The significance of the broken ray transform (BRT) is due to its occurrence in a number of modalities spanning optical, x-ray, and nuclear imaging. When data are indexed by the scatter location, the BRT is both linear and shift invariant. Analyzing the BRT as a linear system provides a new perspective on the inverse problem. In this framework we contrast prior inversion formulas and identify numerical issues. This has practical benefits as well. We clarify the extent of data required for global reconstruction by decomposing the BRT as a linear combination of cone beam transforms. Additionally we leverage the two dimensional Fourier transform to derive new inversion formulas that are computationally efficient for arbitrary scatter angles. Results of numerical simulations are presented.

In this article, the authors investigate the relationship between family‐of‐origin experiences and counseling effectiveness of counselors in training.

Psychosocial and personality factors are known to contribute to the maintenance of and recovery from chronic pain conditions but less is known about their influence on the efficacy of pain treatment programs. The purpose of the present study is to examine the ability of the Millon Behavioral Medicine Diagnostic (MBMD), a broadband measure of personality and psychosocial characteristics, to predict response to multidisciplinary pain treatment. 93 patients completed the MBMD, and ratings of current pain and average pain on an 11 point scale, prior to a multidisciplinary pain management program. Ratings of current and average pain were completed upon program completion. Participants were classified as "successful" or "unsuccessful" program completers based on pain reductions of ≥2 points. After program completion, 47 % of participants evidenced successful pain reductions. These successful participants had lower scores on depression and on coping style scales measuring introversive, inhibited, and dejected tendencies at baseline. Additionally, lower pre-treatment depression scores and lower scores on each of these coping style scales predicted lower pain ratings at discharge independent of educational level and pre-treatment pain ratings. The MBMD may be a useful tool to delineate patients who are likely to make significant treatment gains in intense, multidisciplinary pain treatment programs.

No abstract

A: Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays. K : Computerized Tomography (CT) and Computed Radiography (CR); Plasma diagnostics -interferometry, spectroscopy and imaging 1Corresponding author. 2See the author list of Overview of the JET preparation for Deuterium-Tritium Operation by E. Joffrin et al. in Nucl.