| First Authors | Coleman Broaddus |
|---|---|
| Authors | Coleman Broaddus, Alexander Krull, Martin Weigert, Uwe Schmidt, Gene Myers |
| Corresponding Authors | |
| Last Authors | Gene Myers |
| Conference Proceedings Volume Title | IEEE ISBI 2020 : International Conference on Biomedical Imaging : April 2-7, 2020, Iowa City, Iowa, USA : symposium proceeding |
| Series Title | IEEE International Symposium on Biomedical Imaging |
| Conference Name | IEEE 17th International Symposium on Biomedical Imaging (ISBI) |
| Conference Location | Iowa City, Iowa, USA |
| Conference Start Date | 2020-04-02 |
| Conference End Date | 2020-04-06 |
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| Publisher | IEEE |
| Conference Proceedings Editors | |
| ISBN | 978-1-5386-9330-8 |
| First Page | 159 |
| Last Page | 163 |
| Open Access | false |
| Print Publication Date | 2020-05-22 |
| Online Publication Date | 2020-05-22 |
| Abstract | Removal of noise from fluorescence microscopy images is an important first step in many biological analysis pipelines. Current state-of-the-art supervised methods employ convolutional neural networks that are trained with clean (ground-truth) images. Recently, it was shown that self-supervised image denoising with blind spot networks achieves excellent performance even when ground-truth images are not available, as is common in fluorescence microscopy. However, these approaches, e.g. Noise2Void ( N2V), generally assume pixel-wise independent noise, thus limiting their applicability in situations where spatially correlated (structured) noise is present. To overcome this limitation, we present Structured Noise2Void (STRUCTN2V), a generalization of blind spot networks that enables removal of structured noise without requiring an explicit noise model or ground truth data. Specifically, we propose to use an extended blind mask (rather than a single pixel/blind spot), whose shape is adapted to the structure of the noise. We evaluate our approach on two real datasets and show that STRUCTN2V considerably improves the removal of structured noise compared to existing standard and blind-spot based techniques. |
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| Affiliated With | CSBD, Myers |
| Selected By | |
| Acknowledged Services | Light Microscopy Facility |
| Publication Status | Published |
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| DOI | 10.1109/ISBI45749.2020.9098336 |
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| Created By | thuem |
| Added Date | 2021-02-03 |
| Last Edited By | herbst |
| Last Edited Date | 2021-06-21 17:42:19.349 |
| Library ID | 7927 |
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