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Cited by 341

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Crowdsourcing the creation of image segmentation algorithms for connectomics

Open access
Arganda-Carreras, Ignacio, Turaga, Srinivas C., Berger, Daniel R., Cireşan, Dan, Giusti, Alessandro, Gambardella, Luca M., Schmidhuber, Jürgen, Laptev, Dmitry, Dwivedi, Sarvesh, Buhmann, Joachim M., Liu, Ting, Seyedhosseini, Mojtaba, Tasdizen, Tolga, Kamentsky, Lee, Burget, Radim, Uher, Vaclav, Tan, Xiao, Sun, Changming, Pham, Tuan D., Bas, Erhan, Uzunbas, Mustafa G., Cardona, Albert, Schindelin, Johannes, Seung, H. Sebastian·2015·Frontiers in Neuroanatomy

Abstract

To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with a consensus of human expert annotations. The winning team had no prior experience with EM images, and employed a convolutional network. This "deep learning" approach has since become accepted as a standard for segmentation of EM images. The challenge has continued to accept submissions, and the best so far has resulted from cooperation between two teams. The challenge has probably saturated, as algorithms cannot progress beyond limits set by ambiguities inherent in 2D scoring and the size of the test dataset. Retrospective evaluation of the challenge scoring system reveals that it was not sufficiently robust to variations in the widths of neurite borders. We propose a solution to this problem, which should be useful for a future 3D segmentation challenge.

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Metadata

Authors
Arganda-Carreras, I., Turaga, S. C., Berger, D. R., Cireşan, D., Giusti, A., Gambardella, L. M., Schmidhuber, J., Laptev, D., Dwivedi, S., Buhmann, J. M., Liu, T., Seyedhosseini, M., Tasdizen, T., Kamentsky, L., Burget, R., Uher, V., Tan, X., Sun, C., Pham, T. D., Bas, E., Uzunbas, M. G., Cardona, A., Schindelin, J., & Seung, H. S.
Venue
Frontiers in Neuroanatomy
Published
2015-11-05
Volume
9
Pages
142-142
ISSN
1662-5129 (ISSN-L)
OpenAlex
W1898703532
Cited by
341
References
11
FWCI
12.70
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Crowdsourcing the creation of image segmentation algorithms for connectomics. https://app.cochat.ai/papers/10.3389/fnana.2015.00142
The paper
Arganda-Carreras, I., Turaga, S. C., Berger, D. R., Cireşan, D., Giusti, A., Gambardella, L. M., Schmidhuber, J., Laptev, D., Dwivedi, S., Buhmann, J. M., Liu, T., Seyedhosseini, M., Tasdizen, T., Kamentsky, L., Burget, R., Uher, V., Tan, X., Sun, C., Pham, T. D., . . . Seung, H. S. (2015). Crowdsourcing the creation of image segmentation algorithms for connectomics. Frontiers in Neuroanatomy. https://doi.org/10.3389/fnana.2015.00142

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.