Difference between revisions of "Non-rigid MR-CT Image Registration"

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[[Image:nonrigid.png |NON-RIGID MR-CT IMAGE REGISTRATION: This tutorial demonstrates how to perform MR-CT and CT-CT non-rigid registrations. In a cryoablation of liver case, we can see a tumor on pre-operated MRI. However, on intra-operated CT image, the tumor can not be seen though cryoproves can be seen. By using non-rigid MR-CT image registration, we can check the distance between the cryoprobes and tumor as shown the figure.  |500px|thumb|right]]
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= Non-rigid Registration of Pre-procedural MRI and Intra-procedural CT for CT-guided Cryoablation Therapy of Liver Cancer Tutorial=
  
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[[Image:nonrigid-cryo.png |PROCESS OF IMAGE REGISTRATION IN CRYOABLATION OF LIVER CASE: Registration process between MR and CT images in cryoablation of a liver case is shown. (1) A transformation matrix T1 was used to deform the pre-procedure contrast enhanced MR image on to the planning CT image. (2) T2 was used to deform the planning CT image on to the intra procedure CT image with cryoprobes. (3) The matrix T2 was combined with T1 to deform the MR image onto the CT image with cryoprobe. |500px|thumb|right]]  
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==Overview==
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This tutorial demonstrates how to perform a pre-operated contrast enhanced MR image to intra-procedure CT image non-rigid registration.
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The case study is CT-guided liver tumor cryoablation.
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[[Image:nonrigid.png |NON-RIGID MR-CT IMAGE REGISTRATION: As shown in this figure, non-rigid registration can enhance visualization of tumor margin and location. |500px|thumb|right]]
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=== Clinical significants ===
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*Non-rigid registrations desirable to compensate for liver deformation caused by patient positioning, respiratory motion, and interventional manipulation.
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*A multi-modality non-rigid registration method can enhance visualization of tumor margins and location during the planning, targeting, and monitoring phases of CT imaging-guided cryoablation procedure.
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[[Image:registrationStrategy.png |REGISTRATION STRATEGY / ROADMAP:  |500px|thumb|right]]  
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=== Tutorial Topics / Targets ===
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* Slicer Modules Used:
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** N4ITKBiasField Correction
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** Editor
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** BRAINSFitIGT Registration
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* Image Processing Tasks Performed:
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** Intensity non-uniformly correction
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** Mask generation / segmentation
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** Inter-modality non-rigid image registration
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* Image Data Used:
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** Pre-operative abdominal MR with surface coil, showing liver
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** Planning and Intra-operative CT with cryo-probe
  
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= Non-rigid MR-CT Image Registration Tutorial=
 
  
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==Overview==
 
  
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This tutorial demonstrates how to perform MR-CT and Ct-CT non-rigid image registrations.
 
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The case study is liver tumor cryoablation.
 
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In this tutorial, the three steps are performed as shown the figure on right side.
 
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*(1) In MR-planning CT image registration, we can obtain the deformed MR image and the Bspline transformation matrix T1 by using pre-procedure contrast enhanced MRI and mask image.
 
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*(2) In plannning CT-intraprocedure CT image registration, we can obtain the deformed planning CT image and the Bspline transformation matrix T2.
 
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*(3) In MR-intraprocedure CT image registration, we can obtain the deformed MR image by using T1 and T2 BSpline transformation matrices.
 
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For non-rigid registration, BRAINSFitIGT and BRAINSResamle modules are used.
 
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In this tutorial, we will show that 3D Slicer with BRAINSFitIGT module allows performing non-rigid image registration and BRAINSResample module allows performing non-rigid image deformation using Bspline transform matrix.
 
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We also shows in cryoablation of liver case, the distance between cryoprobe on CT image and tumor on MR image can be confirmed easily by using the non-rigid MR-CT image registration.
 
  
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=== Overview ===
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* This tutorial will go through the following steps (in order):
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* Preprocessing
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** MRI mask generation
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** CT mask generation
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** MRI Bias Field Intensity Correction
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* Registration
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** MRI-CT(#1) non-rigid registration
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** CT(#1)-CT(#2) affine registration
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** Resampling & Fusion
  
