Paper
12 June 1986 Automated Tracking Of The Vascular Tree In DSA Images Using A Double-Square-Box Region-Of-Search Algorithm
Kenneth R. Hoffmann, Kunio Doi, Heang-Ping Chan, Laura Fencil, Hiroshi Fujita, Alan Muraki
Author Affiliations +
Proceedings Volume 0626, Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems; (1986) https://doi.org/10.1117/12.975409
Event: Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems (PACS IV) for Medical Applications, 1986, Newport Beach, CA, United States
Abstract
We have developed a double-square-box region-of-search algorithm for semi-automated tracking of the vascular tree. Starting from a user-specified point, the algorithm accurately and automatically tracks the connected vessels in the entire vascular tree. In this study, we used the tracking algorithm in conjunction with the iterative deconvolution technique to obtain accurate vessel sizes and contrasts along the vessels being tracked. The tracking algorithm used the vessel size information to generate square-box regions of search for subsequent tracking points. Both the vessel size and the vessel contrast were monitored to determine the point at which tracking of a particular vessel would be terminated. The vessel sizes and contrasts along the vascular tree will be useful for further quantitative analysis of the vessels. At present, the algorithm accurately tracks the vascular tree into regions in which the ratio between the vessel contrast and the root mean square (RMS) noise is approximately 3 for vessel sizes of 0.5 mm or more.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth R. Hoffmann, Kunio Doi, Heang-Ping Chan, Laura Fencil, Hiroshi Fujita, and Alan Muraki "Automated Tracking Of The Vascular Tree In DSA Images Using A Double-Square-Box Region-Of-Search Algorithm", Proc. SPIE 0626, Application of Optical Instrumentation in Medicine XIV and Picture Archiving and Communication Systems, (12 June 1986); https://doi.org/10.1117/12.975409
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Cited by 40 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Deconvolution

Angiography

Image segmentation

Medicine

Algorithm development

Quantitative analysis

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