CV

Work experience

2026-current: Associate Professor
- AGH University of Kraków, Poland
- Duties include: Research in Medical Image Analysis & Computer Vision - DeepImplant project, Teaching, PhD supervision
2026-current: Team Leader - Medical Image Analysis
- Sano Science, Poland
- Duties include: Leading the Medical Image Analysis Team, Leading the MultiGeoMed and FaceTwin projects
2021-2026: Assistant Professor
- AGH University of Kraków, Poland
- Duties include: Research in Medical Image Analysis & Computer Vision - DeepImplant and DiagNeuro projects, Teaching
2025-2026: Senior Researcher
- Sano Science, Poland
- Duties include: Research & Development in Artificial Intelligence and Medical Imaging - MultiGeoMed project
2024-current: Deep Learning Expert
- ShenAI, Poland
- Duties include: Research & Development in Deep Learning
2021-2025: Postdoctoral Researcher
- HES-SO Valais-Wallis, Switzerland
- Duties include: Research in Medical Image Analysis - ExaMode and BigPicture projects
2020-2024: Scientific Developer
- MedApp S.A, Poland
- Duties include: Research & Development in Artificial Intelligence and Mixed Reality
2016-2021: Research Assistant
- AGH University of Kraków, Poland
- Duties include: Research in Medical Image Analysis & Computer Vision, Teaching

Projects

NCN - Sonata 20 - MultiGeoMed - Principal Intestigator - 2025-10-01 - 2028-10-01 - 1 246 840 PLN
NCBR - LIDER XIII - DeepImplant - LIDER13/0038/2022 - Principal Investigator - 2023-03-01 - 2026-03-01 - 1 500 000 PLN
IHI Innovative Health Initiative - BigPicture - Postdoctoral Researcher - 2021-02-01- 2025-08-31 - 70 081 907 EUR
UE Horizon 2020 - ExaMode - Postdoctoral Researcher - 2019-01-01 - 2023-07-01
NCBR - LIDER XII - DiagNeuro - LIDER12/0049/L-12/2020 - AI Researcher - 2022-01-01 - 2025-01-01 - 1 500 000 PLN
NCN - Preludium 15 - Medical image registration methods focused on the problem of missing data - 2018/29/N/ST6/00143 - Principal Investigator - 2019-01-24 - 2022-01-23 - 185 400 PLN
NCN - Etiuda 7 - Localization of breast tumor using medical image registration algorithms - 2019/32/T/ST6/00065 - Principal Investigator - 2019-10-01 - 2020-09-30 - 144 264 PLN

Education

PostDoc in Computer Science, HES-SO Valais-Wallis, Switzerland, 2021-2025
Ph.D in Biomedical Engineering (Computer Science), AGH University of Kraków, Poland, 2021
M.S. in Computer Science & Biomedical Engineering, AGH University of Kraków, Poland, 2016
B.S. in Biomedical Engineering, AGH University of Kraków, 2015

Achievements

2025 - Polityka Scientific Award in Technical Sciences
2025 - 1st place at the FuseMyCells Challenge
2025 - 1st place at the InnoDiament competition as the supervisor of the best Master Thesis
2024 - 1st place at the BraTS-Path Challenge
2024 - 3rd place at the LightMyCells Challenge
2023 - 1st place at ACROBAT 2023 Challenge
2023 - 1st (clinical), 3rd (meshing), and 4th (quantiative) places at SEG.A 2023 Challenge
2023 - 3rd place at ToothFairy Challenge
2023 - 2nd place at MVSEG Challenge
2023 - Scientist of the Future Award, FIR, Poland
2022 - FNP START Scholarship for the research in Biomedical Engineering
2022 - Winner of the ABB Competition for the best PhD Thesis, ABB, Poland
2022 - 1st place at BraTS-Reg Challenge (ISBI Edition)
2021 - 1st place at AutoImplant 2021 Challenge
2021 - Minister’s Scholarship, Scholarship for Outstanding Young Scientists in Poland (Medical Image Analysis and Deep Learning).

