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Found 3 papers, 2 papers with code
Microscopy Image Segmentation via Point and Shape Regularized Data Synthesis
Current deep learning-based approaches for the segmentation of microscopy images heavily rely on large amount of training data with dense annotation, which is highly costly and laborious in practice.
Improved Counting and Localization from Density Maps for Object Detection in 2D and 3D Microscopy Imaging
Our results show improved performance in counting and localization of objects in 2D and 3D microscopy data.
Point-supervised Segmentation of Microscopy Images and Volumes via Objectness Regularization
Annotation is a major hurdle in the semantic segmentation of microscopy images and volumes due to its prerequisite expertise and effort.
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