A single scan skeletonization algorithm: application to medical imaging of trabecular bone

Aurore Arlicot; Yves Amouriq; Pierre Evenou; Nicolas Normand; Jean-Pierre Guédon

doi:10.1117/12.844250

12 March 2010 A single scan skeletonization algorithm: application to medical imaging of trabecular bone

Aurore Arlicot, Yves Amouriq, Pierre Evenou, Nicolas Normand, Jean-Pierre Guédon

Proceedings Volume 7623, Medical Imaging 2010: Image Processing; 762317 (2010) https://doi.org/10.1117/12.844250
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

Shape description is an important step in image analysis. The skeleton is used as a simple, compact representation of a shape. A skeleton represents the line centered in the shape and must be homotopic and one point wide. Current skeletonization algorithms compute the skeleton over several image scans, using either thinning algorithms or distance transforms. The principle of thinning is to delete points as one goes along, preserving the topology of the shape. On the other hand, the maxima of the local distance transform identifies the skeleton and is an equivalent way to calculate the medial axis. However, with this method, the skeleton obtained is disconnected so it is required to connect all the points of the medial axis to produce the skeleton. In this study we introduce a translated distance transform and adapt an existing distance driven homotopic algorithm to perform skeletonization with a single scan and thus allow the processing of unbounded images. This method is applied, in our study, on micro scanner images of trabecular bones. We wish to characterize the bone micro architecture in order to quantify bone integrity.

Citation Download Citation

Aurore Arlicot, Yves Amouriq, Pierre Evenou, Nicolas Normand, and Jean-Pierre Guédon "A single scan skeletonization algorithm: application to medical imaging of trabecular bone", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762317 (12 March 2010); https://doi.org/10.1117/12.844250

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