July 2010 Image Registration Techniques, Benchmarking, Strategy Surgical Planning Laboratory Center for Neurological Imaging July 2010 Lidwien Veugen Supervision.

Slides:



Advertisements
Similar presentations
VBM Voxel-based morphometry
Advertisements

Image Registration  Mapping of Evolution. Registration Goals Assume the correspondences are known Find such f() and g() such that the images are best.
Mutual Information Based Registration of Medical Images
NA-MIC National Alliance for Medical Image Computing Slicer3 Tutorial / Registration Library: Case 29 - DTI converting and aligning diffusion.
NA-MIC National Alliance for Medical Image Computing Slicer3 Tutorial / Registration Library: Case 03 - DTI aligning low-resolution diffusion.
Gordon Wright & Marie de Guzman 15 December 2010 Co-registration & Spatial Normalisation.
Medical Image Registration Kumar Rajamani. Registration Spatial transform that maps points from one image to corresponding points in another image.
Image Registration: Demons Algorithm JOJO
Nonrigid Registration
Xiaofen Zheng, Jayaram Udupa, Xinjian Chen Medical Image Processing Group Department of Radiology University of Pennsylvania Feb 10, 2008 (4:30 – 4:50pm)
Realigning and Unwarping MfD
Tuesday Seminar Deformable Image Registration
Registration of two scanned range images using k-d tree accelerated ICP algorithm By Xiaodong Yan Dec
Medical Image Registration Dept. of Biomedical Engineering Biomedical Image Analysis
Medical Imaging Mohammad Dawood Department of Computer Science University of Münster Germany.
Non-Rigid Registration. Why Non-Rigid Registration  In many applications a rigid transformation is sufficient. (Brain)  Other applications: Intra-subject:
CS CS 175 – Week 2 Processing Point Clouds Registration.
Yujun Guo Kent State University August PRESENTATION A Binarization Approach for CT-MR Registration Using Normalized Mutual Information.
Image Registration Narendhran Vijayakumar (Naren) 12/17/2007 Department of Electrical and Computer Engineering 1.
SPM+fMRI. K space K Space Mechanism of BOLD Functional MRI Brain activity Oxygen consumptionCerebral blood flow Oxyhemoglobin Deoxyhemoglobin Magnetic.
Medical Image Registration
Preprocessing II: Between Subjects John Ashburner Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London, UK.
Haskins fMRI Workshop Part I: Data Acquisition & Preprocessing.
FMRI Preprocessing John Ashburner. Contents *Preliminaries *Rigid-Body and Affine Transformations *Optimisation and Objective Functions *Transformations.
A Survey of Medical Image Registration J.B.Maintz,M.A Viergever Medical Image Analysis,1998.
NA-MIC National Alliance for Medical Image Computing Slicer3 Tutorial: Registration Library Case 19 Multi-stage registration for group.
Lecture 24: Cross-correlation and spectral analysis MP574.
Co-registration and Spatial Normalisation
National Alliance for Medical Image Computing Registration in Slicer3 Julien Jomier Kitware Inc.
Intersubject Surface Mapping with Nonrigid Registration for Neurosurgery Vishal Majithia Presented in partial fulfillment of the requirements for the Degree.
Quantitative Brain Structure Analysis on MR Images
Multimodal Interaction Dr. Mike Spann
CSci 6971: Image Registration Lecture 3: Images and Transformations March 1, 2005 Prof. Charlene Tsai.
Coregistration and Spatial Normalisation
Introduction EE 520: Image Analysis & Computer Vision.
Jan Kamenický Mariánská  We deal with medical images ◦ Different viewpoints - multiview ◦ Different times - multitemporal ◦ Different sensors.
A Novel Image Registration Pipeline for 3- D Reconstruction from Microscopy Images Kun Huang, PhD; Ashish Sharma, PhD; Lee Cooper, MS; Kun Huang, PhD;
Image Registration as an Optimization Problem. Overlaying two or more images of the same scene Image Registration.
Medical Image Analysis Image Registration Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
NA-MIC National Alliance for Medical Image Computing Registering Image Volumes in Slicer Steve Pieper.
Spatio-Temporal Free-Form Registration of Cardiac MR Image Sequences Antonios Perperidis s /02/2006.
Algorithms for Image Registration: Advanced Normalization Tools (ANTS) Brian Avants, Nick Tustison, Gang Song, James C. Gee Penn Image Computing and Science.
Conclusions The success rate of proposed method is higher than that of traditional MI MI based on GVFI is robust to noise GVFI based on f1 performs better.
Image Registration with Hierarchical B-Splines Z. Xie and G. Farin.
Statistical Parametric Mapping Lecture 11 - Chapter 13 Head motion and correction Textbook: Functional MRI an introduction to methods, Peter Jezzard, Paul.
1 Multimodal Registration Clinic “All Things Registered” I.Theory & Tool Overview II.Live.
NA-MIC National Alliance for Medical Image Computing Slicer3 Tutorial Nonrigid Atlas Registration Dominik Meier, Ron Kikinis February.
MultiModality Registration Using Hilbert-Schmidt Estimators By: Srinivas Peddi Computer Integrated Surgery II April 6 th, 2001.
Comparison of Image Registration Methods David Grimm Joseph Handfield Mahnaz Mohammadi Yushan Zhu March 18, 2004.
Introduction to Medical Imaging Regis Introduction to Medical Imaging Registration Alexandre Kassel Course
Ki-Chang Kwak. Average Brain Templates Used for Registration.
A 2D/3D correspondence building method for reconstruction of a 3D bone surface model Longwei Fang
NA-MIC National Alliance for Medical Image Computing Slicer3 Tutorial: Registration Library Case 08 Serial PET-CT Dominik Meier, Ron.
CSE 554 Lecture 8: Alignment
CENG 789 – Digital Geometry Processing 08- Rigid-Body Alignment
Group Averaging of fMRI Data
University of Ioannina
Fereshteh S. Bashiri Advisors: Zeyun Yu, Roshan M. D’souza
Dominik Meier, Ron Kikinis Sept. 2010
CT-based surrogates of pulmonary ventilation in lung cancer:
Mutual Information Based Registration of Medical Images
Multi-modality image registration using mutual information based on gradient vector flow Yujun Guo May 1,2006.
Computational Neuroanatomy for Dummies
MPHY8149: Image Registration
CSE 554 Lecture 10: Extrinsic Deformations
Image Registration 박성진.
Brain Registration and Multipurpose Postprocessing
Anatomical Measures John Ashburner
Image Registration  Mapping of Evolution
Registration Foundations
Presentation transcript:

July 2010 Image Registration Techniques, Benchmarking, Strategy Surgical Planning Laboratory Center for Neurological Imaging July 2010 Lidwien Veugen Supervision by Dominik S. Meier, PhD

July 2010 Contents - Introduction Image Registration, 3D Slicer - Theory Transformations, Similarity Metrics - Benchmarking Time/Memory vs Iterations/Samples - Registration Strategies - Registration Cases Brains, PET-CT, EMPIRE10

July 2010 Introduction Image Registration: - Process of matching multiple image by optimal transformation 3D Slicer: - Free Open Source Software program - Huge amount of Registration Modules/Methods

July D Slicer

July 2010 Theory Transformations Mapping points from original spatial coordinates to new spatial coordinates: (u,v,w) = T{(x,y,z)} Rigid Transform Rotation + Translation (u,v,w) = R*(x,y,z) + t 6 DOF Affine Transform Rotation + Translation + Scaling + Shear (u,v,w) = A*(x,y,z) + t 12 DOF

July 2010 Theory Transformations BSpline Spline: function defined piecewice by polynomials Cubic grid of moving control points describes deformation 3 DOF per control point BrainsDemonWarp Thirion + Maxwell: Image registration based on optical flow Boundaries are semi-permeable membranes with effectors/demons High DOF

July 2010 Theory Transformation BRAINSFit - Rigid, Affine, BSpline - Mutual Information - 6/12/higher DOF Expert Automated Registration - Pipelines: Rigid, Affine, BSpline - MutualInfo + MeanSqE + NormCorr - 6/12/higher DOF Plastimatch - Pipeline: Rigid/Affine, BSpline(s) - MutualInfo + MeanSqE - 6/12/higher DOF

July 2010 Theory Similarity Metrics Tells to what degree two images are aligned Based on: intensity, landmarks Mutual Information - Measure of the statistical dependence between two random variables: Information about image A that is shared by B and vice versa - Maximized if the two images are spatially aligned - Based on Shannon entropy H: measure of intensity prediction - Fast measure

