Biomedical subjects

J W Trobaugh

Publications and source records attributed to J W Trobaugh.

4 recordsLinked to original sources

PubMed2005

Non-invasive estimation of hyperthermia temperatures with ultrasound.

Ultrasound is an attractive modality for temperature monitoring because it is non-ionizing, convenient, inexpensive and has relatively simple signal processing requirements. This modality may be useful for temperature estimation if a temperature-dependent ultrasonic parameter can be identified, measured and calibrated. The most prominent methods for using ultrasound as a non-invasive thermometer exploit either (1) echo shifts due to changes in tissue thermal expansion and speed of sound (SOS), (2) variation in the attenuation coefficient or (3) change in backscattered energy from tissue inhomogeneities. The use of echo shifts has received the most attention in the last decade. By tracking scattering volumes and measuring the time shift of received echoes, investigators have been able to predict the temperature from a region of interest both theoretically and experimentally in phantoms, in isolated tissue regions in vitro and preliminary in vivo studies. A limitation of this method for general temperature monitoring is that prior knowledge of both SOS and thermal-expansion coefficients is necessary. Acoustic attenuation is dependent on temperature, but with significant changes occurring only at temperatures above 50 degrees C, which may lead to its use in thermal ablation therapies. Minimal change in attenuation, however, below this temperature range reduces its attractiveness for use in clinical hyperthermia. Models and measurements of the change in backscattered energy suggest that, over the clinical hyperthermia temperature range, changes in backscattered energy are dependent on the properties of individual scatterers or scattering regions. Calibration of the backscattered energy from different tissue regions is an important goal of this approach. All methods must be able to cope with motion of the image features on which temperature estimates are based. A crucial step in identifying a viable ultrasonic approach to temperature estimation is its performance during in vivo tests.

Animals↗

PubMed2001

A physically based, probabilistic model for ultrasonic images incorporating shape, microstructure, and system characteristics.

Recent successes with Bayesian methods for analysis of shape in medical images have motivated our development of a shape-based data likelihood for ultrasound, the foundation of which is a computationally feasible, pixel-based, probabilistic image model. Previous probabilistic models for ultrasound generally assume an analytic form, e.g., Rayleigh, Rician, K, Generalized K, etc., then attempt to fit data to the model. Assumptions and intensive computation inherent in such an approach make it unsuitable for our purposes. In the pursuit of a new model, we have described previously a physical model for image formation that incorporates the imaging system characteristics, the surface shape, and the surface microstructure. That physical model was validated via a visual comparison of simulated and actual images of a cadaveric vertebra. In this work, a random phasor sum representation of the physical model provides the basis for a probabilistic form. In contrast to existing probabilistic models, we compute the amplitude mean and variance directly from the physical model. These statistics can be displayed as images to characterize the tissue, but, more importantly, they permit the subsequent assignment of a suitable density function to each pixel for the purposes of constructing a data likelihood. The order of these steps, i.e., first computing the statistics and then assigning a density function, permits the inclusion of the local surface shape, the surface microstructure, and the system characteristics at every image pixel without violating the physical model. Currently, the value of the SNR0, the ratio of the mean to the standard deviation, is used to estimate whether a pixel is Rayleigh- or non-Rayleigh-distributed. This assessment forms the basis for a data likelihood constructed as a product of Rayleigh and Gaussian density functions describing the individual image pixels.

Humans↗

PubMedDate not supplied

Three-dimensional imaging with stereotactic ultrasonography.

Stereotactic ultrasonography is a technique for determining the position and orientation of B-mode ultrasound images in a reference coordinate system. A technique for constructing three-dimensional (3D) image volumes has been developed that uses this new technology. Given several registered images, a 3D volume is constructed either by a "nearest-neighbor" or a "closest-points" interpolation approach. The resulting volume can be rendered using 3D rendering software. In addition, the voxels in the volume are at known positions allowing determination of position for structures in the volume. Results are shown for various test cases, and applicability to medical imaging applications and stereotactic neurosurgery is discussed.

Algorithms↗

PubMedDate not supplied

Frameless stereotactic ultrasonography: method and applications.

In stereotactic neurosurgery, computed tomography (CT) and magnetic resonance (MR) images are registered in a coordinate system defined with respect to the skull. By intraoperatively tracking the coordinate position of a surgical instrument, various displays can be formed which show the position of the instrument in the MR and/or CT images. However, the accuracy of this display varies because intracranial structures may shift or warp from their position prior to surgery. Ultrasonic imaging systems provide real-time images of the brain, but structures in these images are difficult to interpret because the images are based on ultrasonic echoes. A method has been developed for the real-time registration of these images. With this registration, software continuously updates a corresponding image constructed from the set of MR and/or CT images used for guidance. By developing this second view of the structures in the ultrasound image, the surgeon can easily interpret the ultrasound image, and it becomes possible to determine the extent of the intra-operative structure shift between the two images.

Algorithms↗