Skills

Artificial Intelligence
- Deep Learning
- Machine Learning
- Reinforcement Learning
- Numerical Methods
- Applied Mathematics
Medical Image Analysis & Computer Vision
- Image Registration
- Image Segmentation
- Image Classification
- Generative Networks
- Reconstruction Methods
- Augmentation Techniques
- 3-D Geometry
- Texture Analysis
- Point-cloud Processing & Analysis
- Surface / Volumetric Meshing
- Mixed & Augmented & Virtual Reality
Programming
- Python (PyTorch, NumPy, Pandas, SciPy, JAX)
- Julia (Flux, DataFrames, SciML)
- C++ (CUDA, OpenMP, Eigen)
- GCP

Publications

Plausible but Unimplantable: A Trustworthiness Audit of Shape Completion Foundation Models for Cranial Defect Reconstruction

M. Wodzinski, K. Kwarciak, D. Hemmerling, M. Daniol, Plausible but Unimplantable: A Trustworthiness Audit of Shape Completion Foundation Models for Cranial Defect Reconstruction, ACCV 2026 TrustFMI Workshop, 2026.

LUMINR: Intensity-conditioned Meta-learned INRs for Accelerated Medical Image Registration

D. Rynczak, M. Wodziński, LUMINR: Intensity-conditioned Meta-learned INRs for Accelerated Medical Image Registration, arXiv preprint, 2026.

MedPCFM-TED: One-Step Point Cloud Flow Matching for Implant Generation via Teacher-Guided Endpoint Distillation

K. Kwarciak, M. Wodziński, MedPCFM-TED: One-Step Point Cloud Flow Matching for Implant Generation via Teacher-Guided Endpoint Distillation, MICCAI 2026 SASHIMI Workshop, 2026.

An Anatomy-Aware Staged Pipeline for Vessel-Specific Intracranial Aneurysm Segmentation in CT and MR Angiography

G. Drwięga, W. Szymański, M. Wodziński, An Anatomy-Aware Staged Pipeline for Vessel-Specific Intracranial Aneurysm Segmentation in CT and MR Angiography, MICCAI 2026 SWITCH+ Workshop, 2026.

SADL: A Size-Adaptive Decision Layer for Chronic Stroke Lesion Segmentation in ISLES 2026

M. Wodziński, G. Drwięga, W. Szymański, SADL: A Size-Adaptive Decision Layer for Chronic Stroke Lesion Segmentation in ISLES 2026, MICCAI 2026 SWITCH+ Workshop, 2026.

Mind the Gap: Mesh-Guided Repair of Broken Vessels

G. Drwięga, W. Szymański, M. Wodziński, Mind the Gap: Mesh-Guided Repair of Broken Vessels, MICCAI 2026 ShapeMI Workshop, 2026.

Automatic segmentation and modeling of the aortic vessel tree: Overview of the SEG.A 2023 aorta segmentation challenge

Y. Jin, A. Pepe, G. M. Melito, Y. Chen, et al., M. Wodzinski, et al., Automatic segmentation and modeling of the aortic vessel tree: Overview of the SEG.A 2023 aorta segmentation challenge, Medical Image Analysis, vol. 115, p. 104324, 2026.

MedPCFM: Improving Medical Point Cloud Completion by Integrating Point Transformers and Flow Matching

K. Kwarciak, M. Wodziński, MedPCFM: Improving Medical Point Cloud Completion by Integrating Point Transformers and Flow Matching, ECCV 2026 AI4M3D Workshop, 2026.

UNet for automatic pneumothorax detection on canine and feline CTs

Tommaso Banzato, Artur Jurgas, Tommaso Pilla, Diane Wilson, Marek Wodzinski, et al., UNet for automatic pneumothorax detection on canine and feline CTs, Scientific Reports, 2026.

MAMA-FLUX.2: Image-to-Image Synthesis of Post-Contrast Breast DCE-MRI for the MAMA-SYNTH Challenge

K. Kwarciak, M. Wodzinski, MAMA-FLUX.2: Image-to-Image Synthesis of Post-Contrast Breast DCE-MRI for the MAMA-SYNTH Challenge, arXiv preprint, 2026.

