Multimodal 3D Registration of Anatomic (MRI) and Functional (fMRI and PET) Intra-Patient Images of the Brain A.G. Legaz-Aparicio 1 , R. Verdú-Monedero 1 , J. Larrey-Ruiz 1 , . López-Mir 2 , V. Naranjo 2 , A. Bernabeu 3 F 1 Universidad Politécnica de Cartagena, Cartagena 30202, Spain 2 Universidad Politécnica de Valencia, I3BH LabHuman, 46022 Valencia, Spain 3 Inscanner S.L, Unidad de Resonancia Magnética, 03016 Alicante, Spain 6th International Work-conference on the Interplay between Natural and Artificial Computation - IWINAC 2015
Outline Introduction 1 Methodology 2 Results 3 Conclusions 4 Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 2 / 29
Outline Introduction 1 Methodology 2 Results 3 Conclusions 4 Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 3 / 29
Introduction. Image registration Image registration: process of finding the optimum geometrical transformation which relates corresponding points of two dataset. Geometrically, the image registration consist of aligning one of the datasets, known as the template set (T) with the other set, known as the reference set (R). The datasets can be taken at different times, from different viewpoints, and/or by different sensors. Applied to medical imaging, the registration process helps to improve the diagnosis and tracking of a wide group of pathologies, as well as assist to plan the most appropriate treatment. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 4 / 29
Introduction. Image registration Image registration: process of finding the optimum geometrical transformation which relates corresponding points of two dataset. Geometrically, the image registration consist of aligning one of the datasets, known as the template set (T) with the other set, known as the reference set (R). The datasets can be taken at different times, from different viewpoints, and/or by different sensors. Applied to medical imaging, the registration process helps to improve the diagnosis and tracking of a wide group of pathologies, as well as assist to plan the most appropriate treatment. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 4 / 29
Introduction. Image registration Image registration: process of finding the optimum geometrical transformation which relates corresponding points of two dataset. Geometrically, the image registration consist of aligning one of the datasets, known as the template set (T) with the other set, known as the reference set (R). The datasets can be taken at different times, from different viewpoints, and/or by different sensors. Applied to medical imaging, the registration process helps to improve the diagnosis and tracking of a wide group of pathologies, as well as assist to plan the most appropriate treatment. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 4 / 29
Introduction. Image registration Image registration: process of finding the optimum geometrical transformation which relates corresponding points of two dataset. Geometrically, the image registration consist of aligning one of the datasets, known as the template set (T) with the other set, known as the reference set (R). The datasets can be taken at different times, from different viewpoints, and/or by different sensors. Applied to medical imaging, the registration process helps to improve the diagnosis and tracking of a wide group of pathologies, as well as assist to plan the most appropriate treatment. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 4 / 29
Introduction. Anatomic-functional images of the brain The functional images of the brain, i.e. fMRI or PET, Do not have detailed structural information. Do not provide a specific anatomical location of the functional information. have a spatial resolution, signal to noise ratio and contrast lower than anatomical images It is necessary to register the functional image with anatomical image to provide a geometrical localization, i.e. MRI. This type of registration is known as multimodal registration due to the different contrast and intensity of the datasets. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 5 / 29
Introduction. Anatomic-functional images of the brain The functional images of the brain, i.e. fMRI or PET, Do not have detailed structural information. Do not provide a specific anatomical location of the functional information. have a spatial resolution, signal to noise ratio and contrast lower than anatomical images It is necessary to register the functional image with anatomical image to provide a geometrical localization, i.e. MRI. This type of registration is known as multimodal registration due to the different contrast and intensity of the datasets. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 5 / 29
