Detection of Organs and Identification of Missing Diagnostic Images Using Deep Learning for Assessment of Diagnostic Image Adequacy

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  • 診断画像適正度の評価のための深層学習を用いた臓器の検出と診断画像欠損部の同定

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<p>The purpose of this study was to evaluate the appropriateness of diagnostic images for automated ultrasound operations. Therefore, two experiments were conducted. The first is to detect the target organ using deep learning. The second is to identify missing parts in the diagnostic images. In the first experiment of organ detection, the IoU and Dice coefficient were 0.947 and 0.972, respectively, indicating high accuracy.In the second experiment to identify the missing parts of the image, the percentage of correct answers for the missing parts on the right side of m was 75.3%, while the percentage of correct answers for the missing parts on the left side was 99.1%.</p>

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