Fusion of 4D echocardiography and cine cardiac magnetic resonance volumes using a salient spatio-temporal analysis

Angélica Atehortúa; Mireille Garreau; Eduardo Romero

doi:10.1117/12.2285956

17 November 2017 Fusion of 4D echocardiography and cine cardiac magnetic resonance volumes using a salient spatio-temporal analysis

Angélica Atehortúa, Mireille Garreau, Eduardo Romero

Author Affiliations +

Proceedings Volume 10572, 13th International Conference on Medical Information Processing and Analysis; 105721A (2017) https://doi.org/10.1117/12.2285956
Event: 13th International Symposium on Medical Information Processing and Analysis, 2017, San Andres Island, Colombia

Abstract

An accurate left (LV) and right ventricular (RV) function quantification is important to support evaluation, diagnosis and prognosis of cardiac pathologies such as the cardiomyopathies. Currently, diagnosis by ultrasound is the most cost-effective examination. However, this modality is highly noisy and operator dependent, hence prone to errors. Therefore, fusion with other cardiac modalities may provide complementary information and improve the analysis of the specific pathologies like cardiomyopathies. This paper proposes an automatic registration between two complementary modalities, 4D echocardiography and Magnetic resonance images, by mapping both modalities to a common space of salience where an optimal registration between them is estimated. The obtained matrix transformation is then applied to the MRI volume which is superimposed to the 4D echocardiography. Manually selected marks in both modalities are used to evaluate the precision of the superimposition. Preliminary results, in three evaluation cases, show the distance between these marked points and the estimated with the transformation is about 2 mm.

Citation Download Citation

Angélica Atehortúa, Mireille Garreau, and Eduardo Romero "Fusion of 4D echocardiography and cine cardiac magnetic resonance volumes using a salient spatio-temporal analysis", Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105721A (17 November 2017); https://doi.org/10.1117/12.2285956

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