Marek Wodzinski - HES SO Valais Publications

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Vorname(n):	Marek
Nachname(n):	Wodzinski

Lasse Hansen, Wiebke Heyer, Christoph Grossbröhmer, Frederic Madesta, Thilo Sentker, Wang Jiazheng, Yuxi Zhang, Hang Zhang, Min Liu, Junyi Wang, Xi Zhu, Yuhua Li, Liwen Wang, Daniil Morozov, Nazim Houachine, Joel Honkamaa, Pekka Marttinen, Yichao Zhou, Zuopeng Tan, Zhuoyuan Wang, Yi Wang, Hongchao Zhou, Shunbo Hu, Yi Zhang, Qian Tao, Lukas Förner, Thomas Wendler, Bailiang Jian, Christian Wachinger, Jin Kim, Dan Ruan, Marek Wodzinski, Henning Müller, Tony Chi Wing Mok, Xi Jia, Jinming Duan, Mikael Brudfors, Seyed-Ahmad Ahmadi, Yunzheng Zhu, William Hsu, Tina Kapur, William M. Wells, Alexandra Golby, Aaron Carass, Harrison Bai, Yihao Liu, Perrine Paul-Gilloteaux, Joakim Lindblad, Natasa Sladoje, Andreas Walter, Junyu Chen, Reuben Dorent, Alessa Hering und Mattias Heinrich, Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges (2025), in: Hansen et al. 2025 / Melba Journal - Machine Learning for Biomedical Imaging, Volume 3

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Myrthe Buser, Dominique C. Simons, Matthijs Fitski, Marc H. W. A. Wijnen, Annemieke S. Littooij, Annemiek H. ter Brugge, Iris N. Vos, Markus H. A. Janse, Mathijs de Boer, Junya Sato, Shoji Kido, Satoshi Kondo, Marek Wodzinski, Henning Müller, Jin Ye, Junjun He, Yannick Kirchhoff, Maximilian R. Rokkus, Gao Haokai, Matias Fernandez-Paton, Diana Viaga-Canuto, David G. Ellis, Michele R. Aizenberg, Bas H. M. van der Velden, Hugo Kuijf, Alberto de Luca und Alida F. W. van der Steeg, Automated segmentation of pediatric neuroblastoma on multi-modal MRI: Results of the SPPIN challenge at MICCAI 2023, MDPI Bioengineering, 2025 (2025), in: MDPI Bioengineering, nov. 25

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Henning Müller und Marek Wodzinski, Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge (2025), in: Arxiv

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Lasse Hansen, Christian Wachinger, Marek Wodzinski, Henning Müller, Mikael Brudfors, William M. Wells, Aaron Carass, Reuben Dorent, Alessa Hering und Mattias Heinrich, Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges (2025), in: Melba, Volume 3(775-791)

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Henning Müller und Marek Wodzinski, Automated segmentation of pediatric neuroblastoma on multi-modal (2025), in: MDPI Bioengineering

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Henning Müller, Marek Wodzinski, Rina Bao, David G. Ellis und Michele R. Aizenberg, BONBID-HIE 2023: Lesion Segmentation Challenge in BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy (2025), in: Publimed

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Artur Jurgas, Marek Wodzinski, Marina D’Amato, Jeroen van der Laak, Manfredo Atzori und Henning Müller, Improving quality control of whole slide images by explicit artifact augmentation (2024), in: Scientific Reports, 14:1(17847)

Niccolò Marini, Stefano marchesin, Lluis Borràs Ferrís, Simon Püttmann, Marek Wodzinski, Riccardo Fratti, Damian Podareanu, Alessandro Caputo, Svetla Boytcheva, Simona Vatrano und others, Automatic labels are as effective as manual labels in digital pathology images classification with deep learning (2025), in: Journal of Pathology Informatics(100462)

Marek Wodzinski und Henning Müller, 3-D Image-to-Image Fusion in Lightsheet Microscopy by Two-Step Adversarial Network: Contribution to the Fusemycells Challenge (2025), in: 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)

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Marek Wodzinski und Henning Müller, Automatic Multi-structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures (2025), in: Supervised and Semi-supervised Multi-structure Segmentation and Landmark Detection in Dental Data (MICCAI 2024), 15571(63-71)

