Segmentation and reconstruction of hepatic veins and intrahepatic portal vein based on the coronal sectional anatomic dataset.

Three-dimensional (3D) reconstruction of intrahepatic vessels is very useful in visualizing the complex anatomy of hepatic veins and intrahepatic portal vein. It also provides a 3D anatomic basis for diagnostic imaging and surgical operation on the liver. In the present study, we built a 3D digitized model of hepatic veins and intrahepatic portal vein based on the coronal sectional anatomic dataset of the liver. The dataset was obtained using the digital freezing milling technique. The pre-reconstructed structures were identified and extracted, and then were segmented by the method of manual intervention. The digitized model of hepatic veins and intrahepatic portal vein was established using 3D medical visualization software. This model facilitated a continuous and dynamic displaying of the hepatic veins and intrahepatic portal vein at different orientations, which demonstrated the complicated relationship of adjacent hepatic veins and intrahepatic portal vein realistically in the 3D space. This study indicated that high-quality 2D images, precise data segmentation, and suitable 3D reconstruction methods ensured the reality and accuracy of the digital visualized model of hepatic veins and intrahepatic portal vein.

Intelligent inferencing and haptic simulation for Chinese acupuncture learning and training.

This paper presents an intelligent virtual environment for Chinese acupuncture learning and training using state-of-the-art virtual reality technology. It is the first step toward developing a comprehensive virtual human model for studying Chinese medicine. Students can learn and practice acupuncture in the proposed 3-D interactive virtual environment that supports a force feedback interface for needle insertion. Thus, students not only "see" but also "touch" the virtual patient. With high performance computers, highly informative and flexible visualization of acupuncture points of various related meridian and collateral can be highlighted to guide the students during training. A computer-based expert system using our newly proposed intelligent fuzzy petri net is designed and implemented to train the students to treat different diseases using acupuncture. Such an intelligent virtual reality system can provide an interesting and effective learning environment for Chinese acupuncture.

Virtual acupuncture human based on chinese visible human dataset.

In this paper, we present our application of latest information technology in assisting the Chinese acupuncture research. Having integrated the Chinese Visible Human (CVH) data, virtual reality, visualization and imaging techniques, we have constructed a 3-dimensional digital human model for acupuncture. This model integrates the meridian positioning, acupoint positioning, arbitrary cutting-plane visualization, multi-layer dissection, needle puncturing simulation, as well as the common diseases-therapy information. Our work can be widely applied to Chinese acupuncture education, clinical usage and scientific research.

A virtual-reality training system for knee arthroscopic surgery.

Surgical training systems based on virtual-reality (VR) simulation techniques offer a cost-effective and efficient alternative to traditional training methods. This paper describes a VR system for training arthroscopic knee surgery. Virtual models used in this system are constructed from the Visual Human Project dataset. Our system simulates soft tissue deformation with topological change in real-time using finite-element analysis. To offer realistic tactile feedback, we build a tailor-made force feedback hardware.

Virtual reality based system for training on knee arthroscopic surgery.

Surgical training systems based on virtual reality (VR) and simulation techniques offer a cost-effective and efficient alternative to traditional training methods. This paper describes a virtual reality system for training arthroscopic knee surgery. The virtual model used in this system is constructed from the Visual Human Project dataset. The system simulates the real-time deformation of soft tissue with topological change using finite element analysis. To offer the realistic tactile feedback, we construct a specialized force feedback hardware.

Detection and measurement of fetal abdominal contour in ultrasound images via local phase information and iterative randomized Hough transform.

