[Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

PubMed

Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

2014-02-01

Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

Multi-Modal Traveler Information System - GCM Corridor Architecture Functional Requirements

DOT National Transportation Integrated Search

1997-11-17

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

PubMed

Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

2015-12-01

In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

Multi-modal diffuse optical techniques for breast cancer neoadjuvant chemotherapy monitoring (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cochran, Jeffrey M.; Busch, David R.; Ban, Han Y.; Kavuri, Venkaiah C.; Schweiger, Martin J.; Arridge, Simon R.; Yodh, Arjun G.

2017-02-01

We present high spatial density, multi-modal, parallel-plate Diffuse Optical Tomography (DOT) imaging systems for the purpose of breast tumor detection. One hybrid instrument provides time domain (TD) and continuous wave (CW) DOT at 64 source fiber positions. The TD diffuse optical spectroscopy with PMT- detection produces low-resolution images of absolute tissue scattering and absorption while the spatially dense array of CCD-coupled detector fibers (108 detectors) provides higher-resolution CW images of relative tissue optical properties. Reconstruction of the tissue optical properties, along with total hemoglobin concentration and tissue oxygen saturation, is performed using the TOAST software suite. Comparison of the spatially-dense DOT images and MR images allows for a robust validation of DOT against an accepted clinical modality. Additionally, the structural information from co-registered MR images is used as a spatial prior to improve the quality of the functional optical images and provide more accurate quantification of the optical and hemodynamic properties of tumors. We also present an optical-only imaging system that provides frequency domain (FD) DOT at 209 source positions with full CCD detection and incorporates optical fringe projection profilometry to determine the breast boundary. This profilometry serves as a spatial constraint, improving the quality of the DOT reconstructions while retaining the benefits of an optical-only device. We present initial images from both human subjects and phantoms to display the utility of high spatial density data and multi-modal information in DOT reconstruction with the two systems.

Multi-modal measurement of the myelin-to-axon diameter g-ratio in preterm-born neonates and adult controls.

PubMed

Melbourne, Andrew; Eaton-Rosen, Zach; De Vita, Enrico; Bainbridge, Alan; Cardoso, Manuel Jorge; Price, David; Cady, Ernest; Kendall, Giles S; Robertson, Nicola J; Marlow, Neil; Ourselin, Sébastien

2014-01-01

Infants born prematurely are at increased risk of adverse functional outcome. The measurement of white matter tissue composition and structure can help predict functional performance and this motivates the search for new multi-modal imaging biomarkers. In this work we develop a novel combined biomarker from diffusion MRI and multi-component T2 relaxation measurements in a group of infants born very preterm and scanned between 30 and 40 weeks equivalent gestational age. We also investigate this biomarker on a group of seven adult controls, using a multi-modal joint model-fitting strategy. The proposed emergent biomarker is tentatively related to axonal energetic efficiency (in terms of axonal membrane charge storage) and conduction velocity and is thus linked to the tissue electrical properties, giving it a good theoretical justification as a predictive measurement of functional outcome.

Electronic health record analysis via deep poisson factor models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration.

PubMed

Young Kim, Eun; Johnson, Hans J

2013-01-01

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

Multi-Modal Nano-Probes for Radionuclide and 5-color Near Infrared Optical Lymphatic Imaging

PubMed Central

Kobayashi, Hisataka; Koyama, Yoshinori; Barrett, Tristan; Hama, Yukihiro; Regino, Celeste A. S.; Shin, In Soo; Jang, Beom-Su; Le, Nhat; Paik, Chang H.; Choyke, Peter L.; Urano, Yasuteru

2008-01-01

Current contrast agents generally have one function and can only be imaged in monochrome, therefore, the majority of imaging methods can only impart uniparametric information. A single nano-particle has the potential to be loaded with multiple payloads. Such multi-modality probes have the ability to be imaged by more than one imaging technique, which could compensate for the weakness or even combine the advantages of each individual modality. Furthermore, optical imaging using different optical probes enables us to achieve multi-color in vivo imaging, wherein multiple parameters can be read from a single image. To allow differentiation of multiple optical signals in vivo, each probe should have a close but different near infrared emission. To this end, we synthesized nano-probes with multi-modal and multi-color potential, which employed a polyamidoamine dendrimer platform linked to both radionuclides and optical probes, permitting dual-modality scintigraphic and 5-color near infrared optical lymphatic imaging using a multiple excitation spectrally-resolved fluorescence imaging technique. PMID:19079788

The evolution of gadolinium based contrast agents: from single-modality to multi-modality

NASA Astrophysics Data System (ADS)

Zhang, Li; Liu, Ruiqing; Peng, Hui; Li, Penghui; Xu, Zushun; Whittaker, Andrew K.

2016-05-01

Gadolinium-based contrast agents are extensively used as magnetic resonance imaging (MRI) contrast agents due to their outstanding signal enhancement and ease of chemical modification. However, it is increasingly recognized that information obtained from single modal molecular imaging cannot satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research, due to its limitation and default rooted in single molecular imaging technique itself. To compensate for the deficiencies of single function magnetic resonance imaging contrast agents, the combination of multi-modality imaging has turned to be the research hotpot in recent years. This review presents an overview on the recent developments of the functionalization of gadolinium-based contrast agents, and their application in biomedicine applications.

Topology optimized design of functionally graded piezoelectric ultrasonic transducers

NASA Astrophysics Data System (ADS)

Rubio, Wilfredo Montealegre; Buiochi, Flávio; Adamowski, Julio Cezar; Silva, Emílio C. N.

2010-01-01

This work presents a new approach to systematically design piezoelectric ultrasonic transducers based on Topology Optimization Method (TOM) and Functionally Graded Material (FGM) concepts. The main goal is to find the optimal material distribution of Functionally Graded Piezoelectric Ultrasonic Transducers, to achieve the following requirements: (i) the transducer must be designed to have a multi-modal or uni-modal frequency response, which defines the kind of generated acoustic wave, either short pulse or continuous wave, respectively; (ii) the transducer is required to oscillate in a thickness extensional mode or piston-like mode, aiming at acoustic wave generation applications. Two kinds of piezoelectric materials are mixed for producing the FGM transducer. Material type 1 represents a PZT-5A piezoelectric ceramic and material type 2 represents a PZT-5H piezoelectric ceramic. To illustrate the proposed method, two Functionally Graded Piezoelectric Ultrasonic Transducers are designed. The TOM has shown to be a useful tool for designing Functionally Graded Piezoelectric Ultrasonic Transducers with uni-modal or multi-modal dynamic behavior.

Bi-Modal Micro-Cathode Arc Thruster for Cube Satellites

NASA Astrophysics Data System (ADS)

Chiu, Dereck

A new concept design, named the Bi-Modal Micro-Cathode Arc Thruster (BM-muCAT), has been introduced utilizing features from previous generations of muCATs and incorporating a multi-propellant functionality. This arc thruster is a micro-Newton level thruster based off of vacuum arc technology utilizing an enhanced magnetic field. Adjusting the magnetic field allows the thrusters performance to be varied. The goal of this thesis is to present a new generation of micro-cathode arc thrusters utilizing a bi-propellant, nickel and titanium, system. Three experimental procedures were run to test the new designs capabilities. Arc rotation experiment was used as a base experiment to ensure erosion was occurring uniformly along each electrode. Ion utilization efficiency was found, using an ion collector, to be up to 2% with the nickel material and 2.5% with the titanium material. Ion velocities were also studied using a time-of-flight method with an enhanced ion detection system. This system utilizes double electrostatic probes to measure plasma propagation. Ion velocities were measured to be 10km/s and 20km/s for nickel and titanium without a magnetic field. With an applied magnetic field of 0.2T, nickel ion velocities almost doubled to about 17km/s, while titanium ion velocities also increased to about 30km/s.

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

An evaluation of the effectiveness of a multi-modal intervention in frail and pre-frail older people with type 2 diabetes - the MID-Frail study: study protocol for a randomised controlled trial

PubMed Central

2014-01-01

Background Diabetes, a highly prevalent, chronic disease, is associated with increasing frailty and functional decline in older people, with concomitant personal, social, and public health implications. We describe the rationale and methods of the multi-modal intervention in diabetes in frailty (MID-Frail) study. Methods/Design The MID-Frail study is an open, randomised, multicentre study, with random allocation by clusters (each trial site) to a usual care group or an intervention group. A total of 1,718 subjects will be randomised with each site enrolling on average 14 or 15 subjects. The primary objective of the study is to evaluate, in comparison with usual clinical practice, the effectiveness of a multi-modal intervention (specific clinical targets, education, diet, and resistance training exercise) in frail and pre-frail subjects aged ≥70 years with type 2 diabetes in terms of the difference in function 2 years post-randomisation. Difference in function will be measured by changes in a summary ordinal score on the short physical performance battery (SPPB) of at least one point. Secondary outcomes include daily activities, economic evaluation, and quality of life. Discussion The MID-Frail study will provide evidence on the clinical, functional, social, and economic impact of a multi-modal approach in frail and pre-frail older people with type 2 diabetes. Trial registration ClinicalTrials.gov: NCT01654341. PMID:24456998

An evaluation of the effectiveness of a multi-modal intervention in frail and pre-frail older people with type 2 diabetes--the MID-Frail study: study protocol for a randomised controlled trial.

PubMed

Rodríguez-Mañas, Leocadio; Bayer, Antony J; Kelly, Mark; Zeyfang, Andrej; Izquierdo, Mikel; Laosa, Olga; Hardman, Timothy C; Sinclair, Alan J; Moreira, Severina; Cook, Justin

2014-01-24

Diabetes, a highly prevalent, chronic disease, is associated with increasing frailty and functional decline in older people, with concomitant personal, social, and public health implications. We describe the rationale and methods of the multi-modal intervention in diabetes in frailty (MID-Frail) study. The MID-Frail study is an open, randomised, multicentre study, with random allocation by clusters (each trial site) to a usual care group or an intervention group. A total of 1,718 subjects will be randomised with each site enrolling on average 14 or 15 subjects. The primary objective of the study is to evaluate, in comparison with usual clinical practice, the effectiveness of a multi-modal intervention (specific clinical targets, education, diet, and resistance training exercise) in frail and pre-frail subjects aged ≥70 years with type 2 diabetes in terms of the difference in function 2 years post-randomisation. Difference in function will be measured by changes in a summary ordinal score on the short physical performance battery (SPPB) of at least one point. Secondary outcomes include daily activities, economic evaluation, and quality of life. The MID-Frail study will provide evidence on the clinical, functional, social, and economic impact of a multi-modal approach in frail and pre-frail older people with type 2 diabetes. ClinicalTrials.gov: NCT01654341.

Advanced magnetic resonance imaging in glioblastoma: a review.

PubMed

Shukla, Gaurav; Alexander, Gregory S; Bakas, Spyridon; Nikam, Rahul; Talekar, Kiran; Palmer, Joshua D; Shi, Wenyin

2017-08-01

Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

A prototype hand-held tri-modal instrument for in vivo ultrasound, photoacoustic, and fluorescence imaging

NASA Astrophysics Data System (ADS)

Kang, Jeeun; Chang, Jin Ho; Wilson, Brian C.; Veilleux, Israel; Bai, Yanhui; DaCosta, Ralph; Kim, Kang; Ha, Seunghan; Lee, Jong Gun; Kim, Jeong Seok; Lee, Sang-Goo; Kim, Sun Mi; Lee, Hak Jong; Ahn, Young Bok; Han, Seunghee; Yoo, Yangmo; Song, Tai-Kyong

2015-03-01

Multi-modality imaging is beneficial for both preclinical and clinical applications as it enables complementary information from each modality to be obtained in a single procedure. In this paper, we report the design, fabrication, and testing of a novel tri-modal in vivo imaging system to exploit molecular/functional information from fluorescence (FL) and photoacoustic (PA) imaging as well as anatomical information from ultrasound (US) imaging. The same ultrasound transducer was used for both US and PA imaging, bringing the pulsed laser light into a compact probe by fiberoptic bundles. The FL subsystem is independent of the acoustic components but the front end that delivers and collects the light is physically integrated into the same probe. The tri-modal imaging system was implemented to provide each modality image in real time as well as co-registration of the images. The performance of the system was evaluated through phantom and in vivo animal experiments. The results demonstrate that combining the modalities does not significantly compromise the performance of each of the separate US, PA, and FL imaging techniques, while enabling multi-modality registration. The potential applications of this novel approach to multi-modality imaging range from preclinical research to clinical diagnosis, especially in detection/localization and surgical guidance of accessible solid tumors.

Multiple utility constrained multi-objective programs using Bayesian theory

NASA Astrophysics Data System (ADS)

Abbasian, Pooneh; Mahdavi-Amiri, Nezam; Fazlollahtabar, Hamed

2018-03-01

A utility function is an important tool for representing a DM's preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utility functions. We induce the probability of the utilities for each objective function using Bayesian theory. Illustrative examples considering dependence and independence of variables are worked through to demonstrate the usefulness of the proposed model.

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

NASA Technical Reports Server (NTRS)

Hearn, Tristan A.

2015-01-01

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Big data sharing and analysis to advance research in post-traumatic epilepsy.

PubMed

Duncan, Dominique; Vespa, Paul; Pitkanen, Asla; Braimah, Adebayo; Lapinlampi, Nina; Toga, Arthur W

2018-06-01

We describe the infrastructure and functionality for a centralized preclinical and clinical data repository and analytic platform to support importing heterogeneous multi-modal data, automatically and manually linking data across modalities and sites, and searching content. We have developed and applied innovative image and electrophysiology processing methods to identify candidate biomarkers from MRI, EEG, and multi-modal data. Based on heterogeneous biomarkers, we present novel analytic tools designed to study epileptogenesis in animal model and human with the goal of tracking the probability of developing epilepsy over time. Copyright © 2017. Published by Elsevier Inc.

Statistical properties of a utility measure of observer performance compared to area under the ROC curve

NASA Astrophysics Data System (ADS)

Abbey, Craig K.; Samuelson, Frank W.; Gallas, Brandon D.; Boone, John M.; Niklason, Loren T.

2013-03-01

The receiver operating characteristic (ROC) curve has become a common tool for evaluating diagnostic imaging technologies, and the primary endpoint of such evaluations is the area under the curve (AUC), which integrates sensitivity over the entire false positive range. An alternative figure of merit for ROC studies is expected utility (EU), which focuses on the relevant region of the ROC curve as defined by disease prevalence and the relative utility of the task. However if this measure is to be used, it must also have desirable statistical properties keep the burden of observer performance studies as low as possible. Here, we evaluate effect size and variability for EU and AUC. We use two observer performance studies recently submitted to the FDA to compare the EU and AUC endpoints. The studies were conducted using the multi-reader multi-case methodology in which all readers score all cases in all modalities. ROC curves from the study were used to generate both the AUC and EU values for each reader and modality. The EU measure was computed assuming an iso-utility slope of 1.03. We find mean effect sizes, the reader averaged difference between modalities, to be roughly 2.0 times as big for EU as AUC. The standard deviation across readers is roughly 1.4 times as large, suggesting better statistical properties for the EU endpoint. In a simple power analysis of paired comparison across readers, the utility measure required 36% fewer readers on average to achieve 80% statistical power compared to AUC.

Clinical Utility and Future Applications of PET/CT and PET/CMR in Cardiology

PubMed Central

Pan, Jonathan A.; Salerno, Michael

2016-01-01

Over the past several years, there have been major advances in cardiovascular positron emission tomography (PET) in combination with either computed tomography (CT) or, more recently, cardiovascular magnetic resonance (CMR). These multi-modality approaches have significant potential to leverage the strengths of each modality to improve the characterization of a variety of cardiovascular diseases and to predict clinical outcomes. This review will discuss current developments and potential future uses of PET/CT and PET/CMR for cardiovascular applications, which promise to add significant incremental benefits to the data provided by each modality alone. PMID:27598207

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2010-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...research, we designed a pilot study utilizing large scale parallel Grid computing harnessing nationwide infrastructure for medical image analysis . Also

Local and global processing of music in high-functioning persons with autism: beyond central coherence?

PubMed

Mottron, L; Peretz, I; Ménard, E

2000-11-01

A multi-modal abnormality in the integration of parts and whole has been proposed to account for a bias toward local stimuli in individuals with autism (Frith, 1989; Mottron & Belleville, 1993). In the current experiment, we examined the utility of hierarchical models in characterising musical information processing in autistic individuals. Participants were 13 high-functioning individuals with autism and 13 individuals of normal intelligence matched on chronological age, nonverbal IQ, and laterality, and without musical experience. The task consisted of same-different judgements of pairs of melodies. Differential local and global processing was assessed by manipulating the level, local or global, at which modifications occurred. No deficit was found in the two measures of global processing. In contrast, the clinical group performed better than the comparison group in the detection of change in nontransposed, contour-preserved melodies that tap local processing. These findings confirm the existence of a "local bias" in music perception in individuals with autism, but challenge the notion that it is accounted for by a deficit in global music processing. The present study suggests that enhanced processing of elementary physical properties of incoming stimuli, as found previously in the visual modality, may also exist in the auditory modality.

Privacy Preserving Facial and Fingerprint Multi-biometric Authentication

NASA Astrophysics Data System (ADS)

Anzaku, Esla Timothy; Sohn, Hosik; Ro, Yong Man

The cases of identity theft can be mitigated by the adoption of secure authentication methods. Biohashing and its variants, which utilizes secret keys and biometrics, are promising methods for secure authentication; however, their shortcoming is the degraded performance under the assumption that secret keys are compromised. In this paper, we extend the concept of Biohashing to multi-biometrics - facial and fingerprint traits. We chose these traits because they are widely used, howbeit, little research attention has been given to designing privacy preserving multi-biometric systems using them. Instead of just using a single modality (facial or fingerprint), we presented a framework for using both modalities. The improved performance of the proposed method, using face and fingerprint, as against either facial or fingerprint trait used in isolation is evaluated using two chimerical bimodal databases formed from publicly available facial and fingerprint databases.

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Transportation Planning and ITS : Putting the Pieces Together

DOT National Transportation Integrated Search

2000-01-01

It is time to mainstream ITS into the intermodal and multi-modal transportation plans of States and metropolitan regions. This publication shows how transportation planning can address ITS more fully and how ITS can be utilized to make the most of th...

Neurocognitive insights on conceptual knowledge and its breakdown

PubMed Central

Lambon Ralph, Matthew A.

2014-01-01

Conceptual knowledge reflects our multi-modal ‘semantic database’. As such, it brings meaning to all verbal and non-verbal stimuli, is the foundation for verbal and non-verbal expression and provides the basis for computing appropriate semantic generalizations. Multiple disciplines (e.g. philosophy, cognitive science, cognitive neuroscience and behavioural neurology) have striven to answer the questions of how concepts are formed, how they are represented in the brain and how they break down differentially in various neurological patient groups. A long-standing and prominent hypothesis is that concepts are distilled from our multi-modal verbal and non-verbal experience such that sensation in one modality (e.g. the smell of an apple) not only activates the intramodality long-term knowledge, but also reactivates the relevant intermodality information about that item (i.e. all the things you know about and can do with an apple). This multi-modal view of conceptualization fits with contemporary functional neuroimaging studies that observe systematic variation of activation across different modality-specific association regions dependent on the conceptual category or type of information. A second vein of interdisciplinary work argues, however, that even a smorgasbord of multi-modal features is insufficient to build coherent, generalizable concepts. Instead, an additional process or intermediate representation is required. Recent multidisciplinary work, which combines neuropsychology, neuroscience and computational models, offers evidence that conceptualization follows from a combination of modality-specific sources of information plus a transmodal ‘hub’ representational system that is supported primarily by regions within the anterior temporal lobe, bilaterally. PMID:24324236

SU-E-J-218: Novel Validation Paradigm of MRI to CT Deformation of Prostate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Padgett, K; University of Miami School of Medicine - Radiology, Miami, FL; Pirozzi, S

2015-06-15

Purpose: Deformable registration algorithms are inherently difficult to characterize in the multi-modality setting due to a significant differences in the characteristics of the different modalities (CT and MRI) as well as tissue deformations. We present a unique paradigm where this is overcome by utilizing a planning-MRI acquired within an hour of the planning-CT serving as a surrogate for quantifying MRI to CT deformation by eliminating the issues of multi-modality comparisons. Methods: For nine subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day asmore » the planning-CT (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets. The diagnostic-MRI was rigidly and deformably aligned to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. Additionally, the quality of rigid alignment was ranked by an imaging physicist. The distances between corresponding anatomical landmarks on rigid and deformed registrations (diagnostic-MR to planning-CT) were evaluated. Results: It was discovered that in cases where the rigid registration was of acceptable quality the deformable registration didn’t improve the alignment, this was true of all metrics employed. If the analysis is separated into cases where the rigid alignment was ranked as unacceptable the deformable registration significantly improved the alignment, 4.62mm residual error in landmarks as compared to 5.72mm residual error in rigid alignments with a p-value of 0.0008. Conclusion: This paradigm provides an ideal testing ground for MR to CT deformable registration algorithms by allowing for inter-modality comparisons of multi-modality registrations. Consistent positioning, bowel and bladder preparation may Result in higher quality rigid registrations than typically achieved which limits the impact of deformable registrations. In this study cases where significant differences exist, deformable registrations provide significant value.« less

Validation of diffuse optical tomography using a bi-functional optical-MRI contrast agent and a hybrid MRI-DOT system

NASA Astrophysics Data System (ADS)

Luk, Alex T.; Lin, Yuting; Grimmond, Brian; Sood, Anup; Uzgiris, Egidijus E.; Nalcioglu, Orhan; Gulsen, Gultekin

2013-03-01

Since diffuse optical tomography (DOT) is a low spatial resolution modality, it is desirable to validate its quantitative accuracy with another well-established imaging modality, such as magnetic resonance imaging (MRI). In this work, we have used a polymer based bi-functional MRI-optical contrast agent (Gd-DTPA-polylysine-IR800) in collaboration with GE Global Research. This multi-modality contrast agent provided not only co-localization but also the same kinetics, to cross-validate two imaging modalities. Bi-functional agents are injected to the rats and pharmacokinetics at the bladder are recovered using both optical and MR imaging. DOT results are validated using MRI results as "gold standard"

Operando Multi-modal Synchrotron Investigation for Structural and Chemical Evolution of Cupric Sulfide (CuS) Additive in Li-S battery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Ke; Zhao, Chonghang; Lin, Cheng-Hung

Conductive metal sulfides are promising multi-functional additives for future lithium-sulfur (Li-S) batteries. These can increase the sulfur cathode’s electrical conductivity to improve the battery’s power capability, as well as contribute to the overall cell-discharge capacity. This multi-functional electrode design showed initial promise; however, complicated interactions at the system level are accompanied by some detrimental side effects. The metal sulfide additives with a chemical conversion as the reaction mechanism, e.g., CuS and FeS 2, can increase the theoretical capacity of the Li-S system. However, these additives may cause undesired parasitic reactions, such as the dissolution of the additive in the electrolyte.more » Studying such complex reactions presents a challenge because it requires experimental methods that can track the chemical and structural evolution of the system during an electrochemical process. To address the fundamental mechanisms in these systems, we employed an operando multimodal x-ray characterization approach to study the structural and chemical evolution of the metal sulfide—utilizing powder diffraction and fluorescence imaging to resolve the former and absorption spectroscopy the latter—during lithiation and de-lithiation of a Li-S battery with CuS as the multi-functional cathode additive. The resulting elucidation of the structural and chemical evolution of the system leads to a new description of the reaction mechanism.« less

Operando Multi-modal Synchrotron Investigation for Structural and Chemical Evolution of Cupric Sulfide (CuS) Additive in Li-S battery

DOE PAGES

Sun, Ke; Zhao, Chonghang; Lin, Cheng-Hung; ...

2017-10-11

Conductive metal sulfides are promising multi-functional additives for future lithium-sulfur (Li-S) batteries. These can increase the sulfur cathode’s electrical conductivity to improve the battery’s power capability, as well as contribute to the overall cell-discharge capacity. This multi-functional electrode design showed initial promise; however, complicated interactions at the system level are accompanied by some detrimental side effects. The metal sulfide additives with a chemical conversion as the reaction mechanism, e.g., CuS and FeS 2, can increase the theoretical capacity of the Li-S system. However, these additives may cause undesired parasitic reactions, such as the dissolution of the additive in the electrolyte.more » Studying such complex reactions presents a challenge because it requires experimental methods that can track the chemical and structural evolution of the system during an electrochemical process. To address the fundamental mechanisms in these systems, we employed an operando multimodal x-ray characterization approach to study the structural and chemical evolution of the metal sulfide—utilizing powder diffraction and fluorescence imaging to resolve the former and absorption spectroscopy the latter—during lithiation and de-lithiation of a Li-S battery with CuS as the multi-functional cathode additive. The resulting elucidation of the structural and chemical evolution of the system leads to a new description of the reaction mechanism.« less

Distributed flow estimation and closed-loop control of an underwater vehicle with a multi-modal artificial lateral line.

PubMed

DeVries, Levi; Lagor, Francis D; Lei, Hong; Tan, Xiaobo; Paley, Derek A

2015-03-25

Bio-inspired sensing modalities enhance the ability of autonomous vehicles to characterize and respond to their environment. This paper concerns the lateral line of cartilaginous and bony fish, which is sensitive to fluid motion and allows fish to sense oncoming flow and the presence of walls or obstacles. The lateral line consists of two types of sensing modalities: canal neuromasts measure approximate pressure gradients, whereas superficial neuromasts measure local flow velocities. By employing an artificial lateral line, the performance of underwater sensing and navigation strategies is improved in dark, cluttered, or murky environments where traditional sensing modalities may be hindered. This paper presents estimation and control strategies enabling an airfoil-shaped unmanned underwater vehicle to assimilate measurements from a bio-inspired, multi-modal artificial lateral line and estimate flow properties for feedback control. We utilize potential flow theory to model the fluid flow past a foil in a uniform flow and in the presence of an upstream obstacle. We derive theoretically justified nonlinear estimation strategies to estimate the free stream flowspeed, angle of attack, and the relative position of an upstream obstacle. The feedback control strategy uses the estimated flow properties to execute bio-inspired behaviors including rheotaxis (the tendency of fish to orient upstream) and station-holding (the tendency of fish to position behind an upstream obstacle). A robotic prototype outfitted with a multi-modal artificial lateral line composed of ionic polymer metal composite and embedded pressure sensors experimentally demonstrates the distributed flow sensing and closed-loop control strategies.

Shapes, scents and sounds: quantifying the full multi-sensory basis of conceptual knowledge.

PubMed

Hoffman, Paul; Lambon Ralph, Matthew A

2013-01-01

Contemporary neuroscience theories assume that concepts are formed through experience in multiple sensory-motor modalities. Quantifying the contribution of each modality to different object categories is critical to understanding the structure of the conceptual system and to explaining category-specific knowledge deficits. Verbal feature listing is typically used to elicit this information but has a number of drawbacks: sensory knowledge often cannot easily be translated into verbal features and many features are experienced in multiple modalities. Here, we employed a more direct approach in which subjects rated their knowledge of objects in each sensory-motor modality separately. Compared with these ratings, feature listing over-estimated the importance of visual form and functional knowledge and under-estimated the contributions of other sensory channels. An item's sensory rating proved to be a better predictor of lexical-semantic processing speed than the number of features it possessed, suggesting that ratings better capture the overall quantity of sensory information associated with a concept. Finally, the richer, multi-modal rating data not only replicated the sensory-functional distinction between animals and non-living things but also revealed novel distinctions between different types of artefact. Hierarchical cluster analyses indicated that mechanical devices (e.g., vehicles) were distinct from other non-living objects because they had strong sound and motion characteristics, making them more similar to animals in this respect. Taken together, the ratings align with neuroscience evidence in suggesting that a number of distinct sensory processing channels make important contributions to object knowledge. Multi-modal ratings for 160 objects are provided as supplementary materials. Copyright © 2012 Elsevier Ltd. All rights reserved.

USING CMAQ-AIM TO EVALUATE THE GAS-PARTICLE PARTITIONING TREATMENT IN CMAQ

EPA Science Inventory

The Community Multi-scale Air Quality model (CMAQ) aerosol component utilizes a modal representation, where the size distribution is represented as a sum of three lognormal modes. Though the aerosol treatment in CMAQ is quite advanced compared to other operational air quality mo...

Multi-Family Pediatric Pain Group Therapy: Capturing Acceptance and Cultivating Change.

PubMed

Huestis, Samantha E; Kao, Grace; Dunn, Ashley; Hilliard, Austin T; Yoon, Isabel A; Golianu, Brenda; Bhandari, Rashmi P

2017-12-07

Behavioral health interventions for pediatric chronic pain include cognitive-behavioral (CBT), acceptance and commitment (ACT), and family-based therapies, though literature regarding multi-family therapy (MFT) is sparse. This investigation examined the utility and outcomes of the Courage to Act with Pain: Teens Identifying Values, Acceptance, and Treatment Effects (CAPTIVATE) program, which included all three modalities (CBT, ACT, MFT) for youth with chronic pain and their parents. Program utility, engagement, and satisfaction were evaluated via quantitative and qualitative feedback. Pain-specific psychological, behavioral, and interpersonal processes were examined along with outcomes related to disability, quality of life, pain interference, fatigue, anxiety, and depressive symptoms. Participants indicated that CAPTIVATE was constructive, engaging, and helpful for social and family systems. Clinical and statistical improvements with large effect sizes were captured for pain catastrophizing, acceptance, and protective parenting but not family functioning. Similar effects were found for functional disability, pain interference, fatigue, anxiety, and depression. Given the importance of targeting multiple systems in the management of pediatric chronic pain, preliminary findings suggest a potential new group-based treatment option for youth and families. Next steps involve evaluating the differential effect of the program over treatment as usual, as well as specific CBT, ACT, and MFT components and processes that may affect outcomes.

Joint MR-PET reconstruction using a multi-channel image regularizer

PubMed Central

Koesters, Thomas; Otazo, Ricardo; Bredies, Kristian; Sodickson, Daniel K

2016-01-01

While current state of the art MR-PET scanners enable simultaneous MR and PET measurements, the acquired data sets are still usually reconstructed separately. We propose a new multi-modality reconstruction framework using second order Total Generalized Variation (TGV) as a dedicated multi-channel regularization functional that jointly reconstructs images from both modalities. In this way, information about the underlying anatomy is shared during the image reconstruction process while unique differences are preserved. Results from numerical simulations and in-vivo experiments using a range of accelerated MR acquisitions and different MR image contrasts demonstrate improved PET image quality, resolution, and quantitative accuracy. PMID:28055827

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine

PubMed Central

Pettersson-Yeo, William; Benetti, Stefania; Marquand, Andre F.; Joules, Richard; Catani, Marco; Williams, Steve C. R.; Allen, Paul; McGuire, Philip; Mechelli, Andrea

2014-01-01

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a single decision function based on an integrated kernel matrix, or, by creating an ensemble of multiple single modality classifiers and integrating their predictions. Here, we describe four integrative approaches: (1) an un-weighted sum of kernels, (2) multi-kernel learning, (3) prediction averaging, and (4) majority voting, and compare their ability to enhance classification accuracy relative to the best single-modality classification accuracy. We achieve this by integrating structural, functional, and diffusion tensor magnetic resonance imaging data, in order to compare ultra-high risk (n = 19), first episode psychosis (n = 19) and healthy control subjects (n = 23). Our results show that (i) whilst integration can enhance classification accuracy by up to 13%, the frequency of such instances may be limited, (ii) where classification can be enhanced, simple methods may yield greater increases relative to more computationally complex alternatives, and, (iii) the potential for classification enhancement is highly influenced by the specific diagnostic comparison under consideration. In conclusion, our findings suggest that for moderately sized clinical neuroimaging datasets, combining different imaging modalities in a data-driven manner is no “magic bullet” for increasing classification accuracy. However, it remains possible that this conclusion is dependent on the use of neuroimaging modalities that had little, or no, complementary information to offer one another, and that the integration of more diverse types of data would have produced greater classification enhancement. We suggest that future studies ideally examine a greater variety of data types (e.g., genetic, cognitive, and neuroimaging) in order to identify the data types and combinations optimally suited to the classification of early stage psychosis. PMID:25076868

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine.

PubMed

Pettersson-Yeo, William; Benetti, Stefania; Marquand, Andre F; Joules, Richard; Catani, Marco; Williams, Steve C R; Allen, Paul; McGuire, Philip; Mechelli, Andrea

2014-01-01

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a single decision function based on an integrated kernel matrix, or, by creating an ensemble of multiple single modality classifiers and integrating their predictions. Here, we describe four integrative approaches: (1) an un-weighted sum of kernels, (2) multi-kernel learning, (3) prediction averaging, and (4) majority voting, and compare their ability to enhance classification accuracy relative to the best single-modality classification accuracy. We achieve this by integrating structural, functional, and diffusion tensor magnetic resonance imaging data, in order to compare ultra-high risk (n = 19), first episode psychosis (n = 19) and healthy control subjects (n = 23). Our results show that (i) whilst integration can enhance classification accuracy by up to 13%, the frequency of such instances may be limited, (ii) where classification can be enhanced, simple methods may yield greater increases relative to more computationally complex alternatives, and, (iii) the potential for classification enhancement is highly influenced by the specific diagnostic comparison under consideration. In conclusion, our findings suggest that for moderately sized clinical neuroimaging datasets, combining different imaging modalities in a data-driven manner is no "magic bullet" for increasing classification accuracy. However, it remains possible that this conclusion is dependent on the use of neuroimaging modalities that had little, or no, complementary information to offer one another, and that the integration of more diverse types of data would have produced greater classification enhancement. We suggest that future studies ideally examine a greater variety of data types (e.g., genetic, cognitive, and neuroimaging) in order to identify the data types and combinations optimally suited to the classification of early stage psychosis.

SU-F-BRF-10: Deformable MRI to CT Validation Employing Same Day Planning MRI for Surrogate Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Padgett, K; Stoyanova, R; Johnson, P

Purpose: To compare rigid and deformable registrations of the prostate in the multi-modality setting (diagnostic-MRI to planning-CT) by utilizing a planning-MRI as a surrogate. The surrogate allows for the direct quantitative analysis which can be difficult in the multi-modality domain where intensity mapping differs. Methods: For ten subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day in which the planning CT was collected (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets.more » The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. The deformed MRI was then rigidly aligned to the planning MRI which was used as the surrogate for the planning-CT. Agreement between the two MRI datasets was scored using intensity based metrics including Pearson correlation and normalized mutual information, NMI. A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb and combined areas. A similar method was used to assess a rigid registration between the diagnostic-MRI and planning-CT. Results: Utilizing the NMI, the deformable registrations were superior to the rigid registrations in 9 of 10 cases demonstrating a 15.94% improvement (p-value < 0.001) within the combined area. The Pearson correlation showed similar results with the deformable registration superior in the same number of cases and demonstrating a 6.97% improvement (p-value <0.011). Conclusion: Validating deformable multi-modality registrations using spatial intensity based metrics is difficult due to the inherent differences in intensity mapping. This population provides an ideal testing ground for MRI to CT deformable registrations by obviating the need for multi-modality comparisons which are inherently more challenging. Deformable registrations generated in this work significantly outperformed rigid alignments. Research reported in this abstract was supported by the NIH National Cancer Institute R21CA153826 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer” and Bankhead-Coley Cancer Research Program 10BT-03 “MRI-Guided Radiotherapy and Biomarkers for Prostate Cancer”.« less

Development of a Multi-modal Tissue Diagnostic System Combining High Frequency Ultrasound and Photoacoustic Imaging with Lifetime Fluorescence Spectroscopy

PubMed Central

Sun, Yang; Stephens, Douglas N.; Park, Jesung; Sun, Yinghua; Marcu, Laura; Cannata, Jonathan M.; Shung, K. Kirk

2010-01-01

We report the development and validate a multi-modal tissue diagnostic technology, which combines three complementary techniques into one system including ultrasound backscatter microscopy (UBM), photoacoustic imaging (PAI), and time-resolved laser-induced fluorescence spectroscopy (TR-LIFS). UBM enables the reconstruction of the tissue microanatomy. PAI maps the optical absorption heterogeneity of the tissue associated with structure information and has the potential to provide functional imaging of the tissue. Examination of the UBM and PAI images allows for localization of regions of interest for TR-LIFS evaluation of the tissue composition. The hybrid probe consists of a single element ring transducer with concentric fiber optics for multi-modal data acquisition. Validation and characterization of the multi-modal system and ultrasonic, photoacoustic, and spectroscopic data coregistration were conducted in a physical phantom with properties of ultrasound scattering, optical absorption, and fluorescence. The UBM system with the 41 MHz ring transducer can reach the axial and lateral resolution of 30 and 65 μm, respectively. The PAI system with 532 nm excitation light from a Nd:YAG laser shows great contrast for the distribution of optical absorbers. The TR-LIFS system records the fluorescence decay with the time resolution of ~300 ps and a high sensitivity of nM concentration range. Biological phantom constructed with different types of tissues (tendon and fat) was used to demonstrate the complementary information provided by the three modalities. Fluorescence spectra and lifetimes were compared to differentiate chemical composition of tissues at the regions of interest determined by the coregistered high resolution UBM and PAI image. Current results demonstrate that the fusion of these techniques enables sequentially detection of functional, morphological, and compositional features of biological tissue, suggesting potential applications in diagnosis of tumors and atherosclerotic plaques. PMID:21894259

Development of a Multi-modal Tissue Diagnostic System Combining High Frequency Ultrasound and Photoacoustic Imaging with Lifetime Fluorescence Spectroscopy.

PubMed

Sun, Yang; Stephens, Douglas N; Park, Jesung; Sun, Yinghua; Marcu, Laura; Cannata, Jonathan M; Shung, K Kirk

2008-01-01

We report the development and validate a multi-modal tissue diagnostic technology, which combines three complementary techniques into one system including ultrasound backscatter microscopy (UBM), photoacoustic imaging (PAI), and time-resolved laser-induced fluorescence spectroscopy (TR-LIFS). UBM enables the reconstruction of the tissue microanatomy. PAI maps the optical absorption heterogeneity of the tissue associated with structure information and has the potential to provide functional imaging of the tissue. Examination of the UBM and PAI images allows for localization of regions of interest for TR-LIFS evaluation of the tissue composition. The hybrid probe consists of a single element ring transducer with concentric fiber optics for multi-modal data acquisition. Validation and characterization of the multi-modal system and ultrasonic, photoacoustic, and spectroscopic data coregistration were conducted in a physical phantom with properties of ultrasound scattering, optical absorption, and fluorescence. The UBM system with the 41 MHz ring transducer can reach the axial and lateral resolution of 30 and 65 μm, respectively. The PAI system with 532 nm excitation light from a Nd:YAG laser shows great contrast for the distribution of optical absorbers. The TR-LIFS system records the fluorescence decay with the time resolution of ~300 ps and a high sensitivity of nM concentration range. Biological phantom constructed with different types of tissues (tendon and fat) was used to demonstrate the complementary information provided by the three modalities. Fluorescence spectra and lifetimes were compared to differentiate chemical composition of tissues at the regions of interest determined by the coregistered high resolution UBM and PAI image. Current results demonstrate that the fusion of these techniques enables sequentially detection of functional, morphological, and compositional features of biological tissue, suggesting potential applications in diagnosis of tumors and atherosclerotic plaques.

Enterprise-wide worklist management.

PubMed

Locko, Roberta C; Blume, Hartwig; Goble, John C

2002-01-01

Radiologists in multi-facility health care delivery networks must serve not only their own departments but also departments of associated clinical facilities. We describe our experience with a picture archiving and communication system (PACS) implementation that provides a dynamic view of relevant radiological workload across multiple facilities. We implemented a distributed query system that permits management of enterprise worklists based on modality, body part, exam status, and other criteria that span multiple compatible PACSs. Dynamic worklists, with lesser flexibility, can be constructed if the incompatible PACSs support specific DICOM functionality. Enterprise-wide worklists were implemented across Generations Plus/Northern Manhattan Health Network, linking radiology departments of three hospitals (Harlem, Lincoln, and Metropolitan) with 1465 beds and 4260 ambulatory patients per day. Enterprise-wide, dynamic worklist management improves utilization of radiologists and enhances the quality of care across large multi-facility health care delivery organizations. Integration of other workflow-related components remain a significant challenge.

A collaborative interaction and visualization multi-modal environment for surgical planning.

PubMed

Foo, Jung Leng; Martinez-Escobar, Marisol; Peloquin, Catherine; Lobe, Thom; Winer, Eliot

2009-01-01

The proliferation of virtual reality visualization and interaction technologies has changed the way medical image data is analyzed and processed. This paper presents a multi-modal environment that combines a virtual reality application with a desktop application for collaborative surgical planning. Both visualization applications can function independently but can also be synced over a network connection for collaborative work. Any changes to either application is immediately synced and updated to the other. This is an efficient collaboration tool that allows multiple teams of doctors with only an internet connection to visualize and interact with the same patient data simultaneously. With this multi-modal environment framework, one team working in the VR environment and another team from a remote location working on a desktop machine can both collaborate in the examination and discussion for procedures such as diagnosis, surgical planning, teaching and tele-mentoring.

The Function of Consciousness in Multisensory Integration

ERIC Educational Resources Information Center

Palmer, Terry D.; Ramsey, Ashley K.