One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training

A. Florkowska, H. Müller, M. Wodzinski, One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training, arXiv preprint, 2026.

Radiomics-based mapping of glioblastoma infiltration beyond contrast enhancement: diffusion–perfusion correlations and survival analysis in large public cohorts

S. Cepeda, O. Esteban-Sinovas, L. T. Luppino, S. Kuttner, M. Wodzinski, et al., Radiomics-based mapping of glioblastoma infiltration beyond contrast enhancement: diffusion–perfusion correlations and survival analysis in large public cohorts, European Journal of Radiology, vol. 201, p. 112888, 2026.

The TopCoW Challenge—Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

K. Yang, F. Musio, Y. Ma, N. Juchler, et al., M. Wodzinski, et al., The TopCoW Challenge—Topology-Aware Circle of Willis Segmentation for CT and MR Angiography, NEJM AI, vol. 3, no. 8, AIdbp2500994, 2026.

Multi-class segmentation of aortic branches and zones in computed tomography angiography: The AortaSeg24 challenge

M. Imran, J. R. Krebs, V. B. Sivaraman, T. Zhang, et al., M. Wodzinski, et al., Multi-class segmentation of aortic branches and zones in computed tomography angiography: The AortaSeg24 challenge, Medical Image Analysis, vol. 113, p. 104188, 2026.

Spectral super-resolution for Parkinson’s voice via representation-level methods under mixed-reality acquisition

M. Dudek, J. Sikora, J. Krzywdziak, M. Zbik, W. Szecowka, M. Wodzinski, M. Daniol, M. Wojcik-Pedziwiatr, D. Hemmerling, Spectral super-resolution for Parkinsons voice via representation-level methods under mixed-reality acquisition, Computer Methods and Programs in Biomedicine, vol. 285, p. 109522, 2026.

Multi-structure segmentation in CBCT volumes: The ToothFairy2 challenge

F. Bolelli, L. Lumetti, N. van Nistelrooij, S. Vinayahalingam, et al., M. Wodzinski, et al., Multi-structure segmentation in CBCT volumes: The ToothFairy2 challenge, Medical Image Analysis, p. 104095, 2026.

Prospective biopsy-controlled validation of an AI model for predicting glioblastoma infiltration: Results from the SupraGlio trial

S. Cepeda, E. Hernando-Pérez, E. Pérez-Riesgo, I. Rodríguez-Valle, O. Esteban-Sinovas, et al., M. Wodzinski, et al., Prospective biopsy-controlled validation of an AI model for predicting glioblastoma infiltration: Results from the SupraGlio trial, Neuro-Oncology, noag088, 2026.

Multimodal Analysis of Speech-Gaze Fusion in Mixed Reality for the Detection of Neurodegenerative Disorders

M. Dudek, J. Sikora, D. Hemmerling, M. Daniol, M. Wodzinski, M. Wojcik-Pedziwiatr, Multimodal Analysis of Speech-Gaze Fusion in Mixed Reality for the Detection of Neurodegenerative Disorders, 2026 IEEE Conference on Virtual Reality and 3D User Interfaces, 2026

Data-Centric Multiclass Aortic Segmentation: Revisiting Classical Architectures in Low-Data Regimes

M. Wodzinski, H. Müller, Data-Centric Multiclass Aortic Segmentation: Revisiting Classical Architectures in Low-Data Regimes, Multi-class Segmentation of the Aorta, 2026.

Development of an artificial intelligence-based algorithm for the detection of left atrial enlargement from feline thoracic radiographs

C. Valente, M.Wodzinski, C. Guglielmini, et al., Development of an artificial intelligence-based algorithm for the detection of left atrial enlargement from feline thoracic radiographs, Veterinary Quarterly, vol. 46, no. 1, 2026.

GRU-Based Deep Multimodal Fusion of Speech and Head-IMU Signals in Mixed Reality for Parkinsons Disease Detection

D. Hemmerling et al., GRU-Based Deep Multimodal Fusion of Speech and Head-IMU Signals in Mixed Reality for Parkinsons Disease Detection, Sensors, vol. 26, no. 1, 2025.

