This work proposes an objective and automated procedure to obtain realistic digital breast tomosynthesis (DBT) images for virtual clinical trials (VCT) using the hybrid approach (simulating lesions in acquired patient images). Based on extensive feedback from a radiologist, we have implemented an automatic selection of an appropriate insertion position that (1) is located in the interior region of the breast, (2) contains sufficient glandular tissue, and (3) has the lowest variance to cope with the presence of prominent background structure and contains no Sobel edge detected blood vessels. Next, the lesion is rotated to align with the breast structures using the histogram of oriented gradient feature descriptor. The spicules of the lesion are extended to improve the fine details of the manually segmented mass models. To reduce the pronounced shadow artefact surrounding the mass, the lesion template is modified with a fitted 2D gaussian to create a softer transition between background and lesion. The realism of 20 simulated lesions using the established automated procedure was scored; 70% of the simulated cases received at least a realism score of 4 out of 5. This means an improvement in realism compared to when lesions without processing are inserted at random locations in the patient background images. Additionally, the automated method eliminates the dependency on the researcher performing the VCT.
|