A finite element-based machine learning approach for modeling the mechanical behavior of the breast tissues under compression in real-time.

This work presents a data-driven method to simulate, in real-time, the biomechanical behavior of the breast tissues in some image-guided interventions such as biopsies or radiotherapy dose delivery as well as to speed up multimodal registration algorithms. Ten real breasts were used for this work. Their deformation due to the displacement of two compression plates was simulated off-line using the finite element (FE) method.

A complete software application for automatic registration of x-ray mammography and magnetic resonance images.

Purpose: This work presents a complete and automatic software application to aid radiologists in breast cancer diagnosis. The application is a fully automated method that performs a complete registration of magnetic resonance (MR) images and x-ray (XR) images in both directions (from MR to XR and from XR to MR) and for both x-ray mammograms, craniocaudal (CC), and mediolateral oblique (MLO). This new approximation allows radiologists to mark points in the MR images and, without any manual intervention, it provides their corresponding points in both types of XR mammograms and vice versa.

Segmentation of the breast skin and its influence in the simulation of the breast compression during an X-ray mammography.

A novel method of skin segmentation is presented aimed to obtain as many pixels belonging to the real skin as possible. This method is validated by experts in radiology. In addition, a biomechanical model of the breast, which considers the skin segmented in this way, is constructed to study the influence of considering real skin in the simulation of the breast compression during an X-ray mammography.

MRI skin segmentation for the virtual deformation of the breast under mammographic compression.

Breast Magnetic Resonance Image skin has similar intensity levels than dense tissue, and may produce segmentation errors if not managed correctly. In this work a novel skin segmentation method is presented and validated by experts, aimed to obtain as many pixels belonging to the real skin as possible. Segmented skin will be used to build a breast biomechanical model to register X-Ray Images with Magnetic Resonance Images in the future, using a virtually deformed Magnetic Resonance Image.