07th of January, 2014 Tuesday SeminarDeformable Image Registration HyunSeok Lee email@example.com
Contents • What is Image Registration? • Deformable Image Registration • Basic concept • Algorithm • Products • Open source • Debates about dose deform • 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
IR – Affine Transformation • Rotation • Translation • Scale • Shear • No more preservation of lengths and angles • Parallel lines are preserved
IR – Perspective Transformation • (xo, yo, zo) world coordinates • (xi, yi) image coordinates
IR – Projective Transformation • (xp, yp) Plane Coordinates • (xi, yi) Image Coordinates • 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 – 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 • Adaptive re-contouring • 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 • Mirada Medical • 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 • Adaptive therapy
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 • 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 • Deformable Image Registration and Adaptive Radiotherapy • It contains well implemented DIR algorithms and the essential functions for ART applications. • Implemented in MATLAB • Need CERR • https://code.google.com/p/dirart/
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.
Task Group No. 132 • Use of Image Registration and Fusion Algorithms and Techniques in Radiotherapy • Emphasis the importance of acceptance testing, including end-to-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.
DIR – Algorithm • Deformation Model
DIR – Algorithm • Matching Criteria (Objective Function)
DIR – Algorithm • Optimization Method