2012-01-01

The function of consciousness was explored in two contexts of audio-visual speech, cross-modal visual attention guidance and McGurk cross-modal integration. Experiments 1, 2, and 3 utilized a novel cueing paradigm in which two different flash suppressed lip-streams cooccured with speech sounds matching one of these streams. A visual target was…

Quantitative Imaging Biomarkers of NAFLD

PubMed Central

Kinner, Sonja; Reeder, Scott B.

2016-01-01

Conventional imaging modalities, including ultrasonography (US), computed tomography (CT), and magnetic resonance (MR), play an important role in the diagnosis and management of patients with nonalcoholic fatty liver disease (NAFLD) by allowing noninvasive diagnosis of hepatic steatosis. However, conventional imaging modalities are limited as biomarkers of NAFLD for various reasons. Multi-parametric quantitative MRI techniques overcome many of the shortcomings of conventional imaging and allow comprehensive and objective evaluation of NAFLD. MRI can provide unconfounded biomarkers of hepatic fat, iron, and fibrosis in a single examination—a virtual biopsy has become a clinical reality. In this article, we will review the utility and limitation of conventional US, CT, and MR imaging for the diagnosis NAFLD. Recent advances in imaging biomarkers of NAFLD are also discussed with an emphasis in multi-parametric quantitative MRI. PMID:26848588

Introduction to clinical and laboratory (small-animal) image registration and fusion.

PubMed

Zanzonico, Pat B; Nehmeh, Sadek A

2006-01-01

Imaging has long been a vital component of clinical medicine and, increasingly, of biomedical research in small-animals. Clinical and laboratory imaging modalities can be divided into two general categories, structural (or anatomical) and functional (or physiological). The latter, in particular, has spawned what has come to be known as "molecular imaging". Image registration and fusion have rapidly emerged as invaluable components of both clinical and small-animal imaging and has lead to the development and marketing of a variety of multi-modality, e.g. PET-CT, devices which provide registered and fused three-dimensional image sets. This paper briefly reviews the basics of image registration and fusion and available clinical and small-animal multi-modality instrumentation.

Multi-Sensor Based State Prediction for Personal Mobility Vehicles

PubMed Central

Gupta, Pankaj; Umata, Ichiro; Watanabe, Atsushi; Even, Jani; Suyama, Takayuki; Ishii, Shin

2016-01-01

This paper presents a study on multi-modal human emotional state detection while riding a powered wheelchair (PMV; Personal Mobility Vehicle) in an indoor labyrinth-like environment. The study reports findings on the habituation of human stress response during self-driving. In addition, the effects of “loss of controllability”, change in the role of the driver to a passenger, are investigated via an autonomous driving modality. The multi-modal emotional state detector sensing framework consists of four sensing devices: electroencephalograph (EEG), heart inter-beat interval (IBI), galvanic skin response (GSR) and stressor level lever (in the case of autonomous riding). Physiological emotional state measurement characteristics are organized by time-scale, in terms of capturing slower changes (long-term) and quicker changes from moment-to-moment. Experimental results with fifteen participants regarding subjective emotional state reports and commercial software measurements validated the proposed emotional state detector. Short-term GSR and heart signal characterizations captured moment-to-moment emotional state during autonomous riding (Spearman correlation; ρ = 0.6, p < 0.001). Short-term GSR and EEG characterizations reliably captured moment-to-moment emotional state during self-driving (Classification accuracy; 69.7). Finally, long-term GSR and heart characterizations were confirmed to reliably capture slow changes during autonomous riding and also of emotional state during participant resting state. The purpose of this study and the exploration of various algorithms and sensors in a structured framework is to provide a comprehensive background for multi-modal emotional state prediction experiments and/or applications. Additional discussion regarding the feasibility and utility of the possibilities of these concepts are given. PMID:27732589

Multi-Sensor Based State Prediction for Personal Mobility Vehicles.

PubMed

Abdur-Rahim, Jamilah; Morales, Yoichi; Gupta, Pankaj; Umata, Ichiro; Watanabe, Atsushi; Even, Jani; Suyama, Takayuki; Ishii, Shin

2016-01-01

This paper presents a study on multi-modal human emotional state detection while riding a powered wheelchair (PMV; Personal Mobility Vehicle) in an indoor labyrinth-like environment. The study reports findings on the habituation of human stress response during self-driving. In addition, the effects of "loss of controllability", change in the role of the driver to a passenger, are investigated via an autonomous driving modality. The multi-modal emotional state detector sensing framework consists of four sensing devices: electroencephalograph (EEG), heart inter-beat interval (IBI), galvanic skin response (GSR) and stressor level lever (in the case of autonomous riding). Physiological emotional state measurement characteristics are organized by time-scale, in terms of capturing slower changes (long-term) and quicker changes from moment-to-moment. Experimental results with fifteen participants regarding subjective emotional state reports and commercial software measurements validated the proposed emotional state detector. Short-term GSR and heart signal characterizations captured moment-to-moment emotional state during autonomous riding (Spearman correlation; ρ = 0.6, p < 0.001). Short-term GSR and EEG characterizations reliably captured moment-to-moment emotional state during self-driving (Classification accuracy; 69.7). Finally, long-term GSR and heart characterizations were confirmed to reliably capture slow changes during autonomous riding and also of emotional state during participant resting state. The purpose of this study and the exploration of various algorithms and sensors in a structured framework is to provide a comprehensive background for multi-modal emotional state prediction experiments and/or applications. Additional discussion regarding the feasibility and utility of the possibilities of these concepts are given.

Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.

PubMed

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Deep learning for hybrid EEG-fNIRS brain–computer interface: application to motor imagery classification

NASA Astrophysics Data System (ADS)

Chiarelli, Antonio Maria; Croce, Pierpaolo; Merla, Arcangelo; Zappasodi, Filippo

2018-06-01

Objective. Brain–computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG with other neuroimaging technologies, such as functional near infrared spectroscopy (fNIRS). A crucial step of BCI is brain state classification from recorded signal features. Deep artificial neural networks (DNNs) recently reached unprecedented complex classification outcomes. These performances were achieved through increased computational power, efficient learning algorithms, valuable activation functions, and restricted or back-fed neurons connections. By expecting significant overall BCI performances, we investigated the capabilities of combining EEG and fNIRS recordings with state-of-the-art deep learning procedures. Approach. We performed a guided left and right hand motor imagery task on 15 subjects with a fixed classification response time of 1 s and overall experiment length of 10 min. Left versus right classification accuracy of a DNN in the multi-modal recording modality was estimated and it was compared to standalone EEG and fNIRS and other classifiers. Main results. At a group level we obtained significant increase in performance when considering multi-modal recordings and DNN classifier with synergistic effect. Significance. BCI performances can be significantly improved by employing multi-modal recordings that provide electrical and hemodynamic brain activity information, in combination with advanced non-linear deep learning classification procedures.

Magnetic resonance spectroscopy of fiber tracts in children with traumatic brain injury: A combined MRS - Diffusion MRI study.

PubMed

Dennis, Emily L; Babikian, Talin; Alger, Jeffry; Rashid, Faisal; Villalon-Reina, Julio E; Jin, Yan; Olsen, Alexander; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-05-10

Traumatic brain injury can cause extensive damage to the white matter (WM) of the brain. These disruptions can be especially damaging in children, whose brains are still maturing. Diffusion magnetic resonance imaging (dMRI) is the most commonly used method to assess WM organization, but it has limited resolution to differentiate causes of WM disruption. Magnetic resonance spectroscopy (MRS) yields spectra showing the levels of neurometabolites that can indicate neuronal/axonal health, inflammation, membrane proliferation/turnover, and other cellular processes that are on-going post-injury. Previous analyses on this dataset revealed a significant division within the msTBI patient group, based on interhemispheric transfer time (IHTT); one subgroup of patients (TBI-normal) showed evidence of recovery over time, while the other showed continuing degeneration (TBI-slow). We combined dMRI with MRS to better understand WM disruptions in children with moderate-severe traumatic brain injury (msTBI). Tracts with poorer WM organization, as shown by lower FA and higher MD and RD, also showed lower N-acetylaspartate (NAA), a marker of neuronal and axonal health and myelination. We did not find lower NAA in tracts with normal WM organization. Choline, a marker of inflammation, membrane turnover, or gliosis, did not show such associations. We further show that multi-modal imaging can improve outcome prediction over a single modality, as well as over earlier cognitive function measures. Our results suggest that demyelination plays an important role in WM disruption post-injury in a subgroup of msTBI children and indicate the utility of multi-modal imaging. © 2018 Wiley Periodicals, Inc.

MIND: modality independent neighbourhood descriptor for multi-modal deformable registration.

PubMed

Heinrich, Mattias P; Jenkinson, Mark; Bhushan, Manav; Matin, Tahreema; Gleeson, Fergus V; Brady, Sir Michael; Schnabel, Julia A

2012-10-01

Deformable registration of images obtained from different modalities remains a challenging task in medical image analysis. This paper addresses this important problem and proposes a modality independent neighbourhood descriptor (MIND) for both linear and deformable multi-modal registration. Based on the similarity of small image patches within one image, it aims to extract the distinctive structure in a local neighbourhood, which is preserved across modalities. The descriptor is based on the concept of image self-similarity, which has been introduced for non-local means filtering for image denoising. It is able to distinguish between different types of features such as corners, edges and homogeneously textured regions. MIND is robust to the most considerable differences between modalities: non-functional intensity relations, image noise and non-uniform bias fields. The multi-dimensional descriptor can be efficiently computed in a dense fashion across the whole image and provides point-wise local similarity across modalities based on the absolute or squared difference between descriptors, making it applicable for a wide range of transformation models and optimisation algorithms. We use the sum of squared differences of the MIND representations of the images as a similarity metric within a symmetric non-parametric Gauss-Newton registration framework. In principle, MIND would be applicable to the registration of arbitrary modalities. In this work, we apply and validate it for the registration of clinical 3D thoracic CT scans between inhale and exhale as well as the alignment of 3D CT and MRI scans. Experimental results show the advantages of MIND over state-of-the-art techniques such as conditional mutual information and entropy images, with respect to clinically annotated landmark locations. Copyright © 2012 Elsevier B.V. All rights reserved.

Enhancing resource coordination for multi-modal evacuation planning.

DOT National Transportation Integrated Search

2013-01-01

This research project seeks to increase knowledge about coordinating effective multi-modal evacuation for disasters. It does so by identifying, evaluating, and assessing : current transportation management approaches for multi-modal evacuation planni...

Body System Effects of a Multi-Modal Training Program Targeting Chronic, Motor Complete Thoracic Spinal Cord Injury.

PubMed

Gant, Katie L; Nagle, Kathleen G; Cowan, Rachel E; Field-Fote, Edelle C; Nash, Mark S; Kressler, Jochen; Thomas, Christine K; Castellanos, Mabelin; Widerström-Noga, Eva; Anderson, Kimberly D

2018-02-01

The safety and efficacy of pharmacological and cellular transplantation strategies are currently being evaluated in people with spinal cord injury (SCI). In studies of people with chronic SCIs, it is thought that functional recovery will be best achieved when drug or cell therapies are combined with rehabilitation protocols. However, any functional recovery attributed to the therapy may be confounded by the conditioned state of the body and by training-induced effects on neuroplasticity. For this reason, we sought to investigate the effects of a multi-modal training program on several body systems. The training program included body-weight-supported treadmill training for locomotion, circuit resistance training for upper body conditioning, functional electrical stimulation for activation of sublesional muscles, and wheelchair skills training for overall mobility. Eight participants with chronic, thoracic-level, motor-complete SCI completed the 12-week training program. After 12 weeks, upper extremity muscular strength improved significantly for all participants, and some participants experienced improvements in function, which may be explained by increased strength. Neurological function did not change. Changes in pain and spasticity were highly variable between participants. This is the first demonstration of the effect of this combination of four training modalities. However, balancing participant and study-site burden with capturing meaningful outcome measures is also an important consideration.

Visual tracking for multi-modality computer-assisted image guidance

NASA Astrophysics Data System (ADS)

Basafa, Ehsan; Foroughi, Pezhman; Hossbach, Martin; Bhanushali, Jasmine; Stolka, Philipp

2017-03-01

With optical cameras, many interventional navigation tasks previously relying on EM, optical, or mechanical guidance can be performed robustly, quickly, and conveniently. We developed a family of novel guidance systems based on wide-spectrum cameras and vision algorithms for real-time tracking of interventional instruments and multi-modality markers. These navigation systems support the localization of anatomical targets, support placement of imaging probe and instruments, and provide fusion imaging. The unique architecture - low-cost, miniature, in-hand stereo vision cameras fitted directly to imaging probes - allows for an intuitive workflow that fits a wide variety of specialties such as anesthesiology, interventional radiology, interventional oncology, emergency medicine, urology, and others, many of which see increasing pressure to utilize medical imaging and especially ultrasound, but have yet to develop the requisite skills for reliable success. We developed a modular system, consisting of hardware (the Optical Head containing the mini cameras) and software (components for visual instrument tracking with or without specialized visual features, fully automated marker segmentation from a variety of 3D imaging modalities, visual observation of meshes of widely separated markers, instant automatic registration, and target tracking and guidance on real-time multi-modality fusion views). From these components, we implemented a family of distinct clinical and pre-clinical systems (for combinations of ultrasound, CT, CBCT, and MRI), most of which have international regulatory clearance for clinical use. We present technical and clinical results on phantoms, ex- and in-vivo animals, and patients.

A Comprehensive, Multi-modal Evaluation of the Assessment System of an Undergraduate Research Methodology Course: Translating Theory into Practice.

PubMed

Mohammad Abdulghani, Hamza; G Ponnamperuma, Gominda; Ahmad, Farah; Amin, Zubair

2014-03-01

To evaluate assessment system of the 'Research Methodology Course' using utility criteria (i.e. validity, reliability, acceptability, educational impact, and cost-effectiveness). This study demonstrates comprehensive evaluation of assessment system and suggests a framework for similar courses. Qualitative and quantitative methods used for evaluation of the course assessment components (50 MCQ, 3 Short Answer Questions (SAQ) and research project) using the utility criteria. RESULTS of multiple evaluation methods for all the assessment components were collected and interpreted together to arrive at holistic judgments, rather than judgments based on individual methods or individual assessment. Face validity, evaluated using a self-administered questionnaire (response rate-88.7%) disclosed that the students perceived that there was an imbalance in the contents covered by the assessment. This was confirmed by the assessment blueprint. Construct validity was affected by the low correlation between MCQ and SAQ scores (r=0.326). There was a higher correlation between the project and MCQ (r=0.466)/SAQ (r=0.463) scores. Construct validity was also affected by the presence of recall type of MCQs (70%; 35/50), item construction flaws and non-functioning distractors. High discriminating indices (>0.35) were found in MCQs with moderate difficulty indices (0.3-0.7). Reliability of the MCQs was 0.75 which could be improved up to 0.8 by increasing the number of MCQs to at least 70. A positive educational impact was found in the form of the research project assessment driving students to present/publish their work in conferences/peer reviewed journals. Cost per student to complete the course was US$164.50. The multi-modal evaluation of an assessment system is feasible and provides thorough and diagnostic information. Utility of the assessment system could be further improved by modifying the psychometrically inappropriate assessment items.

A Comprehensive, Multi-modal Evaluation of the Assessment System of an Undergraduate Research Methodology Course: Translating Theory into Practice

PubMed Central

Mohammad Abdulghani, Hamza; G. Ponnamperuma, Gominda; Ahmad, Farah; Amin, Zubair

2014-01-01

Objective: To evaluate assessment system of the 'Research Methodology Course' using utility criteria (i.e. validity, reliability, acceptability, educational impact, and cost-effectiveness). This study demonstrates comprehensive evaluation of assessment system and suggests a framework for similar courses. Methods: Qualitative and quantitative methods used for evaluation of the course assessment components (50 MCQ, 3 Short Answer Questions (SAQ) and research project) using the utility criteria. Results of multiple evaluation methods for all the assessment components were collected and interpreted together to arrive at holistic judgments, rather than judgments based on individual methods or individual assessment. Results: Face validity, evaluated using a self-administered questionnaire (response rate-88.7%) disclosed that the students perceived that there was an imbalance in the contents covered by the assessment. This was confirmed by the assessment blueprint. Construct validity was affected by the low correlation between MCQ and SAQ scores (r=0.326). There was a higher correlation between the project and MCQ (r=0.466)/SAQ (r=0.463) scores. Construct validity was also affected by the presence of recall type of MCQs (70%; 35/50), item construction flaws and non-functioning distractors. High discriminating indices (>0.35) were found in MCQs with moderate difficulty indices (0.3-0.7). Reliability of the MCQs was 0.75 which could be improved up to 0.8 by increasing the number of MCQs to at least 70. A positive educational impact was found in the form of the research project assessment driving students to present/publish their work in conferences/peer reviewed journals. Cost per student to complete the course was US$164.50. Conclusions: The multi-modal evaluation of an assessment system is feasible and provides thorough and diagnostic information. Utility of the assessment system could be further improved by modifying the psychometrically inappropriate assessment items. PMID:24772117

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

Volume curtaining: a focus+context effect for multimodal volume visualization

NASA Astrophysics Data System (ADS)

Fairfield, Adam J.; Plasencia, Jonathan; Jang, Yun; Theodore, Nicholas; Crawford, Neil R.; Frakes, David H.; Maciejewski, Ross

2014-03-01

In surgical preparation, physicians will often utilize multimodal imaging scans to capture complementary information to improve diagnosis and to drive patient-specific treatment. These imaging scans may consist of data from magnetic resonance imaging (MR), computed tomography (CT), or other various sources. The challenge in using these different modalities is that the physician must mentally map the two modalities together during the diagnosis and planning phase. Furthermore, the different imaging modalities will be generated at various resolutions as well as slightly different orientations due to patient placement during scans. In this work, we present an interactive system for multimodal data fusion, analysis and visualization. Developed with partners from neurological clinics, this work discusses initial system requirements and physician feedback at the various stages of component development. Finally, we present a novel focus+context technique for the interactive exploration of coregistered multi-modal data.

Multimodal neural correlates of cognitive control in the Human Connectome Project.

PubMed

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions hypothesized to be modulated by cognitive control signaling, such as visual cortex. Taken together, these results illustrate the potential utility of multi-modal analyses in identifying the neural correlates of cognitive control across different indicators of brain structure and function. Copyright © 2017 Elsevier Inc. All rights reserved.

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

Capsule endoscopy in Crohn’s disease: Are we seeing any better?

PubMed Central

Hudesman, David; Mazurek, Jonathan; Swaminath, Arun

2014-01-01

Crohn’s disease (CD) is a complex, immune-mediated disorder that often requires a multi-modality approach for optimal diagnosis and management. While traditional methods include ileocolonoscopy and radiologic modalities, increasingly, capsule endoscopy (CE) has been incorporated into the algorithm for both the diagnosis and monitoring of CD. Multiple studies have examined the utility of this emerging technology in the management of CD, and have compared it to other available modalities. CE offers a noninvasive approach to evaluate areas of the small bowel that are difficult to reach with traditional endoscopy. Furthermore, CE maybe favored in specific sub segments of patients with inflammatory bowel disease (IBD), such as those with IBD unclassified (IBD-U), pediatric patients and patients with CD who have previously undergone surgery. PMID:25278698

vECTlab—A fully integrated multi-modality Monte Carlo simulation framework for the radiological imaging sciences

NASA Astrophysics Data System (ADS)

Peter, Jörg; Semmler, Wolfhard

2007-10-01

Alongside and in part motivated by recent advances in molecular diagnostics, the development of dual-modality instruments for patient and dedicated small animal imaging has gained attention by diverse research groups. The desire for such systems is high not only to link molecular or functional information with the anatomical structures, but also for detecting multiple molecular events simultaneously at shorter total acquisition times. While PET and SPECT have been integrated successfully with X-ray CT, the advance of optical imaging approaches (OT) and the integration thereof into existing modalities carry a high application potential, particularly for imaging small animals. A multi-modality Monte Carlo (MC) simulation approach at present has been developed that is able to trace high-energy (keV) as well as optical (eV) photons concurrently within identical phantom representation models. We show that the involved two approaches for ray-tracing keV and eV photons can be integrated into a unique simulation framework which enables both photon classes to be propagated through various geometry models representing both phantoms and scanners. The main advantage of such integrated framework for our specific application is the investigation of novel tomographic multi-modality instrumentation intended for in vivo small animal imaging through time-resolved MC simulation upon identical phantom geometries. Design examples are provided for recently proposed SPECT-OT and PET-OT imaging systems.

Evaluation of Title I Program, Community School Distrlct 31, New York City. 1978-79 School Year. Final Report, E.D.L. Reading Lab.

ERIC Educational Resources Information Center

Knight, Michael E.

This program was designed to improve reading skills and to provide intensive remediation for students in grades six through nine. Specialized materials and equipment were provided by Educational Development Laboratories (EDL). The EDL Reading Laboratory utilized the Learning 100 program, a multi-modality developmental and remedial program. Small…

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2009-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...pilot study to utilize large scale parallel Grid computing to harness the nationwide cluster infrastructure for optimization of medical image ... analysis parameters. Additionally, we investigated the use of cutting edge dataanalysis/ mining techniques as applied to Ultrasound, FFDM, and DCE-MRI Breast

[Comparative Study of Patient Identifications for Conventional and Portable Chest Radiographs Utilizing ROC Analysis].

PubMed

Kawashima, Hiroki; Hayashi, Norio; Ohno, Naoki; Matsuura, Yukihiro; Sanada, Shigeru

2015-08-01

To evaluate the patient identification ability of radiographers, previous and current chest radiographs were assessed with observer study utilizing a receiver operating characteristics (ROCs) analysis. This study included portable and conventional chest radiographs from 43 same and 43 different patients. The dataset used in this study was divided into the three following groups: (1) a pair of portable radiographs, (2) a pair of conventional radiographs, and (3) a combination of each type of radiograph. Seven observers participated in this ROC study, which aimed to identify same or different patients, using these datasets. ROC analysis was conducted to calculate the average area under ROC curve obtained by each observer (AUCave), and a statistical test was performed using the multi-reader multi-case method. Comparable results were obtained with pairs of portable (AUCave: 0.949) and conventional radiographs (AUCave: 0.951). In a comparison between the same modality, there were no significant differences. In contrast, the ability to identify patients by comparing a portable and conventional radiograph (AUCave: 0.873) was lower than with the matching datasets (p=0.002 and p=0.004, respectively). In conclusion, the use of different imaging modalities reduces radiographers' ability to identify their patients.

Functional-structural reorganisation of the neuronal network for auditory perception in subjects with unilateral hearing loss: Review of neuroimaging studies.

PubMed

Heggdal, Peder O Laugen; Brännström, Jonas; Aarstad, Hans Jørgen; Vassbotn, Flemming S; Specht, Karsten

2016-02-01

This paper aims to provide a review of studies using neuroimaging to measure functional-structural reorganisation of the neuronal network for auditory perception after unilateral hearing loss. A literature search was performed in PubMed. Search criterions were peer reviewed original research papers in English completed by the 11th of March 2015. Twelve studies were found to use neuroimaging in subjects with unilateral hearing loss. An additional five papers not identified by the literature search were provided by a reviewer. Thus, a total of 17 studies were included in the review. Four different neuroimaging methods were used in these studies: Functional magnetic resonance imaging (fMRI) (n = 11), diffusion tensor imaging (DTI) (n = 4), T1/T2 volumetric images (n = 2), magnetic resonance spectroscopy (MRS) (n = 1). One study utilized two imaging methods (fMRI and T1 volumetric images). Neuroimaging techniques could provide valuable information regarding the effects of unilateral hearing loss on both auditory and non-auditory performance. fMRI-studies showing a bilateral BOLD-response in patients with unilateral hearing loss have not yet been followed by DTI studies confirming their microstructural correlates. In addition, the review shows that an auditory modality-specific deficit could affect multi-modal brain regions and their connections. Copyright © 2015 Elsevier B.V. All rights reserved.

Noninvasively measuring oxygen saturation of human finger-joint vessels by multi-transducer functional photoacoustic tomography

NASA Astrophysics Data System (ADS)

Deng, Zijian; Li, Changhui

2016-06-01

Imaging small blood vessels and measuring their functional information in finger joint are still challenges for clinical imaging modalities. In this study, we developed a multi-transducer functional photoacoustic tomography (PAT) system and successfully imaged human finger-joint vessels from ˜1 mm to <0.2 mm in diameter. In addition, the oxygen saturation (SO2) values of these vessels were also measured. Our results demonstrate that PAT can provide both anatomical and functional information of individual finger-joint vessels with different sizes, which might help the study of finger-joint diseases, such as rheumatoid arthritis.

Contemporary Multi-Modal Historical Representations and the Teaching of Disciplinary Understandings in History

ERIC Educational Resources Information Center

Donnelly, Debra J.

2018-01-01

Traditional privileging of the printed text has been considerably eroded by rapid technological advancement and in Australia, as elsewhere, many History teaching programs feature an array of multi-modal historical representations. Research suggests that engagement with the visual and multi-modal constructs has the potential to enrich the pedagogy…

Multi-Modal Transportation System Simulation

DOT National Transportation Integrated Search

1971-01-01

THE PRESENT STATUS OF A LABORATORY BEING DEVELOPED FOR REAL-TIME SIMULATION OF COMMAND AND CONTROL FUNCTIONS IN TRANSPORTATION SYSTEMS IS DISCUSSED. DETAILS ARE GIVEN ON THE SIMULATION MODELS AND ON PROGRAMMING TECHNIQUES USED IN DEFINING AND EVALUAT...

Multifunctional quantum dots-based cancer diagnostics and stem cell therapeutics for regenerative medicine.

PubMed

Onoshima, Daisuke; Yukawa, Hiroshi; Baba, Yoshinobu

2015-12-01

A field of recent diagnostics and therapeutics has been advanced with quantum dots (QDs). QDs have developed into new formats of biomolecular sensing to push the limits of detection in biology and medicine. QDs can be also utilized as bio-probes or labels for biological imaging of living cells and tissues. More recently, QDs has been demonstrated to construct a multifunctional nanoplatform, where the QDs serve not only as an imaging agent, but also a nanoscaffold for diagnostic and therapeutic modalities. This review highlights the promising applications of multi-functionalized QDs as advanced nanosensors for diagnosing cancer and as innovative fluorescence probes for in vitro or in vivo stem cell imaging in regenerative medicine. Copyright © 2015 Elsevier B.V. All rights reserved.

Device, Algorithm and Integrated Modeling Research for Performance-Drive Multi-Modal Optical Sensors

DTIC Science & Technology

2012-12-17

to!feature!aided!tracking! using !spectral! information .! ! !iii! •! A!novel!technique!for!spectral!waveband!selection!was!developed!and! used !as! part! of ... of !spectral! information ! using !the!tunable!single;pixel!spectrometer!concept.! •! A! database! was! developed! of ! spectral! reflectance! measurements...exploring! the! utility! of ! spectral! and! polarimetric! information !to!help!with!the!vehicle!tracking!application.!Through!the! use ! of ! both

Pedestrian Levels of Service (LOS) at Muir Woods National Monument (California): An introduction to multi-modal LOS for parks and protected areas

Treesearch

Peter R. Pettengill; Robert E. Manning; William Valliere; Laura E. Anderson

2010-01-01

Historically, transportation planning and management have been guided largely by principles of efficiency. Specifically, the Transportation Research Board has utilized a levels of service (LOS) framework to assess quality of service in terms of traffic congestion, speed and travel time, and maximum road capacity. In the field of park and outdoor recreation management,...

Use of Multi-Modal Media and Tools in an Online Information Literacy Course: College Students' Attitudes and Perceptions

ERIC Educational Resources Information Center

Chen, Hsin-Liang; Williams, James Patrick

2009-01-01

This project studies the use of multi-modal media objects in an online information literacy class. One hundred sixty-two undergraduate students answered seven surveys. Significant relationships are found among computer skills, teaching materials, communication tools and learning experience. Multi-modal media objects and communication tools are…

Pre-Motor Response Time Benefits in Multi-Modal Displays

DTIC Science & Technology

2013-11-12

when animals are presented with stimuli from two sensory modalities as compared with stimulation from only one modality. The combinations of two...modality attention and orientation behaviors (see also Wallace, Meredith, & Stein, 609 !998). Multi-modal stimulation in the world is not always...perceptually when the stimuli are congruent. In another study, Craig (2006) had participants judge the direction of apparent motion by stimulating

Multi-Modal Traveler Information System - Information Clearinghouse Final Network

DOT National Transportation Integrated Search

1997-07-23

This Working Paper will summarize the lessons learned from the initial implementation of the Information Clearinghouse and outline the proposed configuration and functional capabilities of the Final Network. In addition, all new users added since Mar...

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

A graph-based approach for the retrieval of multi-modality medical images.

PubMed

Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

2014-02-01

In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state-of-the-art methods such as visual words using the scale- invariant feature transform (SIFT) and relational matrices representing the spatial arrangements of objects. Copyright © 2013 Elsevier B.V. All rights reserved.

Large-area photogrammetry based testing of wind turbine blades

NASA Astrophysics Data System (ADS)

Poozesh, Peyman; Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter; Harvey, Eric; Yarala, Rahul

2017-03-01

An optically based sensing system that can measure the displacement and strain over essentially the entire area of a utility-scale blade leads to a measurement system that can significantly reduce the time and cost associated with traditional instrumentation. This paper evaluates the performance of conventional three dimensional digital image correlation (3D DIC) and three dimensional point tracking (3DPT) approaches over the surface of wind turbine blades and proposes a multi-camera measurement system using dynamic spatial data stitching. The potential advantages for the proposed approach include: (1) full-field measurement distributed over a very large area, (2) the elimination of time-consuming wiring and expensive sensors, and (3) the need for large-channel data acquisition systems. There are several challenges associated with extending the capability of a standard 3D DIC system to measure entire surface of utility scale blades to extract distributed strain, deflection, and modal parameters. This paper only tries to address some of the difficulties including: (1) assessing the accuracy of the 3D DIC system to measure full-field distributed strain and displacement over the large area, (2) understanding the geometrical constraints associated with a wind turbine testing facility (e.g. lighting, working distance, and speckle pattern size), (3) evaluating the performance of the dynamic stitching method to combine two different fields of view by extracting modal parameters from aligned point clouds, and (4) determining the feasibility of employing an output-only system identification to estimate modal parameters of a utility scale wind turbine blade from optically measured data. Within the current work, the results of an optical measurement (one stereo-vision system) performed on a large area over a 50-m utility-scale blade subjected to quasi-static and cyclic loading are presented. The blade certification and testing is typically performed using International Electro-Technical Commission standard (IEC 61400-23). For static tests, the blade is pulled in either flap-wise or edge-wise directions to measure deflection or distributed strain at a few limited locations of a large-sized blade. Additionally, the paper explores the error associated with using a multi-camera system (two stereo-vision systems) in measuring 3D displacement and extracting structural dynamic parameters on a mock set up emulating a utility-scale wind turbine blade. The results obtained in this paper reveal that the multi-camera measurement system has the potential to identify the dynamic characteristics of a very large structure.

Architecture for a PACS primary diagnosis workstation

NASA Astrophysics Data System (ADS)

Shastri, Kaushal; Moran, Byron

1990-08-01

A major factor in determining the overall utility of a medical Picture Archiving and Communications (PACS) system is the functionality of the diagnostic workstation. Meyer-Ebrecht and Wendler [1] have proposed a modular picture computer architecture with high throughput and Perry et.al [2] have defined performance requirements for radiology workstations. In order to be clinically useful, a primary diagnosis workstation must not only provide functions of current viewing systems (e.g. mechanical alternators [3,4]) such as acceptable image quality, simultaneous viewing of multiple images, and rapid switching of image banks; but must also provide a diagnostic advantage over the current systems. This includes window-level functions on any image, simultaneous display of multi-modality images, rapid image manipulation, image processing, dynamic image display (cine), electronic image archival, hardcopy generation, image acquisition, network support, and an easy user interface. Implementation of such a workstation requires an underlying hardware architecture which provides high speed image transfer channels, local storage facilities, and image processing functions. This paper describes the hardware architecture of the Siemens Diagnostic Reporting Console (DRC) which meets these requirements.

Fixed Base Modal Survey of the MPCV Orion European Service Module Structural Test Article

NASA Technical Reports Server (NTRS)

Winkel, James P.; Akers, J. C.; Suarez, Vicente J.; Staab, Lucas D.; Napolitano, Kevin L.

2017-01-01

Recently, the MPCV Orion European Service Module Structural Test Article (E-STA) underwent sine vibration testing using the multi-axis shaker system at NASA GRC Plum Brook Station Mechanical Vibration Facility (MVF). An innovative approach using measured constraint shapes at the interface of E-STA to the MVF allowed high-quality fixed base modal parameters of the E-STA to be extracted, which have been used to update the E-STA finite element model (FEM), without the need for a traditional fixed base modal survey. This innovative approach provided considerable program cost and test schedule savings. This paper documents this modal survey, which includes the modal pretest analysis sensor selection, the fixed base methodology using measured constraint shapes as virtual references and measured frequency response functions, and post-survey comparison between measured and analysis fixed base modal parameters.

Eigenvectors phase correction in inverse modal problem

NASA Astrophysics Data System (ADS)

Qiao, Guandong; Rahmatalla, Salam

2017-12-01

The solution of the inverse modal problem for the spatial parameters of mechanical and structural systems is heavily dependent on the quality of the modal parameters obtained from the experiments. While experimental and environmental noises will always exist during modal testing, the resulting modal parameters are expected to be corrupted with different levels of noise. A novel methodology is presented in this work to mitigate the errors in the eigenvectors when solving the inverse modal problem for the spatial parameters. The phases of the eigenvector component were utilized as design variables within an optimization problem that minimizes the difference between the calculated and experimental transfer functions. The equation of motion in terms of the modal and spatial parameters was used as a constraint in the optimization problem. Constraints that reserve the positive and semi-positive definiteness and the inter-connectivity of the spatial matrices were implemented using semi-definite programming. Numerical examples utilizing noisy eigenvectors with augmented Gaussian white noise of 1%, 5%, and 10% were used to demonstrate the efficacy of the proposed method. The results showed that the proposed method is superior when compared with a known method in the literature.

Multi-modality image fusion based on enhanced fuzzy radial basis function neural networks.

PubMed

Chao, Zhen; Kim, Dohyeon; Kim, Hee-Joung

2018-04-01

In clinical applications, single modality images do not provide sufficient diagnostic information. Therefore, it is necessary to combine the advantages or complementarities of different modalities of images. Recently, neural network technique was applied to medical image fusion by many researchers, but there are still many deficiencies. In this study, we propose a novel fusion method to combine multi-modality medical images based on the enhanced fuzzy radial basis function neural network (Fuzzy-RBFNN), which includes five layers: input, fuzzy partition, front combination, inference, and output. Moreover, we propose a hybrid of the gravitational search algorithm (GSA) and error back propagation algorithm (EBPA) to train the network to update the parameters of the network. Two different patterns of images are used as inputs of the neural network, and the output is the fused image. A comparison with the conventional fusion methods and another neural network method through subjective observation and objective evaluation indexes reveals that the proposed method effectively synthesized the information of input images and achieved better results. Meanwhile, we also trained the network by using the EBPA and GSA, individually. The results reveal that the EBPGSA not only outperformed both EBPA and GSA, but also trained the neural network more accurately by analyzing the same evaluation indexes. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Multimodality medical image database for temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-05-01

This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Multi-Sensor Information Integration and Automatic Understanding

DTIC Science & Technology

2008-05-27

distributions for target tracks and class which are utilized by an active learning cueing management framework to optimally task the appropriate sensor...modality to cued regions of interest. Moreover, this active learning approach also facilitates analyst cueing to help resolve track ambiguities in complex...scenes. We intend to leverage SIG’s active learning with analyst cueing under future efforts with ONR and other DoD agencies. Obtaining long- term

Multi-Sensor Information Integration and Automatic Understanding

DTIC Science & Technology

2008-08-27

distributions for target tracks and class which are utilized by an active learning cueing management framework to optimally task the appropriate sensor modality...to cued regions of interest. Moreover, this active learning approach also facilitates analyst cueing to help resolve track ambiguities in complex...scenes. We intend to leverage SIG’s active learning with analyst cueing under future efforts with ONR and other DoD agencies. Obtaining long- term

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

Detection of relationships among multi-modal brain imaging meta-features via information flow.

PubMed

Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

2018-01-15

Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is powerful, intuitive and very efficiently provides a high-level overview of a massive data space. In our application it exposes both expected relationships and relationships very rarely considered worth investigating by clinical researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data

PubMed Central

Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F

2007-01-01

Background Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. Results We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: . Conclusion MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine. PMID:17937818

MindSeer: a portable and extensible tool for visualization of structural and functional neuroimaging data.

PubMed

Moore, Eider B; Poliakov, Andrew V; Lincoln, Peter; Brinkley, James F

2007-10-15

Three-dimensional (3-D) visualization of multimodality neuroimaging data provides a powerful technique for viewing the relationship between structure and function. A number of applications are available that include some aspect of 3-D visualization, including both free and commercial products. These applications range from highly specific programs for a single modality, to general purpose toolkits that include many image processing functions in addition to visualization. However, few if any of these combine both stand-alone and remote multi-modality visualization in an open source, portable and extensible tool that is easy to install and use, yet can be included as a component of a larger information system. We have developed a new open source multimodality 3-D visualization application, called MindSeer, that has these features: integrated and interactive 3-D volume and surface visualization, Java and Java3D for true cross-platform portability, one-click installation and startup, integrated data management to help organize large studies, extensibility through plugins, transparent remote visualization, and the ability to be integrated into larger information management systems. We describe the design and implementation of the system, as well as several case studies that demonstrate its utility. These case studies are available as tutorials or demos on the associated website: http://sig.biostr.washington.edu/projects/MindSeer. MindSeer provides a powerful visualization tool for multimodality neuroimaging data. Its architecture and unique features also allow it to be extended into other visualization domains within biomedicine.

Intra-operative label-free multimodal multiphoton imaging of breast cancer margins and microenvironment (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sun, Yi; You, Sixian; Tu, Haohua; Spillman, Darold R.; Marjanovic, Marina; Chaney, Eric J.; Liu, George Z.; Ray, Partha S.; Higham, Anna; Boppart, Stephen A.

2017-02-01

Label-free multi-photon imaging has been a powerful tool for studying tissue microstructures and biochemical distributions, particularly for investigating tumors and their microenvironments. However, it remains challenging for traditional bench-top multi-photon microscope systems to conduct ex vivo tumor tissue imaging in the operating room due to their bulky setups and laser sources. In this study, we designed, built, and clinically demonstrated a portable multi-modal nonlinear label-free microscope system that combined four modalities, including two- and three- photon fluorescence for studying the distributions of FAD and NADH, and second and third harmonic generation, respectively, for collagen fiber structures and the distribution of micro-vesicles found in tumors and the microenvironment. Optical realignments and switching between modalities were motorized for more rapid and efficient imaging and for a light-tight enclosure, reducing ambient light noise to only 5% within the brightly lit operating room. Using up to 20 mW of laser power after a 20x objective, this system can acquire multi-modal sets of images over 600 μm × 600 μm at an acquisition rate of 60 seconds using galvo-mirror scanning. This portable microscope system was demonstrated in the operating room for imaging fresh, resected, unstained breast tissue specimens, and for assessing tumor margins and the tumor microenvironment. This real-time label-free nonlinear imaging system has the potential to uniquely characterize breast cancer margins and the microenvironment of tumors to intraoperatively identify structural, functional, and molecular changes that could indicate the aggressiveness of the tumor.

Feature-based fusion of medical imaging data.

PubMed

Calhoun, Vince D; Adali, Tülay

2009-09-01

The acquisition of multiple brain imaging types for a given study is a very common practice. There have been a number of approaches proposed for combining or fusing multitask or multimodal information. These can be roughly divided into those that attempt to study convergence of multimodal imaging, for example, how function and structure are related in the same region of the brain, and those that attempt to study the complementary nature of modalities, for example, utilizing temporal EEG information and spatial functional magnetic resonance imaging information. Within each of these categories, one can attempt data integration (the use of one imaging modality to improve the results of another) or true data fusion (in which multiple modalities are utilized to inform one another). We review both approaches and present a recent computational approach that first preprocesses the data to compute features of interest. The features are then analyzed in a multivariate manner using independent component analysis. We describe the approach in detail and provide examples of how it has been used for different fusion tasks. We also propose a method for selecting which combination of modalities provides the greatest value in discriminating groups. Finally, we summarize and describe future research topics.

Intraoperative imaging-guided cancer surgery: from current fluorescence molecular imaging methods to future multi-modality imaging technology.

PubMed

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery.

Intraoperative Imaging-Guided Cancer Surgery: From Current Fluorescence Molecular Imaging Methods to Future Multi-Modality Imaging Technology

PubMed Central

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery. PMID:25250092

On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics

NASA Astrophysics Data System (ADS)

Mohammed Anzar, Sharafudeen Thaha; Sathidevi, Puthumangalathu Savithri

2014-12-01

In this paper, we have considered the utility of multi-normalization and ancillary measures, for the optimal score level fusion of fingerprint and voice biometrics. An efficient matching score preprocessing technique based on multi-normalization is employed for improving the performance of the multimodal system, under various noise conditions. Ancillary measures derived from the feature space and the score space are used in addition to the matching score vectors, for weighing the modalities, based on their relative degradation. Reliability (dispersion) and the separability (inter-/intra-class distance and d-prime statistics) measures under various noise conditions are estimated from the individual modalities, during the training/validation stage. The `best integration weights' are then computed by algebraically combining these measures using the weighted sum rule. The computed integration weights are then optimized against the recognition accuracy using techniques such as grid search, genetic algorithm and particle swarm optimization. The experimental results show that, the proposed biometric solution leads to considerable improvement in the recognition performance even under low signal-to-noise ratio (SNR) conditions and reduces the false acceptance rate (FAR) and false rejection rate (FRR), making the system useful for security as well as forensic applications.

