#### Transcript Deformable Image Registration

```07th of January, 2014
Tuesday Seminar
Deformable Image Registration
HyunSeok Lee
[email protected]
Contents
• What is Image Registration?
• Deformable Image Registration
–
–
–
–
Basic concept
Algorithm
Products
Open source
• TG132
What is image registration?
• Image registration is the process of transforming
different sets of data into one coordinate system.
• Registration is necessary in order to be able to
compare or integrate the data obtained from
different measurements.
IR – Rigid Transformation
• Rotation
• Translation
• Scale
 x1 

p1   
 y1 
 x2 

p2   
 y2 
 s1 

s1   
s2 
  

p 2  t  s R p1
 cos(  )  sin( )
R  

sin(

)
cos(

)


  t1 
t1   
t 2 
IR – Affine Transformation
•
•
•
•
Rotation
Translation
Scale
Shear
 x 2   a 13   a 11  a 12   x1 

  
 
y
a
a

a
y
22   1 
 2   23   21
– No more preservation of lengths and angles
– Parallel lines are preserved
IR – Perspective Transformation
• (xo, yo, zo)  world coordinates
• (xi, yi)  image coordinates
xi 
yi 
 fx o
zo  f
 fy o
zo  f
IR – Projective Transformation
• (xp, yp)  Plane Coordinates
• (xi, yi)  Image Coordinates
xi 
a11 x p  a12 y p  a13
a 31 x p  a 32 y p  a 33
yi 
a 21 x p  a 22 y p  a 23
a 31 x p  a 32 y p  a 33
• amn  coefficients from the equations of the
scene and the image planes
IR – Non-Rigid Transformation
• Needed for inter-subject registration and distortion
correction
• Non-linear
• Many different parameterizations
• Too much flexibility in the transformation can lead to
undesirable results
Deformable Image Registration
• Fundamental task in medical image processing
• Typical uses
– Longitudinal studies
• where temporal structural or anatomical changes are
investigated
– Matching of images from different patients
– Multi-modal registration
• matching images of the same patient acquired by different
imaging technologies
DIR – Algorithm
Deformation
Model
Matching
Criteria
(Objective
Function)
Optimization
Method
DIR – Products
• MIM Software Inc.
– Intensity-based free-form deformable registration
(VoxAlign)
–
–
–
–
–
PET/CT, MR/CT and 4D data sets deformable fusion
Atlas-based auto-contouring
Dose Accumulation
Deformable registration QA and reporting
Intensity-based Methods
• Intensity-based methods compare intensity patterns
in images via correlation metrics
• Sum of Squared Differences
• Normalized Cross-Correlation
• Mutual Information
Feature-based Methods
• Feature-based methods find correspondence
between image features such as points, lines, and
contours.
• Distance between corresponding points
• Similarity metric between feature values
– e.g. curvature-based registration
Free-form Deformations
• The general idea is to deform an image by manipulating
a regular grid of control points that are distributed across
the image at an arbitrary mesh resolution.
• Control points can be moved and the position of
individual pixels between the control points is computed
from the positions of surrounding control points.
DIR – Products
– Algorithms are based on published algorithms but
have been developed and optimized for particular RO
use-cases and modality combinations.
• e.g. CT-CT Optic Flow algorithm for PET/CT fusion
• e.g. CT-MR multi-modal algorithm for MRI fusion
– Multimodal deformable fusion
• CT, PET, PET/CT, MRI and CBCT, including 4D data sets
– Automatic contouring
• using an atlas or previously contoured case
– Dose warping and summation
DIR – Products
• Velocity Medical Solutions
– Multi-resolution modified basis spline algorithm
– Multi-modality demons algorithm
– Multi-modality deformable image registration
• CT, MR, PET and SPECT
– Atlas-based auto-contouring
– Treatment response assessment
DIR – Open Source
• ITK
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–
–
–
Insight Segmentation and Registration Toolkit
An extensive suite of software tools for image analysis
Implemented in C++
http://www.itk.org/itkindex.html
DIR – Open Source
• DIRART
– It contains well implemented DIR algorithms and the
essential functions for ART applications.
– Implemented in MATLAB
– Need CERR
DIR – Open Source
• Plastimatch
– For high performance volumetric registration of medical
images
– ITK-based algorithms for translation, rigid, affine,
demons, and B-spline registration
• Some methods are GPU and multicore accelerated
– Implemented in C++
– Plugin to 3D Slicer
• software package for visualization and medical image
computing
– http://plastimatch.org/
It is not appropriate to “deform” dose
along with DIR in ART
• For ART it is common to collect images of the patient throughout the
course of therapy.
• Because of temporal variations, it is usually necessary to deform
images so as to merge them into a cohesive dataset.
• This image registration makes the accurate merging of dose
distributions difficult.
• Some have decided to do this by “deforming” the dose distributions,
somewhat analogous to deforming the images, but it has been
suggested that this is not appropriate.
• Use of Image Registration and Fusion Algorithms and
– Emphasis the importance of acceptance testing, including endto-end tests, phantom tests, and clinical data tests.
– Describe the methods for validation and quality assurance of
image registration techniques.
– Describe techniques for patient specific validation.
Deformable PRESAGE® dosimeter
Discussion & Question