Results 1 -
6 of
6
3D Visualization of Vasculature: An Overview
"... Summary. A large variety of techniques has been developed to visualize vascular structures. These techniques differ in the necessary preprocessing effort, in the computational effort to create the visualizations, in the accuracy with respect to the underlying image data and in the visual quality of ..."
Abstract
-
Cited by 8 (0 self)
- Add to MetaCart
(Show Context)
Summary. A large variety of techniques has been developed to visualize vascular structures. These techniques differ in the necessary preprocessing effort, in the computational effort to create the visualizations, in the accuracy with respect to the underlying image data and in the visual quality of the result. In this overview, we compare 3D visualization methods and discuss their applicability for diagnosis, therapy planning and educational purposes. We consider direct volume rendering as well as surface rendering. In particular, we distinguish model-based approaches, which rely on model assumptions to create “idealized ” easy-to-interpret visualizations and model-free approaches, which represent the data more faithfully. Furthermore, we discuss interaction techniques to explore vascular structures and illustrative techniques which map additional information on a vascular tree, such as the distance to a tumor. Finally, navigation within vascular trees (virtual angioscopy) is discussed. Despite the diversity and number of existing methods, there is still a demand for future research which is also discussed. 1
Magisterarbeit Robust Segmentation of Tubular Structures in 3D Volume Data
"... Segmentation of tubular structures like blood vessels and airways in 3D volume data is of vital interest for medical applications like diagnosis and surgical planning. The aim of this diploma thesis is to facilitate the efficient analysis of vessels by developing an automatic segmentation method. Fi ..."
Abstract
-
Cited by 2 (0 self)
- Add to MetaCart
(Show Context)
Segmentation of tubular structures like blood vessels and airways in 3D volume data is of vital interest for medical applications like diagnosis and surgical planning. The aim of this diploma thesis is to facilitate the efficient analysis of vessels by developing an automatic segmentation method. First, the method uses a vessel detection filter, which is based on a novel multiscale medialness function. The filter allows to distinguish between tube-like and other structures and provides an estimate of the tube’s radius. Second, centerlines of the tubes are extracted and the vessel tree is reconstructed by taking the physiological properties of the vessels into account. The centerline and radius information is further used to build an initial tube representation. Third, the final segmentation step uses the tube representation to initialize and constrain a level set method for tubular structures. Computer generated phantom data sets are used for evaluation of different levels of known properties of CT data sets. Results show the robustness of the developed method against noise and anisotropic voxels. Finally, experiments with two real CT data sets demonstrate the applicability of the method to different tubular structures. 1 Zusammenfassung Die Segmentierung von tubulären Strukturen, wie z.B. Blutgefäßen oder Atemwegen in 3D-Volumsdaten, ist für medizinische Diagnostik und die
Model-free Surface Visualization of Vascular Trees
"... Expressive and efficient visualizations of complex vascular structures are essential for medical applications, such as diagnosis and therapy planning. A variety of techniques has been developed which provide smooth high-quality visualizations of vascular structures based on rather simple model assum ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Expressive and efficient visualizations of complex vascular structures are essential for medical applications, such as diagnosis and therapy planning. A variety of techniques has been developed which provide smooth high-quality visualizations of vascular structures based on rather simple model assumptions. For diagnostic applications, these model assumptions and the resulting deviations from the actual vessel surface are not acceptable. We present a model-free approach which employs the binary result of a prior vessel segmentation as input. Instead of directly converting the segmentation result into a surface, we compute a point cloud which is adaptively refined at thin structures, where aliasing effects are particularly obvious and artifacts may occur. The point cloud is transformed into a surface representation by means of MPU Implicits, which provide a smooth piecewise quadratic approximation. Our method has been applied to a variety of datasets including pathologic cases. The generated visualizations are considerably more accurate than model-based approaches. Compared to other model-free approaches, our method produces smoother results.
Implicit Reconstruction of Vasculatures Using Bivariate Piecewise Algebraic Splines
"... Abstract—Vasculature geometry reconstruction from volu-metric medical data is a crucial task in the development of computer guided minimally invasive vascular surgery systems. In this paper, a technique for reconstructing the geometry of vasculatures using bivariate implicit splines is developed. Wi ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
(Show Context)
Abstract—Vasculature geometry reconstruction from volu-metric medical data is a crucial task in the development of computer guided minimally invasive vascular surgery systems. In this paper, a technique for reconstructing the geometry of vasculatures using bivariate implicit splines is developed. With the proposed technique, an implicit geometry representation of the vascular tree can be accurately constructed based on the voxels extracted directly from the surface of a certain vascular structure in a given volumetric medical dataset. Experimental results show that the geometric representation built using our method can faithfully represent the morphology and topology of vascular structures. In addition, both the qualitative and the quantitative validations have been performed to show that the reconstructed vessel geometry is of high accuracy and smoothness. An virtual angioscopy system has been implemented to indicate one of the strengths of our proposed method. Index Terms—Implicit modeling, vasculature reconstruction, virtual angioscopy. I.
Open Access Scale-adaptive surface modeling of vascular structures
"... Background: The effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education. These applications require good balance with respect to surface smoothness, surface accuracy, triangle quality and surface size. Methods: Our method first extracts th ..."
Abstract
- Add to MetaCart
(Show Context)
Background: The effective geometric modeling of vascular structures is crucial for diagnosis, therapy planning and medical education. These applications require good balance with respect to surface smoothness, surface accuracy, triangle quality and surface size. Methods: Our method first extracts the vascular boundary voxels from the segmentation result, and utilizes these voxels to build a three-dimensional (3D) point cloud whose normal vectors are estimated via covariance analysis. Then a 3D implicit indicator function is computed from the oriented 3D point cloud by solving a Poisson equation. Finally the vessel surface is generated by a proposed adaptive polygonization algorithm for explicit 3D visualization. Results: Experiments carried out on several typical vascular structures demonstrate that the presented method yields both a smooth morphologically correct and a topologically preserved two-manifold surface, which is scale-adaptive to the local curvature of the surface. Furthermore, the presented method produces fewer and
Advisor
"... To all HCC patients Die Neugier steht immer an erster Stelle eines Problems, das gelöst werden will. — Galileo Galilei (1564- 1642) In liver surgery, tumor resection is often the only curative treatment for patients suffering from liver cancer. A detailed planning must precede the actual interventio ..."
Abstract
- Add to MetaCart
(Show Context)
To all HCC patients Die Neugier steht immer an erster Stelle eines Problems, das gelöst werden will. — Galileo Galilei (1564- 1642) In liver surgery, tumor resection is often the only curative treatment for patients suffering from liver cancer. A detailed planning must precede the actual intervention, because information about liver shape, tumor location, and the arrangement of the vascular structure is required. In addition, quantitative assessment of volumes and distances plays an important role in pre-operative planning. Currently, in clinical routine, an intervention plan is usually elaborated using the information retrieved from a tomographic imaging modality such as X-ray computed tomography. By inspecting a stack of gray-valued two-dimensional images, a threedimensional model must be established mentally. While radiologists are trained for this type of analysis, surgeons often have problems, because they are naturally oriented towards 3D due to the nature of their clinical work.
