A Direct Geometry Processing Cartilage Generation Method Using Segmented Bone Models from Datasets with Poor Cartilage Visibility

Research output: Contribution to conferencePaperResearchpeer-review

We present a method to generate subject-specific cartilage for the hip joint. Given bone geometry, our approach is agnostic to image modality, creates conforming interfaces, and is well suited for finite element analysis. We demonstrate our method on ten hip joints showing anatomical shape consistency and well-behaved stress patterns. Our method is fast and may assist in large-scale biomechanical population studies of the hip joint when manual segmentation or training data is not feasible.
Original languageEnglish
Publication date1 Nov 2022
DOIs
Publication statusPublished - 1 Nov 2022

Bibliographical note

@InProceedings{10.1007/978-3-031-09327-2_11,
author="Moshfeghifar, Faezeh
and Nielsen, Max Kragballe
and Tasc{\'o}n-Vidarte, Jos{\'e} D.
and Darkner, Sune
and Erleben, Kenny",
editor="Nielsen, Poul M.F.
and Nash, Martyn P.
and Li, Xinshan
and Miller, Karol
and Wittek, Adam",
title="A Direct Geometry Processing Cartilage Generation Method Using Segmented Bone Models from Datasets with Poor Cartilage Visibility",
booktitle="Computational Biomechanics for Medicine",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="155--169",
abstract="Moshfeghifar, FaezehNielsen, Max KragballeTasc{\'o}n-Vidarte, Jos{\'e} D.Darkner, SuneErleben, KennyWe present a method to generate subject-specific cartilage for the hip joint. Given bone geometry, our approach is agnostic to image modality, creates conforming interfaces, and is well suited for finite element analysis. We demonstrate our method on ten hip joints showing anatomical shape consistency and well-behaved stress patterns. Our method is fast and may assist in large-scale biomechanical population studies of the hip joint when manual segmentation or training data is not feasible.",
isbn="978-3-031-09327-2"
}

ID: 324596558