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And on Monday, the year-old shared a chilling warning to those considering a breast enlargement with plastic surgery. Read More About Us. Technical Validation The purpose of constructing anthropomorphic numerical breast models is to enable design, development and testing of new breast imaging techniques. Free model breasts, the model elements are created as modules clustersenabling reconfigurable modfl and adaptability in terms of sizes and shapes. The breast Free model breasts Nude posted can also be worn under a bikini. Final Say. The existing Open Comments threads will continue to exist for those who do not subscribe to Independent Premium. Spread the word. Google Scholar 5.

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A Nature Research Journal. A repository of anthropomorphic numerical breast models is made available for the scientific community to support research and development of microwave imaging technologies for diagnostic and therapeutic applications. These models are constructed from magnetic resonance imaging MRI scans acquired at our university hospital. Our 3D breast modelling method is used to translate the MRI scans into 3D models representing the geometry and microwave-frequency properties of tissues in the breast.

The reconstructed models demonstrate anatomical realism, reconfigurable complexity, and flexibility to adapt to simulations of various microwave imaging techniques and prototype systems. With these models, realistic and rigorous test scenarios can be defined in simulations to support feasibility analysis, performance verification and design improvements of developing microwave imaging techniques, prior to testing on experimental systems.

A repository of breast models is created which includes breasts of varying classification — fatty, scattered, heterogeneous, and dense. In addition, the models include brief documentation to facilitate researchers in selecting a model by matching its features with their requirements. Download metadata file. Machine-accessible metadata file describing the reported data ISA-tab format.

These models offer several advantages over experimental breast phantoms, including capturing a high degree of realism in terms of shape, size, internal structure, and heterogeneity of the tissue properties. In addition, these models provide the flexibility of embedding tumours of varying type, size, and morphology at different locations. This allows the generation of a large number of test cases to conduct rigorous testing, feasibility analysis, performance verification, and design improvements for microwave breast imaging techniques.

A 3D numerical breast model is similar to a three-dimensional data matrix, where each element of the matrix, known as a voxel, signifies a certain tissue at a specific location inside a human breast. These models can be conveniently constructed from breast MRI scans, as these images provide information on the spatial distribution of tissues in the breast.

Creating microwave-frequency models from MRI images also involves mapping pixel intensities in the MRI scans to dielectric properties for the microwave models. A notable method is presented in 9 , with an associated breast model repository These models have been widely used to investigate microwave imaging techniques. Recently, we introduced methods to generate models using a pipeline that takes advantage of 3D processing methods to reduce artefacts and promote anatomical connectivity.

The modelling approach also enables the construction of adjustable models with reconfigurable model complexity or shape. In this work, we present a new repository of high quality breast models derived for the first time from 3. The aim of this repository is to provide the research community with an expanded set of models. We apply our 3D breast modelling method 14 to construct models demonstrating anatomically realistic shape and structural connectivity.

Our breast model repository has several features which are expected to enhance its applicability and convenience. First, the model elements are created as modules clusters , enabling reconfigurable complexity and adaptability in terms of sizes and shapes.

Second, the repository contains models of both left and right breasts of each volunteer, which is favourable for developing differential imaging algorithms. Third, the models are available in multiple file formats, compatible with a wide range of computational software packages. Furthermore, each model has associated pre-computed tissue property files, which are readily importable in simulation software. All of these model attributes enhance convenience and applicability throughout the developmental stages of imaging technologies, ranging from initial idea verification to advanced design, analysis and rigorous testing.

To construct a repository of anthropomorphic numerical breast models, high resolution MRI scans were selected. These scans were acquired at our university hospital University of Calgary, Foothills Campus as part of a patient study involving microwave imaging prototype systems.

The MRI scans served as the ground truth to assist in the interpretation of the microwave imaging results. Moreover, these scans were used to construct anatomically realistic numerical breast models, which are important tools for research and development of novel medical imaging technologies. The 3. This scan sequence enables fat-free imaging to reveal underlying breast anatomy. These 2D slices are merged together to form a 3D volume, where the spatial extent of each voxel element is 0.

A full spectrum of breast classification is covered including fatty, scattered density, heterogeneously dense, and dense breast models. However, a single 1. In addition, the breast tumour from this scan was segmented and made available as a separate model element for the researchers to include with healthy breast models and simulate a diseased breast. Table 1 summarizes the study input, processing technique, and data output for the model repository. The 3D breast modelling method employs various volume processing techniques to transform the MRI scans to 3D numerical models.

This method has previously been described in detail In the first stage, a 3D breast mask is generated to identify the breast region from the background. This is achieved by traversing the scan in three orthogonal planes transverse, sagittal and coronal while sensing the breast surface using a threshold value computed from the background voxels. The breast surface is constructed by taking the intersection of the three surfaces identified across each orthogonal plane.

