A fast algorithm for local minimum and maximum filters on rectangular and octagonal kernels
Pattern Recognition Letters
Fast computation of morphological operations with arbitrary structuring elements
Pattern Recognition Letters
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Vessel Tracking in Peripheral CTA Datasets -- An Overview
SCCG '01 Proceedings of the 17th Spring conference on Computer graphics
A review of vessel extraction techniques and algorithms
ACM Computing Surveys (CSUR)
Cerebral Vascular Atlas Generation for Anatomical Knowledge Modeling and Segmentation Purpose
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Mathematical Morphology: 40 Years On : Proceedings of the 7th International Symposium on Mathematical Morphology, April 18-20, 2005 (Computational Imaging and Vision)
Grey-level hit-or-miss transforms-Part I: Unified theory
Pattern Recognition
A review on MR vascular image processing: skeleton versus nonskeleton approaches: part II
IEEE Transactions on Information Technology in Biomedicine
Grey-level hit-or-miss transforms-Part I: Unified theory
Pattern Recognition
A hit-or-miss transform for multivariate images
Pattern Recognition Letters
Morphological description of color images for content-based image retrieval
IEEE Transactions on Image Processing
Attribute-filtering and knowledge extraction for vessel segmentation
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
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The hit-or-miss transform (HMT) is a fundamental operation on binary images, widely used since 40 years. As it is not increasing, its extension to grey-level images is not straightforward, and very few authors have considered it. Moreover, despite its potential usefulness, very few applications of the grey-level HMT have been proposed until now. Part I of this paper [B. Naegel, N. Passat, C. Ronse, Grey-level hit-or-miss transforms-part I: unified theory. Pattern Recogn., in press doi:10.1016/j.patcog.2006.06.004] was devoted to the description of a theory enabling to unify the main definitions of the grey-level HMT, mainly proposed by Ronse and Soille, respectively. Part II of this paper, developed hereafter, deals with the applicative potential of the grey-level HMT, illustrated by its use for vessel segmentation from 3D angiographic data. Different HMT-based segmentation methods are then described and analysed, leading to concrete analysis techniques for brain and liver vessels, but also providing algorithmic strategies which could further be used for many other kinds of image processing applications.