10 citations · 13 across the 7 of their papers we have counts for
7 papers
Automatic Skull Reconstruction by Deep Learnable Symmetry Enforcement
Marek Wodzinski, Mateusz Daniol, Daria Hemmerling
Every year, thousands of people suffer from skull damage and require personalized implants to fill the cranial cavity. Unfortunately, the waiting time for reconstruction surgery ca…
Unsupervised Skull Segmentation via Contrastive MR-to-CT Modality Translation
Kamil Kwarciak, Mateusz Daniol, Daria Hemmerling +1
The skull segmentation from CT scans can be seen as an already solved problem. However, in MR this task has a significantly greater complexity due to the presence of soft tissues r…
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 +1
Modeling and manufacturing of personalized cranial implants are important research areas that may decrease the waiting time for patients suffering from cranial damage. The modeling…
Automatic Cranial Defect Reconstruction with Self-Supervised Deep Deformable Masked Autoencoders
Marek Wodzinski, Daria Hemmerling, Mateusz Daniol
Thousands of people suffer from cranial injuries every year. They require personalized implants that need to be designed and manufactured before the reconstruction surgery. The man…
Eye-tracking in Mixed Reality for Diagnosis of Neurodegenerative Diseases
Mateusz Daniol, Daria Hemmerling, Jakub Sikora +3
Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for trackin…
High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers
Marek Wodzinski, Mateusz Daniol, Daria Hemmerling +1
Each year thousands of people suffer from various types of cranial injuries and require personalized implants whose manual design is expensive and time-consuming. Therefore, an aut…
Deep Learning-based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling
Marek Wodzinski, Mateusz Daniol, Miroslaw Socha +3
The goal of this work is to propose a robust, fast, and fully automatic method for personalized cranial defect reconstruction and implant modeling. We propose a two-step deep learn…