Sensei: A Multi-Modal Framework for Assessing Stress Resiliency

DTIC Science & Technology

2013-04-30

DATE MAY2013 2. REPORT TYPE 4. TITLE AND SUBTITLE Sensei: A Multi-Modal Framework for Assessing Stress Resiliency 6. AUTHOR(S) 7. PERFORMING...Report: Distribution A Page 1 of 3 SRI International (Sarnoff) Document Sensei: A Multi-Modal Framework for Assessing Stress Resiliency (April... Stress Markers in Real-Time in Lab Environment with graded exposure to ICT’s scenarios MAC 1-6 During this reporting period, we established

Interactive dual-volume rendering visualization with real-time fusion and transfer function enhancement

NASA Astrophysics Data System (ADS)

Macready, Hugh; Kim, Jinman; Feng, David; Cai, Weidong

2006-03-01

Dual-modality imaging scanners combining functional PET and anatomical CT constitute a challenge in volumetric visualization that can be limited by the high computational demand and expense. This study aims at providing physicians with multi-dimensional visualization tools, in order to navigate and manipulate the data running on a consumer PC. We have maximized the utilization of pixel-shader architecture of the low-cost graphic hardware and the texture-based volume rendering to provide visualization tools with high degree of interactivity. All the software was developed using OpenGL and Silicon Graphics Inc. Volumizer, tested on a Pentium mobile CPU on a PC notebook with 64M graphic memory. We render the individual modalities separately, and performing real-time per-voxel fusion. We designed a novel "alpha-spike" transfer function to interactively identify structure of interest from volume rendering of PET/CT. This works by assigning a non-linear opacity to the voxels, thus, allowing the physician to selectively eliminate or reveal information from the PET/CT volumes. As the PET and CT are rendered independently, manipulations can be applied to individual volumes, for instance, the application of transfer function to CT to reveal the lung boundary while adjusting the fusion ration between the CT and PET to enhance the contrast of a tumour region, with the resultant manipulated data sets fused together in real-time as the adjustments are made. In addition to conventional navigation and manipulation tools, such as scaling, LUT, volume slicing, and others, our strategy permits efficient visualization of PET/CT volume rendering which can potentially aid in interpretation and diagnosis.

Potential of PET-MRI for imaging of non-oncologic musculoskeletal disease.

PubMed

Kogan, Feliks; Fan, Audrey P; Gold, Garry E

2016-12-01

Early detection of musculoskeletal disease leads to improved therapies and patient outcomes, and would benefit greatly from imaging at the cellular and molecular level. As it becomes clear that assessment of multiple tissues and functional processes are often necessary to study the complex pathogenesis of musculoskeletal disorders, the role of multi-modality molecular imaging becomes increasingly important. New positron emission tomography-magnetic resonance imaging (PET-MRI) systems offer to combine high-resolution MRI with simultaneous molecular information from PET to study the multifaceted processes involved in numerous musculoskeletal disorders. In this article, we aim to outline the potential clinical utility of hybrid PET-MRI to these non-oncologic musculoskeletal diseases. We summarize current applications of PET molecular imaging in osteoarthritis (OA), rheumatoid arthritis (RA), metabolic bone diseases and neuropathic peripheral pain. Advanced MRI approaches that reveal biochemical and functional information offer complementary assessment in soft tissues. Additionally, we discuss technical considerations for hybrid PET-MR imaging including MR attenuation correction, workflow, radiation dose, and quantification.

A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring.

PubMed

Pantelopoulos, Alexandros; Saldivar, Enrique; Roham, Masoud

2011-01-01

In this paper a wireless modular, multi-modal, multi-node patch platform is described. The platform comprises low-cost semi-disposable patch design aiming at unobtrusive ambulatory monitoring of multiple physiological parameters. Owing to its modular design it can be interfaced with various low-power RF communication and data storage technologies, while the data fusion of multi-modal and multi-node features facilitates measurement of several biosignals from multiple on-body locations for robust feature extraction. Preliminary results of the patch platform are presented which illustrate the capability to extract respiration rate from three different independent metrics, which combined together can give a more robust estimate of the actual respiratory rate.

Multi-Modal Use of a Socially Directed Call in Bonobos

PubMed Central

Genty, Emilie; Clay, Zanna; Hobaiter, Catherine; Zuberbühler, Klaus

2014-01-01

‘Contest hoots’ are acoustically complex vocalisations produced by adult and subadult male bonobos (Pan paniscus). These calls are often directed at specific individuals and regularly combined with gestures and other body signals. The aim of our study was to describe the multi-modal use of this call type and to clarify its communicative and social function. To this end, we observed two large groups of bonobos, which generated a sample of 585 communicative interactions initiated by 10 different males. We found that contest hooting, with or without other associated signals, was produced to challenge and provoke a social reaction in the targeted individual, usually agonistic chase. Interestingly, ‘contest hoots’ were sometimes also used during friendly play. In both contexts, males were highly selective in whom they targeted by preferentially choosing individuals of equal or higher social rank, suggesting that the calls functioned to assert social status. Multi-modal sequences were not more successful in eliciting reactions than contest hoots given alone, but we found a significant difference in the choice of associated gestures between playful and agonistic contexts. During friendly play, contest hoots were significantly more often combined with soft than rough gestures compared to agonistic challenges, while the calls' acoustic structure remained the same. We conclude that contest hoots indicate the signaller's intention to interact socially with important group members, while the gestures provide additional cues concerning the nature of the desired interaction. PMID:24454745

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

PubMed Central

Goscinski, Wojtek J.; McIntosh, Paul; Felzmann, Ulrich; Maksimenko, Anton; Hall, Christopher J.; Gureyev, Timur; Thompson, Darren; Janke, Andrew; Galloway, Graham; Killeen, Neil E. B.; Raniga, Parnesh; Kaluza, Owen; Ng, Amanda; Poudel, Govinda; Barnes, David G.; Nguyen, Toan; Bonnington, Paul; Egan, Gary F.

2014-01-01

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. PMID:24734019

Cross contrast multi-channel image registration using image synthesis for MR brain images.

PubMed

Chen, Min; Carass, Aaron; Jog, Amod; Lee, Junghoon; Roy, Snehashis; Prince, Jerry L

2017-02-01

Multi-modal deformable registration is important for many medical image analysis tasks such as atlas alignment, image fusion, and distortion correction. Whereas a conventional method would register images with different modalities using modality independent features or information theoretic metrics such as mutual information, this paper presents a new framework that addresses the problem using a two-channel registration algorithm capable of using mono-modal similarity measures such as sum of squared differences or cross-correlation. To make it possible to use these same-modality measures, image synthesis is used to create proxy images for the opposite modality as well as intensity-normalized images from each of the two available images. The new deformable registration framework was evaluated by performing intra-subject deformation recovery, intra-subject boundary alignment, and inter-subject label transfer experiments using multi-contrast magnetic resonance brain imaging data. Three different multi-channel registration algorithms were evaluated, revealing that the framework is robust to the multi-channel deformable registration algorithm that is used. With a single exception, all results demonstrated improvements when compared against single channel registrations using the same algorithm with mutual information. Copyright © 2016 Elsevier B.V. All rights reserved.

Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration

PubMed Central

Blinowska, Katarzyna; Müller-Putz, Gernot; Kaiser, Vera; Astolfi, Laura; Vanderperren, Katrien; Van Huffel, Sabine; Lemieux, Louis

2009-01-01

Until relatively recently the vast majority of imaging and electrophysiological studies of human brain activity have relied on single-modality measurements usually correlated with readily observable or experimentally modified behavioural or brain state patterns. Multi-modal imaging is the concept of bringing together observations or measurements from different instruments. We discuss the aims of multi-modal imaging and the ways in which it can be accomplished using representative applications. Given the importance of haemodynamic and electrophysiological signals in current multi-modal imaging applications, we also review some of the basic physiology relevant to understanding their relationship. PMID:19547657

Computational Intelligence Techniques for Tactile Sensing Systems

PubMed Central

Gastaldo, Paolo; Pinna, Luigi; Seminara, Lucia; Valle, Maurizio; Zunino, Rodolfo

2014-01-01

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach. PMID:24949646

Computational intelligence techniques for tactile sensing systems.

PubMed

Gastaldo, Paolo; Pinna, Luigi; Seminara, Lucia; Valle, Maurizio; Zunino, Rodolfo

2014-06-19

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach.

Adding Pluggable and Personalized Natural Control Capabilities to Existing Applications

PubMed Central

Lamberti, Fabrizio; Sanna, Andrea; Carlevaris, Gilles; Demartini, Claudio

2015-01-01

Advancements in input device and sensor technologies led to the evolution of the traditional human-machine interaction paradigm based on the mouse and keyboard. Touch-, gesture- and voice-based interfaces are integrated today in a variety of applications running on consumer devices (e.g., gaming consoles and smartphones). However, to allow existing applications running on desktop computers to utilize natural interaction, significant re-design and re-coding efforts may be required. In this paper, a framework designed to transparently add multi-modal interaction capabilities to applications to which users are accustomed is presented. Experimental observations confirmed the effectiveness of the proposed framework and led to a classification of those applications that could benefit more from the availability of natural interaction modalities. PMID:25635410

Solid tumors.

PubMed

Richardson, R C

1985-05-01

Soft-tissue tumors are similar in their behavior. Benign tumors can be easily resected in most cases, whereas malignant tumors are relentless in their locally invasive characteristics. A clear understanding of the constraints of the pathologist in reaching a confirmed diagnosis and a logical plan utilizing surgery as the major modality of therapy are necessary for successful management of these tumors. It appears that radiation combined with hyperthermia is beginning to play a significant role in the local control of soft-tissue sarcomas and that single or multi-agent chemotherapy may be of benefit in treatment of nonresectable or metastatic soft-tissue sarcomas. For the immediate future, surgery remains the only nonexperimental modality of therapy, but the rapid advances in the other therapy methods are encouraging.

Adding pluggable and personalized natural control capabilities to existing applications.

PubMed

Lamberti, Fabrizio; Sanna, Andrea; Carlevaris, Gilles; Demartini, Claudio

2015-01-28

Advancements in input device and sensor technologies led to the evolution of the traditional human-machine interaction paradigm based on the mouse and keyboard. Touch-, gesture- and voice-based interfaces are integrated today in a variety of applications running on consumer devices (e.g., gaming consoles and smartphones). However, to allow existing applications running on desktop computers to utilize natural interaction, significant re-design and re-coding efforts may be required. In this paper, a framework designed to transparently add multi-modal interaction capabilities to applications to which users are accustomed is presented. Experimental observations confirmed the effectiveness of the proposed framework and led to a classification of those applications that could benefit more from the availability of natural interaction modalities.

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

PubMed

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Stochastic Approaches to Understanding Dissociations in Inflectional Morphology

ERIC Educational Resources Information Center

Plunkett, Kim; Bandelow, Stephan

2006-01-01

Computer modelling research has undermined the view that double dissociations in behaviour are sufficient to infer separability in the cognitive mechanisms underlying those behaviours. However, all these models employ "multi-modal" representational schemes, where functional specialisation of processing emerges from the training process.…

Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation.

PubMed

Eytan, Danny; Pang, Elizabeth W; Doesburg, Sam M; Nenadovic, Vera; Gavrilovic, Bojan; Laussen, Peter; Guerguerian, Anne-Marie

2016-01-01

Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.

Rhesus macaques recognize unique multi-modal face-voice relations of familiar individuals and not of unfamiliar ones

PubMed Central

Habbershon, Holly M.; Ahmed, Sarah Z.; Cohen, Yale E.

2013-01-01

Communication signals in non-human primates are inherently multi-modal. However, for laboratory-housed monkeys, there is relatively little evidence in support of the use of multi-modal communication signals in individual recognition. Here, we used a preferential-looking paradigm to test whether laboratory-housed rhesus could “spontaneously” (i.e., in the absence of operant training) use multi-modal communication stimuli to discriminate between known conspecifics. The multi-modal stimulus was a silent movie of two monkeys vocalizing and an audio file of the vocalization from one of the monkeys in the movie. We found that the gaze patterns of those monkeys that knew the individuals in the movie were reliably biased toward the individual that did not produce the vocalization. In contrast, there was not a systematic gaze pattern for those monkeys that did not know the individuals in the movie. These data are consistent with the hypothesis that laboratory-housed rhesus can recognize and distinguish between conspecifics based on auditory and visual communication signals. PMID:23774779

Extraction of Modal Parameters from Spacecraft Flight Data

NASA Technical Reports Server (NTRS)

James, George H.; Cao, Timothy T.; Fogt, Vincent A.; Wilson, Robert L.; Bartkowicz, Theodore J.

2010-01-01

The modeled response of spacecraft systems must be validated using flight data as ground tests cannot adequately represent the flight. Tools from the field of operational modal analysis would typically be brought to bear on such structures. However, spacecraft systems have several complicated issues: 1. High amplitudes of loads; 2. Compressive loads on the vehicle in flight; 3. Lack of generous time-synchronized flight data; 4. Changing properties during the flight; and 5. Major vehicle changes due to staging. A particularly vexing parameter to extract is modal damping. Damping estimation has become a more critical issue as new mass-driven vehicle designs seek to use the highest damping value possible. The paper will focus on recent efforts to utilize spacecraft flight data to extract system parameters, with a special interest on modal damping. This work utilizes the analysis of correlation functions derived from a sliding window technique applied to the time record. Four different case studies are reported in the sequence that drove the authors understanding. The insights derived from these four exercises are preliminary conclusions for the general state-of-the-art, but may be of specific utility to similar problems approached with similar tools.

The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample.

PubMed

Taylor, Jason R; Williams, Nitin; Cusack, Rhodri; Auer, Tibor; Shafto, Meredith A; Dixon, Marie; Tyler, Lorraine K; Cam-Can; Henson, Richard N

2017-01-01

This paper describes the data repository for the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) initial study cohort. The Cam-CAN Stage 2 repository contains multi-modal (MRI, MEG, and cognitive-behavioural) data from a large (approximately N=700), cross-sectional adult lifespan (18-87years old) population-based sample. The study is designed to characterise age-related changes in cognition and brain structure and function, and to uncover the neurocognitive mechanisms that support healthy cognitive ageing. The database contains raw and preprocessed structural MRI, functional MRI (active tasks and resting state), and MEG data (active tasks and resting state), as well as derived scores from cognitive behavioural experiments spanning five broad domains (attention, emotion, action, language, and memory), and demographic and neuropsychological data. The dataset thus provides a depth of neurocognitive phenotyping that is currently unparalleled, enabling integrative analyses of age-related changes in brain structure, brain function, and cognition, and providing a testbed for novel analyses of multi-modal neuroimaging data. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Multiscale and multi-modality visualization of angiogenesis in a human breast cancer model

PubMed Central

Cebulla, Jana; Kim, Eugene; Rhie, Kevin; Zhang, Jiangyang

2017-01-01

Angiogenesis in breast cancer helps fulfill the metabolic demands of the progressing tumor and plays a critical role in tumor metastasis. Therefore, various imaging modalities have been used to characterize tumor angiogenesis. While micro-CT (μCT) is a powerful tool for analyzing the tumor microvascular architecture at micron-scale resolution, magnetic resonance imaging (MRI) with its sub-millimeter resolution is useful for obtaining in vivo vascular data (e.g. tumor blood volume and vessel size index). However, integration of these microscopic and macroscopic angiogenesis data across spatial resolutions remains challenging. Here we demonstrate the feasibility of ‘multiscale’ angiogenesis imaging in a human breast cancer model, wherein we bridge the resolution gap between ex vivo μCT and in vivo MRI using intermediate resolution ex vivo MR microscopy (μMRI). To achieve this integration, we developed suitable vessel segmentation techniques for the ex vivo imaging data and co-registered the vascular data from all three imaging modalities. We showcase two applications of this multiscale, multi-modality imaging approach: (1) creation of co-registered maps of vascular volume from three independent imaging modalities, and (2) visualization of differences in tumor vasculature between viable and necrotic tumor regions by integrating μCT vascular data with tumor cellularity data obtained using diffusion-weighted MRI. Collectively, these results demonstrate the utility of ‘mesoscopic’ resolution μMRI for integrating macroscopic in vivo MRI data and microscopic μCT data. Although focused on the breast tumor xenograft vasculature, our imaging platform could be extended to include additional data types for a detailed characterization of the tumor microenvironment and computational systems biology applications. PMID:24719185

Operational modal analysis of a high-rise multi-function building with dampers by a Bayesian approach

NASA Astrophysics Data System (ADS)

Ni, Yanchun; Lu, Xilin; Lu, Wensheng

2017-03-01

The field non-destructive vibration test plays an important role in the area of structural health monitoring. It assists in monitoring the health status and reducing the risk caused by the poor performance of structures. As the most economic field test among the various vibration tests, the ambient vibration test is the most popular and is widely used to assess the physical condition of a structure under operational service. Based on the ambient vibration data, modal identification can help provide significant previous study for model updating and damage detection during the service life of a structure. It has been proved that modal identification works well in the investigation of the dynamic performance of different kinds of structures. In this paper, the objective structure is a high-rise multi-function office building. The whole building is composed of seven three-story structural units. Each unit comprises one complete floor and two L shaped floors to form large spaces along the vertical direction. There are 56 viscous dampers installed in the building to improve the energy dissipation capacity. Due to the special feature of the structure, field vibration tests and further modal identification were performed to investigate its dynamic performance. Twenty-nine setups were designed to cover all the degrees of freedom of interest. About two years later, another field test was carried out to measure the building for 48 h to investigate the performance variance and the distribution of the modal parameters. A Fast Bayesian FFT method was employed to perform the modal identification. This Bayesian method not only provides the most probable values of the modal parameters but also assesses the associated posterior uncertainty analytically, which is especially relevant in field vibration tests arising due to measurement noise, sensor alignment error, modelling error, etc. A shaking table test was also implemented including cases with and without dampers, which assists in investigating the effect of dampers. The modal parameters obtained from different tests were investigated separately and then compared with each other.

Transcutaneous electrical neurostimulation in functional pain.

PubMed

Richardson, R R; Arbit, J; Siqueira, E B; Zagar, R

1981-01-01

Transcutaneous electrical neurostimulation (TENS) has recently emerged as a distinct therapeutic modality in the alleviation of acute and chronic pain. We applied this modality to 15 nonsurgical low-back pain patients having diagnoses of functional pain, with 40% initially having significant pain relief (50% of greater). However, this pain-alleviating effect of TENS did not last longer than two months. After initiation of neurostimulation, increased pain and/or bizarre and inappropriate sensations and behavior frequently developed. We also applied this modality in the diagnostic evaluation and treatment of 24 patients having diagnoses of postsurgical chronic intractable low-back pain of psychosomatic origin and achieved similar results. In both groups, we utilized a simplified poststimulation "normal-saline-sterile-water intramuscular injection test" to confirm the findings from transcutaneous electrical neurostimulation and to verify the functional basis of the present low-back pain.

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

PubMed

Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

2015-10-01

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley & Sons, Ltd.

Quality models for audiovisual streaming

NASA Astrophysics Data System (ADS)

Thang, Truong Cong; Kim, Young Suk; Kim, Cheon Seog; Ro, Yong Man

2006-01-01

Quality is an essential factor in multimedia communication, especially in compression and adaptation. Quality metrics can be divided into three categories: within-modality quality, cross-modality quality, and multi-modality quality. Most research has so far focused on within-modality quality. Moreover, quality is normally just considered from the perceptual perspective. In practice, content may be drastically adapted, even converted to another modality. In this case, we should consider the quality from semantic perspective as well. In this work, we investigate the multi-modality quality from the semantic perspective. To model the semantic quality, we apply the concept of "conceptual graph", which consists of semantic nodes and relations between the nodes. As an typical of multi-modality example, we focus on audiovisual streaming service. Specifically, we evaluate the amount of information conveyed by a audiovisual content where both video and audio channels may be strongly degraded, even audio are converted to text. In the experiments, we also consider the perceptual quality model of audiovisual content, so as to see the difference with semantic quality model.

A Logic for Inclusion of Administrative Domains and Administrators in Multi-domain Authorization

NASA Astrophysics Data System (ADS)

Iranmanesh, Zeinab; Amini, Morteza; Jalili, Rasool

Authorization policies for an administrative domain or a composition of multiple domains in multi-domain environments are determined by either one administrator or multiple administrators' cooperation. Several logic-based models for multi-domain environments' authorization have been proposed; however, they have not considered administrators and administrative domains in policies' representation. In this paper, we propose the syntax, proof theory, and semantics of a logic for multi-domain authorization policies including administrators and administrative domains. Considering administrators in policies provides the possibility of presenting composite administration having applicability in many collaborative applications. Indeed, administrators and administrative domains stated in policies can be used in authorization. The presented logic is based on modal logic and utilizes two calculi named the calculus of administrative domains and the calculus of administrators. It is also proved that the logic is sound. A case study is presented signifying the logic application in practical projects.

Multi-Sensory, Multi-Modal Concepts for Information Understanding

DTIC Science & Technology

2004-04-01

September 20022-2 Outline • The modern dilemma of knowledge acquisition • A vision for information access and understanding • Emerging concepts for...Multi-Sensory, Multi-Modal Concepts for Information Understanding David L. Hall, Ph.D. School of Information Sciences and Technology The... understanding . INTRODUCTION Historically, information displays for display and understanding of data fusion products have focused on the use of vision

Dual-Modality, Dual-Functional Nanoprobes for Cellular and Molecular Imaging

PubMed Central

Menon, Jyothi U.; Gulaka, Praveen K.; McKay, Madalyn A.; Geethanath, Sairam; Liu, Li; Kodibagkar, Vikram D.

2012-01-01

An emerging need for evaluation of promising cellular therapies is a non-invasive method to image the movement and health of cells following transplantation. However, the use of a single modality to serve this purpose may not be advantageous as it may convey inaccurate or insufficient information. Multi-modal imaging strategies are becoming more popular for in vivo cellular and molecular imaging because of their improved sensitivity, higher resolution and structural/functional visualization. This study aims at formulating Nile Red doped hexamethyldisiloxane (HMDSO) nanoemulsions as dual modality (Magnetic Resonance Imaging/Fluorescence), dual-functional (oximetry/detection) nanoprobes for cellular and molecular imaging. HMDSO nanoprobes were prepared using a HS15-lecithin combination as surfactant and showed an average radius of 71±39 nm by dynamic light scattering and in vitro particle stability in human plasma over 24 hrs. They were found to readily localize in the cytosol of MCF7-GFP cells within 18 minutes of incubation. As proof of principle, these nanoprobes were successfully used for fluorescence imaging and for measuring pO2 changes in cells by magnetic resonance imaging, in vitro, thus showing potential for in vivo applications. PMID:23382776

Comparison of multi-modal early oral nutrition for the tolerance of oral nutrition with conventional care after major abdominal surgery: a prospective, randomized, single-blind trial.

PubMed

Sun, Da-Li; Li, Wei-Ming; Li, Shu-Min; Cen, Yun-Yun; Xu, Qing-Wen; Li, Yi-Jun; Sun, Yan-Bo; Qi, Yu-Xing; Lin, Yue-Ying; Yang, Ting; Lu, Qi-Ping; Xu, Peng-Yuan

2017-02-10

Early oral nutrition (EON) has been shown to improve recovery of gastrointestinal function, length of stay and mortality after abdominal surgery; however, early oral nutrition often fails during the first week after surgery. Here, a multi-modal early oral nutrition program is introduced to promote recovery of gastrointestinal function and tolerance of oral nutrition. Consecutive patients scheduled for abdominal surgery were randomized to the multimodal EON group or a group receiving conventional care. The primary endpoint was the time of first defecation. The secondary endpoints were outcomes and the cost-effectiveness ratio in treating infectious complications. The rate of infectious-free patients was regarded as the index of effectiveness. One hundred seven patients were randomly assigned to groups. Baseline characteristics were similar for both groups. In intention-to-treat analysis, the success rate of oral nutrition during the first week after surgery in the multimodal EON group was 44 (83.0%) versus 31 (57.4%) in the conventional care group (P = 0.004). Time to first defecation, time to flatus, recovery time of bowel sounds, and prolonged postoperative ileus were all less in the multimodal EON group (P < 0.05). The median postoperative length of stay in the multimodal EON group was 8 days (6, 12) versus 10 days (7, 18) in the conventional care group (P < 0.001). The total cost of treatment and nutritional support were also less in the multi-modal early oral nutrition group (P < 0.001). The effectiveness was 84.9 and 79.9% in the multimodal EON and conventional care group, respectively (P = 0.475). However, the cost-effectiveness ratio was USD 537.6 (506.1, 589.3) and USD 637.8 (593.9, 710.3), respectively (P < 0.001). The multi-modal early oral nutrition program was an effective way to improve tolerance of oral nutrition during the first week after surgery, decrease the length of stay and improve cost-effectiveness after abdominal surgery. Registration number: ChiCTR-TRC-14004395 . Registered 15 March 2014.

Extravasation of polymeric nanomedicines across tumor vasculature.

PubMed

Danquah, Michael K; Zhang, Xin A; Mahato, Ram I

2011-07-18

Tumor microvasculature is fraught with numerous physiological barriers which hinder the efficacy of anticancer agents. These barriers include chaotic blood supply, poor tumor vasculature permeability, limited transport across the interstitium due to high interstitial pressure and absence of lymphatic network. Abnormal microvasculature also leads to hypoxia and acidosis which limits effectiveness of chemotherapy. These barriers restrict drug or drug carrier extravasation which hampers tumor regression. Targeting key features of the tumor microenvironment such as tumor microvessels, interstitial hypertension and tumor pH is a promising approach to improving the efficacy of anticancer drugs. This review highlights the current knowledge on the distinct tumor microenvironment generated barriers which limit extravasation of drugs and focuses on modalities for overcoming these barriers using multi-functional polymeric carriers. Special attention is given to utilizing polymeric nanomedicines to facilitate extravasation of anticancer drugs for future cancer therapy. Copyright © 2010 Elsevier B.V. All rights reserved.

Medical image diagnoses by artificial neural networks with image correlation, wavelet transform, simulated annealing

NASA Astrophysics Data System (ADS)

Szu, Harold H.

1993-09-01

Classical artificial neural networks (ANN) and neurocomputing are reviewed for implementing a real time medical image diagnosis. An algorithm known as the self-reference matched filter that emulates the spatio-temporal integration ability of the human visual system might be utilized for multi-frame processing of medical imaging data. A Cauchy machine, implementing a fast simulated annealing schedule, can determine the degree of abnormality by the degree of orthogonality between the patient imagery and the class of features of healthy persons. An automatic inspection process based on multiple modality image sequences is simulated by incorporating the following new developments: (1) 1-D space-filling Peano curves to preserve the 2-D neighborhood pixels' relationship; (2) fast simulated Cauchy annealing for the global optimization of self-feature extraction; and (3) a mini-max energy function for the intra-inter cluster-segregation respectively useful for top-down ANN designs.

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

PubMed

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

Rational chemical design of the next generation of molecular imaging probes based on physics and biology: mixing modalities, colors and signals

PubMed Central

Longmire, Michelle R.; Ogawa, Mikako; Choyke, Peter L.

2012-01-01

In recent years, numerous in vivo molecular imaging probes have been developed. As a consequence, much has been published on the design and synthesis of molecular imaging probes focusing on each modality, each type of material, or each target disease. More recently, second generation molecular imaging probes with unique, multi-functional, or multiplexed characteristics have been designed. This critical review focuses on (i) molecular imaging using combinations of modalities and signals that employ the full range of the electromagnetic spectra, (ii) optimized chemical design of molecular imaging probes for in vivo kinetics based on biology and physiology across a range of physical sizes, (iii) practical examples of second generation molecular imaging probes designed to extract complementary data from targets using multiple modalities, color, and comprehensive signals (277 references). PMID:21607237

Spatial accessibility to healthcare services in Shenzhen, China: improving the multi-modal two-step floating catchment area method by estimating travel time via online map APIs.

PubMed

Tao, Zhuolin; Yao, Zaoxing; Kong, Hui; Duan, Fei; Li, Guicai

2018-05-09

Shenzhen has rapidly grown into a megacity in the recent decades. It is a challenging task for the Shenzhen government to provide sufficient healthcare services. The spatial configuration of healthcare services can influence the convenience for the consumers to obtain healthcare services. Spatial accessibility has been widely adopted as a scientific measurement for evaluating the rationality of the spatial configuration of healthcare services. The multi-modal two-step floating catchment area (2SFCA) method is an important advance in the field of healthcare accessibility modelling, which enables the simultaneous assessment of spatial accessibility via multiple transport modes. This study further develops the multi-modal 2SFCA method by introducing online map APIs to improve the estimation of travel time by public transit or by car respectively. As the results show, the distribution of healthcare accessibility by multi-modal 2SFCA shows significant spatial disparity. Moreover, by dividing the multi-modal accessibility into car-mode and transit-mode accessibility, this study discovers that the transit-mode subgroup is disadvantaged in the competition for healthcare services with the car-mode subgroup. The disparity in transit-mode accessibility is the main reason of the uneven pattern of healthcare accessibility in Shenzhen. The findings suggest improving the public transit conditions for accessing healthcare services to reduce the disparity of healthcare accessibility. More healthcare services should be allocated in the eastern and western Shenzhen, especially sub-districts in Dapeng District and western Bao'an District. As these findings cannot be drawn by the traditional single-modal 2SFCA method, the advantage of the multi-modal 2SFCA method is significant to both healthcare studies and healthcare system planning.

Drug-related webpages classification based on multi-modal local decision fusion

NASA Astrophysics Data System (ADS)

Hu, Ruiguang; Su, Xiaojing; Liu, Yanxin

2018-03-01

In this paper, multi-modal local decision fusion is used for drug-related webpages classification. First, meaningful text are extracted through HTML parsing, and effective images are chosen by the FOCARSS algorithm. Second, six SVM classifiers are trained for six kinds of drug-taking instruments, which are represented by PHOG. One SVM classifier is trained for the cannabis, which is represented by the mid-feature of BOW model. For each instance in a webpage, seven SVMs give seven labels for its image, and other seven labels are given by searching the names of drug-taking instruments and cannabis in its related text. Concatenating seven labels of image and seven labels of text, the representation of those instances in webpages are generated. Last, Multi-Instance Learning is used to classify those drugrelated webpages. Experimental results demonstrate that the classification accuracy of multi-instance learning with multi-modal local decision fusion is much higher than those of single-modal classification.

Emerging therapies to treat frailty syndrome in the elderly.

PubMed

Cherniack, E Paul; Florez, Hermes J; Troen, Bruce R

2007-09-01

Frailty syndrome (FS) has become increasingly recognized as a major predictor of co-morbidities and mortality in older individuals. Interventions with the potential to benefit frail elders include nutritional supplementation (vitamins D, carotenoids, creatine, dehydroepiandrosterone (DHEA), and beta-hydroxy-beta-methylbutyrate) and exercise modalities (tai chi and cobblestone walking). While these have not been explicitly tested for their impact on FS, vitamin D supplementation appears to offer significant promise in enhancing long-term health of the elderly. Exercise modalities such as tai chi and cobblestone walking, because of probable low risk and ease of participation, may also confer benefit. Additional studies are needed to investigate interventions that directly prevent, delay, and/or ameliorate frailty. Successful therapies may well involve multi-component approaches utilizing a combination of medication, nutritional supplementation, and exercise.

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.

SSF loads and controllability during assembly

NASA Technical Reports Server (NTRS)

Larson, Charles R.; Ghofranian, S.; Fujii, E.

1993-01-01

The Orbiter Primary Reaction Control System (PRCS) pulse width and firing frequency is restricted to prevent excessive loads in the Space Station Freedom (SSF). The feasibility of using the SSF Control Moment Gyros (CMG) as a secondary controller for load relief is evaluated. The studies revealed the CMG not only reduced loads but were useful for other SSF functions: vibration suppression and modal excitation. Vibration suppression lowers the g level for the SSF micro-g experiments and damps the low frequency oscillations that cause crew sickness. Modal excitation could be used for the modal identification experiment and health monitoring. The CMG's reduced the peak loads and damped the vibrations. They were found to be an effective multi-purpose ancillary device for SSF operation.

Multi-Modal Traveler Information System - Gateway Interface Control Requirements

DOT National Transportation Integrated Search

1997-10-30

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Hybrid-modality high-resolution imaging: for diagnostic biomedical imaging and sensing for disease diagnosis

NASA Astrophysics Data System (ADS)

Murukeshan, Vadakke M.; Hoong Ta, Lim

2014-11-01

Medical diagnostics in the recent past has seen the challenging trend to come up with dual and multi-modality imaging for implementing better diagnostic procedures. The changes in tissues in the early disease stages are often subtle and can occur beneath the tissue surface. In most of these cases, conventional types of medical imaging using optics may not be able to detect these changes easily due to its penetration depth of the orders of 1 mm. Each imaging modality has its own advantages and limitations, and the use of a single modality is not suitable for every diagnostic applications. Therefore the need for multi or hybrid-modality imaging arises. Combining more than one imaging modalities overcomes the limitation of individual imaging method and integrates the respective advantages into a single setting. In this context, this paper will be focusing on the research and development of two multi-modality imaging platforms. The first platform combines ultrasound and photoacoustic imaging for diagnostic applications in the eye. The second platform consists of optical hyperspectral and photoacoustic imaging for diagnostic applications in the colon. Photoacoustic imaging is used as one of the modalities in both platforms as it can offer deeper penetration depth compared to optical imaging. The optical engineering and research challenges in developing the dual/multi-modality platforms will be discussed, followed by initial results validating the proposed scheme. The proposed schemes offer high spatial and spectral resolution imaging and sensing, and is expected to offer potential biomedical imaging solutions in the near future.

A novel automated method for doing registration and 3D reconstruction from multi-modal RGB/IR image sequences

NASA Astrophysics Data System (ADS)

Kirby, Richard; Whitaker, Ross

2016-09-01

In recent years, the use of multi-modal camera rigs consisting of an RGB sensor and an infrared (IR) sensor have become increasingly popular for use in surveillance and robotics applications. The advantages of using multi-modal camera rigs include improved foreground/background segmentation, wider range of lighting conditions under which the system works, and richer information (e.g. visible light and heat signature) for target identification. However, the traditional computer vision method of mapping pairs of images using pixel intensities or image features is often not possible with an RGB/IR image pair. We introduce a novel method to overcome the lack of common features in RGB/IR image pairs by using a variational methods optimization algorithm to map the optical flow fields computed from different wavelength images. This results in the alignment of the flow fields, which in turn produce correspondences similar to those found in a stereo RGB/RGB camera rig using pixel intensities or image features. In addition to aligning the different wavelength images, these correspondences are used to generate dense disparity and depth maps. We obtain accuracies similar to other multi-modal image alignment methodologies as long as the scene contains sufficient depth variations, although a direct comparison is not possible because of the lack of standard image sets from moving multi-modal camera rigs. We test our method on synthetic optical flow fields and on real image sequences that we created with a multi-modal binocular stereo RGB/IR camera rig. We determine our method's accuracy by comparing against a ground truth.

Scar Management of the Burned Hand

PubMed Central

Sorkin, Michael; Cholok, David; Levi, Benjamin

2017-01-01

Unimpaired hand function is critical in almost all activities of daily living. Burn injury can result in hypertrophic scar formation that can lead to debilitating functional deficits and poor aesthetic outcomes. Initial algorithms of acute burn management involve early debridement and skin grafting and early mobilization to prevent formation of hypertrophic scarring and ultimately digit contractures. While non-operative modalities in the early phase of scar maturation are critical to minimize hypertrophic scar formation, surgical management is often indicated in order to restore hand function. The essential tenant of operative scar management is release of tension, which can often be achieved through local tissue rearrangement. Laser therapy has emerged as a central pillar of subsequent scar rehabilitation with several modalities that address scar texture, color, pruritis and thickness. These can be utilized in conjunction with local corticosteroid treatment and other emerging modalities to modulate the scar and achieve optimal hand function. These treatment tools provide an effective resource for the reconstructive surgeon to treat hypertrophic hand scars. PMID:28363297

Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

PubMed Central

Wang, Ge; Zhang, Jie; Gao, Hao; Weir, Victor; Yu, Hengyong; Cong, Wenxiang; Xu, Xiaochen; Shen, Haiou; Bennett, James; Furth, Mark; Wang, Yue; Vannier, Michael

2012-01-01

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine. PMID:22768108

Functional connectivity in the mouse brain imaged by B-mode photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xing, Wenxin; Xia, Jun; Wang, Lihong V.

2014-03-01

The increasing use of mouse models for human brain disease studies, coupled with the fact that existing functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing acoustic-resolution photoacoustic microscopy (AR-PAM), we imaged spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images were acquired noninvasively in B-scan mode with a fast frame rate, a large field of view, and a high spatial resolution. At a location relative to the bregma 0, correlations were investigated inter-hemispherically between bilaterally homologous regions, as well as intra-hemispherically within the same functional regions. The functional connectivity in different functional regions was studied. The locations of these regions agreed well with the Paxinos mouse brain atlas. The functional connectivity map obtained in this study can then be used in the investigation of brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy. Our experiments show that photoacoustic microscopy is capable to detect connectivities between different functional regions in B-scan mode, promising a powerful functional imaging modality for future brain research.

Multi-Modal Traveler Information System - Alternative GCM Corridor Technologies and Strategies

DOT National Transportation Integrated Search

1997-10-24

The purpose of this working paper is to summarize current and evolving Intelligent Transportation System (ITS) technologies and strategies related to the design, development, and deployment of regional multi-modal traveler information systems. This r...

Prospectus on Multi-Modal Aspects of Human Factors in Transportation

DOT National Transportation Integrated Search

1991-02-01

This prospectus identifies and discusses a series of human factors : issues which are critical to transportation safety and productivity, and : examines the potential benefits that can accrue from taking a multi-modal : approach to human factors rese...

Multi-Modal Traveler Information System - GCM Corridor Architecture Interface Control Requirements

DOT National Transportation Integrated Search

1997-10-31

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Multi-modal Registration for Correlative Microscopy using Image Analogies

PubMed Central

Cao, Tian; Zach, Christopher; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

2014-01-01

Correlative microscopy is a methodology combining the functionality of light microscopy with the high resolution of electron microscopy and other microscopy technologies for the same biological specimen. In this paper, we propose an image registration method for correlative microscopy, which is challenging due to the distinct appearance of biological structures when imaged with different modalities. Our method is based on image analogies and allows to transform images of a given modality into the appearance-space of another modality. Hence, the registration between two different types of microscopy images can be transformed to a mono-modality image registration. We use a sparse representation model to obtain image analogies. The method makes use of corresponding image training patches of two different imaging modalities to learn a dictionary capturing appearance relations. We test our approach on backscattered electron (BSE) scanning electron microscopy (SEM)/confocal and transmission electron microscopy (TEM)/confocal images. We perform rigid, affine, and deformable registration via B-splines and show improvements over direct registration using both mutual information and sum of squared differences similarity measures to account for differences in image appearance. PMID:24387943

Rehabilitation outcomes of stroke patients treated with multi-modal endovascular reperfusion therapy.

PubMed

Meiner, Z; Cohen, J E; Gomori, J M; Sajin, A; Schwartz, I; Tsenter, J; Yovchev, I; Eichel, R; Ben-Hur, T; Leker, R R

2012-03-01

The aim of this study was to investigate the influence of multi-modal endovascular reperfusion therapy (MMRT) on functional outcomes following rehabilitation. Data from 14 MMRT-treated patients were analyzed and compared to MMRT-ineligible, age and stroke severity-matched patients treated at the same Neurological and Rehabilitation departments. Neurological evaluation was assessed with the NIH stroke scale (NIHSS). Activity of daily living was measured using the FIMTM instrument. Functional outcome was measured using the modified Rankin scale (mRS). The baseline characteristics of both groups were similar. NIHSS scores were lower in the MMRT group and they had slightly better functional and rehabilitation scores on admission to rehabilitation. At the end of rehabilitation, more MMRT-treated patients reached functional independence (mRS≤2; 50% vs. 7% respectively P=0.03). FIM scores were also higher in the MMRT group (mean score 93.3 vs. 87.7, respectively) but the difference did not reach significance. The delta in FIM and NIHSS scores obtained during rehabilitation did not significantly differ between the groups. MMRT remained a significant modifier of good outcome after regression analysis (OR 21.5 95% CI 1.1-410). MMRT-treated patients have better chances of attaining independence after rehabilitation therapy. However, the additional improvements gained while in active rehabilitation were independent of reperfusion status.

Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma.

PubMed

Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

2015-02-28

To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P<0.001) and objective tumor response (P=0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P=0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P<0.001). Multivariate analysis identified tumor stage (P<0.001) and tumor type (P=0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P<0.001), surgical treatment (P=0.009), and multi-modal treatment (P=0.002) were identified as independent post-treatment prognostic factors. TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC.

Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma

PubMed Central

Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

2015-01-01

AIM: To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). METHODS: A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. RESULTS: In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P < 0.001) and objective tumor response (P = 0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P = 0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P < 0.001). Multivariate analysis identified tumor stage (P < 0.001) and tumor type (P = 0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P < 0.001), surgical treatment (P = 0.009), and multi-modal treatment (P = 0.002) were identified as independent post-treatment prognostic factors. CONCLUSION: TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC. PMID:25741147

Virtually-augmented interfaces for tactical aircraft.

PubMed

Haas, M W

1995-05-01

The term Fusion Interface is defined as a class of interface which integrally incorporates both virtual and non-virtual concepts and devices across the visual, auditory and haptic sensory modalities. A fusion interface is a multi-sensory virtually-augmented synthetic environment. A new facility has been developed within the Human Engineering Division of the Armstrong Laboratory dedicated to exploratory development of fusion-interface concepts. One of the virtual concepts to be investigated in the Fusion Interfaces for Tactical Environments facility (FITE) is the application of EEG and other physiological measures for virtual control of functions within the flight environment. FITE is a specialized flight simulator which allows efficient concept development through the use of rapid prototyping followed by direct experience of new fusion concepts. The FITE facility also supports evaluation of fusion concepts by operational fighter pilots in a high fidelity simulated air combat environment. The facility was utilized by a multi-disciplinary team composed of operational pilots, human-factors engineers, electronics engineers, computer scientists, and experimental psychologists to prototype and evaluate the first multi-sensory, virtually-augmented cockpit. The cockpit employed LCD-based head-down displays, a helmet-mounted display, three-dimensionally localized audio displays, and a haptic display. This paper will endeavor to describe the FITE facility architecture, some of the characteristics of the FITE virtual display and control devices, and the potential application of EEG and other physiological measures within the FITE facility.

Development and reliability of a multi-modality scoring system for evaluation of disease progression in pre-clinical models of osteoarthritis: celecoxib may possess disease-modifying properties.

PubMed

Panahifar, A; Jaremko, J L; Tessier, A G; Lambert, R G; Maksymowych, W P; Fallone, B G; Doschak, M R

2014-10-01

We sought to develop a comprehensive scoring system for evaluation of pre-clinical models of osteoarthritis (OA) progression, and use this to evaluate two different classes of drugs for management of OA. Post-traumatic OA (PTOA) was surgically induced in skeletally mature rats. Rats were randomly divided in three groups receiving either glucosamine (high dose of 192 mg/kg) or celecoxib (clinical dose) or no treatment. Disease progression was monitored utilizing micro-magnetic resonance imaging (MRI), micro-computed tomography (CT) and histology. Pertinent features such as osteophytes, subchondral sclerosis, joint effusion, bone marrow lesion (BML), cysts, loose bodies and cartilage abnormalities were included in designing a sensitive multi-modality based scoring system, termed the rat arthritis knee scoring system (RAKSS). Overall, an inter-observer correlation coefficient (ICC) of greater than 0.750 was achieved for each scored feature. None of the treatments prevented cartilage loss, synovitis, joint effusion, or sclerosis. However, celecoxib significantly reduced osteophyte development compared to placebo. Although signs of inflammation such as synovitis and joint effusion were readily identified at 4 weeks post-operation, we did not detect any BML. We report the development of a sensitive and reliable multi-modality scoring system, the RAKSS, for evaluation of OA severity in pre-clinical animal models. Using this scoring system, we found that celecoxib prevented enlargement of osteophytes in this animal model of PTOA, and thus it may be useful in preventing OA progression. However, it did not show any chondroprotective effect using the recommended dose. In contrast, high dose glucosamine had no measurable effects. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Simultaneous acquisition of magnetic resonance spectroscopy (MRS) data and positron emission tomography (PET) images with a prototype MR-compatible, small animal PET imager

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Velan, S. Sendhil; Lemieux, Susan; Kross, Brian; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.

2007-06-01

Multi-modality imaging (such as PET-CT) is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET, fused with anatomical images created by MRI, allow the correlation of form with function. Perhaps more exciting than the combination of anatomical MRI with PET, is the melding of PET with MR spectroscopy (MRS). Thus, two aspects of physiology could be combined in novel ways to produce new insights into the physiology of normal and pathological processes. Our team is developing a system to acquire MRI images and MRS spectra, and PET images contemporaneously. The prototype MR-compatible PET system consists of two opposed detector heads (appropriate in size for small animal imaging), operating in coincidence mode with an active field-of-view of ˜14 cm in diameter. Each detector consists of an array of LSO detector elements coupled through a 2-m long fiber optic light guide to a single position-sensitive photomultiplier tube. The use of light guides allows these magnetic field-sensitive elements of the PET imager to be positioned outside the strong magnetic field of our 3T MRI scanner. The PET scanner imager was integrated with a 12-cm diameter, 12-leg custom, birdcage coil. Simultaneous MRS spectra and PET images were successfully acquired from a multi-modality phantom consisting of a sphere filled with 17 brain relevant substances and a positron-emitting radionuclide. There were no significant changes in MRI or PET scanner performance when both were present in the MRI magnet bore. This successful initial test demonstrates the potential for using such a multi-modality to obtain complementary MRS and PET data.

Multi-Modal Traveler Information System - Performance Criteria for Evaluating GCM Corridor Strategies & Technologies

DOT National Transportation Integrated Search

1997-07-16

The Gary-Chicago-Milwaukee (GCM) Multi-Modal Traveler Information System (MMTIS) is a complex project involving a wide spectrum of participants. In order to facilitate its implementation it is important to understand the direction of the MMTIS. This ...

Dynamic mobility applications policy analysis : policy and institutional issues for multi-modal intelligent traffic signal system (MMITSS).

DOT National Transportation Integrated Search

2015-03-01

The Connected Vehicle Mobility Policy team (herein, policy team) developed this report to document policy considerations for the Multi-Modal Intelligent Traffic Signal System, or MMITSS. MMITSS comprises a bundle of dynamic mobility application...

Multi-modal magnetic resonance imaging and histology of vascular function in xenografts using macromolecular contrast agent hyperbranched polyglycerol (HPG-GdF).

PubMed

Baker, Jennifer H E; McPhee, Kelly C; Moosvi, Firas; Saatchi, Katayoun; Häfeli, Urs O; Minchinton, Andrew I; Reinsberg, Stefan A

2016-01-01

Macromolecular gadolinium (Gd)-based contrast agents are in development as blood pool markers for MRI. HPG-GdF is a 583 kDa hyperbranched polyglycerol doubly tagged with Gd and Alexa 647 nm dye, making it both MR and histologically visible. In this study we examined the location of HPG-GdF in whole-tumor xenograft sections matched to in vivo DCE-MR images of both HPG-GdF and Gadovist. Despite its large size, we have shown that HPG-GdF extravasates from some tumor vessels and accumulates over time, but does not distribute beyond a few cell diameters from vessels. Fractional plasma volume (fPV) and apparent permeability-surface area product (aPS) parameters were derived from the MR concentration-time curves of HPG-GdF. Non-viable necrotic tumor tissue was excluded from the analysis by applying a novel bolus arrival time (BAT) algorithm to all voxels. aPS derived from HPG-GdF was the only MR parameter to identify a difference in vascular function between HCT116 and HT29 colorectal tumors. This study is the first to relate low and high molecular weight contrast agents with matched whole-tumor histological sections. These detailed comparisons identified tumor regions that appear distinct from each other using the HPG-GdF biomarkers related to perfusion and vessel leakiness, while Gadovist-imaged parameter measures in the same regions were unable to detect variation in vascular function. We have established HPG-GdF as a biocompatible multi-modal high molecular weight contrast agent with application for examining vascular function in both MR and histological modalities. Copyright © 2015 John Wiley & Sons, Ltd.

Missing Modality Transfer Learning via Latent Low-Rank Constraint.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2015-11-01

Transfer learning is usually exploited to leverage previously well-learned source domain for evaluating the unknown target domain; however, it may fail if no target data are available in the training stage. This problem arises when the data are multi-modal. For example, the target domain is in one modality, while the source domain is in another. To overcome this, we first borrow an auxiliary database with complete modalities, then consider knowledge transfer across databases and across modalities within databases simultaneously in a unified framework. The contributions are threefold: 1) a latent factor is introduced to uncover the underlying structure of the missing modality from the known data; 2) transfer learning in two directions allows the data alignment between both modalities and databases, giving rise to a very promising recovery; and 3) an efficient solution with theoretical guarantees to the proposed latent low-rank transfer learning algorithm. Comprehensive experiments on multi-modal knowledge transfer with missing target modality verify that our method can successfully inherit knowledge from both auxiliary database and source modality, and therefore significantly improve the recognition performance even when test modality is inaccessible in the training stage.

A feasibility study of evaluating transportation security systems and associated multi-modal efficiency impacts

DOT National Transportation Integrated Search

2006-08-01

The overall purpose of this research project is to conduct a feasibility study and development of a general methodology to determine the impacts on multi-modal and system efficiency of alternative freight security measures. The methodology to be exam...

The Spectrum Analysis Solution (SAS) System: Theoretical Analysis, Hardware Design and Implementation.

PubMed

Narayanan, Ram M; Pooler, Richard K; Martone, Anthony F; Gallagher, Kyle A; Sherbondy, Kelly D

2018-02-22

This paper describes a multichannel super-heterodyne signal analyzer, called the Spectrum Analysis Solution (SAS), which performs multi-purpose spectrum sensing to support spectrally adaptive and cognitive radar applications. The SAS operates from ultrahigh frequency (UHF) to the S-band and features a wideband channel with eight narrowband channels. The wideband channel acts as a monitoring channel that can be used to tune the instantaneous band of the narrowband channels to areas of interest in the spectrum. The data collected from the SAS has been utilized to develop spectrum sensing algorithms for the budding field of spectrum sharing (SS) radar. Bandwidth (BW), average total power, percent occupancy (PO), signal-to-interference-plus-noise ratio (SINR), and power spectral entropy (PSE) have been examined as metrics for the characterization of the spectrum. These metrics are utilized to determine a contiguous optimal sub-band (OSB) for a SS radar transmission in a given spectrum for different modalities. Three OSB algorithms are presented and evaluated: the spectrum sensing multi objective (SS-MO), the spectrum sensing with brute force PSE (SS-BFE), and the spectrum sensing multi-objective with brute force PSE (SS-MO-BFE).

The Spectrum Analysis Solution (SAS) System: Theoretical Analysis, Hardware Design and Implementation

PubMed Central

Pooler, Richard K.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.

2018-01-01

This paper describes a multichannel super-heterodyne signal analyzer, called the Spectrum Analysis Solution (SAS), which performs multi-purpose spectrum sensing to support spectrally adaptive and cognitive radar applications. The SAS operates from ultrahigh frequency (UHF) to the S-band and features a wideband channel with eight narrowband channels. The wideband channel acts as a monitoring channel that can be used to tune the instantaneous band of the narrowband channels to areas of interest in the spectrum. The data collected from the SAS has been utilized to develop spectrum sensing algorithms for the budding field of spectrum sharing (SS) radar. Bandwidth (BW), average total power, percent occupancy (PO), signal-to-interference-plus-noise ratio (SINR), and power spectral entropy (PSE) have been examined as metrics for the characterization of the spectrum. These metrics are utilized to determine a contiguous optimal sub-band (OSB) for a SS radar transmission in a given spectrum for different modalities. Three OSB algorithms are presented and evaluated: the spectrum sensing multi objective (SS-MO), the spectrum sensing with brute force PSE (SS-BFE), and the spectrum sensing multi-objective with brute force PSE (SS-MO-BFE). PMID:29470448

The sweet spot: FDG and other 2-carbon glucose analogs for multi-modal metabolic imaging of tumor metabolism

PubMed Central

Cox, Benjamin L; Mackie, Thomas R; Eliceiri, Kevin W

2015-01-01

Multi-modal imaging approaches of tumor metabolism that provide improved specificity, physiological relevance and spatial resolution would improve diagnosing of tumors and evaluation of tumor progression. Currently, the molecular probe FDG, glucose fluorinated with 18F at the 2-carbon, is the primary metabolic approach for clinical diagnostics with PET imaging. However, PET lacks the resolution necessary to yield intratumoral distributions of deoxyglucose, on the cellular level. Multi-modal imaging could elucidate this problem, but requires the development of new glucose analogs that are better suited for other imaging modalities. Several such analogs have been created and are reviewed here. Also reviewed are several multi-modal imaging studies that have been performed that attempt to shed light on the cellular distribution of glucose analogs within tumors. Some of these studies are performed in vitro, while others are performed in vivo, in an animal model. The results from these studies introduce a visualization gap between the in vitro and in vivo studies that, if solved, could enable the early detection of tumors, the high resolution monitoring of tumors during treatment, and the greater accuracy in assessment of different imaging agents. PMID:25625022

An overview of contemporary nuclear cardiology.

PubMed

Lewin, Howard C; Sciammarella, Maria G; Watters, Thomas A; Alexander, Herbert G

2004-01-01

Myocardial perfusion single photon emission computed tomography (SPECT) is a widely utilized noninvasive imaging modality for the diagnosis, prognosis, and risk stratification of coronary artery disease. It is clearly superior to the traditional planar technique in terms of imaging contrast and consequent diagnostic and prognostic yield. The strength of SPECT images is largely derived from the three-dimensional, volumetric nature of its image. Thus, this modality permits three-dimensional assessment and quantitation of the perfused myocardium and functional assessment through electrocardiographic gating of the perfusion images.

MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery

PubMed Central

Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

2016-01-01

Purpose Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation. PMID:27330239

MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery

NASA Astrophysics Data System (ADS)

Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

2016-03-01

Purpose: Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method: The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result: The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions: A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation.

MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery.

PubMed

Reaungamornrat, S; De Silva, T; Uneri, A; Wolinsky, J-P; Khanna, A J; Kleinszig, G; Vogt, S; Prince, J L; Siewerdsen, J H

2016-02-27

Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation.

Content-independent embedding scheme for multi-modal medical image watermarking.

PubMed

Nyeem, Hussain; Boles, Wageeh; Boyd, Colin

2015-02-04

As the increasing adoption of information technology continues to offer better distant medical services, the distribution of, and remote access to digital medical images over public networks continues to grow significantly. Such use of medical images raises serious concerns for their continuous security protection, which digital watermarking has shown great potential to address. We present a content-independent embedding scheme for medical image watermarking. We observe that the perceptual content of medical images varies widely with their modalities. Recent medical image watermarking schemes are image-content dependent and thus they may suffer from inconsistent embedding capacity and visual artefacts. To attain the image content-independent embedding property, we generalise RONI (region of non-interest, to the medical professionals) selection process and use it for embedding by utilising RONI's least significant bit-planes. The proposed scheme thus avoids the need for RONI segmentation that incurs capacity and computational overheads. Our experimental results demonstrate that the proposed embedding scheme performs consistently over a dataset of 370 medical images including their 7 different modalities. Experimental results also verify how the state-of-the-art reversible schemes can have an inconsistent performance for different modalities of medical images. Our scheme has MSSIM (Mean Structural SIMilarity) larger than 0.999 with a deterministically adaptable embedding capacity. Our proposed image-content independent embedding scheme is modality-wise consistent, and maintains a good image quality of RONI while keeping all other pixels in the image untouched. Thus, with an appropriate watermarking framework (i.e., with the considerations of watermark generation, embedding and detection functions), our proposed scheme can be viable for the multi-modality medical image applications and distant medical services such as teleradiology and eHealth.

Geographic Distribution of CT, MRI and PET Devices in Japan: A Longitudinal Analysis Based on National Census Data.

PubMed

Matsumoto, Masatoshi; Koike, Soichi; Kashima, Saori; Awai, Kazuo

2015-01-01

Japan has the most CT and MRI scanners per unit population in the world; however, the geographic distribution of these technologies is currently unknown. Moreover, nothing is known of the cause-effect relationship between the number of diagnostic imaging devices and their geographic distribution. Data on the number of CT, MRI and PET devices and that of their utilizations in all 1829 municipalities of Japan was generated, based on the Static Survey of Medical Institutions conducted by the government. The inter-municipality equity of the number of devices or utilizations was evaluated with Gini coefficient. Between 2005 and 2011, the number of CT, MRI and PET devices in Japan increased by 47% (8789 to 12945), 19% (5034 to 5990) and 70% (274 to 466), respectively. Gini coefficient of the number of devices was largest for PET and smallest for CT (p for PET-MRI difference <0.001; MRI-CT difference <0.001). For all three modalities, Gini coefficient steadily decreased (p for 2011-2005 difference: <0.001 for CT; 0.003 for MRI; and <0.001 for PET). The number of devices in old models (single-detector CT, MRI<1.5 tesla, and conventional PET) decreased, while that in new models (multi-detector CT, MRI≥1.5 tesla, and PET-CT) increased. Gini coefficient of the old models increased or remained unchanged (increase rate of 9%, 3%, and -1%; p for 2011-2008 difference <0.001, 0.072, and 0.562, respectively), while Gini coefficient of the new models decreased (-10%, -9%, and -10%; p for 2011-2008 difference <0.001, <0.001, and <0.001 respectively). Similar results were observed in terms of utilizations. The more abundant a modality, the more equal the modality's distribution. Any increase in the modality made its distribution more equal. The geographic distribution of the diagnostic imaging technology in Japan appears to be affected by spatial competition derived from a market force.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barstow, Del R; Patlolla, Dilip Reddy; Mann, Christopher J

Abstract The data captured by existing standoff biometric systems typically has lower biometric recognition performance than their close range counterparts due to imaging challenges, pose challenges, and other factors. To assist in overcoming these limitations systems typically perform in a multi-modal capacity such as Honeywell s Combined Face and Iris (CFAIRS) [21] system. While this improves the systems performance, standoff systems have yet to be proven as accurate as their close range equivalents. We will present a standoff system capable of operating up to 7 meters in range. Unlike many systems such as the CFAIRS our system captures high qualitymore » 12 MP video allowing for a multi-sample as well as multi-modal comparison. We found that for standoff systems multi-sample improved performance more than multi-modal. For a small test group of 50 subjects we were able to achieve 100% rank one recognition performance with our system.« less

Key informant interviews test plan : model deployment of a regional, multi-modal 511 traveler information system

DOT National Transportation Integrated Search

2004-01-28

This document presents the detailed plan to conduct the Key Informants Interviews Test, one of several test activities to be conducted as part of the national evaluation of the regional, multi-modal 511 Traveler Information System Model Deployment. T...

Logistics, Multimodal, and Shipper Partner 2.0.15 Tools: Guide to Importing Carrier Data Using the Outside Data Import Function 2015 Data Year - United States Version

EPA Pesticide Factsheets

This document provides guidance for Logistics, Multi-modal, and Shippers on how to use outside data collection systems to populate the SmartWay tools carrier data and activity sections using an automated method. (EPA publication # EPA-420-B-16-057a)

The Mind Research Network - Mental Illness Neuroscience Discovery Grant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, J.; Calhoun, V.

The scientific and technological programs of the Mind Research Network (MRN), reflect DOE missions in basic science and associated instrumentation, computational modeling, and experimental techniques. MRN's technical goals over the course of this project have been to develop and apply integrated, multi-modality functional imaging techniques derived from a decade of DOE-support research and technology development.

Assessment and Treatment of Stereotypic Vocalizations in a Taiwanese Adolescent with Autism: A Case Study

ERIC Educational Resources Information Center

Wu, Ya-Ping; Mirenda, Pat; Wang, Hwa-Pey; Chen, Ming-Chung

2010-01-01

This case study describes the processes of functional analysis and modality assessment that were utilized to design a communication intervention for an adolescent with autism who engaged in loud and disruptive vocalizations for most of the school day. The functional analysis suggested that the vocalizations served both tangible and escape…

A View on the Importance of "Multi-Attribute Method" for Measuring Purity of Biopharmaceuticals and Improving Overall Control Strategy.

PubMed

Rogers, Richard S; Abernathy, Michael; Richardson, Douglas D; Rouse, Jason C; Sperry, Justin B; Swann, Patrick; Wypych, Jette; Yu, Christopher; Zang, Li; Deshpande, Rohini

2017-11-30

Today, we are experiencing unprecedented growth and innovation within the pharmaceutical industry. Established protein therapeutic modalities, such as recombinant human proteins, monoclonal antibodies (mAbs), and fusion proteins, are being used to treat previously unmet medical needs. Novel therapies such as bispecific T cell engagers (BiTEs), chimeric antigen T cell receptors (CARTs), siRNA, and gene therapies are paving the path towards increasingly personalized medicine. This advancement of new indications and therapeutic modalities is paralleled by development of new analytical technologies and methods that provide enhanced information content in a more efficient manner. Recently, a liquid chromatography-mass spectrometry (LC-MS) multi-attribute method (MAM) has been developed and designed for improved simultaneous detection, identification, quantitation, and quality control (monitoring) of molecular attributes (Rogers et al. MAbs 7(5):881-90, 2015). Based on peptide mapping principles, this powerful tool represents a true advancement in testing methodology that can be utilized not only during product characterization, formulation development, stability testing, and development of the manufacturing process, but also as a platform quality control method in dispositioning clinical materials for both innovative biotherapeutics and biosimilars.

Intrinsic embedded sensors for polymeric mechatronics: flexure and force sensing.

PubMed

Jentoft, Leif P; Dollar, Aaron M; Wagner, Christopher R; Howe, Robert D

2014-02-25

While polymeric fabrication processes, including recent advances in additive manufacturing, have revolutionized manufacturing, little work has been done on effective sensing elements compatible with and embedded within polymeric structures. In this paper, we describe the development and evaluation of two important sensing modalities for embedding in polymeric mechatronic and robotic mechanisms: multi-axis flexure joint angle sensing utilizing IR phototransistors, and a small (12 mm), three-axis force sensing via embedded silicon strain gages with similar performance characteristics as an equally sized metal element based sensor.

Intrinsic Embedded Sensors for Polymeric Mechatronics: Flexure and Force Sensing

PubMed Central

Jentoft, Leif P.; Dollar, Aaron M.; Wagner, Christopher R.; Howe, Robert D.

2014-01-01

While polymeric fabrication processes, including recent advances in additive manufacturing, have revolutionized manufacturing, little work has been done on effective sensing elements compatible with and embedded within polymeric structures. In this paper, we describe the development and evaluation of two important sensing modalities for embedding in polymeric mechatronic and robotic mechanisms: multi-axis flexure joint angle sensing utilizing IR phototransistors, and a small (12 mm), three-axis force sensing via embedded silicon strain gages with similar performance characteristics as an equally sized metal element based sensor. PMID:24573310

Asymmetries of the human social brain in the visual, auditory and chemical modalities.

PubMed

Brancucci, Alfredo; Lucci, Giuliana; Mazzatenta, Andrea; Tommasi, Luca

2009-04-12

Structural and functional asymmetries are present in many regions of the human brain responsible for motor control, sensory and cognitive functions and communication. Here, we focus on hemispheric asymmetries underlying the domain of social perception, broadly conceived as the analysis of information about other individuals based on acoustic, visual and chemical signals. By means of these cues the brain establishes the border between 'self' and 'other', and interprets the surrounding social world in terms of the physical and behavioural characteristics of conspecifics essential for impression formation and for creating bonds and relationships. We show that, considered from the standpoint of single- and multi-modal sensory analysis, the neural substrates of the perception of voices, faces, gestures, smells and pheromones, as evidenced by modern neuroimaging techniques, are characterized by a general pattern of right-hemispheric functional asymmetry that might benefit from other aspects of hemispheric lateralization rather than constituting a true specialization for social information.

Optimal Wonderful Life Utility Functions in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan; Swanson, Keith (Technical Monitor)

2000-01-01

The mathematics of Collective Intelligence (COINs) is concerned with the design of multi-agent systems so as to optimize an overall global utility function when those systems lack centralized communication and control. Typically in COINs each agent runs a distinct Reinforcement Learning (RL) algorithm, so that much of the design problem reduces to how best to initialize/update each agent's private utility function, as far as the ensuing value of the global utility is concerned. Traditional team game solutions to this problem assign to each agent the global utility as its private utility function. In previous work we used the COIN framework to derive the alternative Wonderful Life Utility (WLU), and experimentally established that having the agents use it induces global utility performance up to orders of magnitude superior to that induced by use of the team game utility. The WLU has a free parameter (the clamping parameter) which we simply set to zero in that previous work. Here we derive the optimal value of the clamping parameter, and demonstrate experimentally that using that optimal value can result in significantly improved performance over that of clamping to zero, over and above the improvement beyond traditional approaches.

Multi-Modal Performance Measures in Oregon: Developing a Transportation Cost Index Based Upon Multi-Modal Network and Land Use Information

DOT National Transportation Integrated Search

2016-02-01

Transportation Cost Index is a performance measure for transportation and land use systems originally proposed and piloted by Reiff and Gregor (2005). It fills important niches of existing similar measures in term of policy areas covered and type of ...

(In)Flexibility of Constituency in Japanese in Multi-Modal Categorial Grammar with Structured Phonology

ERIC Educational Resources Information Center

Kubota, Yusuke

2010-01-01

This dissertation proposes a theory of categorial grammar called Multi-Modal Categorial Grammar with Structured Phonology. The central feature that distinguishes this theory from the majority of contemporary syntactic theories is that it decouples (without completely segregating) two aspects of syntax--hierarchical organization (reflecting…

Alternative Fuels Data Center: Multi-Modal Transportation

Science.gov Websites

examples of resources to help travelers use multi-modal transportation. OpenTripPlanner Map - an online transportation modes including transit (bus or train), walking, and bicycling 511 - a one-stop source from the of alternative transportation modes. A 2010 evaluation by the Oregon Transportation Research and

Multi-modality 3D breast imaging with X-Ray tomosynthesis and automated ultrasound.

PubMed

Sinha, Sumedha P; Roubidoux, Marilyn A; Helvie, Mark A; Nees, Alexis V; Goodsitt, Mitchell M; LeCarpentier, Gerald L; Fowlkes, J Brian; Chalek, Carl L; Carson, Paul L

2007-01-01

This study evaluated the utility of 3D automated ultrasound in conjunction with 3D digital X-Ray tomosynthesis for breast cancer detection and assessment, to better localize and characterize lesions in the breast. Tomosynthesis image volumes and automated ultrasound image volumes were acquired in the same geometry and in the same view for 27 patients. 3 MQSA certified radiologists independently reviewed the image volumes, visually correlating the images from the two modalities with in-house software. More sophisticated software was used on a smaller set of 10 cases, which enabled the radiologist to draw a 3D box around the suspicious lesion in one image set and isolate an anatomically correlated, similarly boxed region in the other modality image set. In the primary study, correlation was found to be moderately useful to the readers. In the additional study, using improved software, the median usefulness rating increased and confidence in localizing and identifying the suspicious mass increased in more than half the cases. As automated scanning and reading software techniques advance, superior results are expected.

Effect of perceptual load on semantic access by speech in children

PubMed Central

Jerger, Susan; Damian, Markus F.; Mills, Candice; Bartlett, James; Tye-Murray, Nancy; Abdi, Hervè

2013-01-01

Purpose To examine whether semantic access by speech requires attention in children. Method Children (N=200) named pictures and ignored distractors on a cross-modal (distractors: auditory-no face) or multi-modal (distractors: auditory-static face and audiovisual-dynamic face) picture word task. The cross-modal had a low load, and the multi-modal had a high load [i.e., respectively naming pictures displayed 1) on a blank screen vs 2) below the talker’s face on his T-shirt]. Semantic content of distractors was manipulated to be related vs unrelated to picture (e.g., picture dog with distractors bear vs cheese). Lavie's (2005) perceptual load model proposes that semantic access is independent of capacity limited attentional resources if irrelevant semantic-content manipulation influences naming times on both tasks despite variations in loads but dependent on attentional resources exhausted by higher load task if irrelevant content influences naming only on cross-modal (low load). Results Irrelevant semantic content affected performance for both tasks in 6- to 9-year-olds, but only on cross-modal in 4–5-year-olds. The addition of visual speech did not influence results on the multi-modal task. Conclusion Younger and older children differ in dependence on attentional resources for semantic access by speech. PMID:22896045

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

PubMed

Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

2015-08-01

Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

WE-H-206-02: Recent Advances in Multi-Modality Molecular Imaging of Small Animals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsui, B.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

Investigation of a dual modal method for bone pathologies using quantitative ultrasound and photoacoustics

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Gannot, Israel; Eyal, Avishay

2015-03-01

Osteoporosis is a widespread disease that has a catastrophic impact on patient's lives and overwhelming related healthcare costs. In recent works, we have developed a multi-spectral, frequency domain photoacoustic method for the evaluation of bone pathologies. This method has great advantages over pure ultrasonic or optical methods as it provides both molecular information from the bone absorption spectrum and bone mechanical status from the characteristics of the ultrasound propagation. These characteristics include both the Speed of Sound (SOS) and Broadband Ultrasonic Attenuation (BUA). To test the method's quantitative predictions, we have constructed a combined ultrasound and photoacoustic setup. Here, we experimentally present a dual modality system, and compares between the methods on bone samples in-vitro. The differences between the two modalities are shown to provide valuable insight into the bone structure and functional status.

Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

PubMed Central

Kampmann, Peter; Kirchner, Frank

2014-01-01

With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach. PMID:24743158

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1990-01-01

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Addressing practical challenges in utility optimization of mobile wireless sensor networks

NASA Astrophysics Data System (ADS)

Eswaran, Sharanya; Misra, Archan; La Porta, Thomas; Leung, Kin

2008-04-01

This paper examines the practical challenges in the application of the distributed network utility maximization (NUM) framework to the problem of resource allocation and sensor device adaptation in a mission-centric wireless sensor network (WSN) environment. By providing rich (multi-modal), real-time information about a variety of (often inaccessible or hostile) operating environments, sensors such as video, acoustic and short-aperture radar enhance the situational awareness of many battlefield missions. Prior work on the applicability of the NUM framework to mission-centric WSNs has focused on tackling the challenges introduced by i) the definition of an individual mission's utility as a collective function of multiple sensor flows and ii) the dissemination of an individual sensor's data via a multicast tree to multiple consuming missions. However, the practical application and performance of this framework is influenced by several parameters internal to the framework and also by implementation-specific decisions. This is made further complex due to mobile nodes. In this paper, we use discrete-event simulations to study the effects of these parameters on the performance of the protocol in terms of speed of convergence, packet loss, and signaling overhead thereby addressing the challenges posed by wireless interference and node mobility in ad-hoc battlefield scenarios. This study provides better understanding of the issues involved in the practical adaptation of the NUM framework. It also helps identify potential avenues of improvement within the framework and protocol.

Experimental modal substructuring to couple and uncouple substructures with flexible fixtures and multi-point connections

NASA Astrophysics Data System (ADS)

Allen, Matthew S.; Mayes, Randall L.; Bergman, Elizabeth J.

2010-11-01

Modal substructuring or component mode synthesis (CMS) has been standard practice for many decades in the analytical realm, yet a number of significant difficulties have been encountered when attempting to combine experimentally derived modal models with analytical ones or when predicting the effect of structural modifications using experimental measurements. This work presents a new method that removes the effects of a flexible fixture from an experimentally obtained modal model. It can be viewed as an extension to the approach where rigid masses are removed from a structure. The approach presented here improves the modal basis of the substructure, so that it can be used to more accurately estimate the modal parameters of the built-up system. New types of constraints are also presented, which constrain the modal degrees of freedom of the substructures, avoiding the need to estimate the connection point displacements and rotations. These constraints together with the use of a flexible fixture enable a new approach for joining structures, especially those with statically indeterminate multi-point connections, such as two circular flanges that are joined by many more bolts than required to enforce compatibility if the substructures were rigid. Fixture design is discussed, one objective of which is to achieve a mass-loaded boundary condition that exercises the substructure at the connection point as it is in the built up system. The proposed approach is demonstrated with two examples using experimental measurements from laboratory systems. The first is a simple problem of joining two beams of differing lengths, while the second consists of a three-dimensional structure comprising a circular plate that is bolted at eight locations to a flange on a cylindrical structure. In both cases frequency response functions predicted by the substructuring methods agree well with those of the actual coupled structures over a significant range of frequencies.

A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative.

PubMed

Mei, Haibo; Poslad, Stefan; Du, Shuang

2017-12-11

Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers' mobile patterns, travellers' modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service.

Towards ultrahigh resting-state functional connectivity in the mouse brain using photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Hariri, Ali; Bely, Nicholas; Chen, Chen; Nasiriavanaki, Mohammadreza

2016-03-01

The increasing use of mouse models for human brain disease studies, coupled with the fact that existing high-resolution functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing both mechanical and optical scanning in the photoacoustic microscopy, we can image spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images is going to be acquired noninvasively with a fast frame rate, a large field of view, and a high spatial resolution. We developed an optical resolution photoacoustic microscopy (OR-PAM) with diode laser. Laser light was raster scanned due to XY-stage movement. Images from ultra-high OR-PAM can then be used to study brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy.

Collaboration Modality, Cognitive Load, and Science Inquiry Learning in Virtual Inquiry Environments

ERIC Educational Resources Information Center

Erlandson, Benjamin E.; Nelson, Brian C.; Savenye, Wilhelmina C.

2010-01-01

Educational multi-user virtual environments (MUVEs) have been shown to be effective platforms for situated science inquiry curricula. While researchers find MUVEs to be supportive of collaborative scientific inquiry processes, the complex mix of multi-modal messages present in MUVEs can lead to cognitive overload, with learners unable to…

Students' Multi-Modal Re-Presentations of Scientific Knowledge and Creativity

ERIC Educational Resources Information Center

Koren, Yitzhak; Klavir, Rama; Gorodetsky, Malka

2005-01-01

The paper brings the results of a project that passed on to students the opportunity for re-presenting their acquired knowledge via the construction of multi-modal "learning resources". These "learning resources" substituted for lectures and books and became the official learning sources in the classroom. The rational for the…

A Multi-Modal Active Learning Experience for Teaching Social Categorization

ERIC Educational Resources Information Center

Schwarzmueller, April

2011-01-01

This article details a multi-modal active learning experience to help students understand elements of social categorization. Each student in a group dynamics course observed two groups in conflict and identified examples of in-group bias, double-standard thinking, out-group homogeneity bias, law of small numbers, group attribution error, ultimate…

A practical salient region feature based 3D multi-modality registration method for medical images

NASA Astrophysics Data System (ADS)

Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

2006-03-01

We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

Digital Course Materials: A Case Study of the Apple iPad in the Academic Environment

ERIC Educational Resources Information Center

Cameron, Andrea H.; Bush, Michael H.

2011-01-01

The newness of the iPad device creates a phenomenon unique and unstudied in the academic environment. By merging the innovations of electronic text, e-reader, and multi-modal functionality, the iPad tablet device can act as an e-reader providing digital course materials as well as a range of other supplementary academic applications. This…

e-Learning, e-Books and Virtual Reference Service: The Nexus between the Library and Education

ERIC Educational Resources Information Center

Nicholas, Pauline; White, Thelma

2012-01-01

The society relies on institutions of higher education to produce a literate workforce; one that is able to function in a dynamic, technological, information-overload environment. In support of this new thrust, most universities have incorporated the use of new media and ICTs in the teaching learning process resulting in a multi-modal approach…

Multisensory Integration Strategy for Modality-Specific Loss of Inhibition Control in Older Adults.

PubMed

Lee, Ahreum; Ryu, Hokyoung; Kim, Jae-Kwan; Jeong, Eunju

2018-04-11

Older adults are known to have lesser cognitive control capability and greater susceptibility to distraction than young adults. Previous studies have reported age-related problems in selective attention and inhibitory control, yielding mixed results depending on modality and context in which stimuli and tasks were presented. The purpose of the study was to empirically demonstrate a modality-specific loss of inhibitory control in processing audio-visual information with ageing. A group of 30 young adults (mean age = 25.23, Standar Desviation (SD) = 1.86) and 22 older adults (mean age = 55.91, SD = 4.92) performed the audio-visual contour identification task (AV-CIT). We compared performance of visual/auditory identification (Uni-V, Uni-A) with that of visual/auditory identification in the presence of distraction in counterpart modality (Multi-V, Multi-A). The findings showed a modality-specific effect on inhibitory control. Uni-V performance was significantly better than Multi-V, indicating that auditory distraction significantly hampered visual target identification. However, Multi-A performance was significantly enhanced compared to Uni-A, indicating that auditory target performance was significantly enhanced by visual distraction. Additional analysis showed an age-specific effect on enhancement between Uni-A and Multi-A depending on the level of visual inhibition. Together, our findings indicated that the loss of visual inhibitory control was beneficial for the auditory target identification presented in a multimodal context in older adults. A likely multisensory information processing strategy in the older adults was further discussed in relation to aged cognition.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Multi-family Group Treatment for Veterans with Mood Disorders: A Pilot Study

PubMed Central

Sherman, Michelle D.; Fischer, Ellen P.; Owen, Richard R.; Lu, Liya; Han, Xiaotong

2015-01-01

Mood disorders affect large numbers of individuals and their families; the ripple effects on relationship functioning can be great. Researchers have advocated for a relational perspective to mood disorder treatment, and several promising treatments have been developed. However, few rigorous evaluations have been conducted within the Veterans Affairs (VA) system. Multifamily group therapy, an evidence-based practice for people living with schizophrenia, has recently been adapted for other psychological disorders with promising results. This report describes the first published evaluation of this treatment modality in the VA system for veterans living with mood disorders. 101 male veterans (74 with major depression and 27 with bipolar disorder) and their family members participated in REACH (Reaching out to Educate and Assist Caring, Healthy Families), a 9-month, manualized, multi-family group treatment, intervention adapted from McFarlane's original multi-family group model. Participants completed self-report questionnaires at four time points across the course of the treatment, and service utilization data for veterans were obtained from VA databases. Both veterans and family members showed improvements in their knowledge about mood disorders, understanding of positive strategies for dealing with situations commonly confronted in mood disorders, and family coping strategies. Veterans also evidenced improvement in family communication and problem-solving behaviors, empowerment, perceived social support, psychiatric symptoms, and overall quality of life. The REACH intervention holds promise as a feasible, acceptable, and effective treatment for veterans living with mood disorders and their families. Further study is warranted. PMID:26336613

Multi-family Group Treatment for Veterans with Mood Disorders: A Pilot Study.

PubMed

Sherman, Michelle D; Fischer, Ellen P; Owen, Richard R; Lu, Liya; Han, Xiaotong

2015-09-01

Mood disorders affect large numbers of individuals and their families; the ripple effects on relationship functioning can be great. Researchers have advocated for a relational perspective to mood disorder treatment, and several promising treatments have been developed. However, few rigorous evaluations have been conducted within the Veterans Affairs (VA) system. Multifamily group therapy, an evidence-based practice for people living with schizophrenia, has recently been adapted for other psychological disorders with promising results. This report describes the first published evaluation of this treatment modality in the VA system for veterans living with mood disorders. 101 male veterans (74 with major depression and 27 with bipolar disorder) and their family members participated in REACH (Reaching out to Educate and Assist Caring, Healthy Families), a 9-month, manualized, multi-family group treatment, intervention adapted from McFarlane's original multi-family group model. Participants completed self-report questionnaires at four time points across the course of the treatment, and service utilization data for veterans were obtained from VA databases. Both veterans and family members showed improvements in their knowledge about mood disorders, understanding of positive strategies for dealing with situations commonly confronted in mood disorders, and family coping strategies. Veterans also evidenced improvement in family communication and problem-solving behaviors, empowerment, perceived social support, psychiatric symptoms, and overall quality of life. The REACH intervention holds promise as a feasible, acceptable, and effective treatment for veterans living with mood disorders and their families. Further study is warranted.

A density distribution algorithm for bone incorporating local orthotropy, modal analysis and theories of cellular solids.

PubMed

Impelluso, Thomas J

2003-06-01

An algorithm for bone remodeling is presented which allows for both a redistribution of density and a continuous change of principal material directions for the orthotropic material properties of bone. It employs a modal analysis to add density for growth and a local effective strain based analysis to redistribute density. General re-distribution functions are presented. The model utilizes theories of cellular solids to relate density and strength. The code predicts the same general density distributions and local orthotropy as observed in reality.

The effectiveness of multi modal representation text books to improve student's scientific literacy of senior high school students

NASA Astrophysics Data System (ADS)

Zakiya, Hanifah; Sinaga, Parlindungan; Hamidah, Ida

2017-05-01

The results of field studies showed the ability of science literacy of students was still low. One root of the problem lies in the books used in learning is not oriented toward science literacy component. This study focused on the effectiveness of the use of textbook-oriented provisioning capability science literacy by using multi modal representation. The text books development method used Design Representational Approach Learning to Write (DRALW). Textbook design which was applied to the topic of "Kinetic Theory of Gases" is implemented in XI grade students of high school learning. Effectiveness is determined by consideration of the effect and the normalized percentage gain value, while the hypothesis was tested using Independent T-test. The results showed that the textbooks which were developed using multi-mode representation science can improve the literacy skills of students. Based on the size of the effect size textbooks developed with representation multi modal was found effective in improving students' science literacy skills. The improvement was occurred in all the competence and knowledge of scientific literacy. The hypothesis testing showed that there was a significant difference on the ability of science literacy between class that uses textbooks with multi modal representation and the class that uses the regular textbook used in schools.

Graduate Student Perceptions of Multi-Modal Tablet Use in Academic Environments

ERIC Educational Resources Information Center

Bryant, Ezzard C., Jr.

2016-01-01

The purpose of this study was to explore graduate student perceptions of use and the ease of use of multi-modal tablets to access electronic course materials, and the perceived differences based on students' gender, age, college of enrollment, and previous experience. This study used the Unified Theory of Acceptance and Use of Technology to…

A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

NASA Astrophysics Data System (ADS)

Faizrahnemoon, Mahsa; Schlote, Arieh; Maggi, Lorenzo; Crisostomi, Emanuele; Shorten, Robert

2015-11-01

This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

Nonspinning numerical relativity waveform surrogates: assessing the model

NASA Astrophysics Data System (ADS)

Field, Scott; Blackman, Jonathan; Galley, Chad; Scheel, Mark; Szilagyi, Bela; Tiglio, Manuel

2015-04-01

Recently, multi-modal gravitational waveform surrogate models have been built directly from data numerically generated by the Spectral Einstein Code (SpEC). I will describe ways in which the surrogate model error can be quantified. This task, in turn, requires (i) characterizing differences between waveforms computed by SpEC with those predicted by the surrogate model and (ii) estimating errors associated with the SpEC waveforms from which the surrogate is built. Both pieces can have numerous sources of numerical and systematic errors. We make an attempt to study the most dominant error sources and, ultimately, the surrogate model's fidelity. These investigations yield information about the surrogate model's uncertainty as a function of time (or frequency) and parameter, and could be useful in parameter estimation studies which seek to incorporate model error. Finally, I will conclude by comparing the numerical relativity surrogate model to other inspiral-merger-ringdown models. A companion talk will cover the building of multi-modal surrogate models.

Hierarchical patch-based co-registration of differently stained histopathology slides

NASA Astrophysics Data System (ADS)

Yigitsoy, Mehmet; Schmidt, Günter

2017-03-01

Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

Band-edge engineering for controlled multi-modal nanolasing in plasmonic superlattices

DOE PAGES

Wang, Danqing; Yang, Ankun; Wang, Weijia; ...

2017-07-10

Single band-edge states can trap light and function as high-quality optical feedback for microscale lasers and nanolasers. However, access to more than a single band-edge mode for nanolasing has not been possible because of limited cavity designs. Here, we describe how plasmonic superlattices-finite-arrays of nanoparticles (patches) grouped into microscale arrays-can support multiple band-edge modes capable of multi-modal nanolasing at programmed emission wavelengths and with large mode spacings. Different lasing modes show distinct input-output light behaviour and decay dynamics that can be tailored by nanoparticle size. By modelling the superlattice nanolasers with a four-level gain system and a time-domain approach, wemore » reveal that the accumulation of population inversion at plasmonic hot spots can be spatially modulated by the diffractive coupling order of the patches. Furthermore, we show that symmetry-broken superlattices can sustain switchable nanolasing between a single mode and multiple modes.« less

Osteo-cise: Strong Bones for Life: Protocol for a community-based randomised controlled trial of a multi-modal exercise and osteoporosis education program for older adults at risk of falls and fractures

PubMed Central

2012-01-01

Background Osteoporosis affects over 220 million people worldwide, and currently there is no ‘cure’ for the disease. Thus, there is a need to develop evidence-based, safe and acceptable prevention strategies at the population level that target multiple risk factors for fragility fractures to reduce the health and economic burden of the condition. Methods/design The Osteo-cise: Strong Bones for Life study will investigate the effectiveness and feasibility of a multi-component targeted exercise, osteoporosis education/awareness and behavioural change program for improving bone health and muscle function and reducing falls risk in community-dwelling older adults at an increased risk of fracture. Men and women aged ≥60 years will participate in an 18-month randomised controlled trial comprising a 12-month structured and supervised community-based program and a 6-month ‘research to practise’ translational phase. Participants will be randomly assigned to either the Osteo-cise intervention or a self-management control group. The intervention will comprise a multi-modal exercise program incorporating high velocity progressive resistance training, moderate impact weight-bearing exercise and high challenging balance exercises performed three times weekly at local community-based fitness centres. A behavioural change program will be used to enhance exercise adoption and adherence to the program. Community-based osteoporosis education seminars will be conducted to improve participant knowledge and understanding of the risk factors and preventative measures for osteoporosis, falls and fractures. The primary outcomes measures, to be collected at baseline, 6, 12, and 18 months, will include DXA-derived hip and spine bone mineral density measurements and functional muscle power (timed stair-climb test). Secondary outcomes measures include: MRI-assessed distal femur and proximal tibia trabecular bone micro-architecture, lower limb and back maximal muscle strength, balance and function (four square step test, functional reach test, timed up-and-go test and 30-second sit-to-stand), falls incidence and health-related quality of life. Cost-effectiveness will also be assessed. Discussion The findings from the Osteo-cise: Strong Bones for Life study will provide new information on the efficacy of a targeted multi-modal community-based exercise program incorporating high velocity resistance training, together with an osteoporosis education and behavioural change program for improving multiple risk factors for falls and fracture in older adults at risk of fragility fracture. Trial registration Australian New Zealand Clinical Trials Registry reference ACTRN12609000100291 PMID:22640372

3D multimodal cardiac data reconstruction using angiography and computerized tomographic angiography registration.

PubMed

Moosavi Tayebi, Rohollah; Wirza, Rahmita; Sulaiman, Puteri S B; Dimon, Mohd Zamrin; Khalid, Fatimah; Al-Surmi, Aqeel; Mazaheri, Samaneh

2015-04-22

Computerized tomographic angiography (3D data representing the coronary arteries) and X-ray angiography (2D X-ray image sequences providing information about coronary arteries and their stenosis) are standard and popular assessment tools utilized for medical diagnosis of coronary artery diseases. At present, the results of both modalities are individually analyzed by specialists and it is difficult for them to mentally connect the details of these two techniques. The aim of this work is to assist medical diagnosis by providing specialists with the relationship between computerized tomographic angiography and X-ray angiography. In this study, coronary arteries from two modalities are registered in order to create a 3D reconstruction of the stenosis position. The proposed method starts with coronary artery segmentation and labeling for both modalities. Then, stenosis and relevant labeled artery in X-ray angiography image are marked by a specialist. Proper control points for the marked artery in both modalities are automatically detected and normalized. Then, a geometrical transformation function is computed using these control points. Finally, this function is utilized to register the marked artery from the X-ray angiography image on the computerized tomographic angiography and get the 3D position of the stenosis lesion. The result is a 3D informative model consisting of stenosis and coronary arteries' information from the X-ray angiography and computerized tomographic angiography modalities. The results of the proposed method for coronary artery segmentation, labeling and 3D reconstruction are evaluated and validated on the dataset containing both modalities. The advantage of this method is to aid specialists to determine a visual relationship between the correspondent coronary arteries from two modalities and also set up a connection between stenosis points from an X-ray angiography along with their 3D positions on the coronary arteries from computerized tomographic angiography. Moreover, another benefit of this work is that the medical acquisition standards remain unchanged, which means that no calibration in the acquisition devices is required. It can be applied on most computerized tomographic angiography and angiography devices.

Structural system identification based on variational mode decomposition

NASA Astrophysics Data System (ADS)

Bagheri, Abdollah; Ozbulut, Osman E.; Harris, Devin K.

2018-03-01

In this paper, a new structural identification method is proposed to identify the modal properties of engineering structures based on dynamic response decomposition using the variational mode decomposition (VMD). The VMD approach is a decomposition algorithm that has been developed as a means to overcome some of the drawbacks and limitations of the empirical mode decomposition method. The VMD-based modal identification algorithm decomposes the acceleration signal into a series of distinct modal responses and their respective center frequencies, such that when combined their cumulative modal responses reproduce the original acceleration response. The decaying amplitude of the extracted modal responses is then used to identify the modal damping ratios using a linear fitting function on modal response data. Finally, after extracting modal responses from available sensors, the mode shape vector for each of the decomposed modes in the system is identified from all obtained modal response data. To demonstrate the efficiency of the algorithm, a series of numerical, laboratory, and field case studies were evaluated. The laboratory case study utilized the vibration response of a three-story shear frame, whereas the field study leveraged the ambient vibration response of a pedestrian bridge to characterize the modal properties of the structure. The modal properties of the shear frame were computed using analytical approach for a comparison with the experimental modal frequencies. Results from these case studies demonstrated that the proposed method is efficient and accurate in identifying modal data of the structures.

DataViewer3D: An Open-Source, Cross-Platform Multi-Modal Neuroimaging Data Visualization Tool

PubMed Central

Gouws, André; Woods, Will; Millman, Rebecca; Morland, Antony; Green, Gary

2008-01-01

Integration and display of results from multiple neuroimaging modalities [e.g. magnetic resonance imaging (MRI), magnetoencephalography, EEG] relies on display of a diverse range of data within a common, defined coordinate frame. DataViewer3D (DV3D) is a multi-modal imaging data visualization tool offering a cross-platform, open-source solution to simultaneous data overlay visualization requirements of imaging studies. While DV3D is primarily a visualization tool, the package allows an analysis approach where results from one imaging modality can guide comparative analysis of another modality in a single coordinate space. DV3D is built on Python, a dynamic object-oriented programming language with support for integration of modular toolkits, and development of cross-platform software for neuroimaging. DV3D harnesses the power of the Visualization Toolkit (VTK) for two-dimensional (2D) and 3D rendering, calling VTK's low level C++ functions from Python. Users interact with data via an intuitive interface that uses Python to bind wxWidgets, which in turn calls the user's operating system dialogs and graphical user interface tools. DV3D currently supports NIfTI-1, ANALYZE™ and DICOM formats for MRI data display (including statistical data overlay). Formats for other data types are supported. The modularity of DV3D and ease of use of Python allows rapid integration of additional format support and user development. DV3D has been tested on Mac OSX, RedHat Linux and Microsoft Windows XP. DV3D is offered for free download with an extensive set of tutorial resources and example data. PMID:19352444

Retrospective case-control non-inferiority analysis of intravenous lidocaine in a colorectal surgery enhanced recovery program.

PubMed

Naik, Bhiken I; Tsang, Siny; Knisely, Anne; Yerra, Sandeep; Durieux, Marcel E

2017-01-31

Enhanced recovery after surgery (ERAS) programs typically utilizes multi-modal analgesia to reduce perioperative opioid consumption. Systemic lidocaine is used in several of these ERAS algorithms and has been shown to reduce opioid use after colorectal surgery. However it is unclear how much the other components of an ERAS protocol contribute to the final outcome. Using a noninferiority analysis we sought to assess the role of perioperative lidocaine in an ERAS program for colorectal surgery, using pain and opioid consumption as outcomes. We conducted a retrospective review of patients who had received intravenous lidocaine perioperatively during colorectal surgery. We matched them with patients who were managed using a multi-component ERAS protocol, which included perioperative lidocaine. We tested a joint hypothesis of noninferiority of lidocaine infusion to ERAS protocol in postoperative pain scores and opioid consumption. We assigned a noninferiority margin of 1 point (on an 11-point numerical rating scale) difference in pain and a ratio [mean (lidocaine) / mean (ERAS)] of 1.2 in opioid consumption, respectively. Fifty-two patients in the lidocaine group were matched with patients in the ERAS group. With regards to opioid consumption, in the overall [1.68 (1.43-1.98)] [odds ratio (95% confidence interval)] analysis and on postoperative day (POD) 1 [2.38 (1.74-3.31)] lidocaine alone was inferior to multi-modal analgesia. On POD 2 and beyond, although the mean odds ratio for opioid consumption was 1.43 [1.43 (1.17-1.73)], the lower limit extended beyond the pre-defined cut-off of 1.2, rendering the outcome inconclusive. For pain scores lidocaine is non-inferior to ERAS [-0.17 (-1.08-0.74)] on POD 2 and beyond. Pain scores on POD 1 and in the overall cohort were inconclusive based on the noninferiority analysis. The addition of a multi-component ERAS protocol to intravenous lidocaine incrementally reduces opioid consumption, most evident on POD 1. For pain scores the data is inconclusive on POD 1, however on POD 2 and beyond lidocaine alone is non-inferior to an ERAS program with lidocaine. Opioid-related complications, including return of bowel function, were not different between the groups despite reduced opioid use in the ERAS group.

A dynamically reconfigurable multi-functional PLL for SRAM-based FPGA in 65nm CMOS technology

NASA Astrophysics Data System (ADS)

Yang, Mingqian; Chen, Lei; Li, Xuewu; Zhang, Yanlong

2018-04-01

Phase-locked loops (PLL) have been widely utilized in FPGA as an important module for clock management. PLL with dynamic reconfiguration capability is always welcomed in FPGA design as it is able to decrease power consumption and simultaneously improve flexibility. In this paper, a multi-functional PLL with dynamic reconfiguration capability for 65nm SRAM-based FPGA is proposed. Firstly, configurable charge pump and loop filter are utilized to optimize the loop bandwidth. Secondly, the PLL incorporates a VCO with dual control voltages to accelerate the adjustment of oscillation frequency. Thirdly, three configurable dividers are presented for flexible frequency synthesis. Lastly, a configuration block with dynamic reconfiguration function is proposed. Simulation results demonstrate that the proposed multi-functional PLL can output clocks with configurable division ratio, phase shift and duty cycle. The PLL can also be dynamically reconfigured without affecting other parts' running or halting the FPGA device.

Advances in Spatial Data Infrastructure, Acquisition, Analysis, Archiving and Dissemination

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuran K.; Rochon, Gilbert L.; Duerr, Ruth; Rank, Robert; Nativi, Stefano; Stocker, Erich Franz

2010-01-01

The authors review recent contributions to the state-of-thescience and benign proliferation of satellite remote sensing, spatial data infrastructure, near-real-time data acquisition, analysis on high performance computing platforms, sapient archiving, multi-modal dissemination and utilization for a wide array of scientific applications. The authors also address advances in Geoinformatics and its growing ubiquity, as evidenced by its inclusion as a focus area within the American Geophysical Union (AGU), European Geosciences Union (EGU), as well as by the evolution of the IEEE Geoscience and Remote Sensing Society's (GRSS) Data Archiving and Distribution Technical Committee (DAD TC).

Feasibility Study for a Structurally Efficient, Multi-Modal Shelter Concept Utilizing Advanced Technology Production Techniques

DTIC Science & Technology

1974-02-01

II I~ x p:1 ns ion P roc cuurc Longitudin:-11 Section, Container Mod·c Configuration r Ex p :m s i on Pro c c d u r e Longitudinal Section...No . I II. I I I. IV. v. VI. VII. VIII. IX. X . XI. XII. XIII. XIV. XV . XVI. XVII . XVIII . XIX. XX. XXI. XXII . XXI II. XXIV...mat e rial s and examples from these categories . Glass Fibers Glass Mi c r os pheres As bestos Carbon Graphite Ce llulose Cotton Jute Rayo n

Uncertain Photometric Redshifts with Deep Learning Methods

NASA Astrophysics Data System (ADS)

D'Isanto, A.

2017-06-01

The need for accurate photometric redshifts estimation is a topic that has fundamental importance in Astronomy, due to the necessity of efficiently obtaining redshift information without the need of spectroscopic analysis. We propose a method for determining accurate multi-modal photo-z probability density functions (PDFs) using Mixture Density Networks (MDN) and Deep Convolutional Networks (DCN). A comparison with a Random Forest (RF) is performed.

Low Complexity Track Initialization and Fusion for Multi-Modal Sensor Networks

DTIC Science & Technology

2012-11-08

feature was demonstrated via the simulations. Aerospace 2011work further documents our investigation of multiple target tracking filters in...bounds that determine how well a sensor network can resolve and localize multiple targets as a function of the operating parameters such as sensor...probability density (PHD) filter for binary measurements using proximity sensors. 15. SUBJECT TERMS proximity sensors, PHD filter, multiple

Magnetic Polarization Measurements of the Multi-modal Plasma Response to 3D fields in the EAST Tokamak

DOE PAGES

Logan, Nikolas; Cui, L.; Wang, Hui -Hui; ...

2018-04-30

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n=2 fields in the same plasma for which the n=1 responses are well synchronized.more » Neither the maximum radial nor the maximum poloidal field response to n=2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n=1 and n=2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.« less

Magnetic Polarization Measurements of the Multi-modal Plasma Response to 3D fields in the EAST Tokamak

DOE Office of Scientific and Technical Information (OSTI.GOV)

Logan, Nikolas; Cui, L.; Wang, Hui -Hui

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n=2 fields in the same plasma for which the n=1 responses are well synchronized.more » Neither the maximum radial nor the maximum poloidal field response to n=2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n=1 and n=2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.« less

Multisensory Integration Strategy for Modality-Specific Loss of Inhibition Control in Older Adults

PubMed Central

Ryu, Hokyoung; Kim, Jae-Kwan; Jeong, Eunju

2018-01-01

Older adults are known to have lesser cognitive control capability and greater susceptibility to distraction than young adults. Previous studies have reported age-related problems in selective attention and inhibitory control, yielding mixed results depending on modality and context in which stimuli and tasks were presented. The purpose of the study was to empirically demonstrate a modality-specific loss of inhibitory control in processing audio-visual information with ageing. A group of 30 young adults (mean age = 25.23, Standard Deviation (SD) = 1.86) and 22 older adults (mean age = 55.91, SD = 4.92) performed the audio-visual contour identification task (AV-CIT). We compared performance of visual/auditory identification (Uni-V, Uni-A) with that of visual/auditory identification in the presence of distraction in counterpart modality (Multi-V, Multi-A). The findings showed a modality-specific effect on inhibitory control. Uni-V performance was significantly better than Multi-V, indicating that auditory distraction significantly hampered visual target identification. However, Multi-A performance was significantly enhanced compared to Uni-A, indicating that auditory target performance was significantly enhanced by visual distraction. Additional analysis showed an age-specific effect on enhancement between Uni-A and Multi-A depending on the level of visual inhibition. Together, our findings indicated that the loss of visual inhibitory control was beneficial for the auditory target identification presented in a multimodal context in older adults. A likely multisensory information processing strategy in the older adults was further discussed in relation to aged cognition. PMID:29641462

A Single Session of rTMS Enhances Small-Worldness in Writer's Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph.

PubMed

Bharath, Rose D; Panda, Rajanikant; Reddam, Venkateswara Reddy; Bhaskar, M V; Gohel, Suril; Bhardwaj, Sujas; Prajapati, Arvind; Pal, Pramod Kumar

2017-01-01

Background and Purpose : Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method : Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer's Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result : A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI ( p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion : Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo . Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not "noise".

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Modality Specificity and Integration in Working Memory: Insights from Visuospatial Bootstrapping

ERIC Educational Resources Information Center

Allen, Richard J.; Havelka, Jelena; Falcon, Thomas; Evans, Sally; Darling, Stephen

2015-01-01

The question of how meaningful associations between verbal and spatial information might be utilized to facilitate working memory performance is potentially highly instructive for models of memory function. The present study explored how separable processing capacities within specialized domains might each contribute to this, by examining the…

Multi-modal molecular diffuse optical tomography system for small animal imaging

PubMed Central

Guggenheim, James A.; Basevi, Hector R. A.; Frampton, Jon; Styles, Iain B.; Dehghani, Hamid

2013-01-01

A multi-modal optical imaging system for quantitative 3D bioluminescence and functional diffuse imaging is presented, which has no moving parts and uses mirrors to provide multi-view tomographic data for image reconstruction. It is demonstrated that through the use of trans-illuminated spectral near infrared measurements and spectrally constrained tomographic reconstruction, recovered concentrations of absorbing agents can be used as prior knowledge for bioluminescence imaging within the visible spectrum. Additionally, the first use of a recently developed multi-view optical surface capture technique is shown and its application to model-based image reconstruction and free-space light modelling is demonstrated. The benefits of model-based tomographic image recovery as compared to 2D planar imaging are highlighted in a number of scenarios where the internal luminescence source is not visible or is confounding in 2D images. The results presented show that the luminescence tomographic imaging method produces 3D reconstructions of individual light sources within a mouse-sized solid phantom that are accurately localised to within 1.5mm for a range of target locations and depths indicating sensitivity and accurate imaging throughout the phantom volume. Additionally the total reconstructed luminescence source intensity is consistent to within 15% which is a dramatic improvement upon standard bioluminescence imaging. Finally, results from a heterogeneous phantom with an absorbing anomaly are presented demonstrating the use and benefits of a multi-view, spectrally constrained coupled imaging system that provides accurate 3D luminescence images. PMID:24954977

Sex in the Curriculum: The Effect of a Multi-Modal Sexual History-Taking Module on Medical Student Skills

ERIC Educational Resources Information Center

Lindau, Stacy Tessler; Goodrich, Katie G.; Leitsch, Sara A.; Cook, Sandy

2008-01-01

Purpose: The objective of this study was to determine the effect of a multi-modal curricular intervention designed to teach sexual history-taking skills to medical students. The Association of Professors of Gynecology and Obstetrics, the National Board of Medical Examiners, and others, have identified sexual history-taking as a learning objective…

Multishaker modal testing

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1987-01-01

The major accomplishments of this research are: (1) the refinement and documentation of a multi-input, multi-output modal parameter estimation algorithm which is applicable to general linear, time-invariant dynamic systems; (2) the development and testing of an unsymmetric block-Lanzcos algorithm for reduced-order modeling of linear systems with arbitrary damping; and (3) the development of a control-structure-interaction (CSI) test facility.

Final Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rasure, John, et. al.

Through past DOE funding, the MIND Research network has funded a national consortium effort that used multi-modal neuroimaging, genetics, and clinical assessment of subjects to study schizophrenia in both first episode and persistently ill patients. Although active recruitment of research participants is complete, this consortium remains active and productive in terms of analysis of this unique multi-modal data collected on over 320 subjects.

Multi-Modal Interaction for Robotic Mules

DTIC Science & Technology

2014-02-26

Multi-Modal Interaction for Robotic Mules Glenn Taylor, Mike Quist, Matt Lanting, Cory Dunham , Patrick Theisen, Paul Muench Abstract...Taylor, Mike Quist, Matt Lanting, Cory Dunham , and Patrick Theisen are with Soar Technology, Inc. (corresponding author: 734-887- 7620; email: glenn...soartech.com; quist@soartech.com; matt.lanting@soartech.com; dunham @soartech.com; patrick.theisen@soartech.com Paul Muench is with US Army TARDEC

Multi-body Dynamic Contact Analysis Tool for Transmission Design

DTIC Science & Technology

2003-04-01

frequencies were computed in COSMIC NASTRAN, and were validated against the published experimental modal analysis [17]. • Using assumed time domain... modal superposition. • Results from the structural analysis (mode shapes or forced response) were converted into IDEAS universal format (dataset 55...ARMY RESEARCH LABORATORY Multi-body Dynamic Contact Analysis Tool for Transmission Design SBIR Phase II Final Report by

Ships/Trains/Planes/Automobiles: A Renaissance of their Interface

NASA Technical Reports Server (NTRS)

Allan, Stanley N.

1974-01-01

This paper highlights some of the major multi-modal interface problems created by technological advances, socio-political individualism and the flexibility of choices we expect from our transportation modes. The emphasis is on the need for a comprehensive national network of multi-modal priorities to enhance the movement of people and goods within the changing physical shape of our cities.

Effect of Multi Modal Representations on the Critical Thinking Skills of the Fifth Grade Students

ERIC Educational Resources Information Center

Öz, Muhittin; Memis, Esra Kabatas

2018-01-01

The purpose of this study was to explore the effects of multi modal representations within writing to learn activities on students' critical thinking. Mixed method was used. The participants included 32 students 5th grade from elementary school. The groups were randomly selected as a control group and the other class was selected as the…

A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps

PubMed Central

Yin, Shouyi; Dai, Xu; Ouyang, Peng; Liu, Leibo; Wei, Shaojun

2014-01-01

In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features. PMID:25333290

Quantitative multi-modal NDT data analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heideklang, René; Shokouhi, Parisa

2014-02-18

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundantmore » information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity.« less

Non-invasive and Non-destructive Characterization of Tissue Engineered Constructs Using Ultrasound Imaging Technologies: A Review.

PubMed

Kim, Kang; Wagner, William R

2016-03-01

With the rapid expansion of biomaterial development and coupled efforts to translate such advances toward the clinic, non-invasive and non-destructive imaging tools to evaluate implants in situ in a timely manner are critically needed. The required multi-level information is comprehensive, including structural, mechanical, and biological changes such as scaffold degradation, mechanical strength, cell infiltration, extracellular matrix formation and vascularization to name a few. With its inherent advantages of non-invasiveness and non-destructiveness, ultrasound imaging can be an ideal tool for both preclinical and clinical uses. In this review, currently available ultrasound imaging technologies that have been applied in vitro and in vivo for tissue engineering and regenerative medicine are discussed and some new emerging ultrasound technologies and multi-modality approaches utilizing ultrasound are introduced.

Analysis of vibration characteristics of opening device for deepwater robot cabin door and study of its structural optimization design

NASA Astrophysics Data System (ADS)

Zeng, Baoping; Liu, Jipeng; Zhang, Yu; Gong, Yajun; Hu, Sanbao

2017-12-01

Deepwater robots are important devices for human to explore the sea, which is being under development towards intellectualization, multitasking, long-endurance and large depth along with the development of science and technology. As far as a deep-water robot is concerned, its mechanical systems is an important subsystem because not only it influences the instrument measuring precision and shorten the service life of cabin devices but also its overlarge vibration and noise lead to disadvantageous effects to marine life within the operational area. Therefore, vibration characteristics shall be key factor for the deep-water robot system design. The sample collection and recycling system of some certain deepwater robot in a mechanism for opening the underwater cabin door for external operation and recycling test equipment is focused in this study. For improving vibration characteristics of locations of the cabin door during opening processes, a vibration model was established to the opening system; and the structural optimization design was carried out to its important structures by utilizing the multi-objective shape optimization and topology optimization method based on analysis of the system vibration. Analysis of characteristics of exciting forces causing vibration was first carried out, which include characteristics of dynamic loads within the hinge clearances and due to friction effects and the fluid dynamic exciting forces during processes of opening the cabin door. Moreover, vibration acceleration responses for a few important locations of the devices for opening the cabin cover were deduced by utilizing the modal synthesis method so that its rigidity and modal frequency may be one primary factor influencing the system vibration performances based on analysis of weighted acceleration responses. Thus, optimization design was carried out to the cabin cover by utilizing the multi-objective topology optimization method to perform reduction of weighted accelerations of key structure locations.

Multi-Modality Imaging in the Evaluation and Treatment of Mitral Regurgitation.

PubMed

Bouchard, Marc-André; Côté-Laroche, Claudia; Beaudoin, Jonathan

2017-10-13

Mitral regurgitation (MR) is frequent and associated with increased mortality and morbidity when severe. It may be caused by intrinsic valvular disease (primary MR) or ventricular deformation (secondary MR). Imaging has a critical role to document the severity, mechanism, and impact of MR on heart function as selected patients with MR may benefit from surgery whereas other will not. In patients planned for a surgical intervention, imaging is also important to select candidates for mitral valve (MV) repair over replacement and to predict surgical success. Although standard transthoracic echocardiography is the first-line modality to evaluate MR, newer imaging modalities like three-dimensional (3D) transesophageal echocardiography, stress echocardiography, cardiac magnetic resonance (CMR), and computed tomography (CT) are emerging and complementary tools for MR assessment. While some of these modalities can provide insight into MR severity, others will help to determine its mechanism. Understanding the advantages and limitations of each imaging modality is important to appreciate their respective role for MR assessment and help to resolve eventual discrepancies between different diagnostic methods. With the increasing use of transcatheter mitral procedures (repair or replacement) for high-surgical-risk patients, multimodality imaging has now become even more important to determine eligibility, preinterventional planning, and periprocedural guidance.

Sensory processes modulate differences in multi-component behavior and cognitive control between childhood and adulthood.

PubMed

Gohil, Krutika; Bluschke, Annet; Roessner, Veit; Stock, Ann-Kathrin; Beste, Christian

2017-10-01

Many everyday tasks require executive functions to achieve a certain goal. Quite often, this requires the integration of information derived from different sensory modalities. Children are less likely to integrate information from different modalities and, at the same time, also do not command fully developed executive functions, as compared to adults. Yet still, the role of developmental age-related effects on multisensory integration processes has not been examined within the context of multicomponent behavior until now (i.e., the concatenation of different executive subprocesses). This is problematic because differences in multisensory integration might actually explain a significant amount of the developmental effects that have traditionally been attributed to changes in executive functioning. In a system, neurophysiological approach combining electroencephaloram (EEG) recordings and source localization analyses, we therefore examined this question. The results show that differences in how children and adults accomplish multicomponent behavior do not solely depend on developmental differences in executive functioning. Instead, the observed developmental differences in response selection processes (reflected by the P3 ERP) were largely dependent on the complexity of integrating temporally separated stimuli from different modalities. This effect was related to activation differences in medial frontal and inferior parietal cortices. Primary perceptual gating or attentional selection processes (P1 and N1 ERPs) were not affected. The results show that differences in multisensory integration explain parts of transformations in cognitive processes between childhood and adulthood that have traditionally been attributed to changes in executive functioning, especially when these require the integration of multiple modalities during response selection. Hum Brain Mapp 38:4933-4945, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Grouping and Segregation of Sensory Events by Actions in Temporal Audio-Visual Recalibration.

PubMed

Ikumi, Nara; Soto-Faraco, Salvador

2016-01-01

Perception in multi-sensory environments involves both grouping and segregation of events across sensory modalities. Temporal coincidence between events is considered a strong cue to resolve multisensory perception. However, differences in physical transmission and neural processing times amongst modalities complicate this picture. This is illustrated by cross-modal recalibration, whereby adaptation to audio-visual asynchrony produces shifts in perceived simultaneity. Here, we examined whether voluntary actions might serve as a temporal anchor to cross-modal recalibration in time. Participants were tested on an audio-visual simultaneity judgment task after an adaptation phase where they had to synchronize voluntary actions with audio-visual pairs presented at a fixed asynchrony (vision leading or vision lagging). Our analysis focused on the magnitude of cross-modal recalibration to the adapted audio-visual asynchrony as a function of the nature of the actions during adaptation, putatively fostering cross-modal grouping or, segregation. We found larger temporal adjustments when actions promoted grouping than segregation of sensory events. However, a control experiment suggested that additional factors, such as attention to planning/execution of actions, could have an impact on recalibration effects. Contrary to the view that cross-modal temporal organization is mainly driven by external factors related to the stimulus or environment, our findings add supporting evidence for the idea that perceptual adjustments strongly depend on the observer's inner states induced by motor and cognitive demands.

Grouping and Segregation of Sensory Events by Actions in Temporal Audio-Visual Recalibration

PubMed Central

Ikumi, Nara; Soto-Faraco, Salvador

2017-01-01

Perception in multi-sensory environments involves both grouping and segregation of events across sensory modalities. Temporal coincidence between events is considered a strong cue to resolve multisensory perception. However, differences in physical transmission and neural processing times amongst modalities complicate this picture. This is illustrated by cross-modal recalibration, whereby adaptation to audio-visual asynchrony produces shifts in perceived simultaneity. Here, we examined whether voluntary actions might serve as a temporal anchor to cross-modal recalibration in time. Participants were tested on an audio-visual simultaneity judgment task after an adaptation phase where they had to synchronize voluntary actions with audio-visual pairs presented at a fixed asynchrony (vision leading or vision lagging). Our analysis focused on the magnitude of cross-modal recalibration to the adapted audio-visual asynchrony as a function of the nature of the actions during adaptation, putatively fostering cross-modal grouping or, segregation. We found larger temporal adjustments when actions promoted grouping than segregation of sensory events. However, a control experiment suggested that additional factors, such as attention to planning/execution of actions, could have an impact on recalibration effects. Contrary to the view that cross-modal temporal organization is mainly driven by external factors related to the stimulus or environment, our findings add supporting evidence for the idea that perceptual adjustments strongly depend on the observer's inner states induced by motor and cognitive demands. PMID:28154529

Urology Residents' Experience and Attitude Toward Surgical Simulation: Presenting our 4-Year Experience With a Multi-institutional, Multi-modality Simulation Model.

PubMed

Chow, Alexander K; Sherer, Benjamin A; Yura, Emily; Kielb, Stephanie; Kocjancic, Ervin; Eggener, Scott; Turk, Thomas; Park, Sangtae; Psutka, Sarah; Abern, Michael; Latchamsetty, Kalyan C; Coogan, Christopher L

2017-11-01

To evaluate the Urological resident's attitude and experience with surgical simulation in residency education using a multi-institutional, multi-modality model. Residents from 6 area urology training programs rotated through simulation stations in 4 consecutive sessions from 2014 to 2017. Workshops included GreenLight photovaporization of the prostate, ureteroscopic stone extraction, laparoscopic peg transfer, 3-dimensional laparoscopy rope pass, transobturator sling placement, intravesical injection, high definition video system trainer, vasectomy, and Urolift. Faculty members provided teaching assistance, objective scoring, and verbal feedback. Participants completed a nonvalidated questionnaire evaluating utility of the workshop and soliciting suggestions for improvement. Sixty-three of 75 participants (84%) (postgraduate years 1-6) completed the exit questionnaire. Median rating of exercise usefulness on a scale of 1-10 ranged from 7.5 to 9. On a scale of 0-10, cumulative median scores of the course remained high over 4 years: time limit per station (9; interquartile range [IQR] 2), faculty instruction (9, IQR 2), ease of use (9, IQR 2), face validity (8, IQR 3), and overall course (9, IQR 2). On multivariate analysis, there was no difference in rating of domains between postgraduate years. Sixty-seven percent (42/63) believe that simulation training should be a requirement of Urology residency. Ninety-seven percent (63/65) viewed the laboratory as beneficial to their education. This workshop model is a valuable training experience for residents. Most participants believe that surgical simulation is beneficial and should be a requirement for Urology residency. High ratings of usefulness for each exercise demonstrated excellent face validity provided by the course. Copyright © 2017 Elsevier Inc. All rights reserved.

Combined multi-modal photoacoustic tomography, optical coherence tomography (OCT) and OCT angiography system with an articulated probe for in vivo human skin structure and vasculature imaging

PubMed Central

Liu, Mengyang; Chen, Zhe; Zabihian, Behrooz; Sinz, Christoph; Zhang, Edward; Beard, Paul C.; Ginner, Laurin; Hoover, Erich; Minneman, Micheal P.; Leitgeb, Rainer A.; Kittler, Harald; Drexler, Wolfgang

2016-01-01

Cutaneous blood flow accounts for approximately 5% of cardiac output in human and plays a key role in a number of a physiological and pathological processes. We show for the first time a multi-modal photoacoustic tomography (PAT), optical coherence tomography (OCT) and OCT angiography system with an articulated probe to extract human cutaneous vasculature in vivo in various skin regions. OCT angiography supplements the microvasculature which PAT alone is unable to provide. Co-registered volumes for vessel network is further embedded in the morphologic image provided by OCT. This multi-modal system is therefore demonstrated as a valuable tool for comprehensive non-invasive human skin vasculature and morphology imaging in vivo. PMID:27699106

Asymmetries of the human social brain in the visual, auditory and chemical modalities

PubMed Central

Brancucci, Alfredo; Lucci, Giuliana; Mazzatenta, Andrea; Tommasi, Luca

2008-01-01

Structural and functional asymmetries are present in many regions of the human brain responsible for motor control, sensory and cognitive functions and communication. Here, we focus on hemispheric asymmetries underlying the domain of social perception, broadly conceived as the analysis of information about other individuals based on acoustic, visual and chemical signals. By means of these cues the brain establishes the border between ‘self’ and ‘other’, and interprets the surrounding social world in terms of the physical and behavioural characteristics of conspecifics essential for impression formation and for creating bonds and relationships. We show that, considered from the standpoint of single- and multi-modal sensory analysis, the neural substrates of the perception of voices, faces, gestures, smells and pheromones, as evidenced by modern neuroimaging techniques, are characterized by a general pattern of right-hemispheric functional asymmetry that might benefit from other aspects of hemispheric lateralization rather than constituting a true specialization for social information. PMID:19064350

Quantitative computed tomography for the prediction of pulmonary function after lung cancer surgery: a simple method using simulation software.

PubMed

Ueda, Kazuhiro; Tanaka, Toshiki; Li, Tao-Sheng; Tanaka, Nobuyuki; Hamano, Kimikazu

2009-03-01

The prediction of pulmonary functional reserve is mandatory in therapeutic decision-making for patients with resectable lung cancer, especially those with underlying lung disease. Volumetric analysis in combination with densitometric analysis of the affected lung lobe or segment with quantitative computed tomography (CT) helps to identify residual pulmonary function, although the utility of this modality needs investigation. The subjects of this prospective study were 30 patients with resectable lung cancer. A three-dimensional CT lung model was created with voxels representing normal lung attenuation (-600 to -910 Hounsfield units). Residual pulmonary function was predicted by drawing a boundary line between the lung to be preserved and that to be resected, directly on the lung model. The predicted values were correlated with the postoperative measured values. The predicted and measured values corresponded well (r=0.89, p<0.001). Although the predicted values corresponded with values predicted by simple calculation using a segment-counting method (r=0.98), there were two outliers whose pulmonary functional reserves were predicted more accurately by CT than by segment counting. The measured pulmonary functional reserves were significantly higher than the predicted values in patients with extensive emphysematous areas (<-910 Hounsfield units), but not in patients with chronic obstructive pulmonary disease. Quantitative CT yielded accurate prediction of functional reserve after lung cancer surgery and helped to identify patients whose functional reserves are likely to be underestimated. Hence, this modality should be utilized for patients with marginal pulmonary function.

The importance of integrated left atrial evaluation: From hypertension to heart failure with preserved ejection fraction.

PubMed

Beltrami, Matteo; Palazzuoli, Alberto; Padeletti, Luigi; Cerbai, Elisabetta; Coiro, Stefano; Emdin, Michele; Marcucci, Rossella; Morrone, Doralisa; Cameli, Matteo; Savino, Ketty; Pedrinelli, Roberto; Ambrosio, Giuseppe

2018-02-01

Functional analysis and measurement of left atrium are an integral part of cardiac evaluation, and they represent a key element during non-invasive analysis of diastolic function in patients with hypertension (HT) and/or heart failure with preserved ejection fraction (HFpEF). However, diastolic dysfunction remains quite elusive regarding classification, and atrial size and function are two key factors for left ventricular (LV) filling evaluation. Chronic left atrial (LA) remodelling is the final step of chronic intra-cavitary pressure overload, and it accompanies increased neurohormonal, proarrhythmic and prothrombotic activities. In this systematic review, we aim to purpose a multi-modality approach for LA geometry and function analysis, which integrates diastolic flow with LA characteristics and remodelling through application of both traditional and new diagnostic tools. The most important studies published in the literature on LA size, function and diastolic dysfunction in patients with HFpEF, HT and/or atrial fibrillation (AF) are considered and discussed. In HFpEF and HT, pulsed and tissue Doppler assessments are useful tools to estimate LV filling pressure, atrio-ventricular coupling and LV relaxation but they need to be enriched with LA evaluation in terms of morphology and function. An integrated evaluation should be also applied to patients with a high arrhythmic risk, in whom eccentric LA remodelling and higher LA stiffness are associated with a greater AF risk. Evaluation of LA size, volume, function and structure are mandatory in the management of patients with HT, HFpEF and AF. A multi-modality approach could provide additional information, identifying subjects with more severe LA remodelling. Left atrium assessment deserves an accurate study inside the cardiac imaging approach and optimised measurement with established cut-offs need to be better recognised through multicenter studies. © 2017 John Wiley & Sons Ltd.

Effective Beginning Handwriting Instruction: Multi-Modal, Consistent Format for 2 Years, and Linked to Spelling and Composing

ERIC Educational Resources Information Center

Wolf, Beverly; Abbott, Robert D.; Berninger, Virginia W.

2017-01-01

In Study 1, the treatment group (N = 33 first graders, M = 6 years 10 months, 16 girls) received Slingerland multi-modal (auditory, visual, tactile, motor through hand, and motor through mouth) manuscript (unjoined) handwriting instruction embedded in systematic spelling, reading, and composing lessons; and the control group (N = 16 first graders,…

Providing University Education in Physical Geography across the South Pacific Islands: Multi-Modal Course Delivery and Student Grade Performance

ERIC Educational Resources Information Center

Terry, James P.; Poole, Brian

2012-01-01

Enormous distances across the vast South Pacific hinder student access to the main Fiji campus of the regional tertiary education provider, the University of the South Pacific (USP). Fortunately, USP has been a pioneer in distance education (DE) and promotes multi-modal delivery of programmes. Geography has embraced DE, but doubts remain about…

Multi-Body Dynamic Contact Analysis. Tool for Transmission Design SBIR Phase II Final Report

DTIC Science & Technology

2003-04-01

shapes and natural frequencies were computed in COSMIC NASTRAN, and were validated against the published experimental modal analysis [17]. • Using...COSMIC NASTRAN via modal superposition. • Results from the structural analysis (mode shapes or forced response) were converted into IDEAS universal...ARMY RESEARCH LABORATORY Multi-body Dynamic Contact Analysis Tool for Transmission Design SBIR Phase II Final Report by

A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative

PubMed Central

Mei, Haibo; Poslad, Stefan; Du, Shuang

2017-01-01

Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers’ mobile patterns, travellers’ modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service. PMID:29232907

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

PubMed

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.