Automated Segmentation of Canine Pulmonary Masses in CT Imaging Using AI

A. Jurgas, S. Burti, M. Wodziński, C. Puccinelli, G.B. Cherubini, S. Citi, G. Poloni, N. Mastromattei, M. Bendazzoli, D. Wilson et al., Automated Segmentation of Canine Pulmonary Masses in CT Imaging Using AI, Veterinary Quarterly, vol. 45, no. 1, 2025.

Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges

L. Hansen, et al., Learn2Reg 2024: New Benchmark Datasets Driving Progress on New Challenges, Machine Learning for Biomedical Imaging, vol. 3, no. 12, 2025.

Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma

Santiago Cepeda, et al., Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma, Scientific Reports, 2025.

BONBID-HIE 2023: Lesion Segmentation Challenge in BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy

Rina Bao, et al., BONBID-HIE 2023: Lesion Segmentation Challenge in BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy, IEEE Transactions on Medical Imaging, 2025.

Mixed-Reality System for Neurodegenerative Disorders: Design, Implementation, and User Evaluation

D. Hemmerling, et al., Mixed-Reality System for Neurodegenerative Disorders: Design, Implementation, and User Evaluation, IEEE Pervasive Computing, vol. 24, no. 4, 2025.

A Community Benchmark for the Automated Segmentation of Pediatric Neuroblastoma on Multi-Modal MRI: Design and Results of the SPPIN Challenge at MICCAI 2023

M.A.D. Buser, D.C. Simons, M. Fitski, M.H.W.A. Wijnen, A.S. Littooij, A.H. ter Brugge, I.N. Vos, M.H.A. Janse, M. de Boer, R. ter Maat et al., A Community Benchmark for the Automated Segmentation of Pediatric Neuroblastoma on Multi-Modal MRI: Design and Results of the SPPIN Challenge at MICCAI 2023, Bioengineering, vol. 12, no. 11, 2025.

Multi-step Segmentation of Pelvic Fractures: Handling Variable Fracture Counts Through Anatomical and Surface Analysis

Artur Jurgas, et al., Multi-step Segmentation of Pelvic Fractures: Handling Variable Fracture Counts Through Anatomical and Surface Analysis, MICCAI Workshop on Deep Generative Models, 2025.

Comparative evaluation of CAM methods for enhancing explainability in veterinary radiography

Piotr Dusza, et al., Comparative evaluation of CAM methods for enhancing explainability in veterinary radiography, Scientific Reports, 2025.

Automated AI-based segmentation of canine hepatic focal lesions from CT studies

Silvia Burti, et al., Automated AI-based segmentation of canine hepatic focal lesions from CT studies, Front. Vet. Sci. 12:1638142. doi: 10.3389/fvets.2025.1638142, 2025.

Automatic labels are as effective as manual labels in digital pathology images classification with deep learning

Niccolo Marini, et al., Automatic labels are as effective as manual labels in digital pathology images classification with deep learning, Journal of Pathology Informatics, 2025.

Unsupervised skull segmentation in MR images utilizing modality translation and super-resolution

Kamil Kwarciak, Mateusz Daniol, Daria Hemmerling, Marek Wodzinski, Unsupervised skull segmentation in MR images utilizing modality translation and super-resolution, Scientific Reports, 2025.

Automatic Multi-structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures

M. Wodzinski, H. Müller, Automatic Multi-structure Segmentation in Cone Beam Computed Tomography Volumes Using Deep Encoder-Decoder Architectures, MICCAI ToothFairy 2024, 2024.

3-D Image-to-Image Fusion in Lightsheet Microscopy by Two-Step Adversarial Network: Contribution to the FuseMyCells Challenge

M. Wodzinski, H. Muller, 3-D Image-to-Image Fusion in Lightsheet Microscopy by Two-Step Adversarial Network: Contribution to the FuseMyCells Challenge, IEEE ISBI 2025, 2025.

