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APPARATUS AND METHOD FOR LEARNING PERIPHERAL ARTERY DIAGNOSIS IMAGE, DIAGNOSIS APPARATUS AND METHOD FOR PERIPHERAL LESION ARTERY HAVING SIGNIFICANT DIFFRENCES USING THE LEARNING MODEL COSTRUCTED BY THE SAME
APPARATUS AND METHOD FOR LEARNING PERIPHERAL ARTERY DIAGNOSIS IMAGE, DIAGNOSIS APPARATUS AND METHOD FOR PERIPHERAL LESION ARTERY HAVING SIGNIFICANT DIFFRENCES USING THE LEARNING MODEL COSTRUCTED BY THE SAME
According to the present invention, an apparatus for diagnosing peripheral arterial disease based on artificial intelligence may be provided. The artificial intelligence-based peripheral artery stenosis diagnosis apparatus includes a data input unit for inputting a peripheral artery image based on an angiographic image of a diagnosis area including the peripheral artery, and the peripheral artery image acquired based on a predetermined time unit. A peripheral artery image interpolation unit having an interpolation image learning model for constructing a learning-based sub-peripheral artery image based on a change in motion, and generating a sub-peripheral artery image corresponding to the peripheral artery image using the interpolated image learning model. And a peripheral artery image analysis unit for analyzing significant peripheral artery disease by checking information provided from the data input unit and the peripheral artery image interpolation unit.
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