12 March 2015 An MRI myocarditis index defined by a PCA-based object recognition algorithm
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Abstract
Magnetic Resonance Imaging (MRI) has shown promising results in diagnosing myocarditis that can be qualitatively observed as enhanced pixels on the cardiac muscles images. In this paper, a myocarditis index, defined as the ratio between enhanced pixels, representing an inflammation, and the total pixels of myocardial muscle, is presented. In order to recognize and quantify enhanced pixels, a PCA-based recognition algorithm is used. The algorithm, implemented in Matlab, was tested by examining a group of 10 patients, referred to MRI with presumptive, clinical diagnosis of myocarditis. To assess intra- and interobserver variability, two observers blindly analyzed data related to the 10 patients by delimiting myocardial region and selecting enhanced pixels. After 5 days the same observers redid the analysis. The obtained myocarditis indexes were compared to an ordinal variable (values in the 1 - 5 range) that represented the blind assessment of myocarditis seriousness given by two radiologists on the base of the patient case histories. Results show that there is a significant correlation (P < 0:001; r = 0:94) between myocarditis indexes and the radiologists' clinical judgments. Furthermore, a good intraobserver and interobserver reproducibility was obtained.
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Rocco Romano, Rocco Romano, Igino De Giorgi, Igino De Giorgi, Fausto Acernese, Fausto Acernese, Gerardo Giordano, Gerardo Giordano, Antonio Orientale, Antonio Orientale, Giovanni Babino, Giovanni Babino, Fabrizio Barone, Fabrizio Barone, } "An MRI myocarditis index defined by a PCA-based object recognition algorithm", Proc. SPIE 9401, Computational Imaging XIII, 94010K (12 March 2015); doi: 10.1117/12.2082547; https://doi.org/10.1117/12.2082547
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