IMRT for image-guided single vocal cord irradiation

PURPOSE: We have been developing an image-guided single vocal cord irradiation technique to treat patients with stage T1a glottic carcinoma. In the present study, we compared the dose coverage to the affected vocal cord and the dose delivered to the organs at risk using conventional, intensity-modulated radiotherapy (IMRT) coplanar, and IMRT non-coplanar techniques.

METHODS AND MATERIALS: For 10 patients, conventional treatment plans using two laterally opposed wedged 6-MV photon beams were calculated in XiO (Elekta-CMS treatment planning system). An in-house IMRT/beam angle optimization algorithm was used to obtain the coplanar and non-coplanar optimized beam angles. Using these angles, the IMRT plans were generated in Monaco (IMRT treatment planning system, Elekta-CMS) with the implemented Monte Carlo dose calculation algorithm. The organs at risk included the contralateral vocal cord, arytenoids, swallowing muscles, carotid arteries, and spinal cord. The prescription dose was 66 Gy in 33 fractions.

RESULTS: For the conventional plans and coplanar and non-coplanar IMRT plans, the population-averaged mean dose ± standard deviation to the planning target volume was 67 ± 1 Gy. The contralateral vocal cord dose was reduced from 66 ± 1 Gy in the conventional plans to 39 ± 8 Gy and 36 ± 6 Gy in the coplanar and non-coplanar IMRT plans, respectively. IMRT consistently reduced the doses to the other organs at risk.

CONCLUSIONS: Single vocal cord irradiation with IMRT resulted in good target coverage and provided significant sparing of the critical structures. This has the potential to improve the quality-of-life outcomes after RT and maintain the same local control rates.

On-line cone beam CT image guidance for vocal cord tumor targeting

Background and purpose: We are developing a technique for highly focused vocal cord irradiation in early glottic carcinoma to optimally treat a target volume confined to a single cord. This technique, in contrast with the conventional methods, aims at sparing the healthy vocal cord. As such a technique requires sub-mm daily targeting accuracy to be effective, we investigate the accuracy achievable with on-line kV-cone beam CT (CBCT) corrections. Materials and methods: CBCT scans were obtained in 10 early glottic cancer patients in each treatment fraction. The grey value registration available in X-ray volume imaging (XVI) software (Elekta, Synergy) was applied to a volume of interest encompassing the thyroid cartilage. After application of the thus derived corrections, residue displacements with respect to the planning CT scan were measured at clearly identifiable relevant landmarks. The intra- and inter-observer variations were also measured. Results: While before correction the systematic displacements of the vocal cords were as large as 2.4 ± 3.3 mm (cranial-caudal population mean ± SD Σ), daily CBCT registration and correction reduced these values to less than 0.2 ± 0.5 mm in all directions. Random positioning errors (SD σ) were reduced to less than 1 mm. Correcting only for translations and not for rotations did not appreciably affect this accuracy. The residue random displacements partly stem from intra-observer variations (SD = 0.2-0.6 mm). Conclusion: The use of CBCT for daily image guidance in combination with standard mask fixation reduced systematic and random set-up errors of the vocal cords to <1 mm prior to the delivery of each fraction dose. Thus, this facilitates the high targeting precision required for a single vocal cord irradiation. © 2009 Elsevier Ireland Ltd. All rights reserved.

Evolution of Hot Loops in an Active Region Core Observed with the SDO Atmospheric Image Assembly

Evidence has accumulated of high temperature (> 4 MK) coronal emission in active region cores that corresponds to structures in equilibrium. Other studies have found evidence of evolving loops. We investigate the EUV intensity and temperature variations of short coronal loops observed in the core of NOAA Active Region 11250 on 13 July 2011. The loops, which run directly between the AR opposite polarities, are first detectable in the 94Å band of Fe XVIII, implying an effective temperature ~ 7 MK. The low temperature component of the 94 Å signal is modeled in terms of a linear superposition of the 193 Å and 171 Å signals in order to separate the hot component. After identifying the loops we have used contemporaneous HMI observations to identify the corresponding inter-moss regions, and we have investigated their time evolution in six AIA EUV channels. The results can be separated into two classes. Group 1 (94Å, 335Å, 211Å) is characterized by hotter temperatures (~2-7 MK), and Group 2 (193Å, 171Å, 131Å) by cooler temperatures (0.4 - 1.6 MK). For Group 1 the intensity peaks in the 94Å channel are followed by maxima in the 335 Å channel with a time lag of ~8 min, suggestive of a cooling pattern with an exponential decay. While the 211Å maxima follow those in the 335 Å channel, there is no systematic relation which would indicate a progressive cooling process through the lower temperatures, as has been observed in other investigations. In Group 2 the signals in the 171 and 131Å channels track each other closely, and lag behind the 193Å. In the inter-moss region of the loop the peak temperature and peak emission measure have opposite trends. The hot 94Å brightenings occur in the central part of the loops with maximum temperatures ~7 MK. Subsequently the loops appear to fill with plasma with an emission measure compatible with the 193 Å signal and temperature in the range ~ 1.5-2 MK. Although the exact details of the time evolution are still under investigation, these non static loops show high levels of intermittency in the 94Å signal (please see poster "Intermittent and Scale-Invariant Intensity Fluctuations in Hot Coronal Loops," by Lawrence et al. in this session).

