| First Authors |
Martin Weigert
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| Authors |
Martin Weigert, Loic Royer, Florian Jug, Gene Myers
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| Corresponding Authors |
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| Last Authors |
Gene Myers
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| Conference Proceedings Volume Title |
Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2017 : 20th International Conference, Quebec City, QC, Canada, September 10-14, 2017, Proceedings, Part II |
| Series Title |
(Lecture Notes in Computer Science ; 10434) |
| Conference Name |
20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017; Quebec City; Canada; 11 September 2017 through 13 September 2017 |
| Conference Location |
Quebec City; Canada |
| Conference Start Date |
2017-09-11 |
| Conference End Date |
2017-09-13 |
| Chapter Number |
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| Publisher |
Springer International Publishing |
| Conference Proceedings Editors |
Maxime Descoteaux
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| ISBN |
978-331966184-1 |
| First Page |
126 |
| Last Page |
134 |
| Open Access |
false |
| Print Publication Date |
2017-09-13 |
| Online Publication Date |
2017-09-04 |
| Abstract |
Fluorescence microscopy images usually show severe anisotropy in axial versus lateral resolution. This hampers downstream processing, i.e. the automatic extraction of quantitative biological data. While deconvolution methods and other techniques to address this problem exist, they are either time consuming to apply or limited in their ability to remove anisotropy. We propose a method to recover isotropic resolution from readily acquired anisotropic data. We achieve this using a convolutional neural network that is trained end-to-end from the same anisotropic body of data we later apply the network to. The network effectively learns to restore the full isotropic resolution by restoring the image under a trained, sample specific image prior. We apply our method to 3 synthetic and 3 real datasets and show that our results improve on results from deconvolution and state-of-the-art super-resolution techniques. Finally, we demonstrate that a standard 3D segmentation pipeline performs on the output of our network with comparable accuracy as on the full isotropic data. © Springer International Publishing AG 2017. |
| PDF |
Weigert_2017_6948.pdf
(2.8 MB)
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| Cover Image |
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| Affiliated With |
CSBD, Jug, Myers, Postdocs, Predoc first author
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| Selected By |
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| Publication Status |
Published |
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| Sfx Link |
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| DOI |
10.1007/978-3-319-66185-8_15 |
| PubMed ID |
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| WebOfScience Link |
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| Display Publisher Download Only |
false |
| Visible On MPI-CBG Website |
true |
| PDF Downloadable |
true |
| Created By |
thuem |
| Added Date |
2017-10-02 |
| Last Edited By |
thuem |
| Last Edited Date |
2017-10-02 11:57:04.408 |
| Library ID |
6948 |
| Document ID |
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| Entry Complete |
true |
| eDoc Compliant |
true |
| Include in Edoc Report |
true |
| In Pure |
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| Ready for eDoc Export |
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| Author Affiliations Complete |
true |
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