1.7k citations · 2.5k across the 12 of their papers we have counts for
3 papers · 1 filter
Self-supervised dense representation learning for live-cell microscopy with time arrow prediction
Benjamin Gallusser, Max Stieber, Martin Weigert
State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. H…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
Organelle-specific segmentation, spatial analysis, and visualization of volume electron microscopy datasets
Andreas Müller, Deborah Schmidt, Lucas Rieckert +2
Volume electron microscopy is the method of choice for the in-situ interrogation of cellular ultrastructure at the nanometer scale. Recent technical advances have led to a rapid in…