Initial commit.

.project

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+<?xml version="1.0" encoding="UTF-8"?>
+<projectDescription>
+	<name>easyFMRI</name>
+	<comment></comment>
+	<projects>
+	</projects>
+	<buildSpec>
+		<buildCommand>
+			<name>de.walware.statet.r.builders.RSupport</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+	</buildSpec>
+	<natures>
+		<nature>de.walware.statet.base.StatetNature</nature>
+		<nature>de.walware.statet.r.RNature</nature>
+	</natures>
+</projectDescription>

DESCRIPTION

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+Package: easyFMRI
+Type: Package
+Title: Functions of fMRI analysis
+Version: 1.0
+Date: 2010-09-17
+Author: Wonsang You
+Maintainer: Wonsang You <you@ifn-magdeburg.de>
+Description: Functions for ROI segmentation in EPI sequence.
+License: GPL (>=2)
+LazyLoad: yes
+Depends: oro.nifti, AnalyzeFMRI
+Packaged: 2010-09-17 12:12:06 UTC; wyou

R/meanROIs.R

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+meanROIs <-
+function(EPIfname, nROIs=31, ROIdir="", prefix="roi_", outfname="meanROIs", writefile=TRUE) {
+
+	require(oro.nifti)
+	require(AnalyzeFMRI)
+
+	# Extract ROI data
+	if(length(ROIdir)>1)
+		ROIdir<-paste(c(ROIdir,"/"), collapse="")
+
+	# Read the EPI sequence
+	#dimEPI<-dim(EPIdata)
+	#nTPs<-dimEPI[4]
+	EPIimg<-paste(c(EPIfname,".img"),sep="",collapse="")
+	EPIhdr<-paste(c(EPIfname,".hdr"),sep="",collapse="")
+	nTPs<-f.read.nifti.header(EPIhdr)$dim[5]
+
+	# Compute mean time series of each ROI
+	mtsROIs<-mat.or.vec(nROIs, nTPs)
+	for(i in seq(1,nROIs)) {
+		ROIfname<-paste(c(ROIdir,prefix,i,".nii.gz"),sep="",collapse="")
+		roi<-readNIfTI(ROIfname)@.Data
+		roipos<-roi>0
+		for(t in seq(1,nTPs)){
+			#epiTP<-epi[,,,t]
+			epiTP<-f.read.nifti.tpt(EPIimg,t)
+			epiTPROI<-epiTP[roipos]
+			mtsROIs[i,t]<-mean(epiTPROI)
+		}
+	}
+
+	mtsROIs
+
+	# Write a text file
+	if(writefile)
+		write.table(mtsROIs, file = paste(c(outfname,".txt"),sep="",collapse=""), 
+				sep = ";", col.names = NA)
+}
+

