A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the extraction and classification of hand outlines
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
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Bone age assessment is a medical procedure to diagnose bone diseases, specifically, growth pathologies. As of today, it is carried out by visual inspection which, needless to say, is a tedious and time consuming action. Automated methods to carry out such a task are therefore desirable. In this paper we take a step in this direction by proposing the automatic detection of a set of anatomical landmarks in positions of interest in radiographs. Such landmarks will then be used to carry out a registration procedure described elsewhere to eventually come up with a bone age estimation. The algorithm finds the landmarks by performing a rough segmentation to find the finger axes and then intensity profiles along the axes are analyzed to locate joints between finger bones.