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HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis
Fall 2006
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HST.583: Functional Magnetic Resonance Imaging: Data Acquisition and Analysis, Fall 2006
Harvard-MIT Division of Health Sciences and Technology
Course Director: Dr. Randy Gollub.
INTRODUCTION
This Lab consists of three parts:
Part 1 : SNR Measurements – Temporal and Spatial Characteristics in Signal and Noise
Part 2 : Determination of MR parameters (T1, T2, T2*) across tissue types and regions of
interest.
Part 3 : EPI distortions due to B0 Inhomogeneity
All experiments will be performed on a human subject. The SNR measurements will also
be run on a phantom for comparison. Some of the data analysis will be performed on the
scanner console, however you will be asked to note the measurements obtained as you
will need them to solve the exercises given in the lab report.
The main goals of this lab are to:
1) Become familiar with basic principles of MRI Physics and
measurements (i.e. SNR, relaxation times, etc).
2) Understand the T1, T2 and T2* properties of various tissue
compartments.
3) Acquire and evaluate phantom data.
4) Perform a human scanning experiment and investigate the
various sources of noise in the fMRI time series.
5) Evaluate EPI distortions through field maps and by varying the
readout properties.
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
1. SNR Measurements
Background
At the most basic level, the SNR depends on the number of protons present in the voxel
(proportional to Voxel Volume if we assume a constant density) and the
MeasurementTime . The latter is a standard aspect of signal averaging assuming the
noise is uncorrelated and distributed in a Gaussian distribution. Each acquisition in the kspace matrix is essentially averaged when the Fourier Transform produces the image.
Therefore the total measurement time is the total amount of time the digitizers are
actually recording k-space samples. For a readout line of 256 samples acquired with a
dwell time (time per sample) of 25μs, this yields an acquisition time of 6.4ms. Sometimes
acquisition time for the readout is expressed in terms of the bandwidth of frequencies
1
present across the image ( BWread ). BWread =
equal to 40kHz for this example.
dwell time
On the Siemens system the BW is expressed in Hz per pixel across the image, so for the
256 matrix above, this is a BWread = 156 Hz/px . The total image acquisition time is the
time per line multiplied by the number of lines (# phase encode steps NPE) and the
number of times each line was averaged (NAVG)
Equation 1 shows the dependence of SNR on some of the above parameters:
Voxel Volume ⋅ N AVG
SNR ∝
(1)
BWread
For fMRI, it is the time-course SNR that is important. Functional MRI is
restricted by multiple sources of variance, such as instrumental sources of error including
thermal noise and shot-to-shot electronic instability, and subject dependent modulations
of the MR signal associated with physiological processes. In addition to respiratory and
cardiac cycle contributions, the physiological noise also consists of a noise element with
BOLD-like TE dependence (Triantafyllou et al. 2005), (Krueger and Glover 2001), and
spatial correlation within gray matter (Krueger and Glover 2001). The origin of this
“BOLD noise” is still not fully understood, but is generally associated with hemodynamic
and metabolic fluctuations in the gray matter. Since the physiological fluctuations
represent a multiplicative modulation of the image signal (Krueger and Glover 2001)
their amplitude scales with the MR image intensity. This is in contrast to the thermal
noise sources which can be represented by the addition of a fixed amount of Gaussian
noise power whose amplitude is determined primarily by the coil loading.
If the noise sources are assumed to be uncorrelated, the total noise in the image
time-course (σ) is related to its thermal (σ0) and physiological (σp) components via:
σ = σ 02 + σ p2 ,
(2)
In our measurements, shot-to-shot scanner instabilities will contribute to both terms, σ0
and σp, depending on their signal dependence. Phantom measurements, however, show that they comprise only a small fraction of the in vivo time course noise. The time-course SNR (tSNR) is then defined as: Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
tSNR =
S
σ + σ p2
2
0
,
(3)
where S is the mean image signal intensity. Defining the SNR in an individual image as
S
SNR0 =
and combining with Eq. (3), we determine the relationship between tSNR
σ0
and SNR0:
tSNR =
SNR0
1 + λ2 ⋅ SNR0 2
(4)
where λ is a constant.
References
1. Triantafyllou C., et al., Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization
of fMRI acquisition parameters. NeuroImage 26, 243–250; 2005.
2. Krueger G, Glover GH. Physiological noise in oxygenation-sensitive magnetic resonance imaging.
Magn Reson Med 46: 631-7; 2001.
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
Experiments
In this exercise we will acquire human MRI data in order to characterize image
signal and noise characteristics and the time-course signal and noise characteristics. Data
will be collected on a 3T Siemens Imager.
