Conventional 3D staging PET/CT in CT simulation for lung cancer: impact of rigid and deformable target volume alignments for radiotherapy treatment planning

Objective: Positron emission tomography (PET)/CT scans can improve target definition in radiotherapy for non-small cell lung cancer (NSCLC). As staging PET/CT scans are increasingly available, we evaluated different methods for co-registration of staging PET/CT data to radiotherapy simulation (RTP) scans.

Methods: 10 patients underwent staging PET/CT followed by RTP PET/CT. On both scans, gross tumour volumes (GTVs) were delineated using CT (GTVCT) and PET display settings. Four PET-based contours (manual delineation, two threshold methods and a source-to-background ratio method) were delineated. The CT component of the staging scan was co-registered using both rigid and deformable techniques to the CT component of RTP PET/CT. Subsequently rigid registration and deformation warps were used to transfer PET and CT contours from the staging scan to the RTP scan. Dice’s similarity coefficient (DSC) was used to assess the registration accuracy of staging-based GTVs following both registration methods with the GTVs delineated on the RTP PET/CT scan.

Results: When the GTVCT delineated on the staging scan after both rigid registration and deformation was compared with the GTVCT on the RTP scan, a significant improvement in overlap (registration) using deformation was observed (mean DSC 0.66 for rigid registration and 0.82 for deformable registration, p50.008). A similar comparison for PET contours revealed no significant improvement in overlap with the use of deformable registration.

Conclusions: No consistent improvements in similarity measures were observed when deformable registration was used for transferring PET-based contours from a staging PET/CT. This suggests that currently the use of rigid registration remains the most appropriate method for RTP in NSCLC.

The development of effective biomarkers for Alzheimer's disease:a review

OBJECTIVE: There is a widely recognised need to develop effective Alzheimer's disease (AD) biomarkers to aid the development of disease-modifying treatments, to facilitate early diagnosis and to improve clinical care. This overview aims to summarise the utility of key neuroimaging and cerebrospinal fluid (CSF) biomarkers for AD, before focusing on the latest efforts to identify informative blood biomarkers. DESIGN: A literature search was performed using PubMed up to September 2011 for reviews and primary research studies of neuroimaging (magnetic resonance imaging, magnetic resonance spectroscopy, positron emission tomography and amyloid imaging), CSF and blood-based (plasma, serum and platelet) biomarkers in AD and mild cognitive impairment. Citations within individual articles were examined to identify additional studies relevant to this review. RESULTS: Evidence of AD biomarker potential was available for imaging techniques reflecting amyloid burden and neurodegeneration. Several CSF measures are promising, including 42 amino acid ß-amyloid peptide (Aß(42) ); total tau (T-tau) protein, reflecting axonal damage; and phosphorylated tau (P-tau), reflecting neurofibrillary tangle pathology. Studies of plasma Aß have produced inferior diagnostic discrimination. Alternative plasma and platelet measures are described, which represent potential avenues for future research. CONCLUSIONS: Several imaging and CSF markers demonstrate utility in predicting AD progression and determining aetiology. These require standardisation before forming core elements of diagnostic criteria. The enormous potential available for identifying a minimally-invasive, easily-accessible blood measure as an effective AD biomarker currently remains unfulfilled. Copyright © 2012 John Wiley & Sons, Ltd.

Understanding macroalgal dispersal in a complex hydrodynamic environment: a combined population genetic and physical modelling approach

Gene flow in macroalgal populations can be strongly influenced by spore or gamete dispersal. This, in turn, is influenced by a convolution of the effects of current flow and specific plant reproductive strategies. Although several studies have demonstrated genetic variability in macroalgal populations over a wide range of spatial scales, the associated current data have generally been poorly resolved spatially and temporally. In this study, we used a combination of population genetic analyses and high-resolution hydrodynamic modelling to investigate potential connectivity between populations of the kelp Laminaria digitata in the Strangford Narrows, a narrow channel characterized by strong currents linking the large semi-enclosed sea lough, Strangford Lough, to the Irish Sea. Levels of genetic structuring based on six microsatellite markers were very low, indicating high levels of gene flow and a pattern of isolation-by-distance, where populations are more likely to exchange migrants with geographically proximal populations, but with occasional long-distance dispersal. This was confirmed by the particle tracking model, which showed that, while the majority of spores settle near the release site, there is potential for dispersal over several kilometres. This combined population genetic and modelling approach suggests that the complex hydrodynamic environment at the entrance to Strangford Lough can facilitate dispersal on a scale exceeding that proposed for L. digitata in particular, and the majority of macroalgae in general. The study demonstrates the potential of integrated physical–biological approaches for the prediction of ecological changes resulting from factors such as anthropogenically induced coastal zone changes.

