no code implementations • 12 Jan 2023 • Ivan Ezhov, Luca Giannoni, Suprosanna Shit, Frederic Lange, Florian Kofler, Bjoern Menze, Ilias Tachtsidis, Daniel Rueckert
In this article, we perform a statistical analysis of the brain tumor patients' HSI scans from the HELICoiD dataset with the aim of identifying the correlation between reflectance spectra and absorption spectra of tissue chromophores.
no code implementations • 3 Dec 2022 • Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit, Johannes Paetzold, Tamaz Amiranashvili, JianGuo Zhang, Daniel Rueckert, Juan Eugenio Iglesias, Benedikt Wiestler, Bjoern Menze
We find that in the natural image domain, CSR behaves on par with the supervised one on several perceptual tests as a metric, and in the medical domain, CSR better quantifies perceptual similarity concerning the experts' ratings.
1 code implementation • 28 Nov 2022 • Nico Stucki, Johannes C. Paetzold, Suprosanna Shit, Bjoern Menze, Ulrich Bauer
In this work, we propose the first topologically and feature-wise accurate metric and loss function for supervised image segmentation, which we term Betti matching.
1 code implementation • 22 Aug 2022 • Rajat Koner, Tanveer Hannan, Suprosanna Shit, Sahand Sharifzadeh, Matthias Schubert, Thomas Seidl, Volker Tresp
We propose three novel components to model short-term and long-term dependency and temporal coherence.
Ranked #1 on
Video Instance Segmentation
on Youtube-VIS 2022 Validation
(using extra training data)
1 code implementation • 21 Jul 2022 • Bastian Wittmann, Fernando Navarro, Suprosanna Shit, Bjoern Menze
Detection Transformers represent end-to-end object detection approaches based on a Transformer encoder-decoder architecture, exploiting the attention mechanism for global relation modeling.
1 code implementation • 17 May 2022 • Florian Kofler, Suprosanna Shit, Ivan Ezhov, Lucas Fidon, Izabela Horvath, Rami Al-Maskari, Hongwei Li, Harsharan Bhatia, Timo Loehr, Marie Piraud, Ali Erturk, Jan Kirschke, Jan Peeken, Tom Vercauteren, Claus Zimmer, Benedikt Wiestler, Bjoern Menze
Blob loss is designed for semantic segmentation problems in which the instances are the connected components within a class.
no code implementations • 17 May 2022 • Florian Kofler, Ivan Ezhov, Lucas Fidon, Izabela Horvath, Ezequiel de la Rosa, John LaMaster, Hongwei Li, Tom Finck, Suprosanna Shit, Johannes Paetzold, Spyridon Bakas, Marie Piraud, Jan Kirschke, Tom Vercauteren, Claus Zimmer, Benedikt Wiestler, Bjoern Menze
To approximate human quality ratings on scarce expert data, we train surrogate quality estimation models.
1 code implementation • 19 Mar 2022 • Suprosanna Shit, Rajat Koner, Bastian Wittmann, Johannes Paetzold, Ivan Ezhov, Hongwei Li, Jiazhen Pan, Sahand Sharifzadeh, Georgios Kaissis, Volker Tresp, Bjoern Menze
We leverage direct set-based object prediction and incorporate the interaction among the objects to learn an object-relation representation jointly.
no code implementations • 1 Mar 2022 • Fernando Navarro, Guido Sasahara, Suprosanna Shit, Ivan Ezhov, Jan C. Peeken, Stephanie E. Combs, Bjoern H. Menze
Automatic localization and segmentation of organs-at-risk (OAR) in CT are essential pre-processing steps in medical image analysis tasks, such as radiation therapy planning.
1 code implementation • 24 Dec 2021 • Lucas Fidon, Suprosanna Shit, Ivan Ezhov, Johannes C. Paetzold, Sébastien Ourselin, Tom Vercauteren
Importantly, we explore the inclusion of a transformer in the bottleneck of the U-Net architecture.
no code implementations • 16 Nov 2021 • Leon Mächler, Ivan Ezhov, Florian Kofler, Suprosanna Shit, Johannes C. Paetzold, Timo Loehr, Benedikt Wiestler, Bjoern Menze
We propose a simple new aggregation strategy for federated learning that won the MICCAI Federated Tumor Segmentation Challenge 2021 (FETS), the first ever challenge on Federated Learning in the Machine Learning community.
1 code implementation • 7 Nov 2021 • Ivan Ezhov, Kevin Scibilia, Katharina Franitza, Felix Steinbauer, Suprosanna Shit, Lucas Zimmer, Jana Lipkova, Florian Kofler, Johannes Paetzold, Luca Canalini, Diana Waldmannstetter, Martin Menten, Marie Metz, Benedikt Wiestler, Bjoern Menze
Current treatment planning of patients diagnosed with a brain tumor, such as glioma, could significantly benefit by accessing the spatial distribution of tumor cell concentration.
