Multilayer Imaging Research Articles

TU‐D‐BRC‐00: The EPID Strikes Back

There has been increased deployment of gantry‐mounted linacs with onboard kilovoltage x‐ray imagers. Despite this trend, most clinics still employ beam's‐eye‐view (BEV) imaging using flat panel electronic portal imaging devices (EPIDs) as a highly useful means of verifying geometric localization pre‐ and post‐delivery. In recent years, there has been increased interest in the use of EPIDs for a variety of clinical and investigational applications ranging from megavoltage cone‐beam CT, in vivo dosimetry, patient‐specific QA to real‐time target localization for dynamic MLC‐based tumor tracking. In conjunction, there are several innovative EPID designs currently under investigation that hold great promise in bringing novel imaging and image‐guidance applications into clinical practice.This symposium is aimed at clinical and research‐oriented medical physicists who want to learn more about current and future megavoltage imaging technology and applications. In this symposium, we will examine the (i) interesting applications that make use of current EPID technology such as volumetric 4D image‐based models, real‐time position estimation for dynamic MLC tracking, etc., (ii) clinical applications such as in vivo EPID dosimetry and (iii) innovative high‐performance EPID designs and exciting future applications, including designs based on thick segmented scintillators, hybrid kV/MV imagers using segmented strip scintillators, and energy‐resolving EPIDs based on multilayer imagers and poly‐Silicon active matrix flat panel imagers.Learning Objectives – In this symposium, the attendees will learn Novel applications using currently available EPIDs Use of EPIDs to perform in vivo dosimetry Novel designs using high‐efficiency, energy resolving EPIDs and future applications of megavoltage imagingJ. Rottmann, Varian Medical SystemsP. Greer, Research Grant Funding from Radiation Oncology Institute (Grant ROI2013‐912), 2013–2014

TU‐D‐BRC‐03: Future EPID Technology and Applications

There has been increased deployment of gantry‐mounted linacs with onboard kilovoltage x‐ray imagers. Despite this trend, most clinics still employ beam's‐eye‐view (BEV) imaging using flat panel electronic portal imaging devices (EPIDs) as a highly useful means of verifying geometric localization pre‐ and post‐delivery. In recent years, there has been increased interest in the use of EPIDs for a variety of clinical and investigational applications ranging from megavoltage cone‐beam CT, in vivo dosimetry, patient‐specific QA to real‐time target localization for dynamic MLC‐based tumor tracking. In conjunction, there are several innovative EPID designs currently under investigation that hold great promise in bringing novel imaging and image‐guidance applications into clinical practice.This symposium is aimed at clinical and research‐oriented medical physicists who want to learn more about current and future megavoltage imaging technology and applications. In this symposium, we will examine the (i) interesting applications that make use of current EPID technology such as volumetric 4D image‐based models, real‐time position estimation for dynamic MLC tracking, etc., (ii) clinical applications such as in vivo EPID dosimetry and (iii) innovative high‐performance EPID designs and exciting future applications, including designs based on thick segmented scintillators, hybrid kV/MV imagers using segmented strip scintillators, and energy‐resolving EPIDs based on multilayer imagers and poly‐Silicon active matrix flat panel imagers.Learning Objectives – In this symposium, the attendees will learn Novel applications using currently available EPIDs Use of EPIDs to perform in vivo dosimetry Novel designs using high‐efficiency, energy resolving EPIDs and future applications of megavoltage imagingJ. Rottmann, Varian Medical SystemsP. Greer, Research Grant Funding from Radiation Oncology Institute (Grant ROI2013‐912), 2013–2014

