4 papers
Practical sensorless aberration estimation for 3D microscopy with deep learning
Debayan Saha, Uwe Schmidt, Qinrong Zhang +6
Estimation of optical aberrations from volumetric intensity images is a key step in sensorless adaptive optics for 3D microscopy. Recent approaches based on deep learning promise a…
An interpretable automated detection system for FISH-based HER2 oncogene amplification testing in histo-pathological routine images of breast and gastric cancer diagnostics
Sarah Schmell, Falk Zakrzewski, Walter de Back +10
Histo-pathological diagnostics are an inherent part of the everyday work but are particularly laborious and associated with time-consuming manual analysis of image data. In order t…
Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy
Martin Weigert, Uwe Schmidt, Robert Haase +2
Accurate detection and segmentation of cell nuclei in volumetric (3D) fluorescence microscopy datasets is an important step in many biomedical research projects. Although many auto…
Cell Detection with Star-convex Polygons
Uwe Schmidt, Martin Weigert, Coleman Broaddus +1
Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications. Recent successful learning-based approaches include per…