Registration Case Library

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http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation

Registration Case Library

Main Mission: Make “Registration Life” easier.

Objectives:

•build a comprehensive library of registration case scenarios

•give users an educated starting point for their own individual registration problem

•avoid excessive repeats in a trial- and error parameter exploration

•educate user community about the particulars of Slicer-based registration

•educate user community about basics of image registration

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Call For Datasets"if you have a registration problem that is not yet covered in our library, send us your case: we will post it along with our best registration solution/strategy. If you agree to the posting of the anonymized image data, you get a free registration, the user community gets a new example case. Everybody wins.”

What We Will Do•seek the best possible registration obtainable with the most recent version of 3DSlicer

•post the anonymized image as a new case in our Slicer Registration Case Library

•post the exact workflow used to obtain the shown solution registration will be posted alongside the data as a guided step-by-step tutorial

•the parameters for successful registration will also be posted as a loadable custom "Registration Preset" file that you can load directly into Slicer and apply on your data

•if you can provide us with fiducial pairs or other criteria that define a good registration, we will use them in optimization efforts.

•the registration objective & background, main challenges and strategy recommendations will be posted

•an acknowledgment of your lab as the data source is posted, if desired with a link to your institution and/or related research papers

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Result Evaluation

• For most, registration is a preprocessing step, not a destination, hence evaluation interest will be chiefly in fast (qualitative) manner

• Hence “Visualization” is first-used method of choice. • exception: sensitivity analyses of pipelines.

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Result Visualization

1. Slicer View Toggle Button & Fade

toggle

fade

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2. Animated GIFs

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3. Color Overlay

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4. Checkerboard

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5. Subtraction/Ratio/Var Image

blendingmode

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6. Label Maps

Visualize Overlap viaHausdorff Distance Module

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7. Volume Rendering

dual rendering: GPU restrictions may apply

8. Surface Model Rendering

requires segmentation of each set

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Registration Parameters

Rigid - Affine

DOF: (3,6,7,9,12)

Multi-resolution: (2x, 4x, 8x, 16x)

Cost function: (MI, NC, MSq, IR)

Mask Image: (Labelmap)

Mask ROI Box: (ROI node)

Initialization: (none, image centers, moments)

Histogram Mask: (excl. intensity range)

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Quantitative Result Assessment

• Fiducial RMS

• ROI image similarity

• Segmentation Overlap

• Global Cost Function Result

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Documents

Registration Case Library