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Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis.

Nemoto K, Dan I, Rorden C, Ohnishi T, Tsuzuki D, Okamoto M, Yamashita F, Asada T - BMC Med Imaging (2011)

Bottom Line: The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive.Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis.It also provides a practical means of sharing analysis environments across sites.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Psychiatry, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan. kiyotaka@nemotos.net

ABSTRACT

Background: A variety of neuroimaging software packages have been released from various laboratories worldwide, and many researchers use these packages in combination. Though most of these software packages are freely available, some people find them difficult to install and configure because they are mostly based on UNIX-like operating systems. We developed a live USB-bootable Linux package named "Lin4Neuro." This system includes popular neuroimaging analysis tools. The user interface is customized so that even Windows users can use it intuitively.

Results: The boot time of this system was only around 40 seconds. We performed a benchmark test of inhomogeneity correction on 10 subjects of three-dimensional T1-weighted MRI scans. The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive. We also installed Lin4Neuro on a virtualization software package that emulates the Linux environment on a Windows-based operation system. Although the processing speed was slower than that under other conditions, it remained comparable.

Conclusions: With Lin4Neuro in one's hand, one can access neuroimaging software packages easily, and immediately focus on analyzing data. Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis. It also provides a practical means of sharing analysis environments across sites.

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Related in: MedlinePlus

Schematic of inhomogeneity correction procedure performed on Lin4Neuro. Input images in the DICOM format were sequentially processed by MRIConvert, BET2, MINC-Tool, N3, and MINC-Tool to generate inhomogeneity-corrected images in NIFTI-1 format. Procedures within the dashed box were automated with a short shell script in Lin4Neuro. Open circles indicate formats. Open squares indicate software used for the procedures.
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Figure 2: Schematic of inhomogeneity correction procedure performed on Lin4Neuro. Input images in the DICOM format were sequentially processed by MRIConvert, BET2, MINC-Tool, N3, and MINC-Tool to generate inhomogeneity-corrected images in NIFTI-1 format. Procedures within the dashed box were automated with a short shell script in Lin4Neuro. Open circles indicate formats. Open squares indicate software used for the procedures.

Mentions: According to the method by Acosta-Cabronero et al., [1] we prepared a batch script, which processes the following in series: First, we stripped the skull and made a mask of the brain using BET2, included in FSL. Second, the processed images were converted to MINC format with the MINC-Tool included in the MINC software package. Third, we performed inhomogeneity correction using N3, included in the MINC software packages. The brain mask generated by BET2 was used to identify the region to which N3 was applied. Finally, the inhomogeneity-corrected images were converted back to NIFTI-1 format with the MINC-Tool, and made ready for segmentation with software packages such as SPM or FSL. A schematic of the processing is shown in Figure 2.


Lin4Neuro: a customized Linux distribution ready for neuroimaging analysis.

Nemoto K, Dan I, Rorden C, Ohnishi T, Tsuzuki D, Okamoto M, Yamashita F, Asada T - BMC Med Imaging (2011)

Schematic of inhomogeneity correction procedure performed on Lin4Neuro. Input images in the DICOM format were sequentially processed by MRIConvert, BET2, MINC-Tool, N3, and MINC-Tool to generate inhomogeneity-corrected images in NIFTI-1 format. Procedures within the dashed box were automated with a short shell script in Lin4Neuro. Open circles indicate formats. Open squares indicate software used for the procedures.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3040700&req=5

Figure 2: Schematic of inhomogeneity correction procedure performed on Lin4Neuro. Input images in the DICOM format were sequentially processed by MRIConvert, BET2, MINC-Tool, N3, and MINC-Tool to generate inhomogeneity-corrected images in NIFTI-1 format. Procedures within the dashed box were automated with a short shell script in Lin4Neuro. Open circles indicate formats. Open squares indicate software used for the procedures.
Mentions: According to the method by Acosta-Cabronero et al., [1] we prepared a batch script, which processes the following in series: First, we stripped the skull and made a mask of the brain using BET2, included in FSL. Second, the processed images were converted to MINC format with the MINC-Tool included in the MINC software package. Third, we performed inhomogeneity correction using N3, included in the MINC software packages. The brain mask generated by BET2 was used to identify the region to which N3 was applied. Finally, the inhomogeneity-corrected images were converted back to NIFTI-1 format with the MINC-Tool, and made ready for segmentation with software packages such as SPM or FSL. A schematic of the processing is shown in Figure 2.

Bottom Line: The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive.Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis.It also provides a practical means of sharing analysis environments across sites.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Psychiatry, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan. kiyotaka@nemotos.net

ABSTRACT

Background: A variety of neuroimaging software packages have been released from various laboratories worldwide, and many researchers use these packages in combination. Though most of these software packages are freely available, some people find them difficult to install and configure because they are mostly based on UNIX-like operating systems. We developed a live USB-bootable Linux package named "Lin4Neuro." This system includes popular neuroimaging analysis tools. The user interface is customized so that even Windows users can use it intuitively.

Results: The boot time of this system was only around 40 seconds. We performed a benchmark test of inhomogeneity correction on 10 subjects of three-dimensional T1-weighted MRI scans. The processing speed of USB-booted Lin4Neuro was as fast as that of the package installed on the hard disk drive. We also installed Lin4Neuro on a virtualization software package that emulates the Linux environment on a Windows-based operation system. Although the processing speed was slower than that under other conditions, it remained comparable.

Conclusions: With Lin4Neuro in one's hand, one can access neuroimaging software packages easily, and immediately focus on analyzing data. Lin4Neuro can be a good primer for beginners of neuroimaging analysis or students who are interested in neuroimaging analysis. It also provides a practical means of sharing analysis environments across sites.

Show MeSH
Related in: MedlinePlus