We will examine the spatial SNR, time-course SNR and their relationship for three
different image resolutions, 5x5x5mm3, 3x3x3mm3 and 1.5x1.5x1.5mm3. In all cases,
images with zero RF will also be obtained to capture the thermal image noise. For
comparison, time series data using the same parameters will also be acquired on a loading
phantom.
Acquisition:
1) Localizer.
2) EPI time series at low resolution 5mm x 5mm x 5mm, 9 slices, 50 time points,
TR=2000ms, TE=32ms, (see protocol epi_5x5x5_signal).
3) Same as #2 but with no RF excitation (just thermal noise)
4) EPI time series at medium resolution 3mm x 3mm x 3mm, 9 slices, 50 time
points, TR=2000ms, TE=32ms (see protocol epi_3x3x3_signal).
5) Same as #4 but with no RF excitation (just thermal noise).
6) EPI time series at higher resolution 1.5mm x 1.5mm x 1.5mm, 9 slices, 50 time
points, TR=2000ms, TE=32ms (see protocol epi_1.5x1.5x1.5_signal).
7) Same as #6 but with no RF excitation (just thermal noise).
Note 1: Typically, thermal noise would be calculated by drawing an ROI outside the
signal area in an image. However in EPI acquisition there are a lot of artifacts present. To
avoid misreading the noise we thus acquire a separate image without an RF that provides
a better representation of thermal noise.
Note 2: Since the thermal noise is random we need to characterize it in terms of its mean,
and standard deviation (or variance). Before we can calculate these quantities, we also
need to know what kind of statistical distribution this noise belongs to. For example, the
most common type of statistical distribution is the Gaussian or normal distribution but the
spatial MRI noise outside of the brain has been empirically determined to follow a
Rayleigh distribution. It is thus simple to compute the mean and variance of the thermal
noise by first computing its variance and mean as though it were Gaussian and applying a
Rayleigh correction factor to account for this difference.
Spatial SNR (SNR0)
The SNR in an individual image (SNR0) is a measure or the image quality. In our
experiments we will evaluate the impact of the spatial resolution on the SNR0. In human
data, ROIs will be defined in cortical gray matter. The SNR0 for a given pixel will be
calculated as the mean pixel value for all the images in the time-series divided by the
standard deviation of the thermal noise of the time-series acquired with no RF excitation
(zero flip angle images).
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
1. Load the EPI images and the Noise time-courses on the mean curve task card.
2. Select the EPI time-course, draw an ROI within the signal area, and record the
mean signal value.
3. Select the Noise time-course, draw an ROI and record the standard deviation.
4. Record your measures in Table 1 and calculate the SNR0.
5. Repeat steps 1-4 for all three spatial resolutions.
6. Repeat steps 1-4 for the phantom data at all three resolutions and record results on
Table 2.
™ Lab Question 1 : Draw the calculated SNR0 as a function of voxel size
and comment on your findings. Describe the differences if any, between
the human and phantom data.
Temporal SNR (tSNR)
Temporal SNR is defined as the image-to-image variance in the time-course and will be
measured on a ROIs based analysis in the cortical gray matter. Temporal SNR in a given
pixel will be determined from the mean pixel value across the 50 time points divided by
its temporal standard deviation.
1. Load the EPI time series images on the viewer.
2. Calculate the Standard Deviation map from the EPI time series through the
scanner UI. Open the Patient Browser, go to Evaluation -> Dynamic Analysis ->
Standard Deviation. Press within series, test and assign a name to the new image
(STD_mymap). A new series is created on your patient browser, named
STD_mymap.
3. Load the images on the mean curve task card. Select both the EPI time course and
the standard deviation map and draw an ROI within the signal area.
4. Record the mean value within the ROI on the EPI images; that is your temporal
mean of the signal.
5. Record the mean value within the ROI on the standard deviation map; that is your
temporal noise.
6. Calculate the temporal SNR from the above quantities and note on Table 1.
7. Repeat steps 1-6 for all three spatial resolutions.
8. Repeat steps 1-6 for the phantom data at all three resolutions and record results on
Table 2.
™ Lab Question 2: Draw the calculated tSNR as a function of voxel size
and comment on your findings. Describe the differences if any, between
the human and phantom data.
Relationship between SNR0 and tSNR
The tSNR will be analyzed as a function of SNR0 for the given set of resolutions. Use the
recorded values from Tables 1 and 2 incorporating the model for tSNR from Eq. 4 (where
λ=0.0107).
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
™ Lab Question 3 : Show the relationship of tSNR as a function of SNR0
when SNR0 is modulated by the voxel size. Describe the differences, if
any, between the human and phantom data. What is the asymptotic limit
for tSNR?
™ Lab Question 4 : You are asked to perform an fMRI study of medial
temporal lobe activation at a high field strength. Which acquisition
parameters would you consider most important to optimize in order to
achieve the best activation results? For a 3T scanner provide a suggested
set of acquisition parameters.
