Lab 3 Fast imaging sequence & 3D imaging Purpose: In this lab study, students will obtain experiences by running fast imaging pulse sequences, including fast spin echo (FSE-XL) and spoiled gradient echo (SPGR), observing image details (contrast, signal/noise intensity change, imaging time, etc.), and performing Signal-to-Noise (SNR) measurements.

I. Fast imaging sequences Spin Echo (SE) and Fast Spin Echo (FSE-XL) with multiple echo trains a. SE

TR/TE (ms): 500/10 2D saggital Zoom mode FOV(cm): 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap (Total imaging time: 1 min 12s)

b. FSE-XL:

Echo train length: 2 TR/TE (ms): 500/10 2D saggital Zoom mode FOV(cm): 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap (Total imaging time: 34s)

c. FSE-XL:

Echo train length: 8 TR/TE (ms): 500/10 2D saggital Zoom mode FOV(cm): 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap (Total imaging time: 10s)

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d. FSE-XL: Echo train length: 16 TR/TE: 500/10 2D saggital Zoom mode FOV(cm): 6 x 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap (Total imaging time: 6s)

Gradient Echo (GRE) and fast Gradient Echo sequences e. GRE

TR/TE (ms): 300/10 2D saggital Zoom mode FOV(cm): 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap BW(kHz) 31.25

f. SPGR:

TR/TE (ms): 300/10 FA 30 2D saggital Zoom mode FOV(cm): 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap BW (kHz) 15.6

g. SPGR:

TR/TE (ms): 300/10 FA 30 2D saggital Zoom mode FOV(cm): 6 x 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap BW (kHz) 31.25

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h. FSPGR: TR/TE (ms): 300/10 2D saggital Zoom mode FOV(cm): 6 x 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap BW (kHz) 31

i. FSPGR:

TR/TE (ms): 100/10 2D saggital Zoom mode FOV(cm): 6 x 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap BW (kHz) 31

j. FSPGR:

TR/TE (ms): 50/10 2D saggital Zoom mode FOV(cm): 6 x 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap BW (kHz) 31

k. FSPGR:

TR/TE (ms): 25/10 2D saggital Zoom mode FOV(cm): 6 x 6 Matrix: 128 x128 Slice thickness 4mm w/ 1.5mm gap BW (kHz) 31

B. Volunteer testing

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II. SNR measurements

NEMA (National Electrical Manufacturer Association) SNR measurement

std

M

NSSNR =

Where SM: Mean of signal in ROI (e.g. egg white or yolk) Nstd: Standard deviation of noise measured at the background Appendix: Citrix logon User name: phys8900 Passwd: BIRC2007 Matlab server logon Right click on the background, and Open a terminal Type: ssh matlab.birc.uga.edu Passwd: BIRC2007

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Lab3 Assignments

Follow the instructions in MRI image processing Toolkit to measure signal from egg white and yolk, background noise, and then calculate SNR for each of the following images. Under /home/qzlab/phys8900/GUI/data/Test_egg/MR/ Check images in the following folders, measure signal and noise (mean and standard deviation), and find out how the SNR changes with bandwidth 2D,ZOOM,spgr_bw15 (Bandwidth 15.5kHz) 2D,ZOOM,spgr_bw30 (Bandwidth 31kHz) Check images in the following folders, measure signal and noise (mean and standard deviation), and answer how the signal/noise changes with TR 2D,ZOOM,fspgr__tr300 (TR=300ms) 2D,ZOOM,fspgr__tr100 (TR=100ms) 2D,ZOOM,fspgr,_tr50 (TR=50ms)

Pulse Sequence

Signal (egg white)

Signal (yolk)

Noise

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MRI Image Processing Toolkit Manual

PHYS 8900

2007

Introduction MRI Image Processing Toolkit is the software to view, process, and analyze MRI images such as Dicom files and raw P files (e.g., Pxxxx.7). Follow the instructions below to learn how to use it. 1, Change directory:

cd /home/qzlab/phys8900/GUI 2, Start Matlab software by typing matlab & 3, Type in "DataAna" in the Matlab command window or double click on the file “DataAna.fig” in the file browsing window. The main interface will start up as following:

4, Here you can choose to load Dicom files or raw files. If you're working on Dicom images, click on the first button. It will pop up a window and let you choose the file:

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5, After the Dicom file is opened, the image will be showed in a separate window like following. Note: there is a sliding bar below the image. It could be used to adjust the scale of the image. If you open a file and can't see anything in this window, try to slide the bar first.

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By dragging the mouse over the region of interest, you could obtain the statistics of pixels values of that region.

To get the signal statistics for the region of interest, prescribe a window within the image, like following. The mean and standard deviation of the pixels in the prescribed window will be displayed on the Matlab terminal.

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To obtain the statistics of the background noise, try to the prescribe a window within the background area, like the following. The mean and standard deviation of the pixels in the prescribed window will be displayed on the Matlab terminal.

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6, If you want to open a raw file, go back to the main interface. Click on "Load Raw Image". It will open up the browse window to let you choose which file to open. Click "Open", a separate window should pop up as following:

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Here, you will choose how the raw data is going to be displayed. Choose one from the list and click on "Show".

a. 3D Raw Data This option will display the amplitude of k-space data (raw data).

b. FFT This option will perform a 2-dimensional Fourier Transform on the raw data to reconstruct the image, and display amplitude of the image

c. Angle This option will display phase of the raw data.

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