The creation and application of brain atlases are of great significance to brain and cognitive science 1 , 2.
The brain atlas is thus considered as the infrastructure of brain science studies and has been widely used in brain mapping studies. Specifically, given the reported morphological differences e. Since the Talairach and Tournoux atlas, many brain templates have been constructed. Additionally, some researchers used multiple MRI scans of one single western subject to make the brain template, such as Colin 7 and a French template 8.
Some attempts have also been made to establish the eastern brain template. Although these efforts made to build the standard brain atlas, there are still insufficiencies in these studies. First, as demonstrated by many previous studies 3 , 10 , 11 , the human brain is highly variable among phenotypically different groups i. Thus, the brain atlas of western population or other races cannot be used in Chinese populations due to the potential bias and error in brain localization. Second, all the previous brain atlases are static, which did not capture the brain atlas as a function of age and gender In , a Chinese brain atlas was also created from high-quality brain MRI scans of 56 Chinese male volunteers aged from 20 years to 30 years , i.
However, this brain atlas was constructed based on a limited sample size, and thus showed inadequate representativeness as no female and elder subjects were included. Recently, we conducted a pilot study to develop a probabilistic MRI brain anatomical atlas based on Chinese healthy subjects ranged from 18 years to 70 years However, these atlases were still not ready for practical applications due to some deficiencies. First, for each atlas, a brain image with intact brain structures and global brain symmetry was chosen to serve as an initial template.
This methodological limitation may drive the standard brain template bias to individual brain. Second, although the same type of scanners 1. Thus, data standardization should be applied in the preprocessing stage to reduce the potential bias effects of multi-center.
Radiology residents and neuroradiology fellows preparing for exams, as well as beginning practitioners will find this book an invaluable tool in learning how to correctly diagnose common and rare pathologies of the brain. Moreover, it was also verified that, in contrast to use the Caucasian template, hippocampus segmentation of Chinese subjects showed significant higher accuracy when using the Chinese template. Open Borders Inc. Lee, J. Whole head. Internationally recognized authors guide the reader through multi-modality imaging approaches for problems, which are grouped according to broad categories, including internal joint derangement, tumors, infection, avascular bone, trauma, arthritis, and prostheses.
The aim of the current study is to develop the Chinese adult brain templates based on a multi-center, large scale dataset over subjects , which is nation-wide study and covers Han Chinese over a variety of regions to reduce the bias to specific region. Particularly, as compared to the previous Chinese brain atlases 3 , 12 , 14 the new atlases based on the larger sample size may represent the brain characteristics of the Chinese population more adequately.
A probabilistic atlas of Chinese brain is shown in Fig. Additionally, as shown in Fig.
We further defined new Chinese standard space, coordinates, and brain area labels. As contrast to the previous template based on Chinese population, i. After comparing the image registration to the Chinese template Chinese and SCBT and to the MNI template, it was found that more deformations were required in brain shape and size to register the ten new Chinese brains to the ICBM template than to the two Chinese templates Table 2. Additionally, we also found that more significant deformations were required to register these new Chinese brains with the mean age of These results reveal that the Chinese templates, especially the age-matched Chinese template SCBT in this validation experiment better represents the shape and size of the Chinese population.
We also manually segmented these Chinese subjects to serve as the ground truth segmentation. The accuracy of atlas-based segmentation was measured in terms of Dice similarity coefficient DSC , which measures the degree of volume overlap of the manual and automatic segmentations.
DSC is defined as:. DSC ranges between 0 and 1, where 1 indicates perfect matching. It was found that the DSC is 0. In this paper, new Chinese brain atlases were constructed and validated using a multi-center MRI dataset of Chinese adults.
In order to make the study more rigorous and effective, we have reduced human intervention during template construction as much as possible. The large and widespread brain MRI database renders the study more representative and unbiased, nevertheless, it also brings some challenges. For instance, some images have quite low image quality. Incorporation of these low quality images would adversely affect the quality of the template.
Thus, we adopted an automatic noise estimation method to first exclude those images with a quite low signal-to-noise ratio SNR. Furthermore, in each iteration of normalization, we did not select any specific subject but use the average brain as the initial reference, so as to reduce the bias during template construction.
Our MRI data come from multiple hospitals in a nationwide scale. Although we have set a consistent standard for image acquisition, these hospitals may use different machines for MRI acquisition. There exists large variance in the intensity profiles of MRIs obtained by different machines.
In order to make consistent analysis of these images, intensity profile was normalized before further processing. To handle the large database, we took an automatic histogram matching method to normalize the histogram of each subject to that of a standard template. After normalization, the histograms of different subjects are, by and large, in the same intensity range. Given the known brain morphometric and volumetric differences between Chinese and Caucasian populations 3 , 15 , the Chinese brain template should be used in the neuroimaging studies of Chinese population due to the potential registration bias and localization deviation when using the Caucasian template as the reference template.
