6,246 research outputs found

    Autofluorescence lifetime augmented reality as a means for real-time robotic surgery guidance in human patients.

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    Due to loss of tactile feedback the assessment of tumor margins during robotic surgery is based only on visual inspection, which is neither significantly sensitive nor specific. Here we demonstrate time-resolved fluorescence spectroscopy (TRFS) as a novel technique to complement the visual inspection of oral cancers during transoral robotic surgery (TORS) in real-time and without the need for exogenous contrast agents. TRFS enables identification of cancerous tissue by its distinct autofluorescence signature that is associated with the alteration of tissue structure and biochemical profile. A prototype TRFS instrument was integrated synergistically with the da Vinci Surgical robot and the combined system was validated in swine and human patients. Label-free and real-time assessment and visualization of tissue biochemical features during robotic surgery procedure, as demonstrated here, not only has the potential to improve the intraoperative decision making during TORS but also other robotic procedures without modification of conventional clinical protocols

    Towards automated visual flexible endoscope navigation

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    Background:\ud The design of flexible endoscopes has not changed significantly in the past 50 years. A trend is observed towards a wider application of flexible endoscopes with an increasing role in complex intraluminal therapeutic procedures. The nonintuitive and nonergonomical steering mechanism now forms a barrier in the extension of flexible endoscope applications. Automating the navigation of endoscopes could be a solution for this problem. This paper summarizes the current state of the art in image-based navigation algorithms. The objectives are to find the most promising navigation system(s) to date and to indicate fields for further research.\ud Methods:\ud A systematic literature search was performed using three general search terms in two medicalโ€“technological literature databases. Papers were included according to the inclusion criteria. A total of 135 papers were analyzed. Ultimately, 26 were included.\ud Results:\ud Navigation often is based on visual information, which means steering the endoscope using the images that the endoscope produces. Two main techniques are described: lumen centralization and visual odometry. Although the research results are promising, no successful, commercially available automated flexible endoscopy system exists to date.\ud Conclusions:\ud Automated systems that employ conventional flexible endoscopes show the most promising prospects in terms of cost and applicability. To produce such a system, the research focus should lie on finding low-cost mechatronics and technologically robust steering algorithms. Additional functionality and increased efficiency can be obtained through software development. The first priority is to find real-time, robust steering algorithms. These algorithms need to handle bubbles, motion blur, and other image artifacts without disrupting the steering process

    Alternative Applications of Trans-Oral Robotic Surgery (TORS): A Systematic Review

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    The role of robotic surgery in the field of oncology has been widely described, in particular for the tumours of the oropharynx and larynx, but its efficacy for benign pathology is inconsistent

    Snake-Like Robots for Minimally Invasive, Single Port, and Intraluminal Surgeries

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    The surgical paradigm of Minimally Invasive Surgery (MIS) has been a key driver to the adoption of robotic surgical assistance. Progress in the last three decades has led to a gradual transition from manual laparoscopic surgery with rigid instruments to robot-assisted surgery. In the last decade, the increasing demand for new surgical paradigms to enable access into the anatomy without skin incision (intraluminal surgery) or with a single skin incision (Single Port Access surgery - SPA) has led researchers to investigate snake-like flexible surgical devices. In this chapter, we first present an overview of the background, motivation, and taxonomy of MIS and its newer derivatives. Challenges of MIS and its newer derivatives (SPA and intraluminal surgery) are outlined along with the architectures of new snake-like robots meeting these challenges. We also examine the commercial and research surgical platforms developed over the years, to address the specific functional requirements and constraints imposed by operations in confined spaces. The chapter concludes with an evaluation of open problems in surgical robotics for intraluminal and SPA, and a look at future trends in surgical robot design that could potentially address these unmet needs.Comment: 41 pages, 18 figures. Preprint of article published in the Encyclopedia of Medical Robotics 2018, World Scientific Publishing Company www.worldscientific.com/doi/abs/10.1142/9789813232266_000

    Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

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    Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

