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Fast WM/GM Boundary Segmentation From MR Images Using The Relationship Between Parametric and Geometric Deformable Models

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Advanced Algorithmic Approaches to Medical Image Segmentation

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

The role of fast shape recovery has always been a critical component in 2-D and 3-D medical imagery since it assists largely in medical therapy such as image guided surgery applications. The applications of shape recovery have been increasing since scanning methods became faster, more accurate and less artifacted (see Chapter 4). Shape recovery of medical organs is more difficult compared to other computer vision and imaging fields. This is primarily due to the large shape variability, structure complexity, several kinds of artifacts and restrictive body scanning methods (the scanning ability is limited to acquiring images in three orthogonal and oblique directions only). The recovery of the White Matter (WM) and Gray Matter (GM) boundaries in the human brain slices is a challenge due to its highly convoluted structure (see Plate 3). In spite of the above complications, we have started to explore faster and more accurate software tools for shape recovery in 2-D and 3-D applications.

© 2001 IEEE. Reprinted with permission from [332]

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© 2002 Springer-Verlag London

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Suri, J.S. (2002). Fast WM/GM Boundary Segmentation From MR Images Using The Relationship Between Parametric and Geometric Deformable Models. In: Suri, J.S., Setarehdan, S.K., Singh, S. (eds) Advanced Algorithmic Approaches to Medical Image Segmentation. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-333-6_8

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  • DOI: https://doi.org/10.1007/978-0-85729-333-6_8

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1043-9

  • Online ISBN: 978-0-85729-333-6

  • eBook Packages: Springer Book Archive

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