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Image Processing for MRIPowerPoint Presentation

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.

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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.

- 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.

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

Vertical axis reflection

- Care mapping:
- spatial transformations
- k-space frequencies

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.

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)

“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

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.

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

Example

- restrict FOV
- surf command
- vertices specified
- no edge color

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

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.

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.

Image Presentation

same image

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.

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).

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.

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

Book Recommendations (cont)

- Digital Image Processing
Digital Image Processing using MATLAB

Gonzalez, Woods and Eddins.

Final Remarks

- “Don’t image process unless the results can be validated.”
- “Concentrate on acquisition not image processing.”

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