Automated determination of hip arthrosis on the Kellgren–Lawrence scale in pelvic digital radiographs scans using machine learning

Karolina Nurzynska, Marek Wodzinski, Adam Piorkowski, et al., Automated determination of hip arthrosis on the Kellgren–Lawrence scale in pelvic digital radiographs scans using machine learning, Computer Methods and Programs in Biomedicine, 2025.

Analysis of Voice, Speech, and Language Biomarkers of Parkinsons Disease Collected in a Mixed Reality Setting

Milosz Dudek, et al., Analysis of Voice, Speech, and Language Biomarkers of Parkinson’s Disease Collected in a Mixed Reality Setting, Sensors, 2025.

Gait analysis in mixed reality for Parkinson’s disease assessment

Daria Hemmerling, et al., Gait analysis in mixed reality for Parkinson’s disease assessment, Biomedical Signal Processing and Control, 2025.

Automatic Skull Reconstruction by Deep Learnable Symmetry Enforcement

Marek Wodzinski, et al., Automatic Skull Reconstruction by Deep Learnable Symmetry Enforcement, Computer Methods and Programs in Biomedicine, 2025.

Artificial Intelligence-Empowered Radiology—Current Status and Critical Review

Rafał Obuchowicz, et al., Artificial Intelligence-Empowered Radiology—Current Status and Critical Review, Diagnostics, Vol. 15, 2025.

MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision

Jianning Li, et al., MedShapeNet – a large-scale dataset of 3D medical shapes for computer vision, Biomedical Engineering / Biomedizinische Technik, Vol. 69, 2024.

Automatic detection and multi-component segmentation of brain metastases in longitudinal MRI

Vincent Andrearczyk, et al., Automatic detection and multi-component segmentation of brain metastases in longitudinal MRI, Scientific Reports, Vol. 14, 2024.

Segmenting the Inferior Alveolar Canal in CBCTs Volumes: the ToothFairy Challenge

Federico Bolelli, et al., Segmenting the Inferior Alveolar Canal in CBCTs Volumes: the ToothFairy Challenge, IEEE Transactions on Medical Imaging, 2024.

Unsupervised Skull Segmentation via Contrastive MR-to-CT Modality Translation

K. Kwarciak, M. Daniol, D. Hemmerling, M. Wodzinski, Unsupervised Skull Segmentation via Contrastive MR-to-CT Modality Translation, ACCV 2024, 2024.

Automatic Registration of SHG and H&E Images with Feature-Based Initial Alignment and Intensity-Based Instance Optimization: Contribution to the COMULIS Challenge

M. Wodzinski, H. Müller, Automatic Registration of SHG and H&E Images with Feature-based Initial Alignment and Intensity-based Instance Optimization: Contribution to the COMULIS Challenge, WBIR 2024, 2024.

Improving deep learning-based automatic cranial defect reconstruction by heavy data augmentation: From image registration to latent diffusion models

Marek Wodzinski, et al., Improving deep learning-based automatic cranial defect reconstruction by heavy data augmentation: From image registration to latent diffusion models, Computers in Biology and Medicine, Vol. 182, 2024.

Patch-Based Encoder-Decoder Architecture For Automatic Transmitted Light To Fluorescence Imaging Transition: Contribution To The Lightmycells Challenge

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

Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning

Niccolò Marini, Stefano Marchesin, Marek Wodzinski, et al., Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning, Medical Image Analysis, 2024.

Development of an artificial intelligence-based algorithm for predicting the severity of myxomatous mitral valve disease from thoracic radiographs by using two grading systems

Carlotta Valente, Marek Wodzinski, Carlo Guglielmini, et al., Development of an artificial intelligence-based algorithm for predicting the severity of myxomatous mitral valve disease from thoracic radiographs by using two grading systems, Research in Veterinary Science, 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, Improving quality control of whole slide images by explicit artifact augmentation, Scientific Reports, 2024.

Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases

Mateusz Daniol et al. Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases, IEEE EMBC 2024, 2024.

Automatic Cranial Defect Reconstruction with Self-Supervised Deep Deformable Masked Autoencoders

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

The ACROBAT 2022 challenge: automatic registration of breast cancer tissue

Philippe Weitz, et al., The ACROBAT 2022 challenge: automatic registration of breast cancer tissue, Medical Image Analysis, 2024.

