1.7k citations
- Technische Universität DresdenDE86 papers
- Max Planck Institute for the Physics of Complex SystemsDE66 papers
- Max Planck Institute of Molecular Cell Biology and GeneticsDE64 papers
- Physics of LifeDE46 papers
- Centre National de la Recherche ScientifiqueFR16 papers
- Sorbonne UniversitéFR11 papers
- Université Paris Sciences et LettresFR9 papers
- Biotechnologisches ZentrumDE8 papers
- Dresden Center for Computational Materials ScienceDE7 papers
- Institut CurieFR7 papers
- Physique des Cellules et CancersFR7 papers
- Princeton UniversityUS7 papers
6 papers · 1 filter
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
A robustness measure for singular point and index estimation in discretized orientation and vector fields
Karl B. Hoffmann, Ivo F. Sbalzarini
The identification of singular points or topological defects in discretized vector fields occurs in diverse areas ranging from the polarization of the cosmic microwave background t…
Noise2Void - Learning Denoising from Single Noisy Images
Alexander Krull, Tim-Oliver Buchholz, Florian Jug
The field of image denoising is currently dominated by discriminative deep learning methods that are trained on pairs of noisy input and clean target images. Recently it has been s…
Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data
Tim-Oliver Buchholz, Mareike Jordan, Gaia Pigino +1
Multiple approaches to use deep learning for image restoration have recently been proposed. Training such approaches requires well registered pairs of high and low quality images.…
Cell Detection with Star-convex Polygons
Uwe Schmidt, Martin Weigert, Coleman Broaddus +1
Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications. Recent successful learning-based approaches include per…
Particle methods enable fast and simple approximation of Sobolev gradients in image segmentation
Ivo F. Sbalzarini, Sophie Schneider, Janick Cardinale
Bio-image analysis is challenging due to inhomogeneous intensity distributions and high levels of noise in the images. Bayesian inference provides a principled way for regularizing…