Using Genome Sequence to Enable the Design of Medicines and Chemical Probes.

PubMed

Angelbello, Alicia J; Chen, Jonathan L; Childs-Disney, Jessica L; Zhang, Peiyuan; Wang, Zi-Fu; Disney, Matthew D

2018-02-28

Rapid progress in genome sequencing technology has put us firmly into a postgenomic era. A key challenge in biomedical research is harnessing genome sequence to fulfill the promise of personalized medicine. This Review describes how genome sequencing has enabled the identification of disease-causing biomolecules and how these data have been converted into chemical probes of function, preclinical lead modalities, and ultimately U.S. Food and Drug Administration (FDA)-approved drugs. In particular, we focus on the use of oligonucleotide-based modalities to target disease-causing RNAs; small molecules that target DNA, RNA, or protein; the rational repurposing of known therapeutic modalities; and the advantages of pharmacogenetics. Lastly, we discuss the remaining challenges and opportunities in the direct utilization of genome sequence to enable design of medicines.

A new approach of building 3D visualization framework for multimodal medical images display and computed assisted diagnosis

NASA Astrophysics Data System (ADS)

Li, Zhenwei; Sun, Jianyong; Zhang, Jianguo

2012-02-01

As more and more CT/MR studies are scanning with larger volume of data sets, more and more radiologists and clinician would like using PACS WS to display and manipulate these larger data sets of images with 3D rendering features. In this paper, we proposed a design method and implantation strategy to develop 3D image display component not only with normal 3D display functions but also with multi-modal medical image fusion as well as compute-assisted diagnosis of coronary heart diseases. The 3D component has been integrated into the PACS display workstation of Shanghai Huadong Hospital, and the clinical practice showed that it is easy for radiologists and physicians to use these 3D functions such as multi-modalities' (e.g. CT, MRI, PET, SPECT) visualization, registration and fusion, and the lesion quantitative measurements. The users were satisfying with the rendering speeds and quality of 3D reconstruction. The advantages of the component include low requirements for computer hardware, easy integration, reliable performance and comfortable application experience. With this system, the radiologists and the clinicians can manipulate with 3D images easily, and use the advanced visualization tools to facilitate their work with a PACS display workstation at any time.

Damage detection of building structures under ambient excitation through the analysis of the relationship between the modal participation ratio and story stiffness

NASA Astrophysics Data System (ADS)

Park, Hyo Seon; Oh, Byung Kwan

2018-03-01

This paper presents a new approach for the damage detection of building structures under ambient excitation based on the inherent modal characteristics. In this study, without the extraction of modal parameters widely utilized in the previous studies on damage detection, a new index called the modal participation ratio (MPR), which is a representative value of the modal response extracted from dynamic responses measured in ambient vibration tests, is proposed to evaluate the change of the system of a structure according to the reduction of the story stiffness. The relationship between the MPR, representing a modal contribution for a specific mode and degree of freedom in buildings, and the story stiffness damage factor (SSDF), representing the extent of reduction in the story stiffness, is analyzed in various damage scenarios. From the analyses with three examples, several rules for the damage localization of building structures are found based on the characteristics of the MPR variation for the first mode subject to change in the SSDF. In addition, a damage severity function, derived from the relationship between the MPR for the first mode in the lowest story and the SSDF, is constructed to identify the severity of story stiffness reduction. Furthermore, the locations and severities of multiple damages are identified via the superposition of the presented damage severity functions. The presented method was applied to detect damage in a three-dimensional reinforced concrete (RC) structure.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

PubMed

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for personalized cancer therapy.

Magnetic polarization measurements of the multi-modal plasma response to 3D fields in the EAST tokamak

NASA Astrophysics Data System (ADS)

Logan, N. C.; Cui, L.; Wang, H.; Sun, Y.; Gu, S.; Li, G.; Nazikian, R.; Paz-Soldan, C.

2018-07-01

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n  =  2 fields in the same plasma for which the n  =  1 responses are well synchronized. Neither the maximum radial nor the maximum poloidal field response to n  =  2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n  =  1 and n  =  2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.

Nanoparticles in practice for molecular-imaging applications: An overview.

PubMed

Padmanabhan, Parasuraman; Kumar, Ajay; Kumar, Sundramurthy; Chaudhary, Ravi Kumar; Gulyás, Balázs

2016-09-01

Nanoparticles (NPs) are playing a progressively more significant role in multimodal and multifunctional molecular imaging. The agents like Superparamagnetic iron oxide (SPIO), manganese oxide (MnO), gold NPs/nanorods and quantum dots (QDs) possess specific properties like paramagnetism, superparamagnetism, surface plasmon resonance (SPR) and photoluminescence respectively. These specific properties make them able for single/multi-modal and single/multi-functional molecular imaging. NPs generally have nanomolar or micromolar sensitivity range and can be detected via imaging instrumentation. The distinctive characteristics of these NPs make them suitable for imaging, therapy and delivery of drugs. Multifunctional nanoparticles (MNPs) can be produced through either modification of shell or surface or by attaching an affinity ligand to the nanoparticles. They are utilized for targeted imaging by magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), positron emission tomography (PET), computed tomography (CT), photo acoustic imaging (PAI), two photon or fluorescent imaging and ultra sound etc. Toxicity factor of NPs is also a very important concern and toxic effect should be eliminated. First generation NPs have been designed, developed and tested in living subjects and few of them are already in clinical use. In near future, molecular imaging will get advanced with multimodality and multifunctionality to detect diseases like cancer, neurodegenerative diseases, cardiac diseases, inflammation, stroke, atherosclerosis and many others in their early stages. In the current review, we discussed single/multifunctional nanoparticles along with molecular imaging modalities. The present article intends to reveal recent avenues for nanomaterials in multimodal and multifunctional molecular imaging through a review of pertinent literatures. The topic emphasises on the distinctive characteristics of nanomaterial which makes them, suitable for biomedical imaging, therapy and delivery of drugs. This review is more informative of indicative technologies which will be helpful in a way to plan, understand and lead the nanotechnology related work. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Primary prevention of cannabis use: a systematic review of randomized controlled trials.

PubMed

Norberg, Melissa M; Kezelman, Sarah; Lim-Howe, Nicholas

2013-01-01

A systematic review of primary prevention was conducted for cannabis use outcomes in youth and young adults. The aim of the review was to develop a comprehensive understanding of prevention programming by assessing universal, targeted, uni-modal, and multi-modal approaches as well as individual program characteristics. Twenty-eight articles, representing 25 unique studies, identified from eight electronic databases (EMBASE, MEDLINE, CINAHL, ERIC, PsycINFO, DRUG, EBM Reviews, and Project CORK), were eligible for inclusion. Results indicated that primary prevention programs can be effective in reducing cannabis use in youth populations, with statistically significant effect sizes ranging from trivial (0.07) to extremely large (5.26), with the majority of significant effect sizes being trivial to small. Given that the preponderance of significant effect sizes were trivial to small and that percentages of statistically significant and non-statistically significant findings were often equivalent across program type and individual components, the effectiveness of primary prevention for cannabis use should be interpreted with caution. Universal multi-modal programs appeared to outperform other program types (i.e, universal uni-modal, targeted multi-modal, targeted unimodal). Specifically, universal multi-modal programs that targeted early adolescents (10-13 year olds), utilised non-teacher or multiple facilitators, were short in duration (10 sessions or less), and implemented boosters sessions were associated with large median effect sizes. While there were studies in these areas that contradicted these results, the results highlight the importance of assessing the interdependent relationship of program components and program types. Finally, results indicated that the overall quality of included studies was poor, with an average quality rating of 4.64 out of 9. Thus, further quality research and reporting and the development of new innovative programs are required.

Primary Prevention of Cannabis Use: A Systematic Review of Randomized Controlled Trials

PubMed Central

Norberg, Melissa M.; Kezelman, Sarah; Lim-Howe, Nicholas

2013-01-01

A systematic review of primary prevention was conducted for cannabis use outcomes in youth and young adults. The aim of the review was to develop a comprehensive understanding of prevention programming by assessing universal, targeted, uni-modal, and multi-modal approaches as well as individual program characteristics. Twenty-eight articles, representing 25 unique studies, identified from eight electronic databases (EMBASE, MEDLINE, CINAHL, ERIC, PsycINFO, DRUG, EBM Reviews, and Project CORK), were eligible for inclusion. Results indicated that primary prevention programs can be effective in reducing cannabis use in youth populations, with statistically significant effect sizes ranging from trivial (0.07) to extremely large (5.26), with the majority of significant effect sizes being trivial to small. Given that the preponderance of significant effect sizes were trivial to small and that percentages of statistically significant and non-statistically significant findings were often equivalent across program type and individual components, the effectiveness of primary prevention for cannabis use should be interpreted with caution. Universal multi-modal programs appeared to outperform other program types (i.e, universal uni-modal, targeted multi-modal, targeted unimodal). Specifically, universal multi-modal programs that targeted early adolescents (10–13 year olds), utilised non-teacher or multiple facilitators, were short in duration (10 sessions or less), and implemented boosters sessions were associated with large median effect sizes. While there were studies in these areas that contradicted these results, the results highlight the importance of assessing the interdependent relationship of program components and program types. Finally, results indicated that the overall quality of included studies was poor, with an average quality rating of 4.64 out of 9. Thus, further quality research and reporting and the development of new innovative programs are required. PMID:23326396

Multishaker modal testing

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.

1983-01-01

Procedures for improving the modal modeling of structures using test data and to determine appropriate analytical models based on substructure experimental data were explored. Two related research topics were considered in modal modeling: using several independently acquired columns of frequency response data, and modal modeling using simultaneous multi-point excitation. In component mode synthesis modeling, the emphasis is on determining the best way to employ complex modes and residuals.

Acta Aeronautica et Astronautica Sinica,

DTIC Science & Technology

1983-07-28

substructural analysis in modal synthesis - two improved substructural assembling techniques 49 9-node quadrilateral isoparametric element 64 Application of laser...Time from Service Data, J. Aircraft, Vol. 15, No. 11, 1978. 48 MULTI-LEVEL SUBSTRUCTURAL ANALYSIS IN MODAL SYNTHESIS -- TWO IMPROVED SUBSTRUCTURAL...34 Modal Synthesis in Structural Dynamic Analysis ," Naching Institute of Aeronautics and Astronautics, 1979. 62a 8. Chang Te-wen, "Free-Interface Modal

Hybrid optical acoustic seafloor mapping

NASA Astrophysics Data System (ADS)

Inglis, Gabrielle

The oceanographic research and industrial communities have a persistent demand for detailed three dimensional sea floor maps which convey both shape and texture. Such data products are used for archeology, geology, ship inspection, biology, and habitat classification. There are a variety of sensing modalities and processing techniques available to produce these maps and each have their own potential benefits and related challenges. Multibeam sonar and stereo vision are such two sensors with complementary strengths making them ideally suited for data fusion. Data fusion approaches however, have seen only limited application to underwater mapping and there are no established methods for creating hybrid, 3D reconstructions from two underwater sensing modalities. This thesis develops a processing pipeline to synthesize hybrid maps from multi-modal survey data. It is helpful to think of this processing pipeline as having two distinct phases: Navigation Refinement and Map Construction. This thesis extends existing work in underwater navigation refinement by incorporating methods which increase measurement consistency between both multibeam and camera. The result is a self consistent 3D point cloud comprised of camera and multibeam measurements. In map construction phase, a subset of the multi-modal point cloud retaining the best characteristics of each sensor is selected to be part of the final map. To quantify the desired traits of a map several characteristics of a useful map are distilled into specific criteria. The different ways that hybrid maps can address these criteria provides justification for producing them as an alternative to current methodologies. The processing pipeline implements multi-modal data fusion and outlier rejection with emphasis on different aspects of map fidelity. The resulting point cloud is evaluated in terms of how well it addresses the map criteria. The final hybrid maps retain the strengths of both sensors and show significant improvement over the single modality maps and naively assembled multi-modal maps.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future.

PubMed

Salama, Gayle R; Heier, Linda A; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John

2017-01-01

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma—Foundations and Future

PubMed Central

Salama, Gayle R.; Heier, Linda A.; Patel, Praneil; Ramakrishna, Rohan; Magge, Rajiv; Tsiouris, Apostolos John

2018-01-01

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes. PMID:29403420

MRIVIEW: An interactive computational tool for investigation of brain structure and function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ranken, D.; George, J.

MRIVIEW is a software system which uses image processing and visualization to provide neuroscience researchers with an integrated environment for combining functional and anatomical information. Key features of the software include semi-automated segmentation of volumetric head data and an interactive coordinate reconciliation method which utilizes surface visualization. The current system is a precursor to a computational brain atlas. We describe features this atlas will incorporate, including methods under development for visualizing brain functional data obtained from several different research modalities.

Development of a multi-criteria evaluation system to assess growing pig welfare.

PubMed

Martín, P; Traulsen, I; Buxadé, C; Krieter, J

2017-03-01

The aim of this paper was to present an alternative multi-criteria evaluation model to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. The WQ assessment protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first step of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion. The utility functions and the aggregation function were constructed in two separated steps. The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) method was used for utility function determination and the Choquet Integral (CI) was used as an aggregation operator. The WQ decision-makers' preferences were fitted in order to construct the utility functions and to determine the CI parameters. The methods were tested with generated data sets for farms of growing pigs. Using the MAUT, similar results were obtained to the ones obtained applying the WQ protocol aggregation methods. It can be concluded that due to the use of an interactive approach such as MACBETH, this alternative methodology is more transparent and more flexible than the methodology proposed by WQ, which allows the possibility to modify the model according, for instance, to new scientific knowledge.

Identification of multi-modal plasma responses to applied magnetic perturbations using the plasma reluctance

DOE PAGES

Logan, Nikolas C.; Paz-Soldan, Carlos; Park, Jong-Kyu; ...

2016-05-03

Using the plasma reluctance, the Ideal Perturbed Equilibrium Code is able to efficiently identify the structure of multi-modal magnetic plasma response measurements and the corresponding impact on plasma performance in the DIII-D tokamak. Recent experiments demonstrated that multiple kink modes of comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n = 2. This multi-modal response is in good agreement with ideal magnetohydrodynamic models, but detailed decompositions presented here show that the mode structures are not fully described by either the least stable modes or the resonant plasma response. This paper identifies the measured response fieldsmore » as the first eigenmodes of the plasma reluctance, enabling clear diagnosis of the plasma modes and their impact on performance from external sensors. The reluctance shows, for example, how very stable modes compose a significant portion of the multi-modal plasma response field and that these stable modes drive significant resonant current. Finally, this work is an overview of the first experimental applications using the reluctance to interpret the measured response and relate it to multifaceted physics, aimed towards providing the foundation of understanding needed to optimize nonaxisymmetric fields for independent control of stability and transport.« less

Design of magnetic and fluorescent nanoparticles for in vivo MR and NIRF cancer imaging

NASA Astrophysics Data System (ADS)

Key, Jaehong

One big challenge for cancer treatment is that it has many errors in detection of cancers in the early stages before metastasis occurs. Using a current imaging modality, the detection of small tumors having potential metastasis is still very difficult. Thus, the development of multi-component nanoparticles (NPs) for dual modality cancer imaging is invaluable. The multi-component NPs can be an alternative to overcome the limitations from an imaging modality. For example, the multi-component NPs can visualize small tumors in both magnetic resonance imaging (MRI) and near infrared fluorescence (NIRF) imaging, which can help find the location of the tumors deep inside the body using MRI and subsequently guide surgeons to delineate the margin of tumors using highly sensitive NIRF imaging during a surgical operation. In this dissertation, we demonstrated the potential of the MRI and NIRF dual-modality NPs for skin and bladder cancer imaging. The multi-component NPs consisted of glycol chitosan, superparamagnetic iron oxide, NIRF dye, and cancer targeting peptides. We characterized the NPs and evaluated them with tumor bearing mice as well as various cancer cells. The findings of this research will contribute to the development of cancer diagnostic imaging and it can also be extensively applied to drug delivery system and fluorescence-guided surgical removal of cancer.

A randomised controlled trial of a web-based multi-modal therapy program to improve executive functioning in children and adolescents with acquired brain injury.

PubMed

Piovesana, Adina; Ross, Stephanie; Lloyd, Owen; Whittingham, Koa; Ziviani, Jenny; Ware, Robert S; McKinlay, Lynne; Boyd, Roslyn N

2017-10-01

To examine the efficacy of a multi-modal web-based therapy program, Move it to improve it (Mitii™) delivered at home to improve Executive Functioning (EF) in children with an acquired brain injury (ABI). Randomised Waitlist controlled trial. Home environment. Sixty children with an ABI were matched in pairs by age and intelligence quotient then randomised to either 20-weeks of Mitii™ training or 20 weeks of Care As Usual (waitlist control; n=30; 17 males; mean age=11y, 11m (±2y, 6m); Full Scale IQ=76.24±17.84). Fifty-eight children completed baseline assessments (32 males; mean age=11.87±2.47; Full Scale IQ=75.21±16.76). Executive functioning was assessed on four domains: attentional control, cognitive flexibility, goal setting, and information processing using subtests from the Wechsler Intelligence Scale for Children (WISC-IV), Delis-Kaplan Executive Functioning System (D-KEFS), Comprehensive Trail Making Test (CTMT), Tower of London (TOL), and Test of Everyday Attention for Children (Tea-Ch). Executive functioning performance in everyday life was assessed via parent questionnaire (Behaviour Rating Inventory of Executive Functioning; BRIEF). No differences were observed at baseline measures. Groups were compared at 20-weeks using linear regression with no significant differences found between groups on all measures of EF. Out of a potential total dose of 60 hours, children in the Mitii™ group completed a mean of 17 hours of Mitii™ intervention. Results indicate no additional benefit to receiving Mitii™ compared to standard care. Mitii™, in its current form, was not shown to improve EF in children with ABI.

Experimental strain modal analysis for beam-like structure by using distributed fiber optics and its damage detection

NASA Astrophysics Data System (ADS)

Cheng, Liangliang; Busca, Giorgio; Cigada, Alfredo

2017-07-01

Modal analysis is commonly considered as an effective tool to obtain the intrinsic characteristics of structures including natural frequencies, modal damping ratios, and mode shapes, which are significant indicators for monitoring the health status of engineering structures. The complex mode indicator function (CMIF) can be regarded as an effective numerical tool to perform modal analysis. In this paper, experimental strain modal analysis based on the CMIF has been introduced. Moreover, a distributed fiber-optic sensor, as a dense measuring device, has been applied to acquire strain data along a beam surface. Thanks to the dense spatial resolution of the distributed fiber optics, more detailed mode shapes could be obtained. In order to test the effectiveness of the method, a mass lump—considered as a linear damage component—has been attached to the surface of the beam, and damage detection based on strain mode shape has been carried out. The results manifest that strain modal parameters can be estimated effectively by utilizing the CMIF based on the corresponding simulations and experiments. Furthermore, damage detection based on strain mode shapes benefits from the accuracy of strain mode shape recognition and the excellent performance of the distributed fiber optics.

A new modal superposition method for nonlinear vibration analysis of structures using hybrid mode shapes

NASA Astrophysics Data System (ADS)

Ferhatoglu, Erhan; Cigeroglu, Ender; Özgüven, H. Nevzat

2018-07-01

In this paper, a new modal superposition method based on a hybrid mode shape concept is developed for the determination of steady state vibration response of nonlinear structures. The method is developed specifically for systems having nonlinearities where the stiffness of the system may take different limiting values. Stiffness variation of these nonlinear systems enables one to define different linear systems corresponding to each value of the limiting equivalent stiffness. Moreover, the response of the nonlinear system is bounded by the confinement of these linear systems. In this study, a modal superposition method utilizing novel hybrid mode shapes which are defined as linear combinations of the modal vectors of the limiting linear systems is proposed to determine periodic response of nonlinear systems. In this method the response of the nonlinear system is written in terms of hybrid modes instead of the modes of the underlying linear system. This provides decrease of the number of modes that should be retained for an accurate solution, which in turn reduces the number of nonlinear equations to be solved. In this way, computational time for response calculation is directly curtailed. In the solution, the equations of motion are converted to a set of nonlinear algebraic equations by using describing function approach, and the numerical solution is obtained by using Newton's method with arc-length continuation. The method developed is applied on two different systems: a lumped parameter model and a finite element model. Several case studies are performed and the accuracy and computational efficiency of the proposed modal superposition method with hybrid mode shapes are compared with those of the classical modal superposition method which utilizes the mode shapes of the underlying linear system.

Multi-Connection Pattern Analysis: Decoding the representational content of neural communication.

PubMed

Li, Yuanning; Richardson, Robert Mark; Ghuman, Avniel Singh

2017-11-15

The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population. Successful MCPA-based decoding indicates the involvement of distributed computational processing and provides a framework for probing the representational structure of the interaction. Simulations demonstrate the efficacy of MCPA in realistic circumstances. In addition, we demonstrate that MCPA can be applied to different signal modalities to evaluate a variety of hypothesis associated with information coding in neural communications. We apply MCPA to fMRI and human intracranial electrophysiological data to provide a proof-of-concept of the utility of this method for decoding individual natural images and faces in functional connectivity data. We further use a MCPA-based representational similarity analysis to illustrate how MCPA may be used to test computational models of information transfer among regions of the visual processing stream. Thus, MCPA can be used to assess the information represented in the coupled activity of interacting neural circuits and probe the underlying principles of information transformation between regions. Copyright © 2017 Elsevier Inc. All rights reserved.

Composite PET and MRI for accurate localization and metabolic modeling: a very useful tool for research and clinic

NASA Astrophysics Data System (ADS)

Bidaut, Luc M.

1991-06-01

In order to help in analyzing PET data and really take advantage of their metabolic content, a system was designed and implemented to align and process data from various medical imaging modalities, particularly (but not only) for brain studies. Although this system is for now mostly used for anatomical localization, multi-modality ROIs and pharmaco-kinetic modeling, more multi-modality protocols will be implemented in the future, not only to help in PET reconstruction data correction and semi-automated ROI definition, but also for helping in improving diagnostic accuracy along with surgery and therapy planning.

Computational method for multi-modal microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

2017-02-01

In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

WE-H-206-03: Promises and Challenges of Benchtop X-Ray Fluorescence CT (XFCT) for Quantitative in Vivo Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, S.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

WE-H-206-01: Photoacoustic Tomography: Multiscale Imaging From Organelles to Patients by Ultrasonically Beating the Optical Diffusion Limit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, L.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

WE-H-206-00: Advances in Preclinical Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

Multi-pulse multi-delay (MPMD) multiple access modulation for UWB

DOEpatents

Dowla, Farid U.; Nekoogar, Faranak

2007-03-20

A new modulation scheme in UWB communications is introduced. This modulation technique utilizes multiple orthogonal transmitted-reference pulses for UWB channelization. The proposed UWB receiver samples the second order statistical function at both zero and non-zero lags and matches the samples to stored second order statistical functions, thus sampling and matching the shape of second order statistical functions rather than just the shape of the received pulses.

Salvage therapy for locally recurrent prostate cancer after radiation.

PubMed

Marcus, David M; Canter, Daniel J; Jani, Ashesh B; Dobbs, Ryan W; Schuster, David M; Carthon, Bradley C; Rossi, Peter J

2012-12-01

External beam radiotherapy (EBRT) is widely utilized as primary therapy for clinically localized prostate cancer. For patients who develop locally recurrent disease after EBRT, local salvage therapy may be indicated. The primary modalities for local salvage treatment in this setting include radical prostatectomy, cryotherapy, and brachytherapy. To date, there is little data describing outcomes and toxicity associated with each of these salvage modalities. A review of the literature was performed to identify studies of local salvage therapy for patients who had failed primary EBRT for localized prostate cancer. We focused on prospective trials and multi-institutional retrospective series in order to identify the highest level of evidence describing these therapies. The majority of reports describing the use of local salvage treatment for recurrent prostate cancer after EBRT are single-institution, retrospective reports, although small prospective studies are available for salvage cryotherapy and salvage brachytherapy. Clinical outcomes and toxicity for each modality vary widely across studies, which is likely due to the heterogeneity of patient populations, treatment techniques, and definitions of failure. In general, most studies demonstrate that local salvage therapy after EBRT may provide long-term local control in appropriately selected patients, although toxicity is often significant. As there are no randomized trials comparing salvage treatment modalities for localized prostate cancer recurrence after EBRT, the selection of a local treatment modality should be made on a patient-by-patient basis, with careful consideration of each patient's disease characteristics and tolerance for the risks of treatment. Additional data, ideally from prospective randomized trials, is needed to guide decision making for patients with local recurrence after EBRT failure.

Sensor modeling and demonstration of a multi-object spectrometer for performance-driven sensing

NASA Astrophysics Data System (ADS)

Kerekes, John P.; Presnar, Michael D.; Fourspring, Kenneth D.; Ninkov, Zoran; Pogorzala, David R.; Raisanen, Alan D.; Rice, Andrew C.; Vasquez, Juan R.; Patel, Jeffrey P.; MacIntyre, Robert T.; Brown, Scott D.

2009-05-01

A novel multi-object spectrometer (MOS) is being explored for use as an adaptive performance-driven sensor that tracks moving targets. Developed originally for astronomical applications, the instrument utilizes an array of micromirrors to reflect light to a panchromatic imaging array. When an object of interest is detected the individual micromirrors imaging the object are tilted to reflect the light to a spectrometer to collect a full spectrum. This paper will present example sensor performance from empirical data collected in laboratory experiments, as well as our approach in designing optical and radiometric models of the MOS channels and the micromirror array. Simulation of moving vehicles in a highfidelity, hyperspectral scene is used to generate a dynamic video input for the adaptive sensor. Performance-driven algorithms for feature-aided target tracking and modality selection exploit multiple electromagnetic observables to track moving vehicle targets.

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

the decisions made by each individual modality. Fusion of features is the simple concatenation of feature vectors from multiple modalities to be...of Features BayesNet MDL 330 LibSVM PCA 80 J48 Wrapper Evaluator 11 3.5.3 Ensemble Based Decision Level Fusion. In ensemble learning multiple ...The high fusion percentages validate our hypothesis that by combining features from multiple modalities, classification accuracy can be improved. As

Multi-modality PET-CT imaging of breast cancer in an animal model using nanoparticle x-ray contrast agent and 18F-FDG

NASA Astrophysics Data System (ADS)

Badea, C. T.; Ghaghada, K.; Espinosa, G.; Strong, L.; Annapragada, A.

2011-03-01

Multi-modality PET-CT imaging is playing an important role in the field of oncology. While PET imaging facilitates functional interrogation of tumor status, the use of CT imaging is primarily limited to anatomical reference. In an attempt to extract comprehensive information about tumor cells and its microenvironment, we used a nanoparticle xray contrast agent to image tumor vasculature and vessel 'leakiness' and 18F-FDG to investigate the metabolic status of tumor cells. In vivo PET/CT studies were performed in mice implanted with 4T1 mammary breast cancer cells.Early-phase micro-CT imaging enabled visualization 3D vascular architecture of the tumors whereas delayedphase micro-CT demonstrated highly permeable vessels as evident by nanoparticle accumulation within the tumor. Both imaging modalities demonstrated the presence of a necrotic core as indicated by a hypo-enhanced region in the center of the tumor. At early time-points, the CT-derived fractional blood volume did not correlate with 18F-FDG uptake. At delayed time-points, the tumor enhancement in 18F-FDG micro-PET images correlated with the delayed signal enhanced due to nanoparticle extravasation seen in CT images. The proposed hybrid imaging approach could be used to better understand tumor angiogenesis and to be the basis for monitoring and evaluating anti-angiogenic and nano-chemotherapies.

Multi-modal intelligent seizure acquisition (MISA) system--a new approach towards seizure detection based on full body motion measures.

PubMed

Conradsen, Isa; Beniczky, Sandor; Wolf, Peter; Terney, Daniella; Sams, Thomas; Sorensen, Helge B D

2009-01-01

Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG) and audio and video recording. The results showed that a non-subject specific MISA system developed on data from the modalities: accelerometer (ACM), gyroscope and EMG is able to detect 98% of the simulated seizures and at the same time mistakes only 4 of the normal movements for seizures. If the system is individualized (subject specific) it is able to detect all simulated seizures with a maximum of 1 false positive. Based on the results from the simulated seizures and normal movements the MISA system seems to be a promising approach to seizure detection.

Multi Modal Anticipation in Fuzzy Space

NASA Astrophysics Data System (ADS)

Asproth, Viveca; Holmberg, Stig C.; Hâkansson, Anita

2006-06-01

We are all stakeholders in the geographical space, which makes up our common living and activity space. This means that a careful, creative, and anticipatory planning, design, and management of that space will be of paramount importance for our sustained life on earth. Here it is shown that the quality of such planning could be significantly increased with help of a computer based modelling and simulation tool. Further, the design and implementation of such a tool ought to be guided by the conceptual integration of some core concepts like anticipation and retardation, multi modal system modelling, fuzzy space modelling, and multi actor interaction.

Nonlinear dynamics of magnetically coupled beams for multi-modal vibration energy harvesting

NASA Astrophysics Data System (ADS)

Abed, I.; Kacem, N.; Bouhaddi, N.; Bouazizi, M. L.

2016-04-01

We investigate the nonlinear dynamics of magnetically coupled beams for multi-modal vibration energy harvesting. A multi-physics model for the proposed device is developed taking into account geometric and magnetic nonlinearities. The coupled nonlinear equations of motion are solved using the Galerkin discretization coupled with the harmonic balance method and the asymptotic numerical method. Several numerical simulations have been performed showing that the expected performances of the proposed vibration energy harvester are significantly promising with up to 130 % in term of bandwidth and up to 60 μWcm-3g-2 in term of normalized harvested power.

Visualizing the anatomical-functional correlation of the human brain

NASA Astrophysics Data System (ADS)

Chang, YuKuang; Rockwood, Alyn P.; Reiman, Eric M.

1995-04-01

Three-dimensional tomographic images obtained from different modalities or from the same modality at different times provide complementary information. For example, while PET shows brain function, images from MRI identify anatomical structures. In this paper, we investigate the problem of displaying available information about structures and function together. Several steps are described to achieve our goal. These include segmentation of the data, registration, resampling, and display. Segmentation is used to identify brain tissue from surrounding tissues, especially in the MRI data. Registration aligns the different modalities as closely as possible. Resampling arises from the registration since two data sets do not usually correspond and the rendering method is most easily achieved if the data correspond to the same grid used in display. We combine several techniques to display the data. MRI data is reconstructed from 2D slices into 3D structures from which isosurfaces are extracted and represented by approximating polygonalizations. These are then displayed using standard graphics pipelines including shaded and transparent images. PET data measures the qualitative rates of cerebral glucose utilization or oxygen consumption. PET image is best displayed as a volume of luminous particles. The combination of both display methods allows the viewer to compare the functional information contained in the PET data with the anatomically more precise MRI data.

Sequential Adaptive Multi-Modality Target Detection and Classification Using Physics Based Models

DTIC Science & Technology

2006-09-01

estimation," R. Raghuram, R. Raich and A.O. Hero, IEEE Intl. Conf. on Acoustics, Speech , and Signal Processing, Toulouse France, June 2006, <http...can then be solved using off-the-shelf classifiers such as radial basis functions, SVM, or kNN classifier structures. When applied to mine detection we...stage waveform selection for adaptive resource constrained state estimation," 2006 IEEE Intl. Conf. on Acoustics, Speech , and Signal Processing

Multi-modal neuroimaging of adolescents with non-suicidal self-injury: Amygdala functional connectivity.

PubMed

Westlund Schreiner, Melinda; Klimes-Dougan, Bonnie; Mueller, Bryon A; Eberly, Lynn E; Reigstad, Kristina M; Carstedt, Patricia A; Thomas, Kathleen M; Hunt, Ruskin H; Lim, Kelvin O; Cullen, Kathryn R

2017-10-15

Non-suicidal self-injury (NSSI) is a significant mental health problem among adolescents. Research is needed to clarify the neurobiology of NSSI and identify candidate neurobiological targets for interventions. Based on prior research implicating heightened negative affect and amygdala hyperactivity in NSSI, we pursued a systems approach to characterize amygdala functional connectivity networks during rest (resting-state functional connectivity [RSFC)]) and a task (task functional connectivity [TFC]) in adolescents with NSSI. We examined amygdala networks in female adolescents with NSSI and healthy controls (n = 45) using resting-state fMRI and a negative emotion face-matching fMRI task designed to activate the amygdala. Connectivity analyses included amygdala RSFC, amygdala TFC, and psychophysiological interactions (PPI) between amygdala connectivity and task conditions. Compared to healthy controls, adolescents with NSSI showed atypical amygdala-frontal connectivity during rest and task; greater amygdala RSFC in supplementary motor area (SMA) and dorsal anterior cingulate; and differential amygdala-occipital connectivity between rest and task. After correcting for depression symptoms, amygdala-SMA RSFC abnormalities, among others, remained significant. This study's limitations include its cross-sectional design and its absence of a psychiatric control group. Using a multi-modal approach, we identified widespread amygdala circuitry anomalies in adolescents with NSSI. While deficits in amygdala-frontal connectivity (driven by depression symptoms) replicates prior work in depression, hyperconnectivity between amygdala and SMA (independent of depression symptoms) has not been previously reported. This circuit may represent an important mechanism underlying the link between negative affect and habitual behaviors. These abnormalities may represent intervention targets for adolescents with NSSI. Copyright © 2017 Elsevier B.V. All rights reserved.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2015-10-01

eyes and image choroidal vessels/capillaries using CARS intravital microscopy Subtask 3: Measure oxy-hemoglobin levels in PBI test and control eyes...AWARD NUMBER: W81XWH-14-1-0537 TITLE: Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia...4. TITLE AND SUBTITLE Mobile, Multimodal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia 5a. CONTRACT NUMBER W81XWH

Development of a new multi-modal Monte-Carlo radiotherapy planning system.

PubMed

Kumada, H; Nakamura, T; Komeda, M; Matsumura, A

2009-07-01

A new multi-modal Monte-Carlo radiotherapy planning system (developing code: JCDS-FX) is under development at Japan Atomic Energy Agency. This system builds on fundamental technologies of JCDS applied to actual boron neutron capture therapy (BNCT) trials in JRR-4. One of features of the JCDS-FX is that PHITS has been applied to particle transport calculation. PHITS is a multi-purpose particle Monte-Carlo transport code. Hence application of PHITS enables to evaluate total doses given to a patient by a combined modality therapy. Moreover, JCDS-FX with PHITS can be used for the study of accelerator based BNCT. To verify calculation accuracy of the JCDS-FX, dose evaluations for neutron irradiation of a cylindrical water phantom and for an actual clinical trial were performed, then the results were compared with calculations by JCDS with MCNP. The verification results demonstrated that JCDS-FX is applicable to BNCT treatment planning in practical use.

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

Control of Spin Wave Dynamics in Spatially Twisted Magnetic Structures

DTIC Science & Technology

2017-06-27

realize high-performance spintronic and magnetic storage devices. 15. SUBJECT TERMS nano- electronics , spin, wave, magnetic, multi-functional, device 16... electronics has required us to develop high-performance and multi-functional electronic devices driven with extremely low power consumption...Spintronics”, simultaneously utilizing the charge and the spin of electrons , provides us with solutions to essential problems for semiconductor-based

An augmented Lagrangian trust region method for inclusion boundary reconstruction using ultrasound/electrical dual-modality tomography

NASA Astrophysics Data System (ADS)

Liang, Guanghui; Ren, Shangjie; Dong, Feng

2018-07-01

The ultrasound/electrical dual-modality tomography utilizes the complementarity of ultrasound reflection tomography (URT) and electrical impedance tomography (EIT) to improve the speed and accuracy of image reconstruction. Due to its advantages of no-invasive, no-radiation and low-cost, ultrasound/electrical dual-modality tomography has attracted much attention in the field of dual-modality imaging and has many potential applications in industrial and biomedical imaging. However, the data fusion of URT and EIT is difficult due to their different theoretical foundations and measurement principles. The most commonly used data fusion strategy in ultrasound/electrical dual-modality tomography is incorporating the structured information extracted from the URT into the EIT image reconstruction process through a pixel-based constraint. Due to the inherent non-linearity and ill-posedness of EIT, the reconstructed images from the strategy suffer from the low resolution, especially at the boundary of the observed inclusions. To improve this condition, an augmented Lagrangian trust region method is proposed to directly reconstruct the shapes of the inclusions from the ultrasound/electrical dual-modality measurements. In the proposed method, the shape of the target inclusion is parameterized by a radial shape model whose coefficients are used as the shape parameters. Then, the dual-modality shape inversion problem is formulated by an energy minimization problem in which the energy function derived from EIT is constrained by an ultrasound measurements model through an equality constraint equation. Finally, the optimal shape parameters associated with the optimal inclusion shape guesses are determined by minimizing the constrained cost function using the augmented Lagrangian trust region method. To evaluate the proposed method, numerical tests are carried out. Compared with single modality EIT, the proposed dual-modality inclusion boundary reconstruction method has a higher accuracy and is more robust to the measurement noise.

Diverse Application of Magnetic Resonance Imaging for Mouse Phenotyping

PubMed Central

Wu, Yijen L.; Lo, Cecilia W.

2017-01-01

Small animal models, particularly mouse models, of human diseases are becoming an indispensable tool for biomedical research. Studies in animal models have provided important insights into the etiology of diseases and accelerated the development of therapeutic strategies. Detailed phenotypic characterization is essential, both for the development of such animal models and mechanistic studies into disease pathogenesis and testing the efficacy of experimental therapeutics. Magnetic Resonance Imaging (MRI) is a versatile and non-invasive imaging modality with excellent penetration depth, tissue coverage, and soft tissue contrast. MRI, being a multi-modal imaging modality, together with proven imaging protocols and availability of good contrast agents, is ideally suited for phenotyping mutant mouse models. Here we describe the applications of MRI for phenotyping structural birth defects involving the brain, heart, and kidney in mice. The versatility of MRI and its ease of use are well suited to meet the rapidly increasing demands for mouse phenotyping in the coming age of functional genomics. PMID:28544650

Photoacoustic and ultrasound dual-modality imaging of human peripheral joints

NASA Astrophysics Data System (ADS)

Xu, Guan; Rajian, Justin R.; Girish, Gandikota; Kaplan, Mariana J.; Fowlkes, J. Brian; Carson, Paul L.; Wang, Xueding

2013-01-01

A photoacoustic (PA) and ultrasound (US) dual modality system, for imaging human peripheral joints, is introduced. The system utilizes a commercial US unit for both US control imaging and PA signal acquisition. Preliminary in vivo evaluation of the system, on normal volunteers, revealed that this system can recover both the structural and functional information of intra- and extra-articular tissues. Confirmed by the control US images, the system, on the PA mode, can differentiate tendon from surrounding soft tissue based on the endogenous optical contrast. Presenting both morphological and pathological information in joint, this system holds promise for diagnosis and characterization of inflammatory joint diseases such as rheumatoid arthritis.

From neurocognition to community participation in serious mental illness: the intermediary role of dysfunctional attitudes and motivation.

PubMed

Thomas, E C; Luther, L; Zullo, L; Beck, A T; Grant, P M

2017-04-01

Evidence for a relationship between neurocognition and functional outcome in important areas of community living is robust in serious mental illness research. Dysfunctional attitudes (defeatist performance beliefs and asocial beliefs) have been identified as intervening variables in this causal chain. This study seeks to expand upon previous research by longitudinally testing the link between neurocognition and community participation (i.e. time in community-based activity) through dysfunctional attitudes and motivation. Adult outpatients with serious mental illness (N = 175) participated, completing follow-up assessments approximately 6 months after initial assessment. Path analysis tested relationships between baseline neurocognition, emotion perception, functional skills, dysfunctional attitudes, motivation, and outcome (i.e. community participation) at baseline and follow-up. Path models demonstrated two pathways to community participation. The first linked neurocognition and community participation through functional skills, defeatist performance beliefs, and motivation. A second pathway linked asocial beliefs and community participation, via a direct path passing through motivation. Model fit was excellent for models predicting overall community participation at baseline and, importantly, at follow-up. The existence of multiple pathways to community participation in a longitudinal model supports the utility of multi-modal interventions for serious mental illness (i.e. treatment packages that build upon individuals' strengths while addressing the array of obstacles to recovery) that feature dysfunctional attitudes and motivation as treatment targets.

LapTrain: multi-modality training curriculum for laparoscopic cholecystectomy-results of a randomized controlled trial.

