Improved MOSSE coronary target tracking algorithm based on feature fusion
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TN20

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    Abstract:

    Computed tomography angiography(CTA), as a non-invasive detection with higher accuracy auxiliary diagnostic method, now is urgently needed to effectively eliminate the interference noise near the coronary artery target and to find a new algorithm that can fully automatic, fast and accurate tracking the target, so as to greatly reduce the pressure on doctors to read the film and assist them in reliable diagnosis and treatment. A new minimum output sum of squared error (MOSSE) algorithm was proposed to achieve automatic accurate and fast tracking of coronary targets by extracting multiple features of coronary arteries and incorporating them into the existing MOSSE tracking method. CTA data from 9 patients (5 males and 4 females, average age 65, 6 with atherosclerosis) in Affiliated Hospital of Hebei University were used to verify the algorithm, and the results were compared with existing coronary target extraction algorithms based on centerline and regional growth. Results show that the new algorithm processing track patient frame data only takes 0. 02 s, the average accuracy of multiple cases was 94. 30%, and the performance is better than the existing coronary target extraction algorithm, it realizes automatic accurate efficient tracking to form severe coronary target change, and provides more efficient assistance to the clinical diagnosis and treatment of coronary heart disease (CHD).

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  • Received:
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  • Online: February 27,2023
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