Automatic multimodal 2D/3D breast image registration using biomechanical FEM models and intensity-based optimization

Hopp, Torsten; Dietzel, Matthias; Baltzer, Pascal; Kreisel, P.; Kaiser, Werner A.; Gemmeke, H.; Ruiter, Nicole V.

doi:10.1016/j.media.2012.10.003

Cited by 69 publications

(63 citation statements)

References 26 publications

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“…The registration method is based on a method originally developed for the registration of Magnetic Resonance Tomography images with X-ray mammograms [9,22] and was successfully applied for the registration of USCT images with X-ray mammograms. The obtained accuracy for an automated registration (TRE 11.9 mm) is slightly better than for the registration with MRI images (13.2 mm), well within the range other MRI-to-mammography registration approaches in literature [20,51] and as well in a range which might assist radiologists in multimodal diagnosis.…”

Section: Discussionmentioning

confidence: 99%

“…However it depends on a number of parameters for the preprocessing, the creation of the biomechanical model and both deformation simulation steps, which influence the registration accuracy. As an optional add-on to adapt these parameters to patient specific conditions, an optimization via image similarity similar to [9] is implemented. The image similarity S is calculated between the projection of the deformed USCT volume image and the corresponding mammogram.…”

Section: Image Registrationmentioning

confidence: 99%

“…The method originates from an automated registration for X-ray mammograms and MRI volumes [9]. In preliminary work [10][11][12] it was successfully applied to in-vivo USCT datasets.…”

Section: Introductionmentioning

confidence: 99%

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

Hopp

Duric

Ruiter

2015

Computerized Medical Imaging and Graphics

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Section: Discussionmentioning

confidence: 99%

Section: Image Registrationmentioning

confidence: 99%

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

Hopp

Duric

Ruiter

2015

Computerized Medical Imaging and Graphics

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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%

“…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%

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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Morphometric study of adipocytes on breast cancer by means of photonic microscopy and image analysis

Suárez-Nájera

Chanona‐Pérez

Valdivia-Flores

et al. 2017

Microscopy Res & Technique

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Worldwide, breast cancer (BrCa) is currently the leading cause of deaths associated to malignant lesions in adult women. Given that some studies have mentioned that peritumoral adipocytes may contribute to breast carcinogenesis, present work sought to quantitative evaluate the morphometry of these cells in a group of adult women. Three thousand six hundred sixty four breast adipocytes, that came from biopsies of a group of adult females with different types of breast carcinomas (ductal, lobular, and mixed) and one with normal tissues, were evaluated through an image analysis (IA) process regarding six morphometric descriptors: area (A), perimeter (P), Feret diameter (F ), aspect ratio (AR), roundness factor (RF), and fractal dimension of cellular contour (FD ). Data showed that the adipocytes of the normal tissues group were bigger (A: 3398 ± 2331 µm , P: 239 ± 83 µm, and F : 79.9 ± 24.5 µm) than those from BrCa samples (A: 2860 ± 1933 µm , P: 214 ± 66 µm, and F : 73.2 ± 22.5 µm), and presented a more irregular contour (FD of 1.370 ± 0.037 for normal group and of 1.335 ± 0.049 for the oncologic one). Moreover, it could be accounted that adipocytes of mixed carcinomas were largest (F : 75.1 ± 22.4 µm) than those of lobular lesions (F : 61.6 ± 22.6 µm), while the adipocytes of ductal carcinomas were the most oval (AR: 1.421 ± 0.524) and roughest (FD : 1.324 ± 0.050) cells. IA results suggest that BrCa lesions can be categorized through a quantitative morphometric evaluation of peritumoral adipocytes. These findings could let the development of an analytical tool to help the Pathologist to enhance the accuracy of the oncologic diagnose.

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Automatic multimodal 2D/3D breast image registration using biomechanical FEM models and intensity-based optimization

Cited by 69 publications

References 26 publications

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

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

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

Morphometric study of adipocytes on breast cancer by means of photonic microscopy and image analysis

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