no code implementations • 21 Mar 2024 • Mathias Öttl, Siyuan Mei, Frauke Wilm, Jana Steenpass, Matthias Rübner, Arndt Hartmann, Matthias Beckmann, Peter Fasching, Andreas Maier, Ramona Erber, Katharina Breininger
However, there is a notable lack of analysis and discussions on the differences between diffusion segmentation and image generation, and thorough evaluations are missing that distinguish the improvements these architectures provide for segmentation in general from their benefit for diffusion segmentation specifically.
no code implementations • 21 Mar 2024 • Mathias Öttl, Frauke Wilm, Jana Steenpass, Jingna Qiu, Matthias Rübner, Arndt Hartmann, Matthias Beckmann, Peter Fasching, Andreas Maier, Ramona Erber, Bernhard Kainz, Katharina Breininger
Specifically, we utilize 1) a style conditioning mechanism which allows to inject style information of previously unseen images during image generation and 2) a content conditioning which can be targeted to a downstream task, e. g., layout for segmentation.
no code implementations • 19 Mar 2024 • Jonathan Ganz, Jonas Ammeling, Samir Jabari, Katharina Breininger, Marc Aubreville
We predicted the source patient of a slide with F1 scores of 50. 16 % and 52. 30 % on the LSCC and LUAD datasets, respectively, and with 62. 31 % on our meningioma dataset.
no code implementations • 13 Feb 2024 • Frauke Wilm, Jonas Ammeling, Mathias Öttl, Rutger H. J. Fick, Marc Aubreville, Katharina Breininger
Previous works showed that the trained network layers differ in their susceptibility to this domain shift, e. g., shallow layers are more affected than deeper layers.
no code implementations • 2 Jan 2024 • Chloé Puget, Jonathan Ganz, Julian Ostermaier, Thomas Konrad, Eda Parlak, Christof Albert Bertram, Matti Kiupel, Katharina Breininger, Marc Aubreville, Robert Klopfleisch
This project aimed at training deep learning models (DLMs) to identify the c-Kit-11 mutational status of MCTs solely based on morphology without additional molecular analysis.
no code implementations • 25 Dec 2023 • Luis Carlos Rivera Monroy, Leonhard Rist, Martin Eberhardt, Christian Ostalecki, Andreas Bauer, Julio Vera, Katharina Breininger, Andreas Maier
This study leverages graph neural networks to integrate MELC data with Radiomic-extracted features for melanoma classification, focusing on cell-wise analysis.
no code implementations • 15 Nov 2023 • Jonas Ammeling, Moritz Hecker, Jonathan Ganz, Taryn A. Donovan, Christof A. Bertram, Katharina Breininger, Marc Aubreville
The volume-corrected mitotic index (M/V-Index) was shown to provide prognostic value in invasive breast carcinomas.
no code implementations • 13 Nov 2023 • Marc Aubreville, Zhaoya Pan, Matti Sievert, Jonas Ammeling, Jonathan Ganz, Nicolai Oetter, Florian Stelzle, Ann-Kathrin Frenken, Katharina Breininger, Miguel Goncalves
This method is, in itself, an oversampling procedure, which has a relatively low sensitivity compared to the definitive tissue analysis on paraffin-embedded sections.
1 code implementation • 6 Oct 2023 • Glejdis Shkëmbi, Johanna P. Müller, Zhe Li, Katharina Breininger, Peter Schüffler, Bernhard Kainz
Breast cancer is a major concern for women's health globally, with axillary lymph node (ALN) metastasis identification being critical for prognosis evaluation and treatment guidance.
no code implementations • 27 Sep 2023 • Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan, Robert Klopfleisch, Jonathan Ganz, Jonas Ammeling, Frauke Wilm, Mitko Veta, Samir Jabari, Markus Eckstein, Jonas Annuscheit, Christian Krumnow, Engin Bozaba, Sercan Cayir, Hongyan Gu, Xiang 'Anthony' Chen, Mostafa Jahanifar, Adam Shephard, Satoshi Kondo, Satoshi Kasai, Sujatha Kotte, VG Saipradeep, Maxime W. Lafarge, Viktor H. Koelzer, Ziyue Wang, Yongbing Zhang, Sen yang, Xiyue Wang, Katharina Breininger, Christof A. Bertram
The challenge provided annotated histologic tumor images from six different domains and evaluated the algorithmic approaches for mitotic figure detection provided by nine challenge participants on ten independent domains.
