Generation of Synthetic-Focus Images from Pulse-Echo Ultrasound using Difference Equations

To produce a complete-dataset, pulse-echo image requires a knowledge of the time of flight (TOF) from each source to each sensor in the transducer array for each site to be imaged. Increasing the speed of TOF calculation is important in adaptive-focus schemes. The authors determined TOF more rapidly than via direct calculation by representing TOF surfaces by two-dimensional (2-D), positive-integer-degree polynomials implemented in their forward-difference form. Errors which accumulate due to the use of a difference equation depend on the degree of the polynomial and on the size of the image. The number of bits needed to address echo samples in backscatter memory and the allowable error define the minimum precision needed for accurate values of TOF, Accurate calculation of TOF, expressed as 10-b addresses in backscatter memory, for each pixel in a 512 x 512 image with a second-degree difference equation requires 44 b of precision, Using the complete dataset from a 32-element array and a second-degree approximation to TOF on a typical graphics workstation reduced generation time of a 512 x 512 image from 702 to 239 s. Parallel formulation of both the TOF calculation and the retrieval and summation of echo samples resulted in significant further reduction in image-generation time. Parallel implementation on a SIMD array with 4096 processors, each of which had an indirect-addressing mode, allowed the generation of a 512 x 512 image in 16.3 s

Software for Modeling Ultrasound Breast Cancer Imaging

Computer-based models are increasingly used in biomedical imaging research to clarify links between anatomical structure, imaging physics, and the information content of medical images. A few three-dimensional breast tissue software models have been developed for mammography simulations to optimize current mammography systems or to test novel systems. It would be beneficial in the development of ultrasound breast imaging to have a similar computational model for simulation. A three-dimensional breast anatomy model with the lobular ducts, periductal and intralobular loose fibrous tissue, interlobular dense fibrous tissue, fat, and skin has been implemented. The parenchymal density of the model can be varied from about 20 to 75% to represent a range of clinically relevant densities. The anatomical model was used as a foundation for a three-dimensional breast tumour model. The tumour model was designed to mimic the ultrasound appearance of features used in tumour classification. Simulated two-dimensional ultrasound images were synthesized from the models using a first-order k-space propagation simulator. Similar to clinical ultrasound images, the simulated images of normal breast tissue exhibited non-Rayleigh speckle in regions of interest consisting of primarily fatty, primarily fibroglandular, and mixed tissue types. The simulated images of tumours reproduced several shape and margin features used in breast tumour diagnosis. The ultrasound wavefront distortion produced in simulations using the anatomical model was evaluated and a second method of modeling wavefront distortion was also proposed in which 10 to 12 irregularly shaped, strongly scattering inclusions were iii superimposed on multiple parallel time-shift screens to create the screen-inclusion model. Simulations of planar pulsed wave propagation through the two proposed models, a conventional parallel time-shift screen model, and digitized breast tissue specimens were compared. The anatomical model and screen-inclusion model were able to produce arrival-time fluctuation and energy-level fluctuation characteristics comparable to the digitized tissue specimens that the parallel-screen model was unable to reproduce. This software is expected to be valuable for imaging simulations that require accurate and detailed representation of the ultrasound characteristics of breast tumours

Ultrasound Imaging

In this book, we present a dozen state of the art developments for ultrasound imaging, for example, hardware implementation, transducer, beamforming, signal processing, measurement of elasticity and diagnosis. The editors would like to thank all the chapter authors, who focused on the publication of this book

Medical ultrasonics: dynamic focusing in diagnostic imaging

The design and implementation of an ultrasonic dynamic focusing annular array system is described. The array is designed for use as a contact transducer and for eventual incorporation into the head of a real-time mechanical scanner.A solution for the continuous wave field of a focused thin ring array is used to examine the effects of the number of rings, ring arrangement and apodisation of the array aperture on its focal plane response. Other aspects of array design are also considered. A suitable method of array fabrication, based on printed circuit board techniques, is described.The design and implementation of an electronic system for the generation, detection and processing of the array signals is given. Digital techniques are used to implement the dynamic delays.The dynamic focusing capabilities of the array are confirmed experimentally. Dynamic focusing of the reception response of the array is usually combined with a fixed focus on transmission. The compromise of fixed focusing on transmission may be overcome by applying the idea of Synthetic Aperture Imaging. An effective dynamic focus is then achieved on both transmission and reception. This novel application to annular arrays is investigated experimentally, and significant advantages are confirmed, however, at the expense of a lower pulse repetition frequency

Toward quantitative limited-angle ultrasound reflection tomography to inform abdominal HIFU treatment planning

High-Intensity Focused Ultrasound (HIFU) is a treatment modality for solid cancers of the liver and pancreas which is non-invasive and free from many of the side-effects of radiotherapy and chemotherapy. The safety and efficacy of abdominal HIFU treatment is dependent on the ability to bring the therapeutic sound waves to a small focal ”lesion” of known and controllable location within the patient anatomy. To achieve this, pre-treatment planning typically includes a numerical simulation of the therapeutic ultrasound beam, in which anatomical compartment locations are derived from computed tomography or magnetic resonance images. In such planning simulations, acoustic properties such as density and speed-of-sound are assumed for the relevant tissues which are rarely, if ever, determined specifically for the patient. These properties are known to vary between patients and disease states of tissues, and to influence the intensity and location of the HIFU lesion. The subject of this thesis is the problem of non-invasive patient-specific measurement of acoustic tissue properties. The appropriate method, also, of establishing spatial correspondence between physical ultrasound transducers and modeled (imaged) anatomy via multimodal image reg-istration is also investigated; this is of relevance both to acoustic tissue property estimation and to the guidance of HIFU delivery itself. First, the principle of a method is demonstrated with which acoustic properties can be recovered for several tissues simultaneously using reflection ultrasound, given accurate knowledge of the physical locations of tissue compartments. Second, the method is developed to allow for some inaccuracy in this knowledge commensurate with the inaccuracy typical in abdominal multimodal image registration. Third, several current multimodal image registration techniques, and two novel modifications, are compared for accuracy and robustness. In conclusion, relevant acoustic tissue properties can, in principle, be estimated using reflected ultrasound data that could be acquired using diagnostic imaging transducers in a clinical setting

Development, Optimization and Clinical Evaluation Of Algorithms For Ultrasound Data Analysis Used In Selected Medical Applications.

The assessment of soft and hard tissues is critical when selecting appropriate protocols for restorative and regenerative therapy in the field of dental surgery. The chosen treatment methodology will have significant ramifications on healing time, success rate and overall long-time oral health. Currently used diagnostic methods are limited to visual and invasive assessments; they are often user-dependent, inaccurate and result in misinterpretation. As such, the clinical need has been identified for objective tissue characterization, and the proposed novel ultrasound-based approach was designed to address the identified need. The device prototype consists of a miniaturized probe with a specifically designed ultrasonic transducer, electronics responsible for signal generation and acquisition, as well as an optimized signal processing algorithm required for data analysis. An algorithm where signals are being processed and features extracted in real-time has been implemented and studied. An in-depth algorithm performance study has been presented on synthetic signals. Further, in-vitro laboratory experiments were performed using the developed device with the algorithm implemented in software on animal-based samples. Results validated the capabilities of the new system to reproduce gingival assessment rapidly and effectively. The developed device has met clinical usability requirements for effectiveness and performance