Attention-driven UNet enhancement for accurate segmentation of bacterial spore outgrowth in microscopy images
Abstract Analyzing microscopy images of large growing cell samples using traditional methods is a complex and time-consuming process. In this work, we have developed an attention-driven UNet-enhanced model using deep learning techniques to efficiently quantify the position, area, and circularity of...
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| Main Authors: | Saqib Qamar, Dmitry Malyshev, Rasmus Öberg, Daniel P. G. Nilsson, Magnus Andersson |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-06-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-05900-6 |
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