no code implementations • 3 Aug 2023 • Jonas Utz, Tobias Weise, Maja Schlereth, Fabian Wagner, Mareike Thies, Mingxuan Gu, Stefan Uderhardt, Katharina Breininger
We show that this increases coherence between generated images and cycled masks and evaluate synthetic datasets on a downstream nuclei segmentation task.
1 code implementation • 14 Jul 2023 • Jingna Qiu, Frauke Wilm, Mathias Öttl, Maja Schlereth, Chang Liu, Tobias Heimann, Marc Aubreville, Katharina Breininger
We find that the efficiency of this method highly depends on the choice of AL step size (i. e., the combination of region size and the number of selected regions per WSI), and a suboptimal AL step size can result in redundant annotation requests or inflated computation costs.
1 code implementation • 11 Jan 2023 • Frauke Wilm, Marco Fragoso, Christof A. Bertram, Nikolas Stathonikos, Mathias Öttl, Jingna Qiu, Robert Klopfleisch, Andreas Maier, Katharina Breininger, Marc Aubreville
Additionally, to quantify the inherent scanner-induced domain shift, we train a tumor segmentation network on each scanner subset and evaluate the performance both in- and cross-domain.
1 code implementation • 15 Dec 2022 • Jonas Ammeling, Lars-Henning Schmidt, Jonathan Ganz, Tanja Niedermair, Christoph Brochhausen-Delius, Christian Schulz, Katharina Breininger, Marc Aubreville
Attention-based multiple instance learning (AMIL) algorithms have proven to be successful in utilizing gigapixel whole-slide images (WSIs) for a variety of different computational pathology tasks such as outcome prediction and cancer subtyping problems.
no code implementations • 15 Dec 2022 • Jonathan Ganz, Karoline Lipnik, Jonas Ammeling, Barbara Richter, Chloé Puget, Eda Parlak, Laura Diehl, Robert Klopfleisch, Taryn A. Donovan, Matti Kiupel, Christof A. Bertram, Katharina Breininger, Marc Aubreville
Nucleolar organizer regions (NORs) are parts of the DNA that are involved in RNA transcription.
1 code implementation • 12 Dec 2022 • Marc Aubreville, Jonathan Ganz, Jonas Ammeling, Taryn A. Donovan, Rutger H. J. Fick, Katharina Breininger, Christof A. Bertram
In this work, we perform, for the first time, automatic subtyping of mitotic figures into normal and atypical categories according to characteristic morphological appearances of the different phases of mitosis.
no code implementations • 29 Nov 2022 • Frauke Wilm, Marco Fragoso, Christof A. Bertram, Nikolas Stathonikos, Mathias Öttl, Jingna Qiu, Robert Klopfleisch, Andreas Maier, Marc Aubreville, Katharina Breininger
Computer-aided systems in histopathology are often challenged by various sources of domain shift that impact the performance of these algorithms considerably.
no code implementations • 11 Nov 2022 • Mathias Öttl, Jana Mönius, Matthias Rübner, Carol I. Geppert, Jingna Qiu, Frauke Wilm, Arndt Hartmann, Matthias W. Beckmann, Peter A. Fasching, Andreas Maier, Ramona Erber, Katharina Breininger
We show the suitability of Generative Adversarial Networks (GANs) and especially diffusion models to create realistic images based on subtype-conditioning for the use case of HER2-stained histopathology.
no code implementations • 10 Nov 2022 • Luis Carlos Rivera Monroy, Leonhard Rist, Martin Eberhardt, Christian Ostalecki, Andreas Baur, Julio Vera, Katharina Breininger, Andreas Maier
For this reason, computer-assisted approaches have gained popularity and shown promising results in tasks such as segmentation and classification of skin disorders.