This study has further demonstrated the differences between Chinese and Caucasian observed in the previous studies Fig. Moreover, it was also verified that, in contrast to use the Caucasian template, hippocampus segmentation of Chinese subjects showed significant higher accuracy when using the Chinese template. Additionally, the current Chinese brain atlas, i. Different from the static brain atlas previously reported e. Actually, by using the identical template construction method, we could customize the Chinese brain template for every age between 18 and This kind of customized brain template, but not a common template as implemented in SPM and AFNI now, is preferable for a specific study, as age has a significant effect on brain structure and morphological characteristics This has been further demonstrated in this study, as SCBT better represents the group of young Chinese subjects than Chinese Table 2.
In the future, users could submit their requirement of the Chinese brain template with the specific age and gender i. It was argued that group-specific brain template for a specific study could be built based on structural MRI of all subjects. However, due to the relatively limited sample size, this kind of group-specific template might have lower SNR and statistical power, thus have worse representativeness. In addition, these group-specific templates may induce new bias between different studies. In contrast, our dynamic brain templates for different ages were built based on a large scale multi-center datasets, which better represent the brain characteristics of the Chinese population of different ages than the static brain template e.
The current Chinese brain template Chinese is constructed using 1.
The next updating of the Chinese brain template may use 3. As is known, except age, gender, ethnicity and disease condition e. Thus, new Chinese brain templates especially applicable to the corresponding sub-populations in terms of age, gender, ethnicity, and disease condition should be built in the future. Two thousand nine hundred healthy adults from 24 provinces of China were recruited by 15 hospitals.
Medical examinations were conducted to exclude subjects with a lifetime history of any neurological, psychiatric, or significant medical illnesses as well as patients with a past history of substance abuse. All participants gave their written informed consents before the experiment were performed.
Seven hundred and forty participants were excluded due to missing information or invalid brain imaging data.
The methods were carried out in accordance with the approved guidelines. All 15 hospitals participating in this study followed the same recruitment procedure and the same MR protocols either Siemens system or GE system. Three-dimensional high-resolution T1-weighted anatomical images were acquired by using an 8-channel phased array head coil. Scanning was performed on a 1. Foam padding and headphones were used to limit head motion and reduce scanning noise.
The quality of each brain volume has been ensured to be in good condition and without observable brain abnormality by an experienced radiologist. To preprocess T1 MRIs, apart from traditional schemes, such as bias field correction using N4ITK and brain orientation adjustment, we have also designed an intensity normalization method to address the intensity profile difference due to different acquisition machines used by different hospitals, and an automatic noise estimation method to control the quality of incorporated images.
As brain MRIs in our project were collected from different hospitals and using different scanners either GE or Siemens , there are distinctive intensity range difference between these images. Matching the intensity profiles of different images from different acquisitions can be good for improving image registration accuracy. Therefore, we have adopted a histogram matching scheme to normalize the histogram of each subject to a standard histogram of a template image, where the histogram of Colin27 was used as the standard histogram in our study due to its high resolution and high signal to noise ratio.
Furthermore, although the image acquisition procedure followed strict standard, there are still some images have quite low image quality. The inclusion of these noisy images in template construction may adversely impact the quality of the templates. Therefore, we applied an automatic noise estimation method 18 for image quality assessment. A threshold of noise level is set to screen out those unacceptable noisy images.
We have constructed 12 templates from the age 20 year to the age 75 year at a 5 years interval. To generate a template from the group of images, inter-subject linear registration was performed to bring the images into the common space. During registration, to exclude the effects of background noise in matching efficiency, we employed a mask scheme in registration, where only voxels in brain mask have been accounted for similarity metric calculation.
After registration, a temporary template was built using the normalized images.
A kernel regression scheme was taken to build the template. That is, the subject with a closer age with respect to the template age will contribute more than those subjects away from the template in age. This kernel regression scheme can help solve the problem of missing subject at a certain age or uneven age distribution. After producing the 12 brain templates for age group from 20 to 75 years old, we also created a whole population brain template serving as the Chinese brain standard space.
Therefore, in the template level, we continue to perform non-rigid registration to bring the 12 templates into one common space and create the final brain template. Two experiments were run to validate the use of the new Chinese atlas i. Brain MRI volumes of ten new Chinese subjects 5 male, The brain global features was then statistically compared between the original brain i. Thus, the deformations during the image registering to the two Chinese templates and to the MNI template could be quantitatively evaluated.
Atlas-based segmentation of hippocampus is a widely used method for automatic segmentation of hippocampus 20 , The hippocampus of an MRI template was first manually labeled by an expert rater. The resulting non-rigid transformation was applied to propagate the manual hippocampus labels in the template image to the target subject image space, serving as the automatic segmentation result for this subject. This procedure was called atlas-based segmentation. In current studies, one of the most widely used atlas for hippocampus segmentation is the AAL atlas 22 , which has been embedded in the SPM toolbox.