Interest Points Localization for Brain Image Using Landmark-Annotated Atlas

摘要

The localization of clinically important points in brain images is crucial for many neurological studies. Conventional manual landmark annotation requires expertise and is often time-consuming. In this work, we propose an automatic approach for interest point localization in brain image using landmark-annotated atlas (LAA). The landmark detection procedure is formulated as a problem of finding corresponding points of the atlas. The LAA is constructed from a set of brain images with clinically relevant landmarks annotated. It provides not only the spatial information of the interest points of the brain but also the optimal features for landmark detection through a learning process. Evaluation was performed on 3D magnetic resonance (MR) data using cross-validation. Obtained results demonstrate that the proposed method achieves the accuracy of ～ 2 mm, which outperforms the traditional methods such as block matching technique and direct image registration.