no code implementations • 15 Sep 2022 • Stefan Ploner, Siyu Chen, Jungeun Won, Lennart Husvogt, Katharina Breininger, Julia Schottenhamml, James Fujimoto, Andreas Maier
Optical coherence tomography (OCT) is a micrometer-scale, volumetric imaging modality that has become a clinical standard in ophthalmology.
no code implementations • 24 Jun 2022 • Kubilay Can Demir, Matthias May, Axel Schmid, Michael Uder, Katharina Breininger, Tobias Weise, Andreas Maier, Seung Hee Yang
This paper presents a new multimodal interventional radiology dataset, called PoCaP (Port Catheter Placement) Corpus.
no code implementations • 6 Apr 2022 • Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas Maier, Jack Breen, Nishant Ravikumar, Youjin Chung, Jinah Park, Ramin Nateghi, Fattaneh Pourakpour, Rutger H. J. Fick, Saima Ben Hadj, Mostafa Jahanifar, Nasir Rajpoot, Jakob Dexl, Thomas Wittenberg, Satoshi Kondo, Maxime W. Lafarge, Viktor H. Koelzer, Jingtang Liang, YuBo Wang, Xi Long, Jingxin Liu, Salar Razavi, April Khademi, Sen yang, Xiyue Wang, Mitko Veta, Katharina Breininger
The goal of the MICCAI MIDOG 2021 challenge has been to propose and evaluate methods that counter this domain shift and derive scanner-agnostic mitosis detection algorithms.
no code implementations • Rheumatology (Oxford) 2022 • Lukas Folle, Sara Bayat, Arnd Kleyer, Filippo Fagni, Lorenz A Kapsner, Maja Schlereth, Timo Meinderink, Katharina Breininger, Koray Tacilar, Gerhard Krönke, Michael Uder, Michael Sticherling, Sebastian Bickelhaupt, Georg Schett, Andreas Maier, Frank Roemer, David Simon
AUROC was 75% for seropositive RA vs. PsA, 74% for seronegative RA vs. PsA and 67% for seropositive vs. seronegative RA.
no code implementations • 8 Feb 2022 • Felix Denzinger, Michael Wels, Oliver Taubmann, Mehmet A. Gülsün, Max Schöbinger, Florian André, Sebastian J. Buss, Johannes Görich, Michael Sühling, Andreas Maier, Katharina Breininger
With coronary artery disease (CAD) persisting to be one of the leading causes of death worldwide, interest in supporting physicians with algorithms to speed up and improve diagnosis is high.
1 code implementation • 27 Jan 2022 • Frauke Wilm, Marco Fragoso, Christian Marzahl, Jingna Qiu, Chloé Puget, Laura Diehl, Christof A. Bertram, Robert Klopfleisch, Andreas Maier, Katharina Breininger, Marc Aubreville
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging.
no code implementations • 27 Jan 2022 • Maja Schlereth, Daniel Stromer, Katharina Breininger, Alexandra Wagner, Lina Tan, Andreas Maier, Ferdinand Knieling
Neuromuscular diseases (NMDs) cause a significant burden for both healthcare systems and society.
no code implementations • 25 Jan 2022 • Maja Schlereth, Daniel Stromer, Yash Mantri, Jason Tsujimoto, Katharina Breininger, Andreas Maier, Caesar Anderson, Pranav S. Garimella, Jesse V. Jokerst
We conclude that deep learning-supported analysis of non-invasive ultrasound images is a promising area of research to automatically extract cross-sectional wound size and depth information with potential value in monitoring response to therapy.
no code implementations • 19 Jan 2022 • Mathias Öttl, Jana Mönius, Christian Marzahl, Matthias Rübner, Carol I. Geppert, Arndt Hartmann, Matthias W. Beckmann, Peter Fasching, Andreas Maier, Ramona Erber, Katharina Breininger
When evaluating the approaches on fully manually annotated images, we observe that the autoencoder-based superpixels achieve a 23% increase in boundary F1 score compared to the baseline SLIC superpixels.
