JULAIN Talk by Eric Upschulte
Uncertainty-Aware Contour Proposal Networks for Cell Segmentation in Multi-Modality High-Resolution Microscopy
Eric Upschulte (INM-1) won a Winner Finalist Award at NeurIPS 2022's Cell segmentation challenge.
Where: online (in the usual JULAIN zoom-meeting room)
In this Journal Club we will discuss the according paper. Eric will give a short intro and is happy to answer your questions about his solution and what it's like to take part in a NeurIPS competition.
The paper presents a simple framework for cell segmentation, based on uncertainty-aware Contour Proposal Networks (CPNs). It is designed to provide high segmentation accuracy while remaining computationally efficient, which makes it an ideal solution for high throughput microscopy applications. Each predicted cell is provided with four uncertainty estimations that give information about the localization accuracy of the detected cell boundaries. Such additional insights are valuable for downstream single-cell analysis in microscopy image-based biology and biomedical research. In the context of the NeurIPS 22 Cell Segmentation Challenge, the proposed solution is shown to generalize well in a multi-modality setting, while respecting domain-specific requirements such as focusing on specific cell types.