™ Lab Question 5 : Draw ROIS on various tissue types, generate the tSNR
as a function of SNR0 in gray matter, white matter and CSF. Record mean
signal and standard deviation of the noise. Comment on your findings.
Table 1 – Human Data
Average values for SNR measurements as a function of image resolution. SNR0
corrected for Rayleigh distribution.
Resolution
Signal
(mm3)
Thermal
Time-Series
Spatial
Temporal
Noise
Noise
SNR
SNR
1.5x1.5x1.5
3x3x3
5x5x5
Table 2 – Phantom Data
Average values for SNR measurements as a function of image resolution. SNR0
corrected for Rayleigh distribution.
Resolution
(mm3)
Signal
Thermal
Time-Series
Spatial
Temporal
Noise
Noise
SNR
SNR
1.5x1.5x1.5
3x3x3
5x5x5
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
Table 3 – Human Data - Gray Matter
Average values for SNR measurements as a function of image resolution. SNR0
corrected for Rayleigh distribution.
Resolution
Signal
(mm3)
Thermal
Time-Series
Spatial
Temporal
Noise
Noise
SNR
SNR
1.5x1.5x1.5
3x3x3
5x5x5
Table 4 – Human Data - White Matter
Average values for SNR measurements as a function of image resolution. SNR0
corrected for Rayleigh distribution.
Resolution
Signal
3
(mm )
Thermal
Time-Series
Spatial
Temporal
Noise
Noise
SNR
SNR
1.5x1.5x1.5
3x3x3
5x5x5
Table 5 – Human Data - CSF
Average values for SNR measurements as a function of image resolution. SNR0
corrected for Rayleigh distribution.
Resolution
(mm3)
Signal
Thermal
Time-Series
Spatial
Temporal
Noise
Noise
SNR
SNR
1.5x1.5x1.5
3x3x3
5x5x5
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
2. T1, T2 and T2* Measurements
Background
To calculate T1 values of the tissue we will be using an inversion recovery turbo spin
echo sequence. We will be sampling the magnetization as a function of the inversion time
(TI). The observed signal intensity is given by the following equation:
S(t) ∝ [1 − 2 exp(−TI / T1)]
(1)
To obtain the transverse relaxation time, T2, values in the brain a series of spin echo
images will be acquired by stepping through a range of TEs. The image intensity is given
by the following equation:
S(t) ∝ exp(−TE / T 2)
(2)
T2star (T2*) is the time constant that describes the decay of the transverse magnetization
including local magnetic field inhomogeneities. T2* is an important relaxation time for
functional studies because it is related to the amount of deoxygenated hemoglobin present
in the brain. To determine the T2* values in gray, white matter and CSF, we will be using
a gradient echo sequence and the signal is described by:
S(t) ∝ exp(−TE / T 2*)
(3)
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
Experiments
In this exercise we will acquire and evaluate human data in order to characterize
T1, T2 and T2* values in brain tissue compartments. Various sequences will be used with
the imaging parameters manipulated so that they provide the appropriate contrast
weightings.
T1 measurements
Acqusition: Total scan time: 5m 38sec
A. Inversion Recovery Turbo Spin Echo (tse_IR) sequence with TR=3000ms,
FOV=240x240, matrix=96x128, repeated for multiple inversion times TI=200,
300, 400, 500, 600, 700, 800, 1000, 1300, 1500, 1700, 2000, 2200 ms.
1.
2.
3.
4.
Load all the images on the viewer.
Draw ROIs in gray matter areas.
Record the mean signal values in Table 1 for each inversion time and ROI.
Repeat steps 1-3 for regions of white matter and CSF.
™ Lab Question 6 : Draw the measured signal as a function of inversion
time for each of the tissue compartments. Calculate the T1 for gray, white
matter and CSF by fitting Eq. (1) to your data. Hint: you will need to use a
nonlinear fitting function such as nlinfit in matlab to accomplish this.
T2 measurements
Acqusition: Total scan time: 9m 42sec
B. SE sequence with TR=4000ms, FOV=220x220, matrix=192x192, 8 echo times in
a range between 14.3ms and 114.4ms and inter-echo spacing 14.3 ms.
5.
6.
7.
8.
Load all the images on the viewer.
Draw ROIs in gray matter areas.
Record the mean signal values in Table 2 for each echo time and ROI.
Repeat steps 1-3 for regions of white matter and CSF.
™ Lab Question 7 : Draw the measured signal as a function of echo time for
each of the tissue compartments. Calculate the T2 for gray, white matter
and CSF by fitting Eq. (2) to your data.
