NA-MIC National Alliance for Medical Image Computing Process-, Work-Flow in Medical Image...

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

Process-, Work-Flow in Medical Image Processing

Guido Gerig

http://na-mic.org

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)

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

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

ITK-SNAP Tour: Preprocessing

Region competition

stopping criterion(thresholding)

Intensity edgestopping criterion

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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

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

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

ITK-SNAP Tour: Segmentation

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

Example: EMS-ITK: Atlas-based brain MRI Segmentation

T1 T2 Tissue Cortex

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

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

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

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

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

UNC Solution: IMAGINE(Matthieu Jomier)

Download: http://www.ia.unc.edu/dev

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

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

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

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 / ….

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