Geodesic B-Score for Improved Assessment of Knee Osteoarthritis

Autor:	Ambellan, Felix, Zachow, Stefan, von Tycowicz, Christoph
Rok vydání:	2021
Předmět:	Computer Science - Computer Vision and Pattern Recognition Mathematics - Differential Geometry Statistics - Applications Statistics - Other Statistics
Druh dokumentu:	Working Paper
Popis:	Three-dimensional medical imaging enables detailed understanding of osteoarthritis structural status. However, there remains a vast need for automatic, thus, reader-independent measures that provide reliable assessment of subject-specific clinical outcomes. To this end, we derive a consistent generalization of the recently proposed B-score to Riemannian shape spaces. We further present an algorithmic treatment yielding simple, yet efficient computations allowing for analysis of large shape populations with several thousand samples. Our intrinsic formulation exhibits improved discrimination ability over its Euclidean counterpart, which we demonstrate for predictive validity on assessing risks of total knee replacement. This result highlights the potential of the geodesic B-score to enable improved personalized assessment and stratification for interventions. Comment: To be published in: Proc. International Conference on Information Processing in Medical Imaging (IPMI) 2021
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2104.01107 Zobrazit plný text záznamu View this record from Arxiv