T2* measurements
Acqusition: Total scan time: 1m 20sec
C. 2D FLASH sequence with TR=100msec, FOV=256x256, matrix=128x128,
sequence was repeated for multiple echo times TE=6, 10, 15, 20, 30, 50, 70, 90
msec.
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
9. Load all the images on the viewer.
10. Draw ROIs in gray matter areas.
11. Record the mean signal values in Table 3 for each echo time and ROI.
12. Repeat steps 1-3 for regions of white matter and CSF.
™ Lab Question 8 : Draw the measured signal as a function of echo time for
each of the tissue compartments. Calculate the T2* of gray and white
matter and CSF by fitting Eq. (3) to your data.
™ Lab Question 9 : According to your measurements how do T2 and T2*
compare for the same tissue compartment? Did you expect these findings?
Explain why.
Table 1 – T1 Measurements
TI (ms)
Gray
White
Matter
Matter
CSF
200
300
400
500
600
700
800
1000
1300
1500
1700
2000
2200
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
Table 2 – T2 Measurements
TE (ms)
Gray
White
Matter
Matter
CSF
14.3
28.6
42.9
57.2
71.5
85.8
100.1
114.4
Table 3 – T2* Measurements
TE (ms)
Gray
White
Matter
Matter
CSF
6
10
15
20
30
50
70
90
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
3. Distortion in EPI due to B0 Inhomogeneity
Background
The echo-planar image (EPI) is distorted due to local field gradients present in the head
during imaging. Since the acquisition of k-space data is very asymmetric in EPI, with the
readout direction points (kx) collected quickly and the phase encode steps (ky) relatively
slowly, the distortion is essentially entirely in the y direction (phase encode direction).
The relative distortion between the two directions can be estimated from the relative
speed of the acquisition. In kx, at a typical readout BW (say 2.2kHz/pixel or 140kHz in
frequency across the 64 pixel image), the dwell time (time between kx samples) is 7.1μs.
The ky sampling rate is slower because of the zig-zag trajectory, and is about 64 times
slower. This gives a sampling spacing of 64 * 7.1μs = 0.45ms. We call this .the "echo
spacing", (esp), of the sequence, the time between gradient echos (acquisition of the kx=0
point).
1
The effective "bandwidth" in the phase encode direction is therefore
across the
esp
image or 1/64*esp = 34.7Hz/pixel. Therefore a B0 shift which induces a 34.7Hz
frequency shift will induce a shift in this region of 1pixel. The frequency shifts in the
"bad susceptibility" regions of the brain are easily in the 100Hz range. Therefore, the
principle metric of how distorted the EPI sequence will be is its effective echo-spacing.
For conventional echo-planar imaging, this is basically limited by the gradient slew rate
and amplitude. Using parallel acceleration such as SENSE or GRAPPA effectively
decreases the esp by a factor of the acceleration factor, (i.e. 2 or 3 fold).
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
Experiments
In this lab we will acquire images with different effective esp and compare the distortion
in the brain.
Acquisition :
1) epi_sp460: voxel size = 3.1 x 3.1 x 3.1, Matrix size = 64x64, BW=2520Hz/px,
ESP=0.46ms, effective esp =0.46ms
2) epi_sp470_grappa: voxel size = 3.1 x 3.1 x 3, Matrix size = 64x64,
BW=2520Hz/px, ESP=0.46ms, effective esp =0.46ms
3) epi_sp730: voxel size = 3.1 x 3.1 x 3, Matrix size = 64x64, BW=1502Hz/px,
ESP=0.73ms, effective esp =0.73ms
™ Lab Question 10: Estimate the distortion in frontal lobes by measuring
distance on the scanner to some reference feature. Plot the distortion in
mm as a function of effective esp.
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\epi_5x5x5_signal TA: 1:44
PAT: Off
Voxel size: 5.0×5.0×5.0 [mm]
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
9
0 [%]
R3.0 A0.3 H27.1 [mm]
T > C-12.5
A >> P
0.340792 [deg]
0 [%] 240 [mm] 100.0 [%] 5 [mm] 2000 [ms] 32 [ms] 1
1
None HEA;HEP Contrast
MTC
Flip angle
Reconstruction
Fat suppr.
Measurements
Delay in TR
Multiple series
Off
90 [deg]
Magnitude
Fat sat.