TU‐D‐BRC‐02: Free Information ‐ EPID‐Based In Vivo Dosimetry

There has been increased deployment of gantry‐mounted linacs with onboard kilovoltage x‐ray imagers. Despite this trend, most clinics still employ beam's‐eye‐view (BEV) imaging using flat panel electronic portal imaging devices (EPIDs) as a highly useful means of verifying geometric localization pre‐ and post‐delivery. In recent years, there has been increased interest in the use of EPIDs for a variety of clinical and investigational applications ranging from megavoltage cone‐beam CT, in vivo dosimetry, patient‐specific QA to real‐time target localization for dynamic MLC‐based tumor tracking. In conjunction, there are several innovative EPID designs currently under investigation that hold great promise in bringing novel imaging and image‐guidance applications into clinical practice.This symposium is aimed at clinical and research‐oriented medical physicists who want to learn more about current and future megavoltage imaging technology and applications. In this symposium, we will examine the (i) interesting applications that make use of current EPID technology such as volumetric 4D image‐based models, real‐time position estimation for dynamic MLC tracking, etc., (ii) clinical applications such as in vivo EPID dosimetry and (iii) innovative high‐performance EPID designs and exciting future applications, including designs based on thick segmented scintillators, hybrid kV/MV imagers using segmented strip scintillators, and energy‐resolving EPIDs based on multilayer imagers and poly‐Silicon active matrix flat panel imagers.Learning Objectives – In this symposium, the attendees will learn Novel applications using currently available EPIDs Use of EPIDs to perform in vivo dosimetry Novel designs using high‐efficiency, energy resolving EPIDs and future applications of megavoltage imagingJ. Rottmann, Varian Medical SystemsP. Greer, Research Grant Funding from Radiation Oncology Institute (Grant ROI2013‐912), 2013–2014

TU‐D‐BRC‐01: Novel Applications for Current EPID Technology

There has been increased deployment of gantry‐mounted linacs with onboard kilovoltage x‐ray imagers. Despite this trend, most clinics still employ beam's‐eye‐view (BEV) imaging using flat panel electronic portal imaging devices (EPIDs) as a highly useful means of verifying geometric localization pre‐ and post‐delivery. In recent years, there has been increased interest in the use of EPIDs for a variety of clinical and investigational applications ranging from megavoltage cone‐beam CT, in vivo dosimetry, patient‐specific QA to real‐time target localization for dynamic MLC‐based tumor tracking. In conjunction, there are several innovative EPID designs currently under investigation that hold great promise in bringing novel imaging and image‐guidance applications into clinical practice.This symposium is aimed at clinical and research‐oriented medical physicists who want to learn more about current and future megavoltage imaging technology and applications. In this symposium, we will examine the (i) interesting applications that make use of current EPID technology such as volumetric 4D image‐based models, real‐time position estimation for dynamic MLC tracking, etc., (ii) clinical applications such as in vivo EPID dosimetry and (iii) innovative high‐performance EPID designs and exciting future applications, including designs based on thick segmented scintillators, hybrid kV/MV imagers using segmented strip scintillators, and energy‐resolving EPIDs based on multilayer imagers and poly‐Silicon active matrix flat panel imagers.Learning Objectives – In this symposium, the attendees will learn Novel applications using currently available EPIDs Use of EPIDs to perform in vivo dosimetry Novel designs using high‐efficiency, energy resolving EPIDs and future applications of megavoltage imagingJ. Rottmann, Varian Medical SystemsP. Greer, Research Grant Funding from Radiation Oncology Institute (Grant ROI2013‐912), 2013–2014

Efficacy evaluation of traditional Chinese medicine combined with sorafenib in the treatment of primary hepatocellular carcinoma in the middle and late stage

Objective Evaluation of the treatment effects between sorafenib soley and by combination of SLFN and Chinese Medicine on mid to later phase hepatic carcinomas patients. Methods Take 48 mid to later phase hepatic carcinomas patients of our hospital from 2010 to 2015. Randomly assign 24 patients to sorafenib group and 24 to sorafenib combine Chinese medicine group. To compare the change of their liver function and multilayer spiral MSCT image. Results There were no significant statistical difference between the two groups on size of the tumors, liver diffusion outside, cancer embolus of portal vein(P>0.05). But there were meaningful statistical difference on TBIL, DBIL, ALT, ALB and GLB(P<0.05). Conclusions Compare to chemotherapy only method, there are no different results on tumor growth and diffusion by combing with Chinese Medicine with sorafenib, but there are some effect on improving liver function and life quality. Key words: Primary hepatocellular carcinoma; Chinese medicine treatment; Multi-layer spiral CT

Carvedilol-Enriched Cold Oxygenated Blood Cardioplegia Improves Left Ventricular Diastolic Function After Weaning From Cardiopulmonary Bypass.