    ๋กœ๋ด‡์„ ์ด์šฉํ•œ ์ž์œจ์  ํ•˜์•…๊ณจ์ฑ„์ทจ ๊ณจ์ ˆ๋‹จ์ˆ ์˜ ๊ธฐ์ดˆ๋ฐฉ๋ฒ• ๊ฐœ๋ฐœ๊ณผ ๊ทธ ์ •ํ™•๋„ ํ‰๊ฐ€

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์น˜์˜ํ•™๋Œ€ํ•™์› ์น˜์˜๊ณผํ•™๊ณผ, 2019. 2. ๊น€์„ฑ๋ฏผ.Objectives: An autonomous robot osteotomy system using direct coordinate determination was developed in our study. The registration accuracy was evaluated by measuring the fiducial localization error (FLE) and target registration error (TRE) and the accuracy of the designed osteotomy method along a preprogrammed plan was evaluated. Furthermore, the accuracy of the robotic osteotomy and a manual osteotomy was compared in regard to cut position, length, angle and depth. Methods: A light-weight-robot was used in this study, with an electric gripper. A direct coordinate determination method, using three points on the teeth, was developed for registration and determination of FLE and TRE, as measured on a mandible model. Sixteen landmarks on the mandible were prepared with holes and zirconia beads and the TRE was computed in ten repeated measurements using the robot. A direct coordinate determination via three points was used for registering and a twenty stone model (7 cm x 7 cm x 3 cm). The osteotomy line was designed similar to the ramal bone graft (2 cm x 1 cm x 0.5 cm). To evaluate accuracy, we measured a position (how accurate the robot arm is located), length (how accurate the robot arm is moving while cutting), angle (the angle at which the robot arm is located), and depth (the depth of the disc cutting) error. Sixteen mandible phantoms were used to simulate the osteotomy for the ramus bone graft. An image of the phantom was obtained by three-dimensional camera scanning and a virtual ramal bone graft was designed with computer software. To evaluate an accuracy and precision, the mandible phantoms were scanned with cone beam computer tomography (CBCT). Cut position, length, angle and depth errors were measured and the results of the