The article "Automatic detection of anatomical landmarks of the aorta in CTA images", has been published in the journal Medical & Biological Engineering & Computing (MBEC) from Springer Nature. MBEC is an official journal of the International Federation of Medical and Biological Engineering (IFMBE). The work described in this paper is the result of a collaboration between researchers from the University of Santiago de Compostela and from CTIM, R&D Center belonging to the University of Las Palmas de Gran Canaria.

In this article, the authors demonstrate the feasibility of a fully automated technology for the accurate detection and identification of several anatomical reference points (landmarks), commonly used in intravascular imaging. This technology uses two different approaches, specially designed for the detection of the aortic root and supra-aortic and visceral branches. In order to adjust the parameters of the developed algorithms, a total of 33 computed tomography scans with different types of pathologies were selected. Furthermore, a total of 30 independently selected computed tomography scans were used to assess their performance. Accuracy was evaluated by comparing the locations of reference points manually marked by human experts with those that were automatically detected. For supra-aortic and visceral branches detection, average values of 91.8 % for recall and 98.8 % for precision were obtained. For aortic root detection, the average difference between the positions marked by the experts and those detected by the computer was 5.7 ± 7.3 mm. Finally, diameters and lengths of the aorta were measured at different locations related to the extracted landmarks. Those measurements agreed with the values reported by the literature.

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