Wavelength-tuneable liquid crystal lasers from the visible to the near-infrared

The study of band-edge lasing from dye-doped chiral nematic liquid crystals has thus far been largely restricted to visible wavelengths. In this paper, a wide range of commercially available laser dyes are examined for their suitability as infrared emitters within a chiral nematic host. Problems such as poor solubility and reduced quantum efficiencies are overcome, and successful band-edge lasing is demonstrated within the range of 735-850 nm, using the dyes LD800, HITC-P and DOTC-P. This paper also reports on progress towards widely tuneable liquid crystal lasers, capable of emission in the region 460- 850 nm. Key to this is the use of common pump source, capable of simultaneously exciting all of the dyes (both infrared and visible) that are present within the system. Towards this aim, we successfully demonstrate near-infrared lasing (800 nm) facilitated by Förster energy transfer between the visible dye DCM, and the infra-red dye LD800, enabling pump wavelengths anywhere between 420 and 532 nm to be used. These results demonstrate that small and low-cost tuneable visible to near-infrared laser sources are achievable, using a single common pump source. Such devices are envisaged to have wide-ranging applications including medical imaging (including optical coherence tomography), point-of-care optical medical diagnostics (such as flow cytometry), telecommunications, and optical signatures for security coatings. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Identification of Materials from Construction Site Images Using Content Based Image Retrieval Techniques

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Microfabrication of electrode patterns for high-frequency ultrasound transducer arrays.

High-frequency ultrasound is needed for medical imaging with high spatial resolution. A key issue in the development of ultrasound imaging arrays to operate at high frequencies (≥30 MHz) is the need for photolithographic patterning of array electrodes. To achieve this directly on 1-3 piezocomposite, the material requires not only planar, parallel, and smooth surfaces, but also an epoxy composite filler that is resistant to chemicals, heat, and vacuum. This paper reports, first, on the surface finishing of 1-3 piezocomposite materials by lapping and polishing. Excellent surface flatness has been obtained, with an average surface roughness of materials as low as 3 nm and step heights between ceramic/polymer of ∼80 nm. Subsequently, high-frequency array elements were patterned directly on top of these surfaces using a photolithography process. A 30-MHz linear array electrode pattern with 50-μm element pitch has been patterned on the lapped and polished surface of a high-frequency 1-3 piezocomposite. Excellent electrode edge definition and electrical contact to the composite were obtained. The composite has been lapped to a final thickness of ∼55 μm. Good adhesion of electrodes on the piezocomposite has been achieved and electrical impedance measurements have demonstrated their basic functionality. The array was then packaged, and acoustic pulse-echo measurements were performed. These results demonstrate that direct patterning of electrodes by photolithography on 1-3 piezocomposite is feasible for fabrication of high-frequency ultrasound arrays. Furthermore, this method is more conducive to mass production than other reported array fabrication techniques.

A high-resolution atlas and statistical model of the human heart from multislice CT

Atlases and statistical models play important roles in the personalization and simulation of cardiac physiology. For the study of the heart, however, the construction of comprehensive atlases and spatio-temporal models is faced with a number of challenges, in particular the need to handle large and highly variable image datasets, the multi-region nature of the heart, and the presence of complex as well as small cardiovascular structures. In this paper, we present a detailed atlas and spatio-temporal statistical model of the human heart based on a large population of 3D+time multi-slice computed tomography sequences, and the framework for its construction. It uses spatial normalization based on nonrigid image registration to synthesize a population mean image and establish the spatial relationships between the mean and the subjects in the population. Temporal image registration is then applied to resolve each subject-specific cardiac motion and the resulting transformations are used to warp a surface mesh representation of the atlas to fit the images of the remaining cardiac phases in each subject. Subsequently, we demonstrate the construction of a spatio-temporal statistical model of shape such that the inter-subject and dynamic sources of variation are suitably separated. The framework is applied to a 3D+time data set of 138 subjects. The data is drawn from a variety of pathologies, which benefits its generalization to new subjects and physiological studies. The obtained level of detail and the extendability of the atlas present an advantage over most cardiac models published previously. © 1982-2012 IEEE.

The production of radionuclides for nuclear medicine from a compact, low-energy accelerator system.

The field of nuclear medicine is reliant on radionuclides for medical imaging procedures and radioimmunotherapy (RIT). The recent shut-downs of key radionuclide producers have highlighted the fragility of the current radionuclide supply network, however. To ensure that nuclear medicine can continue to grow, adding new diagnostic and therapy options to healthcare, novel and reliable production methods are required. Siemens are developing a low-energy, high-current - up to 10MeV and 1mA respectively - accelerator. The capability of this low-cost, compact system for radionuclide production, for use in nuclear medicine procedures, has been considered.

Graphene modelocked VECSELs

In the past decade, passively modelocked optically pumped vertical external cavity surface emitting lasers (OPVECSELs), sometimes referred to as semiconductor disk lasers (OP-SDLs), impressively demonstrated the potential for generating femtosecond pulses at multi-Watt average output powers with gigahertz repetition rates. Passive modelocking with a semiconductor saturable absorber mirror (SESAM) is well established and offers many advantages such as a flexible design of the parameters and low non-saturable losses. Recently, graphene has emerged as an attractive wavelength-independent alternative saturable absorber for passive modelocking in various lasers such as fiber or solid-state bulk lasers because of its unique optical properties. Here, we present and discuss the modelocked VECSELs using graphene saturable absorbers. The broadband absorption due to the linear dispersion of the Dirac electrons in graphene makes this absorber interesting for wavelength tunable ultrafast VECSELs. Such widely tunable modelocked sources are in particularly interesting for bio-medical imaging applications. We present a straightforward approach to design the optical properties of single layer graphene saturable absorber mirrors (GSAMs) suitable for passive modelocking of VECSELs. We demonstrate sub-500 fs pulses from a GSAM modelocked VECSEL. The potential for broadband wavelength tuning is confirmed by covering 46 nm in modelocked operation using three different VECSEL chips and up to 21 nm tuning in pulsed operation is achieved with one single gain chip. A linear and nonlinear optical characterization of different GSAMs with different absorption properties is discussed and can be compared to SESAMs. © 2014 SPIE.

Imaging the femoral cortex: Thickness, density and mass from clinical CT

There is growing evidence that focal thinning of cortical bone in the proximal femur may predispose a hip to fracture. Detecting such defects in clinical CT is challenging, since cortices may be significantly thinner than the imaging system's point spread function. We recently proposed a model-fitting technique to measure sub-millimetre cortices, an ill-posed problem which was regularized by assuming a specific, fixed value for the cortical density. In this paper, we develop the work further by proposing and evaluating a more rigorous method for estimating the constant cortical density, and extend the paradigm to encompass the mapping of cortical mass (mineral mg/cm 2) in addition to thickness. Density, thickness and mass estimates are evaluated on sixteen cadaveric femurs, with high resolution measurements from a micro-CT scanner providing the gold standard. The results demonstrate robust, accurate measurement of peak cortical density and cortical mass. Cortical thickness errors are confined to regions of thin cortex and are bounded by the extent to which the local density deviates from the peak, averaging 20% for 0.5mm cortex. © 2012 Elsevier B.V.