Once the breast region is identified, a clustering method is applied in stage two to segment the breast tissues into skin, fat and fibroglandular clusters. The segmented tissues can be further sub-clustered to add reconfigurability to the reconstructed models, where the increasing number of sub-clusters implies increasing level of model complexity tissue heterogeneity.

Since the fibroglandular tissues of the breast have significant heterogeneity in dielectric properties, we create multiple models with varying number of fibroglandular sub-clusters.

In contrast, the fat tissues of the breast are fairly homogeneous in terms of the dielectric properties and hence they are represented by a single fat cluster. The various stages of the breast modelling method are shown in Fig. The breast MRI scan is the study input, which is fed to the 3D breast modelling method for processing.

The output data is 3D numerical breast model comprised of tissue clusters, including skin, fat and single or multiple fibroglandular clusters. The outcome of the first two stages of our modelling methodology is the breast region segmented into a set of 3D model elements clusters , including skin, fat and fibroglandular clusters.

Each element of this set is mutually exclusive of the other elements, providing ability to process each breast tissue independently. The processing may include sub-clustering of the model elements to add complexity to the model or applying tissue specific deformation to emulate physical effects of experimental systems. The processed clusters can then be assembled to construct a model with desired features. To complete the model construction for microwave imaging applications, the clusters are assigned dielectric tissue properties using a linear mapping strategy 9.

This involves defining voxel intensity ranges for different tissues based on the statistics of model intensities and assigning dielectric property curves to each range using the values published in the literature The average voxel intensities of the clusters are computed and compared with the intensity ranges to determine the weighting factor with which property curves are combined to yield their dielectric properties. It should be noted that the clustering approach will not allow the model to achieve the highest degree of heterogeneity.

However, allowing the user control on the model complexity may benefit the development process of new imaging technologies. For instance, it provides the user an ability to design a set of experiments with progressively increasing level of breast heterogeneity to verify the robustness of the imaging algorithms.

In addition, such models can also be used to analyse the impact of model complexity on microwave imaging signals to quantify their sensitivity in resolving fine structural details of the breast.

A preliminary study 15 conducted with these models showed a difference between scattered microwave responses acquired from single homogeneous and multiple heterogenous clusters models. However, a high degree of similarity in scattered responses was observed between models with 8 and 16 fibroglandular clusters. This understanding can be used to design simple yet realistic numerical models with heterogeneity levels which microwave signals are realistically expected to resolve.

In addition, the knowledge of this can also help us later in developing experimental phantoms with limited yet realistic heterogeneity. Another advantage of modelling breast tissues as clusters is their suitability for commercially available full wave electromagnetic softwares. The model clusters can conveniently be imported as 3D objects and assigned dielectric properties. These objects can also be easily transformed according to the simulation requirements.

The breast model repository includes example scripts to demonstrate its usage. A detailed description of these scripts, coding languages and functionalities can be found in the Usage Notes section.

This model repository extends the range and variety of breast models reported in our earlier work on breast modelling method 14 , including four additional models of scattered and heterogenous classification. These folders further contain three sub-folders called model elements folder , containing model elements with varying numbers of fibroglandular clusters. More information about these scripts is included in the Usage Notes section.

Each folder contains two sub-folders corresponding to breast side. The breast side folders further contain three sub-folders each, containing models of varying number of fibroglandular clusters.

This format is convenient for researchers using Matlab-based custom built 2D or 3D electromagnetic solvers. A complete model can be easily imported into a simulation space as a 3D data matrix for full 3D simulations while 2D slices matrices can also be extracted for simpler and faster 2D simulations. This model format provides advantages of efficient storage, transfer and language independent access.

The voxelized model is also available in HDF5 format and the corresponding properties are stored in the XML format model properties file. This file VoxelizedModel. The application programming interface API provided by HDF5 developers is used to construct a single model file containing model data and properties as groups and elements while related model features such as breast health, class, density, name, and number of tissue clusters etc.

The HDF5 format was selected due to its portability and suitability to store large and complex data. In addition, it is a language independent format supported by many software packages that allows for greater accessibility and reuse value of the data. In addition, the developers provide a viewer software HDFView for quick visualization, browsing and editing of data.

A summary of available model data, property formats, types and compatibility with simulation software is included in Table 2. This format enables convenient structuring of the model elements as groups e.

In addition, it also enables storage of 3D model elements as 3D data matrices. The availability of model elements as 3D clusters enables simulation of breast deformation to emulate real imaging scenarios, such as breast compression during breast mammogram acquisition. The voxelized model can allow only basic model deformations, achievable by scaling voxel sizes in desired dimensions. However, the STL based model can be used to model complex deformations.

This format can be imported as a finite element model and converted into a biomechanical model by assigning tissue specific elastic properties. The last file of the model clusters folder ModelProperties. The XML file format allows the creation of custom markups or tags to define a data structure and include data as elements or attributes.

Free model breasts

Free model breasts

Free model breasts