Efficient image registration for the analysis of different phases of - - PowerPoint PPT Presentation

Efficient image registration for the analysis of different phases of contrast-enhanced liver CT data

R.Verdú, J. Larrey, J.Morales

• F. López,V. Naranjo, M. Alcañiz, R.López,

Universitat Politècnica de València Universidad Politécnica de Cartagena. Unidad de Cirugía y Trasplante Hepático, Hospital La Fe, Valencia.

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Introduction Variational Image Registration Results Conclusions

Outline

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Introduction Variational Image Registration Results Conclusions

Outline

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Hepatocellular carcinoma is responsible for a large proportion of liver cancers. HepaPlan is a research and development project which is intended to assist the physician in the diagnosis, plan the treatment, track the evolution of the pathology over time. HepaPlan quantitatively classify the diseases with the highest degree of

• bjectivity

a 3-D view of the liver structure

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Introduction

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Tri-phase 3D CT under contrast agent injection. Adquisition at different times depending on the arrival time of the contrast agent. Three studies Non contrast phase. Arterial phase. Venous phase.

Introduction

No exact correspondence between the studies. Non Rigid Deformation method in the frequency domain At least two times faster than

• ther approaches in the spatial

domain

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

Introduction Variational Image Registration Results Conclusions

Outline

Variational Image Registration

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

2.Variational Image Registration

Registration : correspondence between two images, template T and reference R. Initial problem: arterial and portal phase WITHOUT registration (checkerboard). Representation of [- 50,350] H.U.

Variational Image Registration

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

2.Variational Image Registration

To minimize the joint energy functional

• measures the distance between the deformed template dataset

and the reference dataset: correlation ratio.

• is a regularizer and determines the smoothness of the

displacement field: diffusion term.

• weights the influence of the regularization.

Variational Image Registration

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

2.Variational Image Registration

Parseval’s theorem Minimization: Euler-Lagrange equation

Variational Image Registration

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• 1. Introducció
• 2. Variational Image Registration 3. Results 4. Conclusions
• 1. Introduction

2.Variational Image Registration

Iteration scheme

iterations

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Introduction Variational Image Registration Results Conclusions

Outline

Results

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• 1. Introducci ón 2. Variational Image Registration 3. Results 4. Conclusions

Three experiments: portal-arterial phase, arterial-non Contrast phase and portal-portal phase for registration. Registration parameters:

• 3. Results

Results

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• 1. Introducci ón 2. Variational Image Registration 3. Results 4. Conclusions

Three experiments: portal-arterial phase, arterial-non Contrast phase and portal-portal phase for registration. Registration parameters:

• 3. Results

EXPERIMENT #1

• Arterial phase and portal phase of the same patient (256 X 256 X 75 voxels)
• 30-60 seconds between the two acquisitions

Results

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• 1. Introducci ón 2. Variational Image Registration 3. Results 4. Conclusions

Three experiments: portal-arterial phase, arterial-non Contrast phase and portal-portal phase for registration. Registration parameters:

• 3. Results

EXPERIMENT #2

• non-contrast phase and arterial phase of the same patient (256 x 256 x 79 voxels)
• several minutes between the two acquisitions

Results

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• 1. Introducci ón 2. Variational Image Registration 3. Results 4. Conclusions

Three experiments: portal-arterial phase, arterial-non Contrast phase and portal-portal phase for registration. Registration parameters:

• 3. Results

EXPERIMENT #3

• two arterial phases of the same patient (256 x 256 x 67 voxels)
• several weeks between the two acquisitions

Results

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• 1. Introducci ón 2. Variational Image Registration 3. Results 4. Conclusions

Without registration With registration

• 3. Results

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Introduction Variational Image Registration Results Conclusions

Outline

Conclusions

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• 1. Introducci ón 2. Variational Image Registration 3. Results 4. Conclusions

Efficient implementation of variational image registration of liver CT data. The method is based on an efficient implementation of diffusion registration in frequency domain. If results are analysed, method achieves the ability and the accuracy to estimate the deformation existing in these 3D acquisitions (PSNR > 27 dB and CR>95%).

• 4. Conclusions

LabHuman 2012 – Thank you for your attention

Valery Naranjo LabHuman - Human Centered Technology Universitat Politècnica de València vnaranjo@labhuman.i3bh.es www.labhuman.com