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IEEE Computer Graphics and Applications. 01/2012; 32:78-86.
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ABSTRACT: The epicardial potential (EP)-targeted inverse problem of electrocardiography (ECG) has been widely investigated as it is demonstrated that EPs reflect underlying myocardial activity. It is a well-known ill-posed problem as small noises in input data may yield a highly unstable solution. Traditionally, L2-norm regularization methods have been proposed to solve this ill-posed problem. But the L2-norm penalty function inherently leads to considerable smoothing of the solution, which reduces the accuracy of distinguishing abnormalities and locating diseased regions. Directly using the L1-norm penalty function, however, may greatly increase computational complexity due to its non-differentiability. We propose an L1-norm regularization method in order to reduce the computational complexity and make rapid convergence possible. Variable splitting is employed to make the L1-norm penalty function differentiable based on the observation that both positive and negative potentials exist on the epicardial surface. Then, the inverse problem of ECG is further formulated as a bound-constrained quadratic problem, which can be efficiently solved by gradient projection in an iterative manner. Extensive experiments conducted on both synthetic data and real data demonstrate that the proposed method can handle both measurement noise and geometry noise and obtain more accurate results than previous L2- and L1-norm regularization methods, especially when the noises are large.
Physics in Medicine and Biology 09/2011; 56(19):6291-310. · 2.83 Impact Factor
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ABSTRACT: The segmentation of the liver in CT (Computed Tomography) volumetric data provide a basis for constructing the three dimensional anatomical model, which is an important prerequisite for a variety of clinical and research applications. In this paper, we introduce an algorithm for semi-automatic liver segmentation in three dimensional CT images based on the deformable model. The deformable model is initialized as an existing simplex mesh model of the liver, which was created from manual segmentation. Deformation of the shape model to adapt to the boundary of a new liver is formulated by minimizing a local cost function associated with each model vertex. In particular, we introduce a new attractor force component to constrain the mesh deformation and refine the segmentation result. The experimental results demonstrated the effectiveness of the proposed method.
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on; 08/2011
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ABSTRACT: A medical image reconstruction method based on sparse Bayesian compressed sensing is presented, and the method employs a hierarchical model of the Laplace prior to model the sparse wavelet coefficients and unknown images. The experiments are designed to compare the Bayesian Compressed Sensing (BCS) method with the Basis Pursuit (BP) algorithm and the Orthogonal Matching Pursuit (OMP) algorithm. The results imply that the presented algorithm exceeds the greedy algorithm and the linear programming such as BP and OMP etc.
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on; 08/2011
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ABSTRACT: Non-invasive quantification of bone shape is crucial in orthopaedic research. The primary objective of this study was to develop an automated statistical morphometry method for comparing the cross-sectional images of normal and diseased bones. The secondary objective involved demonstrating the effectiveness of the proposed method in distinguishing AIS patients from normal controls. This framework is composed of bone segmentation followed by measurements of maximum and minimum bone diameters, inter-group and intra-group statistical morphometry, and statistical analysis of bone thickness. The proposed framework was applied to detect bone morphological abnormality in adolescent idiopathic scoliosis (AIS) patients. The forearm bones in cross-sectional peripheral quantitative computed tomography (pQCT) images from 23 AIS patients and 16 normal controls were analyzed. The radius outer contour was found to be rounder and the radius cortical bone was thinner in AIS patients compared to normal controls.
Medical Engineering & Physics 06/2011; 33(9):1103-7. · 1.62 Impact Factor
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ABSTRACT: A VR-based training system for practicing biopsies simulates ultrasound imagery by stitching multiple ultrasound volumes on the basis of a 3D scale-invariant feature transform algorithm. In addition, a six-degree-of-freedom force model delivers a realistic haptic rendering of needle insertion.
IEEE Computer Graphics and Applications 05/2011; · 1.41 Impact Factor
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ABSTRACT: The objective evaluation of the color and shade in stained images remains unsolved and is frequently and extensively encountered in biomedical studies. Most of the evaluations on the color and shade in the stained images are currently performed by subjective grading, which is prone to be affected by inter-reader variation. This paper introduces a novel approach to automatically quantify the color and shade in the stained histological image based on its similarity map in the CIELAB color space with respect to a user specified reference color. The proposed algorithm was applied on three datasets, i.e., a phantom image, the Prussian blue staining of human osteosarcoma cell culture, and histological sections of the Prussian blue stained rat kidney, liver and spleen. The result shows that our method is able to represent the color and shade as a numerical value that correlated well with human perception.
Cytometry Part A 03/2011; 79(4):311-6. · 3.73 Impact Factor
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ABSTRACT: To accelerate the simultaneous algebraic reconstruction technique (SART) with motion compensation for speedy and quality computed tomography reconstruction by exploiting CUDA-enabled GPU.
Two core techniques are proposed to fit SART into the CUDA architecture: (1) a ray-driven projection along with hardware trilinear interpolation, and (2) a voxel-driven back-projection that can avoid redundant computation by combining CUDA shared memory. We utilize the independence of each ray and voxel on both techniques to design CUDA kernel to represent a ray in the projection and a voxel in the back-projection respectively. Thus, significant parallelization and performance boost can be achieved. For motion compensation, we rectify each ray's direction during the projection and back-projection stages based on a known motion vector field.
