Threshold independent detection and localization of diffraction-limited spots.
In biomedical microscopy data, a common task involves the detection of diffraction-limited spots that visualize single proteins, domains, mRNAs, and many more. These spots were traditionally detected with mathematical operators such as Laplacian of Gaussian. These operators, however, rely on human input ranging from image-intensity thresholds, approximative spot sizes, etc. This process is tedious and not always reliable. DeepBlink relies on neural networks to automatically find spots without the need for human intervention. DeepBlink is available as a ready-to-use command-line interface.
Figshare hosts the datasets which show the train/val/tests splits used.
Cite items from this project
3D Printing in Medicine
3D-Printed Materials and Systems
Abhandlungen aus dem Mathematischen Seminar der Universität Hamburg