NDLI: Drosophila Embryo Stage Annotation Using Label Propagation

Content Provider	IEEE Xplore Digital Library
Author	Kazmar, T. Kvon, E.Z. Stark, A. Lampert, C.H.
Copyright Year	2013
Description	Author affiliation: Res. Inst. of Mol. Pathology (IMP), Vienna, Austria (Kazmar, T.; Kvon, E.Z.; Stark, A.) \|\| Inst. of Sci. & Technol. Austria, Klosterneuburg, Austria (Lampert, C.H.)
Abstract	In this work we propose a system for automatic classification of Drosophila embryos into developmental stages. While the system is designed to solve an actual problem in biological research, we believe that the principle underlying it is interesting not only for biologists, but also for researchers in computer vision. The main idea is to combine two orthogonal sources of information: one is a classifier trained on strongly invariant features, which makes it applicable to images of very different conditions, but also leads to rather noisy predictions. The other is a label propagation step based on a more powerful similarity measure that however is only consistent within specific subsets of the data at a time. In our biological setup, the information sources are the shape and the staining patterns of embryo images. We show experimentally that while neither of the methods can be used by itself to achieve satisfactory results, their combination achieves prediction quality comparable to human performance.
Sponsorship	IEEE Comput. Soc.
Starting Page	1089
Ending Page	1096
File Size	609976
Page Count	8
File Format	PDF
ISBN	9781479928408
ISSN	15505499
DOI	10.1109/ICCV.2013.139
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Embryo Training Shape DNA Training data Genomics
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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