Aortic valve disorders are the most frequent form of valvular heart disorders (VHD) affecting nearly 3% of the global population. A large fraction among them are aortic root diseases, such as aortic root aneurysm, often requiring surgical procedures (valve-sparing) as a treatment. Visual non-invasive assessment techniques could assist during pre-selection of adequate patients, planning procedures and afterward evaluation of the same. However state of the art approaches try to model a rather short part of the aortic root, insufficient to assist the physician during intervention planning. In this paper we propose a novel approach for morphological and functional quantification of both the aortic valve and the ascending aortic root. A novel physiological shape model is introduced, consisting of the aortic valve root, leaflets and the ascending aortic root. The model parameters are hierarchically estimated using robust and fast learning-based methods. Experiments performed on 63 CT sequences (630 Volumes) and 21 single phase CT volumes demonstrated an accuracy of 1.39mm and a speed of 30 seconds (3D+t series) for this approach. To the best of our knowledge this is the first time a complete model of the aortic valve (including leaflets) and the ascending aortic root, estimated from CT, has been proposed.     «

Aortic valve disorders are the most frequent form of valvular heart disorders (VHD) affecting nearly 3% of the global population. A large fraction among them are aortic root diseases, such as aortic root aneurysm, often requiring surgical procedures (valve-sparing) as a treatment. Visual non-invasive assessment techniques could assist during pre-selection of adequate patients, planning procedures and afterward evaluation of the same. However state of the art approaches try to model a rather sho...     »