96 citations · 128 across the 4 of their papers we have counts for
5 papers
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data
Christoph Reich, Tim Prangemeier, Özdemir Cetin +1
Convolutional neural networks (CNNs) are the current state-of-the-art meta-algorithm for volumetric segmentation of medical data, for example, to localize COVID-19 infected tissue…
Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
Christoph Reich, Tim Prangemeier, Christian Wildner +1
Time-lapse fluorescent microscopy (TLFM) combined with predictive mathematical modelling is a powerful tool to study the inherently dynamic processes of life on the single-cell lev…
Generation and Simulation of Yeast Microscopy Imagery with Deep Learning
Christoph Reich
Time-lapse fluorescence microscopy (TLFM) is an important and powerful tool in synthetic biological research. Modeling TLFM experiments based on real data may enable researchers to…
Attention-Based Transformers for Instance Segmentation of Cells in Microstructures
Tim Prangemeier, Christoph Reich, Heinz Koeppl
Detecting and segmenting object instances is a common task in biomedical applications. Examples range from detecting lesions on functional magnetic resonance images, to the detecti…
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning
Tim Prangemeier, Christian Wildner, André O. Françani +2
Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data. The challenge is exasperated in the setting of microstructured envi…