Rao-Blackwellised particle filter for colour-based tracking

Colour-based particle filters have been used exhaustively in the literature given rise to multiple applications However tracking coloured objects through time has an important drawback since the way in which the camera perceives the colour of the object can change Simple updates are often used to address this problem which imply a risk of distorting the model and losing the target In this paper a joint image characteristic-space tracking is proposed which updates the model simultaneously to the object location In order to avoid the curse of dimensionality a Rao-Blackwellised particle filter has been used Using this technique the hypotheses are evaluated depending on the difference between the model and the current target appearance during the updating stage Convincing results have been obtained in sequences under both sudden and gradual illumination condition changes Crown Copyright (C) 2010 Published by Elsevier B V All rights reserved

An efficient particle filter for color-based tracking in complex scenes

In this paper, we introduce an efficient method for particle selection in tracking objects in complex scenes. Firstly, we improve the proposal distribution function of the tracking algorithm, including current observation, reducing the cost of evaluating particles with a very low likelihood. In addition, we use a partitioned sampling approach to decompose the dynamic state in several stages. It enables to deal with high-dimensional states without an excessive computational cost. To represent the color distribution, the appearance of the tracked object is modelled by sampled pixels. Based on this representation, the probability of any observation is estimated using non-parametric techniques in color space. As a result, we obtain a Probability color Density Image (PDI) where each pixel points its membership to the target color model. In this way, the evaluation of all particles is accelerated by computing the likelihood p(z|x) using the Integral Image of the PDI.

Rao-blackwellized particle filter for human appearance and position tracking

In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.

Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics

In this paper, a novel framework for visual tracking of human body parts is introduced. The approach presented demonstrates the feasibility of recovering human poses with data from a single uncalibrated camera by using a limb-tracking system based on a 2-D articulated model and a double-tracking strategy. Its key contribution is that the 2-D model is only constrained by biomechanical knowledge about human bipedal motion, instead of relying on constraints that are linked to a specific activity or camera view. These characteristics make our approach suitable for real visual surveillance applications. Experiments on a set of indoor and outdoor sequences demonstrate the effectiveness of our method on tracking human lower body parts. Moreover, a detail comparison with current tracking methods is presented.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Generation of overdense and high-energy electron-positron-pair plasmas by irradiation of a thin foil with two ultraintense lasers

A scheme for enhanced quantum electrodynamics (QED) production of electron-positron-pair plasmas is proposed that uses two ultraintense lasers irradiating a thin solid foil from opposite sides. In the scheme, under a proper matching condition, in addition to the skin-depth emission of gamma-ray photons and Breit-Wheeler creation of pairs on each side of the foil, a large number of high-energy electrons and photons from one side can propagate through it and interact with the laser on the other side, leading to much enhanced gamma-ray emission and pair production. More importantly, the created pairs can be collected later and confined to the center by opposite laser radiation pressures when the foil becomes transparent, resulting in the formation of unprecedentedly overdense and high-energy pair plasmas. Two-dimensional QED particle-in-cell simulations show that electron-positron-pair plasmas with overcritical density 10(22) cm(-3) and a high energy of 100s of MeV are obtained with 10 PW lasers at intensities 10(23) W/cm(2), which are of key significance for laboratory astrophysics studies.

Plasma ionization through wave-particle interaction in a capacitively coupled radio-frequency discharge

Phase resolved optical emission spectroscopy, with high temporal resolution, shows that wave-particle interactions play a fundamental role in sustaining capacitively coupled rf plasmas. The measurements are in excellent agreement with a simple particle-in-cell simulation. Excitation and ionization mechanisms are dominated by beam-like electrons, energized through the advancing and retreating electric fields of the rf sheath. The associated large-amplitude electron waves, driven by a form of two-stream instability, result in power dissipation through electron trapping and phase mixing. (c) 2007 American Institute of Physics.

Target Detection and Tracking With Heterogeneous Sensors

We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.