1 code implementation • 11 Apr 2024 • Marc Aubreville, Jonathan Ganz, Jonas Ammeling, Christopher C. Kaltenecker, Christof A. Bertram
The QUILT-1M dataset is the first openly available dataset containing images harvested from various online sources.
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 • 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.
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 • 26 Sep 2023 • Andreas Haghofer, Eda Parlak, Alexander Bartel, Taryn A. Donovan, Charles-Antoine Assenmacher, Pompei Bolfa, Michael J. Dark, Andrea Fuchs-Baumgartinger, Andrea Klang, Kathrin Jäger, Robert Klopfleisch, Sophie Merz, Barbara Richter, F. Yvonne Schulman, Jonathan Ganz, Josef Scharinger, Marc Aubreville, Stephan M. Winkler, Matti Kiupel, Christof A. Bertram
Algorithmic morphometry was compared with karyomegaly estimates by 11 pathologists, manual nuclear morphometry of 12 cells by 9 pathologists, and the mitotic count as a benchmark.
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 • 1 Jun 2023 • Pablo Pernias, Dominic Rampas, Mats L. Richter, Christopher J. Pal, Marc Aubreville
This highly compressed representation of an image provides much more detailed guidance compared to latent representations of language and this significantly reduces the computational requirements to achieve state-of-the-art results.
no code implementations • CVPR 2023 • Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, Ali Emre Kavur, Oldřich Kodym, Michal Kozubek, Jianning Li, Hongwei Li, Jun Ma, Carlos Martín-Isla, Bjoern Menze, Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patiño, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin Van Wijnen, Martin Wagner, Donglai Wei, Amine Yamlahi, Moi Hoon Yap, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, Jihoon Cho, Chanyeol Choi, Qi Dou, Ivan Ezhov, Christoph M. Friedrich, Clifton Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García Faura, Maria Grammatikopoulou, SeulGi Hong, Mostafa Jahanifar, Ikbeom Jang, Abdolrahim Kadkhodamohammadi, Inha Kang, Florian Kofler, Satoshi Kondo, Hugo Kuijf, Mingxing Li, Minh Huan Luu, Tomaž Martinčič, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, Subeen Pang, Jinah Park, Sung-Hong Park, Szymon Płotka, Elodie Puybareau, Nasir Rajpoot, Kanghyun Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Štepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Helene Urien, João L. Vilaça, Kareem Abdul Wahid, Haojie Wang, Jiacheng Wang, Liansheng Wang, Xiyue Wang, Benedikt Wiestler, Marek Wodzinski, Fangfang Xia, Juanying Xie, Zhiwei Xiong, Sen yang, Yanwu Yang, Zixuan Zhao, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein
The "typical" lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning.
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.
4 code implementations • 14 Nov 2022 • Dominic Rampas, Pablo Pernias, Marc Aubreville
Recent advancements in the domain of text-to-image synthesis have culminated in a multitude of enhancements pertaining to quality, fidelity, and diversity.
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.
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 • 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.
1 code implementation • 24 Aug 2020 • Marc Aubreville, Christof A. Bertram, Taryn A. Donovan, Christian Marzahl, Andreas Maier, Robert Klopfleisch
We achieved a mean F1-score of 0. 791 on the test set and of up to 0. 696 on a human breast cancer dataset.
1 code implementation • 10 Jul 2020 • Christof A. Bertram, Mitko Veta, Christian Marzahl, Nikolas Stathonikos, Andreas Maier, Robert Klopfleisch, Marc Aubreville
To date, some datasets on mitotic figures are available and were used for development of promising deep learning-based algorithms.
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.
1 code implementation • 13 Apr 2020 • Christian Marzahl, Christof A. Bertram, Marc Aubreville, Anne Petrick, Kristina Weiler, Agnes C. Gläsel, Marco Fragoso, Sophie Merz, Florian Bartenschlager, Judith Hoppe, Alina Langenhagen, Anne Jasensky, Jörn Voigt, Robert Klopfleisch, Andreas Maier
However, a significant percentage of the deliberately introduced false labels was not identified by the experts.