Due to the characteristic artifacts of ultrasound images, e.g., speckle noise, shadows and intensity inhomogeneity, traditional intensity-based methods usually have limited success on the segmentation of fetal abdominal contour. This paper presents a novel approach to detect and measure the abdominal contour from fetal ultrasound images in two steps. First, a local phase-based measure called multiscale feature asymmetry (MSFA) is de ned from the monogenic signal to detect the boundaries of fetal abdomen. The MSFA measure is intensity invariant and provides an absolute measurement for the signi cance of features in the image. Second, in order to detect the ellipse that ts to the abdominal contour, the iterative randomized Hough transform is employed to exclude the interferences of the inner boundaries, after which the detected ellipse gradually converges to the outer boundaries of the abdomen. Experimental results in clinical ultrasound images demonstrate the high agreement between our approach and manual approach on the measurement of abdominal circumference (mean sign difference is 0.42% and correlation coef cient is 0.9973), which indicates that the proposed approach can be used as a reliable and accurate tool for obstetrical care and diagnosis.

A multiresolution framework for ultrasound image segmentation by combinative active contours.

We propose a novel multiresolution framework for ultrasound image segmentation in this paper. The framework exploits both local intensity and local phase information to tackle the degradations of ultrasound images. First, multiresolution scheme is adopted to build a Gaussian pyramid for each speckled image. Speckle noise is gradually smoothed out at higher levels of the pyramid. Then local intensity-driven active contours are employed to locate the coarse contour of the target from the coarsest image, followed by local phase-based geodesic active contours to further refine the contour in finer images. Compared with traditional gradient-based methods, phase-based methods are more suitable for ultrasound images because they are invariant to variations in image contrast. Experimental results on left ventricle segmentation from echocardiographic images demonstrate the advantages of the proposed model.

Mesh quality oriented 3D geometric vascular modeling based on parallel transport frame.

While a number of methods have been proposed to reconstruct geometrically and topologically accurate 3D vascular models from medical images, little attention has been paid to constantly maintain high mesh quality of these models during the reconstruction procedure, which is essential for many subsequent applications such as simulation-based surgical training and planning. We propose a set of methods to bridge this gap based on parallel transport frame. An improved bifurcation modeling method and two novel trifurcation modeling methods are developed based on 3D Bézier curve segments in order to ensure the continuous surface transition at furcations. In addition, a frame blending scheme is implemented to solve the twisting problem caused by frame mismatch of two successive furcations. A curvature based adaptive sampling scheme combined with a mesh quality guided frame tilting algorithm is developed to construct an evenly distributed, non-concave and self-intersection free surface mesh for vessels with distinct radius and high curvature. Extensive experiments demonstrate that our methodology can generate vascular models with better mesh quality than previous methods in terms of surface mesh quality criteria.

A serious game for learning ultrasound-guided needle placement skills.

Ultrasound-guided needle placement is a key step in a lot of radiological intervention procedures such as biopsy, local anesthesia and fluid drainage. To help training future intervention radiologists, we develop a serious game to teach the skills involved. We introduce novel techniques for realistic simulation and integrate game elements for active and effective learning. This game is designed in the context of needle placement training based on the some essential characteristics of serious games. Training scenarios are interactively generated via a block-based construction scheme. A novel example-based texture synthesis technique is proposed to simulate corresponding ultrasound images. Game levels are defined based on the difficulties of the generated scenarios. Interactive recommendation of desirable insertion paths is provided during the training as an adaptation mechanism. We also develop a fast physics-based approach to reproduce the shadowing effect of needles in ultrasound images. Game elements such as time-attack tasks, hints and performance evaluation tools are also integrated in our system. Extensive experiments are performed to validate its feasibility for training.

A catheterization-training simulator based on a fast multigrid solver.

A VR-based simulator helps trainees develop skills for catheterization, a fundamental but difficult procedure in vascular interventional radiology. A deformable model simulates the complicated behavior of guide wires and catheters, using the principle of minimum total potential energy. A fast, stable multigrid solver ensures realistic simulation and real-time interaction. In addition, the system employs geometrically and topologically accurate vascular models based on improved parallel-transport frames, and it implements efficient collision detection. Experiments evaluated the method's stability, the solver's execution time, how well the simulation preserved the catheter's curved tip, and the catheter deformation's realism. An empirical study based on a typical selective-catheterization procedure assessed the system's feasibility and effectiveness.

