Image-based reconstruction of anthropomorphic breast phantoms for synthetic mammogram generation

The aim of this work is the generation of realistic synthetic mammograms, using as an input of the imaging acquisition simulation process digital anthropomorphic phantoms, reconstructed from sets of dedicated breast computed tomography (BCT) images from different patients. The voxel-based structure and the segmentation into fibroglandular, adipose and skin tissues are performed through trivariate tensor-product B-spline approximation and morphological operations. The obtained phantoms can be modified by means of geometrical transformations that replicate typical breast shape deformities, and by locally introducing virtual masses and calcifications. After simulating biomechanical compression of the 3D breast phantoms, we generate the mammograms in both craniocaudal (CC) and mediolateral oblique (MLO) views, modelling the x-ray interaction with breast tissues with a Monte Carlo approach implemented in the in silico breast imaging pipeline VICTRE.

The methodology proposed here can contribute to the creation of synthetic mammogram databases, to be used for in silico testing of diagnostic and therapeutic techniques, as well as for the validation of artificial intelligence (AI) systems in diagnostic imaging and cancer screening. The great advantage is that, from a single BCT scan, it is possible to generate multiple realistic mammograms, with different anatomical features, in terms of breast shape and size, and type and location of lesions.