This page is provided for those readers with computer programming experience who are interested in processing a set of raw, k-space MRI data. The data set consists of 256x256 (65,536) complex points in an ascii text format. The first is a 65,536 complex, one-dimensional array of numbers, and the second is a 256x256 two dimensional complex array. Use whatever programming language you are familiar with. Matlab or IDL may be the fastest while Excel can be used but will be the slowest.

The one-dimensional array file has the following format.
Real(1) Imaginary(1)
Real(2) Imaginary(2)
Real(3) Imaginary(3)
...

The Real and Imaginary pairs are space deliminated while the different complex points are deliminated with a [CR] [LF]. The numerical values of the first three points are
-0.0000009 -0.0000011
-0.0000023 0.0000037
-0.0000076 -0.0000015
...
Click here for the file.

The two dimensional array of complex points are tab deliminated with a [CR] [LF] after 256 points. The real and imaginary parts of the complex number are separated by the sign of the imaginary component. The imaginary component is followed by a lower case i. The format of the first three points in the first row are as follows.
-0.0000009-0.0000011i -0.000006-0.0000074i 0.000003-0.0000025i
Click here for the file.

Check your download and input to your program by taking the magnitude of the two-dimensional array. You should see a black image with a few bright spots in the center. Next perform a Fourier transform on the original 2D array in the vertical direction to yield this real and imaginary data. Now perform a Fourier transform in the horizontal direction to yield this real and imaginary data. Lastly, take the magnitude of the 2D Fourier transformed data.

A variety of programing languages can be used to perform the above transformations and operations. A language such as Matlab will be fastest, while Microsoft Excel will be one of the slower ones. Many fast Fourier transform programs require exchanging of the top half of the data with the bottom half of the data. If you see a divided image, place the left half of the image to the right of the right half of the image.

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