A novel 3D multi-scale lineness filter for vessel detection

The branching pattern and geometry of coronary microvessels are of high interest to understand and model the blood flow distribution and the processes of contrast invasion, ischemic changes and repair in the heart in detail. Analysis is performed on high resolution, 3D volumes of the arterial microv...

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Bibliographic Details
Published in:	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Vol. 10; no. Pt 2; p. 436
Main Authors:	Bennink, H E, van Assen, H C, Streekstra, G J, ter Wee, R, Spaan, J A E, ter Haar Romeny, B M
Format:	Journal Article
Language:	English
Published:	Germany 2007
Subjects:	Algorithms Artificial Intelligence Coronary Vessels - anatomy & histology Humans Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Imaging, Three-Dimensional - methods Microcirculation - anatomy & histology Microscopy - methods Models, Biological Models, Statistical Pattern Recognition, Automated - methods Reproducibility of Results Sensitivity and Specificity
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Summary:	The branching pattern and geometry of coronary microvessels are of high interest to understand and model the blood flow distribution and the processes of contrast invasion, ischemic changes and repair in the heart in detail. Analysis is performed on high resolution, 3D volumes of the arterial microvasculature of entire goat hearts, which are acquired with an imaging cryomicrotome. Multi-scale vessel detection is an important step required for a detailed quantitative analysis of the coronary microvasculature. Based on visual inspection, the derived lineness filter shows promising results on real data and digital phantoms, on the way towards accurate computerized reconstructions of entire coronary trees. The novel lineness filter exploits the local first and second order multi-scale derivatives in order to give an intensity-independent response to line centers and to suppress unwanted responses to steep edges.
DOI:	10.1007/978-3-540-75759-7_53