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Found 10 papers, 3 papers with code
Annotated Biomedical Video Generation using Denoising Diffusion Probabilistic Models and Flow Fields
It is composed of a denoising diffusion probabilistic model (DDPM) generating high-fidelity synthetic cell microscopy images and a flow prediction model (FPM) predicting the non-rigid transformation between consecutive video frames.
Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation
Modern biomedical image analysis using deep learning often encounters the challenge of limited annotated data.
Denoising Diffusion Probabilistic Models for Generation of Realistic Fully-Annotated Microscopy Image Data Sets
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 particularly effective method.
Semi- and Self-Supervised Multi-View Fusion of 3D Microscopy Images using Generative Adversarial Networks
Recent developments in fluorescence microscopy allow capturing high-resolution 3D images over time for living model organisms.
3D fluorescence microscopy data synthesis for segmentation and benchmarking
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 reproducible way.
Robust 3D Cell Segmentation: Extending the View of Cellpose
Increasing data set sizes of 3D microscopy imaging experiments demand for an automation of segmentation processes to be able to extract meaningful biomedical information.
Spherical Harmonics for Shape-Constrained 3D Cell Segmentation
Recent microscopy imaging techniques allow to precisely analyze cell morphology in 3D image data.
CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANs
Automatic analysis of spatio-temporal microscopy images is inevitable for state-of-the-art research in the life sciences.
Algorithms used for the Cell Segmentation Benchmark Competition at ISBI 2019 by RWTH-GE
The presented algorithms for segmentation and tracking follow a 3-step approach where we detect, track and finally segment nuclei.
CNN-based Preprocessing to Optimize Watershed-based Cell Segmentation in 3D Confocal Microscopy Images
The quantitative analysis of cellular membranes helps understanding developmental processes at the cellular level.
