Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
The directional filter bank: a multirate filter bank for the directional decomposition of images
The directional filter bank: a multirate filter bank for the directional decomposition of images
Scale and the differential structure of images
Image and Vision Computing - Special issue: information processing in medical imaging 1991
Model-based detection of tubular structures in 3D images
Computer Vision and Image Understanding
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Shape Preserving Filament Enhancement Filtering
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Muliscale Vessel Enhancement Filtering
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Directional Anisotropic Diffusion Applied to Segmentation of Vessels in 3D Images
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A review of vessel extraction techniques and algorithms
ACM Computing Surveys (CSUR)
A new directional filter bank for image analysis and classification
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03
A filter bank for the directional decomposition of images: theoryand design
IEEE Transactions on Signal Processing
Rules for multidimensional multirate structures
IEEE Transactions on Signal Processing
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
IEEE Transactions on Image Processing
Improved structures of maximally decimated directional filter Banks for spatial image analysis
IEEE Transactions on Image Processing
Directional filter bank-based fingerprint feature extraction and matching
IEEE Transactions on Circuits and Systems for Video Technology
Pattern Recognition Letters
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Retinal vessel segmentation using a probabilistic tracking method
Pattern Recognition
Finger-vein ROI localization and vein ridge enhancement
Pattern Recognition Letters
Linear feature enhancement based on morphological operation and Gabor function
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Towards finger-vein image restoration and enhancement for finger-vein recognition
Information Sciences: an International Journal
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Vessel enhancement is an important preprocessing step in accurate vessel-tree reconstruction which is necessary in many medical imaging applications. Conventional vessel enhancement approaches used in the literature are Hessian-based filters, which are found to be sensitive to noise and sometimes give discontinued vessels due to junction suppression. In this paper, we propose a novel framework for vessel enhancement for angiography images. The proposed approach incorporates the use of line-like directional features present in an image, extracted by a directional filter bank, to obtain more precise Hessian analysis in noisy environment and thus can correctly reveal small and thin vessels. Also, the directional image decomposition helps to avoid junction suppression, which in turn, yields continuous vessel tree. Qualitative and quantitative evaluations performed on both synthetic and real angiography images show that the proposed filter generates better performance in comparison against two Hessian-based approaches. In average, it is relatively 3.74% and 7.02% less noise-sensitive and performs 5.83% and 6.21% better compared to the two approaches, respectively.