A blind-deblurring method based on a compressed-sensing scheme in digital breast tomosynthesis

Abstract Background and objective Digital breast tomosynthesis (DBT) is a well-established multiplanar imaging modality in breast examinations designed to overcome the limitations of conventional mammography. However, reconstructed DBT images from the acquired projection data are often limited in image performance due mainly to blur artifacts resulting from inherent aspects of imaging systems, including detector resolution and the finite focal spot of the x-ray tube. Methods We investigated an effective blind-deblurring method based on a compressed-sensing scheme in an attempt to solve the blurring problem in DBT. We implemented the proposed algorithm and performed a systematic simulation and an experiment to demonstrate its viability. In both simulation and experiment, all of the projection data were taken with a tomographic angle of θ  = 32° and an angle step of Δ θ  = 2°. The proposed deblurring algorithm was then applied to the projection data before performing the common filtered-backprojection-based DBT reconstruction process. Results The deblurred projection images showed much better image performance compared with the blurred projection images, demonstrating the viability of the proposed blind-deblurring scheme in conventional radiography. The PSNR and RMSE characteristics of the deblurred DBT image improved by factors of approximately 1.63 and 0.37, respectively, compared with those of the blurred DBT image. Conclusions Our results indicate that the proposed blind-deblurring method was effective in reducing the blurring problem in both DBT and in conventional radiography, excluding additional measurement of the system response function.