To investigate whether adding carvedilol, a nonselective β- and selective α1-receptor blocking agent with antioxidant properties, to oxygenated blood cardioplegia improves myocardial function after weaning from bypass. A randomized controlled study. A university laboratory. Twenty anesthetized pigs, Norwegian Landrace. On cardiopulmonary bypass, cardiac arrest was induced with cold (12°C), oxygenated blood cardioplegia, enriched with carvedilol or vehicle, and repeated every 20 minutes. After 100 minutes, the heart was reperfused and weaned. Left ventricular function was evaluated with pressure-volume loops, local myocardial systolic strain, and strain rate from Speckle tracking analysis and multilayer short-axis tissue Doppler Imaging. In the carvedilol group, the load-independent logarithmic end-diastolic pressure volume relationship, β, decreased from 1 to 3 hours of reperfusion and was low, 0.028±0.004 v 0.042±0.007 (p<0.05) in controls at 3 hours, demonstrating improved left ventricular compliance. The diastolic relaxation constant τ was decreased, 28.9±0.6 ms v 34.6±1.3 ms (pg<0.035), and dP/dtmin was more negative,-1,462±145 mmHg/s v-1,105±105 mmHg/s (pg = 0.024), for carvedilol v control group. The systolic variables, preload recruitable stroke work and end-systolic pressure-volume relationship, did not differ between groups, neither did left ventricular systolic strain and strain rate. Myocardial oxidative stress, measured as tissue levels of malondialdehyde, was reduced by carvedilol, 0.19±0.01 compared to 0.24±0.01 nmol/mg (p = 0.004) in controls. Carvedilol added to blood cardioplegia improved diastolic cardiac function and reduced oxidative stress during the first 3 hours after reperfusion in a porcine model, with 100 minutes of cardioplegic arrest.

Nanoparticle motion and deposition near the triple line in evaporating sessile water droplet on a superhydrophilic substrate

The evaporation of a sessile droplet with suspended nonvolatile materials has been extensively studied for its particular characteristics in heat and mass transfer. The deposition patterns of it were believed to be controlled by the contact line movement; however, the mechanisms of the deposition patterns are very complicated, especially due to the nanoparticle movement near the triple line. In this paper, the nanoparticle movement and deposition near the contact line of a drying droplet are experimentally investigated, using fluorescent nanoparticles as direct tracers. It shows that the nanoparticle velocity in the thin liquid film region, obtained by the evanescent wave based multilayer nano-particle image velocimetry (MnPIV) technique, can be much higher than that near the liquid–vapor interface at the later stage of evaporation process in water droplet on a superhydrophilic substrate. On the other hand, the deposition patterns, which exhibits scattered dots, radial spokes and multi-rings due to the constant contact radius (CCR) and constant contact angle (CCA) modes happened recurrently during the evaporation process, can also be altered substantially by the nanoparticle concentration, which is an important parameter influencing the energy barrier. The analysis on the energy barrier indicates that there exists the maximum energy barrier when the deposition transits from lambdoid pattern to multi-ring pattern.

Learning Multilayer Channel Features for Pedestrian Detection.

Pedestrian detection based on the combination of convolutional neural network (CNN) and traditional handcrafted features (i.e., HOG+LUV) has achieved great success. In general, HOG+LUV are used to generate the candidate proposals and then CNN classifies these proposals. Despite its success, there is still room for improvement. For example, CNN classifies these proposals by the fully connected layer features, while proposal scores and the features in the inner-layers of CNN are ignored. In this paper, we propose a unifying framework called multi-layer channel features (MCF) to overcome the drawback. It first integrates HOG+LUV with each layer of CNN into a multi-layer image channels. Based on the multi-layer image channels, a multi-stage cascade AdaBoost is then learned. The weak classifiers in each stage of the multi-stage cascade are learned from the image channels of corresponding layer. Experiments on Caltech data set, INRIA data set, ETH data set, TUD-Brussels data set, and KITTI data set are conducted. With more abundant features, an MCF achieves the state of the art on Caltech pedestrian data set (i.e., 10.40% miss rate). Using new and accurate annotations, an MCF achieves 7.98% miss rate. As many non-pedestrian detection windows can be quickly rejected by the first few stages, it accelerates detection speed by 1.43 times. By eliminating the highly overlapped detection windows with lower scores after the first stage, it is 4.07 times faster than negligible performance loss.

