The paper presents StarDist-3D, a deep learning method that segments 3D cell nuclei by predicting starlike polyhedra with only 96 radial distances per pixel and efficient non-maximum suppression.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy
The paper presents StarDist-3D, a deep learning method that segments 3D cell nuclei by predicting starlike polyhedra with only 96 radial distances per pixel and efficient non-maximum suppression.