DocumentCode
1432534
Title
Contrast-Independent Curvilinear Structure Detection in Biomedical Images
Author
Obara, Boguslaw ; Fricker, Mark ; Gavaghan, David ; Grau, Vicente
Author_Institution
Oxford e-Res. Centre, Oxford Centre for Integrative Syst. Biol., Oxford, UK
Volume
21
Issue
5
fYear
2012
fDate
5/1/2012 12:00:00 AM
Firstpage
2572
Lastpage
2581
Abstract
Many biomedical applications require detection of curvilinear structures in images and would benefit from automatic or semiautomatic segmentation to allow high-throughput measurements. Here, we propose a contrast-independent approach to identify curvilinear structures based on oriented phase congruency, i.e., the phase congruency tensor (PCT). We show that the proposed method is largely insensitive to intensity variations along the curve and provides successful detection within noisy regions. The performance of the PCT is evaluated by comparing it with state-of-the-art intensity-based approaches on both synthetic and real biological images.
Keywords
image segmentation; medical image processing; object detection; PCT; biomedical applications; biomedical image detection; contrast-independent curvilinear structure detection; phase congruency tensor; semiautomatic segmentation; Eigenvalues and eigenfunctions; Equations; Feature extraction; Mathematical model; Noise; Tensile stress; Vectors; Bioimage informatics; curvilinear structure; live-wire tracing; phase congruency tensor (PCT); Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2012.2185938
Filename
6140570
Link To Document