Extensive experiments demonstrate the proposed techniques can provide faster reconstruction without compromising image quality. The process rate is nearly 100 projections s (-1), and it is about 150 times faster than a CPU-based SART. The reconstructed image is compared against ground truth visually and quantitatively by peak signal-to-noise ratio (PSNR) and line profiles. We further evaluate the reconstruction quality using quantitative metrics such as signal-to-noise ratio (SNR) and mean-square-error (MSE). All these reveal that satisfactory results are achieved. The effects of major parameters such as ray sampling interval and relaxation parameter are also investigated by a series of experiments. A simulated dataset is used for testing the effectiveness of our motion compensation technique. The results demonstrate our reconstructed volume can eliminate undesirable artifacts like blurring.
Our proposed method has potential to realize instantaneous presentation of 3D CT volume to physicians once the projection data are acquired.
International Journal of Computer Assisted Radiology and Surgery 03/2011; 6(2):187-99. · 1.48 Impact Factor
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Proceedings of the International Conference on Human Factors in Computing Systems, CHI 2011, Vancouver, BC, Canada, May 7-12, 2011; 01/2011
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International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, China, July 10-13, 2011, Proceedings; 01/2011
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International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, China, July 10-13, 2011, Proceedings; 01/2011
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International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, China, July 10-13, 2011, Proceedings; 01/2011
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International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, China, July 10-13, 2011, Proceedings; 01/2011
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IEEE Computer Graphics and Applications. 01/2011; 31:36-48.
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ABSTRACT: This paper describes the development of a Chinese Acupuncture Expert System (CAES) that will assist the learning and practice of medical acupuncture. This was the development of a Chinese Acupuncture Expert System which incorporated eight functional modules. These modules were 1) Add Patient Record subsystem; 2) Diagnosis subsystem ; 3) Acupuncture Prescription subsystem ; 4) Needle Insertion Position Animation subsystem ; 5) Acupuncture Points Usage Statistic subsystem ; 6) History Query subsystem; 7) Acupuncture Points Query subsystem and 8) Diagnosis Remarks and Diagnosis Record Save subsystem. Two databases were built-Patient Record database and Diagnosis (Acupuncture) Knowledge database. All the Traditional Chinese Medicine (TCM) knowledge and acupuncture treatment prescriptions were extracted from officially used TCM textbooks and received guidance and expert advice from two acupuncturists working in this project. A Chinese Acupuncture Expert System (CAES) was built, which after the input from users of any Chinese disease symptoms and signs, it can provide a list of related TCM syndrome diagnoses based on the patients' disease symptoms and signs, and at the same time it can offer advice of the appropriate Chinese acupuncture treatment to the users. CAES also provided text descriptions and acupuncture animations showing the acupoint locations and the direction and depth of the needle insertion technique. Therefore users can easily learn acupuncture and practice it. This new acupuncture expert system will hopefully provide an easy way for users to learn and practice Chinese Acupuncture and establish its usefulness after it was fully evaluated.
Journal of Medical Systems 01/2011; 36(3):1883-90. · 1.13 Impact Factor
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ABSTRACT: 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.
International Journal of Biomedical Imaging 01/2011; 2011:815246.
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ABSTRACT: 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.
Progress in Biophysics and Molecular Biology 12/2010; 103(2-3):252-61. · 3.20 Impact Factor
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ABSTRACT: Enhancement of vessels in medical images is still an unsolved problem. Multiscale approaches were proposed to improve the vessel enhancement effect based on the structure size and image resolution. Vessel enhancing diffusion (VED) filter is one of the multiscale approaches, which was based on the scale space theory. VED performs well on enhancing vessel structures but cannot preserve complex structures such as the vessel junctions. In this paper, a structure-preserving diffusion tensor is defined in the diffusion equation, which brings a structure-preserving vessel enhancing diffusion filter. Through the multiscale framework, the proposed method enhances the vessel structures especially the complex structure such as junctions. Experimental evaluation performed on various vessel data sets demonstrated the effectiveness of the proposed method.
Image Processing (ICIP), 2010 17th IEEE International Conference on; 10/2010
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ABSTRACT: High-resolution peripheral quantitative computed tomography (HR-pQCT) is a new noninvasive bone imaging technology that generates high-resolution 3-D images for quantitatively analysis of the bone microarchitecture in human. To enable quantitative evaluation of bone changes, either bone gain or loss, accurate alignment between the baseline and follow-up scans of the same individual is necessary. The major difficulties in achieving efficient and automatic registration of the HR-pQCT data are the large data size, deformations in the nonskeletal structures, and the complexity of the trabecular bone geometry. In this paper, we propose an automatic surface-based approach for fast and accurate registration of the HR-pQCT data, where the rigid registration is applied on the surfaces of the bony structures extracted from the grayscale HR-pQCT. The bony structure segmentation is performed via an automatic method that can adaptively determine the thresholds for separating the bony structure from the background and nonskeletal tissues. Experimental results performed on ten pairs of baseline and follow-up wrist scans of five adolescents and five elderly patients with osteoporosis showed the advantage of the proposed method in the high degree of automation, while the resultant parameters describing bone mineral density and trabecular architecture after registration were comparable with the outputs of the scanner's software. This automatic and accurate matching procedure may contribute to the clinical application and research of HR-pQCT.
IEEE Transactions on Information Technology in Biomedicine 10/2010; · 1.68 Impact Factor
