• 제목/요약/키워드: virtual patient dataset

검색결과 3건 처리시간 0.018초

가상환자 데이터세트를 기반으로 악관절과 심미를 고려한 진단 및 치료계획 수립 (From TMJ to 3D Digital Smile Design with Virtual Patient Dataset for diagnosis and treatment planning)

  • 이수영;강동휘;이도연;김희철
    • 대한심미치과학회지
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    • 제30권2호
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    • pp.71-90
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    • 2021
  • 가상 환자 데이터 세트는 단일 환자로부터 획득한 구강스캔 안면스캔 전신스캔 하악운동경로데이터 등 다양한 소스의 진단 데이터를 하나의 3차원 좌표계로 정렬한 데이터의 집합이다. 치과의사는 가상 환자 데이터 세트를 사용하여 효과적으로 치료 계획을 수립하고 다양한 치료 계획을 가상공간상에서 시뮬레이션 할 수 있으며, 가상 환자 데이터 세트에서 환자의 미소를 디자인 후 그 결과를 시뮬레이션하고 최적의 치료결과를 선택할 수 있다. 가상공간에서 선택된 치료 계획은 3D 프린팅, 밀링, 사출 성형과 같은 제조 기술을 사용하여 환자에게 동일하게 전달될 수 있다. 이러 치료 계획의 전달은 임시 수복물 제작 및 환자의 구강 내에서 목업 확인을 통해 최종 보철물 제작으로 연결할 수 있다. 이와 같이 진단 데이터, 중첩 및 가공의 정확도가 보장된다면 3차원 가상공간 상에서 시뮬레이션된 3D 디지털 스마일 디자인을 실제 환자에게 정확하게 전달할 수 있다. 가상환자데이터세트의 임상적용방법으로 동기능적교합측정 검사를 통해 교합조정치료를 치료계획에서 배제할수 있는 의사결정방법과, 턱관절질환을 가지고 있는 청소년기 특발성 척추측만증 환자의 턱관절 치료전후 전신스캔 비교분석방법, 그리고 전악수복증례인 상하악 총의치환자 진료시 가상환자데이터세트에 기반한 교합평면분석 및 디지털심미분석방법을 제시하였다.

의료용 훈련을 위한 가상현실에 대한 연구 (Virtual Environments for Medical Training: Soft tissue modeling)

  • 김정
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.372-377
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    • 2007
  • For more than 2,500 years, surgical teaching has been based on the so called "see one, do one, teach one" paradigm, in which the surgical trainee learns by operating on patients under close supervision of peers and superiors. However, higher demands on the quality of patient care and rising malpractice costs have made it increasingly risky to train on patients. Minimally invasive surgery, in particular, has made it more difficult for an instructor to demonstrate the required manual skills. It has been recognized that, similar to flight simulators for pilots, virtual reality (VR) based surgical simulators promise a safer and more comprehensive way to train manual skills of medical personnel in general and surgeons in particular. One of the major challenges in the development of VR-based surgical trainers is the real-time and realistic simulation of interactions between surgical instruments and biological tissues. It involves multi-disciplinary research areas including soft tissue mechanical behavior, tool-tissue contact mechanics, computer haptics, computer graphics and robotics integrated into VR-based training systems. The research described in this paper addresses the problem of characterizing soft tissue properties for medical virtual environments. A system to measure in vivo mechanical properties of soft tissues was designed, and eleven sets of animal experiments were performed to measure in vivo and in vitro biomechanical properties of porcine intra-abdominal organs. Viscoelastic tissue parameters were then extracted by matching finite element model predictions with the empirical data. Finally, the tissue parameters were combined with geometric organ models segmented from the Visible Human Dataset and integrated into a minimally invasive surgical simulation system consisting of haptic interface devices and a graphic display.

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Effect of the Number of Projected Images on the Noise Characteristics in Tomosynthesis Imaging

  • Fukui, Ryohei;Matsuura, Ryutaro;Kida, Katsuhiro;Goto, Sachiko
    • 한국의학물리학회지:의학물리
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    • 제32권2호
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    • pp.50-58
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    • 2021
  • Purpose: In this study, we investigated the relationship between the noise characteristics and the number of projected images in tomosynthesis using a digital phantom. Methods: The digital phantom consisted of a columnar phantom in the center of the image and a spherical phantom with a diameter of 80 pixels. A virtual scan was performed, and 128 projected images (Tomo_w/o) of the phantoms were obtained. The image noise according to the Poisson distribution was added to the projected images (Tomo_×1). Furthermore, another projected image with additional noise was prepared (Tomo_×1/2). For each dataset, we created datasets with 64 (half) and 32 (quarter) projections by removing the even-numbered images twice from the 128 (fully) projected images. Tomosynthesis images were reconstructed by filtered back projection (FBP). The modulation transfer function (MTF) was estimated using the sphere method, and the noise power spectrum (NPS) was estimated using the two-dimensional Fourier transform method. Results: The MTFs did not change between datasets, and the NPSs improved as the number of projected images increased. The noise characteristics of the Tomo_×1_half images were the same as those of the Tomo_×1/2_full. Conclusions: To achieve a reduction in the patient dose in tomosynthesis acquisition, we recommend reducing the number of projected images rather than reducing the dose per projection.