A Novel FEM-Based Numerical Solver for Interactive Catheter Simulation in Virtual Catheterization.

Virtual reality-based simulators are very helpful for trainees to acquire the skills of manipulating catheters and guidewires during the vascular interventional surgeries. In the development of such a simulator, however, it is a great challenge to realistically model and simulate deformable catheters and guidewires in an interactive manner. We propose a novel method to simulate the motion of catheters or guidewires and their interactions with patients' vascular system. Our method is based on the principle of minimal total potential energy. We formulate the total potential energy in the vascular interventional circumstance by summing up the elastic energy deriving from the bending of the catheters or guidewires, the potential energy due to the deformation of vessel walls, and the work by the external forces. We propose a novel FEM-based approach to simulate the deformation of catheters and guidewires. The motion of catheters or the guidewires and their responses to every input from the interventionalist can be calculated globally. Experiments have been conducted to validate the feasibility of the proposed method, and the results demonstrate that our method can realistically simulate the complex behaviors of catheters and guidewires in an interactive manner.

A meshless rheological model for blood-vessel interaction in endovascular simulation.

A meshless rheological model is proposed for medical simulation of vascular procedures. Due to the complexity of rheologic models involved in endovascular simulations, delivering a high level of interactivity with realistic biomechanical feedback is still a challenge. In this paper, we propose a particle-based rheologic modeling method for virtual catheterisation training applications. The effect of blood rheology has been simulated through a smoothed particle hydrodynamics (SPH) formulation of non-Newtonian flow. By modeling vessel wall structure as virtual particles, a pure Lagrange particle formulation for fluid-structure interaction (FSI) is purposed for modeling the blood-vessel interaction. We further propose a flow-related thrombus (clot) formation-dissolution model based on our fluid-solid interaction framework. A physics processing API (PhysX) friendly implementation is proposed for incorporating the rheological properties of blood and vessel wall into our framework. Results have demonstrated the feasibility of employing our proposed meshfree framework in simulating blood-vessel interaction and clotting behaviors which are essential to endovascular simulations. Having benefited from the elegant formulation of Lagrangian particle interaction, interactive framerates of the simulation can be maintained under hardware-acceleration.

A novel modeling framework for multilayered soft tissue deformation in virtual orthopedic surgery.

Realistic modeling of soft tissue deformation is crucial to virtual orthopedic surgery, especially orthopedic trauma surgery which involves layered heterogeneous soft tissues. In this paper, a novel modeling framework for multilayered soft tissue deformation is proposed in order to facilitate the development of orthopedic surgery simulators. We construct our deformable model according to the layered structure of real human organs, and this results in a multilayered model. The division of layers is based on the segmented Chinese Visible Human (CVH) dataset. This enhances the realism and accuracy in the simulation. For the sake of efficiency, we employ 3D mass-spring system to our multilayered model. The nonlinear passive biomechanical properties of skin and skeletal muscle are achieved by introducing a bilinear elasticity scheme to the springs in the mass-spring system. To efficiently and accurately reproduce the biomechanical properties of certain human tissues, an optimization approach is employed in configuring the parameters of the springs. Experimental data from biomechanics literatures are used as benchmarking references. With the employment of Physics Processing Unit (PPU) and high quality volume visualization, our framework is developed into an interactive and intuitive platform for virtual surgery training systems. Several experiments demonstrate the feasibility of the proposed framework in providing interactive and realistic deformation for orthopedic surgery simulation.

Learning blood management in orthopedic surgery through gameplay.

Orthopedic surgery treats the musculoskeletal system, in which bleeding is common and can be fatal. To help train future surgeons in this complex practice, researchers designed and implemented a serious game for learning orthopedic surgery. The game focuses on teaching trainees blood management skills, which are critical for safe operations. Using state-of-the-art graphics technologies, the game provides an interactive and realistic virtual environment. It also integrates game elements, including task-oriented and time-attack scenarios, bonuses, game levels, and performance evaluation tools. To study the system's effect, the researchers conducted experiments on player completion time and off-target contacts to test their learning of psychomotor skills in blood management.

