: This paper describes a method for the enhancement of curvilinear structures such as vessels and bronchi in 3D medical images. A 3D line enhancement filter is developed with the aim of discriminating line structures from other structures and recovering line structures of various widths. The 3D line filter is based on a combination of the eigenvalues of the 3D Hessian matrix. Multi-scale integration is formulated by taking the maximum among single-scale filter responses, and its characteristics are examined to derive criteria for the selection of parameters in the formulation. The resultant multi-scale line-filtered images provide significantly improved segmentation and visualization of curvilinear structures. The usefulness of the method is demonstrated by the segmentation and visualization of brain vessels from MRI (magnetic resonance imaging) and MRA (magnetic resonance angiography), bronchi from a chest CT, and liver vessels (portal veins) from an abdominal CT. Keywords: 3D image ...

Vessel segmentation algorithms are the critical components of circulatory blood vessel analysis systems. We present a survey of vessel extraction techniques and algorithms. We put the various vessel extraction approaches and techniques in perspective by means of a classification of the existing research. While we have mainly targeted the extraction of blood vessels, neurosvascular structure in particular, we have also reviewed some of the segmentation methods for the tubular objects that show similar characteristics to vessels. We have divided vessel segmentation algorithms and techniques into six main categories: (1) pattern recognition techniques, (2) model-based approaches, (3) tracking-based approaches, (4) artificial intelligence-based approaches, (5) neural network-based approaches, and (6) miscellaneous tube-like object detection approaches. Some of these categories are further divided into sub- categories. We have also created tables to compare the papers in each category against such criteria as dimensionality, input type, pre-processing, user interaction, and result type.

This paper describes an object-based approach to the problem of reconstructing three-dimensional descriptions of arterial trees from a few angiographic projections. The method incorporates aprioriknowledge of the structure of branching arteries into a natural optimality criterion that encompasses the entire arterial tree. This global approach enables reconstruction from a few noisy projection images. We present an efficient optimization algorithm for object estimation, and demonstrate its performance on simulated, phantom, and in vivo magnetic resonance angiograms.

In this paper we present a algorithm for the real-time enhancement and detection of blood vessels in medical images. The algorithm is based on a set of linear lters sensitive to vessels of dierent orientation and thickness. Such lters are obtained as linear combinations of properly shifted Gaussian kernels. The output of multiple oriented vessel-enhancing lters can be integrated to obtain images in which vessels are highly enhanced independently of their direction and thickness. To avoid spurious responses in the presence of step edges or to enhance the skeletons of vessels, the output of directional lters can be validated before integration. Skeleton detection and vessel segmentation can be performed via thresholding with hysteresis. Experimental results on synthetic images and real coronary arteriograms are reported. Keywords Vessel Enhancement, Vessel Detection, Realtime Processing, Skeleton Detection, Vessel Segmentation. Address for Correspondence Riccardo Poli...

There is considerable currentinterest in deriving accurate dimensional measurements of the internal geometry of complex manufactured parts, particularly castings. This paper describes an approachtothereconstruction of 3D part geometry from multiple digital X-ray images. A novel method for radiographic stereo is described whichtakes into accountthespecial imaging geometry of the digital X-ray sensor modeled by a linear moving array, or pushbroom, camera. The 3D reconstruction algorithm employs a nominal geometric model which is perturbed by X-rayimage constraints. Manufacturing applications are discussed and illustrated by experimental results on synthetic phantoms and actual casting images.

. We propose a hybrid method using both geometric and intensity information to reconstruct multiple curved object boundaries from sparse sets of X-ray images. We have implementated this approach and present several examples on real and synthetic data. 1 Introduction We propose a hybrid method using both geometric and intensity information to reconstruct multiple curved object boundaries from sparse sets of X-ray (digital radiographic) images. Working in the plane, we reconstruct smooth boundary curves from one-dimensional X-ray images. Our approach has applications in medical imaging (reconstruction of organs and tumors from sparse sets of X-ray images, stereo reconstruction of coronary arteries from angiograms, registration of CT models and X-ray images) and manufacturing (part acquisition and tolerancing, registration, and non-destructive evaluation). Reconstruction from a sparse or limited-angle set of X-ray images is important for a number of reasons. If a few views are adequate f...

In this study, a method for reconstructing ellipsoids from its three projection contours is described. The line integral projection of elipsoid with uniform density is developed for any projection view. Our reconstruction algorithm starts from the detecting projection contours that has elliptic shape. Then three sets of estimated ellipse parameters are used in reconstructing the ellipsoid. The method takes into account background, noise and blurring. The performance of the method is evaluated for various types of background structures, different ellipsoid dimensions and different levels of noise. Result demonstrates the validity and usefulness of the proposed method. I.

Arterial diameter estimation from x-ray cineangiograms is important for quantifying coronary artery disease (CAD) and for evaluating therapy. This is a difficult problem especially in narrow cross-sections which are plagued by large measurement errors. We present a novel diameter estimator which reduces the magnitude and variability of this measurement error. Our approach is based on a parametric non-linear imaging model for xray cine-angiography and a practical method for estimating unknown model parameters directly from the image data. These developments allow us to exploit additional diameter information contained within the intensity profile amplitude --- a feature which is overlooked by existing methods. Our implementation uses a two-step procedure: the first step estimates the imaging model parameters directly from the angiographic frame; the second step uses these measurements to estimate the vessel parameters of interest from the the same image. In Monte-Carlo simulation over a range of imaging conditions, our approach consistently produced lower estimation error and variability than conventional methods. In actual x-ray images, our estimator is also better than existing methods for the diameters examined (0.4 -- 4.0). These improvements are most significant in the range of narrow vessel widths associated with severe coronary artery disease.

Objective testing of centerline extraction accuracy in quantitative coronary angiography (QCA) algorithms is a very difficult task. Standard tools for this task are not yet available. We present a simulation tool that generates synthetic angiographic images of a single coronary artery with predetermined centerline and diameter function. This simulation tool was used creating a library of images for the objective comparison and evaluation of QCA algorithms. This technique also provides the means for understanding the relationship between the algorithms' performance and limitations and the vessel's geometrical parameters. In this paper, two algorithms are evaluated and the results are presented. Index Terms---Centerline estimation, coronary geometrical complexity, lumen centerline detection, performance evaluation, QCA, simulation tool.