50
0 [ms]
Off
Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1 Raw filter
Interpolation
Rel. SNR: 1.00
USER: benner\ep2d_bold_MGH_pro_tb R >> L
A >> P
F >> H
240 [mm]
240 [mm]
45 [mm]
Physio
1st Signal/Mode
None
BOLD
t-Test
Threshold
Window
Starting ignore meas
Paradigm size
Meas
Motion correction
Spatial filter
0
4.00
Growing
0
1
Ignore
0
0
Sequence
Introduction
Averaging mode
Bandwidth
Free echo spacing
Echo spacing
Off Long term 3472 [Hz/Px] Off 0.36 [ms] ------------------------------------------------------------------------------------
EPI factor
RF pulse type
Gradient mode
48 Normal Fast ------------------------------------------------------------------------------------
Dummy Scans
2
48 100 [%] Off Off Off ------------------------------------------------------------------------------------
PAT mode
Matrix Coil Mode
None Auto (CP) Geometry
Multi-slice mode
Series
Interleaved
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off On On ------------------------------------------------------------------------------------
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Off H
0 [mm] S-C-T
R >> L A >> P F >> H ------------------------------------------------------------------------------------
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume Position
Orientation
Rotation
Standard Off Off Off 240.360 [V] R3.0 A0.3 H27.1 [mm] T > C-12.5 0.340792 [deg] 1/+
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\epi_3x3x3_signal TA: 1:44
PAT: Off
Voxel size: 3.0×3.0×3.0 [mm]
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
9
67 [%]
R3.0 A0.3 H27.1 [mm]
T > C-12.5
A >> P
0.340792 [deg]
0 [%] 192 [mm] 100.0 [%] 3 [mm] 2000 [ms] 32 [ms] 1
1
None HEA;HEP Contrast
MTC
Flip angle
Reconstruction
Fat suppr.
Measurements
Delay in TR
Multiple series
Off
90 [deg]
Magnitude
Fat sat.
50
0 [ms]
Off
Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1 Raw filter
Interpolation
Rel. SNR: 1.00
USER: benner\ep2d_bold_MGH_pro_tb R >> L
A >> P
F >> H
192 [mm]
192 [mm]
44 [mm]
Physio
1st Signal/Mode
None
BOLD
t-Test
Threshold
Window
Starting ignore meas
Paradigm size
Meas
Motion correction
Spatial filter
0
4.00
Growing
0
1
Ignore
0
0
Sequence
Introduction
Averaging mode
Bandwidth
Free echo spacing
Echo spacing
Off
Long term
2520 [Hz/Px]
Off
0.47 [ms]
------------------------------------------------------------------------------------
EPI factor
RF pulse type
Gradient mode
64
Normal
Fast
------------------------------------------------------------------------------------
Dummy Scans
2
64 100 [%] Off Off Off ------------------------------------------------------------------------------------
PAT mode
Matrix Coil Mode
None Auto (CP) Geometry
Multi-slice mode
Series
Interleaved
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off On On ------------------------------------------------------------------------------------
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Off H
0 [mm] S-C-T
R >> L A >> P F >> H ------------------------------------------------------------------------------------
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume Position
Orientation
Rotation
Standard Off Off Off 240.360 [V] R3.0 A0.3 H27.1 [mm] T > C-12.5 0.340792 [deg] 2/+
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\epi_1.5x1.5x1.5_signal TA: 1:44
PAT: Off
Voxel size: 1.5×1.5×1.5 [mm]
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
9
233 [%]
R3.0 A0.3 H27.1 [mm]
T > C-12.5
A >> P
0.340792 [deg]
0 [%] 192 [mm] 100.0 [%] 1.5 [mm] 2000 [ms] 30 [ms] 1
1
None HEA;HEP Contrast
MTC
Flip angle
Reconstruction
Fat suppr.
Measurements
Delay in TR
Multiple series
Off
90 [deg]
Magnitude
Fat sat.
50
0 [ms]
Off
Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1 Raw filter
Interpolation
Rel. SNR: 1.00
USER: benner\ep2d_bold_MGH_pro_tb R >> L
A >> P
F >> H
192 [mm]
192 [mm]
42 [mm]
Physio
1st Signal/Mode
None
BOLD
t-Test
Threshold
Window
Starting ignore meas
Paradigm size
Meas
Motion correction
Spatial filter
0
4.00
Growing
0
1
Ignore
0
0
Sequence
Introduction
Averaging mode
Bandwidth
Free echo spacing
Echo spacing
Off Long term 1502 [Hz/Px] Off 0.75 [ms] ------------------------------------------------------------------------------------
EPI factor
RF pulse type
Gradient mode
128 Normal Fast ------------------------------------------------------------------------------------
Dummy Scans
2
128 100 [%] 5/8 Off Off ------------------------------------------------------------------------------------
PAT mode
Matrix Coil Mode
None Auto (CP) Geometry
Multi-slice mode
Series
Interleaved
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off On On ------------------------------------------------------------------------------------
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Off H
0 [mm] S-C-T
R >> L A >> P F >> H ------------------------------------------------------------------------------------
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume Position
Orientation
Rotation
Standard Off Off Off 240.360 [V] R3.0 A0.3 H27.1 [mm] T > C-12.5 0.340792 [deg] 3/-
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\se_mc TA: 9:42
Voxel size: 1.1×1.1×5.0 [mm]
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE[1]
TE[2]
TE[3]
TE[4]
TE[5]
TE[6]
TE[7]
TE[8]
Averages
Concatenations
Filter
Coil elements
1
100 [%]
R0.7 A10.8 H12.2 [mm]
T > C-10.3
A >> P
0 [deg]
0 [%] 220 [mm] 100.0 [%] 5 [mm] 4000 [ms] 14.3 [ms] 28.6 [ms] 42.9 [ms] 57.2 [ms] 71.5 [ms] 85.8 [ms] 100.1 [ms] 114.4 [ms] 1
1
Raw filter HEA;HEP Contrast
MTC
Magn. preparation
Flip angle
Reconstruction
Fat suppr.
