Models of breast lesions based on three-dimensional X-ray breast images

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

High-flexibility combinatorial peptide synthesis with laser-based transfer of monomers in solid matrix material

Laser writing is used to structure surfaces in many different ways in materials and life sciences. However, combinatorial patterning applications are still limited. Here we present a method for cost-efficient combinatorial synthesis of very-high-density peptide arrays with natural and synthetic monomers. A laser automatically transfers nanometre-thin solid material spots from different donor slides to an acceptor. Each donor bears a thin polymer film, embedding one type of monomer. Coupling occurs in a separate heating step, where the matrix becomes viscous and building blocks diffuse and couple to the acceptor surface. Furthermore, we can consecutively deposit two material layers of activation reagents and amino acids. Subsequent heat-induced mixing facilitates an in situ activation and coupling of the monomers. This allows us to incorporate building blocks with click chemistry compatibility or a large variety of commercially available non-activated, for example, posttranslationally modified building blocks into the array’s peptides with >17,000 spots per cm²

A platform for Image Reconstruction in X-ray Imaging: Medical Applications using CBCT and DTS algorithms

This paper presents the architecture of a software platform implemented in C++, for the purpose of testing and evaluation of reconstruction algorithms in X-ray imaging. The fundamental elements of the platform are classes, tightened together in a logical hierarchy. Real world objects as an X-ray source or a flat detector can be defined and implemented as instances of corresponding classes. Various operations (e.g. 3D transformations, loading, saving, filtering of images, creation of planar or curved objects of various dimensions) have been incorporated in the software tool as class methods, as well. The user can easily set up any arrangement of the imaging chain objects in 3D space and experiment with many different trajectories and configurations. Selected 3D volume reconstructions using simulated data acquired in specific scanning trajectories are used as a demonstration of the tool. The platform is considered as a basic tool for future investigations of new reconstruction methods in combination with various scanning configurations

Contrast detail phantoms for X-ray phase-contrast mammography and tomography

Primary goal of this study is to investigate the visibility of low contrast details of different size on images obtained at conventional mammography unit, and at a monochromatic synchrotron radiation source, in absorption based and phase contrast imaging setups. For this purpose, three physical phantoms made of paraffin as a bulk material were used. They embedded various low contrast features. Single projection images were acquired with the GE Senographe mammography unit and at the beamline ID17, ESRF, Grenoble. Comparison of images showed that images obtained in a phase contrast mode have more visible details than the images acquired either in absorption mode at the synchrotron or at the conventional x-ray mammography unit. Analysis for δ and μ suggests that paraffin may be a suitable material for the manufacturing of tissue-mimicking phantoms dedicated to phase contrast applications. Results will be exploited in the development of a dedicated phantom for phase contrast imaging.The final publication is available at https://link.springer.com/chapter/10.1007%2F978-3-319-41546-8_7

SEGMENTATION OF CANCER FORMATIONS FROM BREAST TOMOSYNTHESIS

This paper presents an algorithm for segmentation of lesions in breast tomosynthesis slices. The implemented approach is based on finding specific values in a region of interest containing the tumor, followed by a set of morphology operations to remove any structures not belonging to the tumor structure, and automatic region growing algorithm to finally obtain the tumor image. The developed algorithm was applied on ten patient sets of breast tomosynthesis images to segment successfully the breast tumors