EsmTemp-Transfer Learning Approach for Predicting Protein Thermostability

A. Sułek, J. Jończyk, P. Orzechowski, AA. Hamed, M. Wodzinski, EsmTemp-Transfer Learning Approach for Predicting Protein Thermostabilitye, International Conference on Computational Science, 2024.

HaN-Seg: The head and neck organ-at-risk CT and MR segmentation challenge

Gašper Podobnik, et al., HaN-Seg: The head and neck organ-at-risk CT and MR segmentation challenge, Radiotherapy and Oncology, 2024.

Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations

Silvia Burti, et al., Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations, Research in Veterinary Science, 2024.

RegWSI: Whole Slide Image Registration using Combined Deep Feature-and Intensity-Based Methods: Winner of the ACROBAT 2023 Challenge

Marek Wodzinski et al. RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge, Computer Methods and Programs in Biomedicine, Vol. 250, 2024.

AI-Based Automated Custom Cranial Implant Design–Challenges and Opportunities with Case Study

Mateusz Daniol, Daria Hemmerling, Marek Wodzinski, AI-Based Automated Custom Cranial Implant Design – Challenges and Opportunities with Case Study, Advances in Manufacturing IV, 2024.

Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge

Marek Wodzinski, Henning Müller, Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge, MICCAI Challenge on Segmentation of the Aorta, 2024.

Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects

Kamil Kwarciak, Marek Wodzinski, Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects, IEEE CVPRW 2023, 2023.

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA

K. Yang, et. al., Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA, In Review, 2024.

Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models

Weronika Celniak, Marek Wodzinski, Artur Jurgas, et. al., Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models, Scientific Reports, Vol. 13, 2024.

An AI-based algorithm for the automatic evaluation of image quality in canine thoracic radiographs

Tommaso Banzato, Marek Wodzinski, Silvia Burti et al. An AI-based algorithm for the automatic evaluation of image quality in canine thoracic radiographs, Scientific Reports, Vol. 13, 2023.

High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers

Marek Wodzinski, et. al., High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers, MICCAI 2023, 2023.

Development of an artificial intelligence-based method for the diagnosis of the severity of myxomatous mitral valve disease from canine chest radiographs

Carlotta Valente, Marek Wodzinski, Carlo Guglielmini, et. al., Development of an artificial intelligence-based method for the diagnosis of the severity of myxomatous mitral valve disease from canine chest radiographs, Frontiers in Veterinary Science, 2023.

Biomedical image analysis competitions: The state of current participation practice

Matthias Eisenmann, et al., Biomedical image analysis competitions: The state of current participation practice, arXiv:2212.08568, 2023.

Robust Multiresolution and Multistain Background Segmentation in Whole Slide Images

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

Why is the winner the best?

Matthias Eisenmann, et al., Why is the winner the best?, IEEE CVPR 2023, 2023.

Vision Transformer for Parkinson’s Disease Classification using Multilingual Sustained Vowel Recordings

Daria Hemmerling, Marek Wodzinski, Juan Rafael Orozco-Arroyave, et. al., Vision Transformer for Parkinson’s Disease Classification using Multilingual Sustained Vowel Recordings, IEEE EMBC 2023, 2023.

Artifact Augmentation for Learning-based Quality Control of Whole Slide Images

Artur Jurgas, Marek Wodzinski, Weronika Celniak, et. al., Artifact Augmentation for Learning-based Quality Control of Whole Slide Images, IEEE EMBC 2023, 2023.

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, et. al., 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, MICCAI BrainLes 2022, 2023.

Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the autoimplant 2021 cranial implant design challenge

Jianning Li, et al., Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the autoimplant 2021 cranial implant design challenge, Medical Image Analysis, Vol. 88, 2023.

DRU-Net: Pulmonary Artery Segmentation via Dense Residual U-Network with Hybrid Loss Function

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

Data-driven color augmentation for H&E stained images in computational pathology

Niccolò Marini, Sebastian Otalora, Marek Wodzinski, et al., Data-driven color augmentation for H&E stained images in computational pathology, Journal of Pathology Informatics, 2023.

Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning

Alessa Hering, et al., Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning, IEEE Transactions on Medical Imaging, Vol. 42, 2023.

Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling

Marek Wodzinski, et al., Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling, Computer Methods and Programs in Biomedicine, Vol. 226, 2022.

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations

Niccolò Marini, et al., Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations, npj Digital Medicine, 2022.

Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets

Marek Wodzinski, Mateusz Daniol, Daria Hemmerling, Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets, MICCAI Cranial Implant Design Challenge, 2021.

An AI-based algorithm for the automatic classification of thoracic radiographs in cats

Tommaso Banzato, Marek Wodzinski, Federico Tauceri, et al., An AI-based algorithm for the automatic classification of thoracic radiographs in cats, Frontiers in Veterinary Science, Vol. 8, 2021.

Adversarial Affine Registration for Real-Time Intraoperative Registration of 3-D US-US for Brain Shift Correction

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

Semi-Supervised Deep Learning-Based Image Registration Method with Volume Penalty for Real-Time Breast Tumor Bed Localization

Marek Wodzinski, et al., Semi-Supervised Deep Learning-Based Image Registration Method with Volume Penalty for Real-Time Breast Tumor Bed Localization, Sensors, 2021.

Learning-based local quality assessment of reflectance confocal microscopy images for dermatology applications

Miroslawa Sikorska, Andrzej Skalski, Marek Wodzinski, et al., Learning-based local quality assessment of reflectance confocal microscopy images for dermatology applications, Biocybernetics and Biomedical Engineering, Vol 41, 2021.

Automatic classification of canine thoracic radiographs using deep learning

Tommaso Banzato, Marek Wodzinski, Silvia Burti, et al., Automatic classification of canine thoracic radiographs using deep learning, Scientific Reports, Vol 11, 2021.

Multistep, automatic and nonrigid image registration method for histology samples acquired using multiple stains

Marek Wodzinski, Andrzej Skalski, Multistep, automatic and nonrigid image registration method for histology samples acquired using multiple stains, Physics in Medicine & Biology, Vol 66., 2021.

DeepHistReg: Unsupervised Deep Learning Registration Framework for Differently Stained Histology Samples

Marek Wodzinski, Henning Müller, DeepHistReg: Unsupervised Deep Learning Registration Framework for Differently Stained Histology Samples, Computer Methods and Programs in Biomedicine, Vol. 198, 2021.

Unsupervised Learning-Based Nonrigid Registration of High Resolution Histology Images

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

Automatic Quality Assessment of Reflectance Confocal Microscopy Mosaics using Attention-Based Deep Neural Network

Marek Wodzinski, et al., Automatic Quality Assessment of Reflectance Confocal Microscopy Mosaics using Attention-Based Deep Neural Network, IEEE EMBC 2020, 2020.

Learning-Based Affine Registration of Histological Images

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

ANHIR: automatic non-rigid histological image registration challenge

Jiří Borovec, et al., ANHIR: automatic non-rigid histological image registration challenge, IEEE Transactions on Medical Imaging, Vol. 39, 2020.

Convolutional Neural Network Approach to Classify Skin Lesions Using Reflectance Confocal Microscopy

Marek Wodzinski, et al., Convolutional Neural Network Approach to Classify Skin Lesions Using Reflectance Confocal Microscopy, IEEE EMBC 2019, 2019.

Deep Learning Approach to Parkinson’s Disease Detection Using Voice Recordings and Convolutional Neural Network Dedicated to Image Classification

Marek Wodzinski, et al. Deep learning approach to Parkinson’s disease detection using voice recordings and convolutional neural network dedicated to image classification, IEEE EMBC 2019, 2019.

Improving oncoplastic breast tumor bed localization for radiotherapy planning using image registration algorithms

Marek Wodzinski, et al., Improving oncoplastic breast tumor bed localization for radiotherapy planning using image registration algorithms, Physics in Medicine & Biology, Vol. 63, 2021.

Marek Wodzinski

CV