Grey-level hit-or-miss transforms - part II: Application to angiographic image processing

被引:23
作者
Naegel, Benoit
Passat, Nicolas
Ronse, Christian
机构
[1] ULP, CNRS, LSIIT, UMR 7005, F-67412 Illkirch Graffenstaden, France
[2] Ecole Ingn Geneva, EIG HES, CH-1202 Geneva, Switzerland
[3] Inst Gaspard Monge, Lab A2SI, Grp ESIEE, F-93162 Noisy Le Grand, France
关键词
mathematical morphology; hit-or-miss transform; grey-level interval operator; angiographic image processing;
D O I
10.1016/j.patcog.2006.06.011
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 1: unified theory. Pattem 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. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:648 / 658
页数:11
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