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Federico Bolelli, Luca Lumetti, Lisheng Wang, Marek Wodzinski, Henning Müller, Klaus Maier-Hain, Bram van Ginneken und Costantino Grana, Segmenting the Inferior Alveolar Canal in CBCTs Volumes: The ToothFairy Challenge (2025), in: IEEE Transactions on Medical Imaging, Volume 44, Issue : 4, Arpil 2025(1890-1906)

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Marek Wodzinski und Henning Müller, Patch-Based Encoder-Decoder Architecture for Automatic Transmitted Light to Fluorescence Imaging Transition: Contribution to the LightMyCells Challenge (2024), in: (pre-print)

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Marek Wodzinski, Niccolò Marini, Manfredo Atzori und Henning Müller, RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge (2024), in: Computer Methods and Programs in Biomedicine

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Philippe Weitz, Masi Valkonen, Leslie Solorzano, Circe Carr, Kimmo Kartasalo, Constance Boissin, Sonja Koivukoski, Aino Kuusela, Dusan Rasic, Yanbo Feng, Sandra Sinius Pouplier, Abhinav Sharma, Kajsa Ledesma Eriksson, Stephanie Robertson, Christian Marzahl, Chandler D. Gatenbee, Alexander R. A. Anderson, Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller, Daniel Budelmann, Nick Weiss, Stefan Heldmann, Johannes Lotz, Jelmer M. Wolterink, Bruno De Santi, Abhijeet Patil, Amit Sethi, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Mahtab Farrokh, Neeraj Kumar, Russell Greiner, Leena Latonen, Anne-Vibeke Laenkholm, Johan Hartman, Pekka Ruusuvuori und Mattias Rantalainen, The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue (2024), in: Medical Image Analysis

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Niccolò Marini, Stefano marchesin, Marek Wodzinski, Alessandro Caputo, Damian Podareanu, Bryan Cardenas Guevara, Svetla Boytcheva, Simona Vatrano, Filippo Fraggetta, Francesco Ciompi, Gianmaria Silvello, Henning Müller und Manfredo Atzori, Multimodal Representations of Biomedical Knowledge from Limited Training Whole Slide Images and Reports using Deep Learning (2024), in: Medical Image Analysis

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Weronika Celniak, Marek Wodzinski, Artur Jurgas, Silvia Burti, Alessandro Zotti, Manfredo Atzori, Henning Müller und Tommaso Banzato, Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models (2023), in: Sci Rep:Article number: 19518 (2023)

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Tommaso Banzato, Marek Wodzinski, Silvia Burti, Eleonora Vettore, Henning Müller und Alessandro Zotti, An AI-based algorithm for the automatic evaluation of image quality in canine thoracic radiographs (2023), in: Springer Nature Limited

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Many Others, Marek Wodzinski und And Even More, Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning (2023), in: IEEE Transactions on Medical Imaging, 42:3

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Marek Wodzinski, Mateusz Daniol, Miroslaw Socha, Daria Hemmerling, Maciej Stanuch und Andrzej Skalski, Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling (2022), in: Computer Methods and Programs in Biomedicine, 226

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Carlotta Valente, Marek Wodzinski, Carlo Guglielmini, Helen Poser, David Chiavegato, Alessandro Zotti, Roberto Venturini und Tommaso Banzato, Development of an artificial intelligence-based method for the diagnosis of the severity of myxomatous mitral valve disease from canine chest radiographs (2023), in: Frontiers in Veterinary Science

Marek Wodzinski, Mateusz Daniol, Daria Hemmerling und Miroslaw Socha, High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers, in: MICCAI 2023, 2023

Jianning Li, David G. Ellis, Oldřich Kodym, Laurel Rauschenbach, Christoph Rieß, Ulrich Sure, Karsten H. Wrede, Carlos M. Alvarez, Marek Wodzinski, Mateusz Daniol, Daria Hemmerling, Hamza Mahdi, Allison Clement, Evan Kim, Zachary Fishman, Cari M. Whyne, James G. Mainprize, Michael R. Hardisty, Shashwat Pathak, Chitimireddy Sindhura, Rama Krishna Sai S. Gorthi, Degala Venkata Kiran, Subrahmanyam Gorthi, Bokai Yang, Ke Fang, Xingyu Li, Artem Kroviakov, Lei Yu, Yuan Jin, Antonio Pepe, Christina Gsaxner, Adam Herout, Victor Alves, Michal Španěl, Michele R. Aizenberg, Jens Kleesiek und Jan Egger, Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge (2023), in: Medical Image Analysis, 88