Unsupervised Multilayer Feature Learning for Satellite Image Scene Classification

This letter proposes a simple but effective approach to automatically learn a multilayer image feature for satellite image scene classification. Different from the hand-crafted features which are empirically designed but lack high generalization ability, the proposed approach can autonomously extract the data-dependent feature. The presented feature extraction algorithm is composed of two layers, and the bases of these two layers are uniformly learned by a plain $K$ -means clustering algorithm. Coincidentally, the feature extraction performance of the aforementioned two layers is consistent with visual processing of human visual cortex. More specifically, the first layer can generate edgelike bases, which are analogous to the neuron responses of primary visual cortex (V1), and the second layer can produce cornerlike bases, which resemble the neuron responses of visual extrastriate cortical area two (V2). The proposed feature extraction approach can automatically extract not only simple structure features (e.g., edges) but also complex structure features (e.g., corners and junctions). The learned feature is further discriminated by the linear support vector machine classifier for scene classification. In order to fairly demonstrate the validity of the proposed feature extraction approach, its satellite image scene classification performance is evaluated on the public UCM-21 data set. Experimental results show that the proposed approach can outperform several recent state-of-the-art approaches.

An affinity triggered MRI nanoprobe for pH-dependent cell labeling

The pH-sensitive affinity pair composed by neutravidin and iminobiotin was used to develop a multilayered Magnetic Resonance Imaging (MRI) nanoprobe responsive to the acidic pH of tumor microenvironment.

クラスターイオンビーム技術の最近の進展&amp;mdash;ナノ加工からバイオ材料評価まで&amp;mdash;

Recent progress of cluster ion beam was overviewed. Various applications, such as nano-fabrication and biological material analysis, have been developed by using cluster effects, which are due to high-density and multiple collision between cluster ion and surface. Control of size and energy of cluster beam is essential. High speed etching with high anisotropy is realized with neutral cluster beam, which has very low energy/atom. Both molecular depth profiling of organic multilayer and high resolution molecular imaging were demonstrated by using cluster ions. These new XPS and SIMS techniques provide new opportunities for polymer, molecular electronics, biological materials and life science.

High capacity secret image sharing using multilayer image steganography with primary cover predictive error

Image steganography is the art of hiding secret message in greyscale or cover images. Easy detection of secret message for any state-of-art image steganography can break the stego system. To prevent the breakdown of the stego system two tier data hiding is used. In this paper, we propose a high capacity image steganography with greyscale primary cover. Predictive primary cover (PPC) is computed from the primary cover using median edge detector (MED) predictor. Predictive error (PE) is the difference between primary cover and the PPC. The high level bit planes of the secret image (payload) are X-ORed with low level bit planes of the PPC and vice-verse. The resulting Stego image is embedded in a secondary cover image using bit plane X-OR algorithm. The cover image used is an RGB colour image. The proposed steganography scheme enhances the level of security of the existing bit plane X-OR algorithm without considerably increasing the computation time and detectability. The experimental results show that the proposed scheme achieves higher level of security with high embedding capacity. Higher level of security achieved by the proposed multilayer steganography scheme enhances the performance and security of the bit plane X-OR algorithm.

High capacity secret image sharing using multilayer image steganography with primary cover predictive error

Image steganography is the art of hiding secret message in greyscale or cover images. Easy detection of secret message for any state-of-art image steganography can break the stego system. To prevent the breakdown of the stego system two tier data hiding is used. In this paper, we propose a high capacity image steganography with greyscale primary cover. Predictive primary cover PPC is computed from the primary cover using median edge detector MED predictor. Predictive error PE is the difference between primary cover and the PPC. The high level bit planes of the secret image payload are X-ORed with low level bit planes of the PPC and vice-verse. The resulting Stego image is embedded in a secondary cover image using bit plane X-OR algorithm. The cover image used is an RGB colour image. The proposed steganography scheme enhances the level of security of the existing bit plane X-OR algorithm without considerably increasing the computation time and detectability. The experimental results show that the proposed scheme achieves higher level of security with high embedding capacity. Higher level of security achieved by the proposed multilayer steganography scheme enhances the performance and security of the bit plane X-OR algorithm.

