Image fusion of Ultrasound Computer Tomography volumes with X-ray mammograms using a biomechanical model based 2D/3D registration

Hopp, Torsten; Duric, Nebojsa; Ruiter, Nicole V.

doi:10.1016/j.compmedimag.2014.10.005

Cited by 24 publications

(17 citation statements)

References 43 publications

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“…However, this method does not reflect a physically realistic deformation of the breast and leads to artifacts in areas closer to where the displacements are applied. In the second case, to define explicitly the compression plates, they are simulated only using a parametric surface or as rigid bodies . This second approach is more common when the FE solver is a commercial tool.…”

Section: Patient‐specific Biomechanical Modelingmentioning

confidence: 99%

“…In the last decades, researchers have focused their efforts on developing algorithms to fuse the information of different imaging modalities considering the patient's position and loading conditions of the breast during image acquisition. [10][11][12] A common process consists in using a biomechanical finite element (FE) model that simulates in a physically realistic way the deformations produced in both the surface and internal tissues of the breast during the mammographic acquisition. Finite element models have been widely used in various medical applications, including brain, 13 heart, 14 liver, 15 lungs, 16 or prostate 17 imaging, composing a wide bibliography.…”

Section: Introductionmentioning

confidence: 99%

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A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

et al. 2017

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Breast magnetic resonance imaging (MRI) and x-ray mammography are two image modalities widely used for the early detection and diagnosis of breast diseases in women. The combination of these modalities leads to a more accurate diagnosis and treatment of breast diseases. The aim of this paper is to review the registration between breast MRI and x-ray mammographic images using patient-specific finite element-based biomechanical models. Specifically, a biomechanical model is obtained from the patient's MRI volume and is subsequently used to mimic the mammographic acquisition. Due to the different patient positioning and movement restrictions applied in each image modality, the finite element analysis provides a realistic physics-based approach to perform the breast deformation. In contrast with other reviews, we do not only expose the overall process of compression and registration but we also include main ideas, describe challenges, and provide an overview of the used software in each step of the process. Extracting an accurate description from the MR images and preserving the stability during the finite element analysis require an accurate knowledge about the algorithms used, as well as the software and underlying physics. The wide perspective offered makes the paper suitable not only for expert researchers but also for graduate students and clinicians. We also include several medical applications in the paper, with the aim to fill the gap between the engineering and clinical performance.

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Section: Patient‐specific Biomechanical Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

et al. 2017

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“…has been used extensively to model breast deformations and compression, including use for breast augmentation, 8,9 multimodality registration, [10][11][12][13][14][15][16][17][18] image-guided surgery, [19][20][21] and tumor tracking. 22,23 Several studies have tracked landmarks to within 5 mm.…”

Section: B Finite-element (Fe) Breast Modelsmentioning

confidence: 99%

“…Corresponding mammograms or compressed image data were not available for the bCT dataset used in our study. So, we were unable to optimize the material parameters or use ground truth displacements as boundary constraints and thus used material properties 18 and boundary constraints from the literature. We also choose to neglect the initial (unknown) stress present in the prone breast.…”

Section: B Finite-element (Fe) Breast Modelsmentioning

confidence: 99%

“…15,24 Other studies have also included the effects of gravity. 9,21,22,25 Current state-of-the-art methods often optimize the initial breast position 16 and/or material parameters [16][17][18]20 through a FE-registration framework. Registrations, between breast MR images at different levels of compression, have also been used to provide boundary constraints to define the displacement of the region posterior to the compression plates in a corresponding FE model.…”

Section: B Finite-element (Fe) Breast Modelsmentioning

confidence: 99%

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Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation

Sturgeon

Kiarashi

et al. 2016

Med. Phys.

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Purpose: The authors are developing a series of computational breast phantoms based on breast CT data for imaging research. In this work, the authors develop a program that will allow a user to alter the phantoms to simulate the effect of gravity and compression of the breast (craniocaudal or mediolateral oblique) making the phantoms applicable to multimodality imaging. Methods: This application utilizes a template finite-element (FE) breast model that can be applied to their presegmented voxelized breast phantoms. The FE model is automatically fit to the geometry of a given breast phantom, and the material properties of each element are set based on the segmented voxels contained within the element. The loading and boundary conditions, which include gravity, are then assigned based on a user-defined position and compression. The effect of applying these loads to the breast is computed using a multistage contact analysis in FEBio, a freely available and well-validated FE software package specifically designed for biomedical applications. The resulting deformation of the breast is then applied to a boundary mesh representation of the phantom that can be used for simulating medical images. An efficient script performs the above actions seamlessly. The user only needs to specify which voxelized breast phantom to use, the compressed thickness, and orientation of the breast. Results: The authors utilized their FE application to simulate compressed states of the breast indicative of mammography and tomosynthesis. Gravity and compression were simulated on example phantoms and used to generate mammograms in the craniocaudal or mediolateral oblique views. The simulated mammograms show a high degree of realism illustrating the utility of the FE method in simulating imaging data of repositioned and compressed breasts. Conclusions: The breast phantoms and the compression software can become a useful resource to the breast imaging research community. These phantoms can then be used to evaluate and compare imaging modalities that involve different positioning and compression of the breast. C 2016 American Association of Physicists in Medicine. [http://dx

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Advances in digital and physical anthropomorphic breast phantoms for x‐ray imaging

Glick

Ikejimba

2018

Medical Physics

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Purpose: With the advent of three-dimensional (3D) breast imaging modalities such as digital breast tomosynthesis (DBT) and dedicated breast CT (bCT), research into new anthropomorphic breast phantoms has accelerated. These breast phantoms are important for the optimization of new breast imaging systems, assessing new regulatory submissions to prove safety and effectiveness, and for developing new approaches to acceptance and constancy testing of 3D breast imaging systems. This paper provides a review of current research investigating both digital and physical breast phantom development for use in x-ray based imaging. Methods: Two approaches for designing anthropomorphic, digital breast phantoms are discussed, procedural model-based phantom generation, where breast features are expressed using mathematical models, and patient-based generation, where breast structures from tissue specimens or patient-based breast MR or CT volumes are segmented. Following this discussion, a review of physical anthropomorphic phantoms is given, with emphasis on the advantages and disadvantages present with each approach. Conclusions: This paper provides a summary of the state-of-the-art in anthropomorphic breast phantom development for x-ray breast imaging. The primary advantage of model-based digital phantoms is that an unlimited number of phantoms with varying size, shape, and density can be generated. Current research on model-based breast phantoms is producing more and more realistic breast models; however, they probably are not yet able to pass the so-called "fool the radiologist" visualization test. Empirical patient-based breast phantoms are typically based on clinical breast CT data and look more realistic. However, clinical breast CT images have limited spatial resolution and thus do not always portray the finer details in the breast. A number of innovative solutions have been proposed for fabricating physical anthropomorphic breast phantoms based on digital phantom models; however, a number of challenges remain, including realistic modeling of x-ray attenuation properties and accurately representing high-frequency structures within breast. Published 2018. This article is a U.S. Government work and is in the public domain in the USA [https://doi.org/10.1002/mp.13110]

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Image fusion of Ultrasound Computer Tomography volumes with X-ray mammograms using a biomechanical model based 2D/3D registration

Cited by 24 publications

References 43 publications

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation

Advances in digital and physical anthropomorphic breast phantoms for x‐ray imaging

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