robotic surgery were compared with that of manual surgery. Results: The mean value of the FLE was 0.84 ยฑ 0.38 mm and the third reference point which detected the lingual fossa of the right second molar had a larger error than the other reference points. The mean value of the TRE was 1.69 ยฑ 0.82 mm and there were significant differences between the anterior body, posterior body, and coronoid/condyle groups. Landmarks at the anterior body had the lowest TRE (0.96 ยฑ 0.47 mm) and landmarks on the coronoid and condyle had the highest TRE (2.12 ยฑ 0.99 mm). An autonomous robot osteotomy with a direct coordinate determination using three points was successfully achieved. On the model RBG osteotomy, the posterior cut had 0.77ยฑ0.32 absolute mean value, the anterior cut had 0.82ยฑ0.43, the inferior cut had 0.76 ยฑ 0.38 and the superior cut had 1.37 ยฑ 0.83, respectively. The absolute mean values for osteotomy errors for position, length, angle, and depth were 0.93 ยฑ 0.45 mm, 0.81 ยฑ 0.34 mm, 1.26 ยฑ 1.35ยฐ, and 1.19 ยฑ 0.73 mm, respectively. The position and length errors were significantly lower than angle and depth errors. In the comparison between robotic surgery and manual surgery, there were significant differences of absolute mean value and variance in all categories. For the robotic surgery, the cut position, length, angle and depth errors were 0.70 ยฑ 0.34 mm, 0.35 ยฑ 0.19 mm, 1.32 ยฑ 0.96ยฐ and 0.59 ยฑ 0.46 mm, respectively. For the manual surgery, the cut position, length, angle and depth errors were 1.83 ยฑ 0.65 mm, 0.62 ยฑ 0.37 mm, 5.96 ยฑ 3.47ยฐ and 0.40 ยฑ 0.31 mm, respectively. The robotic surgery had significantly higher accuracy and lower variance for cut position, length and angle errors. On the other hand, the depth error had a significantly higher absolute mean value and variance than the robotic surgery. Conclusions: An autonomous robot osteotomy scheme was developed, using the direct coordinate determination by three