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Kamil Kwarciak und Marek Wodzinski, Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects, in: ICCV 2023 Proceedings, 2023

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Artur Jurgas, Marek Wodzinski, Weronika Celniak, Manfredo Atzori und Henning Müller, Artifact Augmentation for Learning-based Quality Control of Whole Slide Images, in: EMBC, Sydney, Australia, 2023

Artur Jurgas, Marek Wodzinski und Henning Müller, Robust Multiresolution and Multistain Background Segmentation in Whole Slide Images, in: PCBBE, Lodz, Poland, 2023

Vincent Andrearczyk, Luis Schiappacasse, Daniel Abler, Marek Wodzinski, Andreas Hottinger, Matthieu Raccaud, Jean Bourhis, John O. Prior, Vincent Dunet und Adrien Depeursinge, Automatic Detection and Multi-Component Segmentation of Brain Metastases in Longitudinal MRI (2024), in: Nature Scientic Reports, 14:1(1-10)

Niccolò Marini, Sebastian Otalora, Marek Wodzinski, Selene Tomassini, Aldo Franco Dragoni, Stéphane Marchand-Maillet, Juan Pedro Dominguez Morales, Lourdes Duran-Lopez, Simona Vatrano, Henning Müller und others, Data-driven color augmentation for H\&E stained images in computational pathology (2023), in: Journal of Pathology Informatics(100183)

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 Rätsch, 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 Plotka, 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-Hain, Paul F. Jäger, Annette Kopp-Schneider und Lena Maier-Hein, Why is the winner the best?, in: CVPR, 2023

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Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori und Henning Müller, Unsupervised Deep Network for Large Deformations followed by Instance Optimization and Objective Function Weighting by Inverse Consistency: Contribution to the BraTS-Reg Challenge, in: MICCAI BrainLes workshop, 2022

Niccolò Marini, Stefano marchesin, Sebastian Otalora, Marek Wodzinski, Alessandro Caputo, mert van Rijthoven, Witali Aswolinskiy, John Melle Bokhorst, Damian Podareanu, Edyta Petters, Svetla Boytcheva, Genziana Buttafuoco, Simona Valtrano, Filippo Fraggetta, Uulke A. van der Heide, Maristella Agosti, Francesco Ciompi, Gianmaria Silvello, Henning Müller und Manfredo Atzori, Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations (2022), in: Nature Partner Journal on Digital Medicine

Niccolò Marini, Marek Wodzinski, Manfredo Atzori und Henning Müller, A multi-task Multiple Instance Learning algorithm to analyze large whole slide images from the BRIGHT challenge 2022, in: ISBI Challenges 2022, Bangalore India, 2022

Tommaso Banzato, Marek Wodzinski, Federico tauceri, Chiara Dona, Filippo Scavazza, Henning Müller und Alessandro Zotti, An AI-based algorithm for the automatic classification of thoracic radiographs in cats (2021), in: Frontiers in Veterinary science

Marek Wodzinski und Henning Müller, InvNet: A Deep Learning Approach to Invert Complex Deformation Fields, in: ISBI, Nice, France, 2021

Marek Wodzinski und Henning Müller, DeepHistReg: Unsupervised Deep Learning Registration Framework for Differently Stained Histology Samples (2021), in: Computer Methods and Programs in Biomedicine

[]: IF 2018: 4.260

Marek Wodzinski, Tommaso Banzato, Manfredo Atzori, Vincent Andrearczyk, Yashin Dicente Cid und Henning Müller, Training a deep neural network for small and highly heterogeneous MRID datasets for cancer grading, in: EMBC Conference, IEEE, 2020

Marek Wodzinski und Henning Müller, Unsupervised Learning-based non-rigid registration of high resolution histology images, in: MICCAI workshop on Machine Learning in Medical Imaging, Springer, 2020

Marek Wodzinski und Henning Müller, Learning-Based Affine Registration of Histological Images, in: International Workshop on Biomedical Image Registration, Springer, Seiten 12--22, 2020

Marek Wodzinski, Tommaso Banzato, Manfredo Atzori, Vincent Andrearczyk, Yashin Dicente Cid und Henning Müller, Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading, in: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine \& Biology Society (EMBC), IEEE, Seiten 1758--1761, 2020

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