23 citations · 110 across the 24 of their papers we have counts for
10 papers · 1 filter
Transformers for CT Reconstruction From Monoplanar and Biplanar Radiographs
Firas Khader, Gustav Müller-Franzes, Tianyu Han +4
Computed Tomography (CT) scans provide detailed and accurate information of internal structures in the body. They are constructed by sending x-rays through the body from different…
A Deep Learning-based in silico Framework for Optimization on Retinal Prosthetic Stimulation
Yuli Wu, Ivan Karetic, Johannes Stegmaier +2
We propose a neural network-based framework to optimize the perceptions simulated by the in silico retinal implant model pulse2percept. The overall pipeline consists of a trainable…
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…
Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Generation
Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh +12
Recent advances in computer vision have shown promising results in image generation. Diffusion probabilistic models in particular have generated realistic images from textual input…
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…
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…
Semi-Automatic Generation of Tight Binary Masks and Non-Convex Isosurfaces for Quantitative Analysis of 3D Biological Samples
Sourabh Bhide, Ralf Mikut, Maria Leptin +1
Current in vivo microscopy allows us detailed spatiotemporal imaging (3D+t) of complete organisms and offers insights into their development on the cellular level. Even though the…
Towards Automatic Embryo Staging in 3D+T Microscopy Images using Convolutional Neural Networks and PointNets
Manuel Traub, Johannes Stegmaier
Automatic analyses and comparisons of different stages of embryonic development largely depend on a highly accurate spatiotemporal alignment of the investigated data sets. In this…