Richard R. Leach

Comparison of ultrasound tomography methods in circular geometry

Extremely high quality data was acquired using an experimental ultrasound scanner developed at Lawrence Livermore National Laboratory using a 2D ring geometry with up to 720 transmitter/receiver transducer positions. This unique geometry allows reflection and transmission modes and transmission imaging and quantification of a 3D volume using 2D slice data. Standard image reconstruction methods were applied to the data including straight-ray filtered back projection, reflection tomography, and diffraction tomography. Newer approaches were also tested such as full wave, full wave adjoint method, bent-ray filtered backprojection, and full-aperture tomography. A variety of data sets were collected including a formalin-fixed human breast tissue sample, a commercial ultrasound complex breast phantom, and cylindrical objects with and without inclusions. The resulting reconstruction quality of the images ranges from poor to excellent. The method and results of this study are described including like-data reconstructions produced by different algorithms with side-by-side image comparisons. Comparisons to medical B-scan and x-ray CT scan images are also shown. Reconstruction methods with respect to image quality using resolution, noise, and quantitative accuracy, and computational efficiency metrics will also be discussed.

Characterizing tissue with acoustic parameters derived from ultrasound data

In contrast to standard reflection ultrasound (US), transmission US holds the promise of more thorough tissue characterization by generating quantitative acoustic parameters. We compare results from a conventional US scanner with data acquired using an experimental circular scanner operating at frequencies of 0.3 - 1.5 MHz. Data were obtained on phantoms and a normal, formalin-fixed, excised breast. Both reflection and transmission-based algorithms were used to generate images of reflectivity, sound speed and attenuation.. Images of the phantoms demonstrate the ability to detect sub-mm features and quantify acoustic properties such as sound speed and attenuation. The human breast specimen showed full field evaluation, improved penetration and tissue definition. Comparison with conventional US indicates the potential for better margin definition and acoustic characterization of masses, particularly in the complex scattering environments of human breast tissue. The use of morphology, in the context of reflectivity, sound speed and attenuation, for characterizing tissue, is discussed.

Near Field Intensity Trends of Main Laser Alignment Images in the National Ignition Facility (NIF)

The National Ignition Facility (NIF) utilizes 192 high-energy laser beams focused with enough power and precision on a hydrogen-filled spherical, cryogenic target to potentially initiate a fusion reaction. NIF has been operational for six years and during that time, thousands of successful laser firings or shots have been executed. Critical instrument measurements and camera images are carefully recorded for each shot. The result is a massive and complex database or ‘big data’ archive that can be used to investigate the state of the laser system at any point in its history or to locate and track trends in the laser operation over time. In this study, the optical light throughput for more than 1600 NIF shots for each of the 192 main laser beams and 48 quads was measured over a three year period from January 2009 to October 2012. The purpose was to verify that the variation in the transmission of light through the optics performed within design expectations during this time period. Differences between average or integrated intensity from images recorded by the input sensor package (ISP) and by the output sensor package (OSP) in the NIF beam-line were examined. A metric is described for quantifying changes in the integrated intensity measurements. Changes in light transmission from the NIF main laser over the three year time-frame are presented.

Recent advances in automatic alignment system for the National Ignition Facility

The automatic alignment system for the National Ignition Facility (NIF) is a large-scale parallel system that directs all 192 laser beams along the 300-m optical path to a 50-micron focus at target chamber in less than 50 minutes. The system automatically commands 9,000 stepping motors to adjust mirrors and other optics based upon images acquired from high-resolution digital cameras viewing beams at various locations. Forty-five control loops per beamline request image processing services running on a LINUX cluster to analyze these images of the beams and references, and automatically steer the beams toward the target. This paper discusses the upgrades to the NIF automatic alignment system to handle new alignment needs and evolving requirements as related to various types of experiments performed. As NIF becomes a continuously-operated system and more experiments are performed, performance monitoring is increasingly important for maintenance and commissioning work. Data, collected during operations, is analyzed for tuning of the laser and targeting maintenance work. Handling evolving alignment and maintenance needs is expected for the planned 30-year operational life of NIF.

Image processing for the automatic alignment at the national ignition facility

The Automatic Alignment system in the National Ignition Facility is responsible for aligning 192 laser beams using camera sensor images. This paper reviews some of the image processing algorithms that generate the crucial alignment positions.

Detecting objects with partial obstruction at the ARC split beam injector images at the National Ignition Facility

The National Ignition Facility (NIF) utilizes 192 beams, four of which are diverted to create the Advanced Radiographic Capability (ARC) by generating a sequence of short laser pulses. This ARC beam after being converted to X-rays will act as a back lighter to create a radiographic movie and provide an unprecedented insight into the imploding dynamics and serve as a diagnostic for tuning the experimental parameters to achieve fusion. One such beam is the centering beam of the pre-amplifier module which due to a split path obstructs the central square alignment fiducials. This fiducial is used for alignment and also as reference for the programmable spatial shaper (PSS) system. Image processing algorithms are used to process the images and calculate the position of various fiducials in the beam path. We discuss the algorithm to process ARC split beam injector (SBI) centering images with partial fiducial information.

