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Fuzzy Digital Topology and Geometry and Their Applications to Medical Imaging
Book chapter   Open access   Peer reviewed

Fuzzy Digital Topology and Geometry and Their Applications to Medical Imaging

Punam K Saha
Pattern Recognition and Machine Intelligence, pp.13-29
Lecture Notes in Computer Science, Springer Berlin Heidelberg
2013
DOI: 10.1007/978-3-642-45062-4_2
url
https://doi.org/10.1007/978-3-642-45062-4_2View
Published (Version of record) Open Access

Abstract

The primary end-goal of most medical imaging research program is to collect information about function and physiology of internal human organs or tissues through a variety of in vivo or ex vivo imaging techniques. Often, medical imaging techniques suffer from limited spatial and temporal resolution, noise, background-inhomogeneity, and other artifacts leading to fuzzy representations of target objects in acquired images. Digital topology and geometry play important roles in medical image processing either by expanding the scope of target information or by providing a strong theoretical foundation to a process enhancing its stability, fidelity, and efficiency. The notions of digital topology and geometry are often intertwined in medical imaging applications and sometime it is difficult to draw a dividing line between them. This paper presents recent advancements and overviews of theory and computation of several fuzzy digital topologic and geometric approaches and describe their applications to medical imaging. More specifically, this paper discusses topics related to three-dimensional simple points, local topological parameters, fuzzy skeletonization, characterization of local structures, and their applications to research and clinical studies.
 digital imaging distance transform Fuzzy subset geometry medical imaging simple point skeletonization topological classification topology

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