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Perfusion Mismatch Analyzer (PMA)
Perfusion Mismatch Analyzer (PMA), developed by Kohsuke Kudo (Advanced Medical Research Center, Section for Ultrahigh-Field MRI, Assistant Professor), is a versatile free software for quantitative analysis of perfusion and diffusion imaging of cerebrovascular disorders. ASIST-Japan releases PMA on condition that it is used exclusively for researh purposes.
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About ASIST-Japan: Acute Stroke Imaging Standardization Group – Japan (ASIST-Japan) is a group that conducts medical research projects dedicated to the standardization of brain computed tomography (CT) and magnetic resonance imaging (MRI) in the clinical setting of acute cerebral stroke. It is supported by a cardiovascular research grant from the Ministry of Health, Labour and Welfare.[Offical Site]
Copyright (C) 2006 Kohsuke Kudo
individual Voxel-based morphometry Adjusting Covariates (iVAC) toolbox
Individual Voxel-based morphometry Adjusting Covariates (iVAC) is a toolbox for SPM8 and SPM12, in which single-subject VBM analysis can be performed with arbitrary covariate adjustment in addition to age and sex.
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2024/4/19 update
Copyright(C) 2011 Fumio Yamashita
Ventricular/sylvian fissure (VS) and high convexity/midline (HCM) ROIs for idiopathic normal pressure hydrocephalus (iNPH) studies
Two regions of interest (ROIs) for the discrimination of idiopathic normal pressure hydrocephalus from normal eldelies and Alzheimer’s disease patients, namely ventriculer and sylvian fissure (VS) ROI, and high convexity/midline (HCM) ROI are available. The ROIs were created from group comparisons among patients with iNPH, patients with AD and healthy elderlies using VBM5 toolbox. See the Neuroradiology 2010 paper* for more detail.
* Yamashita, F., et al., Detection of changes in cerebrospinal fluid space in idiopathic normal pressure hydrocephalus using voxel-based morphometry. Neuroradiology, 2010. 52(5): p. 381-386.
Copyright(C) 2011 Fumio Yamashita
Substantia nigra pars compacta atlas
A substantia nigra pars compacta (SNc) region of interest (ROI) is available. The ROI of the SNc was created by manually drawn around the neuromelanin-related hyperintensity areas on the averaged images calculated from the neuromelanin-sensitive T1-weighted 3D spoiled gradient echo images of 22 healthy controls using advanced normalization tools (ANTs). See the Neuroreport 2016 paper* for more detail. Finally, the ROI was warped to the JHU-Eve atlas space (MRI Studio, https://www.mristudio.org).
* Yamashita, F., et al., Detection of changes in the ventral tegmental area of patients with schizophrenia using neuromelanin-sensitive MRI. Neuorreport, 2016;27(5):289–94.
Copyright(C) 2016 Kenji Ito
Digital phantom data for evaluating the tracer delay-induced effect
The tracer delay in perfusion analysis has been reported to affect perfusion parameters such as CBF, CBV and MTT. To evaluate the differences in tracer delay-induced effects of various algorithms for CT perfusion analysis, we designed a digital phantom data set (DICOM files) that simulates delays in the arrival of the contrast agent. The digital phantom data was created from actual source images of dynamic CT perfusion scans. These images were divided in half at the midline of the brain, and frames the left half of the images was shifted from 1 to 5 frames forward or backward to simulate positive and negative delays (For more details please see delow).
Copyright(C) 2009 Kohsuke Kudo
Digital phantom data for evaluating the accuracy and reliability of CT and MR perfusion analysis software
CT and MR perfusion are widely used for acute ischemic stroke, hemodynamic ischemia, subarachnoid hemorrhage and brain tumors. A variety of CT and MR perfusion analysis software have been made available, however, there are substantial differences between these programs and algorithms in terms of their maps and quantitative values. To evaluate the accuracy and reliability of perfusion analysis software, we designed a digital phantom data set (DICOM files) for CT and MR perfusion on the basis of the widely accepted tracer kinetic theory in which the true values of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and tracer arrival delay (For more details please see delow).
Copyright(C) 2012 Kohsuke Kudo
NIfTI to DICOM converter software (NifTI_DICOM_Converter)
When DICOM image is converted into NIfTI format, most of image information stored in DICOM header is lost. This software (written by Kohsuke KUDO) can convert image format from NIfTI to DICOM, by adding original DICOM header to image data in NIfTI.
1. Click the [Open NifTI] button and select NifTI file.
2. Click the [Open DICOM] button and select DICOM files. Note that you should select original DICOM files used to convert into NIfTI.
3. Click the [Save DICOM] button and save new DICOM files to your favorite location. When the number of DICOM files in Step 2 differs from the slice number of NifTi file in Step 1, [Save DICOM] button will be disabled. If you want to change the series number in new DOCOM files, you can set a new number to [New Series No.].
Copyright(C) 2011 Kohsuke Kudo