R/orthoROIs.R

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+orthoROIs <-
+function(nROIs=31, ThRes=5, ROIdir="", targetdir="newROIs", mode="minimal", prefix="roi_", newprefix="roi_", writefile=TRUE, gzipped=TRUE, verbose=TRUE) {
+
+	require(oro.nifti)
+
+	# Extract ROI data
+	if(length(ROIdir)>1)
+		ROIdir<-paste(c(ROIdir,"/"), collapse="")
+
+	ROIdata<-c()
+	for(i in seq(1,nROIs)) {
+		roi<-readNIfTI(paste(c(ROIdir,prefix,i,".nii.gz"),sep="",collapse=""))@.Data
+		ROIdata<-c(ROIdata,list(roi))
+	}
+
+	# Evaluate overlaps
+	olMat<-mat.or.vec(nROIs, nROIs)
+	thr<-mat.or.vec(nROIs,1)
+	for(i in seq(1,nROIs-1)) {
+		x1<-ROIdata[[i]]
+		olMat[i,i]<-0
+		for(j in seq(i+1,nROIs)) {			
+			x2<-ROIdata[[j]]
+			olMat[i,j]<-length(x1[x1&x2])
+		}
+	}
+
+	# The number of overlapped ROIs
+	nOverlapROIpairs<-length(olMat[olMat>0])
+	nTotalROIpairs<-nROIs*(nROIs-1)/2
+
+	# The number of overlapped Voxels
+	nOverlapVoxels<-sum(olMat[olMat>0])
+
+	if(verbose){
+		msg <- paste(c("The number of overlapped ROI pairs", nOverlapROIpairs,"/",nTotalROIpairs),collapse = " ")
+		print(msg)
+		msg <- paste(c(" The number of overlapped Voxels= ", nOverlapVoxels),collapse = " ")
+		print(msg)
+	}
+
+	# Resize ROIs to eliminate overlaps
+	olMat<-mat.or.vec(nROIs, nROIs)
+	thr<-mat.or.vec(nROIs,1)
+	for(i in seq(1,nROIs-1)) {
+		x1<-ROIdata[[i]]
+		olMat[i,i]<-0
+		for(j in seq(i+1,nROIs)) {			
+			x2<-ROIdata[[j]]
+			olMat[i,j]<-length(x1[x1&x2])
+
+			if(olMat[i,j]>0){
+				if(mode=="minimal"){
+					x1<-replace(x1,(x1>0)&(x2>0),0)
+					ROIdata[[j]]<-replace(x2,(x1>0)&(x2>0),0)
+				}else{
+					nOverlapVoxelsInROI<-olMat[i,j]
+
+					ux1<-x1
+					ux2<-x2
+					thr1<-thr[i]
+					thr2<-thr[j]
+					for(r in seq(1,trunc(ThRes))){
+						ThrRes<-1/10^r
+						while(nOverlapVoxelsInROI>0){
+							tmp_thr1<-thr1+ThrRes
+							tmp_thr2<-thr2+ThrRes
+							tmp_ux1<-replace(ux1,ux1<thr1,0)
+							tmp_ux2<-replace(ux2,ux2<thr2,0)
+							nOverlapVoxelsInROI<-length(tmp_ux1[tmp_ux1&tmp_ux2])
+
+							if(nOverlapVoxelsInROI>=0){
+								thr1<-tmp_thr1
+								thr2<-tmp_thr2
+								ux1<-tmp_ux1
+								ux2<-tmp_ux2
+							}
+						}
+					}
+					x1<-ux1
+					ROIdata[[j]]<-ux2
+					thr[i]<-thr1
+					thr[j]<-thr2	
+				}			
+			}
+		}
+		ROIdata[[i]]<-x1
+	}
+
+	# Verify overlaps
+	olMat<-mat.or.vec(nROIs, nROIs)
+	for(i in seq(1,nROIs-1)) {
+		x1<-ROIdata[[i]]
+		olMat[i,i]<-0
+		for(j in seq(i+1,nROIs)) {			
+			x2<-ROIdata[[j]]
+			olMat[i,j]<-length(x1[x1&x2])
+		}
+	}
+
+	nNewOverlapROIpairs<-length(olMat[olMat>0]) # The number of overlapped ROIs
+	nNewOverlapVoxels<-sum(olMat[olMat>0]) # The number of overlapped Voxels
+
+	if(verbose){
+		msg <- paste(c("The number of new overlapped ROI pairs", nNewOverlapROIpairs,"/",nTotalROIpairs),collapse = " ")
+		print(msg)
+		msg <- paste(c(" The number of new overlapped Voxels= ", nNewOverlapVoxels),collapse = " ")
+		print(msg)		
+	}
+
+	# Write NIFTI files
+	if(writefile){
+		dir.create(paste(c(ROIdir,targetdir),sep="",collapse=""))
+		for(i in seq(1,nROIs)){
+			roi.fname<-paste(c(ROIdir,targetdir,"/",newprefix,i),sep="",collapse="")
+			roi.nifti<-nifti(ROIdata[[i]],datatype=64) # double type
+			writeNIfTI(roi.nifti, roi.fname, gzipped=gzipped, verbose=FALSE)
+		}
+	}
+
+	if(mode=="minimal"){
+		dat<-drop(list(ROIData=ROIdata,nOverlapROIpairs,nOverlapVoxels,
+						nNewOverlapROIpairs,nNewOverlapVoxels))
+	}else{
+		dat<-drop(list(ROIData=ROIdata,thr=thr,nOverlapROIpairs,nOverlapVoxels,
+						nNewOverlapROIpairs,nNewOverlapVoxels))
+	}
+	invisible(dat)
+}
+

