Remote control intervention surgery robotic system improves treatment effect on cardiovascular patients and reduces X-ray exposure. However, at the time of the first procedure, CT (computerized tomography) and other ultrasound diagnostic equipment should be used because the operator must insert the cannula directly into the patient's leg. Improvements to this have been un-met-needs of hospitals. In this paper, we developed a system that can insert the cannula intuitively and quickly by displaying blood vessels at a glance through the system using smart wearable glasses. The core development method is as follows. In order to project augmented reality onto the surgical image, CT scan angiography image is extracted and processed. In the process, three CT-Markers are used to create a coordinate system of blood vessel images. Additionally, a reference marker is photographed on a single camera to obtain a camera coordinate system. Since the CT marker and the reference marker are in the same position, 3D registration is performed. In the text, a detailed explanation will be given.

Purpose: The purpose of this study was to evaluate the effect according to the NEX, VENC, targeted cardiac phases on the velocity measurement of 4D phase-contrast MRI. Materials and Methods: The abdominal aortic phantom was made to experiment. The working fluid was mixed with water and glycerin to mimic the density and viscosity of human blood. The inlet velocity was Reynolds number 2000. The experimental conditions were NEX 1 and 4, VENC 102 cm/s and 200 cm/s, and 10 and 15 targeted cardiac phases, respectively. The average flow rate, average velocity, maximum velocity, and cross-section area were measured. Results: As a result of the case-by-case comparison, the error rate was less than 5%. There was no significant difference (p > 0.05). Conclusion: It is expected that this result will be useful for acquiring blood flow information in clinical practice.

Arrhythmia is basically diagnosed with the electrocardiogram (ECG) signal, however, ECG is difficult to measure and it requires expert help in analyzing the signal. On the other hand, the radial pulse can be measured with easy and uncomplicated way in daily life, and could be suitable bio-signal for the recent untact paradigm and extensible signal for diagnosis of Korean medicine based on pulse pattern. In this study, we developed an irregular radial pulse detection algorithm based on a learning model and considered its applicability as arrhythmia screening. A total of 1432 pulse waves including irregular pulse data were used in the experiment. Three data sets were prepared with minimal preprocessing to avoid the heuristic feature extraction. As classification algorithms, elastic net logistic regression, random forest, and extreme gradient boosting were applied to each data set and the irregular pulse detection performances were estimated using area under the receiver operating characteristic curve based on a 10-fold cross-validation. The extreme gradient boosting method showed the superior performance than others and found that the classification accuracy reached 99.7%. The results confirmed that the proposed algorithm could be used for arrhythmia screening. To make a fusion technology integrating western and Korean medicine, arrhythmia subtype classification from the perspective of Korean medicine will be needed for future research.

Needle detection in ultrasound images is sometimes difficult due to obstruction of fat tissues. Accurate needle detection using continuous ultrasound (CUS) images is a vital stage of treatment planning for tissue biopsy and brachytherapy. The main goal of the study is classified into two categories. First, new detection model, i.e. D-Attention Unet, is developed by combining the context information of 3D medical data and CUS images. Second, the D-Attention Unet model was compared with other models to verify its usefulness for needle detection in continuous ultrasound images. The continuous needle images taken with ultrasonic waves were converted into still images for dataset to evaluate the performance of the D-Attention Unet. The dataset was used for training and testing. Based on the results, the proposed D-Attention Unet model showed the better performance than other 3 models (Unet, D-Unet and Attention Unet), with Dice Similarity Coefficient (DSC), Recall and Precision at 71.9%, 70.6% and 73.7%, respectively. In conclusion, the D-Attention Unet model provides accurate needle detection for US-guided biopsy or brachytherapy, facilitating the clinical workflow. Especially, this kind of research is enthusiastically being performed on how to add image processing techniques to learning techniques. Thus, the proposed method is applied in this manner, it will be more effective technique than before.

As the number of people with gait disorders increases, the demand for using wheelchairs increases and the area of a ctivity for people with disabilities expands, thereby they increasing the demand for riding comfortability in various driving environments. Therefore, this study is to develop an entry-level active suspension system that apply to wheelchairs and to evaluate its usability. The suspension applied in this paper consists of a coil spring, a shock absorber, a control module to control the strength of the shock absorber, and a road surface condition monitoring system. A wheelchair occupant secures the riding comfort by adjusting the coil strength of the shock absorber in 12 steps according to various road conditions. Therefore, the mechanical properties were evaluated through the structural analysis of the suspension system, and the tendency toward the magnitude of the road surface vibration attenuated according to the rigidity of the suspension through the vibration test was attempted. In conclusion, as a result of structural analysis of the suspension system, stress in a range lower than the yield strength of the material was generated, and the vibration test showed the effect of attenuating the vibration generated from the road surface when the stiffness of the suspension was adjusted.

Vessel sealing is a medical device that converts electrical or ultrasonic energy into thermal energy and leads to seal, coagulate, and cut the vessel by protein modification within the walls or surrounding connective tissues. As most of surgeries have recently been conducted with minimally invasive surgery, the demand and market for vessel sealing are expected to get bigger. However, there is a problem that electrosurgical or ultrasonic surgical is applied and we have a high risk to evaluate the strength of seal, because the collateral and particular standards currently in force follows have not been establish. Therefore, in this study, we investigated some papers studied on the efficacy and safety of the device, the guidance of FDA and test papers previously conducted from 3 individual subject device made in Korea. We found there is a relationship between burst pressure and the performance of the device, therefore, we propose the vascular bursting pressure test for evaluating the safety and performance of the vessel sealing.