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The National Ignition Facility (NIF) is now producing experimental results for the study of inertial confinement fusion (ICF). These results are captured by complex diagnostic systems and are key to achieving NIF's goal to demonstrate thermonuclear burn of deuterium and tritium fuel in a laboratory setting. High bandwidth gamma-ray fusion-burn measurements and soft X-ray indirect and direct drive energetic measurements are both captured with oscilloscope recording systems that distort or modulate the raw data. The Shot Data Analysis team has developed signal processing corrections for these oscilloscope recording systems through an automated engine. Once these corrections are applied, accurate fundamental quantities can be discerned.

The requirements for beam and target alignment for successful ignition experiments on the National Ignition Facility (NIF) are stringent: the average of beams to the target must be within 25 μm. Beam and target alignment are achieved with the Target Alignment Sensor (TAS). The TAS is a precision optical device that is inserted into target chamber center to facilitate both beam and target alignment. It incorporates two camera views (upper/lower and side) mounted on each of two stage assemblies (jaws) to view and align the target. It also incorporates a large mirror on each of the two assemblies to reflect the alignment beams onto the upper/lower cameras for beam alignment. The TAS is located in the chamber using reference features by viewing it with two external telescope views. The two jaws are adjusted in elevation to match the desired beam and target alignment locations. For some shot setups, a sequence of TAS positions is required to achieve the full setup and alignment. In this paper we describe the TAS, the characterization of the TAS coordinates for beam and target alignment, and summarize pointing shots that demonstrate the accuracy of beam-target alignment.

The 192 laser beams in the National Ignition Facility (NIF) are automatically aligned to the target-chamber center using images obtained through charged coupled device (CCD) cameras. Several of these cameras are in and around the target chamber during an experiment. Current experiments for the National Ignition Campaign are attempting to achieve nuclear fusion. Neutron yields from these high energy fusion shots expose the alignment cameras to neutron radiation. The present work explores modeling and predicting laser alignment performance degradation due to neutron radiation effects, and demonstrates techniques to mitigate performance degradation. Camera performance models have been created based on the measured camera noise from the cumulative single-shot fluence at the camera location. We have found that the effect of the neutron-generated noise for all shots to date have been well within the alignment tolerance of half a pixel, and image processing techniques can be utilized to reduce the effect even further on the beam alignment.

New ultrasound data, obtained with a circular experimental scanner, are compared with data obtained with standard X-ray CT. Ultrasound data obtained by scanning fixed breast tissue were used to generate images of sound speed and reflectivity. The ultrasound images exhibit approximately 1 mm resolution and about 20 dB of dynamic range. All data were obtained in a circular geometry. X-ray CT scans were used to generate X-ray images corresponding to the same 'slices' obtained with the ultrasound scanner. The good match of sensitivity, resolution and angular coverage between the ultrasound and X-ray data makes possible a direct comparison of the three types of images. We present the results of such a comparison for an excised breast fixed in formalin. The results are presented visually using various types of data fusion. A general correspondence between the sound speed, reflectivity and X-ray morphologies is found. The degree to which data fusion can help characterize tissue is assessed by examining the quantitative correlations between the ultrasound and X-ray images.

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.

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 back projection, 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.