2 code implementations • 3 Nov 2021 • Lucas Fidon, Michael Aertsen, Suprosanna Shit, Philippe Demaerel, Sébastien Ourselin, Jan Deprest, Tom Vercauteren
Label-set loss functions allow to train deep neural networks with partially segmented images, i. e. segmentations in which some classes may be grouped into super-classes.
no code implementations • 3 Sep 2021 • Suprosanna Shit, Ivan Ezhov, Leon Mächler, Abinav R., Jana Lipkova, Johannes C. Paetzold, Florian Kofler, Marie Piraud, Bjoern H. Menze
In this paper, we propose a neural solver to learn an optimal iterative scheme in a data-driven fashion for any class of PDEs.
1 code implementation • 30 Aug 2021 • Johannes C. Paetzold, Julian McGinnis, Suprosanna Shit, Ivan Ezhov, Paul Büschl, Chinmay Prabhakar, Mihail I. Todorov, Anjany Sekuboyina, Georgios Kaissis, Ali Ertürk, Stephan Günnemann, Bjoern H. Menze
Moreover, we benchmark numerous state-of-the-art graph learning algorithms on the biologically relevant tasks of vessel prediction and vessel classification using the introduced vessel graph dataset.
1 code implementation • CVPR 2021 • Suprosanna Shit, Johannes C. Paetzold, Anjany Sekuboyina, Ivan Ezhov, Alexander Unger, Andrey Zhylka, Josien P. W. Pluim, Ulrich Bauer, Bjoern H. Menze
Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research.
no code implementations • 14 May 2021 • Fernando Navarro, Christopher Watanabe, Suprosanna Shit, Anjany Sekuboyina, Jan C. Peeken, Stephanie E. Combs, Bjoern H. Menze
Self-supervision has demonstrated to be an effective learning strategy when training target tasks on small annotated data-sets.
no code implementations • 22 Apr 2021 • Izabela Horvath, Johannes C. Paetzold, Oliver Schoppe, Rami Al-Maskari, Ivan Ezhov, Suprosanna Shit, Hongwei Li, Ali Ertuerk, Bjoern H. Menze
Novel multimodal imaging methods are capable of generating extensive, super high resolution datasets for preclinical research.
no code implementations • 10 Mar 2021 • Florian Kofler, Ivan Ezhov, Fabian Isensee, Fabian Balsiger, Christoph Berger, Maximilian Koerner, Beatrice Demiray, Julia Rackerseder, Johannes Paetzold, Hongwei Li, Suprosanna Shit, Richard McKinley, Marie Piraud, Spyridon Bakas, Claus Zimmer, Nassir Navab, Jan Kirschke, Benedikt Wiestler, Bjoern Menze
It is often unclear how to optimize abstract metrics, such as human expert perception, in convolutional neural network (CNN) training.
no code implementations • 4 Mar 2021 • Fabian Balsiger, Alain Jungo, Naren Akash R J, Jianan Chen, Ivan Ezhov, Shengnan Liu, Jun Ma, Johannes C. Paetzold, Vishva Saravanan R, Anjany Sekuboyina, Suprosanna Shit, Yannick Suter, Moshood Yekini, Guodong Zeng, Markus Rempfler
With this growth, however, come new challenges for the community.
1 code implementation • 29 Oct 2020 • Kelly Payette, Priscille de Dumast, Hamza Kebiri, Ivan Ezhov, Johannes C. Paetzold, Suprosanna Shit, Asim Iqbal, Romesa Khan, Raimund Kottke, Patrice Grehten, Hui Ji, Levente Lanczi, Marianna Nagy, Monika Beresova, Thi Dao Nguyen, Giancarlo Natalucci, Theofanis Karayannis, Bjoern Menze, Meritxell Bach Cuadra, Andras Jakab
It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders.
no code implementations • 22 Sep 2020 • Amirhossein Bayat, Suprosanna Shit, Adrian Kilian, Jürgen T. Liechtenstein, Jan S. Kirschke, Bjoern H. Menze
The first subnetwork is designed to complete the shape of the downsampled defective skull.
