深層学習に基づく臓器追従および超音波画像の適正度評価に関する研究

抄録

Ultrasound-based diagnoses' quality depends on the physician's skill in handling the probe, which can be affected by patient respiratory motions. To address this, a diagnostic robot with a deep learning-based visual servo system was developed. It uses two image processing methods, BiSeNet V2 for target kidney location detection and ResNet 50 for evaluating ultrasound image appropriateness, aiming to alleviate burdens on physicians.