Application of B-splines FFD image registration in breast cancer radiotherapy planning. - Marek Wodzinski; Andrzej Skalski; Piotr Kedzierawski; Tomasz Kuszewski (IWSSIP, 2017)

Application of demons image registration algorithms in resected breast cancer lodge localization. - Marek Wodzinski; Andrzej Skalski; Izabela Ciepiela; Tomasz Kuszewski; Piotr Kedzierawski (SPA, 2017)

Volume regularization in explicit image registration used for breast cancer bed localization. - Marek Wodzinski; Andrzej Skalski; Izabela Ciepiela; Tomasz Kuszewski; Piotr Kedzierawski (ISBI, 2018)

Artificial CT Data Generation Method with Known Ground-Truth for Image Registration with Missing Data. - Marek Wodzinski; Andrzej Skalski (IST, 2018)

Rigid Registration Method for Medical Volumes with Large Deformations and Missing Data. - Marek Wodzinski; Andrzej Skalski (IWSSIP, 2018)

Resection-Based Demons Regularization for Breast Tumor Bed Propagation. - Marek Wodzinski; Andrzej Skalski (RAMBO+BIA+TIA@MICCAI, 2018)

Deep Learning Approach to Parkinson's Disease Detection Using Voice Recordings and Convolutional Neural Network Dedicated to Image Classification. - Marek Wodzinski; Andrzej Skalski; Daria Hemmerling; Juan Rafael Orozco-Arroyave; Elmar Nöth (EMBC, 2019)

Convolutional Neural Network Approach to Classify Skin Lesions Using Reflectance Confocal Microscopy. - Marek Wodzinski; Andrzej Skalski; Alexander Witkowski; Giovanni Pellacani; Joanna Ludzik (EMBC, 2019)

Automatic Nonrigid Histological Image Registration with Adaptive Multistep Algorithm. - Marek Wodzinski; Andrzej Skalski (CoRR, 2019)

Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading. - Marek Wodzinski; Tommaso Banzato; Manfredo Atzori; Vincent Andrearczyk; Yashin Dicente Cid; Henning Müller (EMBC, 2020)

Automatic Quality Assessment of Reflectance Confocal Microscopy Mosaics using Attention-Based Deep Neural Network. - Marek Wodzinski; Miroslawa Pajak; Andrzej Skalski; Alexander Witkowski; Giovanni Pellacani; Joanna Ludzik (EMBC, 2020)

Multi-step, Learning-Based, Semi-supervised Image Registration Algorithm. - Marek Wodzinski (MICCAI (Challenges), 2020)

Unsupervised Learning-Based Nonrigid Registration of High Resolution Histology Images. - Marek Wodzinski; Henning Müller (MLMI@MICCAI, 2020)

Learning-Based Affine Registration of Histological Images. - Marek Wodzinski; Henning Müller (WBIR, 2020)

Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network. - Maciej Stanuch; Marek Wodzinski; Andrzej Skalski (Sensors, 2020)

ANHIR: Automatic Non-Rigid Histological Image Registration Challenge. - Jirí Borovec; Jan Kybic; Ignacio Arganda-Carreras; Dmitry V. Sorokin; Gloria Bueno; Alexander V. Khvostikov; Spyridon Bakas; Eric I-Chao Chang; Stefan Heldmann; Kimmo Kartasalo; Leena Latonen; Johannes Lotz 002; et al. (IEEE Trans. Medical Imaging, 2020)

Invnet: A Deep Learning Approach To Invert Complex Deformation Fields. - Marek Wodzinski; Henning Müller (ISBI, 2021)

Semi-supervised Multilevel Symmetric Image Registration Method for Magnetic Resonance Whole Brain Images. - Marek Wodzinski (MIDOG/MOOD/Learn2Reg@MICCAI, 2021)

Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets. - Marek Wodzinski; Mateusz Daniol; Daria Hemmerling (AutoImplant@MICCAI, 2021)

Adversarial Affine Registration for Real-Time Intraoperative Registration of 3-D US-US for Brain Shift Correction. - Marek Wodzinski; Andrzej Skalski (ASMUS@MICCAI, 2021)