 
==Tutorials==
 
==Tutorials==
  
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'''Non-rigid MR-CT Image Registration Module tutorial''' : to perform MR-CT and CT-CT image registration [[Media:ShapeAnalysisModule-Tutorial.ppt|‏ [ppt]]][[Media:ShapeAnalysisModule-Tutorial.pdf|‏ [pdf]]]
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'''Non-rigid Registration of Pre-procedural MRI and Intra-procedural CT for CT-guided Cryoablation Therapy of Liver Cancer Tutorial'''  [[Media:Non-rigid_Registration_of_Pre-procedural_MRI_and_Intra-procedural_CT_for_CT-guided_Cryoablation_Therapy_of_Liver_Cancer_TutorialContestSummer2011.ppt‎|‏ [ppt]]][[Media:Non-rigid_Registration_of_Pre-procedural_MRI_and_Intra-procedural_CT_for_CT-guided_Cryoablation_Therapy_of_Liver_Cancer_TutorialContestSummer2011.pdf|‏ [pdf]]]
  
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==Tutorial materials==
  
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==Tutorial materials==
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'''Material data''':
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*[[Media:Non-rigid_MR_CT_Image_RegistrationTutorialData_TutorialContestSummer2011.tar.gz| Non-rigid_MR_CT_Image_RegistrationTutorialData_TutorialContestSummer2011.tar.gz ]]
  
  
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'''ShapeAnalysisModule data ''':
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==Reference==  
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*[http://www.nitrc.org/docman/index.php?group_id=308&selected_doc_group_id=760&language_id=1#folder Link to NITRC ]
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This method is based on the registration workflow originally developed for prostate MRI registration as follows.
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* or directly here :[[Media:ShapeAnalysisModuleTutorialData_TutorialContestSummer2011.zip|‏ ShapeAnalysisModuleTutorialData_TutorialContestSummer2011.zip]]
 
  
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A. Fedorov, K. Tuncali, F. Fennessy, J. Tokuda, N. Hata, S.W. Wells, R. Kikinis, and C.M. Tempany. Hierarchical Image Registration for Improved Sampling during 3T MRI-guided Transperineal Targeted Prostate Biopsy, ISMRM 2011
  
 
==People==
 
==People==

Latest revision as of 21:52, 22 June 2011

Home < Non-rigid MR-CT Image Registration

Non-rigid Registration of Pre-procedural MRI and Intra-procedural CT for CT-guided Cryoablation Therapy of Liver Cancer Tutorial

Overview

This tutorial demonstrates how to perform a pre-operated contrast enhanced MR image to intra-procedure CT image non-rigid registration. The case study is CT-guided liver tumor cryoablation.

NON-RIGID MR-CT IMAGE REGISTRATION: As shown in this figure, non-rigid registration can enhance visualization of tumor margin and location.

Clinical significants

  • Non-rigid registrations desirable to compensate for liver deformation caused by patient positioning, respiratory motion, and interventional manipulation.
  • A multi-modality non-rigid registration method can enhance visualization of tumor margins and location during the planning, targeting, and monitoring phases of CT imaging-guided cryoablation procedure.
REGISTRATION STRATEGY / ROADMAP:

Tutorial Topics / Targets

  • Slicer Modules Used:
    • N4ITKBiasField Correction
    • Editor
    • BRAINSFitIGT Registration
  • Image Processing Tasks Performed:
    • Intensity non-uniformly correction
    • Mask generation / segmentation
    • Inter-modality non-rigid image registration
  • Image Data Used:
    • Pre-operative abdominal MR with surface coil, showing liver
    • Planning and Intra-operative CT with cryo-probe



Overview

  • This tutorial will go through the following steps (in order):
  • Preprocessing
    • MRI mask generation
    • CT mask generation
    • MRI Bias Field Intensity Correction
  • Registration
    • MRI-CT(#1) non-rigid registration
    • CT(#1)-CT(#2) affine registration
    • Resampling & Fusion

Tutorials

Non-rigid Registration of Pre-procedural MRI and Intra-procedural CT for CT-guided Cryoablation Therapy of Liver Cancer Tutorial ‏ [ppt]‏ [pdf]

Tutorial materials

Material data:


Reference

This method is based on the registration workflow originally developed for prostate MRI registration as follows.

A. Fedorov, K. Tuncali, F. Fennessy, J. Tokuda, N. Hata, S.W. Wells, R. Kikinis, and C.M. Tempany. Hierarchical Image Registration for Improved Sampling during 3T MRI-guided Transperineal Targeted Prostate Biopsy, ISMRM 2011

People

Atsushi Yamada, Ph.D. (Research Associate, Brigham and Women's Hospital and Harvard Medical School)
Dominik S. Meier, Ph.D. (Assistant Professor, Brigham and Women's Hospital and Harvard Medical School)
Nobuhiko Hata, Ph.D. (Associate Professor, Brigham and Women's Hospital and Harvard Medical School)


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