Fei Hou

A parallelized 4D reconstruction algorithm for vascular structures and motions based on energy optimization

In this paper, we present a parallel 4D vessel reconstruction algorithm that simultaneously recovers 3D structure, shape, and motion based on multiple views of X-ray angiograms. The fundamental goal is to assist the analysis and diagnosis of interventional surgery in the most efficient way towards interactive and accurate performance. We start with a fully parallelized algorithm to extract vessels as well as their skeletons and topologies from dynamic image sequences. Then, instead of resorting to registration, we present an algorithm to formulate the reconstruction problem as an energy minimization problem with color, coherence, and topology constraints to reconstruct the 3D vessel initially, which is robust to combat noise and incomplete information in images. Next, we incorporate temporal information into our energy optimization framework to track and reconstruct 4D kinematics of the dynamic vessels, which is also capable of recovering previous incomplete and misleading shapes acquired from static images otherwise. We demonstrate our system in coronary arteries reconstruction and movement tracking for percutaneous coronary intervention surgery to help medical practitioners learn about the 3D shapes and their motions of the coronary arteries of specific patient. We envision that our system would be of high assistance for diagnosis and therapy to treat vessel-related diseases in a clinical setting in the near future.

Robust and high-fidelity guidewire simulation with applications in percutaneous coronary intervention system

Real-time and realistic physics-based simulation of deformable objects is of great value to medical intervention, training, and planning in virtual environments. This paper advocates a virtual-reality (VR) approach to minimally-invasive surgery/therapy (e.g., percutaneous coronary intervention) in medical procedures. In particular, we devise a robust and accurate physics-based modeling and simulation algorithm for the guidewire interaction with blood vessels. We also showcase a VR-based prototype system for simulating percutaneous coronary intervention and mimicing the intervention therapy, which affords the utility of flexible, slender guidewires to advance diagnostic or therapeutic catheters into a patients vascular anatomy, supporting various real-world interaction tasks. The slender body of guidewires are modeled using the famous Cosserat theory of elastic rods. We derive the equations of motion for guidewires with continuous energies and integrate them with the implicit Euler solver, that guarantees robustness and stability. Our approachs originality is primarily founded upon its power, flexibility, and versatility when interacting with the surrounding environment, including novel strategies in the hybrid of geometry and physics, material variability, dynamic sampling, constraint handling and energy-driven physical responses. Our experimental results have shown that this prototype system is both stable and efficient with real-time performance. In the long run, our algorithm and system are expected to contribute to interactive VR-based procedure training and treatment planning.

A method of 3D modeling and codec

Abstract3D modeling and codec of real objects are hot issues in the field of virtual reality. In this paper, we propose an automatic registration two range images method and a cycle based automatic global registration algorithm for rapidly and automatically registering all range images and constructing a realistic 3D model. Besides, to meet the requirement of huge data transmission over Internet, we present a 3D mesh encoding/decoding method for encoding geometry, topology and attribute data with high compression ratio and supporting progressive transmission. The research results have already been applied successfully in digital museum.

Trivariate Biharmonic B-Splines

In this paper, we formulate a novel trivariate biharmonic B‐spline defined over bounded volumetric domain. The properties of bi‐Laplacian have been well investigated, but the straightforward generalization from bivariate case to trivariate one gives rise to unsatisfactory discretization, due to the dramatically uneven distribution of neighbouring knots in 3D. To ameliorate, our original idea is to extend the bivariate biharmonic B‐spline to the trivariate one with novel formulations based on quadratic programming, approximating the properties of localization and partition of unity. And we design a novel discrete biharmonic operator which is optimized more robustly for a specific set of functions for unevenly sampled knots compared with previous methods. Our experiments demonstrate that our 3D discrete biharmonic operators are robust for unevenly distributed knots and illustrate that our algorithm is superior to previous algorithms.

Interactive Urban Map Design with Template and Parameterization

Cities are the largest human artifacts and appear often in digital entertainment. To create a virtual city, a roadmap has to be designed and a large number of buildings need to be generated. In this paper, we describe a method for procedurally generating urban map using template based techniques and parameterization algorithms in an interactive way. Our system is designed to allow developers hands on interactive control over the generation process. It can be controlled by a set of parameters that users can alter numerically or by manually operation in order to constrain and guide the results to fit a particular applications need. We achieve this by providing an interface allowing the user to directly manipulate geometric elements such as road intersection nodes and angle range between road segments, and to directly control many aspects of the procedural generation. The results are updated in real time, thus facilitating an interactive design process. Index Terms—map; template; paramerization

A novel method based on color information for scanned data alignment

This paper presents a rapid and robust method to align large sets of range scans captured by a 3D scanner automatically. The method incorporates the color information from the range data into the pairwise registration. Firstly, it detects the features using SIFT (Scale-Invariant Feature Transform) on grayscale images generated from two range scans to align. Then a quasi-dense matching algorithm, based on the match propagation principle, is applied to specify the matching pixel pairs between two images. All matches obtained are mapped to 3D space but in different world coordinates, and fitered by the 3D geometry constraint discovered from the range data. The remaining set of point correspondences is used to estimate the rigid transformation. Finally, a modified ICP (Iterative Closest Point) algorithm is applied to refine the result. The paper also describes a framework to use this alignment method for object reconstruction. The reconstruction proceeds by acquiring several range scans with color information from different directions, following which pair-wise of range data are aligned with the above method selectively and iteratively. Then a model graph containing the correct pair-wise matches is created and a span tree specifying a complete model is constructed. Finally a global optimization is performed to refine the result. This reconstruction technique achieves a robust and high performance in the application of rebuilding the 3D models of culture heritages for virtual museum automatically.

Direct Extraction of Feature Curves from Volume Image for Illustration and Vectorization Based on 2D/3D Curve Mapping

This paper proposes a parallel and direct semantic feature curve extraction method from 3D volume image for vectorization and illustration. Our approach is motivated by reconstructing 3D geometric information from multiple rendered images under multi-view in computer vision. The 2D rendered images are rich in the visual sense by color and opacity that convey the structure of volume data, so it is significant for the user to understand the structure of 3D volume data better if we can recover feature curves from those 2D images. Compared with conventional line extraction methods, which mainly focus on extracting feature curves from iso-surfaces in object space, we extract feature curves directly from volume images. Most of the computation can be computed in parallel on GPU with CUDA acceleration.

Structure-Based Mesh Completion

Meshes acquired with range scanning devices typ- ically contain complex holes missing salient structure features. This paper presents a novel method to complete meshes by means of structure propagation. In our system, firstly, the unknown region is commonly filled with smooth patch that interpolates the shape and density of the surrounding mesh. Secondly, the user manually specifies the missing structure information by extending a few sketch curves from known to unknown area in a proper viewpoint. Thirdly, structure propagation is operated in a greedy manner with constraints of structure and consistency. Finally, structural geometric details are transferred onto the unknown region by operating over the intrinsic representation based on the Laplacian of the mesh. We demonstrate our approach at several examples, showing that complete meshes are generated in a pleasing way and preserve the structural geometric details as much as possible. Index Terms—Mesh completion, sketch, structure propagation.