Diffusion Imaging Quality Control with DTIPrep

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NA-MIC National Alliance for Medical Image Computing http://na-mic.org Diffusion Imaging Quality Control with DTIPrep Martin Styner, PhD University of North Carolina Neuro Image Research and Analysis Lab

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Diffusion Imaging Quality Control with DTIPrep. Martin Styner, PhD University of North Carolina Neuro Image Research and Analysis Lab. DWI/DTI QC. This tutorial teaches you how to do quality control (QC) of diffusion images both for DTI as well as other diffusion models (such as HARDI) - PowerPoint PPT Presentation

Transcript of Diffusion Imaging Quality Control with DTIPrep

Page 1: Diffusion Imaging Quality Control with  DTIPrep

NA-MICNational Alliance for Medical Image Computing http://na-mic.org

Diffusion Imaging Quality Control with DTIPrep

Martin Styner, PhD

University of North CarolinaNeuro Image Research and Analysis Lab

Page 2: Diffusion Imaging Quality Control with  DTIPrep

National Alliance for Medical Image Computing http://na-mic.org

Slide 2

DWI/DTI QC

• This tutorial teaches you how to do quality control (QC) of diffusion images both for DTI as well as other diffusion models (such as HARDI)

• DWI/DTI QC is performed with the NA-MIC tool DTIPrep– Can be called within Slicer– Also stand-alone tool

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National Alliance for Medical Image Computing http://na-mic.org

Slide 3

Dataset

For this tutorial you will need some DWI/DTI data files that can be found on this link :http://hdl.handle.net/1926/1759

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Diffusion Artifacts

Diffusion images are sensitive to a number of artifacts• Motion• Eddy-current distortions• Noise/SNR issues• Vibrational artifacts• Venetian blind artifacts• “unknown”…Bad DWI’s are removed

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National Alliance for Medical Image Computing http://na-mic.org

Slide 5

Outline

• DTI QC pipeline1. Start DTIPrep2. Load DWI dataset

• Check DWI & gradient info3. Protocol for Automatic QC4. Run Automatic QC on DWI5. Final Visual QC6. Check DTI glyphs in Slicer

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Slide 6

DTIPrep• Stand alone/Slicer module• NITRC page: http://www.nitrc.org/projects/dtiprep/

– Additional manual on NITRC page• Protocol based QC

– Protocol defines all the parameters• Automatic report creation• Embed/Cropping of DWI data

– Same size images => simplifies processing• Visualization of gradient scheme

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Slide 7

Start Slicer 4

Linux/Mac users :Launch the Slicerexecutable located inthe Slicer4 directory

Windows users :Select StartAll ProgramsSlicer4.0.1SlicerOr launch the Slicer executable from Slicer4 directory

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Slide 8

Start DTIPrep within Slicer

1. Select DTIPrep– Diffusion category

2. Create new Commandline module

3. Click “Apply”4. DTIPrep starts up

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Slide 9

DTIPrep Main Window

Toolbar

Info Window

DWI Viewers

3D Viewer

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Slide 10

Load DWI image

• Click NRRD icon• File Dialog

– Select your DWI– DTI/DTIPrep_JB.nhdr

• “Open”• Done with loading

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Slide 11

DWI info

DetailedDWIInfo

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National Alliance for Medical Image Computing http://na-mic.org

Slide 12

Gradient info in 3D

Displays gradient scheme on unit sphere(F = File)

- Check for uniformity

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National Alliance for Medical Image Computing http://na-mic.org

Slide 13

Protocol in DTIPrep

• Protocol defines parameters• Use default parameters or load prior

parameter set• Select “Protocol” tab• Select “Default”• Detailed parameters

– See manual on NITRC

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National Alliance for Medical Image Computing http://na-mic.org

Slide 14

Run QC• Select “RunByProtocol”

– Runs for a few minutes (5-15)• Checks:1. Image dimensions2. Gradients directions3. Intensity changes across slices4. Excessive motion across slices5. motion and eddy current

correction6. Residual motion detection7. Optional noise removal

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Slide 15

QC Result

• Loads QC’ed DWI when finished

• Detailed reporting• Directions after

motion correction• Reasons for

exclusion

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Slide 16

Visual QC & Save

• Double click on “VC_Status”

• Option to include or exclude

• Often unnecessary

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Slide 17

Conclusion

• DTI QC is a must• DTIPrep & Slicer provide

comprehensive QC• This tutorial guided you through the

“default” use of DTIPrep• Future: Better Slicer integration,

directional artifacts detection & correction (Farzinfar et al, ISBI 2012)

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Slide 18

Acknowledgment

• National Alliance for Medical Image ComputingNIH U54EB005149

• UNC: Mahshid Farzinfar, Zhexing Liu, Jean-Baptiste Berger, Clement Vachet, Cheryl Dietrich, Rachel Smith, Eric Maltbie, Yundi Shi, Aditya Gupta

• Utah: Guido Gerig, Sylvain Gouttard• Iowa: Hans Johnson, Joy Matsui• Liu, Z., et al. (2010). Quality control of diffusion weighted

images. Proceedings of SPIE, 7628(1), 76280J.