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Image Processing for MRI






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Image Processing for MRI. Tips and Pitfalls. Patient -> Image -> Beyond. signal reception FFT indices, coordinates File formats DICOM – 3D positions window levels. 16 bits are not enough precision. ~16 bit analogue to digital converter integers 0 – 65535.
Image Processing for MRI

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Slide 1

Image Processing for MRI

Tips and Pitfalls

Slide 2

Patient -> Image -> Beyond

  • signal reception

  • FFT

  • indices, coordinates

  • File formats

  • DICOM – 3D positions

  • window levels

Slide 3

16 bits are not enough precision

  • ~16 bit analogue to digital converter

    • integers 0 – 65535.

  • True dynamic range is higher (variable attenuators in receiver chain).

  • Complex FFT and other processing.

  • Use “intensity” image (floating point values), rather than indexed or rgb.

    • avoid read/writing intermediate files in tiff, gif.

Slide 4

FAST Fourier Transform Convention

Slide 5

FFT on 2D k-space

k-space

FFT

Slide 6

FFT Recipe

1 shift

2 FFT

3 unshift

Slide 7

FFT other tips

  • 1/N scaling between forward and reverse.

  • Lack of convention for forward/reverse.

  • Don’t 3D FFT multi-slice data.

  • Beware of indices and the location of DC.

0

N/2 + 1

N/2

Slide 8

Vertical axis reflection

  • Care mapping:

  • spatial transformations

  • k-space frequencies

Slide 9

2D data in memory and files

2D data stored sequentially in 1D memory/file

MATLAB matrix(row, column)

IDL matrix(column, row)

C array [ index1 ] [ index2 ]

index is written out most rapidly

Symptoms: rotated (transposed) images.

Slide 10

File Formats

  • See David Clunie’s Medical Image web site. http://www.dclunie.com/

  • Files contain: Information and pixel values.

  • Information in either:

    • fixed length header (gipl)

    • fixed length separate file (Analyze)

    • tags (ACR/NEMA, tiff, DICOM, SPI)

Slide 11

Big endian

“big end first”

Unix

Motorola Mac

Little endian

“little end first”

Intel (Windows and Linux on a PC)

Endian (not indian)

Order in which multiple byte variables are stored

Slide 12

Endian (cont)

Problems reading file previously written on a different system.

Most standard image file types and readers cope.

MATLAB – specify within fopen

IDL - byte swapping commands.

Do not just swap every pair of bytes blindly.

Slide 13

3D Information in DICOM

right-handed coordinate system

+z Head

ImagePositionPatient

(x,y,z)

r

centre of top-left pixel

+y Posterior

ImageOrientationPatient

c

(rx, ry, rz, cx, cy, cz)

image row and column directions

+x Patient Left

Slide 14

Example

Example

  • restrict FOV

  • surf command

  • vertices specified

  • no edge color

!! relies on radiographer correctly entering supine/prone, head-foot !!

Slide 15

Decoding a DICOM directory

  • Thousands of files often with meaningless names.

    • Set up DICOM node to use sensible file names.

    • Examine the slice separations in 3D space using ImagePositionPatient.

    • for cardiac phases, use TriggerDelay?

  • Future standard: Multi-frame DICOM objects for MR. Also allow annotation for tractography, fMRI etc.

Slide 16

Coordinates

}?

(0,0)

(1,1)

(0.5,0.5)

Tip: generate a 4x4 image, plot a point.

To find rotation centres, create a cross test object.

Slide 17

Image Presentation

same image

Slide 18

Window levels

  • Alarming differences in gamma

    • CRT, LCD

    • Sun, Mac, PC.

    • printer, toner level.

    • projector, room brightness.

  • Fix lower range at 0, adjust upper based on inspection (e.g. exclude fat). Guess gamma. Present with a colour bar.

  • Future: support for .png gamma correction.

Slide 19

Misc.

  • In subtraction images, beware of negative values wrapping round the integer range.

  • signed vs. unsigned integers

  • MR data is complex: transpose, complex conjugate and Hermitian transpose are not the same.

  • http://www.itk.org

    • software

    • test data (BrainWeb, Visible Human)

    • software links (Image Magick, MRIConvert).

Slide 20

misc. (cont)

  • vtk good for surface visualisation.

  • Data is discrete, not continuous.

  • Voxels usually anisotropic.

  • Care: voxel sizes (distortion) and resolution (reduced phase encodes).

  • sinc interpolation is best on bandlimited data – but you may need the raw data, not a truncated image.

Slide 21

Book Recommendations

  • 3D coordinates, transformations, plane.

    Computer Graphics

    Foley, van Dam, Feiner, Hughes.

  • Numerical programming (not code itself)

    Numerical Recipes in C www.nr.com

    Press, Teukolsky, Flannery, Vetterling.

  • Eigenvalues, SVD, FFT, Google search!

    Numerical Computing with MATLAB

    Moler www.mathworks.com/moler

Slide 22

Book Recommendations (cont)

  • Digital Image Processing

    Digital Image Processing using MATLAB

    Gonzalez, Woods and Eddins.

Slide 23

Final Remarks

  • “Don’t image process unless the results can be validated.”

  • “Concentrate on acquisition not image processing.”


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