Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method.
10.3348/kjr.2012.13.4.391
- Author:
Masami GOTO
1
;
Osamu ABE
;
Tosiaki MIYATI
;
Hiroyuki KABASAWA
;
Hidemasa TAKAO
;
Naoto HAYASHI
;
Tomomi KUROSU
;
Takeshi IWATSUBO
;
Fumio YAMASHITA
;
Hiroshi MATSUDA
;
Harushi MORI
;
Akira KUNIMATSU
;
Shigeki AOKI
;
Kenji INO
;
Keiichi YANO
;
Kuni OHTOMO
Author Information
1. Department of Radiological Technology, University of Tokyo Hospital, Tokyo 113-8655, Japan. car6_pa2_rw@yahoo.co.jp
- Publication Type:Original Article
- Keywords:
Atlas-based;
Bias correction;
Brain volumetry;
Intensity non-uniformity;
Non-parametric non-uniform intensity normalization
- MeSH:
Adult;
Atlases as Topic;
Brain Mapping/*methods;
Female;
Humans;
Image Enhancement/methods;
Image Processing, Computer-Assisted/*methods;
Magnetic Resonance Imaging/*methods;
Male;
Middle Aged;
Software;
Statistics, Nonparametric
- From:Korean Journal of Radiology
2012;13(4):391-402
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVE: Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. MATERIALS AND METHODS: Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 x [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. RESULTS: A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. CONCLUSION: The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.