Near-wall fluid flow near the pinned contact line during droplet evaporation

Drop evaporation is a fundamental and complex phenomenon in nature and industrial processes. For the case of pinned contact line mode, however, we still lack a comprehensive understanding of the near-wall fluid flow during drop evaporation. In this paper, we measure the in-plane average velocities near the pinned contact line during evaporation of deionized water and aqueous ethanol solutions by the multilayer nano-particle image velocimetry (MnPIV) technique. The results show that the Marangoni convection near the triple-phase contact line is negligible for the flow pattern during the natural evaporation process without heat source being applied. The near-wall velocity profiles experience the decrease of thin film thickness just before the droplet shrinking process. The thin film thickness in the ethanol solution appears to decrease earlier than that in deionized water and the total shrinking time is much shorter than water. The thin film thickness decreases linearly before decreasing exponentially in about the first 100nm. The transition time also becomes earlier for the high-concentration solutions due to higher evaporation flux, while the transition thickness is larger for ethanol solutions with higher concentrations due to the inverse relation between the transition thickness and the surface tension.

Multiple‐Channel Local Binary Fitting Model for Medical Image Segmentation

This study proposes an innovative M-L (Multiple-channel local binary fitting) model for medical image segmentation. Designed to improve upon existing image segmentation models, the M-L model introduces a regional limit function to the multi-band active contour model to enable multilayer image segmentation. The Gaussian kernel function is used to improve the previous model's robustness, necessitating the use of a new initialization curve which enhances the accuracy of segmentation results. Compared to existing image segmentation methods, the proposed M-L model improves numerical stability and efficiency through the introduction of a new penalty term and an increased step length. This simulation experiment verifies the advantages of the new M-L model for improved medical image segmentation, including increased efficiency and usability of the model.

A knowledge-based multi-layered image annotation system

Major challenge in automatic image annotation is bridging the semantic gap between the computable low-level image features and the human-like interpretation of images. The interpretation includes concepts on different levels of abstraction that cannot be simply mapped to features but require additional reasoning with general and domain-specific knowledge. The problem is even more complex since knowledge in context of image interpretation is often incomplete, imprecise, uncertain and ambiguous in nature. Thus, in this paper we propose a fuzzy-knowledge based intelligent system for image annotation, which is able to deal with uncertain and ambiguous knowledge and can annotate images with concepts on different levels of abstraction that is more human-like. The main contributions are associated with an original approach of using a fuzzy knowledge-representation scheme based on the Fuzzy Petri Net (KRFPN) formalism. The acquisition of knowledge is facilitated in a way that besides the general knowledge provided by the expert, the computable facts and rules about the concepts, as well as their reliability, are produced automatically from data. The reasoning capability of the fuzzy inference engine of the KRFPN is used in a novel way for inconsistency checking of the classified image segments, automatic scene recognition, and the inference of generalized and derived classes.The results of image interpretation of Corel images belonging to the domain of outdoor scenes achieved by the proposed system outperform the published results obtained on the same image base in terms of average precision and recall. Owing to the fuzzy-knowledge representation scheme, the obtained image interpretation is enriched with new, more general and abstract concepts that are close to concepts people use to interpret these images.