R/tsROI.R

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+tsROI <-
+function(ROIidx, EPIfname, ROIdir="", prefix="roi_", outfname="tsROI", writefile=TRUE) {
+
+	require(oro.nifti)
+	require(AnalyzeFMRI)
+
+	# Extract ROI data
+	if(length(ROIdir)>1)
+		ROIdir<-paste(c(ROIdir,"/"), collapse="")
+
+	# Read the EPI sequence
+	#dimEPI<-dim(EPIdata)
+	#nTPs<-dimEPI[4]
+	EPIimg<-paste(c(EPIfname,".img"),sep="",collapse="")
+	EPIhdr<-paste(c(EPIfname,".hdr"),sep="",collapse="")
+	nTPs<-f.read.nifti.header(EPIhdr)$dim[5]
+
+	# Compute mean time series of each ROI
+	ROIfname<-paste(c(ROIdir,prefix,ROIidx,".nii.gz"),sep="",collapse="")
+	roi<-readNIfTI(ROIfname)@.Data
+	roipos<-roi>0
+	ts<-c()
+	for(t in seq(1,nTPs)){		
+		epiTP<-f.read.nifti.tpt(EPIimg,t)
+		#epiTP<-EPIdata[,,,t]
+		epiTPROI<-epiTP[roipos]
+		ts<-rbind(ts,epiTPROI)
+	}
+
+	ts
+
+	# Write a text file
+	if(writefile)
+		write.table(ts, file = paste(c(outfname,".txt"),sep="",collapse=""), 
+				sep = ";", col.names = NA)
+}
+

man/easyFMRI-package.Rd

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+\name{easyFMRI-package}
+\alias{easyFMRI-package}
+\alias{easyFMRI}
+\docType{package}
+\title{
+Functions for FMRI Analysis
+}
+\description{
+Functions for ROI segmentation in EPI sequences
+}
+\details{
+\tabular{ll}{
+Package: \tab easyFMRI\cr
+Type: \tab Package\cr
+Version: \tab 1.0\cr
+Date: \tab 2010-09-17\cr
+License: \tab GPL (>=2)\cr
+LazyLoad: \tab yes\cr
+}
+}
+\author{
+Wonsang You
+
+Maintainer: Wonsang You <you@ifn-magdeburg.de>
+}
+\references{
+Wonsang You (2010) ROI Data Extraction from FMRI BOLD Signals of the Human Brain, Technical Reports of the Leibniz Institute for Neurobiology, TR 10016.
+}
+\keyword{ package }
+\seealso{
+
+}
+\examples{
+ROIdata<-orthoROIs()
+}

man/meanROIs.Rd

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+\name{meanROIs}
+\alias{meanROIs}
+%- Also NEED an '\alias' for EACH other topic documented here.
+\title{
+The average time series of each ROI
+}
+\description{
+Computing the average time series of each ROI in the given EPI sequence
+}
+\usage{
+meanROIs(EPIfname, nROIs = 31, ROIdir = "", prefix = "roi_", 
+     outfname = "meanROIs", writefile = TRUE)
+}
+%- maybe also 'usage' for other objects documented here.
+\arguments{
+  \item{EPIfname}{
+the file name of a EPI sequence (The file format should be ANALYZE such as \code{hdr} and \code{img}. For example, if the original file is "\code{foo.img}", the input value should be "\code{foo}".)
+}
+  \item{nROIs}{
+the number of ROIs. Default is \code{31}.
+}
+  \item{ROIdir}{
+the directory of ROI definition files. These files should contain the individual zipped NIFTI files (nii.gz) corresponding to ROIs. Default is current working directory.
+}
+  \item{prefix}{
+the common prefix of ROI definition files. Default is \code{roi_}. Then, the files should be titled as \code{roi_1.nii.gz}, \code{roi_2.nii.gz}, and so forth.
+}
+  \item{outfname}{
+the outout text file name. Default is \code{meanROIs}.
+}
+  \item{writefile}{
+Enable to write the output text file. Default is \code{TRUE}.
+}
+}
+\details{
+This function computes the average time series of each ROI in the given EPI sequence. The ROI definition files should be given a priori.
+}
+\value{
+A matrix of averaged time series for ROIs. Row indicates a time point, and column does an ROI.
+}
+\references{
+Wonsang You (2010) ROI Data Extraction from FMRI BOLD Signals of the Human Brain, Technical Reports of the Leibniz Institute for Neurobiology, TR 10016.
+}
+\author{
+Wonsang You
+}
+\note{
+%%  ~~further notes~~
+}
+
+%% ~Make other sections like Warning with \section{Warning }{....} ~
+
+\seealso{
+\code{\link{tsROI}}
+}
+\examples{
+mts<-meanROIs("foo")
+}
+% Add one or more standard keywords, see file 'KEYWORDS' in the
+% R documentation directory.
+\keyword{ averaged ROI }
+\keyword{ FMRI }% __ONLY ONE__ keyword per line