Vascular Centerline Research Articles

Curve-Like Structure Extraction Using Minimal Path Propagation With Backtracking.

Minimal path techniques can efficiently extract geometrically curve-like structures by finding the path with minimal accumulated cost between two given endpoints. Though having found wide practical applications (e.g., line identification, crack detection, and vascular centerline extraction), minimal path techniques suffer from some notable problems. The first one is that they require setting two endpoints for each line to be extracted (endpoint problem). The second one is that the connection might fail when the geodesic distance between the two points is much shorter than the desirable minimal path (shortcut problem). In addition, when connecting two distant points, the minimal path connection might become inefficient as the accumulated cost increases over the propagation and results in leakage into some non-feature regions near the starting point (accumulation problem). To address these problems, this paper proposes an approach termed minimal path propagation with backtracking. We found that the information in the process of backtracking from reached points can be well utilized to overcome the above problems and improve the extraction performance. The whole algorithm is robust to parameter setting and allows a coarse setting of the starting point. Extensive experiments with both simulated and realistic data are performed to validate the performance of the proposed method.

Quantitative Analysis of Deformable Model-Based 3-D Reconstruction of Coronary Artery From Multiple Angiograms.

Three-dimensional (3-D) reconstruction of the coronary artery is important for the diagnosis and interventional treatment of cardiovascular diseases. In this paper, a novel mean composited external force back-projective composition model is proposed and integrated into the deformable model framework for the 3-D reconstruction of coronary arteries from multiple angiograms. The parametric snake evolves toward the real vascular centerline in 3-D space based on the integrated internal energy and composited external energy. In addition, a polynomial function is constructed to determine the diameter of the cross section of the vascular segments, which fully utilizes the back-projection information of multiple angiograms. The deformable and proposed methods are comparatively validated using phantom datasets and routine angiographic images with respect to space and reprojection Euclidean distance errors. The experimental results demonstrate the effectiveness and robustness of the proposed model, which can achieve a mean space error of 0.570 mm and a mean reprojection error of 0.351 mm. In addition, the influence of the angle difference to the reconstruction accuracy is discussed and validated on phantom datasets, which demonstrate that an angle difference of for any two angiograms is suitable for the 3-D reconstruction process.

External force back-projective composition and globally deformable optimization for 3-D coronary artery reconstruction

The clinical value of the 3D reconstruction of a coronary artery is important for the diagnosis and intervention of cardiovascular diseases. This work proposes a method based on a deformable model for reconstructing coronary arteries from two monoplane angiographic images acquired from different angles. First, an external force back-projective composition model is developed to determine the external force, for which the force distributions in different views are back-projected to the 3D space and composited in the same coordinate system based on the perspective projection principle of x-ray imaging. The elasticity and bending forces are composited as an internal force to maintain the smoothness of the deformable curve. Second, the deformable curve evolves rapidly toward the true vascular centerlines in 3D space and angiographic images under the combination of internal and external forces. Third, densely matched correspondence among vessel centerlines is constructed using a curve alignment method. The bundle adjustment method is then utilized for the global optimization of the projection parameters and the 3D structures. The proposed method is validated on phantom data and routine angiographic images with consideration for space and re-projection image errors. Experimental results demonstrate the effectiveness and robustness of the proposed method for the reconstruction of coronary arteries from two monoplane angiographic images. The proposed method can achieve a mean space error of 0.564 mm and a mean re-projection error of 0.349 mm.

Quantitative Analysis of Deformable Model based 3-D Reconstruction of Coronary Artery from Multiple Angiograms

Three-dimensional (3-D) reconstruction of the coronary artery is important for the diagnosis and interventional treatment of cardiovascular diseases. In this paper, a novel mean composited external force back-projective composition model is proposed and integrated into the deformable model framework for the 3-D reconstruction of coronary arteries from multiple angiograms. The parametric snake evolves toward the real vascular centerline in 3-D space based on the integrated internal energy and composited external energy. In addition, a polynomial function is constructed to determine the diameter of the cross section of the vascular segments, which fully utilizes the back-projection information of multiple angiograms. The deformable and proposed methods are comparatively validated using phantom datasets and routine angiographic images with respect to space and reprojection Euclidean distance errors. The experimental results demonstrate the effectiveness and robustness of the proposed model, which can achieve a mean space error of 0.570 mm and a mean reprojection error of 0.351 mm. In addition, the influence of the angle difference to the reconstruction accuracy is discussed and validated on phantom datasets, which demonstrate that an angle difference of for any two angiograms is suitable for the 3-D reconstruction process.

