Yao Lu PhD, Presenter: Nothing to Disclose

Heang-Ping Chan PhD, Abstract Co-Author: Research collaboration, General Electric Company

Jun Wei PhD, Abstract Co-Author: Nothing to Disclose

Ravi Kumar Samala PhD, Abstract Co-Author: Nothing to Disclose

Lubomir M. Hadjiiski PhD, Abstract Co-Author: Nothing to Disclose

Paul L. Carson PhD, Abstract Co-Author: Research collaboration, General Electric Company Research collaboration, Sonetics Ultrasound, Inc Research collaboration, ZONARE Medical Systems, Inc Research collaboration, Light Age, Inc

Both mass and microcalcifications (MCs) are important signs for breast cancer. Most regularization methods depend on local gradient and may treat the ill-defined margins or subtle spiculations of masses and subtle MCs as noise because of their small gradient. In this study, we developed a new bilateral-filter regularization method utilizing the multiscale structure (MBiF) of the image to enhance subtle edges and MCs in DBT.

DBT data were first decomposed into frequency bands using the Laplacian Pyramid Decomposition. The mass margins and spiculations fall into the low-frequency (LF) bands while MCs, edges and noise fall into the high-frequency (HF) bands. Bilateral filtering with domain and range filters optimized for subtle signals was applied to the HF bands to exploit simultaneously the spatial and gray level information for enhancing the signals while suppressing noise. The image was reconstructed from the Laplacian pyramid after bilateral regularization in selected frequency bands. With IRB approval, DBT of subjects with MCs or masses was acquired with a GE prototype DBT system. DBT was reconstructed with SART regularized by MBiF and the total p-norm variation (TpV) method. The full width at half maximum (FWHM) of the gray-level profile of MCs or spiculations and the contrast-to-noise ratio (CNR) of MCs were used as sharpness and contrast measures to compare the two methods and without regularization (NR).

MBiF reduced spurious noise and contouring artifacts compared to TpV, thus preserving the image quality of the structured background. MBiF achieved 100-200% higher CNR for large MCs and 50-100% higher CNR for subtle MCs than NR, and 50-100% higher CNR than TpV for all MCs. The FWHMs of MCs were comparable among different methods. For spiculated masses, TpV blurred the spiculations and margins while MBiF preserved the edge sharpness and enhanced the mass margins. The FWHM of subtle spiculations by TpV was 25% larger than those by MBiF and NR.

The new MBiF method enhanced the CNR of MCs and preserved the sharpness of MCs and spiculated masses. MBiF provided better image quality of the structured background and was superior to TpV and NR for both MCs and masses.

A regularized DBT reconstruction method that reduces noise and enhances the visibility of both MCs and masses may improve breast cancer detection and patient care without increasing dose.

Lu, Y, Chan, H, Wei, J, Samala, R, Hadjiiski, L, Carson, P, Multiscale Bilateral Regularization in Digital Breast Tomosynthesis (DBT).  Radiological Society of North America 2012 Scientific Assembly and Annual Meeting, November 25 - November 30, 2012 ,Chicago IL. http://archive.rsna.org/2012/12034478.html