Fat sat. mode
Water suppr.
Measurements
Off
None
180 [deg]
Magnitude
None
Strong
None
1
Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1
Raw filter
Intensity
Slope
Filter 2
Large FoV
Filter 3
Prescan Normalize
Filter 4
Normalize
Filter 5
Elliptical filter
Interpolation
Geometry
Multi-slice mode
Series
192
100 [%]
6/8
On
Weak
25
Rel. SNR: 1.00
SIEMENS: se_mc Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Matrix Coil Mode
H
0 [mm]
S-C-T
R >> L A >> P F >> H Auto (CP) ------------------------------------------------------------------------------------
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume Position
Orientation
Rotation
R >> L
A >> P
F >> H
Physio
1st Signal/Mode
Tune up Off Off Off 330.070 [V] Isocenter Transversal 0 [deg] 350 [mm] 263 [mm] 350 [mm] None
------------------------------------------------------------------------------------
Dark blood
Off
Inline
Subtract
Std-Dev-Sag
Std-Dev-Cor
Std-Dev-Tra
Std-Dev-Time
MIP-Sag
MIP-Cor
MIP-Tra
MIP-Time
Save original images
0
0
0
0
0
0
0
0
0
1
Sequence
Introduction
Averaging mode
Contrasts
Bandwidth
Allowed delay
On Short term 8
202 [Hz/Px] 0 [s] ------------------------------------------------------------------------------------
RF pulse type
Gradient mode
Normal Fast Off
Off
Off
Off
Off
Interleaved
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off On On ------------------------------------------------------------------------------------
Save uncombined
Scan at current TP
Off Off 1/-
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\FLASH_T2star_TE6
+ TA: 9.6 [s]
Voxel size: 2.0×2.0×5.0 [mm]
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
1
20 [%] R0.7 A10.8 H12.2 [mm] T > C-10.3 A >> P 0 [deg] 0 [%] 256 [mm] 100.0 [%] 5 [mm] 100 [ms] 6 [ms] 1
1
Raw filter HEA;HEP Contrast
MTC
Flip angle
Reconstruction
Fat suppr.
Water suppr.
Measurements
Off
15 [deg]
Magnitude
None
None
1
Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1
Raw filter
Intensity
Slope
Filter 2
Large FoV
Filter 3
Prescan Normalize
Filter 4
Normalize
Filter 5
Elliptical filter
Interpolation
Geometry
Multi-slice mode
Series
128
100 [%]
6/8
On
Weak
25
Off
Off
Off
Rel. SNR: 1.00
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume
Position
Orientation
Rotation
R >> L
A >> P
F >> H
USER: FLASH
Off
Off
Off
319.952 [V]
Isocenter
Transversal
0 [deg]
350 [mm]
263 [mm]
350 [mm]
Physio
1st Signal/Mode
None
Inline
Subtract
Std-Dev-Sag
Std-Dev-Cor
Std-Dev-Tra
Std-Dev-Time
MIP-Sag
MIP-Cor
MIP-Tra
MIP-Time
Save original images
0
0
0
0
0
0
0
0
0
1
Sequence
Introduction
Dimension
Averaging mode
Contrasts
Bandwidth
Off 2D Long term 1
300 [Hz/Px] ------------------------------------------------------------------------------------
Gradient mode
RF spoiling
Fast On ------------------------------------------------------------------------------------
Online ICE
Selection box
Spoil me!