Human-Computer Interaction Image and Video Processing
no code implementations • 28 Jan 2020 • Hendrik Schröter, Tobias Rosenkranz, Alberto N. Escalante B., Marc Aubreville, Andreas Maier
To improve monaural speech enhancement in noisy environments, we propose CLCNet, a framework based on complex valued linear coding.
no code implementations • 25 Nov 2019 • Marc Aubreville, Christof A. Bertram, Samir Jabari, Christian Marzahl, Robert Klopfleisch, Andreas Maier
We were able to show that domain adversarial training considerably improves accuracy when applying mitotic figure classification learned from the canine on the human data sets (up to +12. 8% in accuracy) and is thus a helpful method to transfer knowledge from existing data sets to new tissue types and species.
2 code implementations • 12 Aug 2019 • Christian Marzahl, Marc Aubreville, Christof A. Bertram, Jason Stayt, Anne-Katherine Jasensky, Florian Bartenschlager, Marco Fragoso-Garcia, Ann K. Barton, Svenja Elsemann, Samir Jabari, Jens Krauth, Prathmesh Madhu, Jörn Voigt, Jenny Hill, Robert Klopfleisch, Andreas Maier
Additionally, we evaluated object detection methods on a novel data set of 17 completely annotated cytology whole slide images (WSI) containing 78, 047 hemosiderophages.
no code implementations • 24 Feb 2019 • Marc Aubreville, Miguel Goncalves, Christian Knipfer, Nicolai Oetter, Helmut Neumann, Florian Stelzle, Christopher Bohr, Andreas Maier
Squamous Cell Carcinoma (SCC) is the most common cancer type of the epithelium and is often detected at a late stage.
1 code implementation • 12 Feb 2019 • Marc Aubreville, Christof A. Bertram, Christian Marzahl, Corinne Gurtner, Martina Dettwiler, Anja Schmidt, Florian Bartenschlager, Sophie Merz, Marco Fragoso, Olivia Kershaw, Robert Klopfleisch, Andreas Maier
Manual count of mitotic figures, which is determined in the tumor region with the highest mitotic activity, is a key parameter of most tumor grading schemes.
no code implementations • 22 Oct 2018 • Marc Aubreville, Christof A. Bertram, Robert Klopfleisch, Andreas Maier
For both approaches, the CNN performs a segmentation of the WSI to assess mitotic activity.
no code implementations • 1 Oct 2018 • Marc Aubreville, Christof A. Bertram, Robert Klopfleisch, Andreas Maier
This map is in a second step used to construct a mitotic activity estimate.
1 code implementation • 7 Feb 2018 • Marc Aubreville, Christof Bertram, Robert Klopfleisch, Andreas Maier
It provides single-click annotations as well as a blind mode for multi-annotations, where the expert is directly shown the microscopy image containing the cells that he has not yet rated.
no code implementations • 3 Nov 2017 • Maike P. Stoeve, Marc Aubreville, Nicolai Oetter, Christian Knipfer, Helmut Neumann, Florian Stelzle, Andreas Maier
Confocal Laser Endomicroscopy (CLE), an optical imaging technique allowing non-invasive examination of the mucosa on a (sub)cellular level, has proven to be a valuable diagnostic tool in gastroenterology and shows promising results in various anatomical regions including the oral cavity.
no code implementations • 26 Jul 2017 • Marc Aubreville, Maximilian Krappmann, Christof Bertram, Robert Klopfleisch, Andreas Maier
The algorithm is able to derive the cell class (mitotic tumor cells, non-mitotic tumor cells and granulocytes) and their position within an image.
no code implementations • 25 Jul 2017 • Marc Aubreville, Miguel Goncalves, Christian Knipfer, Nicolai Oetter, Tobias Wuerfl, Helmut Neumann, Florian Stelzle, Christopher Bohr, Andreas Maier
We find that the network trained on the oral cavity data reaches an accuracy of 89. 45% and an area-under-the-curve (AUC) value of 0. 955, when applied on the vocal cords data.
no code implementations • 5 Mar 2017 • Marc Aubreville, Christian Knipfer, Nicolai Oetter, Christian Jaremenko, Erik Rodner, Joachim Denzler, Christopher Bohr, Helmut Neumann, Florian Stelzle, Andreas Maier
For this work, CLE image sequences (7894 images) from patients diagnosed with OSCC were obtained from 4 specific locations in the oral cavity, including the OSCC lesion.