Bone age assessment is a task performed daily in hospitals worldwide, this involves a clinician estimating the age of a patient from a radiograph of the non-dominant hand. In this paper, we propose a combination of image processing and feature extraction algorithms to automatically predict the Tanner-Whitehouse bone stage, the assessment standard used in forming bone age estimates.
|Title of host publication||Intelligent Data Engineering and Automated Learning - IDEAL 2012|
|Number of pages||9|
|Publication status||Published - 2012|
|Name||Lecture Notes in Computer Sciences|