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Magnetic Resonance Materials in Physics, Biology and Medicine

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01-04-2016 | Editorial

Tissue segmentation: a crucial tool for quantitative MRI and visualization of anatomical structures

Author: Fritz Schick

Published in: Magnetic Resonance Materials in Physics, Biology and Medicine | Issue 2/2016

Abstract

Automatic or semi-automatic segmentation of tissue types or organs is well established for X-ray-based computed tomography, with its fixed grey-scale and tissue classes with well-established ranges of Hounsfield units. MRI is much more powerful with regard to soft tissue contrast and quantitative assessment of tissue properties (e.g., perfusion, diffusion, fat content), but the principle of signal generation and recording in MRI leads to inherent problems if simple threshold based segmentation procedures are applied. In this editorial in the special issue of MAGMA on tissue segmentation, a number of relevant methodical, scientific, and clinical aspects of reliable tissue segmentation using data recording by MRI are reported and discussed.

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Title: Tissue segmentation: a crucial tool for quantitative MRI and visualization of anatomical structures
Author: Fritz Schick
Publication date: 01-04-2016
Publisher: Springer Berlin Heidelberg
Published in: Magnetic Resonance Materials in Physics, Biology and Medicine / Issue 2/2016
Print ISSN: 0968-5243
Electronic ISSN: 1352-8661
DOI: https://doi.org/10.1007/s10334-016-0549-0

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Tissue segmentation: a crucial tool for quantitative MRI and visualization of anatomical structures

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Other articles of this Issue 2/2016

Segmentation of human brain using structural MRI

A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging

Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches

A method for the automatic segmentation of brown adipose tissue

Segmentation of joint and musculoskeletal tissue in the study of arthritis

Segmentation and characterization of interscapular brown adipose tissue in rats by multi-parametric magnetic resonance imaging