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Unwanted motion is a serious problem in enhancing servoing performance in an affected area, which incorporates stones/tumours in non-invasive ultrasound theragnostic systems (NIUTS). To solve this problem, we proposed a new method for restricting the motion of the affected area ventrodorsally in the region of interest (ROI) in ultrasound imaging. To do so, we introduce a bed mechanism for NIUTS. It is confirmed that a human kidney could be tracked and followed appropriately using the proposedmethod and the newly constructed bed system.

We have developed a non-invasive ultrasound theragnostic system (NIUTS) that tracks and follows the movement of an affected area (kidney stone/tumor, in this study) while irradiating it with high-intensity focused ultrasound (HIFU). In this paper, we propose a method to simplify extracting, tracking and following, monitoring the affected area by using a bed-type non-invasive ultrasound theragnostic system.

We have been studying the technologizing and digitalizing skills of the medical professionals in the medical diagnostics and therapeutics. The concept of technologizing and digitalizing medical skills involves extracting functions in medical professional skills and reconstructing and implementing these extracted functions in the mechanisms, controllers, and image-processing algorithms of the medical support system. In this paper, we focus on the kidney stone extraction skills of medical professionals by utilizing robot vision technology, and discuss a methodology for technologizing and digitalizing medical diagnostic and therapeutic skills for a non-invasive ultrasound theragnostic system.

This paper presents a real-time pose estimation method as a part of robotic HIFU treatment system for moving volumetric targets. For the acquired biplane US images, current pose of the preoperative model is calculated by iterative segmentation and registration. Seed contours for the segmentation in each iteration is provided by previously registered preoperative 3-D model. The segmented boundary points then update the pose of 3-D model. The boundary outlier-removal makes the algorithm robust against partially noisy boundaries as well as the spatial boundary points accelerates the algorithm to be calculated in real-time. By the phantom experiments, registration accuracy for a biplane US image data was evaluated, and the processing time was also investigated.

Background Applying ultrasound (US)-guided high-intensity focused ultrasound (HIFU) therapy for kidney tumours is currently very difficult, due to the unclearly observed tumour area and renal motion induced by human respiration. In this research, we propose new methods by which to track the indistinct tumour area and to compensate the respiratory tumour motion for US-guided HIFU treatment. Methods For tracking indistinct tumour areas, we detect the US speckle change created by HIFU irradiation. In other words, HIFU thermal ablation can coagulate tissue in the tumour area and an intraoperatively created coagulated lesion (CL) is used as a spatial landmark for US visual tracking. Specifically, the condensation algorithm was applied to robust and real-time CL speckle pattern tracking in the sequence of US images. Moreover, biplanar US imaging was used to locate the three-dimensional position of the CL, and a three-actuator system drives the end-effector to compensate for the motion. Finally, we tested the proposed method by using a newly devised phantom model that enables both visual tracking and a thermal response by HIFU irradiation. Results In the experiment, after generation of the CL in the phantom kidney, the end-effector successfully synchronized with the phantom motion, which was modelled by the captured motion data for the human kidney. The accuracy of the motion compensation was evaluated by the error between the end-effector and the respiratory motion, the RMS error of which was approximately 2 mm. Conclusion This research shows that a HIFU-induced CL provides a very good landmark for target motion tracking. By using the CL tracking method, target motion compensation can be realized in the US-guided robotic HIFU system. Copyright © 2011 John Wiley & Sons, Ltd.

The authors have investigated a construction methodology for a non-invasive ultrasound theragnostic system, called NIUTS, to track and follow moving body targets, such as tumors / stones located in moving organs (kidneys, livers, etc.), robustly and precisely, so as to compensate for nearly 90 percent of target motions in ultrasound images, while irradiating therapeutic ultrasound to focal lesions. In the present report, we propose a novel servo recovery algorithm for NIUTS. We confirm the effectiveness of the implemented servo recovery algorithm for a real human kidney, which, as far as we know, is the first successful report of semi-autonomous servo recovery systems for lost body targets. This robust servo recovery method could provide an indispensable tool for precise, safe, and efficient treatments of tumors and stones.

Information and robot technology (IRT) is drawing increasing attention in the technologizing and digitalizing of medical professional skills. In fields such as manufacturing, high-precision tasks, not possible with human, skills have been already realized by industrial robots. The medical field thus expected to advance with progress in the development of medical robots able to provide diagnosis and therapy that are much more precise than those of conventional medical professionals.Copyright © 2012 by ASME

We propose a non-invasive ultrasound theragnostic system that tracks movement in an affected area (kidney stones, in the present study) by irradiating the area with high-intensity focused ultrasound (HIFU). In the present paper, the concept behind a novel medical support system that integrates therapy and diagnostics (theragnostics) is illustrated. The required functions for the proposed system are discussed and an overview of the constructed system configuration is illustrated. The problems associated with kidney stone motion tracking by ultrasonography are described. In order to overcome these problems, we consider two approaches. The first approach is to minimize the servoing error so as to enhance both the efficiency of the therapy and the safety of the patient. The second approach is to reduce the effect of the servoing error. With respect to the first approach, we propose a robust detection method of the stone position based on shape information. With respect to the second approach, we propose a solution for controlling the HIFU irradiation power in accordance with the servoing error, primarily in order to enhance the safety of the patient.

Applying ultrasound (US)-guided high-intensity focused ultrasound (HIFU) therapy for kidney tumours is currently very difficult, due to the unclearly observed tumour area and renal motion induced by human respiration. In this research, we propose new methods by which to track the indistinct tumour area and to compensate the respiratory tumour motion for US-guided HIFU treatment.For tracking indistinct tumour areas, we detect the US speckle change created by HIFU irradiation. In other words, HIFU thermal ablation can coagulate tissue in the tumour area and an intraoperatively created coagulated lesion (CL) is used as a spatial landmark for US visual tracking. Specifically, the condensation algorithm was applied to robust and real-time CL speckle pattern tracking in the sequence of US images. Moreover, biplanar US imaging was used to locate the three-dimensional position of the CL, and a three-actuator system drives the end-effector to compensate for the motion. Finally, we tested the proposed method by using a newly devised phantom model that enables both visual tracking and a thermal response by HIFU irradiation.In the experiment, after generation of the CL in the phantom kidney, the end-effector successfully synchronized with the phantom motion, which was modelled by the captured motion data for the human kidney. The accuracy of the motion compensation was evaluated by the error between the end-effector and the respiratory motion, the RMS error of which was approximately 2 mm.This research shows that a HIFU-induced CL provides a very good landmark for target motion tracking. By using the CL tracking method, target motion compensation can be realized in the US-guided robotic HIFU system.