Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects. (arXiv:2308.04883v1 [eess.IV])

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. The main challenge is associated with the high
diversity of possible cranial defects. The lack of appropriate data sources
negatively influences the data-driven nature of deep learning algorithms.
Hence, one of the possible solutions to overcome this problem is to rely on
synthetic data. In this work, we propose three …

arxiv augmentation automation become challenge data data sources deep generative networks deep learning deep learning techniques defects design diversity generative hot networks personalized process process automation terms