DocumentCode :
2809160
Title :
A local maximum intensity projection tracing of vasculature in Knife-Edge Scanning Microscope volume data
Author :
Han, Donghyeop ; Keyser, John ; Choe, Yoonsuck
Author_Institution :
Dept. of Comput. Sci., Texas A&M Univ., College Station, TX, USA
fYear :
2009
fDate :
June 28 2009-July 1 2009
Firstpage :
1259
Lastpage :
1262
Abstract :
A local maximum intensity projection (MIP) approach to the extraction of a 3D vascular network, acquired by the Knife-Edge Scanning Microscope (KESM), is presented. We build a local volume for local MIP processing at each tracing step in order to reduce the dimension of input data from 3D to 2D, which leads to a 65.22% reduction of computation time compared to 3D tracing method. The proposed method makes use of existing 2D tracing methods, extending them into a 3D tracing method. Our experimental results show that our approach can rapidly and accurately extract the medial axis of vascular data acquired by the KESM.
Keywords :
biomedical optical imaging; blood vessels; brain; feature extraction; medical image processing; neurophysiology; optical microscopy; 2D tracing method; 3D neuronal vascular network extraction; 3D tracing method; KESM; MIP approach; brain vasculature; computation time reduction; input dimension reduction; knife-edge scanning microscope volume data; local MIP processing; local maximum intensity projection tracing; medial axis vascular data extraction; Computational complexity; Computer science; Data mining; Filters; Intelligent networks; Kernel; Medical conditions; Mice; Microscopy; Object detection; Dimension Reduction; Hessian Filter; Local MIP; Tracing; Vasculature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
ISSN :
1945-7928
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
Type :
conf
DOI :
10.1109/ISBI.2009.5193291
Filename :
5193291
Link To Document :
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