Principal Curves for Lumen Center Extraction and Flow Channel Width Estimation in 3-D Arterial Networks: Theory, Algorithm, and Validation

Abstract

Abstract-We present an energy-minimization-based framework for locating the centerline and estimating the width of tubelike objects from their structural network with a nonparametric model. The nonparametric representation promotes simple modeling of nested branches and -way furcations, i.e., structures that abound in an arterial network, e.g., a cerebrovascular circulation. Our method is capable of extracting the entire vascular tree from an angiogram in a single execution with a proper initialization. A succinct initial model from the user with arterial network inlets, outlets, and branching points is sufficient for complex vasculature. The novel method is based upon the theory of principal curves. In this paper, theoretical extension to grayscale angiography is discussed, and an algorithm to find an arterial network as principal curves is also described. Quantitative validation on a number of simulated data sets, synthetic volumes of 19 BrainWeb vascular models, and 32 Rotterdam Coronary Artery volumes was conducted. We compared the algorithm to a state-of-the-art method and further tested it on two clinical data sets. Our algorithmic outputs-lumen centers and flow channel widths-are important to various medical and clinical applications, e.g., vasculature segmentation, registration and visualization, virtual angioscopy, and vascular atlas formation and population study.

Metal work-function-dependent barrier height of Ni contacts with metal-embedded nanoparticles to 4H-SiC

“…To investigate the effect of the NPs at the Ni/SiC interface on the electrical properties, current-voltage [ I-V ] and capacitance-voltage [ C-V ] characteristics of the devices were measured by using a Keithley 4200 semiconductor parameter analyzer (Keithley Instruments Inc., Cleveland, OH, USA). The experimental results have also been compared with an analytic model based on Tung's theory [11-13] and further verified by considering band diagram and electric field distribution using a physics-based two-dimensional numerical simulator Atlas (Silvaco Inc., Santa Clara, CA, USA) [19]. …”

Automatic segmentation method for bone and blood vessel in murine hindlimb

“…It is essential to delineate blood vessels from hindlimbs in the diagnosis and treatment of peripheral arterial occlusive disease and in the registration of medical images obtained at different times. 1,2 Magnetic resonance angiography is commonly utilized to differentiate the signal of peripheral blood vessels from backgrounds by the injection of blood pool agents. 3,4 Meanwhile, the detection of vascular diseases is also conducted via computed tomography angiography (CTA).…”

“…Aiming to handle the problems existing in the three above-mentioned aspects, we propose an automatic method to segment bones and blood vessels in murine hindlimb in this paper. The main contribution of this work is threefold: (1) To eliminate the interference of bones on the segmentation of blood vessels, we employ the split Bregman method to segment bones in the first place. This is rational because the split Bregman method has high-priority in recognizing object of high gray-scale intensity value and large geometrical size, 32 which exactly corresponds to the properties of bones in murine hindlimb.…”

Review. Automatic Segmentation Techniques of the Coronary Artery Using CT Images in Acute Coronary Syndromes

“…The literature includes several studies that follow the data-driven approach, namely they treat the notion of the vascular tree in a general way, as a set of interconnected tubular structures, with possible bifurcations and stenoses, but without using any anatomical information. These studies usually concentrate on image quality enhancement for vessel recognition, 73 accurate detection of bifurcations and branches, [74][75][76][77] extraction of the most probable centerline, 78,79 vessel diameter estimation, 79,80 and the identification of odd structures. 81,82 Although they are very important in the development of useful medical data processing techniques, these general studies do not take into consideration any anatomical information of a chosen vessel tree.…”