highly constrained back projection (hypr) thank you to oliver wieben!!
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HHighlighlYY Constrained Back Constrained Back PRPRojection (ojection (HYPRHYPR))
Thank you to Oliver Wieben!!
K-space
time
1 3 5 7 9
‘Composite’
HHighlighlYY Constrained Back Constrained Back PRPRojection (ojection (HYPRHYPR))
HHighlighlYY Constrained Back Constrained Back PRPRojection (ojection (HYPRHYPR))
• An approximate acquisition and reconstruction method
• Images should be sparse (few pixels w/signal)
• No movement allowed!
• Fairly high spatio-temporal correlations
• Radial under-sampling at each time frame• Decrease total scan time• Improve temporal resolution
• Composite image • Combines data from many time frames • Allows higher SNR for each time frame• Constrains the backprojection reconstruction for each time frame which reduces streak artifacts
Mistretta, et al., MRM 55:30-40;2006
Interleaving – Dynamic ImagingInterleaving – Dynamic Imaging1. Acquire data in interleaves
Highly undersample each time frame
1 2 3 4 5 6 7 8 9 ….
K-space
CE-MRA time
artery vein
signal
All Inclusive CompositeAll Inclusive Composite2. Calculate composite images
Sum of ALL projections through time
1 2 3 4 5 6 7 8 9 ….
K-space
All inclusive composite
Sliding CompositeSliding Composite2. Calculate composite images
Sum of “some” projections through time
1 2 3 4 5 6 7 8 9 ….
K-space
2. Calculate composite imagesSum of “some” projections through time
1 2 3 4 5 6 7 8 9 ….
K-space
Sliding CompositeSliding Composite
2. Calculate composite imagesSum of “some” projections through time
1 2 3 4 5 6 7 8 9 ….
K-space
Sliding CompositeSliding Composite
All-inclusive versus Sliding CompositeAll-inclusive versus Sliding Composite
All-inclusive Composite+ High SNR
+ Few streak artifacts
Good for nearly homogeneous temporal behaviour
– In CE-MRA: contains early and late filling vessels
The SNR of the composite dictates the SNR in thetime-resolved images
Sliding Composite– Lower SNR– More streak artifacts
+ Better separates early and late filling vessels
k-space projections
Image-space projections
N21
1D FT 1D FT 1D FT 1D FT
N21
Time frames withinterleaved angular projections
time
Filtered backproject.
Composite image
or sum,regrid, and FT
Multiply
HYPR time frame N
Radon + Unfiltered backprojection
P/Pc
PPc
Sum over all projections
H C . ppci
Unfiltered backproject.
BackprojectionBackprojection
k-space projections
Image-space projections
N21
1D FT 1D FT 1D FT 1D FT
N21
Time frames withinterleaved angular projections
time
Filtered backproject.
Composite image
or sum,regrid, and FT
Multiply
HYPR time frame N
Radon + Unfiltered backprojection
P/Pc
PPc
Sum over all projections
Unfiltered backproject.
H C . ppci
Input (Truth)
Composite Weighting HYPR
× =
Schematic
Two Vessels – Horizontal – All-inclusiveTwo Vessels – Horizontal – All-inclusive
F. Korosec & Y. Wu
Input (Truth)
Composite Weighting HYPR
× =
Schematic
Wro
ng!
Two Vessels – Vertical – All-inclusiveTwo Vessels – Vertical – All-inclusive
F. Korosec & Y. Wu
More Projections per HYPR Time FrameMore Projections per HYPR Time Frame
HYPR
HYPR
HYPR
HYPR
Weighting
Weighting
Weighting
Weighting
1 Projection 4 Projections
2 Projections 8 Projections
F. Korosec & Y. Wu
Input Curves and Vessel LocationsInput Curves and Vessel Locations
Input Curves Vessel Locations
F. Korosec & Y. Wu
Composite Image #5Composite Image #5Composite
100 projections5 frames x 20proj/frame
Time Frame #5
Input Curves
Time frame #5
F. Korosec & Y. Wu
Composite Image #5Composite Image #5Composite
100 projections5 frames x 20proj/frame
Time Frame #11
Input Curves
Time frame #11
F. Korosec & Y. Wu
Time Curves – Input and HYPRTime Curves – Input and HYPR
Input HYPR
F. Korosec & Y. Wu
HYPR SimulationHYPR Simulation
Parameters– Gd-doped water injected in tube
– 2D Fourier acquisition @ 1 frame / s
– Generate k-space projections from images (Matlab)
– Simulate HYPR acquisition
– 32 projections per interleave
– 8 unique sets of interleaves• -> 256 angles sampled
– Composite image: moving window [-4 .. +3]
Simulation – Time Frame 5Simulation – Time Frame 5Original Undersampled
Composite HYPR
Simulation – Time Frame 9Simulation – Time Frame 9Original Undersampled
Composite HYPR
Comparison Videos: FootComparison Videos: Foot
Undersampled16 projections per time frame
T = 2.0 s
HYPR
T = 2.0 s
Comparison Videos: CalfsComparison Videos: Calfs
Undersampled16 projections per time frame
T = 2.1 s
HYPR
T = 2.1 s FOV = 48 cm, BW = 62.5 kHz, flip = 25 deg.
TR/TE = 5.2 / 1.1 msHYPR frame rate = 2.1 sComposite: sliding window (duration: 16*2 = 32s)
ApplicationsApplications
HYPR Applications– Dynamic Contrast-enhanced
MR Angiography– Quantitative Flow Imaging– Diffusion Tensor Imaging– MR and CT Perfusion Imaging– Cardiac Function
HYPR SummaryHYPR Summary
– Improves temporal resolution (also reduces total imaging time)
– Improves SNR by incorporation of a time averaged composite image
– Small number of projections are used to produce weighting images that are multiplied by high SNR composite image
– Composite image constrains backprojection to reduce streak artifacts
– Degree of achievable undersampling depends on
• sparsity
• spatio-temporal correlation
• acceptable error