3D ultrasound centerline tracking of abdominal vessels for endovascular navigation

Vessel lumen centerline extraction is important for intraoperative tracking of abdominal vessels and guidance of endovascular instruments. Three-dimensional ultrasound has gained increasing acceptance as a safe and convenient surgical image guidance modality. We aimed to optimize vascular centerline detection and tracking in 3D ultrasound. To overcome the intrinsic limitation of low ultrasound image quality, an active contour method (snake) was used to track changes in vessel geometry. We tested two variants of a classic snake using the image gradient and gradient vector field (GVF) as external forces. We validated these methods in liver ultrasound images of 10 healthy volunteers, acquired at three breath-holding instances during the exhalation phase. We calculated the distances between the vessel centerlines as detected by algorithms and a gold standard consisting of manual annotations performed by an expert. Both methods (GVF and image gradient) can accurately estimate the actual centerlines with average Euclidean distances of 0.77 and 1.24 mm for GVF and gradient, respectively. Both methods can automatically follow vessel morphology and position changes. The proposed approach is feasible for liver vessel centerline extraction from 3D ultrasound images. The algorithm can follow the movement of the vessels during respiration; further improvements of hardware components are needed for a real-time implementation.

Isolated kidney phantom for development of biothermal vascular models with application to high intensity focused ultrasound therapy

A methodology using magnetic resonance angiography (MRA) is presented for identifying thermally significant blood vessels in isolated kidneys, specifically for use in biothermal model development with application to high intensity focused ultrasound (HIFU). A combination of a proven preservation technique, newly developed MR-compatible experimental procedures and the refinement of MR pulse sequence parameters was used to determine vascular characteristics using high-resolution three-dimensional time-of-flight MRA image of flow through isolated kidneys. Results presented are twofold. First, improved vessel visibility was attained through decreasing the magnetic resonance imaging bandwidth from 150 to 30 Hz/pixel while simultaneously increasing the echo time, repetition time, and flip angle; vascular center line extraction showed an 18% improvement in the number of vessel segments detected and a 23% increase in length of the terminal segments over a base line technique without improvements. Second, the overall system was shown to be practical to determine vascular flow effects during HIFU heating; testing results from heating the kidney with HIFU are presented, showing a decrease of average kidney temperature with an increase of flow rate through the kidney with localized cooling demonstrated surrounding known vessel locations.

Reconstruction of three-dimensional coronary arterial dynamics from multi-view angiogram sequences

A method for reconstructing 3-D motion of coronary arteries from single-plane X-ray angiogram sequences on two approximately orthogonal views is proposed. 2-D motion is firstly estimated separately along vascular centerlines extracted from angiographic projection pairs. The 3-D displacement vector of each arterial skeleton point at one instant is then reconstructed by calculating the spatial coordinates of its two ends from corresponding projections. 3-D configuration and dynamics of arteries are finally characterized. The effectiveness of the algorithm has been demonstrated on vascular phantom images and clinical angiograms and results are encouraging.

Vascular centerline extraction in 3D MR angiograms to optimize acquisition plane for blood flow measurement by phase contrast MRI

Cerebral blood flow (CBF) is an important parameter in the diagnosis and choice of therapeutic strategy of the cerebro-vascular disorders. Reliable quantification of the CBF requires a preliminary determination of an imaging plane close to orthogonal cross-sections of the vessel of interest. This can be calculated for each vessel separately, but a simultaneous determination for the four principal arteries irrigating the brain would improve the acquisition process. This article presents two algorithms devised for this purpose. The first one determines the centerline of each of the four vessels of interest. The centerline extraction is done by an iterative prediction–estimation tracking technique based on a multi-scale analysis of image moments and on a shape model close to “snakes”. The second algorithm seeks the plane that minimizes a criterion of orthogonality with respect to these centerlines. The method was evaluated on 3D images of 35 patients. All but one centerline, out of 140 arteries, were correctly extracted. For each patient the algorithm found a plane with an orthogonality error not exceeding 12° per artery. The operating time (interaction + computation) was within 1 min by patient on a standard PC.

Snake modeling and distance transform approach to vascular centerline extraction and quantification

A new method for fully automated centerline extraction and quantification of microvascular structures in confocal microscopy (CM) images is presented. Our method uses the idea of active contour models as well as path planning and distance transforms for the three-dimensional centerline extraction of elongated objects such as vessels. The proposed approach is especially efficient for centerline extraction of complex branching structures. The method performance is validated in several CM images of both normal and stroked rat brains as well as simulated objects. The results confirm the efficiency of the proposed method in extracting the medial curve of vessels, which is essential for the computation of quantitative parameters.