Index of content:
Volume 104, Issue 6, December 1998
- BIOACOUSTICS 
104(1998); http://dx.doi.org/10.1121/1.423944View Description Hide Description
Analysis of acoustic signals recorded from the U.S. Navy’s SOund SUrveillance System (SOSUS) was used to detect and locate blue whale (Balaenoptera musculus) calls offshore in the northeast Pacific. The long, low-frequency components of these calls are characteristic of calls recorded in the presence of blue whales elsewhere in the world. Mean values for frequency and time characteristics from field-recorded blue whale calls were used to develop a simple matched filter for detecting such calls in noisy time series. The matched filter was applied to signals from three different SOSUS arrays off the coast of the Pacific Northwest to detect and associate individual calls from the same animal on the different arrays. A U.S. Navy maritime patrol aircraft was directed to an area where blue whale calls had been detected on SOSUS using these methods, and the presence of a vocalizing blue whale was confirmed at the site with field recordings from sonobuoys.
104(1998); http://dx.doi.org/10.1121/1.423945View Description Hide Description
This study reports the use of unsupervised, self-organizing neural network to categorize the repertoire of false killer whale vocalizations. Self-organizing networks are capable of detecting patterns in their input and partitioning those patterns into categories without requiring that the number or types of categories be predefined. The inputs for the neural networks were two-dimensional characterization of false killer whale vocalizations, where each vocalization was characterized by a sequence of short-time measurements of duty cycle and peak frequency. The first neural network used competitive learning, where units in a competitive layer distributed themselves to recognize frequently presented input vectors. This network resulted in classes representing typical patterns in the vocalizations. The second network was a Kohonen feature map which organized the outputs topologically, providing a graphical organization of pattern relationships. The networks performed well as measured by (1) the average correlation between the input vectors and the weight vectors for each category, and (2) the ability of the networks to classify novel vocalizations. The techniques used in this study could easily be applied to other species and facilitate the development of objective, comprehensive repertoire models.
104(1998); http://dx.doi.org/10.1121/1.423946View Description Hide Description
The relative importance of the fat and muscle layers of the human abdominal wall in producing ultrasonic wavefront distortion was assessed by means of direct measurements. Specimens employed included six whole abdominal wall specimens and twelve partial specimens obtained by dividing each whole specimen into a fat and a muscle layer. In the measurement technique employed, a hemispheric transducer transmitted a 3.75-MHz ultrasonic pulse through a tissue section. The received wavefront was measured by a linear array translated in the elevation direction to synthesize a two-dimensional aperture. Insertion loss was also measured at various locations on each specimen. Differences in arrival time and energy level between the measured waveforms and computed references that account for geometric delay and spreading were calculated. After correction for the effects of geometry, the received waveforms were synthetically focused. The characteristics of the distortion produced by each specimen and the quality of the resulting focus were analyzed and compared. The measurements show that muscle produces greater arrival time distortion than fat while fat produces greater energy level distortion than muscle, but that the distortion produced by the entire abdominal wall is not equivalent to a simple combination of distortion effects produced by the layers. The results also indicate that both fat and muscle layers contribute significantly to the distortion of ultrasonic beams by the abdominal wall. However, the spatial characteristics of the distortion produced by fat and muscle layers differ substantially. Distortion produced by muscle layers, as well as focal images aberrated by muscle layers, show considerable anisotropy associated with muscle fiber orientation. Distortion produced by fat layers shows smaller-scale, granular structure associated with scattering from the septa surrounding individual fat lobules. Thick layers of fat may be expected to cause poor image quality due to both scattering and bulk absorption effects, while thick muscle layers may be expected to cause focus aberration due to large arrival time fluctuations. Correction of aberrated focuses using time-shift compensation shows more complete correction for muscle sections than for fat sections, so that correction methods based on phase screen models may be more appropriate for muscle layers than for fat layers.
104(1998); http://dx.doi.org/10.1121/1.423947View Description Hide Description
Wavefront propagation through the abdominal wall was simulated using a finite-difference time-domain implementation of the linearized wave propagationequations for a lossless, inhomogeneous, two-dimensional fluid as well as a simplified straight-ray model for a two-dimensional absorbing medium. Scanned images of six human abdominal wall cross sections provided the data for the propagation media in the simulations. The images were mapped into regions of fat, muscle, and connective tissue, each of which was assigned uniform sound speed, density, and absorption values. Propagation was simulated through each whole specimen as well as through each fat layer and muscle layer individually. Wavefronts computed by the finite-difference method contained arrival time, energy level, and wave shape distortion similar to that in measurements. Straight-ray simulations produced arrival time fluctuations similar to measurements but produced much smaller energy level fluctuations. These simulations confirm that both fat and muscle produce significant wavefront distortion and that distortion produced by fat sections differs from that produced by muscle sections. Spatial correlation of distortion with tissue composition suggests that most major arrival time fluctuations are caused by propagation through large-scale inhomogeneities such as fatty regions within muscle layers, while most amplitude and waveform variations are the result of scattering from smaller inhomogeneities such as septa within the subcutaneous fat. Additional finite-difference simulations performed using uniform-layer models of the abdominal wall indicate that wavefront distortion is primarily caused by tissue structures and inhomogeneities rather than by refraction at layer interfaces or by variations in layer thicknesses.
In vitro characterization of a novel, tissue-targeted ultrasonic contrast system with acoustic microscopy104(1998); http://dx.doi.org/10.1121/1.423948View Description Hide Description
Targeted ultrasonic contrast systems are designed to enhance the reflectivity of selected tissuesin vivo [Lanza et al., Circulation 94, 3334 (1996)]. In particular, these agents hold promise for the minimally invasive diagnosis and treatment of a wide array of pathologies, most notably tumors, thromboses, and inflamed tissues. In the present study, acoustic microscopy was used to assess the efficacy of a novel, perfluorocarbon based contrast agent to enhance the inherent acoustic reflectivity of biological and synthetic substrates. Data from these experiments were used to postulate a simple model describing the observed enhancements. Frequency averaged reflectivity (30–55 MHz) was shown to increase for nitrocellulose membranes with targeted contrast. Enhancements of and for plasma and whole blood clots, respectively, were measured between 20 and 35 MHz. A proposed acoustic transmission line model predicted the targeted contrast system would increase the acoustic reflectivity of the nitrocellulose membrane, whole blood clot, and fibrin plasma clot by 2.6, 8.0, and 31.8 dB, respectively. These predictions were in reasonable agreement with the experimental results of this paper. In conclusion, acoustic microscopy provides a rapid and sensitive approach for in vitro characterization, development, and testing of mathematical models of targeted contrast systems. Given the current demand for targeted contrast systems for medicaldiagnostic and therapeutic use, the use of acoustic microscopy may provide a useful tool in the development of these agents.