Anatomical triangulation: from sparse landmarks to dense annotation of the skeleton in CT images

Marie Bieth, Rene Donner, Georg Langs, Markus Schwaiger and Bjoern Menze

Abstract

The automated annotation of bones that are visible in CT images of the skeleton is a challenging task which has, so far, been approached for only certain subregions of the skeleton, such as the spine or hip. In this paper, we propose a novel annotation algorithm for automatically identifying structures and substructures in the whole skeleton. Our annotation algorithm makes use of recent advances in anatomical landmarks detection and is capable of generalising local information about landmarks to a dense label map of the full skeleton by anatomical triangulation. We follow a recognition approach that combines the use of distance-based features for measuring Euclidean and geodesic distances to a few given landmark locations, a parts-based model that is disambiguating anatomical substructures, and an iterative scheme for considering distances to the previously detected structures and, hence, to a dense set of anatomical reference points. We propose an annotation protocol for 136 substructures of the skeleton and test our annotation algorithm on 18 CT images. On average, we obtain a Dice score of 90.54.

Session

Medical Applications

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DOI

10.5244/C.29.84
https://dx.doi.org/10.5244/C.29.84

Citation

Marie Bieth, Rene Donner, Georg Langs, Markus Schwaiger and Bjoern Menze. Anatomical triangulation: from sparse landmarks to dense annotation of the skeleton in CT images. In Xianghua Xie, Mark W. Jones, and Gary K. L. Tam, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 84.1-84.10. BMVA Press, September 2015.

Bibtex

@inproceedings{BMVC2015_84,
	title={Anatomical triangulation: from sparse landmarks to dense annotation of the skeleton in CT images},
	author={Marie Bieth and Rene Donner and Georg Langs and Markus Schwaiger and Bjoern Menze},
	year={2015},
	month={September},
	pages={84.1-84.10},
	articleno={84},
	numpages={10},
	booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
	publisher={BMVA Press},
	editor={Xianghua Xie, Mark W. Jones, and Gary K. L. Tam},
	doi={10.5244/C.29.84},
	isbn={1-901725-53-7},
	url={https://dx.doi.org/10.5244/C.29.84}
}