Learning continuous shape priors from sparse data with neural implicit functions

Author:

Amiranashvili TamazORCID,Lüdke David,Li Hongwei BranORCID,Zachow StefanORCID,Menze Bjoern H.ORCID

Funder

Federal Ministry of Education and Research Bonn Office

Helmut Horten Foundation

Publisher

Elsevier BV

Reference33 articles.

1. Statistical shape models: understanding and mastering variation in anatomy;Ambellan,2019

2. Automated segmentation of knee bone and cartilage combining statistical shape knowledge and convolutional neural networks: Data from the osteoarthritis initiative;Ambellan;Med. Image Anal.,2019

3. Rigid motion invariant statistical shape modeling based on discrete fundamental forms: Data from the osteoarthritis initiative and the alzheimer’s disease neuroimaging initiative;Ambellan;Med. Image Anal.,2021

4. Geodesic b-score for improved assessment of knee osteoarthritis;Ambellan,2021

5. Learning shape reconstruction from sparse measurements with neural implicit functions;Amiranashvili,2022

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