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DtiStudio
Susumu MoriJohns Hopkins University
Overall direction of DTI research
DWIs
Smaller b (<1,200), fewer directions (<30), 2mm, 5 min
Larger b (> 3,000), more directions (>60), lower resolution, longer time
Tensor calculation
High Angular-Resolution Diffusion Imaging
Overall direction of DTI research
DWIs
Smaller b (<1,200), fewer directions (<30), 2mm, 5 min
Tensor calculation
Overall direction of DTI research
DWIs
Smaller b (<1,200), fewer directions (<30), 2mm, 5 min
Tensor calculation
• Automated and quantitative quality control pipeline• Fully automated cloud-based web-based pipeline• Integration of image quantification schemes• Dynamic programming for fiber tracking• Automated fiber tracking
DtiStudio
How DTI studies could go wrong
Motion
Eddy-current distortion
Outlier pixels (dropout, ghost)
Registration
Slice rejectionPixel rejection
Motion monitoringEddy current monitoring
Motion monitoring
Non-physiological motion
20 40 60 80 100 120 140 160-3
-2
-1
0
1
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Rep 1 Rep 2 Rep 3 Rep 4 Rep 5
XMR-SNR-test-AH: dtRegVoltranslationy
DW
I tansl
atio
ny:
mm
# of DWI20 40 60 80 100 120 140 160
0
0.5
1
1.5
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2.5
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3.5
4
Rep 1 Rep 2 Rep 3 Rep 4 Rep 5
XMR-SNR-test-AH: cumulateddtrotationmetric
DW
I rota
tionm
etric
: degre
e
# of DWI
Eddy current monitoring
Importance of tensor fitting quality
Images that CAN’T be registered
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
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4.5
apparent translation: mm
abso
lute
fitti
ng e
rror b
efor
e re
gist
ratio
n:
0 0.5 1 1.5 2 2.5 30
0.5
1
1.5
2
2.5
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3.5
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4.5
apparent translation: mm
abso
lute
fitti
ng e
rror a
fter r
egis
tratio
n:
A B
C
D E
Outlier rejection
50 100 150
50
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150
0
20
40
60
80
50 100 150
50
100
150
0
20
40
60
80
50 100 150
50
100
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a b c d
e f g h
i j k l
Original image
After registrationArtifact masked
Select subject to show results
Population report Matlab code
MriStudio Pipeline
DWIs
DtiStudio
DiffeoMapRoiEditor
254 structures
Example of multi-modal analysis
Automated pipelineRead DICOM data
Tensor calculation QC report
Scalar map calculation Save images
Skull-strip
Linear registration
Atlas-based parcellation
Save images
Save tables
Database solution
Initiate image analysis pipeline
Specify the data for analysis
Calculation startsResults become available
Fiber tracking: path-generation
Automated parcellation of the brain
Fiber tracking: path-generation
Overall direction of DTI research
DWIs
Smaller b (<1,200), fewer directions (<30), 2mm, 5 min
Tensor calculation
• Automated and quantitative quality control pipeline• Fully automated cloud-based web-based pipeline• Integration of image quantification schemes• Dynamic programming for fiber tracking• Automated fiber tracking
Acknowledgment• Program development
– Hangyi Jiang– Xin Li
• Server implementation– Anthony Kolasny– Can Ceritoglu– Bill Schneider
• Quantification module– Michael Miller– Yue Li– Xiaoying Tang
• Atlas generation– Kenichi Oishi– Anderia Faria