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Does a CNN-based deep learning solution accurately detect the left ventricle in arterial input function images for inline perfusion mapping?
Does a CNN-based deep learning solution accurately detect the left ventricle in arterial input function images for inline perfusion mapping?
A deep learning CNN-based solution can detect the left ventricle blood pool in arterial input function images with near-perfect accuracy (99.98%), facilitating automated inline perfusion mapping.
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Enables automated inline perfusion mapping; leaves open prospective validation before clinical adoption.
A CNN-based solution to detect the LV blood pool from the arterial input function image series was developed, validated, and deployed. A high LV detection accuracy of 99.98% was achieved.
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Xue et al. (2020) studied this question.
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