Specialised Image Capture Systems for a DIET Breast Cancer Screening System

Digital Image-based Elasto-Tomography (DIET) is an emerging technology for non-invasive breast cancer screening. This technology actuates breast tissue and measures the surface motion using digital imaging technology. The internal distribution of stiffness is then reconstructed using Boundary Element or Finite Element Methods (FEM or BEM). However, obtaining accurate imaging at high frequency and high resolution in terms of numbers of pixels is challenging if enough accuracy is to be obtained in the motion sensing to deliver a useful result. The overall focus of such mechatronic and digitally centred systems is on providing a low-cost, radiation dose-free and portable screening system capable of screening numerous patients per day – in direct contrast to current low throughput, non-portable and high cost x-ray and MRI based approaches. Thus, DIET technology relies on obtaining high resolution images of a breasts surface under high frequency actuation, typically in the range of 50-100Hz. Off-the-shelf digital cameras and imaging elements are unable to capture images directly at these speeds. A method is presented for obtaining the required high speed image capture at a resolution of 1280x1024 pixels and actuation frequency of 100Hz. The prototype apparatus presented uses two imaging sensors in combination with frame grabbers and a dSpace™ control system, to produce an automated image capture system. The system integrates a precision controlled strobe lighting system to selectively capture sinusoids at different points in the sinusoidal cycle of response. The final working system produced images that enabled effective 3D motion tracking of the surface of a silicon phantom actuated at 100Hz. The surface of the phantom was strobed at pre-selected phases from 0 to 360 degrees, and an image was captured for each phase. The times at which image capture occurred were calculated for a phase lag increment of 10 degrees resulting in an image effectively every 0.00028s for the actuator cycle of 0.01s. The comparison of the actual trigger times and pre-selected ideal trigger times gave a mean absolute error of 1.4%, thus demonstrating the accuracy of the final system. Final validation is performed using this system to track motion in a silicon gel phantom. The motion is tracked accurately using a novel Euclidean Invariant signature method. Both cameras delivered similar results with over 90% of points tracked to within 1-2%. This level of accuracy confirms the ability to effectively accurately reconstruct the stiffness as validated in other related studies

A microsatellite marker for yellow rust resistance in wheat

Bulk segregant analysis (BSA) was used to identify molecular markers associated with yellow rust disease resistance in wheat (Triticum aestivum L.). DNAs isolated from the selected yellow rust tolerant and susceptible F-2 individuals derived from a cross between yellow rust resistant and susceptible wheat genotypes were used to established a "tolerant" and a "susceptible" DNA pool. The BSA was then performed on these DNA pools using 230 markers that were previously mapped onto the individual wheat chromosomes. One of the SSR markers (Xgwm382) located on chromosome group 2 (A, B, D genomes) was present in the resistant parent and the resistant bulk but not in the susceptible parent and the susceptible bulk, suggesting that this marker is linked to a yellow rust resistance gene. The presence of Xgwm382 was also tested in 108 additional wheat genotypes differing in yellow rust resistance. This analysis showed that 81% of the wheat genotypes known to be yellow rust resistant had the Xgwm382 marker, further suggesting that the presence of this marker correlates with yellow rust resistance in diverse wheat germplasm. Therefore, Xgwm382 could be useful for marker assisted selection of yellow rust resistances genotypes in wheat breeding programs

BOUT++: a framework for parallel plasma fluid simulations

A new modular code called BOUT++ is presented, which simulates 3D fluid equations in curvilinear coordinates. Although aimed at simulating Edge Localised Modes (ELMs) in tokamak X-point geometry, the code is able to simulate a wide range of fluid models (magnetised and unmagnetised) involving an arbitrary number of scalar and vector fields, in a wide range of geometries. Time evolution is fully implicit, and 3rd-order WENO schemes are implemented. Benchmarks are presented for linear and non-linear problems (the Orszag-Tang vortex) showing good agreement. Performance of the code is tested by scaling with problem size and processor number, showing efficient scaling to thousands of processors. Linear initial-value simulations of ELMs using reduced ideal MHD are presented, and the results compared to the ELITE linear MHD eigenvalue code. The resulting mode-structures and growth-rate are found to be in good agreement (BOUT++ = 0.245, ELITE = 0.239). To our knowledge, this is the first time dissipationless, initial-value simulations of ELMs have been successfully demonstrated.Comment: Submitted to Computer Physics Communications. Revised to reduce page count. 18 pages, 16 figure

Evidence of psi(3770) non-DD-bar Decay to J/psi pi+pi-

Evidence of $\psi(3770)$ decays to a non-${D \bar D}$ final state is observed. A total of $11.8 \pm 4.8 \pm 1.3$ \psi(3770) \to \PPJP events are obtained from a data sample of 27.7 $\rm {pb^{-1}}$ taken at center-of-mass energies around 3.773 GeV using the BES-II detector at the BEPC. The branching fraction is determined to be BF(\psi(3770) \to \PPJP)=(0.34\pm 0.14 \pm 0.09)%, corresponding to the partial width of \Gamma(\psi(3770) \to \PPJP) = (80 \pm 33 \pm 23) keV.Comment: 8 pages, 7 figures, Submitted to Physics Letters

Vision-based 3D Surface Motion Capture for the DIET Breast Cancer Screening System

Breast cancer is one of the most prevalent forms of cancer in the world today. The search for effective treatment and screening methods is a highly active area of research. The Digital Image-based ElastoTomography (DIET) project is a new breast cancer screening system under development, where surface motion from the mechanically actuated breast is measured in 3D, and used as input to an inverse problem solving for breast elasticity. Cancerous lesions appear as high contrast features, being an order of magnitude stiffer than healthy tissue. The 3D motion capture is measured by an array of digital cameras using computer vision techniques. This paper presents a computer vision imaging system for the capture of 3D breast surface motion for the DIET system, including the image acquisition system, camera calibration, and 3D surface and motion reconstruction. Results are presented for experiments performed with silicone gel phantoms, with conditions designed to replicate the clinical procedure. Full 3D surface motion is successfully captured using an array of 5 cameras. Some successful results from the DIET inverse problem are also presented to demonstrate the viability of the system in practice

Strobe Imaging System for Digital Image-based Elasto-Tomography Breast Cancer Screening

Digital Image-based Elasto-Tomography (DIET) technology relies on obtaining high resolution images of a breasts surface under high frequency actuation, typically in the range of 50-100Hz. Off-the-shelf digital cameras and imaging elements are unable to capture images directly at these speeds. A method based on strobe imaging is presented for obtaining the required high speed image capture at a resolution of 1280x1024 pixels and actuation frequency of 100 Hz. The final working system produced images that enabled effective 3D motion tracking of the surface of a silicon phantom. The motion is tracked accurately using a novel Euclidean Invariant signature method