Optimum switch sizing for class DE amplifier

Recently, integrated class DE ampli fiers without matching networks have been proposed as a compact solution to drive a multi-element piezoelectric ultrasound transducer array for high-intensity focused ultrasound (HIFU) therapy. These transducers produce acoustic energy that translates into heat for tissue ablation. In order to steer the focal zone, each element in the transducer array is driven at a different phase. Hence, there's a need for the power amplifi er with a digital control unit in this application. Since each element in the transducer array has a different electrical characteristic and they have to be driven at the same frequency, it is a challenge to drive all transducers in the array at their optimum conditions. This work introduces strategies to determine efficient driving parameters for an entire transducer array. In addition. a method to improve the power efficiency of the class DE amplifi er by choosing the optimum size for switching MOSFETs is also proposed. During the operation of a class DE ampli fier, losses are caused by the ON resistance and the drivers of the MOSFET gate capacitances. These parameters are directly dependent on the size of the switching MOSFETs. A wider MOSFET will have a higher gate capacitance, but lower ON resistance. With the correct sizing, these losses can be greatly reduced to improve power efficiency and prevent excessive heating. The challenge with this method is the wide selection of transducers with varying impedance. As the load impedance changes, the MOSFET size also needs to be changed to maintain the maximum power efficiency. Also, the proposed design must deliver at least 1 W output power to the transducer in order to produce enough acoustic pressure. This output requirement will limit the available technology that can be used to design the amplifi er. In addition, this work also proposes a new driving circuit that consumes less power to operate, and also allows a full 0-360 degree phase shift. The design is simulated with Spectre simulator using 0.35 m 50V CMOS process data available from Austria Micro Systems. The proposed design can deliver 1422mW of average power to 6-elements transducer array, and achieve up to 91% power efficiency

In-Suit Doppler Technology Assessment

The objective of this program was to perform a technology assessment survey of non-invasive air embolism detection utilizing Doppler ultrasound methodologies. The primary application of this technology will be a continuous monitor for astronauts while performing extravehicular activities (EVA's). The technology assessment was to include: (1) development of a full understanding of all relevant background research; and (2) a survey of the medical ultrasound marketplace for expertise, information, and technical capability relevant to this development. Upon completion of the assessment, LSR was to provide an overview of technological approaches and R&D/manufacturing organizations

Doctor of Philosophy

dissertationCongenital heart defects are classes of birth defects that affect the structure and function of the heart. These defects are attributed to the abnormal or incomplete development of a fetal heart during the first few weeks following conception. The overall detection rate of congenital heart defects during routine prenatal examination is low. This is attributed to the insufficient number of trained personnel in many local health centers where many cases of congenital heart defects go undetected. This dissertation presents a system to identify congenital heart defects to improve pregnancy outcomes and increase their detection rates. The system was developed and its performance assessed in identifying the presence of ventricular defects (congenital heart defects that affect the size of the ventricles) using four-dimensional fetal chocardiographic images. The designed system consists of three components: 1) a fetal heart location estimation component, 2) a fetal heart chamber segmentation component, and 3) a detection component that detects congenital heart defects from the segmented chambers. The location estimation component is used to isolate a fetal heart in any four-dimensional fetal echocardiographic image. It uses a hybrid region of interest extraction method that is robust to speckle noise degradation inherent in all ultrasound images. The location estimation method's performance was analyzed on 130 four-dimensional fetal echocardiographic images by comparison with manually identified fetal heart region of interest. The location estimation method showed good agreement with the manually identified standard using four quantitative indexes: Jaccard index, Sørenson-Dice index, Sensitivity index and Specificity index. The average values of these indexes were measured at 80.70%, 89.19%, 91.04%, and 99.17%, respectively. The fetal heart chamber segmentation component uses velocity vector field estimates computed on frames contained in a four-dimensional image to identify the fetal heart chambers. The velocity vector fields are computed using a histogram-based optical flow technique which is formulated on local image characteristics to reduces the effect of speckle noise and nonuniform echogenicity on the velocity vector field estimates. Features based on the velocity vector field estimates, voxel brightness/intensity values, and voxel Cartesian coordinate positions were extracted and used with kernel k-means algorithm to identify the individual chambers. The segmentation method's performance was evaluated on 130 images from 31 patients by comparing the segmentation results with manually identified fetal heart chambers. Evaluation was based on the Sørenson-Dice index, the absolute volume difference and the Hausdorff distance, with each resulting in per patient average values of 69.92%, 22.08%, and 2.82 mm, respectively. The detection component uses the volumes of the identified fetal heart chambers to flag the possible occurrence of hypoplastic left heart syndrome, a type of congenital heart defect. An empirical volume threshold defined on the relative ratio of adjacent fetal heart chamber volumes obtained manually is used in the detection process. The performance of the detection procedure was assessed by comparison with a set of images with confirmed diagnosis of hypoplastic left heart syndrome and a control group of normal fetal hearts. Of the 130 images considered 18 of 20 (90%) fetal hearts were correctly detected as having hypoplastic left heart syndrome and 84 of 110 (76.36%) fetal hearts were correctly detected as normal in the control group. The results show that the detection system performs better than the overall detection rate for congenital heart defect which is reported to be between 30% and 60%

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Medical image analysis methods for anatomical surface reconstruction using tracked 3D ultrasound

The thesis focuses on a study of techniques for acquisition and reconstruction of surface data from anatomical objects by means of tracked 3D ultrasound. In the context of the work two experimental scanning systems are developed and tested on both artificial objects and biological tissues. The first system is based on the freehand ultrasound principle and utilizes a conventional 2D ultrasound transducer coupled with an electromechanical 3D position tracker. The main properties and the basic features of this system are discussed. A number of experiments show that its accuracy in the close to ideal conditions reaches 1.2 mm RMS. The second proposed system implements the sequential triggered scanning approach. The system consists of an ultrasound machine, a workstation and a scanning body (a moving tank filled with liquid and a transducer fixation block) that performs transducer positioning and tracking functions. The system is tested on artificial and real bones. The performed experiments illustrate that it provides significantly better accuracy than the freehand ultrasound (about 0.2 mm RMS) and allows acquiring regular data with a good precision. This makes such a system a promising tool for orthopaedic and trauma surgeons during contactless X-ray-free examinations of injured extremities. The second major subject of the thesis concerns development of medical image analysis methods for 3D surface reconstruction and 2D object detection. We introduce a method based on mesh-growing surface reconstruction that is designed for noisy and sparse data received from 3D tracked ultrasound scanners. A series of experiments on synthetic and ultrasound data show an appropriate reconstruction accuracy. The reconstruction error is measured as the averaged distance between the faces of the mesh and the points from the cloud. Dependently on the initial settings of the method the error varies in range 0.04 - 0.2% for artificial data and 0.3 - 0.7 mm for ultrasound bone data. The reconstructed surfaces correctly interpolate the original point clouds and demonstrate proper smoothness. The next significant problem considered in the work is 2D object detection. Although medical object detection is not integrated into the developed scanning systems, it can be used as a possible further extension of the systems for automatic detection of specific anatomical structures. We analyse the existent object detection methods and introduce a modification of the one based on the popular Generalized Hough Transform (GHT). Unlike the original GHT, the developed method is invariant to rotation and uniform scaling, and uses an intuitive two-point parametrization. We propose several implementations of the feature-to-vote conversion function with the corresponding vote analysis principles. Special attention is devoted to a study of the hierarchical vote analysis and its probabilistic properties. We introduce a parameter space subdivision strategy that reduces the probability of vote peak omission, and show that it can be efficiently implemented in practice using the Gumbel probability distribution