Title :
Blood vessel segmentation using moving-window robust automatic threshold selection
Author :
Wilkinson, Michael H F ; Wijbenga, Tsjipke ; De Vries, Gijs ; Westenberg, Michel A.
Author_Institution :
Inst. of Math. & Comput. Sci., Groningen Univ., Netherlands
Abstract :
Two moving-window methods, using either flat or Gaussian weighted windows, for local thresholding with robust automatic threshold selection are developed. The results show that fast segmentation of blood vessels against a varying background and noise is possible at modest computational cost. Volumes of 128 x 2562 and 2563 can be segmented in 3.1 s and 6.6 s, for flat, and 12.6 s and 30.8 s for Gaussian windows, respectively, on a 1.9 GHz Pentium 4.
Keywords :
blood vessels; image segmentation; medical image processing; Gaussian weighted windows; blood vessel segmentation; flat weighted windows; moving-window robust automatic threshold selection; Background noise; Biomedical imaging; Blood vessels; Detectors; Image edge detection; Image segmentation; Mathematics; Noise reduction; Noise robustness; Rats;
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7803-7750-8
DOI :
10.1109/ICIP.2003.1246876