Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular ***,the manual calculation of these parameters is challenging due to the high variability am...
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Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular ***,the manual calculation of these parameters is challenging due to the high variability among patients and the time-consuming nature of the *** this study,the authors introduce a framework named MultiJSQ,comprising the feature presentation network(FRN)and the indicator prediction network(IEN),which is designed for simultaneous jointsegmentation and *** FRN is tailored for representing global image features,facilitating the direct acquisition of left ventricle(LV)contour images through pixel ***,the IEN incorporates specifically designed modules to extract relevant clinical *** authors’method considers the interdependence of different tasks,demonstrating the validity of these relationships and yielding favourable *** extensive experiments on cardiac MR images from 145 patients,MultiJSQ achieves impressive outcomes,with low mean absolute errors of 124 mm^(2),1.72 mm,and 1.21 mm for areas,dimensions,and regional wall thicknesses,respectively,along with a Dice metric score of *** experimental findings underscore the excellent performance of our framework in LV segmentation and quantification,highlighting its promising clinical application prospects.
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