A new regularization technique for limited-view sound-speed imaging

Reconstructing sound-speed maps from the limited view offered by a linear array of ultrasonic sensors has been a long-standing challenge in medical diagnostics and nondestructive evaluation. Because of the limited range of angles that can be used to interrogate the volume beneath the array, the inverse problem of retrieving sound-speed maps from scattering measurements is highly ill-posed. The missing angles cause significant artifacts that degrade the image by altering the values of sound speed and producing ghost features. This paper introduces the virtual image space component iterative technique (VISCIT), which addresses the limited-view problem by introducing a new regularization technique which iteratively compensates for the missing components by applying an adaptive threshold to the reconstruction. The effectiveness of the method in yielding high-accuracy sound-speed maps is demonstrated using a complex numerical phantom and validated experimentally with an agar phantom. It is shown that sound-speed contrast as low as 1.3% is readily detectable, thus paving the way for more sensitive and selective detection of damage precursors and early stage diseases.