13 March 2013 Development of a novel constellation based landmark detection algorithm
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Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86693F (2013) https://doi.org/10.1117/12.2006471
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Anatomical landmarks such as the anterior commissure (AC) and posterior commissure (PC) are commonly used by researchers for co-registration of images. In this paper, we present a novel, automated approach for landmark detection that combines morphometric constraining and statistical shape models to provide accurate estimation of landmark points. This method is made robust to large rotations in initial head orientation by extracting extra information of the eye centers using a radial Hough transform and exploiting the centroid of head mass (CM) using a novel estimation approach. To evaluate the effectiveness of this method, the algorithm is trained on a set of 20 images with manually selected landmarks, and a test dataset is used to compare the automatically detected against the manually detected landmark locations of the AC, PC, midbrain-pons junction (MPJ), and fourth ventricle notch (VN4). The results show that the proposed method is accurate as the average error between the automatically and manually labeled landmark points is less than 1 mm. Also, the algorithm is highly robust as it was successfully run on a large dataset that included different kinds of images with various orientation, spacing, and origin.
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Ali Ghayoor, Ali Ghayoor, Jatin G. Vaidya, Jatin G. Vaidya, Hans J. Johnson, Hans J. Johnson, "Development of a novel constellation based landmark detection algorithm", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693F (13 March 2013); doi: 10.1117/12.2006471; https://doi.org/10.1117/12.2006471

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