Abstract:
A fast and accurate scatter imaging technique to differentiate cancerous and healthy breast tissue is introduced in this work. Such a technique would have wide-ranging clinical applications from intra-operative margin assessment to breast cancer screening. Coherent Scatter Computed Tomography (CSCT) has been shown to differentiate cancerous from healthy tissue, but the need to raster scan a pencil beam at a series of angles and slices in order to reconstruct 3D images makes it prohibitively time consuming. In this work we apply the coded aperture coherent scatter spectral imaging technique to reconstruct 3D images of breast tissue samples from experimental data taken without the rotation usually required in CSCT. We present our experimental implementation of coded aperture scatter imaging, the reconstructed images of the breast tissue samples and segmentations of the 3D images in order to identify the cancerous and healthy tissue inside of the samples. We find that coded aperture scatter imaging is able to reconstruct images of the samples and identify the distribution of cancerous and healthy tissues (i.e., fibroglandular, adipose, or a mix of the two) inside of them. Coded aperture scatter imaging has the potential to provide scatter images that automatically differentiate cancerous and healthy tissue inside of ex vivo samples within a time on the order of a minute.