Robot Arm Orientation Compensation Algorithm for Reproducibility Enhancement in Lower Limb Ultrasound Examination

Albstract: Venous insufficiency in the lower limbs is a disease in which the veins have difficulty returning blood to the heart, and as the condition worsens, it can significantly adversely affect daily life. Ultrasound examination is a widely used approach due to its non-invasive nature, but conventional manual scanning is highly dependent on operator, resulting in inconsistent image quality and poor reproducibility. To address this issue, we first analyze the image similarity between a reference image and an image acquired during re-examination at the same contact point and evaluate image reproducibility using the Structural Similarity Index (SSIM). Subsequently, we propose an algorithm that optimizes the probe orientation in real-time to enhance the SSIM between reference image and current one. Discrepancies between reference and follow-up images, caused by factors such as contact variation or patient movement, are compensated by adjusting the roll and pitch angles of the probe using a gradient ascent method based on SSIM. The proposed method is expected to obtain more consistent ultrasound image, leading to reliable follow-up diagnosis by monitoring the target vessels or tissues within the image.