This paper presents a method for creation of computational models of breast lesions with irregular shapes from patient Digital Breast Tomosynthesis (DBT) images or breast cadavers and whole-body Computed Tomography (CT) images. The approach includes six basic steps: (a) normalization of the intensity of the tomographic images; (b) image noise reduction; (c) binarization of the lesion area, (d) application of morphological operations to further decrease the level of artefacts; (e) application of a region growing technique to segment the lesion; and (f) creation of a final 3D lesion model. The algorithm is semi-automatic as the initial selection of the region of the lesion and the seeds for the region growing are done interactively. A software tool, performing all of the required steps, was developed in MATLAB. The method was tested and evaluated by analysing anonymized sets of DBT patient images diagnosed with lesions. Experienced radiologists evaluated the segmentation of the tumours in the slices and the obtained 3D lesion shapes. They concluded for a quite satisfactory delineation of the lesions. In addition, for three DBT cases, a delineation of the tumours was performed independently by the radiologists. In all cases the abnormality volumes segmented by the proposed algorithm were smaller than those outlined by the experts. The calculated Dice similarity coefficients for algorithm-radiologist and radiologist-radiologist showed similar values. Another selected tumour case was introduced into a computational breast model to recursively assess the algorithm. The relative volume difference between the ground-truth tumour volume and the one obtained by applying the algorithm on the synthetic volume from the virtual DBT study is 5% which demonstrates the satisfactory performance of the proposed segmentation algorithm. The software tool we developed was used to create models of different breast abnormalities, which were then stored in a database for use by researchers working in this field. Anthropomorphic voxel breast phantoms with realistic tissue
Objective. This work describes an approach for producing physical anthropomorphic breast phantoms from clinical patient data using three-dimensional (3D) fused-deposition modelling (FDM) printing. Approach. The source of the anthropomorphic model was a clinical Magnetic Resonance Imaging (MRI) patient image set, which was segmented slice by slice into adipose and glandular tissues, skin and tumour formations; thus obtaining a four component computational breast model. The segmented tissues were mapped to specific Hounsfield Units (HU) values, which were derived from clinical breast Computed Tomography (CT) data. The obtained computational model was used as a template for producing a physical anthropomorphic breast phantom using 3D printing. FDM technology with only one polylactic acid filament was used. The physical breast phantom was scanned at Siemens SOMATOM Definition CT. Quantitative and qualitative evaluation were carried out to assess the clinical realism of CT slices of the physical breast phantom. Main results. The comparison between selected slices from the computational breast phantom and CT slices of the physical breast phantom shows similar visual x-ray appearance of the four breast tissue structures: adipose, glandular, tumour and skin. The results from the task-based evaluation, which involved three radiologists, showed a high degree of realistic clinical radiological appearance of the modelled breast components. Measured HU values of the printed structures are within the range of HU values used in the computational phantom. Moreover, measured physical parameters of the breast phantom, such as weight and linear dimensions, agree very well with the corresponding ones of the computational breast models. Significance. The presented approach, based on a single FDM material, was found suitable for manufacturing of a physical breast phantom, which mimics well the 3D spatial distribution of the different breast tissues and their x-ray absorption properties. As such, it could be successfully exploited in advanced x-ray breast imaging research applications.
INTRODUCTION: 3D anthropomorphic models of human tissues have become a requirement for conducting realistic virtual studies. One of the current directions in the research of X-ray imaging is the development of physical models with 3D printing techniques using specific materials aiming to obtain replica of the human body tissues with similar radiological characteristics.Aim: The aim of this study is to create a calibration phantom for establishing the X-ray properties of different cartridge infills and their suitability to represent the X-ray properties of different breast types. MATERIALS AND METHODS:A physical calibration model consisting of 22 objects was designed and printed by using an inkjet printer. A mixture was obtained from 5 mL printer ink and 3 g of potassium iodide (KI), which was used to fill the printer's cartridge and to print the model on a set of plain office paper. Experimental X-ray images of the physical model were acquired on radiographic system SEDECAL X PLUS LP+. The obtained attenuation coefficient of the printing mixture was evaluated and compared to the breast tissue coefficients corresponding to the used X-ray energy. RESULTS AND DISCUSSION:The physical model was printed on ten office sheets and stacked above one another. The obtained attenuation coefficient of the printing mixture was found very similar to that of the glandular tissue of the breast for the used X-ray energy. CONCLUSION:The obtained printer ink-KI mixture is suitable for representing the glandular part of breast tissue. The method has the potential to be used for creation of a realistic physical breast model.
X-ray phase-contrast imaging is a high-resolution imaging that permits an increase of the perceptibility of the details in three-dimensional objects, such as human tissues compared to conventional absorption imaging. There are different approaches for implementing phase-contrast imaging and their introduction into clinical practice requires advanced computational tools. A long-term goal of our research is the development of computational models of breast phase-contrast imaging. The aim of this study is to develop a software module for implementing grating-based phase-contrast imaging. For this purpose, an existing in-house software application for x-ray imaging with a function to model and simulate propagation-based phase-contrast x-ray images has been extended to include a model of grating-based imaging. To test the new functionality, four computational phantoms reflecting features, which can be screened in the real breast tissue and which differ in their complexity, were designed. Planar x-ray images in absorption, propagation-based and grating-based modes were generated and compared. Results showed improved visual appearance of the simulated objects in images obtained by simulating grating-based imaging setup. The developed subroutine is planned to be experimentally validated at synchrotron facility. The new software functionality will be exploited in studies related to new x-ray imaging techniques for breast screening and diagnosing.
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