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Medical Image Computing and Computer-Assisted Intervention: MICCAI 2005: 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I

James S. Duncan ; Guido Gerig (eds.)

En conferencia: 8º International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) . Palm Springs, CA, USA . October 26, 2005 - October 29, 2005

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

Image Processing and Computer Vision; Pattern Recognition; Computer Graphics; Artificial Intelligence (incl. Robotics); Imaging / Radiology; Health Informatics

Disponibilidad
Institución detectada Año de publicación Navegá Descargá Solicitá
No detectada 2005 SpringerLink

Información

Tipo de recurso:

libros

ISBN impreso

978-3-540-29327-9

ISBN electrónico

978-3-540-32094-4

Editor responsable

Springer Nature

País de edición

Reino Unido

Fecha de publicación

Información sobre derechos de publicación

© Springer-Verlag Berlin Heidelberg 2005

Tabla de contenidos

Kinematic Geometry of Osteotomies

Erin J. Smith; J. Tim Bryant; Randy E. Ellis

This paper presents a novel method for defining an osteotomy that can be used to represent all types of osteotomy procedures. In essence, we model an osteotomy as a lower-pair mechanical joint to derive the kinematic geometry of the osteotomy. This method was implemented using a commercially available animation software suite in order to simulate a variety of osteotomy procedures. Two osteotomy procedures are presented for a femoral malunion in order to demonstrate the advantages of our kinematic model in developing optimal osteotomy plans. The benefits of this kinematic model include the ability to evaluate the effects of various kinds of osteotomy and the elimination of potentially error-prone radiographic assessment of deformities.

- Biological Imaging - Simulation and Modeling I | Pp. 902-909

Predictive Camera Tracking for Bronchoscope Simulation with CONDensation

Fani Deligianni; Adrian Chung; Guang Zhong

This paper exploits the use of temporal information to minimize the ambiguity of camera motion tracking in bronchoscope simulation. The condensation algorithm (Sequential Monte Carlo) has been used to propagate the probability distribution of the state space. For motion prediction, a second-order auto-regressive model has been used to characterize camera motion in a bounded lumen as encountered in bronchoscope examination. The method caters for multi-modal probability distributions, and experimental results from both phantom and patient data demonstrate a significant improvement in tracking accuracy especially in cases where there is airway deformation and image artefacts.

- Biological Imaging - Simulation and Modeling I | Pp. 910-916

Experimental Validation of a 3D Dynamic Finite-Element Model of a Total Knee Replacement

Joel L. Lanovaz; Randy E. Ellis

A 3D forward-dynamics model of a total knee replacement was developed using an explicit finite-element package. The model incorporated both a tibiofemoral and a patellofemoral joint and allowed full 6-DOF kinematics for both joints. Simulated quadriceps contraction was used to drive the model. For validation, a unique experimental apparatus was constructed to simulate an open-chain extension motion under quadriceps control. The ligamentous constraints of the MCL and LCL were simulated using tension springs. The kinematics of the tibia and patella were recorded along with the net forces and moments applied to the femur. Several ligament and inertial configurations were simulated. The RMS differences between the experimental data and model predictions across all simulations were excellent for both the kinematics (angles: 0.3 – 1.6°, displacements: 0.1 – 0.8 mm) and kinetics (forces: 5 – 11 N, moments: 0.2 – 0.6 Nm). The validated model will be extended with physiologically realistic ligaments and utilized in surgical planning simulations.

- Biological Imaging - Simulation and Modeling I | Pp. 917-924

An In Vitro Patient-Tailored Model of Human Cerebral Artery for Simulating Endovascular Intervention

Seiichi Ikeda; Fumihito Arai; Toshio Fukuda; Makoto Negoro; Keiko Irie; Ikuo Takahashi

An in vitro patient-tailored reproduction model of cerebral artery, a hardware platform for simulating endovascular intervention for making diagnoses and surgical trainings is presented. 3-D configuration of vessel lumen is reproduced as vessel model with 13 m modeling resolution, using CT and MRI information. Physical characteristics of cerebral artery, such as elastic modulus and friction coefficient, are also reproduced. We also propose a novel method to visualize stress condition on vessel wall using photoelastic effect. Consequently, it should be helpful for clinical applications, academic researches and other various purposes.

- Biological Imaging - Simulation and Modeling I | Pp. 925-932