Search Results for author: Pavel Tomancak

Found 4 papers, 4 papers with code

Embedding-based Instance Segmentation in Microscopy

1 code implementation25 Jan 2021 Manan Lalit, Pavel Tomancak, Florian Jug

Automatic detection and segmentation of objects in 2D and 3D microscopy data is important for countless biomedical applications.

Instance Segmentation Semantic Segmentation

Leveraging Self-supervised Denoising for Image Segmentation

1 code implementation27 Nov 2019 Mangal Prakash, Tim-Oliver Buchholz, Manan Lalit, Pavel Tomancak, Florian Jug, Alexander Krull

Deep learning (DL) has arguably emerged as the method of choice for the detection and segmentation of biological structures in microscopy images.

Denoising Semantic Segmentation

Fully Unsupervised Probabilistic Noise2Void

1 code implementation27 Nov 2019 Mangal Prakash, Manan Lalit, Pavel Tomancak, Alexander Krull, Florian Jug

Image denoising is the first step in many biomedical image analysis pipelines and Deep Learning (DL) based methods are currently best performing.

Image Denoising

scenery -- Flexible Virtual Reality Visualisation on the Java VM

2 code implementations16 Jun 2019 Ulrik Günther, Tobias Pietzsch, Aryaman Gupta, Kyle I. S. Harrington, Pavel Tomancak, Stefan Gumhold, Ivo F. Sbalzarini

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.


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