Test Time
dARRAY [1]
dARRAY [2]
dARRAY [3]
Off Second Choice On 10 ms 1 [UnitArr] 12 [UnitArr] 22 [UnitArr] Off
Off
Sequential
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off
On
On
------------------------------------------------------------------------------------
Save uncombined
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Matrix Coil Mode
Off
Off
H
0 [mm]
S-C-T
R >> L
A >> P
F >> H
Auto (CP)
------------------------------------------------------------------------------------
Shim mode
Tune up 1/-
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\tse_IR1 TA: 0:26
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
PAT: Off
Voxel size: 1.9×1.9×5.0 [mm]
Rel. SNR: 1.00
Coronal
Transversal
SIEMENS: tse A >> P F >> H ------------------------------------------------------------------------------------
1
50 [%]
R0.7 A10.8 H12.2 [mm]
T > C-10.3
R >> L
90 [deg]
0 [%]
240 [mm]
75.0 [%]
5 [mm]
3000 [ms]
12 [ms]
1
1
None
HEA;HEP
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume
Position
Orientation
Rotation
R >> L
A >> P
F >> H
Physio
1st Signal/Mode
Tune up
Off
Off
Off
330.070 [V]
Isocenter
Transversal
0 [deg]
350 [mm]
263 [mm]
350 [mm]
None ------------------------------------------------------------------------------------
Dark blood
Off ------------------------------------------------------------------------------------
Contrast
MTC
Magn. preparation
TI
Flip angle
Reconstruction
Fat suppr.
Fat sat. mode
Water suppr.
Measurements
Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1 Raw filter
Filter 2 Large FoV
Filter 3 Prescan Normalize
Filter 4 Normalize
Filter 5 Elliptical filter
Interpolation
Resp. control
Off
Slice-sel. IR
1000 [ms]
180 [deg]
Real
None
Strong
None
1
128 100 [%] Off Off Off Off Off Off Off ------------------------------------------------------------------------------------
PAT mode
Matrix Coil Mode
None Auto (CP) Geometry
Multi-slice mode
Series
Interleaved
Interleaved
Off Inline
Subtract
Std-Dev-Sag
Std-Dev-Cor
Std-Dev-Tra
Std-Dev-Time
MIP-Sag
MIP-Cor
MIP-Tra
MIP-Time
Save original images
0
0
0
0
0
0
0
0
0
1
Sequence
Introduction
Dimension
Compensate T2 decay
Averaging mode
Contrasts
Bandwidth
Flow comp.
Allowed delay
Echo spacing
On 2D Off Short term 1
130 [Hz/Px] No 0 [s] 11.7 [ms] ------------------------------------------------------------------------------------
Turbo factor
RF pulse type
Gradient mode
Hyperecho
15 Normal Fast Off ------------------------------------------------------------------------------------
Special sat.
None
------------------------------------------------------------------------------------
System
Body
HEP
HEA
Off On On ------------------------------------------------------------------------------------
Save uncombined
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Off Off H
0 [mm] S-C-T
R >> L 1/Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\epi_esp730 TA: 2.0 [s]
PAT: Off
Voxel size: 3.1×3.1×3.0 [mm]
USER: benner\ep2d_bold_MGH_pro_tb A >> P
F >> H
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
9
67 [%]
R0.3 A11.0 F2.1 [mm]
T > C-10.4
A >> P
0.340792 [deg]
0 [%] 200 [mm] 100.0 [%] 3 [mm] 2000 [ms] 30 [ms] 1
1
None HEA;HEP Contrast
MTC
Flip angle
Reconstruction
Fat suppr.
Measurements
Delay in TR
Off 90 [deg] Magnitude Fat sat. 1
0 [ms] Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1 Raw filter
Interpolation
Rel. SNR: 1.00
200 [mm]
44 [mm]
Physio
1st Signal/Mode
None
BOLD
t-Test
Threshold
Window
Starting ignore meas
Paradigm size
Meas
Motion correction
Spatial filter
0
4.00
Growing
0
1
Ignore
0
0
Sequence
Introduction
Averaging mode
Bandwidth
Free echo spacing
Echo spacing
Off Long term 1502 [Hz/Px] Off 0.73 [ms] ------------------------------------------------------------------------------------
EPI factor
RF pulse type
Gradient mode
64 Normal Fast ------------------------------------------------------------------------------------
Dummy Scans
0
64 100 [%] Off Off Off ------------------------------------------------------------------------------------
PAT mode
Matrix Coil Mode
None Auto (CP) Geometry
Multi-slice mode
Series
Interleaved
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off On On ------------------------------------------------------------------------------------
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Off H
0 [mm] S-C-T
R >> L A >> P F >> H ------------------------------------------------------------------------------------
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume Position
Orientation
Rotation
R >> L
Standard Off Off Off 240.360 [V] R0.3 A11.0 F2.1 [mm] T > C-10.4 0.340792 [deg] 200 [mm] 1/+
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\epi_esp460 TA: 2.0 [s]
PAT: Off
Voxel size: 3.1×3.1×3.1 [mm]
USER: benner\ep2d_bold_MGH_pro_tb A >> P
F >> H
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
9
67 [%]
R0.3 A11.0 F2.1 [mm]
T > C-10.4
A >> P
0.340792 [deg]
0 [%] 200 [mm] 100.0 [%] 3.1 [mm] 2000 [ms] 30 [ms] 1
1
None HEA;HEP Contrast
MTC
Flip angle
Reconstruction
Fat suppr.
