DocumentCode :
837866
Title :
Nonrigid Registration of Joint Histograms for Intensity Standardization in Magnetic Resonance Imaging
Author :
Jäger, Florian ; Hornegger, Joachim
Author_Institution :
Dept. of Pattern Recognition, Friedrich-Alexander-Univ. Erlangen-Nuremberg, Erlangen
Volume :
28
Issue :
1
fYear :
2009
Firstpage :
137
Lastpage :
150
Abstract :
A major disadvantage of magnetic resonance imaging (MRI) compared to other imaging modalities like computed tomography is the fact that its intensities are not standardized. Our contribution is a novel method for MRI signal intensity standardization of arbitrary MRI scans, so as to create a pulse sequence dependent standard intensity scale. The proposed method is the first approach that uses the properties of all acquired images jointly (e.g., T1- and T2-weighted images). The image properties are stored in multidimensional joint histograms. In order to normalize the probability density function (pdf) of a newly acquired data set, a nonrigid image registration is performed between a reference and the joint histogram of the acquired images. From this matching a nonparametric transformation is obtained, which describes a mapping between the corresponding intensity spaces and subsequently adapts the image properties of the newly acquired series to a given standard. As the proposed intensity standardization is based on the probability density functions of the data sets only, it is independent of spatial coherence or prior segmentations of the reference and current images. Furthermore, it is not designed for a particular application, body region or acquisition protocol. The evaluation was done using two different settings. First, MRI head images were used, hence the approach can be compared to state-of-the-art methods. Second, whole body MRI scans were used. For this modality no other normalization algorithm is known in literature. The Jeffrey divergence of the pdfs of the whole body scans was reduced by 45%. All used data sets were acquired during clinical routine and thus included pathologies.
Keywords :
biomedical MRI; image registration; medical image processing; intensity standardization; joint histograms; magnetic resonance imaging; nonparametric transformation; nonrigid registration; normalization algorithm; probability density function; pulse sequence-dependent standard intensity scale; Body regions; Computed tomography; Histograms; Image registration; Image segmentation; Magnetic resonance imaging; Multidimensional systems; Probability density function; Spatial coherence; Standardization; General intensity scale; intensity normalization; magnetic resonance imaging (MRI); nonrigid registration; signal intensity standardization; whole body MRI; Brain; Humans; Image Processing, Computer-Assisted; Information Storage and Retrieval; Magnetic Resonance Imaging; Multiple Sclerosis; Pattern Recognition, Automated; Reference Standards; Signal Processing, Computer-Assisted; Subtraction Technique; Whole Body Imaging;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2008.2004429
Filename :
4601458
Link To Document :
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