Physicians use ultrasound scans to do diagnosis by making real-time images of internal organs, because such scans are safe, inexpensive, and non-invasive. However, aging society and limited numbers of physician make it difficult for patients in remote areas to be diagnosed. Besides, physician's technical skills affect the interpretation of the scans and thus the results of the examination. Thus, development of a robotic system for remote diagnosis is required to solve the problems. For this purpose, we proposed the development of a robotic system for automatic ultrasound imaging focusing on human liver. In this paper, we present several elements developed for the robotic system. First element is an algorithm for estimating the position of liver to guide the probe to scan initial position which is the epigastric region. Second element is ultrasound probe scanning protocol design to obtain whole image of the liver. Third element is force control algorithm to maintain the contact between the probe and human body even though the patient is breathing. Fourth element is an algorithm for detecting and correcting the probe's position when improper ultrasound images occurred. These algorithms with an implementation program control the apparatus: a Mitsubishi Electric's MELFA RV-1 six axis manipulator and tested on human subjects. The results confirmed the effectiveness of the approach.
Physicians use ultrasound scans to obtain real-time images of internal organs, because such scans are safe and inexpensive. However, people in remote areas face difficulties to be scanned due to aging society and physician's shortage. Hence, it is important to develop an autonomous robotic system to perform remote ultrasound scans. Previously, we developed a robotic system for automatic ultrasound scan focusing on human's liver. In order to make it a completely autonomous system, we present in this paper a way to autonomously localize the epigastric region as the starting position for the automatic ultrasound scan. An image processing algorithm marks the umbilicus and mammary papillae on a digital photograph of the patient's abdomen. Then, we made estimation for the location of the epigastric region using the distances between these landmarks. A supporting algorithm distinguishes rib position from epigastrium using the relationship between force and displacement. We implemented these algorithms with the automatic scanning system into an apparatus: a Mitsubishi Electric's MELFA RV-1 six axis manipulator. Tests on 14 healthy male subjects showed the apparatus located the epigastric region with a success rate of 94%. The results suggest that image recognition was effective in localizing a human body part.
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