Small Lesion Detection with Resolution Enhancement Compression PAUL LINDEN, 1 JOSE R. SANCHEZ 2 AND MICHAEL L. OELZE 1 1 Beckman Institute 405 N. Mathews Urbana, Illinois 61801 oelze@illinois.edu 2 Bradley University 1501 W. Bradley Avenue Peoria, IL 61625 A novel coded-excitation method, resolution-enhancement compression (REC), increases the axial resolution and the echo signal-to-noise ratio (eSNR) for an ultrasonic imaging system. The REC tech- nique was examined for its ability to improve lesion detectability. The REC technique was used to dou- ble the –3-dB fractional pulse-echo bandwidth of an ultrasonic source in both simulations and experiments. The increase in usable bandwidth increased lesion detectability compared to conventional pulsing (CP) techniques and coded excitation using a linear chirp (LC). Lesion detectibility was quanti- fied through lesion signal-to-noise ratio (lSNR), which is a metric that quantifies the ability of an isolated observer to detect a focal lesion against a background. In simulations, a higher lSNR value was observed using the REC technique for lesions ranging in size from 1 mm to 8 mm in diameter. In addition, the eSNR was increased by almost 15 dB. To validate simulation results, a hydrogel-cone phantom was con- structed to provide lesions with +6-dB contrast of different sizes. A transducer was scanned perpendicu- lar to the major axis of the cone at different levels to provide lesions of 3, 5 and 8 mm in diameter. The lSNR was estimated for lesions of different sizes and using the three excitation techniques, i.e., CP, LC and REC. In experiments, the lSNR was observed to be higher using the REC technique than the other pulsing techniques. The lSNR scores for REC were higher by 15%, 45% and 40% for the 3, 5 and 8 mm over the other two excitation techniques. The eSNR was increased by 5.7 dB. Therefore, accrding to the lSNR metric, the improvement in spatial resolution from the REC technique resulted in improved detectability of small lesions. KEY WORDS: Coded excitation; lesion signal-to-noise ratio (lSNR); pulse compression; resolution en- hancement compression (REC); Wiener filter. I. INTRODUCTION Improving image quality in a diagnostic ultrasound system is a natural goal. Image quality in ultrasound systems can be characterized by contrast resolution, echo signal-to-noise ratio (eSNR) and spatial resolution. Contrast resolution can be quantified through the con- trast-to-noise ratio (CNR). Typically, contrast between soft tissues is low compared to other imaging modalities. The reflectivity between tissue interfaces can be as low as 1 part in 10 6 . 1 The impedance mismatch between tissue structures results in the reflection or scattering of ultrasound and it is this reflected ultrasound that is used to produce images. Scattering of sound from objects can be classified into three broad categories: specular, diffractive and diffusive. 2 Specular refers to scattering from objects much larger than the wavelength; diffractive to objects about the same size as the wavelength; and diffusive to objects much smaller than a wavelength. The speckle in biomedical ultrasound images results from scat- tering from objects smaller than a wavelength. This scattering is deterministic and cannot be removed by time averaging of the signal. However, information about the subwavelength scatterers can be inferred from the backscattered ultrasound. 3 ULTRASONIC IMAGING 32, 16- 32 (2010) 16 0161-7346/10 $18.00 Copyright 2010 by Dynamedia, Inc. All rights of reproduction in any form reserved.