Image analysis algorithms for the advanced radiographic capability (ARC) grating tilt sensor at the National Ignition Facility

The Advance Radiographic Capability (ARC) at the National Ignition Facility (NIF) is a laser system designed to produce a sequence of short pulses used to backlight imploding fuel capsules. Laser pulses from a short-pulse oscillator are dispersed in wavelength into long, low-power pulses, injected in the NIF main laser for amplification, and then compressed into high-power pulses before being directed into the NIF target chamber. In the target chamber, the laser pulses hit targets which produce x-rays used to backlight imploding fuel capsules. Compression of the ARC laser pulses is accomplished with a set of precision-surveyed optical gratings mounted inside of vacuum vessels. The tilt of each grating is monitored by a measurement system consisting of a laser diode, camera and crosshair, all mounted in a pedestal outside of the vacuum vessel, and a mirror mounted on the back of a grating inside the vacuum vessel. The crosshair is mounted in front of the camera, and a diffraction pattern is formed when illuminated with the laser diode beam reflected from the mirror. This diffraction pattern contains information related to relative movements between the grating and the pedestal. Image analysis algorithms have been developed to determine the relative movements between the gratings and pedestal. In the paper we elaborate on features in the diffraction pattern, and describe the image analysis algorithms used to monitor grating tilt changes. Experimental results are provided which indicate the high degree of sensitivity provided by the tilt sensor and image analysis algorithms.

Higher accuracy template for corner cube reflected image

Video images of laser beams are analyzed to determine the position of the laser beams for alignment purpose in the National Ignition Facility (NIF). Algorithms process beam images to facilitate automated laser alignment. One such beam image, known as the corner cube reflected pinhole image, exhibits wide beam quality variations that are processed by a matched-filter-based algorithm. The challenge is to design a representative template that captures these variations while at the same time assuring accurate position determination. This paper describes the development of a new analytical template to accurately estimate the center of a beam with good image quality. The templates are constructed to exploit several key recurring features observed in the beam images. When the beam image quality is low, the algorithm chooses a template that contains fewer features. The algorithm was implemented using a Xilinx Virtex II Pro FPGA implementation that provides a speedup of about 6.4 times over a baseline 3GHz Pentium 4 processor.

Centroid stabilization in alignment of FOA corner cube: designing of a matched filter

The current automation of image-based alignment of NIF high energy laser beams is providing the capability of executing multiple target shots per day. An important aspect of performing multiple shots in a day is to reduce additional time spent aligning specific beams due to perturbations in those beam images. One such alignment is beam centration through the second and third harmonic generating crystals in the final optics assembly (FOA), which employs two retro-reflecting corner cubes to represent the beam center. The FOA houses the frequency conversion crystals for third harmonic generation as the beams enters the target chamber. Beam-to-beam variations and systematic beam changes over time in the FOA corner-cube images can lead to a reduction in accuracy as well as increased convergence durations for the template based centroid detector. This work presents a systematic approach of maintaining FOA corner cube centroid templates so that stable position estimation is applied thereby leading to fast convergence of alignment control loops. In the matched filtering approach, a template is designed based on most recent images taken in the last 60 days. The results show that new filter reduces the divergence of the position estimation of FOA images.

Alignment Mask Design and Image Processing for the Advanced Radiographic Capability (ARC) at the National Ignition Facility

The Advance Radiographic Capability (ARC) at the National Ignition Facility (NIF) is a laser system that employs up to four petawatt (PW) lasers to produce a sequence of short pulses that generate X-rays which backlight high-density inertial confinement fusion (ICF) targets. ARC is designed to produce multiple, sequential X-ray images by using up to eight back lighters. The images will be used to examine the compression and ignition of a cryogenic deuterium-tritium target with tens-of-picosecond temporal resolution during the critical phases of an ICF shot. Multi-frame, hard-X-ray radiography of imploding NIF capsules is a capability which is critical to the success of NIFs missions. As in the NIF system, ARC requires an optical alignment mask that can be inserted and removed as needed for precise positioning of the beam. Due to ARC’s split beam design, inserting the nominal NIF main laser alignment mask in ARC produced a partial blockage of the mask pattern. Requirements for a new mask design were needed. In this paper we describe the ARC mask requirements, the resulting mask design pattern, and the image analysis algorithms used to detect and identify the beam and reference centers required for ARC alignment.