Frequency implementation of the Euler-Lagrange equations for variational image registration

Monedero, Rafael Verdú; Ruiz, Jorge Larrey; Sánchez, Juan Morales

doi:10.1109/lsp.2007.913588

Cited by 12 publications

(6 citation statements)

References 15 publications

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“…As stated in [15], this strategy allows for an efficient implementation, which runs twice faster than most state-ofart approaches [17]. To avoid too high values of the step (learning parameter), every time the derivative direction changes abruptly, the optimizer assumes that a local maximum or minimum has been passed by and reacts halving the size of the step.…”

Section: Image Registration Proceduresmentioning

confidence: 99%

DRR and Portal Image Registration for Automatic Patient Positioning in Radiotherapy Treatment

et al. 2011

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Image processing turns out to be essential in the planning and verification of radiotherapy treatments. Before applying a radiotherapy treatment, a dosimetry planning must be performed. Usually, the planning is done by means of an X-ray volumetric analysis using computerized tomography, where the area to be radiated is marked out. During the treatment phase, it is necessary to place the patient under the particle accelerator exactly as considered in the dosimetry stage. Coarse alignment is achieved using fiduciary markers placed over the patient's skin as external references. Later, fine alignment is provided by comparing a digitally reconstructed radiography (DRR) from the planning stage and a portal image captured by the accelerator in the treatment stage. The preprocessing of DRR and portal images, as well as the minimization of the non-shared information between both kinds of images, is mandatory for the correct operation of the image registration algorithm. With this purpose, mathematical morphology and image processing techniques have been used. The present work describes a fully automatic method to calculate more accurately the necessary displacement of the couch to place the patient exactly at the planned position. The proposed method to achieve the correct positioning of the patient is based on advanced image registration techniques. Preliminary results show a perfect match with the displacement estimated by the physician.

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Section: Image Registration Proceduresmentioning

confidence: 99%

DRR and Portal Image Registration for Automatic Patient Positioning in Radiotherapy Treatment

et al. 2011

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“…is the 3D Fourier transform of the so-called external forces field, ( ) f x (please refer to Appendix A, Eqs. (A.1)-(A.2) for a definition of this field), and A  is a diagonal 3×3 matrix whose elements are scalar functions which implement the spatial derivatives in the frequency domain, 22 allowing for their computation by means of products:…”

Section: Methodsmentioning

confidence: 99%

“…Equation (5) provides a stable implementation for the computation of a numerical solution for the displacement field, and in a more efficient way than existing approaches if the 3D fast Fourier transform (FFT) is used. 22 In order to solve (5) in its current state (i.e., formulated in the frequency domain), a timemarching scheme can be employed, yielding the following equation:…”

Section: Methodsmentioning

confidence: 99%

Efficient Variational Approach to Multimodal Registration of Anatomical and Functional Intra-Patient Tumorous Brain Data

Legaz-Aparicio

Verdú‐Monedero

Larrey-Ruiz

et al. 2016

Int. J. Neur. Syst.

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This paper addresses the functional localization of intra-patient images of the brain. Functional images of the brain (fMRI and PET) provide information about brain function and metabolism whereas anatomical images (MRI and CT) supply the localization of structures with high spatial resolution. The goal is to find the geometric correspondence between functional and anatomical images in order to complement and fuse the information provided by each imaging modality. The proposed approach is based on a variational formulation of the image registration problem in the frequency domain. It has been implemented as a C/C[Formula: see text] library which is invoked from a GUI. This interface is routinely used in the clinical setting by physicians for research purposes (Inscanner, Alicante, Spain), and may be used as well for diagnosis and surgical planning. The registration of anatomic and functional intra-patient images of the brain makes it possible to obtain a geometric correspondence which allows for the localization of the functional processes that occur in the brain. Through 18 clinical experiments, it has been demonstrated how the proposed approach outperforms popular state-of-the-art registration methods in terms of efficiency, information theory-based measures (such as mutual information) and actual registration error (distance in space of corresponding landmarks).

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“…The second registration step is based on a variational approach which has been formulated in the frequency domain [35,36], and also implemented in the frequency domain [37] providing a fast and efficient registration method.…”

Section: Intensity-based Registrationmentioning

confidence: 99%

“…where ξ ∈ N is the iteration index, l = {1, 2} in this 2D problem, H(ω) is a low pass filter in the frequency domain andf (ω) = (f 1 (ω),f 2 (ω)) is the Fourier transform of the external forces field. For further details, please refer to [35,36].…”

Section: Intensity-based Registrationmentioning

confidence: 99%

Multimodal registration of optical microscopic and infrared spectroscopic images from different tissue sections: An application to colon cancer

Peñaranda

Naranjo

Verdú‐Monedero

et al. 2017

Digital Signal Processing

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Frequency implementation of the Euler-Lagrange equations for variational image registration

Cited by 12 publications

References 15 publications

DRR and Portal Image Registration for Automatic Patient Positioning in Radiotherapy Treatment

DRR and Portal Image Registration for Automatic Patient Positioning in Radiotherapy Treatment

Efficient Variational Approach to Multimodal Registration of Anatomical and Functional Intra-Patient Tumorous Brain Data

Multimodal registration of optical microscopic and infrared spectroscopic images from different tissue sections: An application to colon cancer

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