no code implementations • 5 Nov 2021 • Sonja Kunzmann, Christian Marzahl, Felix Denzinger, Christof A. Bertram, Robert Klopfleisch, Katharina Breininger, Vincent Christlein, Andreas Maier
Annotating data, especially in the medical domain, requires expert knowledge and a lot of effort.
no code implementations • 25 Aug 2021 • Frauke Wilm, Christian Marzahl, Katharina Breininger, Marc Aubreville
This work presents a mitotic figure detection algorithm developed as a baseline for the challenge, based on domain adversarial training.
1 code implementation • 19 Aug 2021 • Christian Marzahl, Jenny Hill, Jason Stayt, Dorothee Bienzle, Lutz Welker, Frauke Wilm, Jörn Voigt, Marc Aubreville, Andreas Maier, Robert Klopfleisch, Katharina Breininger, Christof A. Bertram
Pulmonary hemorrhage (P-Hem) occurs among multiple species and can have various causes.
1 code implementation • MICCAI Workshop COMPAY 2021 • Christian Marzahl, Frauke Wilm, Christine Kröger, Franz F Dressler, Lars Tharun, Sven Perner, Christof Bertram, Jörn Voigt, Robert Klopfleisch, Andreas Maier, Marc Aubreville, Katharina Breininger
The registration of whole slide images (WSIs) provides the basis for many subsequent processing steps in digital pathology.
1 code implementation • MICCAI Workshop COMPAY 2021 • Jonathan Ganz, Tobias Kirsch, Lucas Hoffmann, Christof A. Bertram, Christoph Hoffmann, Andreas Maier, Katharina Breininger, Ingmar Blümcke, Samir Jabari, Marc Aubreville
In a first approach, image patches are sampled from this region and regression is based on morphological features encoded by a ResNet-based network.
2 code implementations • 30 Mar 2021 • Marc Aubreville, Christof Bertram, Mitko Veta, Robert Klopfleisch, Nikolas Stathonikos, Katharina Breininger, Natalie ter Hoeve, Francesco Ciompi, Andreas Maier
Hypothesizing that the scanner device plays a decisive role in this effect, we evaluated the susceptibility of a standard mitosis detection approach to the domain shift introduced by using a different whole slide scanner.
no code implementations • 13 Jan 2021 • Christian Marzahl, Christof A. Bertram, Frauke Wilm, Jörn Voigt, Ann K. Barton, Robert Klopfleisch, Katharina Breininger, Andreas Maier, Marc Aubreville
We evaluated our pipeline in a cross-validation setup with a fixed training set using a dataset of six equine WSIs of which four are partially annotated and used for training, and two fully annotated WSI are used for validation and testing.
2 code implementations • 5 Jan 2021 • Christof A. Bertram, Taryn A. Donovan, Marco Tecilla, Florian Bartenschlager, Marco Fragoso, Frauke Wilm, Christian Marzahl, Katharina Breininger, Andreas Maier, Robert Klopfleisch, Marc Aubreville
For this study, we created the first open source data-set with 19, 983 annotations of BiNC and 1, 416 annotations of MuNC in 32 histological whole slide images of ccMCT.
no code implementations • 4 Dec 2020 • Frauke Wilm, Christof A. Bertram, Christian Marzahl, Alexander Bartel, Taryn A. Donovan, Charles-Antoine Assenmacher, Kathrin Becker, Mark Bennett, Sarah Corner, Brieuc Cossic, Daniela Denk, Martina Dettwiler, Beatriz Garcia Gonzalez, Corinne Gurtner, Annika Lehmbecker, Sophie Merz, Stephanie Plog, Anja Schmidt, Rebecca C. Smedley, Marco Tecilla, Tuddow Thaiwong, Katharina Breininger, Matti Kiupel, Andreas Maier, Robert Klopfleisch, Marc Aubreville
Density of mitotic figures in histologic sections is a prognostically relevant characteristic for many tumours.
no code implementations • 5 Oct 2020 • Felix Denzinger, Michael Wels, Katharina Breininger, Mehmet A. Gülsün, Max Schöbinger, Florian André, Sebastian Buß, Johannes Görich, Michael Sühling, Andreas Maier
Coronary CT angiography (CCTA) has established its role as a non-invasive modality for the diagnosis of coronary artery disease (CAD).
