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ORCIDMarek Wodzinski
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2020 – today
- 2024
[j13]Marek Wodzinski
, Kamil Kwarciak, Mateusz Daniol, Daria Hemmerling:
Improving deep learning-based automatic cranial defect reconstruction by heavy data augmentation: From image registration to latent diffusion models. Comput. Biol. Medicine 182: 109129 (2024)- [j12]Marek Wodzinski, Niccolò Marini, Manfredo Atzori, Henning Müller:
RegWSI: Whole slide image registration using combined deep feature- and intensity-based methods: Winner of the ACROBAT 2023 challenge. Comput. Methods Programs Biomed. 250: 108187 (2024) - [j11]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, 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, Mattias Rantalainen:
The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue. Medical Image Anal. 97: 103257 (2024) - [j10]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, Manfredo Atzori:
Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning. Medical Image Anal. 97: 103303 (2024) - [c29]Adam Sulek, Jakub Jonczyk, Patryk Orzechowski, Ahmed Abdeen Hamed, Marek Wodzinski:
EsmTemp - Transfer Learning Approach for Predicting Protein Thermostability. ICCS (3) 2024: 187-194 - [c28]Daria Hemmerling, Mateusz Daniol, Marek Wodzinski, Joanna Stepien, Pawel Jemiolo, Marta Kaczmarska, Jakub Kaminski, Magdalena Wójcik-Pedziwiatr:
Augmented Reality Platform for Neurological Evaluations. INI-DH@AVI 2024: 43-47 - [c27]Marek Wodzinski, Henning Müller:
Patch-Based Encoder-Decoder Architecture For Automatic Transmitted Light To Fluorescence Imaging Transition: Contribution To The Lightmycells Challenge. ISBI 2024: 1-4 - [c26]Daria Hemmerling, Pawel Jemiolo, Mateusz Daniol, Marek Wodzinski, Jakub Kaminski, Magdalena Wójcik-Pedziwiatr:
Multimodal Approach for the Diagnosis of Neurodegenerative Disorders Using Augmented Reality. VR Workshops 2024: 1166-1167 - [i18]Monika Górka, Daniel Jaworek, Marek Wodzinski:
Deep Learning-Based Segmentation of Tumors in PET/CT Volumes: Benchmark of Different Architectures and Training Strategies. CoRR abs/2404.09761 (2024) - [i17]Mateusz Daniol, Daria Hemmerling, Jakub Sikora, Pawel Jemiolo, Marek Wodzinski, Magdalena Wójcik-Pedziwiatr:
Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases. CoRR abs/2404.12984 (2024) - [i16]Marek Wodzinski, Daria Hemmerling, Mateusz Daniol:
Automatic Cranial Defect Reconstruction with Self-Supervised Deep Deformable Masked Autoencoders. CoRR abs/2404.13106 (2024) - [i15]Marek Wodzinski, Niccolò Marini, Manfredo Atzori, Henning Müller:
RegWSI: Whole Slide Image Registration using Combined Deep Feature- and Intensity-Based Methods: Winner of the ACROBAT 2023 Challenge. CoRR abs/2404.13108 (2024) - [i14]Marek Wodzinski, Niccolò Marini, Manfredo Atzori, Henning Müller:
DeeperHistReg: Robust Whole Slide Images Registration Framework. CoRR abs/2404.14434 (2024) - [i13]Marek Wodzinski, Henning Müller:
Patch-Based Encoder-Decoder Architecture for Automatic Transmitted Light to Fluorescence Imaging Transition: Contribution to the LightMyCells Challenge. CoRR abs/2406.01187 (2024) - [i12]Marek Wodzinski, Kamil Kwarciak, Mateusz Daniol, Daria Hemmerling:
Improving Deep Learning-based Automatic Cranial Defect Reconstruction by Heavy Data Augmentation: From Image Registration to Latent Diffusion Models. CoRR abs/2406.06372 (2024) - [i11]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. CoRR abs/2406.11538 (2024) - [i10]Niccolò Marini, Stefano Marchesin, Lluis Borras Ferris, Simon Püttmann, Marek Wodzinski, Riccardo Fratti, Damian Podareanu, Alessandro Caputo, Svetla Boytcheva, Simona Vatrano, Filippo Fraggetta, Iris Nagtegaal, Gianmaria Silvello, Manfredo Atzori, Henning Müller:
Automatic Labels are as Effective as Manual Labels in Biomedical Images Classification with Deep Learning. CoRR abs/2406.14351 (2024) - 2023
- [j9]Jianning Li, 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, 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 Spanel, Michele R. Aizenberg, Jens Kleesiek, Jan Egger:
Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge. Medical Image Anal. 88: 102865 (2023) - [j8]Manahil Zulfiqar, Maciej Stanuch, Marek Wodzinski, Andrzej Skalski:
DRU-Net: Pulmonary Artery Segmentation via Dense Residual U-Network with Hybrid Loss Function. Sensors 23(12): 5427 (2023) - [j7]Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey A. Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Pew-Thian Yap, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Jens Sjölund, Daniel Grzech, Huaqi Qiu, Zeju Li, Alexander Thorley, Jinming Duan, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett A. Landman, Yuankai Huo, Keelin Murphy, Nikolas Lessmann, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich:
Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning. IEEE Trans. Medical Imaging 42(3): 697-712 (2023) - [c25]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 M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, A. Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patino, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin M. H. van Wijnen, Martin Wagner, D. Wei, Amine Yamlahi, Moi Hoon Yap, C. Yuan, Maximilian Zenk, A. Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, J. Cho, C. Choi, Q. Dou, Ivan Ezhov, Christoph M. Friedrich, C. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García-Faura, Maria Grammatikopoulou, S. Hong, Mostafa Jahanifar, I. Jang, Abdolrahim Kadkhodamohammadi, I. Kang, Florian Kofler, S. Kondo, Hugo Jaco Kuijf, M. Li, M. Luu, Tomaz Martincic, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, S. Pang, J. Park, S. Park, Szymon Plotka, Élodie Puybareau, Nasir M. Rajpoot, K. Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Stepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Hélène Urien, João L. Vilaça, Kareem A. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, Benedikt Wiestler, Marek Wodzinski, F. Xia, J. Xie, Z. Xiong, S. Yang, Y. Yang, Z. Zhao, Klaus H. Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein:
Why is the Winner the Best? CVPR 2023: 19955-19966 - [c24]Daria Hemmerling, Marek Wodzinski, Juan Rafael Orozco-Arroyave, David Sztahó, Mateusz Daniol, Pawel Jemiolo, Magdalena Wójcik-Pedziwiatr:
Vision Transformer for Parkinson's Disease Classification using Multilingual Sustained Vowel Recordings. EMBC 2023: 1-4 - [c23]Artur Jurgas, Marek Wodzinski, Weronika Celniak, Manfredo Atzori, Henning Müller:
Artifact Augmentation for Learning-based Quality Control of Whole Slide Images. EMBC 2023: 1-4 - [c22]Kamil Kwarciak, Marek Wodzinski:
Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects. ICCV (Workshops) 2023: 1058-1066 - [c21]Marek Wodzinski, Henning Müller:
Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge. SEG.A@MICCAI 2023: 42-54 - [c20]Marek Wodzinski, Mateusz Daniol, Daria Hemmerling, Miroslaw Socha:
High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers. MICCAI (9) 2023: 333-343 - [c19]Artur Jurgas, Marek Wodzinski, Manfredo Atzori, Henning Müller:
Robust Multiresolution and Multistain Background Segmentation in Whole Slide Images. PCBBE 2023: 29-40 - [i9]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, 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, Mattias Rantalainen:
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue. CoRR abs/2305.18033 (2023) - [i8]Marek Wodzinski, Mateusz Daniol, Daria Hemmerling, Miroslaw Socha:
High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers. CoRR abs/2308.03813 (2023) - [i7]Kamil Kwarciak, Marek Wodzinski:
Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects. CoRR abs/2308.04883 (2023) - [i6]Marek Wodzinski, Henning Müller:
Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge. CoRR abs/2310.15827 (2023) - [i5]Kaiyuan Yang, 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, Diana Waldmannstetter, Florian Kofler, Fernando Navarro, Martin J. Menten, Ivan Ezhov, Daniel Rueckert, Iris N. Vos, Ynte M. Ruigrok, Birgitta K. Velthuis, Hugo J. Kuijf, Julien Hämmerli, Catherine Wurster, Philippe Bijlenga, Laura Westphal, Jeroen Bisschop, Elisa Colombo, Hakim Baazaoui, Andrew Makmur, James Hallinan, Benedikt Wiestler, Jan S. Kirschke, Roland Wiest, Emmanuel Montagnon, Laurent Létourneau-Guillon, Adrian Galdran, Francesco Galati, Daniele Falcetta, Maria A. Zuluaga, Chaolong Lin, Haoran Zhao, Zehan Zhang, Sinyoung Ra, Jongyun Hwang, Hyunjin Park, Junqiang Chen, Marek Wodzinski, Henning Müller, et al.:
Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA. CoRR abs/2312.17670 (2023) - 2022
- [j6]Marek Wodzinski, Mateusz Daniol, Miroslaw Socha, Daria Hemmerling, Maciej Stanuch, Andrzej Skalski:
Deep learning-based framework for automatic cranial defect reconstruction and implant modeling. Comput. Methods Programs Biomed. 226: 107173 (2022) - [j5]Niccolò Marini, Stefano Marchesin, Sebastian Otálora, Marek Wodzinski, Alessandro Caputo, Mart van Rijthoven, Witali Aswolinskiy, John-Melle Bokhorst, Damian Podareanu, Edyta Petters, Svetla Boytcheva, Genziana Buttafuoco, Simona Vatrano, Filippo Fraggetta, Jeroen van der Laak, Maristella Agosti, Francesco Ciompi, Gianmaria Silvello, Henning Müller, Manfredo Atzori:
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations. npj Digit. Medicine 5 (2022) - [c18]Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller:
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. BrainLes@MICCAI 2022: 241-251 - [i4]Marek Wodzinski, Mateusz Daniol, Miroslaw Socha, Daria Hemmerling, Maciej Stanuch, Andrzej Skalski:
Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling. CoRR abs/2204.06310 (2022) - [i3]Marek Wodzinski, Artur Jurgas, Niccolò Marini, Manfredo Atzori, Henning Müller:
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. CoRR abs/2211.07386 (2022) - 2021
- [j4]Marek Wodzinski, Henning Müller:
DeepHistReg: Unsupervised Deep Learning Registration Framework for Differently Stained Histology Samples. Comput. Methods Programs Biomed. 198: 105799 (2021) - [j3]Marek Wodzinski, Izabela Ciepiela, Tomasz Kuszewski, Piotr Kedzierawski, Andrzej Skalski:
Semi-Supervised Deep Learning-Based Image Registration Method with Volume Penalty for Real-Time Breast Tumor Bed Localization. Sensors 21(12): 4085 (2021) - [c17]Marek Wodzinski, Henning Müller:
Invnet: A Deep Learning Approach To Invert Complex Deformation Fields. ISBI 2021: 1302-1305 - [c16]Marek Wodzinski, Mateusz Daniol, Daria Hemmerling:
Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets. AutoImplant@MICCAI 2021: 29-44 - [c15]Marek Wodzinski, Andrzej Skalski:
Adversarial Affine Registration for Real-Time Intraoperative Registration of 3-D US-US for Brain Shift Correction. ASMUS@MICCAI 2021: 75-84 - [c14]Marek Wodzinski:
Semi-supervised Multilevel Symmetric Image Registration Method for Magnetic Resonance Whole Brain Images. MIDOG/MOOD/Learn2Reg@MICCAI 2021: 186-191 - [i2]Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey A. Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Huaqi Qiu, Zeju Li, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett A. Landman, Yuankai Huo, Keelin Murphy, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich:
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning. CoRR abs/2112.04489 (2021) - 2020
- [j2]Maciej Stanuch, Marek Wodzinski, Andrzej Skalski:
Contact-Free Multispectral Identity Verification System Using Palm Veins and Deep Neural Network. Sensors 20(19): 5695 (2020) - [j1]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, Michelle Noga, Sarthak Pati, Kumaradevan Punithakumar, Pekka Ruusuvuori, Andrzej Skalski, Nazanin Tahmasebi, Masi Valkonen, Ludovic Venet, Yizhe Wang, Nick Weiss, Marek Wodzinski, Yu Xiang, Yan Xu, Yan Yan, Paul A. Yushkevich, Shengyu Zhao, Arrate Muñoz-Barrutia:
ANHIR: Automatic Non-Rigid Histological Image Registration Challenge. IEEE Trans. Medical Imaging 39(10): 3042-3052 (2020) - [c13]Marek Wodzinski, Tommaso Banzato, Manfredo Atzori, Vincent Andrearczyk, Yashin Dicente Cid, Henning Müller:
Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading. EMBC 2020: 1758-1761 - [c12]Marek Wodzinski, Miroslawa Pajak, Andrzej Skalski, Alexander Witkowski, Giovanni Pellacani, Joanna Ludzik:
Automatic Quality Assessment of Reflectance Confocal Microscopy Mosaics using Attention-Based Deep Neural Network. EMBC 2020: 1824-1827 - [c11]Marek Wodzinski:
Multi-step, Learning-Based, Semi-supervised Image Registration Algorithm. MICCAI (Challenges) 2020: 94-99 - [c10]Marek Wodzinski, Henning Müller:
Unsupervised Learning-Based Nonrigid Registration of High Resolution Histology Images. MLMI@MICCAI 2020: 484-493 - [c9]Marek Wodzinski, Henning Müller:
Learning-Based Affine Registration of Histological Images. WBIR 2020: 12-22
2010 – 2019
- 2019
- [c8]Marek Wodzinski, Andrzej Skalski, Daria Hemmerling, Juan Rafael Orozco-Arroyave, Elmar Nöth:
Deep Learning Approach to Parkinson's Disease Detection Using Voice Recordings and Convolutional Neural Network Dedicated to Image Classification. EMBC 2019: 717-720 - [c7]Marek Wodzinski, Andrzej Skalski, Alexander Witkowski, Giovanni Pellacani, Joanna Ludzik:
Convolutional Neural Network Approach to Classify Skin Lesions Using Reflectance Confocal Microscopy. EMBC 2019: 4754-4757 - [i1]Marek Wodzinski, Andrzej Skalski:
Automatic Nonrigid Histological Image Registration with Adaptive Multistep Algorithm. CoRR abs/1904.00982 (2019) - 2018
- [c6]Marek Wodzinski, Andrzej Skalski, Izabela Ciepiela, Tomasz Kuszewski, Piotr Kedzierawski:
Volume regularization in explicit image registration used for breast cancer bed localization. ISBI 2018: 173-176 - [c5]Marek Wodzinski, Andrzej Skalski:
Artificial CT Data Generation Method with Known Ground-Truth for Image Registration with Missing Data. IST 2018: 1-5 - [c4]Marek Wodzinski, Andrzej Skalski:
Rigid Registration Method for Medical Volumes with Large Deformations and Missing Data. IWSSIP 2018: 1-5 - [c3]Marek Wodzinski, Andrzej Skalski:
Resection-Based Demons Regularization for Breast Tumor Bed Propagation. RAMBO+BIA+TIA@MICCAI 2018: 3-12 - 2017
- [c2]Marek Wodzinski, Andrzej Skalski, Piotr Kedzierawski, Tomasz Kuszewski:
Application of B-splines FFD image registration in breast cancer radiotherapy planning. IWSSIP 2017: 1-5 - [c1]Marek Wodzinski, Andrzej Skalski, Izabela Ciepiela, Tomasz Kuszewski, Piotr Kedzierawski:
Application of demons image registration algorithms in resected breast cancer lodge localization. SPA 2017: 400-405
Coauthor Index
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