Measurements
Delay in TR
Off 90 [deg] Magnitude Fat sat. 1
0 [ms] Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1 Raw filter
Interpolation
Rel. SNR: 1.00
200 [mm]
45 [mm]
Physio
1st Signal/Mode
None
BOLD
t-Test
Threshold
Window
Starting ignore meas
Paradigm size
Meas
Motion correction
Spatial filter
0
4.00
Growing
0
1
Ignore
0
0
Sequence
Introduction
Averaging mode
Bandwidth
Free echo spacing
Echo spacing
Off Long term 2520 [Hz/Px] Off 0.46 [ms] ------------------------------------------------------------------------------------
EPI factor
RF pulse type
Gradient mode
64 Normal Fast ------------------------------------------------------------------------------------
Dummy Scans
0
64 100 [%] Off Off Off ------------------------------------------------------------------------------------
PAT mode
Matrix Coil Mode
None Auto (CP) Geometry
Multi-slice mode
Series
Interleaved
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off On On ------------------------------------------------------------------------------------
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Off H
0 [mm] S-C-T
R >> L A >> P F >> H ------------------------------------------------------------------------------------
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume Position
Orientation
Rotation
R >> L
Standard Off Off Off 240.360 [V] R0.3 A11.0 F2.1 [mm] T > C-10.4 0.340792 [deg] 200 [mm] 2/+
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
SIEMENS MAGNETOM TrioTim syngo MR 2006T
\\USER\INVESTIGATORS\HST_583\PhysicsClass\epi_esp460_grappa2 TA: 8.0 [s]
PAT: 2
Voxel size: 3.0×3.0×3.0 [mm]
Routine
Slice group 1
Slices
Dist. factor
Position
Orientation
Phase enc. dir.
Rotation
Phase oversampling
FoV read
FoV phase
Slice thickness
TR
TE
Averages
Concatenations
Filter
Coil elements
9
67 [%]
R0.3 A23.9 H8.1 [mm]
Transversal
A >> P
0.340792 [deg]
0 [%] 192 [mm] 100.0 [%] 3 [mm] 2000 [ms] 30 [ms] 1
1
None HEA;HEP Contrast
MTC
Flip angle
Reconstruction
Fat suppr.
Measurements
Delay in TR
Off 90 [deg] Magnitude Fat sat. 1
0 [ms] Rel. SNR: 1.00
USER: benner\ep2d_bold_MGH_pro_tb Rotation
R >> L
A >> P
F >> H
0.340792 [deg]
192 [mm]
192 [mm]
44 [mm]
Physio
1st Signal/Mode
None
BOLD
t-Test
Threshold
Window
Starting ignore meas
Paradigm size
Meas
Motion correction
Spatial filter
0
4.00
Growing
0
1
Ignore
0
0
Sequence
Introduction
Averaging mode
Bandwidth
Free echo spacing
Echo spacing
Off Long term 2520 [Hz/Px] Off 0.48 [ms] ------------------------------------------------------------------------------------
EPI factor
RF pulse type
Gradient mode
64 Normal Fast ------------------------------------------------------------------------------------
Resolution
Base resolution
Phase resolution
Phase partial Fourier
Filter 1 Raw filter
Interpolation
Dummy Scans
0
64 100 [%] Off Off Off ------------------------------------------------------------------------------------
PAT mode
Accel. factor PE
Ref. lines PE
Matrix Coil Mode
Geometry
Multi-slice mode
Series
GRAPPA 2
32 Auto (Triple) Interleaved
Interleaved
------------------------------------------------------------------------------------
Special sat.
System
Body
HEP
HEA
None
Off On On ------------------------------------------------------------------------------------
Scan at current TP
Scan region position
Scan region position
MSMA
Sagittal
Coronal
Transversal
Off H
0 [mm] S-C-T
R >> L A >> P F >> H ------------------------------------------------------------------------------------
Shim mode
Adjust with body coil
Confirm freq. adjustment
Assume Silicone
Ref. amplitude [1H]
Adjust volume Position
Orientation
Standard Off Off Off 240.360 [V] R0.3 A23.9 H8.1 [mm]
Transversal
3/Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.
Cite as: Cristina Triantafyllou and Larry Wald
, HST.583 Functional Magnetic Resonance Imaging: Data Acquisition
and Analysis, Fall 2006. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu
(Accessed MM DD, YYYY). License: Creative Commons BY-NC-SA.