1 code implementation • 8 Aug 2020 • Hongwei Li, Aurore Menegaux, Benita Schmitz-Koep, Antonia Neubauer, Felix JB Bäuerlein, Suprosanna Shit, Christian Sorg, Bjoern Menze, Dennis Hedderich
In the last two decades, neuroscience has produced intriguing evidence for a central role of the claustrum in mammalian forebrain structure and function.
no code implementations • 10 Jul 2020 • Stefan Gerl, Johannes C. Paetzold, Hailong He, Ivan Ezhov, Suprosanna Shit, Florian Kofler, Amirhossein Bayat, Giles Tetteh, Vasilis Ntziachristos, Bjoern Menze
Raster-scan optoacoustic mesoscopy (RSOM) is a powerful, non-invasive optical imaging technique for functional, anatomical, and molecular skin and tissue analysis.
1 code implementation • 22 Apr 2020 • Ahmad B Qasim, Ivan Ezhov, Suprosanna Shit, Oliver Schoppe, Johannes C. Paetzold, Anjany Sekuboyina, Florian Kofler, Jana Lipkova, Hongwei Li, Bjoern Menze
Exploiting learning algorithms under scarce data regimes is a limitation and a reality of the medical imaging field.
2 code implementations • 13 Apr 2020 • Rajat Koner, Suprosanna Shit, Volker Tresp
In this work, we propose a novel transformer formulation for scene graph generation and relation prediction.
3 code implementations • 16 Mar 2020 • Suprosanna Shit, Johannes C. Paetzold, Anjany Sekuboyina, Ivan Ezhov, Alexander Unger, Andrey Zhylka, Josien P. W. Pluim, Ulrich Bauer, Bjoern H. Menze
Accurate segmentation of tubular, network-like structures, such as vessels, neurons, or roads, is relevant to many fields of research.
1 code implementation • MIDL 2019 • Ahmad B Qasim, Ivan Ezhov, Suprosanna Shit, Oliver Schoppe, Johannes Paetzold, Anjany Sekuboyina, Florian Kofler, Jana Lipkova, Hongwei Li, Bjoern Menze
Exploiting learning algorithms under scarce data regimes is a limitation and a reality of the medical imaging field.
2 code implementations • 24 Jan 2020 • Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat, Maximilian Löffler, Hans Liebl, Hongwei Li, Giles Tetteh, Jan Kukačka, Christian Payer, Darko Štern, Martin Urschler, Maodong Chen, Dalong Cheng, Nikolas Lessmann, Yujin Hu, Tianfu Wang, Dong Yang, Daguang Xu, Felix Ambellan, Tamaz Amiranashvili, Moritz Ehlke, Hans Lamecker, Sebastian Lehnert, Marilia Lirio, Nicolás Pérez de Olaguer, Heiko Ramm, Manish Sahu, Alexander Tack, Stefan Zachow, Tao Jiang, Xinjun Ma, Christoph Angerman, Xin Wang, Kevin Brown, Alexandre Kirszenberg, Élodie Puybareau, Di Chen, Yiwei Bai, Brandon H. Rapazzo, Timyoas Yeah, Amber Zhang, Shangliang Xu, Feng Hou, Zhiqiang He, Chan Zeng, Zheng Xiangshang, Xu Liming, Tucker J. Netherton, Raymond P. Mumme, Laurence E. Court, Zixun Huang, Chenhang He, Li-Wen Wang, Sai Ho Ling, Lê Duy Huynh, Nicolas Boutry, Roman Jakubicek, Jiri Chmelik, Supriti Mulay, Mohanasankar Sivaprakasam, Johannes C. Paetzold, Suprosanna Shit, Ivan Ezhov, Benedikt Wiestler, Ben Glocker, Alexander Valentinitsch, Markus Rempfler, Björn H. Menze, Jan S. Kirschke
Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel-level by a human-machine hybrid algorithm (https://osf. io/nqjyw/, https://osf. io/t98fz/).
no code implementations • 8 Oct 2019 • Suprosanna Shit, Abinav Ravi Venkatakrishnan, Ivan Ezhov, Jana Lipkova, Marie Piraud, Bjoern Menze
The existing implicit schemes are usually iterative and employ a general-purpose solver which may be sub-optimal for a specific class of PDEs.
1 code implementation • 14 Aug 2019 • Fernando Navarro, Suprosanna Shit, Ivan Ezhov, Johannes Paetzold, Andrei Gafita, Jan Peeken, Stephanie Combs, Bjoern Menze
Multi-organ segmentation in whole-body computed tomography (CT) is a constant pre-processing step which finds its application in organ-specific image retrieval, radiotherapy planning, and interventional image analysis.
no code implementations • 1 Jul 2019 • Ivan Ezhov, Jana Lipkova, Suprosanna Shit, Florian Kofler, Nore Collomb, Benjamin Lemasson, Emmanuel Barbier, Bjoern Menze
In this work, we propose a learning-based technique for the estimation of tumor growth model parameters from medical scans.
6 code implementations • 13 Jan 2019 • Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivantik, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yu, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern Menze
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018.