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Magnetic Resonance Materials in Physics, Biology and Medicine

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11.01.2016 | Review Article

Principles and methods for automatic and semi-automatic tissue segmentation in MRI data

verfasst von: Lei Wang, Teodora Chitiboi, Hans Meine, Matthias Günther, Horst K. Hahn

Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine | Ausgabe 2/2016

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Abstract

The development of magnetic resonance imaging (MRI) revolutionized both the medical and scientific worlds. A large variety of MRI options have generated a huge amount of image data to interpret. The investigation of a specific tissue in 3D or 4D MR images can be facilitated by image processing techniques, such as segmentation and registration. In this work, we provide a brief review of the principles and methods that are commonly applied to achieve superior tissue segmentation results in MRI. The impacts of MR image acquisition on segmentation outcome and the principles of selecting and exploiting segmentation techniques tailored for specific tissue identification tasks are discussed. In the end, two exemplary applications, breast and fibroglandular tissue segmentation in MRI and myocardium segmentation in short-axis cine and real-time MRI, are discussed to explain the typical challenges that can be posed in practical segmentation tasks in MRI data. The corresponding solutions that are adopted to deal with these challenges of the two practical segmentation tasks are thoroughly reviewed.

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Titel: Principles and methods for automatic and semi-automatic tissue segmentation in MRI data
verfasst von: Lei Wang
Teodora Chitiboi
Hans Meine
Matthias Günther
Horst K. Hahn
Publikationsdatum: 11.01.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine / Ausgabe 2/2016
Print ISSN: 0968-5243
Elektronische ISSN: 1352-8661
DOI: https://doi.org/10.1007/s10334-015-0520-5

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Principles and methods for automatic and semi-automatic tissue segmentation in MRI data

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