A New Model for Array Spatial Signature for Two-Layer Imaging With Applications to Nondestructive Testing Using Ultrasonic Arrays

Imaging multilayer materials is a common challenge in seismology, medical diagnosis, and nondestructive testing. One of the applications of multilayer imaging is ultrasonic immersion test where the material under test and the transducer array are immersed in water. The main imaging challenge in immersion test (or in imaging any multilayer medium) is that since the sound wave propagates with different speeds in different layers of a multilayer medium, such a medium cannot be assumed homogenous. As a result, calculating the sound travel time for the received signal due to backscattering from such a nonhomogenous medium is not as straightforward as in the case of homogenous materials. In this paper, we propose a new model for the array spatial signature which can be used in frequency-domain algorithms that are used for imaging a two-layer medium when an array of transducers is utilized. To do so, we model the interface between the two layers as a spatially distributed source which consists of infinite number of point sources. Then, we use this model to develop a new array spatial signature for any point inside the second layer of a two-layer medium. This new array spatial signature can be used for multilayer ultrasonic imaging in frequency-domain imaging techniques including the conventional beamforming technique, the MUSIC method, and the Capon algorithm. Numerical simulations as well as experimental data are used to examine the accuracy of the proposed model.

Near-Wall Velocity and Temperature Measurements in the Meniscus Region for Staggered Glass Beads.

Velocity and temperature fields in the meniscus are crucial for the heat transfer mechanism in porous medium. The meniscus zone, however, is narrow so that it is difficult for observation. The velocimetry and thermometry in the near-wall region of the surface provide possible measurement methods with the development of micro/nanotechnology. Being exponentially decay in the intensity, the evanescent-wave illumination has the advantage of high spatial resolution and non-intrusion for these measurement methods. The multilayer nano-particle image velocimetry (MnPIV) uses the evanescent-wave illumination, decayed exponentially with the wall-normal distance, to obtain near-wall velocity data at different distances from the wall. The thermometry in the meniscus region could also use the evanescent-wave to illuminate the fluorescence dye, the emitted intensity of which changes with temperature. In this paper, these techniques are employed to measure the near-wall velocity and temperature between the porous media and the ITO heater, in order to explore the role of meniscus during convection of water. Near-wall velocity and temperature of the deionized water, seeded with 100 nm fluorescent colloidal tracers and flow in the staggered glass beads with diameters ranging from 2 mm to 6 mm, are obtained and discussed.

NERO’S ANCESTRY AND THE CONSTRUCTION OF IMPERIAL IDEOLOGY IN THE EARLY EMPIRE. A METHODOLOGICAL CASE STUDY

Within the discipline of ancient history, diverse types of sources, such as coins, inscriptions, portraits and texts, are often combined to create a coherent image of a particular ruler. A good example of how such a process works is the way in which reconstructions by modern scholars of the emperor Nero tend to look for a clearly defined ‘Neronian image’, by bringing together various types of primary evidence without paying sufficient attention to these sources’ medial contexts. This article argues that such a reconstruction does not do justice to the complex and multi-layered image of the last Julio-Claudian. By focusing on one particular aspect of Neronian imagery, the propagation of this emperor’s ancestry, we will argue that different types of sources, stemming from varying contexts and addressing different groups, cannot unproblematically be combined. Through an investigation of the ancestral messages spread by imperial and provincial coins, epigraphic evidence and portraiture, it becomes clear that systematic analysis of ancient media, their various contexts and inconsistencies is needed before combining them. Such an analysis reveals patterns within the different sources and shows that, in creating imperial images, rulers were constrained by both medial and local traditions. Modern studies of ancient images should therefore consider this medial and geographical variety in order to do justice to the multi-faceted phenomenon of imperial representation.

A novel image annotation model based on content representation with multi-layer segmentation

Image automatic annotation is an important issue of semantic-based image retrieval, and it is still a challenging problem for the reason of semantic gap. In this paper, a novel model with three parts is proposed. The first one is multi-layer image segmentation, in which saliency analysis and normalized cut are combined to segment images into semantic regions in the first layer. While in the second layer, the semantic regions are segmented into grids further . The second one is image content representation by region-based bag-of-words (RBoW) model, which is the variant of BoW model. Considering the correlations of labels, we adopt second-order CRFs as the third part of our model to ensure the accuracy of automatic image annotation. Experimental results show that our multi-layer segmentation-based image annotation model can achieve promising performance for multi-labeling and outperform the model based on single-layer segmentation and previous algorithm on Corel 5K and Pascal VOC 2007 datasets .