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Found 4 papers, 4 papers with code
Embedding-based Instance Segmentation in Microscopy
Automatic detection and segmentation of objects in 2D and 3D microscopy data is important for countless biomedical applications.
Fully Unsupervised Probabilistic Noise2Void
Image denoising is the first step in many biomedical image analysis pipelines and Deep Learning (DL) based methods are currently best performing.
Leveraging Self-supervised Denoising for Image Segmentation
Deep learning (DL) has arguably emerged as the method of choice for the detection and segmentation of biological structures in microscopy images.
scenery -- Flexible Virtual Reality Visualisation on the Java VM
Life science today involves computational analysis of a large amount and variety of data, such as volumetric data acquired by state-of-the-art microscopes, or mesh data resulting from analysis of such data or simulations.
Graphics
