no code implementations • 26 Mar 2024 • Rüveyda Yilmaz, Dennis Eschweiler, Johannes Stegmaier
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.
no code implementations • 7 Mar 2024 • Yuli Wu, Julian Wittmann, Peter Walter, Johannes Stegmaier
However, the information transmission between the camera and retinal cells is often limited by the low resolution of the electrode array and the lack of specificity for different ganglion cell types, resulting in suboptimal stimulations.
no code implementations • 17 Jan 2024 • Raphael van Kempen, Tim Rehbronn, Abin Jose, Johannes Stegmaier, Bastian Lampe, Timo Woopen, Lutz Eckstein
Our findings demonstrate that our novel method, involving temporal offset augmentation through randomized frame skipping in sequences, enhances object detection accuracy compared to both the baseline model (Pillar-based Object Detection) and no augmentation.
no code implementations • 9 Nov 2023 • Yuli Wu, Weidong He, Dennis Eschweiler, Ningxin Dou, Zixin Fan, Shengli Mi, Peter Walter, Johannes Stegmaier
Modern biomedical image analysis using deep learning often encounters the challenge of limited annotated data.
1 code implementation • 9 Sep 2023 • Long Chen, Yuli Wu, Johannes Stegmaier, Dorit Merhof
Designing metrics for evaluating instance segmentation revolves around comprehensively considering object detection and segmentation accuracy.
no code implementations • 11 May 2023 • Firas Khader, Jakob Nikolas Kather, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn
However, while the conventional transformer allows for a simultaneous processing of a large set of input tokens, the computational demand scales quadratically with the number of input tokens and thus quadratically with the number of image patches.
no code implementations • 11 May 2023 • Firas Khader, Gustav Müller-Franzes, Tianyu Han, Sven Nebelung, Christiane Kuhl, Johannes Stegmaier, Daniel Truhn
X-rays are widely available and even if the CT reconstructed from these radiographs is not a replacement of a complete CT in the diagnostic setting, it might serve to spare the patients from radiation where a CT is only acquired for rough measurements such as determining organ size.
no code implementations • 7 Feb 2023 • Yuli Wu, Ivan Karetic, Johannes Stegmaier, Peter Walter, Dorit Merhof
The pre-trained retinal implant model is also a U-Net, which is trained to mimic the biomimetic perceptual model implemented in pulse2percept.
1 code implementation • 2 Jan 2023 • Dennis Eschweiler, Rüveyda Yilmaz, Matisse Baumann, Ina Laube, Rijo Roy, Abin Jose, Daniel Brückner, Johannes Stegmaier
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.
1 code implementation • 18 Dec 2022 • Firas Khader, Gustav Mueller-Franzes, Tianci Wang, Tianyu Han, Soroosh Tayebi Arasteh, Christoph Haarburger, Johannes Stegmaier, Keno Bressem, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
Multimodal deep learning has been used to predict clinical endpoints and diagnoses from clinical routine data.
1 code implementation • 7 Nov 2022 • Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baessler, Sebastian Foersch, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn
Furthermore, we demonstrate that synthetic images can be used in a self-supervised pre-training and improve the performance of breast segmentation models when data is scarce (dice score 0. 91 vs. 0. 95 without vs. with synthetic data).
no code implementations • 5 Aug 2021 • Canyu Yang, Dennis Eschweiler, Johannes Stegmaier
Recent developments in fluorescence microscopy allow capturing high-resolution 3D images over time for living model organisms.
1 code implementation • 21 Jul 2021 • Dennis Eschweiler, Malte Rethwisch, Mareike Jarchow, Simon Koppers, Johannes Stegmaier
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.
