Search

Item does not contain fulltext, Breast computed tomography (BCT) is an emerging application of X-ray tomography in radiological practice. A few clinical prototypes are under evaluation in hospitals and new systems are under development aiming at improving spatial and contrast resolution and reducing delivered dose. At the same time, synchrotron-radiation phase-contrast mammography has been demonstrated to offer substantial advantages when compared with conventional mammography. At Elettra, the Italian synchrotron radiation facility, a clinical program of phase-contrast BCT based on the free-space propagation approach is under development. In this paper, full-volume breast samples imaged with a beam energy of 32 keV delivering a mean glandular dose of 5 mGy are presented. The whole acquisition setup mimics a clinical study in order to evaluate its feasibility in terms of acquisition time and image quality. Acquisitions are performed using a high-resolution CdTe photon-counting detector and the projection data are processed via a phase-retrieval algorithm. Tomographic reconstructions are compared with conventional mammographic images acquired prior to surgery and with histologic examinations. Results indicate that BCT with monochromatic beam and free-space propagation phase-contrast imaging provide relevant three-dimensional insights of breast morphology at clinically acceptable doses and scan times.

© 2017, The Natural Computing Applications Forum. This paper proposes a novel method for robust visual tracking of arbitrary objects, based on the combination of image-based prediction and position refinement by weighted correlation. The effectiveness of the proposed approach is demonstrated on a challenging set of dynamic video sequences, extracted from the final of triple jump at the London 2012 Summer Olympics. A comparison is made against five baseline tracking systems. The novel system shows remarkable superior performances with respect to the other methods, in all considered cases characterized by changing background, and a large variety of articulated motions. The novel architecture, from here onward named 2D Recurrent Neural Network (2D-RNN), is derived from the well-known recurrent neural network model and adopts nearest neighborhood connections between the input and context layers in order to store the temporal information content of the video. Starting from the selection of the object of interest in the first frame, neural computation is applied to predict the position of the target in each video frame. Normalized cross-correlation is then applied to refine the predicted target position. 2D-RNN ensures limited complexity, great adaptability and a very fast learning time. At the same time, it shows on the considered dataset fast execution times and very good accuracy, making this approach an excellent candidate for automated analysis of complex video streams.

Hadrontherapy treatments use charged particles (e.g. protons and carbon ions) to treat tumors. During a therapeutic treatment with carbon ions, the beam undergoes nuclear fragmentation processes giving rise to significant yields of secondary charged particles. An accurate prediction of these production rates is necessary to estimate precisely the dose deposited into the tumours and the surrounding healthy tissues. Nowadays, a limited set of double differential carbon fragmentation cross-section is available. Experimental data are necessary to benchmark Monte Carlo simulations for their use in hadrontherapy. The purpose of the FIRST experiment is to study nuclear fragmentation processes of ions with kinetic energy in the range from 100 to 1000 MeV/u. Tracks are reconstructed using information from a pixel silicon detector based on the CMOS technology. The performances achieved using this device for hadrontherapy purpose are discussed. For each reconstruction step (clustering, tracking and vertexing), different methods are implemented. The algorithm performances and the accuracy on reconstructed observables are evaluated on the basis of simulated and experimental data.

The knowledge about fragmentation processes in ion-ion interactions is fundamental in hadrontherapy and radiation protection in space missions. Hadrontherapy, based on 12C, features many advantages with respect to conventional radiation therapy with photons due to the possibility to shape the dose delivery region in tissues but side effects of the projectile fragmentation in healthy tissues are not negligible. NASA recently pointed out that measurements for some light ions and kinetic energies are missing in nuclear fragmentation databases. FIRST experiment aims to measure the fragmentation doubledifferential cross section of 12C in the energy range 100-1000 MeV/u on several elements, constituents of organic tissues and electronic devices, in order to fill some of the mentioned lack of information on light ions. A first set of data has been taken in 2011 at GSI (Darmstadt), using 12C beam at 400 MeV/u on C and Au targets. About 3·107 events with C target and 5 × 106 with Au target were recorded. Together with these data other sets of runs have been collected to calibrate the forward part of the whole experimental setup, the ToF-Wall. The calibration procedure and the detector performances, which fit the experiment requirements for what concerns efficiency, resolution and stability, will be illustrated. Moreover, some preliminary results concerning the 12C-12C elastic scattering, in agreement with the Rutherford model, will be presented.

Thomson scattering x-ray sources can provide spectral distributions that are ideally suited for mammography with sufficient fluence rates. In this article, the authors investigate the effects of different spectral distributions on the image quality in simulated images of a breast mammographic phantom containing details of different compositions and thicknesses. They simulated monochromatic, quasimonochromatic, and polychromatic x-ray sources in order to define the energy for maximum figure of merit (signal-difference-to-noise ratio squared/mean glandular dose), the effect of an energy spread, and the effect of the presence of higher-order harmonics. The advantages of these sources with respect to conventional polychromatic sources as a function of phantom and detail thickness were also investigated. The results show that the energy for the figure of merit peak is between 16 and 27.4 keV, depending on the phantom thickness and detail composition and thickness. An energy spread of about 1 keV standard deviation, easily achievable with compact x-ray sources, does not appreciably affect the image quality.

A detailed knowledge of the light ions interaction processes with matter is of great interest in basic and applied physics. As an example, particle therapy and space radioprotection require highly accurate fragmentation cross-section measurements to develop shielding materials and estimate acute and late health risks for manned missions in space and for treatment planning in particle therapy. The Fragmentation of Ions Relevant for Space and Therapy experiment at the Helmholtz Center for Heavy Ion research (GSI) was designed and built by an international collaboration from France, Germany, Italy, and Spain for studying the collisions of a C-12 ion beam with thin targets. The collaboration's main purpose is to provide the double-differential cross-section measurement of carbon-ion fragmentation at energies that are relevant for both tumor therapy and space radiation protection applications. Fragmentation cross sections of light ions impinging on a wide range of thin targets are also essential to validate the nuclear models implemented in MC simulations that, in such an energy range, fail to reproduce the data with the required accuracy. This paper presents the single differential carbon-ion fragmentation cross sections on a thin gold target, measured as a function of the fragment angle and kinetic energy in the forward angular region (theta less than or similar to 6 degrees), aiming to provide useful data for the benchmarking of the simulation softwares used in light ions fragmentation applications. The C-12 ions used in the measurement were accelerated at the energy of 400 MeV/nucleon by the SIS (heavy ion synchrotron) GSI facility.

© Springer International Publishing Switzerland 2016. The efficient tracking of articulated bodies over time is an essential element of pattern recognition and dynamic scenes analysis. This paper proposes a novel method for robust visual tracking, based on the combination of image-based prediction and weighted correlation. Starting from an initial guess, neural computation is applied to predict the position of the target in each video frame. Normalized cross-correlation is then applied to refine the predicted target position. Image-based prediction relies on a novel architecture, derived from the Elman’s Recurrent Neural Networks and adopting nearest neighborhood connections between the input and context layers in order to store the temporal information content of the video. The proposed architecture, named 2D Recurrent Neural Network, ensures both a limited complexity and a very fast learning stage. At the same time, it guarantees fast execution times and excellent accuracy for the considered tracking task. The effectiveness of the proposed approach is demonstrated on a very challenging set of dynamic image sequences, extracted from the final of triple jump at the London 2012 Summer Olympics. The system shows remarkable performance in all considered cases, characterized by changing background and a large variety of articulated motions.