In bbuchsbaum/neuroim2: Data Structures and IO for Neuroimaging Data with an Emphasis on Functional Magnetic Resonance Imaging (FMRI)

knitr::opts_chunk$set(collapse = T, comment = "#>")

Reading a NIFTI formatted image volume

The way to read an volumetric image file is to use read_vol:

    library(neuroim2)
    file_name <- system.file("extdata", "global_mask.nii", package="neuroim2")
    vol <- read_vol(file_name)

Working with image volumes

Information about the geometry of the image volume is shown here:

    print(vol)

read_vol returns an object of class NeuroVol object which extends an R array and has 3 dimensions (x,y,z).

    class(vol)

    is.array(vol)

    dim(vol)

    vol[1,1,1]

    vol[64,64,24]

Arithmetic can be performed on images as if they were ordinary arrays:

    vol2 <- vol + vol
    sum(vol2) == 2 * sum(vol)

    vol3 <- vol2 - 2*vol
    all(vol3 == 0)

A numeric image volume can be converted to a binary image as follows:

    vol2 <- as.logical(vol)
    class(vol2)
    print(vol2[1,1,1])

We can also create a NeuroVol instance from an array or numeric vector. First we consruct a standard R array:

    x <- array(0, c(64,64,64))

Now we reate a NeuroSpace instance that describes the geometry of the image including, at minimum, its dimensions and voxel spacing.

    bspace <- NeuroSpace(dim=c(64,64,64), spacing=c(1,1,1))
    vol <- NeuroVol(x, bspace)
    vol

We do not usually have to create NeuroSpace objects, because geometric information about an image is automatically determined from information stored in the image file header. Thus, NeuroSpace objects are usually copied from existing images using the space extractor function when needed:

    vol2 <- NeuroVol((vol+1)*25, space(vol))
    max(vol2)
    space(vol2)

Writing a NIFTI formatted image volume

When we're ready to write an image volume to disk, we use write_vol

    write_vol(vol2, "output.nii")

    ## adding a '.gz' extension results ina gzipped file.
    write_vol(vol2, "output.nii.gz")

We can also display a NeuroVol instance. Lets download an MNI image from the web and plot it.

    temp <- tempfile()
    uri = "http://www.bic.mni.mcgill.ca/~vfonov/nihpd/obj1/nihpd_asym_07.5-13.5_nifti.zip"
    download.file(uri,temp)
    cmd <- paste("unzip ", "-d", dirname(temp), temp)
    system(cmd)
    vol <- read_vol(paste0(dirname(temp), "/nihpd_asym_07.5-13.5_t1w.nii"))

Now we can display it using the plot command. We will show every 15th slice.

   plot(vol, zlevels=seq(1, dim(vol)[3], by=15))

bbuchsbaum/neuroim2 documentation built on March 29, 2024, 6:36 p.m.