a.23701

Reference137 articles.

1. Methods for Cell and Particle Tracking

2. A Feature Set for Cytometry on Digitized Microscopic Images

3. Machine learning in cell biology – teaching computers to recognize phenotypes

4. Next-Generation Machine Learning for Biological Networks

5. The perceptron: A probabilistic model for information storage and organization in the brain.

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