ABSTRACT
In this paper, thick-film piezoelectric lead zirconate titanate (PZT) ceramic resonators with thicknesses down to tens of micrometers have been fabricated by tape-casting processing. PZT ceramic resonators with composition near the morphotropic phase boundary and with different dopants added were prepared for piezoelectric transducer applications. Material property characterization for these thick-film PZT resonators is essential for device design and applications. For the property characterization, a recently developed normalized electrical impedance spectrum method was used to determine the electromechanical coefficient and the complex piezoelectric, elastic, and dielectric coefficients from the electrical measurement of resonators using thick films. In this work, nine PZT thick-film resonators have been fabricated and characterized, and two different types of resonators, namely thickness longitudinal and transverse modes, were used for material property characterization. The results were compared with those determined by the IEEE standard method, and they agreed well. It was found that depending on the PZT formulation and dopants, the relative permittivities ε(T)(33)/ε(0) measured at 2 kHz for these thick-films are in the range of 1527 to 4829, piezoelectric stress constants (e(33) in the range of 15 to 26 C/m(2), piezoelectric strain constants (d(31)) in the range of -169 × 10(-12) C/N to -314 × 10(-12) C/N, electromechanical coupling coefficients (k(t)) in the range of 0.48 to 0.53, and k(31) in the range of 0.35 to 0.38. The characterization results shows tape-casting processing can be used to fabricate high-quality PZT thick-film resonators, and the extracted material constants can be used to for device design and application.
ABSTRACT
The automated extraction of brain vessels from magnetic resonance angiography (MRA) has found its applications in vascular disease diagnosis, endovascular operation and neurosurgical planning. In this paper we first present a concise technical review on cerebral vasculature extraction from MRA. It reveals the latest development in the area of vessel extraction. Then we detail the main challenges to the researchers working in the vessel extraction and segmentation area. Based on the review and our experience in the area, we finally present our proposals on ways of developing robust vessel extracting algorithm. Examples of brain vasculature extracted with advanced hybrid approach are shown. Twenty one references are given.