July 2010 Theory Similarity Metrics Normalized Cross Correlation - Based on cross correlation - Maximized if the two images are spatially aligned - Intra-patient + Intra-modality - Time consuming Mean Squared Difference - Summation of the squared differences between two images - Minimized if the two images are spatially aligned - Intra-patient + Intra-modality - Time consuming

July 2010 Theory Optimization Optimization algorithm: Tries to find a global solution to an energy function - Gradient descent - Statistical optimization - Line search algorithm - One-plus-one evolutionary - Multiresolution

July 2010 Registration Accuracy Subtraction Fixed - Moving Registered Checkerboard Alternating squares from fixed and moving image

July 2010 Benchmarking Effect of the amount of iterations and samples on CPU time and memory for different modules/methods Rigid: 4 methods Affine: 7 methods BSpline: 2 methods Default: Samples = 10000, Iterations = 200 Iterations: 11 values, ranging from 25 to Samples: 20 values, ranging from 25 to

July 2010 Benchmarking Fast results with: SPL Dell Linux Cluster of 50 computers  Creates log-file of every job  Matlab

July 2010 Benchmarking Results

July 2010 Benchmarking Results Time vs Iterations - Not much effect - Increase: Brainsfit, Exp.Autom. - Decrease: Multiresolution - Constant: BSpline modules Time vs Samples - Increase: All modules, except: - Decrease: Exp.Autom. NormCr - 10  800 seconds (0.003%  13%) - Rigid < Affine < BSpline Memory vs Iterations Not much effect - Increase: All modules, except: - Constant: Brainsfit, Multires - Lowest: 2MB; Highest: 155MB Memory vs Samples - Increase: All modules, except: - Decrease: Exp.Autom. NormCr - Lowest: Rigid (10-100MB) - Highest: BSpline ( MB)

July 2010 Registration Cases Slicer Registration Case Library

July 2010 Registration Strategies Choice of Transformation Modality, Subject, Inter/Intra, Part of body Choice of Similarity Metric Inter/Intra, Time/Accuracy Focus Time/Accuracy/Memory  Sim.metric/iterations/samples Fixed Image Resolution/Contrast

July 2010 Registration Cases EMPIRE10 Evaluation of Methods for Pulmonary Image Registration 2010 = Challenge of International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 20 Pairs of chest CT scans: variety scanners, voxel size, breathing phase Evaluation: Lung boundaries, Fissures, Landmarks, Singularities

July 2010 Registration Cases

July 2010 Registration Cases EMPIRE10 - Registration Pipeline: 1.Fast Affine Registration 2.Fast nonrigid Bspline Registration (grid = 7) 3.Fast nonrigid Bspline Registration (grid = 12) 4.Fast nonrigid Bspline Registration (grid = 17) 5.BrainsDemonWarp

July 2010 Registration Cases EMPIRE10 - Quality Registration Subtraction + MATLAB help in evaluation registration: Median pixelvalue of absolute subtracted image: the lower the better

July 2010 Registration Cases fMRI alignment to structural scan (T1) - Fixed: T1 scan (anatomical reference) - Moving: fMRI scan - Problem: Low tissue contrast, acquisition related distortions Registration based on ventricles only

July 2010 Registration Cases Aging Mobility Study 2 year follow-up - 2 Exams at different times: nonrigid (BSpline) - Incorrect axis-info - Fixed: MPRAGE - Moving: T2, FLAIR

July 2010 Registration Cases Inter-subject Normal brain MIDASexample - Fixed: T1 - Moving: T2, MRA - Interpatient: non-rigid (BSpline)

July 2010 Registration Cases PET-CT Fusion 2 - Intersubject: nonrigid BSpline, BrainsDemonWarp - Fixed: CT-scan patient 1 - Moving: CT-scan patient 2 - Problem: Different posture

July 2010 Registration Cases Brain Intersubject PNL-XNAT - Intersubject: nonrigid (BSpline) - Problems with (too much) BSpline

July 2010 Registration Cases Brain Intersubject OrientationFlx - Intersubject: nonrigid (BSpline) - Fixed: T1 - Moving: T2 - Problems with nested transformations

July Fixed: Colin27 - Moving: Patient - Orientation! Registration Cases Brain Intersubject Dartmouth Montreal Neurological Institue: Colin27 for group analysis in MRI studies

July 2010 Acknowledgements Finally, I would like to thank everybody from CNI for the possibility to do an internship here! Thanks to my supervisor Dominik S. Meier, PhD

July 2010 Questions? ?