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20232026
most citedImproving Deep Learning-based Automatic Cranial Defect Reconstruction by Heavy Data Augmentation: From Image Registration to Latent Diffusion Models

1 citations · 1 across the 6 of their papers we have counts for

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eess.IV2024

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…

eess.IV2023

Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects

Kamil Kwarciak, Marek Wodzinski

The design of personalized cranial implants is a challenging and tremendous task that has become a hot topic in terms of process automation with the use of deep learning techniques…