23 citations · 39 across the 8 of their papers we have counts for
10 papers
Annotated Biomedical Video Generation using Denoising Diffusion Probabilistic Models and Flow Fields
Rüveyda Yilmaz, Dennis Eschweiler, Johannes Stegmaier
The segmentation and tracking of living cells play a vital role within the biomedical domain, particularly in cancer research, drug development, and developmental biology. These ar…
Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation
Yuli Wu, Weidong He, Dennis Eschweiler +5
Modern biomedical image analysis using deep learning often encounters the challenge of limited annotated data. To overcome this issue, deep generative models can be employed to syn…
Denoising Diffusion Probabilistic Models for Generation of Realistic Fully-Annotated Microscopy Image Data Sets
Dennis Eschweiler, Rüveyda Yilmaz, Matisse Baumann +5
Recent advances in computer vision have led to significant progress in the generation of realistic image data, with denoising diffusion probabilistic models proving to be a particu…
Semi- and Self-Supervised Multi-View Fusion of 3D Microscopy Images using Generative Adversarial Networks
Canyu Yang, Dennis Eschweiler, Johannes Stegmaier
Recent developments in fluorescence microscopy allow capturing high-resolution 3D images over time for living model organisms. To be able to image even large specimens, techniques…
3D fluorescence microscopy data synthesis for segmentation and benchmarking
Dennis Eschweiler, Malte Rethwisch, Mareike Jarchow +2
Automated image processing approaches are indispensable for many biomedical experiments and help to cope with the increasing amount of microscopy image data in a fast and reproduci…
Robust 3D Cell Segmentation: Extending the View of Cellpose
Dennis Eschweiler, Richard S. Smith, Johannes Stegmaier
Increasing data set sizes of 3D microscopy imaging experiments demand for an automation of segmentation processes to be able to extract meaningful biomedical information. Due to th…
Spherical Harmonics for Shape-Constrained 3D Cell Segmentation
Dennis Eschweiler, Malte Rethwisch, Simon Koppers +1
Recent microscopy imaging techniques allow to precisely analyze cell morphology in 3D image data. To process the vast amount of image data generated by current digitized imaging te…
CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANs
Dennis Bähr, Dennis Eschweiler, Anuk Bhattacharyya +3
Automatic analysis of spatio-temporal microscopy images is inevitable for state-of-the-art research in the life sciences. Recent developments in deep learning provide powerful tool…
Algorithms used for the Cell Segmentation Benchmark Competition at ISBI 2019 by RWTH-GE
Dennis Eschweiler, Johannes Stegmaier
The presented algorithms for segmentation and tracking follow a 3-step approach where we detect, track and finally segment nuclei. In the preprocessing phase, we detect centroids o…
CNN-based Preprocessing to Optimize Watershed-based Cell Segmentation in 3D Confocal Microscopy Images
Dennis Eschweiler, Thiago V. Spina, Rohan C. Choudhury +3
The quantitative analysis of cellular membranes helps understanding developmental processes at the cellular level. Particularly 3D microscopic image data offers valuable insights i…