points on the teeth, and proved an accurate method for registration. The incisal edge or buccal pit of the teeth were more proper reference points than the fossa of the teeth. The measured RMS of the TRE increased when the target moved away from the reference points. Robotic surgery showed high accuracy and precision in positioning and reduced accuracy in controlling the depth of disc sawing. The robotic surgery showed high accuracy and precision in positioning and somewhat low accuracy in controlling the depth of the disc sawing. Comparing robotic and manual surgeries, the robotic surgery was superior in accuracy and precision in position, length and angle. However, the manual surgery had higher accuracy and precision in depth.1. ๋ชฉ ์  ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์„ธ ์  ์ ‘์ด‰์„ ํ†ตํ•œ ์ขŒํ‘œ ๊ฒฐ์ • ๋ฐฉ์‹์„ ํ†ตํ•ด ์‹ค์ œ ๋ชจ๋ธ์˜ ์ขŒํ‘œ์™€ ๋กœ๋ด‡์ด ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์ขŒํ‘œ๋ฅผ ์ •ํ•ฉํ•˜๋Š” ๋ฐฉ์‹์„ ์ด์šฉํ•˜์—ฌ ์ž์œจ ๋กœ๋ด‡์„ ์ด์šฉํ•œ ํ•˜์•…๊ณจ์ฑ„์ทจ ๊ณจ์ ˆ๋‹จ์ˆ ์˜ ๊ธฐ์ดˆ๋ฐฉ๋ฒ•์„ ๊ฐœ๋ฐœํ•˜๊ณ ์ž ํ•œ๋‹ค. ๊ฐœ๋ฐœ๋œ ์ •ํ•ฉ ๋ฐฉ๋ฒ•์˜ ์œ„์น˜ ์ถ”์  ์˜ค๋ฅ˜ (fiducial localization error)์™€ ๋ชฉํ‘œ ์ •ํ•ฉ ์˜ค๋ฅ˜ (target registration error)๋ฅผ ์ธก์ •ํ•˜์—ฌ ์ •ํ•ฉ์˜ ์ •ํ™•์„ฑ์„ ํ‰๊ฐ€ํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋˜ํ•œ ์‚ฌ์ „์— ํ”„๋กœ๊ทธ๋ž˜๋ฐ๋œ ๊ณจ์ ˆ๋‹จ์„ ์ง์œก๋ฉด์ฒด ๋ชจ๋ธ์— ์‹œํ–‰ํ•˜๊ณ  ์œ„์น˜, ๊ธธ์ด, ๊ฐ๋„, ๊นŠ์ด์˜ ์˜ค๋ฅ˜๋ฅผ ์ธก์ •ํ•˜์—ฌ ์ •ํ™•์„ฑ์„ ์•Œ์•„๋ณด๊ณ ์ž ํ•œ๋‹ค. ์ถ”๊ฐ€์ ์œผ๋กœ 3์ฐจ์› ๊ฐ€์ƒ์ˆ˜์ˆ ์„ ํ†ตํ•ด ํ•˜์•… ์ƒํ–‰์ง€ ๊ณจ์ด์‹์ˆ (ramal bone graft)์„ ์„ค๊ณ„ํ•˜๊ณ  ํ•˜์•… ํŒฌํ…€ ๋ชจํ˜•์—์„œ ์ด์— ๋งž๊ฒŒ ์ž์œจ ๋กœ๋ด‡์ด ๊ณจ์ ˆ๋‹จ์ˆ ์„ ์ˆ˜ํ–‰ํ•˜์—ฌ ์•…๊ณจ์—์„œ ์žˆ์–ด์„œ ๋กœ๋ด‡์„ ์ด์šฉํ•œ ๊ณจ์ ˆ๋‹จ์ˆ ์˜ ์ •ํ™•์„ฑ์„ ํ‰๊ฐ€ํ•ด ๋ณด๊ณ  ๋ฐ˜๋Œ€์ธก์€ ๋Œ€์กฐ๊ตฐ์œผ๋กœ ์™ธ๊ณผ์˜๊ฐ€ ๊ธฐ์กด์˜ ์ „ํ†ต์ ์ธ ๋ฐฉ์‹์œผ๋กœ ๊ณจ์ ˆ๋‹จ์ˆ ์„ ์ˆ˜ํ–‰ํ•จ์œผ๋กœ์จ ์–‘์ธก์„ ๋น„๊ตํ•˜๊ณ ์ž ํ•œ๋‹ค. 2. ๋ฐฉ ๋ฒ• ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ฒฝ๋Ÿ‰ ๋กœ๋ด‡์˜ ์ตœ์ข… ์ž‘์šฉ์ฒด(end effector)์— ์ „์ž ๊ทธ๋ฆฌํผ(gripper)๋ฅผ ์—ฐ๊ฒฐํ•˜๊ณ  ์ด ๊ทธ๋ฆฌํผ๊ฐ€ ์ˆ˜์ˆ ์šฉ ์ ˆ์‚ญ๊ธฐ๊ตฌ๋‚˜ ๋””์Šคํฌ๊ฐ€ ์—ฐ๊ฒฐ๋œ ์น˜๊ณผ์šฉ ํ•ธ๋“œํ”ผ์Šค๋ฅผ ์žก๊ณ  ๊ณจ์ ˆ๋‹จ์„ ์ˆ˜ํ–‰ํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ์‹ค์ œ ๋ชจ๋ธ์˜ ์ขŒํ‘œ์™€ ๋กœ๋ด‡์ด ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์ขŒํ‘œ๋ฅผ ์ค‘์ฒฉํ•˜๊ธฐ ์œ„ํ•ด ์„ธ ์ ์„ ์ฐ์–ด ์ฒซ๋ฒˆ์งธ ์ ์„ ์›์ ์œผ๋กœ ํ•˜๊ณ , ๋‘๋ฒˆ์งธ ์ ์˜ ๋ฐฉํ–ฅ์„ x์ถ•์œผ๋กœ, ๊ทธ๋ฆฌ๊ณ  ์„ธ ๋ฒˆ์งธ ์ ์ด ๊ฒฐ์ •ํ•˜๋Š” ํ‰๋ฉด์„ xy ํ‰๋ฉด์œผ๋กœ ์ธ์‹ํ•˜๋„๋ก ํ•˜์˜€๋‹ค. ์ฒซ๋ฒˆ์งธ ์‹คํ—˜์—์„œ๋Š” ์œ„์น˜ ์ถ”์  ์˜ค๋ฅ˜์™€ ๋ชฉํ‘œ ์ •ํ•ฉ ์˜ค๋ฅ˜์˜ ํ‰๊ฐ€๋ฅผ ์œ„ํ•ด ํ•˜์•…๊ณจ ๋ชจ๋ธ์— ์น˜์•„์˜ ๊ธฐ์ค€ ์„ธ ์ ๊ณผ ํ•˜์•…๊ณจ์˜ ์ด 16๊ฐœ์˜ ๋ชฉํ‘œ ์œ„์น˜์— 1mm ๊ตฌ๋ฉ์„ ๋šซ๊ณ  1mm ์ง€๋ฆ„์˜ ์ง€๋ฅด์ฝ”๋‹ˆ์•„ ๊ตฌ๋ฅผ ์ ์šฉํ•˜์—ฌ CBCT ์ƒ์—์„œ ์ž˜ ๋ณด์ผ ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ๊ฐ ๋ชฉํ‘œ ์œ„์น˜์— 10๋ฒˆ์”ฉ ๋ฐ˜๋ณตํ•˜์—ฌ ์œ„์น˜๋ฅผ ์ธ์‹ํ•˜์—ฌ ์˜ค๋ฅ˜๋ฅผ ๊ณ„์‚ฐํ•˜๊ณ  ๋ชฉํ‘œ ์ •ํ•ฉ ์˜ค๋ฅ˜์˜ ์œ„์น˜๋ณ„ ์ฐจ์ด๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋‘๋ฒˆ์งธ ์‹คํ—˜์—์„œ๋Š” ์ด 20 ๊ฐœ์˜ ์ง์œก๋ฉด์ฒด ์„๊ณ  ๋ชจ๋ธ (7cm x 7cm x 3cm)์„ ์ œ์ž‘ํ•˜์˜€๊ณ  ์„๊ณ ์˜ ์ ˆ๋‹จ ํฌ๊ธฐ๋Š” ํ•˜์•… ์ƒํ–‰์ง€ ๊ณจ์ฑ„์ทจ์„ ์œ„ํ•œ ๊ณจ์ ˆ๋‹จ ํฌ๊ธฐ (2cm x 1cm x 0.5cm)์™€ ๋™์ผํ•˜๊ฒŒ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ๋กœ๋ด‡ํŒ”์„ ์ด์šฉํ•˜์—ฌ 3์  ์ ‘์ด‰์„ ํ•˜๋ฉด ์ขŒํ‘œ๊ฐ’์„ ๊ณ„์‚ฐํ•˜์—ฌ ๋ฏธ๋ฆฌ ํ”„๋กœ๊ทธ๋ž˜๋ฐ๋œ ์œ„์น˜์—์„œ ๊ณจ์ ˆ๋‹จ์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๋กœ๋ด‡์— ์˜ํ•ด ์ˆ˜ํ–‰๋œ ์„๊ณ  ์ ˆ๋‹จ์„ ์€ ์œ„์น˜, ๊ธธ์ด ๊ฐ๋„ ๋ฐ ๊นŠ์ด๋กœ ๋‚˜๋ˆ„์–ด ์˜ค๋ฅ˜๋ฅผ ์ธก์ •ํ•˜์˜€๋‹ค. ์„ธ๋ฒˆ์งธ ์‹คํ—˜์—์„œ๋Š” ํ•˜์•… ์ƒํ–‰์ง€ ๊ณจ์ฑ„์ทจ๋ฅผ ์œ„ํ•œ ๊ณจ์ ˆ๋‹จ ์‹คํ—˜์„ ์œ„ํ•ด ์ด 16๊ฐœ์˜ ํ•˜์•… ํŒฌํ…€ ๋ชจํ˜•์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ํŒฌํ…€ ๋ชจํ˜•์„ ์‚ผ์ฐจ์› ์Šค์บ๋‹์œผ๋กœ ์‚ผ์ฐจ์› ์˜์ƒ์„ ์–ป๊ณ  ๊ฐ€์ƒ ์ˆ˜์ˆ ์„ ์‹œํ–‰ํ•˜์—ฌ ๊ณจ์ ˆ๋‹จ ํฌ๊ธฐ์™€ ํ˜•ํƒœ ๊ทธ๋ฆฌ๊ณ  ๊ทธ ์œ„์น˜์— ๋Œ€ํ•œ ๊ณ„ํš์„ ์„ธ์› ๋‹ค. ์ด ๊ฐ€์ƒ ์ˆ˜์ˆ  ๊ณ„ํš์— ๋”ฐ๋ผ ๋กœ๋ด‡์ด ํŒฌํ…€ ๋ชจ๋ธ์— ๊ณจ์ ˆ๋‹จ ์ˆ˜์ˆ ์„ ํ•˜์˜€๋‹ค. ๋ฐ˜๋Œ€ ์ธก์€ ๋Œ€์กฐ๊ตฐ์œผ๋กœ ๊ธฐ์กด์˜ ์ „ํ†ต์ ์ธ ๋ฐฉ์‹์œผ๋กœ ์™ธ๊ณผ์˜๊ฐ€ ์ˆ˜ํ–‰ํ•˜์—ฌ ์–‘์ธก์˜ ์˜ค์ฐจ๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ์ ˆ๋‹จ์„ ์˜ ์œ„์น˜, ๊ธธ์ด, ๊ฐ๋„ ๋ฐ ๊นŠ์ด๋ฅผ ์ธก์ •ํ•˜์—ฌ ๊ฐ๊ฐ์˜ ์ •ํ™•๋„๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ์œ„์น˜ ์˜ค๋ฅ˜๋Š” x์ถ•์œผ๋กœ๋Š” ๋กœ๋ด‡์ด ํ‘œ๋ฉด ์ ‘์ด‰์„ ์ธ์‹ํ•˜๊ณ  ๊ณจ์ ˆ๋‹จ์„ ์‹œํ–‰ํ•˜๊ธฐ์— 0์˜ ๊ฐ’์œผ๋กœ ์ธก์ •๋˜์—ˆ๊ณ  y ์ถ•๊ณผ z ์ถ•์œผ๋กœ ๋‚˜๋ˆ„์–ด ์ธก์ •๋˜์—ˆ์œผ๋ฉฐ ํ‰๊ท ๊ฐ’๊ณผ ์ œ๊ณฑํ‰๊ท ์ œ๊ณฑ๊ทผ๋ฅผ ๊ณ„์‚ฐํ•˜์˜€๋‹ค. 3. ๊ฒฐ ๊ณผ ์œ„์น˜ ์ถ”์  ์˜ค๋ฅ˜์™€ ๋ชฉํ‘œ ์ •ํ•ฉ ์˜ค๋ฅ˜๋Š” ๊ฐ๊ฐ 0.49ยฑ0.22 mm ์™€ 0.98ยฑ0.47 mm๋กœ ์ธก์ •๋˜์—ˆ์œผ๋ฉฐ ๊ธฐ์ค€์ ‘์—์„œ ๋ฉ€์–ด์งˆ์ˆ˜๋ก ๋ชฉํ‘œ ์ •ํ•ฉ ์˜ค๋ฅ˜๋Š” ๋” ํฐ ๊ฐ’์„ ๋ณด์˜€๋‹ค. ์„๊ณ  ๋ชจ๋ธ ์‹คํ—˜์—์„œ ์ ˆ๋‹จ์„ ์˜ ์œ„์น˜, ๊ธธ์ด, ๊ฐ๋„ ๋ฐ ๊นŠ์ด์˜ ํ‰๊ท ๊ณผ ํ‘œ์ค€์˜ค์ฐจ๋Š” ๊ฐ๊ฐ 0.93 ยฑ 0.45 mm, 0.81 ยฑ 0.34 mm, 1.26 ยฑ 1.35ยฐ, 1.19 ยฑ 0.73 mm ์ด์—ˆ๋‹ค. ์œ„์น˜๊ฐ€ ๊ฐ€์žฅ ์ •ํ™•ํ•œ ๊ฐ’์„ ๋ณด์˜€์œผ๋ฉฐ ๊ธธ์ด ๊ทธ๋ฆฌ๊ณ  ๊นŠ์ด ์ˆœ์œผ๋กœ ์˜ค์ฐจ๊ฐ€ ์ฆ๊ฐ€ํ•˜์˜€์œผ๋ฉฐ, ๊ฐ๋„์™€ ์ ˆ๋‹จ ๊นŠ์ด ์ œ์–ด๊ฐ€ ๊ฐ€์žฅ ์˜ค์ฐจ๊ฐ€ ๋งŽ์€ ์ˆ ์‹์ด์—ˆ๋‹ค. ํ•˜์•… ํŒฌํ…€ ์ˆ˜์ˆ ์—์„œ ๋กœ๋ด‡์„ ์ด์šฉํ•œ ๊ณจ์ ˆ๋‹จ์˜ ์œ„์น˜, ๊ธธ์ด, ๊ฐ๋„ ๋ฐ ๊นŠ์ด ์˜ค์ฐจ ๊ฐ’์€ ๊ฐ๊ฐ 0.70 ยฑ 0.34 mm, 0.35 ยฑ 0.19 mm, 1.32 ยฑ 0.96ยฐ, 0.59 ยฑ 0.46 mm ์˜€์œผ๋ฉฐ ์™ธ๊ณผ์˜์˜ ๊ณจ์ ˆ๋‹จ์—์„œ๋Š” ๊ฐ’์ด ๊ฐ๊ฐ 1.83 ยฑ 0.65 mm, 0.62 ยฑ 0.37 mm, 5.96 ยฑ 3.47ยฐ, 0.40 ยฑ 0.31 mm ์˜€๋‹ค. ์œ„์น˜, ๊ธธ์ด, ๊ฐ๋„ ์˜ค์ฐจ๋Š” ๋กœ๋ด‡์ด ๋” ์ž‘์€ ๊ฐ’์„ ๋ณด์˜€๊ณ  ๊นŠ์ด ์˜ค์ฐจ๋Š” ์™ธ๊ณผ์˜์˜ ์ˆ˜์ˆ ์—์„œ ๋” ์ž‘์€ ๊ฐ’์„ ๋ณด์˜€๋‹ค. 4. ๊ฒฐ ๋ก  ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•˜์•… ์ƒํ–‰์ง€ ๊ณจ์ฑ„์ทจ๋ฅผ ์œ„ํ•œ ์ž์œจ ๋กœ๋ด‡์„ ์ด์šฉํ•œ ๊ณจ์ ˆ๋‹จ ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•˜์˜€๊ณ  ์œ„์น˜์ถ”์ ์˜ค๋ฅ˜์™€ ๋ชฉํ‘œ์ •ํ•ฉ์˜ค๋ฅ˜ ๋ชจ๋‘ ์šฐ์ˆ˜ํ•œ ๊ฐ’์„ ๋ณด์˜€๋‹ค. ์„๊ณ  ๋ชจํ˜•๊ณผ ํ•˜์•… ํŒฌํ…€ ๋ชจํ–ฅ์„ ์ด์šฉํ•œ ๋‘๊ฐ€์ง€ ์‹คํ—˜ ๋ชจ๋‘์—์„œ ์œ ์šฉ์„ฑ๊ณผ ํ–ฅ์ƒ๋œ ์ •ํ™•์„ฑ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์„ธ์  ์ ‘์ด‰ ์ขŒํ‘œ ๊ฒฐ์ • ์‹œ์Šคํ…œ์€ ์‹ค์ œ ๋ชจ๋ธ์˜ ์ขŒํ‘œ๋ฅผ ๋กœ๋ด‡์˜ ์ขŒํ‘œ๋กœ ๋“ฑ๋กํ•˜๋Š” ๋ฐ ์œ ์šฉํ•œ ์‹œ์Šคํ…œ์ด์—ˆ์œผ๋ฉฐ, ํ•˜์•… ์ƒํ–‰์ง€ ๊ณจ์ ˆ๋‹จ์ˆ ์— ๋Œ€ํ•œ ์ž์œจ๋กœ๋ด‡ ์‹œ์Šคํ…œ์˜ ์ •ํ™•๋„๋Š” ๊ธฐ์กด์˜ ์™ธ๊ณผ์˜๊ฐ€ ์ง์ ‘ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐฉ์‹๋ณด๋‹ค ์šฐ์ˆ˜ํ•˜์˜€๋‹ค.Abstract (in English) 1. Introduction 1 2. Materials and Methods. 