Reconstruction of volumetric ultrasound panorama based on improved 3D SIFT.

Registration of ultrasound volumes is a key issue for the reconstruction of volumetric ultrasound panorama. In this paper, we propose an improved three-dimensional (3D) scale invariant feature transform (SIFT) algorithm to globally register ultrasound volumes acquired from dedicated ultrasound probe, where local deformations are corrected by block-based warping algorithm. Original SIFT algorithm is extended to 3D and improved by combining the SIFT detector with Rohr3D detector to extract complementary features and applying the diffusion distance algorithm for robust feature comparison. Extensive experiments have been performed on both phantom and clinical data sets to demonstrate the effectiveness and robustness of our approach.

Volumetric ultrasound panorama based on 3D SIFT.

The reconstruction of three-dimensional (3D) ultrasound panorama from multiple ultrasound volumes can provide a wide field of view for better clinical diagnosis. Registration of ultrasound volumes has been a key issue for the success of this panoramic process. In this paper, we propose a method to register and stitch ultrasound volumes, which are scanned by dedicated ultrasound probe, based on an improved 3D Scale Invariant Feature Transform (SIFT) algorithm. We propose methods to exclude artifacts from ultrasound images in order to improve the overall performance in 3D feature point extraction and matching. Our method has been validated on both phantom and clinical data sets of human liver. Experimental results show the effectiveness and stability of our approach, and the precision of our method is comparable to that of the position tracker based registration.

An ultrasound-guided organ biopsy simulation with 6DOF haptic feedback.

Ultrasound-guided biopsy is one of the most fundamental, but difficult, skills to acquire in interventional radiology. Intensive training, especially in the needle insertion, is required for trainee radiologists to perform safe procedures. In this paper, we propose a virtual reality simulation system to facilitate the training of radiologists and physicians in this procedures. Key issues addressed include a 3D anatomical model reconstruction, data fusion of multiple ultrasound volumes and computed tomography (CT), realistic rendering, interactive navigation, and haptic feedbacks in six degrees of freedom (DOF). Simulated ultrasound imagery based on real ultrasound data is presented to users, in real-time, while performing an examination on the needle placement into a virtual anatomical model. Our system delivers a realistic haptic feeling for trainees throughout the simulated needle insertion procedure, permitting repeated practices with no danger to patients.

Orthopedics surgery trainer with PPU-accelerated blood and tissue simulation.

This paper presents a novel orthopedics surgery training system with both the components for modeling as well as simulating the deformation and visualization in an efficient way. By employing techniques such as optimization, segmentation and center line extraction, the modeling of deformable model can be completed with minimal manual involvement. The novel trainer can simulate rigid body, soft tissue and blood with state-of-the-art techniques, so that convincing deformation and realistic bleeding can be achieved. More important, newly released Physics Processing Unit (PPU) is adopted to tackle the high requirement for physics related computations. Experiment shows that the acceleration gain from PPU is significant for maintaining interactive frame rate under a complex surgical environments of orthopedics surgery.

Virtual reality techniques. Application to anatomic visualization and orthopaedics training.

Surgical training systems using virtual reality simulation techniques offer a cost-effective alternative to traditional training methods. In this sense, techniques for interactive visualization and virtual reality surgery have been one of the very important research areas. We describe various techniques we have used in developing a virtual reality system for anatomic visualization and training arthroscopic knee surgeons. Virtual models used in our systems are constructed from the Visible Human Project and Chinese Visible Human data sets. We present our various developments in segmentation, personal-computer-based real-time volume visualization, soft tissue deformation with topological change in real-time using finite element analysis, and soft tissue cutting with tactile feedback.