1 code implementation • 3 May 2021 • 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.
no code implementations • 23 Oct 2020 • Dennis Eschweiler, Malte Rethwisch, Simon Koppers, Johannes Stegmaier
Recent microscopy imaging techniques allow to precisely analyze cell morphology in 3D image data.
no code implementations • 22 Oct 2020 • Dennis Bähr, Dennis Eschweiler, Anuk Bhattacharyya, Daniel Moreno-Andrés, Wolfram Antonin, Johannes Stegmaier
Automatic analysis of spatio-temporal microscopy images is inevitable for state-of-the-art research in the life sciences.
1 code implementation • 10 Feb 2020 • Tobias Brudermueller, Dennis L. Shung, Adrian J. Stanley, Johannes Stegmaier, Smita Krishnaswamy
We show the utility of our pipeline on a network that is trained on biomedical data.
1 code implementation • 30 Jan 2020 • Sourabh Bhide, Ralf Mikut, Maria Leptin, Johannes Stegmaier
Current in vivo microscopy allows us detailed spatiotemporal imaging (3D+t) of complete organisms and offers insights into their development on the cellular level.
no code implementations • 1 Oct 2019 • 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.
no code implementations • 15 Apr 2019 • Dennis Eschweiler, Johannes Stegmaier
The presented algorithms for segmentation and tracking follow a 3-step approach where we detect, track and finally segment nuclei.
no code implementations • 16 Oct 2018 • Dennis Eschweiler, Thiago V. Spina, Rohan C. Choudhury, Elliot Meyerowitz, Alexandre Cunha, Johannes Stegmaier
The quantitative analysis of cellular membranes helps understanding developmental processes at the cellular level.
no code implementations • 19 Jun 2018 • Nadezhda Prodanova, Johannes Stegmaier, Stephan Allgeier, Sebastian Bohn, Oliver Stachs, Bernd Köhler, Ralf Mikut, Andreas Bartschat
Transfer learning is a powerful tool to adapt trained neural networks to new tasks.
no code implementations • 26 Oct 2017 • Thiago V. Spina, Johannes Stegmaier, Alexandre X. Falcão, Elliot Meyerowitz, Alexandre Cunha
SEGMENT3D is a comprehensive application that can be applied to other 3D imaging modalities and general objects.
no code implementations • 18 Oct 2017 • Johannes Stegmaier, Thiago V. Spina, Alexandre X. Falcão, Andreas Bartschat, Ralf Mikut, Elliot Meyerowitz, Alexandre Cunha
Automated segmentation approaches are crucial to quantitatively analyze large-scale 3D microscopy images.
no code implementations • 11 Apr 2017 • Ralf Mikut, Andreas Bartschat, Wolfgang Doneit, Jorge Ángel González Ordiano, Benjamin Schott, Johannes Stegmaier, Simon Waczowicz, Markus Reischl
The decision to a Matlab-based solution was made to use the wide mathematical functionality of this package provided by The Mathworks Inc. SciXMiner is controlled by a graphical user interface (GUI) with menu items and control elements like popup lists, checkboxes and edit elements.
no code implementations • 17 Feb 2017 • Julian Arz, Peter Sanders, Johannes Stegmaier, Ralf Mikut
Cell nuclei segmentation is one of the most important tasks in the analysis of biomedical images.
no code implementations • 30 Aug 2016 • Johannes Stegmaier
Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions.
no code implementations • 3 Aug 2016 • Johannes Stegmaier, Ralf Mikut
The general concept introduced in this contribution represents a new approach to efficiently exploit prior knowledge to improve the result quality of image analysis pipelines.
no code implementations • 17 Apr 2016 • Johannes Stegmaier, Julian Arz, Benjamin Schott, Jens C. Otte, Andrei Kobitski, G. Ulrich Nienhaus, Uwe Strähle, Peter Sanders, Ralf Mikut
Systematic validation is an essential part of algorithm development.
no code implementations • 9 Feb 2016 • Benjamin Schott, Johannes Stegmaier, Masanari Takamiya, Ralf Mikut
The described framework can be used to gain knowledge out of object databases in many different fields.