Zoom-invariant vision of figural shape: the mathematics of cores
Computer Vision and Image Understanding
Zoom-invariant vision of figural shape: effects on cores of image disturbances
Computer Vision and Image Understanding
Model-based detection of tubular structures in 3D images
Computer Vision and Image Understanding
Efficient Skeletonization of Volumetric Objects
IEEE Transactions on Visualization and Computer Graphics
Flux Maximizing Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Detection and Quantification of Line and Sheet Structures in 3-D Images
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Automation of hessian-based tubularity measure response function in 3D biomedical images
Journal of Biomedical Imaging - Special issue on modern mathematics in biomedical imaging
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This paper describes an algorithm for extracting pulmonary vascular trees (arteries plus veins) from three-dimensional (3D) thoracic computed tomographic (CT) images. The algorithm integrates tube enhancement filter and traversal approaches which are based on eigenvalues and eigenvectors of a Hessian matrix to extract thin peripheral segments as well as thick vessels close to the lung hilum. The resultant algorithm was applied to a simulation data set and 44 scans from 22 human subjects imaged via multidetector-row CT (MDCT) during breath holds at 85% and 20% of their vital capacity. A quantitative validation was performed with more than 1000 manually identified points selected from inside the vessel segments to assess true positives (TPs) and 1000 points randomly placed outside of the vessels to evaluate false positives (FPs) in each case. On average, for both the high and low volume lung images, 99% of the points was properly marked as vessel and 1% of the points were assessed as FPs. Our hybrid segmentation algorithm provides a highly reliablemethod of segmenting the combined pulmonary venous and arterial trees which in turn will serve as a critical starting point for further quantitative analysis tasks and aid in our overall goal of establishing a normative atlas of the human lung.