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

arXiv:2308.03813v2 Announce Type: replace-cross
Abstract: 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 automatic, dedicated system to increase the availability of personalized cranial reconstruction is highly desirable. The problem of the automatic cranial defect reconstruction can be formulated as the shape completion task and solved using dedicated deep networks. Currently, the most common approach is to use the volumetric representation and apply deep …

abstract arxiv availability cloud cs.ai cs.cv cs.lg cs.na design eess.iv iterative low math.na people personalized replace resolution transformers type types