Laser & Optoelectronics Progress, Volume. 55, Issue 4, 041101(2018)
Algorithm of Automatic Detection of Blood Vessel Stenosis with Sub-Pixel Level of Digital Subtraction Angiography
Figures & Tables(7)
Fig. 1. Image enhancement effects of adaptive multi-scale filtering. (a) Original image; (b) image after multi-scale self-adaptive filtering
Fig. 2. Extracted central axis of blood vessel. (a) Blood vessel after multi-scale self-adaptive filtering; (b) central axis of blood vessel
Fig. 3. Sketch of sub-pixel edge detection. (a) Image of ideal step edge; (b) image of ideal step edge after rotation
Fig. 4. Sub-pixel edge extraction and stenosis detection based on Zernike moments. (a) Extraction of sub-pixel edge; (b) schematic of diameter measurement based on dynamical ball
Table 1. Stenosis experimental and contrast results of DSA images (stenosis rate of NASCET)%
View tableTable 1. Stenosis experimental and contrast results of DSA images (stenosis rate of NASCET)%
Location R NASCETExpert calibration Level set algorithm Steger algorithm Proposed algorithm 1 45.2 39.6 48.2 46.8 2 40.8 36.2 44.6 42.1 3 52.6 45.7 50.0 55.2 4 37.9 33.6 39.9 38.1 5 28.1 22.8 26.2 28.9 6 55.5 50.5 59.6 57.9 7 56.7 49.9 62.5 58.3 8 33.5 29.1 30.8 33.2 9 60.9 49.5 66.6 63.4 10 41.1 37.4 38.9 42.5 11 33.7 30.8 36.1 42.9 12 22.4 20.1 24.2 23.5
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Fan Zhang, Xiangting Chen, Xinhong Zhang. Algorithm of Automatic Detection of Blood Vessel Stenosis with Sub-Pixel Level of Digital Subtraction Angiography[J]. Laser & Optoelectronics Progress, 2018, 55(4): 041101
Paper Information
Category: Imaging Systems
Received: Aug. 30, 2017
Accepted: --
Published Online: Sep. 11, 2018
The Author Email: Xinhong Zhang ( 10120039@vip.henu.edu.cn)
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