Introduction. Anatomic-functional images of the brain The functional images of the brain, i.e. fMRI or PET, Do not have detailed structural information. Do not provide a specific anatomical location of the functional information. have a spatial resolution, signal to noise ratio and contrast lower than anatomical images It is necessary to register the functional image with anatomical image to provide a geometrical localization, i.e. MRI. This type of registration is known as multimodal registration due to the different contrast and intensity of the datasets. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 5 / 29
Introduction. Anatomic-functional images of the brain The functional images of the brain, i.e. fMRI or PET, Do not have detailed structural information. Do not provide a specific anatomical location of the functional information. have a spatial resolution, signal to noise ratio and contrast lower than anatomical images It is necessary to register the functional image with anatomical image to provide a geometrical localization, i.e. MRI. This type of registration is known as multimodal registration due to the different contrast and intensity of the datasets. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 5 / 29
Introduction. Anatomic-functional images of the brain The functional images of the brain, i.e. fMRI or PET, Do not have detailed structural information. Do not provide a specific anatomical location of the functional information. have a spatial resolution, signal to noise ratio and contrast lower than anatomical images It is necessary to register the functional image with anatomical image to provide a geometrical localization, i.e. MRI. This type of registration is known as multimodal registration due to the different contrast and intensity of the datasets. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 5 / 29
Introduction. Anatomic-functional images of the brain The functional images of the brain, i.e. fMRI or PET, Do not have detailed structural information. Do not provide a specific anatomical location of the functional information. have a spatial resolution, signal to noise ratio and contrast lower than anatomical images It is necessary to register the functional image with anatomical image to provide a geometrical localization, i.e. MRI. This type of registration is known as multimodal registration due to the different contrast and intensity of the datasets. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 5 / 29
Introduction. Software for image registration ITK (2005) Open source library implemented in C++ Only incorporates parametric methods L. Ibáñez et al., The ITK Software Guide , Kitware, Clifton Park, NY, 2005. Elastix (2010) Library in C++ based on ITK Non-rigid transformations use parametric models (B-Splines). S. Klein et al., “ Elastix : A toolbox for intensity-based medical image registration”, IEEE Trans. Medical Imaging , vol. 29, no. 1, pp. 196-205, 2010. FLIRT - Fast and Flexible Image Registration Toolbox (2007) Library implemented in C++. Elastic registration (2D y 3D), diffusion (2D) and curvature (2D) Nils Papenberg et al., “A Fast and Flexible Image Registration Toolbox”, Proc. of the BVM 2007. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 6 / 29
Introduction. Software for image registration ITK (2005) Open source library implemented in C++ Only incorporates parametric methods L. Ibáñez et al., The ITK Software Guide , Kitware, Clifton Park, NY, 2005. Elastix (2010) Library in C++ based on ITK Non-rigid transformations use parametric models (B-Splines). S. Klein et al., “ Elastix : A toolbox for intensity-based medical image registration”, IEEE Trans. Medical Imaging , vol. 29, no. 1, pp. 196-205, 2010. FLIRT - Fast and Flexible Image Registration Toolbox (2007) Library implemented in C++. Elastic registration (2D y 3D), diffusion (2D) and curvature (2D) Nils Papenberg et al., “A Fast and Flexible Image Registration Toolbox”, Proc. of the BVM 2007. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 6 / 29
Introduction. Software for image registration ITK (2005) Open source library implemented in C++ Only incorporates parametric methods L. Ibáñez et al., The ITK Software Guide , Kitware, Clifton Park, NY, 2005. Elastix (2010) Library in C++ based on ITK Non-rigid transformations use parametric models (B-Splines). S. Klein et al., “ Elastix : A toolbox for intensity-based medical image registration”, IEEE Trans. Medical Imaging , vol. 29, no. 1, pp. 196-205, 2010. FLIRT - Fast and Flexible Image Registration Toolbox (2007) Library implemented in C++. Elastic registration (2D y 3D), diffusion (2D) and curvature (2D) Nils Papenberg et al., “A Fast and Flexible Image Registration Toolbox”, Proc. of the BVM 2007. Legaz et al. (UPCT-LABHUMAN) IWINAC 2015 June, 3 6 / 29
Recommend
More recommend