PubMed

Kowalewski, K F; Garrow, C R; Proctor, T; Preukschas, A A; Friedrich, M; Müller, P C; Kenngott, H G; Fischer, L; Müller-Stich, B P; Nickel, F

2018-02-12

Multiple training modalities for laparoscopy have different advantages, but little research has been conducted on the benefit of a training program that includes multiple different training methods compared to one method only. This study aimed to evaluate benefits of a combined multi-modality training program for surgical residents. Laparoscopic cholecystectomy (LC) was performed on a porcine liver as the pre-test. Randomization was stratified for experience to the multi-modality Training group (12 h of training on Virtual Reality (VR) and box trainer) or Control group (no training). The post-test consisted of a VR LC and porcine LC. Performance was rated with the Global Operative Assessment of Laparoscopic Skills (GOALS) score by blinded experts. Training (n = 33) and Control (n = 31) were similar in the pre-test (GOALS: 13.7 ± 3.4 vs. 14.7 ± 2.6; p = 0.198; operation time 57.0 ± 18.1 vs. 63.4 ± 17.5 min; p = 0.191). In the post-test porcine LC, Training had improved GOALS scores (+ 2.84 ± 2.85 points, p < 0.001), while Control did not (+ 0.55 ± 2.34 points, p = 0.154). Operation time in the post-test was shorter for Training vs. Control (40.0 ± 17.0 vs. 55.0 ± 22.2 min; p = 0.012). Junior residents improved GOALS scores to the level of senior residents (pre-test: 13.7 ± 2.7 vs. 18.3 ± 2.9; p = 0.010; post-test: 15.5 ± 3.4 vs. 18.8 ± 3.8; p = 0.120) but senior residents remained faster (50.1 ± 20.6 vs. 25.0 ± 1.9 min; p < 0.001). No differences were found between groups on the post-test VR trainer. Structured multi-modality training is beneficial for novices to improve basics and overcome the initial learning curve in laparoscopy as well as to decrease operation time for LCs in different stages of experience. Future studies should evaluate multi-modality training in comparison with single modalities. German Clinical Trials Register DRKS00011040.

An empirical study on the utility of BRDF model parameters and topographic parameters for mapping vegetation in a semi-arid region with MISR imagery

USDA-ARS?s Scientific Manuscript database

Multi-angle remote sensing has been proved useful for mapping vegetation community types in desert regions. Based on Multi-angle Imaging Spectro-Radiometer (MISR) multi-angular images, this study compares roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with th...

Optimal Reward Functions in Distributed Reinforcement Learning

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan

2000-01-01

We consider the design of multi-agent systems so as to optimize an overall world utility function when (1) those systems lack centralized communication and control, and (2) each agents runs a distinct Reinforcement Learning (RL) algorithm. A crucial issue in such design problems is to initialize/update each agent's private utility function, so as to induce best possible world utility. Traditional 'team game' solutions to this problem sidestep this issue and simply assign to each agent the world utility as its private utility function. In previous work we used the 'Collective Intelligence' framework to derive a better choice of private utility functions, one that results in world utility performance up to orders of magnitude superior to that ensuing from use of the team game utility. In this paper we extend these results. We derive the general class of private utility functions that both are easy for the individual agents to learn and that, if learned well, result in high world utility. We demonstrate experimentally that using these new utility functions can result in significantly improved performance over that of our previously proposed utility, over and above that previous utility's superiority to the conventional team game utility.

A novel method for flow pattern identification in unstable operational conditions using gamma ray and radial basis function.

PubMed

Roshani, G H; Nazemi, E; Roshani, M M

2017-05-01

Changes of fluid properties (especially density) strongly affect the performance of radiation-based multiphase flow meter and could cause error in recognizing the flow pattern and determining void fraction. In this work, we proposed a methodology based on combination of multi-beam gamma ray attenuation and dual modality densitometry techniques using RBF neural network in order to recognize the flow regime and determine the void fraction in gas-liquid two phase flows independent of the liquid phase changes. The proposed system is consisted of one 137 Cs source, two transmission detectors and one scattering detector. The registered counts in two transmission detectors were used as the inputs of one primary Radial Basis Function (RBF) neural network for recognizing the flow regime independent of liquid phase density. Then, after flow regime identification, three RBF neural networks were utilized for determining the void fraction independent of liquid phase density. Registered count in scattering detector and first transmission detector were used as the inputs of these three RBF neural networks. Using this simple methodology, all the flow patterns were correctly recognized and the void fraction was predicted independent of liquid phase density with mean relative error (MRE) of less than 3.28%. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Dual-Modality System for Both Multi-Color Ultrasound-Switchable Fluorescence and Ultrasound Imaging

PubMed Central

Kandukuri, Jayanth; Yu, Shuai; Cheng, Bingbing; Bandi, Venugopal; D’Souza, Francis; Nguyen, Kytai T.; Hong, Yi; Yuan, Baohong

2017-01-01

Simultaneous imaging of multiple targets (SIMT) in opaque biological tissues is an important goal for molecular imaging in the future. Multi-color fluorescence imaging in deep tissues is a promising technology to reach this goal. In this work, we developed a dual-modality imaging system by combining our recently developed ultrasound-switchable fluorescence (USF) imaging technology with the conventional ultrasound (US) B-mode imaging. This dual-modality system can simultaneously image tissue acoustic structure information and multi-color fluorophores in centimeter-deep tissue with comparable spatial resolutions. To conduct USF imaging on the same plane (i.e., x-z plane) as US imaging, we adopted two 90°-crossed ultrasound transducers with an overlapped focal region, while the US transducer (the third one) was positioned at the center of these two USF transducers. Thus, the axial resolution of USF is close to the lateral resolution, which allows a point-by-point USF scanning on the same plane as the US imaging. Both multi-color USF and ultrasound imaging of a tissue phantom were demonstrated. PMID:28165390

Peer Education Versus Computer-Based Education: Improve Utilization of Library Databases Among Direct Care Nurses.

PubMed

Gonzalez, Roxana; O'Brien-Barry, Patricia; Ancheta, Reginaldo; Razal, Rennuel; Clyne, Mary Ellen

A quasiexperimental study was conducted to demonstrate which teaching modality, peer education or computer-based education, improves the utilization of the library electronic databases and thereby evidence-based knowledge at the point of care. No significant differences were found between the teaching modalities. However, the study identified the need to explore professional development teaching modalities outside the traditional classroom to support an evidence-based practice healthcare environment.

Novel MDM-PON scheme utilizing self-homodyne detection for high-speed/capacity access networks.

PubMed

Chen, Yuanxiang; Li, Juhao; Zhu, Paikun; Wu, Zhongying; Zhou, Peng; Tian, Yu; Ren, Fang; Yu, Jinyi; Ge, Dawei; Chen, Jingbiao; He, Yongqi; Chen, Zhangyuan

2015-12-14

In this paper, we propose a cost-effective, energy-saving mode-division-multiplexing passive optical network (MDM-PON) scheme utilizing self-homodyne detection for high-speed/capacity access network based on low modal-crosstalk few-mode fiber (FMF) and all-fiber mode multiplexer/demultiplexer (MUX/DEMUX). In the proposed scheme, one of the spatial modes is used to transmit a portion of signal carrier (namely pilot-tone) as the local oscillator (LO), while the others are used for signal-bearing channels. At the receiver, the pilot-tone and the signal can be separated without strong crosstalk and sent to the receiver for coherent detection. The spectral efficiency (SE) is significantly enhanced when multiple spatial channels are used. Meanwhile, the self-homodyne detection scheme can effectively suppress laser phase noise, which relaxes the requirement for the lasers line-width at the optical line terminal or optical network units (OLT/ONUs). The digital signal processing (DSP) at the receiver is also simplified since it removes the need for frequency offset compensation and complex phase correction, which reduces the computational complexity and energy consumption. Polarization division multiplexing (PDM) that offers doubled SE is also supported by the scheme. The proposed scheme is scalable to multi-wavelength application when wavelength MUX/DEMUX is utilized. Utilizing the proposed scheme, we demonstrate a proof of concept 4 × 40-Gb/s orthogonal frequency division multiplexing (OFDM) transmission over 55-km FMF using low modal-crosstalk two-mode FMF and MUX/DEMUX with error free operation. Compared with back to back case, less than 1-dB Q-factor penalty is observed after 55-km FMF of the four channels. Signal power and pilot-tone power are also optimized to achieve the optimal transmission performance.

Obstacle traversal and self-righting of bio-inspired robots reveal the physics of multi-modal locomotion

NASA Astrophysics Data System (ADS)

Li, Chen; Fearing, Ronald; Full, Robert

Most animals move in nature in a variety of locomotor modes. For example, to traverse obstacles like dense vegetation, cockroaches can climb over, push across, reorient their bodies to maneuver through slits, or even transition among these modes forming diverse locomotor pathways; if flipped over, they can also self-right using wings or legs to generate body pitch or roll. By contrast, most locomotion studies have focused on a single mode such as running, walking, or jumping, and robots are still far from capable of life-like, robust, multi-modal locomotion in the real world. Here, we present two recent studies using bio-inspired robots, together with new locomotion energy landscapes derived from locomotor-environment interaction physics, to begin to understand the physics of multi-modal locomotion. (1) Our experiment of a cockroach-inspired legged robot traversing grass-like beam obstacles reveals that, with a terradynamically ``streamlined'' rounded body like that of the insect, robot traversal becomes more probable by accessing locomotor pathways that overcome lower potential energy barriers. (2) Our experiment of a cockroach-inspired self-righting robot further suggests that body vibrations are crucial for exploring locomotion energy landscapes and reaching lower barrier pathways. Finally, we posit that our new framework of locomotion energy landscapes holds promise to better understand and predict multi-modal biological and robotic movement.

SU-E-J-109: Accurate Contour Transfer Between Different Image Modalities Using a Hybrid Deformable Image Registration and Fuzzy Connected Image Segmentation Method.

PubMed

Yang, C; Paulson, E; Li, X

2012-06-01

To develop and evaluate a tool that can improve the accuracy of contour transfer between different image modalities under challenging conditions of low image contrast and large image deformation, comparing to a few commonly used methods, for radiation treatment planning. The software tool includes the following steps and functionalities: (1) accepting input of images of different modalities, (2) converting existing contours on reference images (e.g., MRI) into delineated volumes and adjusting the intensity within the volumes to match target images (e.g., CT) intensity distribution for enhanced similarity metric, (3) registering reference and target images using appropriate deformable registration algorithms (e.g., B-spline, demons) and generate deformed contours, (4) mapping the deformed volumes on target images, calculating mean, variance, and center of mass as the initialization parameters for consecutive fuzzy connectedness (FC) image segmentation on target images, (5) generate affinity map from FC segmentation, (6) achieving final contours by modifying the deformed contours using the affinity map with a gradient distance weighting algorithm. The tool was tested with the CT and MR images of four pancreatic cancer patients acquired at the same respiration phase to minimize motion distortion. Dice's Coefficient was calculated against direct delineation on target image. Contours generated by various methods, including rigid transfer, auto-segmentation, deformable only transfer and proposed method, were compared. Fuzzy connected image segmentation needs careful parameter initialization and user involvement. Automatic contour transfer by multi-modality deformable registration leads up to 10% of accuracy improvement over the rigid transfer. Two extra proposed steps of adjusting intensity distribution and modifying the deformed contour with affinity map improve the transfer accuracy further to 14% averagely. Deformable image registration aided by contrast adjustment and fuzzy connectedness segmentation improves the contour transfer accuracy between multi-modality images, particularly with large deformation and low image contrast. © 2012 American Association of Physicists in Medicine.

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

Context-Aware Fusion of RGB and Thermal Imagery for Traffic Monitoring

PubMed Central

Alldieck, Thiemo; Bahnsen, Chris H.; Moeslund, Thomas B.

2016-01-01

In order to enable a robust 24-h monitoring of traffic under changing environmental conditions, it is beneficial to observe the traffic scene using several sensors, preferably from different modalities. To fully benefit from multi-modal sensor output, however, one must fuse the data. This paper introduces a new approach for fusing color RGB and thermal video streams by using not only the information from the videos themselves, but also the available contextual information of a scene. The contextual information is used to judge the quality of a particular modality and guides the fusion of two parallel segmentation pipelines of the RGB and thermal video streams. The potential of the proposed context-aware fusion is demonstrated by extensive tests of quantitative and qualitative characteristics on existing and novel video datasets and benchmarked against competing approaches to multi-modal fusion. PMID:27869730

Diffusion imaging and transcranial magnetic stimulation assessment of transcallosal pathways in chronic stroke.

PubMed

Mang, Cameron S; Borich, Michael R; Brodie, Sonia M; Brown, Katlyn E; Snow, Nicholas J; Wadden, Katie P; Boyd, Lara A

2015-10-01

To examine the relationship of transcallosal pathway microstructure and transcallosal inhibition (TCI) with motor function and impairment in chronic stroke. Diffusion-weighted magnetic resonance imaging and transcranial magnetic stimulation (TMS) data were collected from 24 participants with chronic stroke and 11 healthy older individuals. Post-stroke motor function (Wolf Motor Function Test) and level of motor impairment (Fugl-Meyer score) were evaluated. Fractional anisotropy (FA) of transcallosal tracts between prefrontal cortices and the mean amplitude decrease in muscle activity during the ipsilateral silent period evoked by TMS over the non-lesioned hemisphere (termed NL-iSPmean) were significantly associated with level of motor impairment and motor function after stroke (p<0.05). A regression model including age, post-stroke duration, lesion volume, lesioned corticospinal tract FA, transcallosal prefrontal tract FA and NL-iSPmean accounted for 84% of variance in motor impairment (p<0.01). Both transcallosal prefrontal tract FA (ΔR(2)=0.12, p=0.04) and NL-iSPmean (ΔR(2)=0.09, p=0.04) accounted for unique variance in motor impairment level. Prefrontal transcallosal tract microstructure and TCI are each uniquely associated with motor impairment in chronic stroke. Utilizing a multi-modal approach to assess transcallosal pathways may improve our capacity to identify important neural substrates of motor impairment in the chronic phase of stroke. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Multi-Modal Curriculum Learning for Semi-Supervised Image Classification.

PubMed

Gong, Chen; Tao, Dacheng; Maybank, Stephen J; Liu, Wei; Kang, Guoliang; Yang, Jie

2016-07-01

Semi-supervised image classification aims to classify a large quantity of unlabeled images by typically harnessing scarce labeled images. Existing semi-supervised methods often suffer from inadequate classification accuracy when encountering difficult yet critical images, such as outliers, because they treat all unlabeled images equally and conduct classifications in an imperfectly ordered sequence. In this paper, we employ the curriculum learning methodology by investigating the difficulty of classifying every unlabeled image. The reliability and the discriminability of these unlabeled images are particularly investigated for evaluating their difficulty. As a result, an optimized image sequence is generated during the iterative propagations, and the unlabeled images are logically classified from simple to difficult. Furthermore, since images are usually characterized by multiple visual feature descriptors, we associate each kind of features with a teacher, and design a multi-modal curriculum learning (MMCL) strategy to integrate the information from different feature modalities. In each propagation, each teacher analyzes the difficulties of the currently unlabeled images from its own modality viewpoint. A consensus is subsequently reached among all the teachers, determining the currently simplest images (i.e., a curriculum), which are to be reliably classified by the multi-modal learner. This well-organized propagation process leveraging multiple teachers and one learner enables our MMCL to outperform five state-of-the-art methods on eight popular image data sets.

One-stop-shop stroke imaging with functional CT.

PubMed

Tong, Elizabeth; Komlosi, Peter; Wintermark, Max

2015-12-01

Advanced imaging techniques have extended beyond traditional anatomic imaging and progressed to dynamic, physiologic and functional imaging. Neuroimaging is no longer a mere diagnostic tool. Multimodal functional CT, comprising of NCCT, PCT and CTA, provides a one-stop-shop for rapid stroke imaging. Integrating those imaging findings with pertinent clinical information can help guide subsequent treatment decisions, medical management and follow-up imaging selection. This review article will briefly discuss the indication and utility of each modality in acute stroke imaging. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

NASA Astrophysics Data System (ADS)

Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

2018-05-01

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging

PubMed Central

Joshi, Bishnu P.; Wang, Thomas D.

2010-01-01

Cancer is one of the major causes of mortality and morbidity in our healthcare system. Molecular imaging is an emerging methodology for the early detection of cancer, guidance of therapy, and monitoring of response. The development of new instruments and exogenous molecular probes that can be labeled for multi-modality imaging is critical to this process. Today, molecular imaging is at a crossroad, and new targeted imaging agents are expected to broadly expand our ability to detect and manage cancer. This integrated imaging strategy will permit clinicians to not only localize lesions within the body but also to manage their therapy by visualizing the expression and activity of specific molecules. This information is expected to have a major impact on drug development and understanding of basic cancer biology. At this time, a number of molecular probes have been developed by conjugating various labels to affinity ligands for targeting in different imaging modalities. This review will describe the current status of exogenous molecular probes for optical, scintigraphic, MRI and ultrasound imaging platforms. Furthermore, we will also shed light on how these techniques can be used synergistically in multi-modal platforms and how these techniques are being employed in current research. PMID:22180839

Differences in Multi-Modal Ultrasound Imaging between Triple Negative and Non-Triple Negative Breast Cancer.

PubMed

Li, Ziyao; Tian, Jiawei; Wang, Xiaowei; Wang, Ying; Wang, Zhenzhen; Zhang, Lei; Jing, Hui; Wu, Tong

2016-04-01

The objective of this study was to identify multi-modal ultrasound imaging parameters that could potentially help to differentiate between triple negative breast cancer (TNBC) and non-TNBC. Conventional ultrasonography, ultrasound strain elastography and 3-D ultrasound (3-D-US) findings from 50 TNBC and 179 non-TNBC patients were retrospectively reviewed. Immunohistochemical examination was used as the reference gold standard for cancer subtyping. Different ultrasound modalities were initially analyzed to define TNBC-related features. Subsequently, logistic regression analysis was applied to TNBC-related features to establish models for predicting TNBC. TNBCs often presented as micro-lobulated, markedly hypo-echoic masses with an abrupt interface (p = 0.015, 0.0015 and 0.004, compared with non-TNBCs, respectively) on conventional ultrasound, and showed a diminished retraction pattern phenomenon in the coronal plane (p = 0.035) on 3-D-US. Our findings suggest that B-mode ultrasound and 3-D-US in multi-modality ultrasonography could be a useful non-invasive technique for differentiating TNBCs from non-TNBCs. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

Evidence-based development and first usability testing of a social serious game based multi-modal system for early screening for atypical socio-cognitive development.

PubMed

Gyori, Miklos; Borsos, Zsófia; Stefanik, Krisztina

2015-01-01

At current, screening for, and diagnosis of, autism spectrum disorders (ASD) are based on purely behavioral data; established screening tools rely on human observation and ratings of relevant behaviors. The research and development project in the focus of this paper is aimed at designing, creating and evaluating a social serious game based multi-modal, interactive software system for screening for high functioning cases of ASD at kindergarten age. The aims of this paper are (1) to summarize the evidence-based design process and (2) to present results from the first usability test of the system. Game topic, candidate responses, and candidate game contents were identified via an iterative literature review. On this basis, the 1^st partial prototype of the fully playable game has been created, with complete data recording functionality but without the decision making component. A first usability test was carried out on this prototype (n=13). Overall results were unambiguously promising. Although sporadic difficulties in, and slightly negative attitudes towards, using the game occasionally arose, these were confined to non-target-group children only. The next steps of development include (1) completing the game design; (2) carrying out first large-n field test; (3) creating the first prototype of the decision making component.

Utility of Functional Hemodynamics and Echocardiography to Aid Diagnosis and Management of Shock.

PubMed

McGee, William T; Raghunathan, Karthik; Adler, Adam C

2015-12-01

The utility of functional hemodynamics and bedside ultrasonography is increasingly recognized as advantageous for both improved diagnosis and management of shock states. In contrast to conventional "static" measures, "dynamic" hemodynamic measures and bedside imaging modalities enhance pathophysiology-based comprehensive understanding of shock states and the response to therapy. The current editions of major textbooks in the primary specialties--in which clinicians routinely encounter patients in shock--including surgery, anesthesia, emergency medicine, and internal medicine continue to incorporate traditional (conventional) descriptions of shock that use well-described (but potentially misleading) intravascular pressures to classify shock states. Reliance on such intravascular pressure measurements is not as helpful as newer "dynamic" functional measures including ultrasonography to both better assess volume responsiveness and biventricular cardiac function. This review thus emphasizes the application of current functional hemodynamics and ultrasonography to the diagnosis and management of shock as a contrast to conventional "static" pressure-based measures.

Perceptual Learning Styles Modalities Utilizing the Multimodal Paired Associates Learning Test: An Analysis of Latinos Born in Central and South America

ERIC Educational Resources Information Center

Ramirez, Matias

2017-01-01

Businesses and Human Resources professionals face the ongoing challenge of continuously upskilling and developing employees. Changes to processes or procedures, changes in technology, changes in job functions, and updates or changes to compliance laws or regulations are all reasons that employees must attend and complete employer-developed…

Design, Simulation, Fabrication and Testing of a Bio-Inspired Amphibious Robot with Multiple Modes of Mobility

DTIC Science & Technology

2012-01-01

performance. Ob- stacle climbing using the tail is compared to results from a previous robot with a posterior body segment and body flexion joint. Actual...3. Mechanisms of Locomotion for Multi-Modal Mobility 3.1. Gate and Tail Design Demands of multi-modal locomotion motivated a quadruped design for...tail instead of a rear body segment simplifies waterproofing design requirements and adds stability both on land and in water. This new morphology is

Percolated microstructures for multi-modal transport enhancement in porous active materials

DOEpatents

McKay, Ian Salmon; Yang, Sungwoo; Wang, Evelyn N.; Kim, Hyunho

2018-03-13

A method of forming a composite material for use in multi-modal transport includes providing three-dimensional graphene having hollow channels, enabling a polymer to wick into the hollow channels of the three-dimensional graphene, curing the polymer to form a cured three-dimensional graphene, adding an active material to the cured three-dimensional graphene to form a composite material, and removing the polymer from within the hollow channels. A composite material formed according to the method is also provided.

Brain Imaging in Alzheimer Disease

PubMed Central

Johnson, Keith A.; Fox, Nick C.; Sperling, Reisa A.; Klunk, William E.

2012-01-01

Imaging has played a variety of roles in the study of Alzheimer disease (AD) over the past four decades. Initially, computed tomography (CT) and then magnetic resonance imaging (MRI) were used diagnostically to rule out other causes of dementia. More recently, a variety of imaging modalities including structural and functional MRI and positron emission tomography (PET) studies of cerebral metabolism with fluoro-deoxy-d-glucose (FDG) and amyloid tracers such as Pittsburgh Compound-B (PiB) have shown characteristic changes in the brains of patients with AD, and in prodromal and even presymptomatic states that can help rule-in the AD pathophysiological process. No one imaging modality can serve all purposes as each have unique strengths and weaknesses. These modalities and their particular utilities are discussed in this article. The challenge for the future will be to combine imaging biomarkers to most efficiently facilitate diagnosis, disease staging, and, most importantly, development of effective disease-modifying therapies. PMID:22474610

a Unified Matrix Polynomial Approach to Modal Identification

NASA Astrophysics Data System (ADS)

Allemang, R. J.; Brown, D. L.

1998-04-01

One important current focus of modal identification is a reformulation of modal parameter estimation algorithms into a single, consistent mathematical formulation with a corresponding set of definitions and unifying concepts. Particularly, a matrix polynomial approach is used to unify the presentation with respect to current algorithms such as the least-squares complex exponential (LSCE), the polyreference time domain (PTD), Ibrahim time domain (ITD), eigensystem realization algorithm (ERA), rational fraction polynomial (RFP), polyreference frequency domain (PFD) and the complex mode indication function (CMIF) methods. Using this unified matrix polynomial approach (UMPA) allows a discussion of the similarities and differences of the commonly used methods. the use of least squares (LS), total least squares (TLS), double least squares (DLS) and singular value decomposition (SVD) methods is discussed in order to take advantage of redundant measurement data. Eigenvalue and SVD transformation methods are utilized to reduce the effective size of the resulting eigenvalue-eigenvector problem as well.

A new strategy for TiO2 whiskers mediated multi-mode cancer treatment

NASA Astrophysics Data System (ADS)

Xu, Peipei; Wang, Ruju; Ouyang, Jian; Chen, Bing

2015-02-01

Traditional Chinese medicine (TCM) which functions as chemotherapeutic or adjuvantly chemotherapeutic agents has been drawing a great many eyeballs for its easy obtain and significant antitumor effects accompanied with less toxic and side effects. PDT (photodynamic therapy) utilizes the fact that certain compounds coined as photosensitizers, when exposed to light of a specific wavelength, are capable of generating cytotoxic reactive oxygen species (ROS) such as hydroxyl radical, hydrogen peroxide, and superoxide to kill cancer cells. Combinations of cancer therapeutic modalities are studied to improve the efficacy of treatment. This study aimed to explore a new strategy of coupling of titanium dioxide whiskers (TiO2 Ws) with the anticancer drug gambogic acid (GA) in photodynamic therapy. The nanocomposites were coined as GA-TiO2. The combination of TiO2 Ws with GA induced a remarkable enhancement in antitumor activity estimated by MTT assay, nuclear DAPI staining, and flow cytometry. Furthermore, the possible signaling pathway was explored by reverse transcription polymerase chain reaction (RT-PCR) and Western blot assay. These results identify TiO2 Ws of good biocompatibility and photocatalytic activity. In human leukemia cells (K562 cells), TiO2 Ws could obviously increase the intracellular concentration of GA and enhance its potential antitumor efficiency, suggesting that TiO2 Ws could act as an efficient drug delivery carrier targeting GA to carcinoma cells. Moreover, photodynamic GA-TiO2 nanocomposites could induce an evident reinforcement in antitumor activity with UV illumination. These results reveal that such modality combinations put forward a promising proposal in cancer therapy.

Inferring multi-scale neural mechanisms with brain network modelling

PubMed Central

Schirner, Michael; McIntosh, Anthony Randal; Jirsa, Viktor; Deco, Gustavo

2018-01-01

The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies. PMID:29308767

Social functioning and socioeconomic changes after introduction of regular dialysis treatment and impact of dialysis modality: a multi-centre survey of Japanese patients.

PubMed

Nakayama, Masaaki; Ishida, Mari; Ogihara, Masahiko; Hanaoka, Kazushige; Tamura, Masahito; Kanai, Hidetoshi; Tonozuka, Yukio; Marshall, Mark R

2015-08-01

Patient socialization and preservation of socioeconomic status are important patient-centred outcomes for those who start dialysis, and retention of employment is a key enabler. This study examined the influence of dialysis inception and modality upon these outcomes in a contemporary Japanese cohort. We conducted a survey of prevalent chronic dialysis patients from 5 dialysis centres in Japan. All patients who had been on peritoneal dialysis (PD) since dialysis inception were recruited, and matched with a sample of those on in-centre haemodialysis (ICHD). We assessed patients' current social functioning (Short Form 36 Health Survey), and evaluated changes to patient employment status, annual income, and general health condition from the pre-dialysis period to the current time. A total of 179 patients were studied (102 PD and 77 ICHD). There were no differences in social functioning by modality. Among them, 113 were employed in the pre-dialysis period with no difference by modality. Of these, 22% became unemployed after dialysis inception, with a corresponding decline in average working hours and annual income. The odds of unemployment after dialysis inception were 5.02 fold higher in those on ICHD compared to those on PD, after adjustment for covariates. There were no changes for those who were already unemployed in the pre-dialysis period. Employment status is significantly hampered by dialysis inception, although PD was associated with superior retention of employment and greater income compared to ICHD. This supports a positive role for PD in preservation of socioeconomic status and potentially other patient-centred outcomes. © 2015 Asian Pacific Society of Nephrology.

Using online modules is a multi-modality teaching system: a high-touch high-tech approach to geriatric education.

PubMed

Gainor, Sara Jane; Goins, R Turner; Miller, Lee Ann

2004-01-01

Making geriatric education available to rural faculty/preceptors, students, and practitioners presents many challenges. Often the only options considered for educating those in the health professions about geriatrics are either traditional face-to-face courses or distance education programs. The purpose of this paper was to examine the use of Web-based modules or courses and other distance learning technology in concert with traditional learning modalities. The Mountain State Geriatric Education Center explored the use of a multi-modal approach within a high-touch, high-tech framework. Our findings indicate the following: it is important to start where participants are ready to begin; flexibility and variety are needed; soliciting evaluative feedback from participants is valuable; there is a need to integrate distance learning with more traditional modalities; and a high-tech, high-touch approach provides a format which participants find acceptable, accessible, and attractive. This assertion does not rule out the use of technology for distance education but rather encourages educators to take advantage of a wide range of modalities, traditional and technological, to reach rural practitioners, faculty, and students.

Outreach in the Delivery of Mental Health Services to Hispanic Elders.

ERIC Educational Resources Information Center

Szapocznik, Jose; And Others

1979-01-01

The study investigated the effectiveness of two outreach/education modalities established to increase the utilization of mental health services by Hispanic elders: (1) a service delivery modality, and (2) a mass media modality. (NQ)

Manual physical therapy combined with high-intensity functional rehabilitation for severe lower extremity musculoskeletal injuries: a case series*

PubMed Central

Crowell, Michael S.; Deyle, Gail D.; Owens, Johnny; Gill, Norman W.

2016-01-01

Objectives Severe lower extremity trauma accounts for large healthcare costs and often results in elective amputation and poor long-term outcomes. The purpose of this case series is to describe an orthopedic manual physical therapy (OMPT) approach combined with a return to run (RTR) clinical pathway consisting of high-intensity functional rehabilitation with a custom energy-storing orthosis. Methods Three consecutive male patients, aged 21–23 years, with severe lower extremity musculoskeletal injuries were treated with a combined intervention that included a mean (SD) of 12 (2·1) OMPT sessions and 24 (8·7) functional rehabilitation sessions over a mean of 6 weeks (1·0). Additional training with a custom energy-storing orthosis consisted of a mean of 15 (1·2) additional sessions over 4 weeks. Patient self-report outcome measures and a variety of physical performance tests captured change in function. Results Baseline lower extremity functional scale (LEFS) and foot and ankle ability measure activities of daily living subscale (FAAM-ADL) scores indicated severe disability. All patients exceeded the minimal clinically important difference (MCID) in at least one self-report outcome or physical performance test without a brace. Two of three patients exceeded the MCID for at least two physical performance tests after training with and utilizing a custom energy-storing orthosis. Discussion Clinically meaningful changes in self-reported function or physical performance were observed in all patients. A multi-modal approach, including manual therapy and functional exercise, may address the entire spectrum of impairments in patients with severe lower extremity trauma, resulting in improvements in both braced and un-braced function. PMID:27252581

Partnering for transportation safety : human-centered systems : operator fatigue management conference

DOT National Transportation Integrated Search

2000-01-01

This Conference was intended to enlist support for, and participation in, a new multi-modal DOT safety initiative. This initiative builds on the modal agency programs within DOT to develop techniques that transportation operating companies can employ...

Multi-Modal Traveler Information System - VMS/HAR State-of-the-Practice

DOT National Transportation Integrated Search

1997-05-30

The Gary-Chicago-Milwaukee (GCM) Corridor is one of the four "Priority Corridors" established by the United States Congress in the Inter-Modal Surface Transportation Efficiency Act (ISTEA). These corridors have been selected for special federal trans...

Failure Analysis of a Complex Learning Framework Incorporating Multi-Modal and Semi-Supervised Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pullum, Laura L; Symons, Christopher T

2011-01-01

Machine learning is used in many applications, from machine vision to speech recognition to decision support systems, and is used to test applications. However, though much has been done to evaluate the performance of machine learning algorithms, little has been done to verify the algorithms or examine their failure modes. Moreover, complex learning frameworks often require stepping beyond black box evaluation to distinguish between errors based on natural limits on learning and errors that arise from mistakes in implementation. We present a conceptual architecture, failure model and taxonomy, and failure modes and effects analysis (FMEA) of a semi-supervised, multi-modal learningmore » system, and provide specific examples from its use in a radiological analysis assistant system. The goal of the research described in this paper is to provide a foundation from which dependability analysis of systems using semi-supervised, multi-modal learning can be conducted. The methods presented provide a first step towards that overall goal.« less

Right ventricular functional analysis utilizing first pass radionuclide angiography for pre-operative ventricular assist device planning: a multi-modality comparison.

PubMed

Avery, Ryan; Day, Kevin; Jokerst, Clinton; Kazui, Toshinobu; Krupinski, Elizabeth; Khalpey, Zain

2017-10-10

Advanced heart failure treated with a left ventricular assist device is associated with a higher risk of right heart failure. Many advanced heart failures patients are treated with an ICD, a relative contraindication to MRI, prior to assist device placement. Given this limitation, left and right ventricular function for patients with an ICD is calculated using radionuclide angiography utilizing planar multigated acquisition (MUGA) and first pass radionuclide angiography (FPRNA), respectively. Given the availability of MRI protocols that can accommodate patients with ICDs, we have correlated the findings of ventricular functional analysis using radionuclide angiography to cardiac MRI, the reference standard for ventricle function calculation, to directly correlate calculated ejection fractions between these modalities, and to also assess agreement between available echocardiographic and hemodynamic parameters of right ventricular function. A retrospective review from January 2012 through May 2014 was performed to identify advanced heart failure patients who underwent both cardiac MRI and radionuclide angiography for ventricular functional analysis. Nine heart failure patients (8 men, 1 woman; mean age of 57.0 years) were identified. The average time between the cardiac MRI and radionuclide angiography exams was 38.9 days (range: 1 - 119 days). All patients undergoing cardiac MRI were scanned using an institutionally approved protocol for ICD with no device-related complications identified. A retrospective chart review of each patient for cardiomyopathy diagnosis, clinical follow-up, and echocardiogram and right heart catheterization performed during evaluation was also performed. The 9 patients demonstrated a mean left ventricular ejection fraction (LVEF) using cardiac MRI of 20.7% (12 - 40%). Mean LVEF using MUGA was 22.6% (12 - 49%). The mean right ventricular ejection fraction (RVEF) utilizing cardiac MRI was 28.3% (16 - 43%), and the mean RVEF calculated by FPRNA was 32.6% (9 - 56%). The mean discrepancy for LVEF between cardiac MRI and MUGA was 4.1% (0 - 9%), and correlation of calculated LVEF using cardiac MRI and MUGA demonstrated an R of 0.9. The mean discrepancy for RVEF between cardiac MRI and FPRNA was 12.0% (range: 2 - 24%) with a moderate correlation (R = 0.5). The increased discrepancies for RV analysis were statistically significant using an unpaired t-test (t = 3.19, p = 0.0061). Echocardiogram parameters of RV function, including TAPSE and FAC, were for available for all 9 patients and agreement with cardiac MRI demonstrated a kappa statistic for TAPSE of 0.39 (95% CI of 0.06 - 0.72) and for FAC of 0.64 (95% of 0.21 - 1.00). Heart failure patients are increasingly requiring left ventricular assist device placement; however, definitive evaluation of biventricular function is required due to the increased mortality rate associated with right heart failure after assist device placement. Our results suggest that FPRNA only has a moderate correlation with reference standard RVEFs calculated using cardiac MRI, which was similar to calculated agreements between cardiac MRI and echocardiographic parameters of right ventricular function. Given the need for identification of patients at risk for right heart failure, further studies are warranted to determine a more accurate estimate of RVEF for heart failure patients during pre-operative ventricular assist device planning.

Structural changes in socio-affective networks: Multi-modal MRI findings in long-term meditation practitioners.

PubMed

Engen, Haakon G; Bernhardt, Boris C; Skottnik, Leon; Ricard, Matthieu; Singer, Tania

2017-08-31

Our goal was to assess the effects of long-term mental training in socio-affective skills on structural brain networks. We studied a group of long-term meditation practitioners (LTMs) who have focused on cultivating socio-affective skills using loving-kindness and compassion meditation for an average of 40k h, comparing these to meditation-naïve controls. To maximize homogeneity of prior practice, LTMs were included only if they had undergone extensive full-time meditation retreats in the same center. MRI-based cortical thickness analysis revealed increased thickness in the LTM cohort relative to meditation-native controls in fronto-insular cortices. To identify functional networks relevant for the generation of socio-affective states, structural imaging analysis were complemented by fMRI analysis in LTMs, showing amplitude increases during a loving-kindness meditation session relative to non-meditative rest in multiple prefrontal and insular regions bilaterally. Importantly, functional findings partially overlapped with regions of cortical thickness increases in the left ventrolateral prefrontal cortex and anterior insula, suggesting that these regions may play a central role in the generation of emotional states relevant for the meditative practice. Our multi-modal MRI approach revealed structural changes in LTMs who have cultivated loving-kindness and compassion for a significant period of their life in functional networks activated by these practices. These preliminary cross-sectional findings motivate future longitudinal work studying brain plasticity following the regular practice of skills aiming at enhancing human altruism and prosocial motivation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brain Structure and Function Associated with a History of Sport Concussion: A Multi-Modal Magnetic Resonance Imaging Study.

PubMed

Churchill, Nathan; Hutchison, Michael; Richards, Doug; Leung, General; Graham, Simon; Schweizer, Tom A

2017-02-15

There is growing concern about the potential long-term consequences of sport concussion for young, currently active athletes. However, there remains limited information about brain abnormalities associated with a history of concussion and how they relate to clinical factors. In this study, advanced MRI was used to comprehensively describe abnormalities in brain structure and function associated with a history of sport concussion. Forty-three athletes (21 male, 22 female) were recruited from interuniversity teams at the beginning of the season, including 21 with a history of concussion and 22 without prior concussion; both groups also contained a balanced sample of contact and noncontact sports. Multi-modal MRI was used to evaluate abnormalities in brain structure and function. Athletes with a history of concussion showed frontal decreases in brain volume and blood flow. However, they also demonstrated increased posterior cortical volume and elevated markers of white matter microstructure. A greater number of prior concussions was associated with more extensive decreases in cerebral blood flow and insular volume, whereas recovery time from most recent concussion was correlated with reduced frontotemporal volume. White matter showed limited correlations with clinical factors, predominantly in the anterior corona radiata. This study provides the first evidence of the long-term effects of concussion on gray matter volume, blood flow, and white matter microstructure within a single athlete cohort. This was examined for a mixture of male and female athletes in both contact and noncontact sports, demonstrating the relevance of these findings for the overall sporting community.

Multi-modal image registration: matching MRI with histology

NASA Astrophysics Data System (ADS)

Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

2010-03-01

Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

Hand hygiene and healthcare system change within multi-modal promotion: a narrative review.

PubMed

Allegranzi, B; Sax, H; Pittet, D

2013-02-01

Many factors may influence the level of compliance with hand hygiene recommendations by healthcare workers. Lack of products and facilities as well as their inappropriate and non-ergonomic location represent important barriers. Targeted actions aimed at making hand hygiene practices feasible during healthcare delivery by ensuring that the necessary infrastructure is in place, defined as 'system change', are essential to improve hand hygiene in healthcare. In particular, access to alcohol-based hand rubs (AHRs) enables appropriate and timely hand hygiene performance at the point of care. The feasibility and impact of system change within multi-modal strategies have been demonstrated both at institutional level and on a large scale. The introduction of AHRs overcomes some important barriers to best hand hygiene practices and is associated with higher compliance, especially when integrated within multi-modal strategies. Several studies demonstrated the association between AHR consumption and reduction in healthcare-associated infection, in particular, meticillin-resistant Staphylococcus aureus bacteraemia. Recent reports demonstrate the feasibility and success of system change implementation on a large scale. The World Health Organization and other investigators have reported the challenges and encouraging results of implementing hand hygiene improvement strategies, including AHR introduction, in settings with limited resources. This review summarizes the available evidence demonstrating the need for system change and its importance within multi-modal hand hygiene improvement strategies. This topic is also discussed in a global perspective and highlights some controversial issues. Copyright © 2013 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Imaging the hard/soft tissue interface.

PubMed

Bannerman, Alistair; Paxton, Jennifer Z; Grover, Liam M

2014-03-01

Interfaces between different tissues play an essential role in the biomechanics of native tissues and their recapitulation is now recognized as critical to function. As a consequence, imaging the hard/soft tissue interface has become increasingly important in the area of tissue engineering. Particularly as several biotechnology based products have made it onto the market or are close to human trials and an understanding of their function and development is essential. A range of imaging modalities have been developed that allow a wealth of information on the morphological and physical properties of samples to be obtained non-destructively in vivo or via destructive means. This review summarizes the use of a selection of imaging modalities on interfaces to date considering the strengths and weaknesses of each. We will also consider techniques which have not yet been utilized to their full potential or are likely to play a role in future work in the area.

[Guidelines for wise utilization of knee imaging].

PubMed

Finestone, Aharon S; Eshed, Iris; Freedman, Yehuda; Beer, Yiftah; Bar-Sever, Zvi; Kots, Yavvgeni; Adar, Eliyahu; Mann, Gideon

2012-02-01

The knee is a complex structure afflicted with diverse pathologies. Correct management of knee complaints demands wise utilization of imaging modalities, considering their accuracy in the specific clinical situation, the patient's safety and availability and financial issues. Some of these considerations are universal, while others are local, depending on medical and insurance systems. There is controversy and unclearness regarding the best imaging modality in different clinical situations. To develop clinical guidelines for utilizing knee imaging. Leading physicians in specialties associated with knee disease and imaging were invited to participate in a panel on the guidelines. Controversies were settled in the main panel or in sub-panels. The panel agreed on the principles in choosing from the various modalities, primarily medical accuracy, followed by patient safety, availability and cost. There was agreement that the physician is responsible to choose the most appropriate diagnostic tool, consulting, when necessary, on the advantages, limitations and risks of the various imaging modalities. A comprehensive table was compiled with the importance of the different imaging modalities in various clinical situations. For the first time, Israeli guidelines on wise utilization of knee imaging are presented. They take into consideration the clinical situations and also availability and financial issues specific to Israel. These guidelines will serve physicians of several disciplines and medical insurers to improve patient management efficiently.

Sociodemographic correlates of cognition in the multi-ethnic study of atherosclerosis (MESA)

USDA-ARS?s Scientific Manuscript database

Our objective was to describe the methodology utilized to evaluate cognitive function in the Multi-Ethnic Study of Atherosclerosis (MESA) and to present preliminary results by age, sex, and race/ethnicity. Cross-sectional measurements of a prospective observational cohort. Residents of 6 U.S. commun...

