We propose an anatomy-based approach for an efficient construction of a three-dimensional human normal cerebral arterial model from segmented and skeletonized angiographic data. The centerline-based model is used for an accurate angiographic data representation. A vascular tree is represented by tubular segments and bifurcations whose construction takes into account vascular anatomy. A bifurcation is defined quantitatively and the algorithm calculating it is given. The centerline is smoothed by means of a sliding average filter. As the vessel radius is sensitive to quality of data as well as accuracy of segmentation and skeletonization, radius outlier removal and radius regression algorithms are formulated and applied. In this way, the approach compensates for some inaccuracies introduced during segmentation and skeletonization. To create the frame of vasculature, we use two different topologies: tubular and B-subdivision based. We also propose a technique to prevent vessel twisting. The analysis of the vascular model is done on a variety of data containing 258 vascular segments and 131 bifurcations. Our approach gives acceptable results from anatomical, topological and geometrical standpoints as well as provides fast visualization and manipulation of the model. The approach is applicable for building a reference cerebrovascular atlas, developing applications for simulation and planning of interventional radiology procedures and vascular surgery, and in education.

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Medical imaging research and clinical applications usually require combination and integration of various techniques ranging from image processing and analysis to realistic visualization to user-friendly interaction. Researchers with different backgrounds coming from diverse areas have been using numerous types of hardware, software, and environments to obtain their results. We also observe that students often build their tools from scratch resulting in redundant work. A generic and flexible medical imaging and visualization toolkit would be helpful in medical research and educational institutes to reduce redundant development work and hence increase research efficiency. This paper presents our experience in developing a Medical Imaging and Visualization Toolkit (BIL-kit) that is a set of comprehensive libraries as well as a number of interactive tools. The BIL-kit covers a wide range of fundamental functions from image conversion and transformation, image segmentation, and analysis to geometric model generation and manipulation, all the way up to 3D visualization and interactive simulation. The toolkit design and implementation emphasize the reusability and flexibility. BIL-kit is implemented in the Java language so that it works in hybrid and dynamic research and educational environments. This also allows the toolkit to extend its usage for the development of Web-based applications. Several BIL-kit-based tools and applications are presented including image converter, image processor, general anatomy model simulator, vascular modeling environment, and volume viewer. BIL-kit is a suitable platform for researchers and students to develop visualization and simulation prototypes, and it can also be used for the development of clinical applications.

No abstract

Medical imaging research and clinical applications usually require combination and integration of various techniques ranging from image processing and analysis to realistic visualization to user-friendly interaction. Researchers with different backgrounds coming from diverse areas have been using numerous types of hardware, software, and environments to obtain their results. We also observe that students often build their tools from scratch resulting in redundant work. A generic and flexible medical imaging and visualization toolkit would be helpful in medical research and educational institutes to reduce redundant development work and hence increase research efficiency. This paper presents our experience in developing a Medical Imaging and Visualization Toolkit (BIL-kit) that is a set of comprehensive libraries as well as a number of interactive tools. The BIL-kit covers a wide range of fundamental functions from image conversion and transformation, image segmentation, and analysis to geometric model generation and manipulation, all the way up to 3D visualization and interactive simulation. The toolkit design and implementation emphasize the reusability and flexibility. BIL-kit is implemented in the Java language so that it works in hybrid and dynamic research and educational environments. This also allows the toolkit to extend its usage for the development of Web-based applications. Several BIL-kit-based tools and applications are presented including image converter, image processor, general anatomy model simulator, vascular modeling environment, and volume viewer. BIL-kit is a suitable platform for researchers and students to develop visualization and simulation prototypes, and it can also be used for the development of clinical applications.