1 - 6 of 6 Chapters
[Since the discovery of X-rays in 1895, many different imaging techniques have been developed which gain visual access to the interior of a closed body without opening it. Nowadays, these techniques are widely used in health-care and biomedical research and constitute a substantial part of the...
[The extraction of information out of 2D or 3D images often relies on the detection, recognition and interpretation of shapes and shape variabilities. This directly involves the (mathematical) representation of shapes as well as methods to account for and measure the morphological differences....
[Statistical shape models are a valuable tool in medical image analysis and are efficiently used in classification, recognition, reconstruction and segmentation methods. The models incorporate statistical knowledge mainly about the expected shape and shape variability. The collection of that...
[In this chapter, the GGM-SSM method is submitted to an extensive evaluation. The aim is to quantitatively compare its performance to other SSM methods in the literature and to gather knowledge about its behaviour and characteristics for different types of shapes. In section 4.1, the performance...
[Segmentation algorithms play a major role in medical image analysis. However, due to typical medical image characteristics as poor contrasts, grey value inhomogeneities, contour gaps, and noise the automatic segmentation of many anatomical structures remains a challenge. Low-level algorithms as...
[Statistical shape models play an important role in medical image analysis, and a wide range of methods well adapted to various applications exists in the literature. The emphasis of this thesis however was not so much to propose a convenient SSM to solve a specific practical problem but to...
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