DeepHistReg: Unsupervised Deep Learning Registration Framework for Differently Stained Histology Samples. - Marek Wodzinski; Henning Müller (Comput. Methods Programs Biomed., 2021)

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning. - Alessa Hering; Lasse Hansen; Tony C. W. Mok; Albert C. S. Chung; Hanna Siebert; Stephanie Häger; Annkristin Lange; Sven Kuckertz; Stefan Heldmann; Wei Shao 008; Sulaiman Vesal; Mirabela Rusu; et al. (CoRR, 2021)

Semi-Supervised Deep Learning-Based Image Registration Method with Volume Penalty for Real-Time Breast Tumor Bed Localization. - Marek Wodzinski; Izabela Ciepiela; Tomasz Kuszewski; Piotr Kedzierawski; Andrzej Skalski (Sensors, 2021)

Unsupervised Method for Intra-patient Registration of Brain Magnetic Resonance Images Based on Objective Function Weighting by Inverse Consistency: Contribution to the BraTS-Reg Challenge. - Marek Wodzinski; Artur Jurgas; Niccolò Marini; Manfredo Atzori; Henning Müller (BrainLes@MICCAI, 2022)

Deep learning-based framework for automatic cranial defect reconstruction and implant modeling. - Marek Wodzinski; Mateusz Daniol; Miroslaw Socha; Daria Hemmerling; Maciej Stanuch; Andrzej Skalski (Comput. Methods Programs Biomed., 2022)

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations. - Niccolò Marini; Stefano Marchesin 001; Sebastian Otálora; Marek Wodzinski; Alessandro Caputo; Mart van Rijthoven; Witali Aswolinskiy; John-Melle Bokhorst; Damian Podareanu; Edyta Petters; Svetla Boytcheva; Genziana Buttafuoco; et al. (npj Digit. Medicine, 2022)

Why is the Winner the Best? - 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; et al. (CVPR, 2023)

Vision Transformer for Parkinson's Disease Classification using Multilingual Sustained Vowel Recordings. - Daria Hemmerling; Marek Wodzinski; Juan Rafael Orozco-Arroyave; David Sztahó; Mateusz Daniol; Pawel Jemiolo; Magdalena Wójcik-Pedziwiatr (EMBC, 2023)

Artifact Augmentation for Learning-based Quality Control of Whole Slide Images. - Artur Jurgas; Marek Wodzinski; Weronika Celniak; Manfredo Atzori; Henning Müller (EMBC, 2023)

Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects. - Kamil Kwarciak; Marek Wodzinski (ICCV (Workshops), 2023)

High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers. - Marek Wodzinski; Mateusz Daniol; Daria Hemmerling; Miroslaw Socha (MICCAI (9), 2023)

Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge. - Marek Wodzinski; Henning Müller (SEG.A@MICCAI, 2023)

Improving Segmentation of Hypoxic Ischemic Encephalopathy Lesions by Heavy Data Augmentation: Contribution to the BONBID Challenge. - Marek Wodzinski; Henning Müller (BONBID-HIE@MICCAI, 2023)

Robust Multiresolution and Multistain Background Segmentation in Whole Slide Images. - Artur Jurgas; Marek Wodzinski; Manfredo Atzori; Henning Müller (PCBBE, 2023)

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA. - Kaiyuan Yang 003; Fabio Musio; Yihui Ma; Norman Juchler; Johannes C. Paetzold; Rami Al-Maskari; Luciano Höher; Hongwei Bran Li; Ibrahim Ethem Hamamci; Anjany Sekuboyina; Suprosanna Shit; Houjing Huang; et al. (CoRR, 2023)

DRU-Net: Pulmonary Artery Segmentation via Dense Residual U-Network with Hybrid Loss Function. - Manahil Zulfiqar; Maciej Stanuch; Marek Wodzinski; Andrzej Skalski (Sensors, 2023)

Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning. - Alessa Hering; Lasse Hansen; Tony C. W. Mok; Albert C. S. Chung; Hanna Siebert; Stephanie Häger; Annkristin Lange; Sven Kuckertz; Stefan Heldmann; Wei Shao 008; Sulaiman Vesal; Mirabela Rusu; et al. (IEEE Trans. Medical Imaging, 2023)

Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge. - Jianning Li 002; David G. Ellis; Oldrich Kodym; Laurèl Rauschenbach; Christoph Rieß; Ulrich Sure; Karsten H. Wrede; Carlos M. Alvarez; Marek Wodzinski; Mateusz Daniol; Daria Hemmerling; Hamza Mahdi; et al. (Medical Image Anal., 2023)

Unsupervised Skull Segmentation via Contrastive MR-to-CT Modality Translation. - Kamil Kwarciak; Mateusz Daniol; Daria Hemmerling; Marek Wodzinski (ACCV Workshops (1), 2024)

Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases. - Mateusz Daniol; Daria Hemmerling; Jakub Sikora; Pawel Jemiolo; Marek Wodzinski; Magdalena Wójcik-Pedziwiatr (EMBC, 2024)

Automatic Cranial Defect Reconstruction with Self-Supervised Deep Deformable Masked Autoencoders. - Marek Wodzinski; Daria Hemmerling; Mateusz Daniol (EMBC, 2024)

EsmTemp - Transfer Learning Approach for Predicting Protein Thermostability. - Adam Sulek; Jakub Jonczyk; Patryk Orzechowski; Ahmed Abdeen Hamed; Marek Wodzinski (ICCS (3), 2024)

Augmented Reality Platform for Neurological Evaluations. - Daria Hemmerling; Mateusz Daniol; Marek Wodzinski; Joanna Stepien; Pawel Jemiolo; Marta Kaczmarska; Jakub Kaminski; Magdalena Wójcik-Pedziwiatr (INI-DH@AVI, 2024)

Patch-Based Encoder-Decoder Architecture For Automatic Transmitted Light To Fluorescence Imaging Transition: Contribution To The Lightmycells Challenge. - Marek Wodzinski; Henning Müller (ISBI, 2024)

Benchmark of Deep Encoder-Decoder Architectures for Head and Neck Tumor Segmentation in Magnetic Resonance Images: Contribution to the HNTSMRG Challenge. - Marek Wodzinski (HNTS-MRG@MICCAI, 2024)

Automatic Multi-structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures. - Marek Wodzinski; Henning Müller (ToothFairy/3DTeethLand/STS@MICCAI, 2024)

Multimodal Approach for the Diagnosis of Neurodegenerative Disorders Using Augmented Reality. - Daria Hemmerling; Pawel Jemiolo; Mateusz Daniol; Marek Wodzinski; Jakub Kaminski; Magdalena Wójcik-Pedziwiatr (VR Workshops, 2024)

Automatic Registration of SHG and H&E Images with Feature-Based Initial Alignment and Intensity-Based Instance Optimization: Contribution to the COMULIS Challenge. - Marek Wodzinski; Henning Müller (WBIR, 2024)

Improving deep learning-based automatic cranial defect reconstruction by heavy data augmentation: From image registration to latent diffusion models. - Marek Wodzinski; Kamil Kwarciak; Mateusz Daniol; Daria Hemmerling (Comput. Biol. Medicine, 2024)

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

Deep Learning-Based Segmentation of Tumors in PET/CT Volumes: Benchmark of Different Architectures and Training Strategies. - Monika Górka; Daniel Jaworek; Marek Wodzinski (CoRR, 2024)

DeeperHistReg: Robust Whole Slide Images Registration Framework. - Marek Wodzinski; Niccolò Marini; Manfredo Atzori; Henning Müller (CoRR, 2024)

Improving Quality Control of Whole Slide Images by Explicit Artifact Augmentation. - Artur Jurgas; Marek Wodzinski; Marina D'Amato; Jeroen van der Laak; Manfredo Atzori; Henning Müller (CoRR, 2024)

