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![Page 1: NA-MIC National Alliance for Medical Image Computing Process-, Work-Flow in Medical Image Processing Guido Gerig .](https://reader035.fdocuments.us/reader035/viewer/2022062518/5697bf751a28abf838c801e0/html5/thumbnails/1.jpg)
NA-MICNational Alliance for Medical Image Computing http://na-mic.org
Process-, Work-Flow in Medical Image Processing
Guido Gerig
http://na-mic.org
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National Alliance for Medical Image Computing http://na-mic.org
Need for Process Flow
• Image Processing and Analysis: – Sequence of processing steps (readers, filters,
mappers, writers, visualization)– Clinical studies: between 30 and x00 datasets– Research: Prototyping Environment
• Process Flow System:– Fully automated (batch) and/or user-guided– Guides user through processing steps– Improved reliability and efficiency– Relieves user from repetitive tasks– Simplified sharing of processing sequences
• Process Flow System: Beyond Script Files (≠UNIX script/PERL/Python)
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National Alliance for Medical Image Computing http://na-mic.org
Example: User-Guided 3-D Level-Set Segmentation (SNAP)
• 3D Snake Segmentation:– Preprocessing (features)– Initialization– Post-editing– User-guidance
• Challenge: Use by non-experts
• Tool: SNAP-ITK (Yushkevich, Ho, Gerig) 5years Project
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National Alliance for Medical Image Computing http://na-mic.org
Level Set Segmentation Pipeline• Preprocessing• Initialization• Segmentation
A wizard guides the user through the segmentation process
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National Alliance for Medical Image Computing http://na-mic.org
ITK-SNAP Tour: Preprocessing
Region competition
stopping criterion(thresholding)
Intensity edgestopping criterion
-1
1
0
0
1
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National Alliance for Medical Image Computing http://na-mic.org
ITK-SNAP Tour: Initialization
• Spherical ‘bubbles’ or a coarse manual segmentation are used to initialize the level set
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National Alliance for Medical Image Computing http://na-mic.org
ITK-SNAP Tour: Parameters
• Different user interfaces:– Intuitive mode– Mathematical mode
• Preview of the forces acting on the level set
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National Alliance for Medical Image Computing http://na-mic.org
ITK-SNAP Tour: Segmentation
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National Alliance for Medical Image Computing http://na-mic.org
Example: EMS-ITK: Atlas-based brain MRI Segmentation
T1 T2 Tissue Cortex
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National Alliance for Medical Image Computing http://na-mic.org
Example: Hippocampus Shape Analysis Workflow
MRI Reformat Manual Landmarking
Gray-value Normalization
Hippocampus Segmentationvia Model Deformation
SphericalParameterization
SPHARM-PDM Shape
QCShape &Corresp.
Alignment& Scaling
Feature Computatione.g. Parcellation orDifference to Model
PriorModels
QC of Features & Statistical Results
Statistical AnalysisOf Features
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National Alliance for Medical Image Computing http://na-mic.org
Example: DTI Analysis in large clinical study (N>100)
• Co-registration of DTI
• Registration of DTI of each subject with:
• structural MRI
• segmentation maps
• lobe parcellation
• user-defined ROIs
• Statistical analysis per ROI
Group 1
Group 2
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National Alliance for Medical Image Computing http://na-mic.org
DTI processing pipeline4 DTI shots (.dcm)
4 DTI shots (.hdr)
Average DTI (.gipl)
FA/ADC maps (Gipl) Tensor field
Average DTI (GE format)
ROI and Lobe analysis Fiber Tracking analysis
Analysis using Imagine Using the FiberTracking tool
TensorCalc
gipl2GE
dcm2hdr
DTIChecker
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National Alliance for Medical Image Computing http://na-mic.org
DTI processing pipeline (ctd.)
FA/ADC maps
Data FusionLinear and nonlinear
registration
Writing Statistics
sMRI (T1/T2/PD)EM-Segmentation
ROIs
Co-registration
ROI and Lobe Analysis
Brain Lobe AtlasMRI atlas template
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National Alliance for Medical Image Computing http://na-mic.org
UNC Solution: IMAGINE(Matthieu Jomier)
Download: http://www.ia.unc.edu/dev
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National Alliance for Medical Image Computing http://na-mic.org
UNC IMAGINE
Imagine can generate Graphic User Interface automatically. Here, an example demonstrating the GUI generation for a recursive Gaussian filter.
• Cross-platform• GUI-based visual programming
environment• Command line applications
integration: Add your own modules
• Full integration ITK/vtk• Modules executed as thread • Memory manager:
allocate/disallocate mem.• Visual feedback/log file• Generates Source code (C++)
and makefile (Dyoxygen document.)
• Generates stand-alone cross-platform software with GUI
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National Alliance for Medical Image Computing http://na-mic.org
“Imagine” & “Batchmake”(Matthieu & Julien Jomier)
Parallel processing with BatchMake interface and script generation. With Batchmake, you can follow progress of your pipeline online
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National Alliance for Medical Image Computing http://na-mic.org
Demonstration Imagine 2
Toy Example: Data Fusion:
• Registration of DTI to sMRI:– Registration T1 and T2/PD– Registration of baseline DTI-0 to T2
(linear, nonlinear)– Use transformation to register FA/ADC to
T1/T2/PD
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National Alliance for Medical Image Computing http://na-mic.org
Discussion• Process Flow Architecture significantly improves efficiency of
research / exchange / “time to market” / large-scale studies• Experience at UNC: Since introduction in ‘04, the ITK-based
ProcessFlow environment has become standard tool (backbone) • NA-MIC: Four uses:
1. Process flow in dedicated tasks (level-set segmentation, DTI processing, shape analysis, segmentation, etc.)
2. Research environment to facilitate prototyping/ exchange/ comparison: Facilitates transfer of research tools to Core 2
3. Clinical studies Core 3: • Process flow systems to set-up a proc. system for individual tasks• Run Batch jobs on large clinical studies → parallel/grid computing• Verify results via qualitative visualization
4. Training/Dissemination Core 5: Process flow systems with visual feedback are excellent for teaching of methodology and tools
• Architectures:LONI Pipeline / AVS / SCIRun / UNC Imagine-1 and 2 / MevisLab / ….
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National Alliance for Medical Image Computing http://na-mic.org
Criteria
• ITK- and NA-MIC toolkit users don’t need to program, does not require advanced programming skills
• Cross-platform• Pipeline processing and visual programming environment• Easy integration, e.g. command-line integration of own
modules• Facilitates tests/comparison/exchange even of complex
software and whole systems• GUI generation, e.g. creation of stand-alone cross-platform
software from Pipeline• Parallel Processing / Script Generation• Clinical studies: Multi-data processing• Desirable for clinical studies: Visual programming language
structures like “for loop”, “if… then … else” and “do… while” functions