Inexact floating-point adder for dynamic image processing

Power has become a key constraint in current nanoscale integrated circuit design due to the increasing demands for mobile computing and a low carbon economy. As an emerging technology, an inexact circuit design offers a promising approach to significantly reduce both dynamic and static power dissipation for error tolerant applications. Although fixed-point arithmetic circuits have been studied in terms of inexact computing, floating-point arithmetic circuits have not been fully considered although require more power. In this paper, the first inexact floating-point adder is designed and applied to high dynamic range (HDR) image processing. Inexact floating-point adders are proposed by approximately designing an exponent subtractor and mantissa adder. Related logic operations including normalization and rounding modules are also considered in terms of inexact computing. Two HDR images are processed using the proposed inexact floating-point adders to show the validity of the inexact design. HDR-VDP is used as a metric to measure the subjective results of the image addition. Significant improvements have been achieved in terms of area, delay and power consumption. Comparison results show that the proposed inexact floating-point adders can improve power consumption and the power-delay product by 29.98% and 39.60%, respectively.

Small animal image-guided radiotherapy: status, considerations and potential for translational impact.

Radiation biology is being transformed by the implementation of small animal image-guided precision radiotherapy into pre-clinical research programmes worldwide. We report on the current status and developments of the small animal radiotherapy field, suggest criteria for the design and execution of effective studies and contend that this powerful emerging technology, used in combination with relevant small animal models, holds much promise for translational impact in radiation oncology.

Automated image analysis for experimental investigations of salt water intrusion in coastal aquifers

A novel methodology has been developed to quantify important saltwater intrusion parameters in a sandbox style experiment using image analysis. Existing methods found in the literature are based mainly on visual observations, which are subjective, labour intensive and limits the temporal and spatial resolutions that can be analysed. A robust error analysis was undertaken to determine the optimum methodology to convert image light intensity to concentration. Results showed that defining a relationship on a pixel-wise basis provided the most accurate image to concentration conversion and allowed quantification of the width of mixing zone between the saltwater and freshwater. A large image sample rate was used to investigate the transient dynamics of saltwater intrusion, which rendered analysis by visual observation unsuitable. This paper presents the methodologies developed to minimise human input and promote autonomy, provide high resolution image to concentration conversion and allow the quantification of intrusion parameters under transient conditions.

A low-cost digital image correlation technique for characterising the shear deformation of fabrics for draping studies

A novel digital image correlation (DIC) technique has been developed to track changes in textile yarn orientations during shear characterisation experiments, requiring only low-cost digital imaging equipment. Fabric shear angles and effective yarn strains are calculated and visualised using this new DIC technique for bias extension testing of an aerospace grade, carbon-fibre reinforcement material with a plain weave architecture. The DIC results are validated by direct measurement, and the use of a wide bias extension sample is evaluated against a more commonly used narrow sample. Wide samples exhibit a shear angle range 25% greater than narrow samples and peak loads which are 10 times higher. This is primarily due to excessive yarn slippage in the narrow samples; hence, the wide sample configuration is recommended for characterisation of shear properties which are required for accurate modelling of textile draping.

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

Accurate image capturing control of bottle caps based on iterative learning control and Kalman filtering

This paper investigates camera control for capturing bottle cap target images in the fault-detection system of an industrial production line. The main purpose is to identify the targeted bottle caps accurately in real time from the images. This is achieved by combining iterative learning control and Kalman filtering to reduce the effect of various disturbances introduced into the detection system. A mathematical model, together with a physical simulation platform is established based on the actual production requirements, and the convergence properties of the model are analyzed. It is shown that the proposed method enables accurate real-time control of the camera, and further, the gain range of the learning rule is also obtained. The numerical simulation and experimental results confirm that the proposed method can not only reduce the effect of repeatable disturbances but also non-repeatable ones.

The idea, the machine, and the art: word and image in the 21st century

Taking in recent advances in neuroscience and digital technology, Gander and Garland assess the state of the inter-arts in America and the Western world, exploring and questioning the primacy of affect in an increasingly hypertextual everyday environment. In this analysis they signal a move beyond W. J. T. Mitchell’s coinage of the ‘imagetext’ to an approach that centres the reader-viewer in a recognition, after John Dewey, of ‘art as experience’. New thinking in cognitive and computer sciences about the relationship between the body and the mind challenges any established definitions of ‘embodiment’, ‘materiality’, ‘virtuality’ and even ‘intelligence, they argue, whilst ‘Extended Mind Theory’, they note, marries our cognitive processes with the material forms with which we engage, confirming and complicating Marshall McLuhan’s insight, decades ago, that ‘all media are “extensions of man”’. In this chapter, Gander and Garland open paths and suggest directions into understandings and critical interpretations of new and emerging imagetext worlds and experiences.

Streaming Elements for FPGA Signal and Image Processing Accelerators

Field programmable gate array devices boast abundant resources with which custom accelerator components for signal, image and data processing may be realised; however, realising high performance, low cost accelerators currently demands manual register transfer level design. Software-programmable ’soft’ processors have been proposed as a way to reduce this design burden but they are unable to support performance and cost comparable to custom circuits. This paper proposes a new soft processing approach for FPGA which promises to overcome this barrier. A high performance, fine-grained streaming processor, known as a Streaming Accelerator Element, is proposed which realises accelerators as large scale custom multicore networks. By adopting a streaming execution approach with advanced program control and memory addressing capabilities, typical program inefficiencies can be almost completely eliminated to enable performance and cost which are unprecedented amongst software-programmable solutions. When used to realise accelerators for fast fourier transform, motion estimation, matrix multiplication and sobel edge detection it is shown how the proposed architecture enables real-time performance and with performance and cost comparable with hand-crafted custom circuit accelerators and up to two orders of magnitude beyond existing soft processors.