Automatic Labels are as Effective as Manual Labels in Biomedical Images Classification with Deep Learning. - Niccolò Marini; Stefano Marchesin 001; Lluis Borras Ferris; Simon Püttmann; Marek Wodzinski; Riccardo Fratti; Damian Podareanu; Alessandro Caputo; Svetla Boytcheva; Simona Vatrano; Filippo Fraggetta; Iris Nagtegaal; et al. (CoRR, 2024)

Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning. - Niccolò Marini; Stefano Marchesin 001; Marek Wodzinski; Alessandro Caputo; Damian Podareanu; Bryan Cardenas Guevara; Svetla Boytcheva; Simona Vatrano; Filippo Fraggetta; Francesco Ciompi; Gianmaria Silvello; Henning Müller; et al. (Medical Image Anal., 2024)

The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue. - Philippe Weitz; Masi Valkonen; Leslie Solorzano; Circe Carr; Kimmo Kartasalo; Constance Boissin; Sonja Koivukoski; Aino Kuusela; Dusan Rasic; Yanbo Feng; Sandra Kristiane Sinius Pouplier; Abhinav Sharma; et al. (Medical Image Anal., 2024)

3-D Image-to-Image Fusion in Lightsheet Microscopy by Two-Step Adversarial Network: Contribution to the Fusemycells Challenge. - Marek Wodzinski; Henning Müller (ISBI, 2025)

Designing Accessible XR for Neurodegenerative Disease Patients: Insights from Parkinson's Disease Case Study. - Daria Hemmerling; Pawel Jemiolo; Mateusz Daniol; Marek Wodzinski; Jakub Kaminski; Magdalena Igras-Cybulska; Magdalena Wójcik-Pedziwiatr (VR Workshops, 2025)

Applying Multimodal Mixed Reality System for Classifying Parkinson's Disease: Design and Evaluation of the Voice Module. - Joanna Stepien; Milosz Dudek; Marek Wodzinski; Mateusz Daniol; Magdalena Igras-Cybulska; Magdalena Wójcik-Pedziwiatr; Daria Hemmerling (VR Workshops, 2025)

Gait analysis in mixed reality for Parkinson's disease assessment. - Daria Hemmerling; Marta Kaczmarska; Bartlomiej Krawczyk; Milosz Dudek; Mateusz Daniol; Pawel Jemiolo; Marek Wodzinski; Magdalena Wójcik-Pedziwiatr (Biomed. Signal Process. Control., 2025)

Automated determination of hip arthrosis on the Kellgren-Lawrence scale in pelvic digital radiographs scans using machine learning. - Karolina Nurzynska; Marek Wodzinski; Adam Piórkowski; Michal Strzelecki; Rafal Obuchowicz; Pawel Kaminski (Comput. Methods Programs Biomed., 2025)

Automatic skull reconstruction by deep learnable symmetry enforcement. - Marek Wodzinski; Mateusz Daniol; Daria Hemmerling (Comput. Methods Programs Biomed., 2025)

Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge. - Muhammad Imran 013; Jonathan R. Krebs; Vishal Balaji Sivaraman; Teng Zhang; Amarjeet Kumar; Walker R. Ueland; Michael J. Fassler; Jinlong Huang; Xiao Sun; Lisheng Wang; Pengcheng Shi; Maximilian Rokuss; et al. (CoRR, 2025)

Segmenting the Inferior Alveolar Canal in CBCTs Volumes: The ToothFairy Challenge. - Federico Bolelli; Luca Lumetti; Shankeeth Vinayahalingam; Mattia Di Bartolomeo; Arrigo Pellacani; Kevin Marchesini; Niels van Nistelrooij; Pieter van Lierop; Tong Xi; Yusheng Liu; Rui Xin 003; Tao Yang 037; et al. (IEEE Trans. Medical Imaging, 2025)

Automated segmenta-on of pediatric neuroblastoma on multi-modal MRI: Results of the SPPIN challenge at MICCAI 2023. - Myrthe A. D. Buser; D. C. Simons; M. Fitski; Marc H. W. A. Wijnen; A. S. Littooij; A. H. ter Brugge; Iris N. Vos; Markus H. A. Janse; M. den Boer; R. ter Maat; Junya Sato; S. Kido; et al. (CoRR, 2025)