12 3. Results 26 4. Discussion 32 5. Conclusions 40 6. References 41 Tables and Figures 48 Abstract (in Korean) 74Docto

    Robotics in Dentistry : A Narrative Review

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    Background: Robotics is progressing rapidly. The aim of this study was to provide a comprehensive overview of the basic and applied research status of robotics in dentistry and discusses its development and application prospects in several major professional fields of dentistry. Methods: A literature search was conducted on databases: MEDLINE, IEEE and Cochrane Library, using MeSH terms: [โ€œroboticsโ€ and โ€œdentistryโ€]. Result: Forty-nine articles were eventually selected according to certain inclusion criteria. There were 12 studies on prosthodontics, reaching 24%; 11 studies were on dental implantology, accounting for 23%. Scholars from China published the most articles, followed by Japan and the United States. The number of articles published between 2011 and 2015 was the largest. Conclusions: With the advancement of science and technology, the applications of robots in dental medicine has promoted the development of intelligent, precise, and minimally invasive dental treatments. Currently, robots are used in basic and applied research in various specialized fields of dentistry. Automatic tooth-crown-preparation robots, tooth-arrangement robots, drilling robots, and orthodontic archwire-bending robots that meet clinical requirements have been developed. We believe that in the near future, robots will change the existing dental treatment model and guide new directions for further development
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