9 March 2011 Automatic evaluation of the Valsalva sinuses from cine-MRI
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Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79620A (2011) https://doi.org/10.1117/12.877673
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States
Abstract
MRI appears to be particularly attractive for the study of the Sinuses of Valsalva (SV), however there is no global consensus on their suitable measurements. In this paper, we propose a new method, based on the mathematical morphology and combining a numerical geodesic reconstruction with an area estimation, to automatically evaluate the SV from a cine-MRI in a cross-sectional orientation. It consists in the extraction of the shape of the SV, the detection of relevant points (commissures, cusps and the centre of the SV), the measurement of relevant distances and in a classification of the valve as bicuspid or tricuspid by a metric evaluation of the SV. Our method was tested on 23 patient examinations and radii calculations were compared with a manual measurement. The classification of the valve as tricuspid or bicuspid was correct for all the cases. Moreover, there are an excellent correlation and an excellent concordance between manual and automatic measurements for images at diastolic phase (r= 0.97; y = x - 0.02; p=NS; mean of differences = -0.1 mm; standard deviation of differences = 2.3 mm) and at systolic phase (r= 0.96; y = 0.97 x + 0.80; p=NS ; mean of differences = -0.1 mm; standard deviation of differences = 2.4 mm). The cross-sectional orientation of the image acquisition plane conjugated with our automatic method provides a reliable morphometric evaluation of the SV, based on the automatic location of the centre of the SV, the commissure and the cusp positions. Measurements of distances between relevant points allow a precise evaluation of the SV.
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Cédric Blanchard, Tadeusz Sliwa, Alain Lalande, Pauliah Mohan, Olivier Bouchot, Yvon Voisin, "Automatic evaluation of the Valsalva sinuses from cine-MRI", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79620A (9 March 2011); doi: 10.1117/12.877673; https://doi.org/10.1117/12.877673
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