Segmentation of Complex Images Based on Component-Trees: Methodological Tools

Abstract

Abstract. Component-trees can be used for the design of image processing methods, and in particular segmentation ones. However, despite their ability to consider various kinds of knowledge and their tractable computation, methodological deadlocks still forbid to efficiently involve them in real applications. In this article, we explore new solutions to some of these deadlocks, and more especially those related to (i) complexity of the structures of interest and (ii) multiple knowledge handling. The usefulness of the proposed strategies is illustrated by preliminary results related to vessel segmentation from 3-D angiographic data.

3D Angiographic Image Segmentation

“…Several other contributions could actually extend and complete this chapter. The readers who are interested in other works related to mathematical morphologybased segmentation methods of 3D angiographic data can also refer to the following articles [21,2,20,1]. More generally, besides the use of morphological and geometric knowledge [9,13], other solutions dealing with the integration of topological knowledge [6,5,7], relational knowledge [3,8], or even the use of temporal information [4] (see also the previous chapter of this book) for the segmentation of medical images, have been investigated during the last years, and have already led to quite interesting results.…”

3D segmentation of coronary arteries based on advanced mathematical morphology techniques

“…vertebrae labelling in 3D CT data [45], or left ventricular myocardium segmentation from 3D+t MR data [46]). In particular, mathematical morphology operators that have been involved in vessel segmentation methods include: watershed transform [47,48], grey-level hit-or-miss transform [5,49], or connected filtering based on component-trees [50,51]. The usefulness of such operators is justified by their intrinsic capacity to model morphological information, and then to enable anatomical knowledge-guided approaches.…”

Ranking Orientation Responses of Path Operators: Motivations, Choices and Algorithmics

“…Recent effort have been directed towards the development of geodesic attributes [16], particularly designed for thin structures. Vectorial attributes are less frequently used [17], due to a more complex handling, often requiring a learning step.…”

“…Various attempts at minimizing these drawbacks have been proposed, either via tilling approaches [17], or with undirected variants of component-trees [18].…”