Statistical approach to anatomical landmark extraction in AP radiographs

A novel method for the automated extraction of important geometrical parameters of the pelvis and hips from APR images is presented. The shape and intensity variations in APR images are encompassed by the statistical shape and appearance models built from a set of training images for each of the three anatomies, i.e., pelvis, right and left hip, separately. The identification of the pelvis and hips is defined as a flexible object recognition problem, which is solved by generating anatomically plausible object instances and matching them to the APR image. The criterion function minimizes the resulting match error and considers the object topology. The obtained flexible object defines the positions of anatomical landmarks, which are further used to calculate the hip joint contact stress. A leave-one-out test was used to evaluate the performance of the proposed method on a set of 26 APR images. The results show the method is able to properly treat image variations and can reliably and accurately identify anatomies in the image and extract the anatomical landmarks needed in the hip joint contact stress calculation.

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