title: Adaptive imaging using the generalized coherence factor.
abstract: Sound-velocity inhomogeneities degrade both spatial and contrast resolutions. This paper proposes a new adaptive imaging technique that uses the generalized coherence factor (GCF) to reduce the focusing errors resulting from the sound-velocity inhomogeneities. The GCF is derived from the spatial spectrum of the received aperture data after proper receive delays have been applied. It is defined as the ratio of the spectral energy within a prespecified low-frequency range to the total energy. It is demonstrated that the low-frequency component of the spectrum corresponds to the coherent portion of the received data, and that the high-frequency component corresponds to the incoherent portion. Hence, the GCF reduces to the coherence factor defined in the literature if the prespecified low-frequency range is restricted to dc only. In addition, the GCF is also an index of the focusing quality and can be used as a weighting factor for the reconstructed image. The efficacy of the GCF technique is demonstrated for focusing errors resulting from the sound-velocity inhomogeneities. Simulations and real ultrasound data are used to evaluate the efficacy of the proposed GCF technique. The characteristics of the GCF, including the effects of the signal-to-noise ratio and the number of channels, are also discussed. The GCF technique also is compared with the correlation-based technique and the parallel adaptive receive compensation algorithm; the improvement in image quality obtained with the proposed technique rivals that of the latter technique. In the presence of a displaced phase screen, this proposed technique also outperforms the correlation-based technique. Computational complexity and implementation issues also are addressed.
authors.affiliation: Department of Electrical Engineering, National Taiwan University, Taipei, ROC.
authors.forename: Pai-Chi
authors.initials: PC
authors.lastname: Li
authors.forename: Meng-Lin
authors.initials: ML
authors.lastname: Li
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003198:Computer Simulation; D003560:Cysts / Q000000981:diagnostic imaging*; D005246:Feedback; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D008954:Models, Biological; D019047:Phantoms, Imaging; D011786:Quality Control; D012542:Scattering, Radiation; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D014159:Transducers; D014463:Ultrasonography / Q000295:instrumentation / Q000379:methods*