2 code implementations • 30 Apr 2020 • Christian Marzahl, Marc Aubreville, Christof A. Bertram, Jennifer Maier, Christian Bergler, Christine Kröger, Jörn Voigt, Katharina Breininger, Robert Klopfleisch, Andreas Maier
In many research areas, scientific progress is accelerated by multidisciplinary access to image data and their interdisciplinary annotation.
no code implementations • 13 Dec 2019 • Felix Denzinger, Michael Wels, Katharina Breininger, Anika Reidelshöfer, Joachim Eckert, Michael Sühling, Axel Schmermund, Andreas Maier
Analysing coronary artery plaque segments with respect to their functional significance and therefore their influence to patient management in a non-invasive setup is an important subject of current research.
no code implementations • 12 Dec 2019 • Felix Denzinger, Michael Wels, Nishant Ravikumar, Katharina Breininger, Anika Reidelshöfer, Joachim Eckert, Michael Sühling, Axel Schmermund, Andreas Maier
A second approach is based on deep learning and relies on centerline extraction as sole prerequisite.
no code implementations • 19 Nov 2019 • Bernhard Stimpel, Christopher Syben, Tobias Würfl, Katharina Breininger, Philipp Hoelter, Arnd Dörfler, Andreas Maier
Additionally, a weighting scheme in the loss computation that favors high-frequency structures is proposed to focus on the important details and contours in projection imaging.
no code implementations • 6 Nov 2019 • Weilin Fu, Katharina Breininger, Zhaoya Pan, Andreas Maier
Results show that for retinal vessel segmentation on DRIVE database, U-Net does not degenerate until surprisingly acute conditions: one level, one filter in convolutional layers, and one training sample.
no code implementations • 14 Jul 2019 • Weilin Fu, Katharina Breininger, Roman Schaffert, Nishant Ravikumar, Andreas Maier
We start with a high-performance U-Net and show by step-by-step conversion that we are able to divide the network into modules of known operators.
no code implementations • 30 Apr 2018 • Tobias Geimer, Paul Keall, Katharina Breininger, Vincent Caillet, Michelle Dunbar, Christoph Bert, Andreas Maier
Data-driven respiratory signal extraction from rotational X-ray scans is a challenge as angular effects overlap with respiration-induced change in the scene.
no code implementations • 11 Apr 2018 • Bernhard Stimpel, Christopher Syben, Tobias Würfl, Katharina Breininger, Katrin Mentl, Jonathan M. Lommen, Arnd Dörfler, Andreas Maier
Our approach is capable of creating X-ray projection images with natural appearance.
1 code implementation • 15 Feb 2018 • Aline Sindel, Katharina Breininger, Johannes Käßer, Andreas Hess, Andreas Maier, Thomas Köhler
We customize features suitable for volumetric MRI to train the random forest and propose a median tree ensemble for robust regression.
no code implementations • 9 Nov 2017 • Weilin Fu, Katharina Breininger, Tobias Würfl, Nishant Ravikumar, Roman Schaffert, Andreas Maier
In this paper, we reformulate the conventional 2-D Frangi vesselness measure into a pre-weighted neural network ("Frangi-Net"), and illustrate that the Frangi-Net is equivalent to the original Frangi filter.
no code implementations • 17 Oct 2017 • Christopher Syben, Bernhard Stimpel, Katharina Breininger, Tobias Würfl, Rebecca Fahrig, Arnd Dörfler, Andreas Maier
In this paper, we present substantial evidence that a deep neural network will intrinsically learn the appropriate way to discretize the ideal continuous reconstruction filter.