Robust Transient Dynamics and Brain Functions

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo

2011-01-01

In the last few decades several concepts of dynamical systems theory (DST) have guided psychologists, cognitive scientists, and neuroscientists to rethink about sensory motor behavior and embodied cognition. A critical step in the progress of DST application to the brain (supported by modern methods of brain imaging and multi-electrode recording techniques) has been the transfer of its initial success in motor behavior to mental function, i.e., perception, emotion, and cognition. Open questions from research in genetics, ecology, brain sciences, etc., have changed DST itself and lead to the discovery of a new dynamical phenomenon, i.e., reproducible and robust transients that are at the same time sensitive to informational signals. The goal of this review is to describe a new mathematical framework – heteroclinic sequential dynamics – to understand self-organized activity in the brain that can explain certain aspects of robust itinerant behavior. Specifically, we discuss a hierarchy of coarse-grain models of mental dynamics in the form of kinetic equations of modes. These modes compete for resources at three levels: (i) within the same modality, (ii) among different modalities from the same family (like perception), and (iii) among modalities from different families (like emotion and cognition). The analysis of the conditions for robustness, i.e., the structural stability of transient (sequential) dynamics, give us the possibility to explain phenomena like the finite capacity of our sequential working memory – a vital cognitive function –, and to find specific dynamical signatures – different kinds of instabilities – of several brain functions and mental diseases. PMID:21716642

Comparative study of probability distribution distances to define a metric for the stability of multi-source biomedical research data.

PubMed

Sáez, Carlos; Robles, Montserrat; García-Gómez, Juan Miguel

2013-01-01

Research biobanks are often composed by data from multiple sources. In some cases, these different subsets of data may present dissimilarities among their probability density functions (PDF) due to spatial shifts. This, may lead to wrong hypothesis when treating the data as a whole. Also, the overall quality of the data is diminished. With the purpose of developing a generic and comparable metric to assess the stability of multi-source datasets, we have studied the applicability and behaviour of several PDF distances over shifts on different conditions (such as uni- and multivariate, different types of variable, and multi-modality) which may appear in real biomedical data. From the studied distances, we found information-theoretic based and Earth Mover's Distance to be the most practical distances for most conditions. We discuss the properties and usefulness of each distance according to the possible requirements of a general stability metric.

CISUS: an integrated 3D ultrasound system for IGT using a modular tracking API

NASA Astrophysics Data System (ADS)

Boctor, Emad M.; Viswanathan, Anand; Pieper, Steve; Choti, Michael A.; Taylor, Russell H.; Kikinis, Ron; Fichtinger, Gabor

2004-05-01

Ultrasound has become popular in clinical/surgical applications, both as the primary image guidance modality and also in conjunction with other modalities like CT or MRI. Three dimensional ultrasound (3DUS) systems have also demonstrated usefulness in image-guided therapy (IGT). At the same time, however, current lack of open-source and open-architecture multi-modal medical visualization systems prevents 3DUS from fulfilling its potential. Several stand-alone 3DUS systems, like Stradx or In-Vivo exist today. Although these systems have been found to be useful in real clinical setting, it is difficult to augment their functionality and integrate them in versatile IGT systems. To address these limitations, a robotic/freehand 3DUS open environment (CISUS) is being integrated into the 3D Slicer, an open-source research tool developed for medical image analysis and surgical planning. In addition, the system capitalizes on generic application programming interfaces (APIs) for tracking devices and robotic control. The resulting platform-independent open-source system may serve as a valuable tool to the image guided surgery community. Other researchers could straightforwardly integrate the generic CISUS system along with other functionalities (i.e. dual view visualization, registration, real-time tracking, segmentation, etc) to rapidly create their medical/surgical applications. Our current driving clinical application is robotically assisted and freehand 3DUS-guided liver ablation, which is fully being integrated under the CISUS-3D Slicer. Initial functionality and pre-clinical feasibility are demonstrated on phantom and ex-vivo animal models.

Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks

NASA Astrophysics Data System (ADS)

Audebert, Nicolas; Le Saux, Bertrand; Lefèvre, Sébastien

2018-06-01

In this work, we investigate various methods to deal with semantic labeling of very high resolution multi-modal remote sensing data. Especially, we study how deep fully convolutional networks can be adapted to deal with multi-modal and multi-scale remote sensing data for semantic labeling. Our contributions are threefold: (a) we present an efficient multi-scale approach to leverage both a large spatial context and the high resolution data, (b) we investigate early and late fusion of Lidar and multispectral data, (c) we validate our methods on two public datasets with state-of-the-art results. Our results indicate that late fusion make it possible to recover errors steaming from ambiguous data, while early fusion allows for better joint-feature learning but at the cost of higher sensitivity to missing data.

Initial Investigation of preclinical integrated SPECT and MR imaging.

PubMed

Hamamura, Mark J; Ha, Seunghoon; Roeck, Werner W; Wagenaar, Douglas J; Meier, Dirk; Patt, Bradley E; Nalcioglu, Orhan

2010-02-01

Single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high-spatial resolution anatomical information as well as complementary functional information. In this study, we utilized a dual modality SPECT/MRI (MRSPECT) system to investigate the integration of SPECT and MRI for improved image accuracy. The MRSPECT system consisted of a cadmium-zinc-telluride (CZT) nuclear radiation detector interfaced with a specialized radiofrequency (RF) coil that was placed within a whole-body 4 T MRI system. The importance of proper corrections for non-uniform detector sensitivity and Lorentz force effects was demonstrated. MRI data were utilized for attenuation correction (AC) of the nuclear projection data and optimized Wiener filtering of the SPECT reconstruction for improved image accuracy. Finally, simultaneous dual-imaging of a nude mouse was performed to demonstrated the utility of co-registration for accurate localization of a radioactive source.

Initial Investigation of Preclinical Integrated SPECT and MR Imaging

PubMed Central

Hamamura, Mark J.; Ha, Seunghoon; Roeck, Werner W.; Wagenaar, Douglas J.; Meier, Dirk; Patt, Bradley E.; Nalcioglu, Orhan

2014-01-01

Single-photon emission computed tomography (SPECT) can provide specific functional information while magnetic resonance imaging (MRI) can provide high-spatial resolution anatomical information as well as complementary functional information. In this study, we utilized a dual modality SPECT/MRI (MRSPECT) system to investigate the integration of SPECT and MRI for improved image accuracy. The MRSPECT system consisted of a cadmium-zinc-telluride (CZT) nuclear radiation detector interfaced with a specialized radiofrequency (RF) coil that was placed within a whole-body 4 T MRI system. The importance of proper corrections for non-uniform detector sensitivity and Lorentz force effects was demonstrated. MRI data were utilized for attenuation correction (AC) of the nuclear projection data and optimized Wiener filtering of the SPECT reconstruction for improved image accuracy. Finally, simultaneous dual-imaging of a nude mouse was performed to demonstrated the utility of co-registration for accurate localization of a radioactive source. PMID:20082527

Pancreatic tissue assessment using fluorescence and reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Chandra, Malavika; Heidt, David; Simeone, Diane; McKenna, Barbara; Scheiman, James; Mycek, Mary-Ann

2007-07-01

The ability of multi-modal optical spectroscopy to detect signals from pancreatic tissue was demonstrated by studying human pancreatic cancer xenografts in mice and freshly excised human pancreatic tumor tissue. Measured optical spectra and fluorescence decays were correlated with tissue morphological and biochemical properties. The measured spectral features and decay times correlated well with expected pathological differences in normal, pancreatitis and adenocarcinoma tissue states. The observed differences between the fluorescence and reflectance properties of normal, pancreatitis and adenocarcinoma tissue indicate a possible application of multi-modal optical spectroscopy to differentiating between the three tissue classifications.

Multispectral scanning laser ophthalmoscopy combined with optical coherence tomography for simultaneous in vivo mouse retinal imaging

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Zam, Azhar; Jian, Yifan; Wang, Xinlei; Burns, Marie E.; Sarunic, Marinko V.; Pugh, Edward N.; Zawadzki, Robert J.

2015-03-01

A compact, non-invasive multi-modal system has been developed for in vivo mouse retina imaging. It is configured for simultaneously detecting green and red fluorescent protein signals with scanning laser ophthalmoscopy (SLO) back-scattered light from the SLO illumination beam, and depth information about different retinal layers by means of Optical Coherence Tomography (OCT). Simultaneous assessment of retinal characteristics with different modalities can provide a wealth of information about the structural and functional changes in the retinal neural tissue and chorio-retinal vasculature in vivo. Additionally, simultaneous acquisition of multiple channels facilitates analysis of the data of different modalities by automatic temporal and structural co-registration. As an example of the instrument's performance we imaged the retina of a mouse with constitutive expression of GFP in microglia cells (Cx3cr1GFP/+), and which also expressed the red fluorescent protein mCherry in Müller glial cells by means of adeno-associated virus delivery (AAV2) of an mCherry cDNA driven by the GFAP (glial fibrillary acid protein) promoter.

Sensor-agnostic photogrammetric image registration with applications to population modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Devin A; Moehl, Jessica J

2016-01-01

Photogrammetric registration of airborne and spaceborne imagery is a crucial prerequisite to many data fusion tasks. While embedded sensor models provide a rough geolocation estimate, these metadata may be incomplete or imprecise. Manual solutions are appropriate for small-scale projects, but for rapid streams of cross-modal, multi-sensor, multi-temporal imagery with varying metadata standards, an automated approach is required. We present a high-performance image registration workflow to address this need. This paper outlines the core development concepts and demonstrates its utility with respect to the 2016 data fusion contest imagery. In particular, Iris ultra-HD video is georeferenced to the Earth surface viamore » registration to DEIMOS-2 imagery, which serves as a trusted control source. Geolocation provides opportunity to augment the video with spatial context, stereo-derived disparity, spectral sensitivity, change detection, and numerous ancillary geospatial layers. We conclude by leveraging these derivative data layers towards one such fusion application: population distribution modeling.« less

Coupled auralization and virtual video for immersive multimedia displays

NASA Astrophysics Data System (ADS)

Henderson, Paul D.; Torres, Rendell R.; Shimizu, Yasushi; Radke, Richard; Lonsway, Brian

2003-04-01

The implementation of maximally-immersive interactive multimedia in exhibit spaces requires not only the presentation of realistic visual imagery but also the creation of a perceptually accurate aural experience. While conventional implementations treat audio and video problems as essentially independent, this research seeks to couple the visual sensory information with dynamic auralization in order to enhance perceptual accuracy. An implemented system has been developed for integrating accurate auralizations with virtual video techniques for both interactive presentation and multi-way communication. The current system utilizes a multi-channel loudspeaker array and real-time signal processing techniques for synthesizing the direct sound, early reflections, and reverberant field excited by a moving sound source whose path may be interactively defined in real-time or derived from coupled video tracking data. In this implementation, any virtual acoustic environment may be synthesized and presented in a perceptually-accurate fashion to many participants over a large listening and viewing area. Subject tests support the hypothesis that the cross-modal coupling of aural and visual displays significantly affects perceptual localization accuracy.

Human factors evaluation of the effectiveness of multi-modality displays in advanced traveler information systems

DOT National Transportation Integrated Search

1999-12-01

To achieve the goals for Advanced Traveler Information Systems (ATIS), significant information will necessarily be provided to the driver. A primary ATIS design issue is the display modality (i.e., visual, auditory, or the combination) selected for p...

Novel minimally invasive multi-modality monitoring modalities in neurocritical care.

PubMed

Al-Mufti, Fawaz; Smith, Brendan; Lander, Megan; Damodara, Nitesh; Nuoman, Rolla; El-Ghanem, Mohammad; Kamal, Naveed; Al-Marsoummi, Sarmad; Alzubaidi, Basim; Nuoaman, Halla; Foreman, Brandon; Amuluru, Krishna; Gandhi, Chirag D

2018-07-15

Elevated intracranial pressure (ICP) following brain injury contributes to poor outcomes for patients, primarily by reducing the caliber of cerebral vasculature, and thereby reducing cerebral blood flow. Careful monitoring of ICP is critical in these patients in order to determine prognosis, implement treatment when ICP becomes elevated, and to judge responsiveness to treatment. Currently, the gold standard for monitoring is invasive pressure transducers, usually an intraventricular monitor, which presents significant risk of infection and hemorrhage. These risks made discovering non-invasive methods for monitoring ICP and cerebral perfusion a priority for researchers. Herein we sought to review recent publications on novel minimally invasive multi-modality monitoring techniques that provide surrogate data on ICP, cerebral oxygenation, metabolism and blood flow. While limitations in various forms preclude them from supplanting the use of invasive monitors, these modalities represent useful screening tools within our armamentarium that may be invaluable when the risks of invasive monitoring outweigh the associated benefits. Copyright © 2018 Elsevier B.V. All rights reserved.

Bi-orthogonality relations for fluid-filled elastic cylindrical shells: Theory, generalisations and application to construct tailored Green's matrices

NASA Astrophysics Data System (ADS)

Ledet, Lasse S.; Sorokin, Sergey V.

2018-03-01

The paper addresses the classical problem of time-harmonic forced vibrations of a fluid-filled cylindrical shell considered as a multi-modal waveguide carrying infinitely many waves. The forced vibration problem is solved using tailored Green's matrices formulated in terms of eigenfunction expansions. The formulation of Green's matrix is based on special (bi-)orthogonality relations between the eigenfunctions, which are derived here for the fluid-filled shell. Further, the relations are generalised to any multi-modal symmetric waveguide. Using the orthogonality relations the transcendental equation system is converted into algebraic modal equations that can be solved analytically. Upon formulation of Green's matrices the solution space is studied in terms of completeness and convergence (uniformity and rate). Special features and findings exposed only through this modal decomposition method are elaborated and the physical interpretation of the bi-orthogonality relation is discussed in relation to the total energy flow which leads to derivation of simplified equations for the energy flow components.

Sudden neurologic deficit.

PubMed

Kellogg, Marissa; Liang, Conrad W; Liebeskind, David S

2016-01-01

Clinicians treating sudden neurologic deficit are being faced with an increasing number of available imaging modalities. In this chapter we discuss a general approach to acute neuroimaging and weigh the considerations that determine which modality or modalities should be utilized. © 2016 Elsevier B.V. All rights reserved.

Comparative Investigation on Modal analysis of LM25 Aluminium alloy with other Aluminim alloys using Finite element analysis software

NASA Astrophysics Data System (ADS)

Arunkumar, S.; Baskaralal, V. P. M.; Muthuraman, V.

2017-03-01

The rudimentary steps of the modal analysis and simulation are carried out. The modal analysis is carried out on the different Aluminum Alloys cantilever beam. The cantilever beam is designed in the graphical environment of the ANSYS. The cantilever beam was fine-tuned on one end with all degree of liberation on this end were taken, beam cannot move and rotate. Mode shapes and natural frequencies are premeditated in platforms ANSYS with arithmetical formulation of the direct solver including the block Lanczos method. Aluminum alloys are widely utilized in much application due to their estimable weight to vigor property. Many examination works have been distributed out to make developments the mechanical properties of aluminum alloys. The composition of alloying elements plays a consequential role in deciding the properties of an alloy. In this study a numerical analysis implement i.e., finite element analysis (FEA) is utilized. The work obtainable in this paper is aimed at the study of effect of modal analysis of different aluminum alloys. The modeling and analysis is carried out utilizing ANSYS FEA software. A modal analysis is carried out to understand the modes of frequency demeanor of the material considered. The modal analysis play a vital role in the design of components subjected to high vibration.

TACT: A Set of MSC/PATRAN- and MSC/NASTRAN- based Modal Correlation Tools

NASA Technical Reports Server (NTRS)

Marlowe, Jill M.; Dixon, Genevieve D.

1998-01-01

This paper describes the functionality and demonstrates the utility of the Test Analysis Correlation Tools (TACT), a suite of MSC/PATRAN Command Language (PCL) tools which automate the process of correlating finite element models to modal survey test data. The initial release of TACT provides a basic yet complete set of tools for performing correlation totally inside the PATRAN/NASTRAN environment. Features include a step-by-step menu structure, pre-test accelerometer set evaluation and selection, analysis and test result export/import in Universal File Format, calculation of frequency percent difference and cross-orthogonality correlation results using NASTRAN, creation and manipulation of mode pairs, and five different ways of viewing synchronized animations of analysis and test modal results. For the PATRAN-based analyst, TACT eliminates the repetitive, time-consuming and error-prone steps associated with transferring finite element data to a third-party modal correlation package, which allows the analyst to spend more time on the more challenging task of model updating. The usefulness of this software is presented using a case history, the correlation for a NASA Langley Research Center (LaRC) low aspect ratio research wind tunnel model. To demonstrate the improvements that TACT offers the MSC/PATRAN- and MSC/DIASTRAN- based structural analysis community, a comparison of the modal correlation process using TACT within PATRAN versus external third-party modal correlation packages is presented.

Time-resolved multi-mass ion imaging: Femtosecond UV-VUV pump-probe spectroscopy with the PImMS camera.

PubMed

Forbes, Ruaridh; Makhija, Varun; Veyrinas, Kévin; Stolow, Albert; Lee, Jason W L; Burt, Michael; Brouard, Mark; Vallance, Claire; Wilkinson, Iain; Lausten, Rune; Hockett, Paul

2017-07-07

The Pixel-Imaging Mass Spectrometry (PImMS) camera allows for 3D charged particle imaging measurements, in which the particle time-of-flight is recorded along with (x, y) position. Coupling the PImMS camera to an ultrafast pump-probe velocity-map imaging spectroscopy apparatus therefore provides a route to time-resolved multi-mass ion imaging, with both high count rates and large dynamic range, thus allowing for rapid measurements of complex photofragmentation dynamics. Furthermore, the use of vacuum ultraviolet wavelengths for the probe pulse allows for an enhanced observation window for the study of excited state molecular dynamics in small polyatomic molecules having relatively high ionization potentials. Herein, preliminary time-resolved multi-mass imaging results from C 2 F 3 I photolysis are presented. The experiments utilized femtosecond VUV and UV (160.8 nm and 267 nm) pump and probe laser pulses in order to demonstrate and explore this new time-resolved experimental ion imaging configuration. The data indicate the depth and power of this measurement modality, with a range of photofragments readily observed, and many indications of complex underlying wavepacket dynamics on the excited state(s) prepared.

Sensei: A Multi-Modal Framework for Assessing Stress Resiliency

DTIC Science & Technology

2013-05-01

Modal Framework for Assessing Stress Resiliency (May 1-31, 2013) From: Ajay Divakaran, Technical Leader Jeffrey Lubin, Senior Research Scientist...17 (May 2013): Task 3.1: Capture Behavioral Stress Markers in Real-Time in Lab Environment with graded exposure to ICT’s scenarios MAC 1-6...Modal Framework for Assessing Stress Resiliency 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER

Brain activity during divided and selective attention to auditory and visual sentence comprehension tasks

PubMed Central

Moisala, Mona; Salmela, Viljami; Salo, Emma; Carlson, Synnöve; Vuontela, Virve; Salonen, Oili; Alho, Kimmo

2015-01-01

Using functional magnetic resonance imaging (fMRI), we measured brain activity of human participants while they performed a sentence congruence judgment task in either the visual or auditory modality separately, or in both modalities simultaneously. Significant performance decrements were observed when attention was divided between the two modalities compared with when one modality was selectively attended. Compared with selective attention (i.e., single tasking), divided attention (i.e., dual-tasking) did not recruit additional cortical regions, but resulted in increased activity in medial and lateral frontal regions which were also activated by the component tasks when performed separately. Areas involved in semantic language processing were revealed predominantly in the left lateral prefrontal cortex by contrasting incongruent with congruent sentences. These areas also showed significant activity increases during divided attention in relation to selective attention. In the sensory cortices, no crossmodal inhibition was observed during divided attention when compared with selective attention to one modality. Our results suggest that the observed performance decrements during dual-tasking are due to interference of the two tasks because they utilize the same part of the cortex. Moreover, semantic dual-tasking did not appear to recruit additional brain areas in comparison with single tasking, and no crossmodal inhibition was observed during intermodal divided attention. PMID:25745395

Brain activity during divided and selective attention to auditory and visual sentence comprehension tasks.

PubMed

Moisala, Mona; Salmela, Viljami; Salo, Emma; Carlson, Synnöve; Vuontela, Virve; Salonen, Oili; Alho, Kimmo

2015-01-01

Using functional magnetic resonance imaging (fMRI), we measured brain activity of human participants while they performed a sentence congruence judgment task in either the visual or auditory modality separately, or in both modalities simultaneously. Significant performance decrements were observed when attention was divided between the two modalities compared with when one modality was selectively attended. Compared with selective attention (i.e., single tasking), divided attention (i.e., dual-tasking) did not recruit additional cortical regions, but resulted in increased activity in medial and lateral frontal regions which were also activated by the component tasks when performed separately. Areas involved in semantic language processing were revealed predominantly in the left lateral prefrontal cortex by contrasting incongruent with congruent sentences. These areas also showed significant activity increases during divided attention in relation to selective attention. In the sensory cortices, no crossmodal inhibition was observed during divided attention when compared with selective attention to one modality. Our results suggest that the observed performance decrements during dual-tasking are due to interference of the two tasks because they utilize the same part of the cortex. Moreover, semantic dual-tasking did not appear to recruit additional brain areas in comparison with single tasking, and no crossmodal inhibition was observed during intermodal divided attention.

Reconstructive procedures for disturbed functions within the upper airway: pharyngeal breathing/snoring

PubMed Central

Verse, Thomas

2005-01-01

Breathing disorders which have their origin within the pharynx mainly occur during sleep. These so-called obstructive sleep-related breathing disorders include three different disturbances which have to be distinguished properly: simple snoring, upper airway resistance syndrome (UARS) and obstructive sleep apnea (OSA). Each disturbance requires a different treatment. Simple snoring does not affect the physical health of the snorer himself, but often leads to social problems due to the annoying character of the breathing sounds. Appropriate treatment modalities are oral devices and transcutaneous or ttransmucosal electrical stimulation of the muscles of the floor of the mouth via surface electrodes. As reconstructive surgical procedures adenotomies, tonsillectomies, tonsillotomies, or adenotonsillectomies are successfully used in children. Moreover, in adults radiofrequency treatments of the tonsils, the soft palate and of the base of tongue, as well as uvulopalatopharyngoplasty (UPPP), laser-assisted uvulopalatoplasty (LAUP) and palatal implants are adequate treatments for simple snoring. Adequate therapies for UARS and mild OSA (less than 20 breathing events per hour of sleep) are oral appliances. Nasal continuos positive airway pressure (NCPAP) ventilation is a very successful treatment modality, but shows low compliance in these patients, as daytime symptoms like excessive sleepiness or or impaired cognitive functions are often unincisive in patients with mild OSA. Reconstructive procedures like UPPP, radiofrequency surgery of the tonsils or the base of tongue, hyoid suspension, mandibular osteotomy with genioglossus advancement (MO) are successful treatment options either as isolated procedures or in combination within so-called multi-level surgery concepts. Goldstandard for the treatment of moderate to severe OSA is the nCPAP ventilation. All patients should at least try this treatment modality. Only in the rare cases of nCPAP failure (2%) and in the relatively frequent cases of nCPAP incompliance (30%) reconstructive surgical procedures become necessary as second choice treatments. These are adenectomies, tonsillectomies, tonsillotomies in children and hyoid suspension, MO, multi-level surgery concepts, or maxillomandibular advancement osteotomies in adults. PMID:22073056

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

Nano-graphene in biomedicine: theranostic applications.

PubMed

Yang, Kai; Feng, Liangzhu; Shi, Xiaoze; Liu, Zhuang

2013-01-21

Owing to their unique physical and chemical properties, graphene and its derivatives such as graphene oxide (GO), reduced graphene oxide (RGO) and GO-nanocomposites have attracted tremendous interest in many different fields including biomedicine in recent years. With every atom exposed on its surface, single-layered graphene shows ultra-high surface area available for efficient molecular loading and bioconjugation, and has been widely explored as novel nano-carriers for drug and gene delivery. Utilizing the intrinsic near-infrared (NIR) optical absorbance, in vivo graphene-based photothermal therapy has been realized, achieving excellent anti-tumor therapeutic efficacy in animal experiments. A variety of inorganic nanoparticles can be grown on the surface of nano-graphene, obtaining functional graphene-based nanocomposites with interesting optical and magnetic properties useful for multi-modal imaging and imaging-guided cancer therapy. Moreover, significant efforts have also been devoted to study the behaviors and toxicology of functionalized nano-graphene in animals. It has been uncovered that both surface chemistry and sizes play key roles in controlling the biodistribution, excretion, and toxicity of nano-graphene. Biocompatibly coated nano-graphene with ultra-small sizes can be cleared out from body after systemic administration, without rendering noticeable toxicity to the treated mice. In this review article, we will summarize the latest progress in this rapidly growing field, and discuss future prospects and challenges of using graphene-based materials for theranostic applications.

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

DOE PAGES

Ziatdinov, Maxim A.; Fujii, Shintaro; Kiguchi, Manabu; ...

2016-11-09

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding windowmore » Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.« less

A measure for assessing the effects of audiovisual speech integration.

PubMed

Altieri, Nicholas; Townsend, James T; Wenger, Michael J

2014-06-01

We propose a measure of audiovisual speech integration that takes into account accuracy and response times. This measure should prove beneficial for researchers investigating multisensory speech recognition, since it relates to normal-hearing and aging populations. As an example, age-related sensory decline influences both the rate at which one processes information and the ability to utilize cues from different sensory modalities. Our function assesses integration when both auditory and visual information are available, by comparing performance on these audiovisual trials with theoretical predictions for performance under the assumptions of parallel, independent self-terminating processing of single-modality inputs. We provide example data from an audiovisual identification experiment and discuss applications for measuring audiovisual integration skills across the life span.

Chronic disorders of consciousness: role of neuroimaging

NASA Astrophysics Data System (ADS)

Kremneva, E.; Sergeev, D.; Zmeykina, E.; Legostaeva, L.; Piradov, M.

2017-08-01

Chronic disorders of consciousness are clinically challenging conditions, and advanced methods of imaging for better understanding of diagnosis and prognosis are needed. Recent functional neuroradiological studies utilizing PET and fMRI demonstrated that besides widespread neuronal loss disruption of interconnection between certain cortical networks after the injury may also play the leading role in the development of behaviourally assessed unresponsiveness. Functional and structural connectivity, evaluated by neuroimaging approaches, may correlate with clinical status and may also play prognostic role. Integration of data from various diagnostic modalities is needed for further progress in this area.

Cardiac and pericardial tumors: A potential application of positron emission tomography-magnetic resonance imaging.

PubMed

Fathala, Ahmed; Abouzied, Mohei; AlSugair, Abdul-Aziz

2017-07-26

Cardiac and pericardial masses may be neoplastic, benign and malignant, non-neoplastic such as thrombus or simple pericardial cysts, or normal variants cardiac structure can also be a diagnostic challenge. Currently, there are several imaging modalities for diagnosis of cardiac masses; each technique has its inherent advantages and disadvantages. Echocardiography, is typically the initial test utilizes in such cases, Echocardiography is considered the test of choice for evaluation and detection of cardiac mass, it is widely available, portable, with no ionizing radiation and provides comprehensive evaluation of cardiac function and valves, however, echocardiography is not very helpful in many cases such as evaluation of extracardiac extension of mass, poor tissue characterization, and it is non diagnostic in some cases. Cross sectional imaging with cardiac computed tomography provides a three dimensional data set with excellent spatial resolution but utilizes ionizing radiation, intravenous iodinated contrast and relatively limited functional evaluation of the heart. Cardiac magnetic resonance imaging (CMR) has excellent contrast resolution that allows superior soft tissue characterization. CMR offers comprehensive evaluation of morphology, function, tissue characterization. The great benefits of CMR make CMR a highly useful tool in the assessment of cardiac masses. (Fluorine 18) fluorodeoxygluocse (FDG) positron emission tomography (PET) has become a corner stone in several oncological application such as tumor staging, restaging, treatment efficiency, FDG is a very useful imaging modality in evaluation of cardiac masses. A recent advance in the imaging technology has been the development of integrated PET-MRI system that utilizes the advantages of PET and MRI in a single examination. FDG PET-MRI provides complementary information on evaluation of cardiac masses. The purpose of this review is to provide several clinical scenarios on the incremental value of PET and MRI in the evaluation of cardiac masses.

Image-guided thoracic surgery in the hybrid operation room.

PubMed

Ujiie, Hideki; Effat, Andrew; Yasufuku, Kazuhiro

2017-01-01

There has been an increase in the use of image-guided technology to facilitate minimally invasive therapy. The next generation of minimally invasive therapy is focused on advancement and translation of novel image-guided technologies in therapeutic interventions, including surgery, interventional pulmonology, radiation therapy, and interventional laser therapy. To establish the efficacy of different minimally invasive therapies, we have developed a hybrid operating room, known as the guided therapeutics operating room (GTx OR) at the Toronto General Hospital. The GTx OR is equipped with multi-modality image-guidance systems, which features a dual source-dual energy computed tomography (CT) scanner, a robotic cone-beam CT (CBCT)/fluoroscopy, high-performance endobronchial ultrasound system, endoscopic surgery system, near-infrared (NIR) fluorescence imaging system, and navigation tracking systems. The novel multimodality image-guidance systems allow physicians to quickly, and accurately image patients while they are on the operating table. This yield improved outcomes since physicians are able to use image guidance during their procedures, and carry out innovative multi-modality therapeutics. Multiple preclinical translational studies pertaining to innovative minimally invasive technology is being developed in our guided therapeutics laboratory (GTx Lab). The GTx Lab is equipped with similar technology, and multimodality image-guidance systems as the GTx OR, and acts as an appropriate platform for translation of research into human clinical trials. Through the GTx Lab, we are able to perform basic research, such as the development of image-guided technologies, preclinical model testing, as well as preclinical imaging, and then translate that research into the GTx OR. This OR allows for the utilization of new technologies in cancer therapy, including molecular imaging, and other innovative imaging modalities, and therefore enables a better quality of life for patients, both during and after the procedure. In this article, we describe capabilities of the GTx systems, and discuss the first-in-human technologies used, and evaluated in GTx OR.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech.

PubMed

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Time-Extended Policies in Mult-Agent Reinforcement Learning

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian K.

2004-01-01

Reinforcement learning methods perform well in many domains where a single agent needs to take a sequence of actions to perform a task. These methods use sequences of single-time-step rewards to create a policy that tries to maximize a time-extended utility, which is a (possibly discounted) sum of these rewards. In this paper we build on our previous work showing how these methods can be extended to a multi-agent environment where each agent creates its own policy that works towards maximizing a time-extended global utility over all agents actions. We show improved methods for creating time-extended utilities for the agents that are both "aligned" with the global utility and "learnable." We then show how to crate single-time-step rewards while avoiding the pi fall of having rewards aligned with the global reward leading to utilities not aligned with the global utility. Finally, we apply these reward functions to the multi-agent Gridworld problem. We explicitly quantify a utility's learnability and alignment, and show that reinforcement learning agents using the prescribed reward functions successfully tradeoff learnability and alignment. As a result they outperform both global (e.g., team games ) and local (e.g., "perfectly learnable" ) reinforcement learning solutions by as much as an order of magnitude.

Using Multi-Media Projects to Foster Teacher Candidates' Multiple Literacy Skills

ERIC Educational Resources Information Center

Lawrence, Salika A.

2010-01-01

This article describes the strategies used to incorporate multi-modal technology literacy experiences into a graduate level course for literacy specialists. The candidates created a multi-media project in response to literature. Their projects revealed that the teacher candidates used a variety of sources to create the project but the Internet was…

Crack Identification in CFRP Laminated Beams Using Multi-Resolution Modal Teager–Kaiser Energy under Noisy Environments

PubMed Central

Xu, Wei; Cao, Maosen; Ding, Keqin; Radzieński, Maciej; Ostachowicz, Wiesław

2017-01-01

Carbon fiber reinforced polymer laminates are increasingly used in the aerospace and civil engineering fields. Identifying cracks in carbon fiber reinforced polymer laminated beam components is of considerable significance for ensuring the integrity and safety of the whole structures. With the development of high-resolution measurement technologies, mode-shape-based crack identification in such laminated beam components has become an active research focus. Despite its sensitivity to cracks, however, this method is susceptible to noise. To address this deficiency, this study proposes a new concept of multi-resolution modal Teager–Kaiser energy, which is the Teager–Kaiser energy of a mode shape represented in multi-resolution, for identifying cracks in carbon fiber reinforced polymer laminated beams. The efficacy of this concept is analytically demonstrated by identifying cracks in Timoshenko beams with general boundary conditions; and its applicability is validated by diagnosing cracks in a carbon fiber reinforced polymer laminated beam, whose mode shapes are precisely acquired via non-contact measurement using a scanning laser vibrometer. The analytical and experimental results show that multi-resolution modal Teager–Kaiser energy is capable of designating the presence and location of cracks in these beams under noisy environments. This proposed method holds promise for developing crack identification systems for carbon fiber reinforced polymer laminates. PMID:28773016

Earth observing system instrument pointing control modeling for polar orbiting platforms

NASA Technical Reports Server (NTRS)

Briggs, H. C.; Kia, T.; Mccabe, S. A.; Bell, C. E.

1987-01-01

An approach to instrument pointing control performance assessment for large multi-instrument platforms is described. First, instrument pointing requirements and reference platform control systems for the Eos Polar Platforms are reviewed. Performance modeling tools including NASTRAN models of two large platforms, a modal selection procedure utilizing a balanced realization method, and reduced order platform models with core and instrument pointing control loops added are then described. Time history simulations of instrument pointing and stability performance in response to commanded slewing of adjacent instruments demonstrates the limits of tolerable slew activity. Simplified models of rigid body responses are also developed for comparison. Instrument pointing control methods required in addition to the core platform control system to meet instrument pointing requirements are considered.

Performance evaluation of a compact PET/SPECT/CT tri-modality system for small animal imaging applications

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Wang, Shi; Ma, Tianyu; Wu, Jing; Liu, Hui; Xu, Tianpeng; Xia, Yan; Fan, Peng; Lyu, Zhenlei; Liu, Yaqiang

2015-06-01

PET, SPECT and CT imaging techniques are widely used in preclinical small animal imaging applications. In this paper, we present a compact small animal PET/SPECT/CT tri-modality system. A dual-functional, shared detector design is implemented which enables PET and SPECT imaging with a same LYSO ring detector. A multi-pinhole collimator is mounted on the system and inserted into the detector ring in SPECT imaging mode. A cone-beam CT consisting of a micro focus X-ray tube and a CMOS detector is implemented. The detailed design and the performance evaluations are reported in this paper. In PET imaging mode, the measured NEMA based spatial resolution is 2.12 mm (FWHM), and the sensitivity at the central field of view (CFOV) is 3.2%. The FOV size is 50 mm (∅)×100 mm (L). The SPECT has a spatial resolution of 1.32 mm (FWHM) and an average sensitivity of 0.031% at the center axial, and a 30 mm (∅)×90 mm (L) FOV. The CT spatial resolution is 8.32 lp/mm @10%MTF, and the contrast discrimination function value is 2.06% with 1.5 mm size cubic box object. In conclusion, a compact, tri-modality PET/SPECT/CT system was successfully built with low cost and high performance.

Antibody Drug Conjugates: Application of Quantitative Pharmacology in Modality Design and Target Selection.

PubMed

Sadekar, S; Figueroa, I; Tabrizi, M

2015-07-01

Antibody drug conjugates (ADCs) are a multi-component modality comprising of an antibody targeting a cell-specific antigen, a potent drug/payload, and a linker that can be processed within cellular compartments to release payload upon internalization. Numerous ADCs are being evaluated in both research and clinical settings within the academic and pharmaceutical industry due to their ability to selectively deliver potent payloads. Hence, there is a clear need to incorporate quantitative approaches during early stages of drug development for effective modality design and target selection. In this review, we describe a quantitative approach and framework for evaluation of the interplay between drug- and systems-dependent properties (i.e., target expression, density, localization, turnover, and affinity) in order to deliver a sufficient amount of a potent payload into the relevant target cells. As discussed, theoretical approaches with particular considerations given to various key properties for the target and modality suggest that delivery of the payload into particular effect cells to be more sensitive to antigen concentrations for targets with slow turnover rates as compared to those with faster internalization rates. Further assessments also suggest that increasing doses beyond the threshold of the target capacity (a function of target internalization and expression) may not impact the maximum amount of payload delivered to the intended effect cells. This article will explore the important application of quantitative sciences in selection of the target and design of ADC modalities.

Multimodal Fusion with Reference: Searching for Joint Neuromarkers of Working Memory Deficits in Schizophrenia

PubMed Central

Qi, Shile; Calhoun, Vince D.; van Erp, Theo G. M.; Bustillo, Juan; Damaraju, Eswar; Turner, Jessica A.; Du, Yuhui; Chen, Jiayu; Yu, Qingbao; Mathalon, Daniel H.; Ford, Judith M.; Voyvodic, James; Mueller, Bryon A.; Belger, Aysenil; Ewen, Sarah Mc; Potkin, Steven G.; Preda, Adrian; Jiang, Tianzi

2017-01-01

Multimodal fusion is an effective approach to take advantage of cross-information among multiple imaging data to better understand brain diseases. However, most current fusion approaches are blind, without adopting any prior information. To date, there is increasing interest to uncover the neurocognitive mapping of specific behavioral measurement on enriched brain imaging data; hence, a supervised, goal-directed model that enables a priori information as a reference to guide multimodal data fusion is in need and a natural option. Here we proposed a fusion with reference model, called “multi-site canonical correlation analysis with reference plus joint independent component analysis” (MCCAR+jICA), which can precisely identify co-varying multimodal imaging patterns closely related to reference information, such as cognitive scores. In a 3-way fusion simulation, the proposed method was compared with its alternatives on estimation accuracy of both target component decomposition and modality linkage detection. MCCAR+jICA outperforms others with higher precision. In human imaging data, working memory performance was utilized as a reference to investigate the covarying functional and structural brain patterns among 3 modalities and how they are impaired in schizophrenia. Two independent cohorts (294 and 83 subjects respectively) were used. Interestingly, similar brain maps were identified between the two cohorts, with substantial overlap in the executive control networks in fMRI, salience network in sMRI, and major white matter tracts in dMRI. These regions have been linked with working memory deficits in schizophrenia in multiple reports, while MCCAR+jICA further verified them in a repeatable, joint manner, demonstrating the potential of such results to identify potential neuromarkers for mental disorders. PMID:28708547

Quantitative reconstructions in multi-modal photoacoustic and optical coherence tomography imaging

NASA Astrophysics Data System (ADS)

Elbau, P.; Mindrinos, L.; Scherzer, O.

2018-01-01

In this paper we perform quantitative reconstruction of the electric susceptibility and the Grüneisen parameter of a non-magnetic linear dielectric medium using measurement of a multi-modal photoacoustic and optical coherence tomography system. We consider the mathematical model presented in Elbau et al (2015 Handbook of Mathematical Methods in Imaging ed O Scherzer (New York: Springer) pp 1169-204), where a Fredholm integral equation of the first kind for the Grüneisen parameter was derived. For the numerical solution of the integral equation we consider a Galerkin type method.

Integrating Soluble Biomarkers and Imaging Technologies in the Identification of Vulnerable Atherosclerotic Patients

PubMed Central

Páramo, José A.; Rodríguez JA, José A.; Orbe, Josune

2006-01-01

The clinical utility of a biomarker depends on its ability to identify high-risk individuals to optimally manage the patient. A new biomarker would be of clinical value if it is accurate and reliable, provides good sensitivity and specificity, and is available for widespread application. Data are accumulating on the potential clinical utility of integrating imaging technologies and circulating biomarkers for the identification of vulnerable (high-risk) cardiovascular patients. A multi-biomarker strategy consisting of markers of inflammation, hemostasis and thrombosis, proteolysis and oxidative stress, combined with new imaging modalities (optical coherence tomography, virtual histology plus IVUS, PET) can increase our ability to identify such thombosis-prone patients. In an ideal scenario, cardiovascular biomarkers and imaging combined will provide a better diagnostic tool to identify high-risk individuals and also more efficient methods for effective therapies to reduce such cardiovascular risk. However, additional studies are required in order to show that this approach can contribute to improved diagnostic and therapeutic of atherosclerotic disease. PMID:19690647

Integrating soluble biomarkers and imaging technologies in the identification of vulnerable atherosclerotic patients.

PubMed

Páramo, José A; Rodríguez Ja, José A; Orbe, Josune

2007-02-07

The clinical utility of a biomarker depends on its ability to identify high-risk individuals to optimally manage the patient. A new biomarker would be of clinical value if it is accurate and reliable, provides good sensitivity and specificity, and is available for widespread application. Data are accumulating on the potential clinical utility of integrating imaging technologies and circulating biomarkers for the identification of vulnerable (high-risk) cardiovascular patients. A multi-biomarker strategy consisting of markers of inflammation, hemostasis and thrombosis, proteolysis and oxidative stress, combined with new imaging modalities (optical coherence tomography, virtual histology plus IVUS, PET) can increase our ability to identify such thombosis-prone patients. In an ideal scenario, cardiovascular biomarkers and imaging combined will provide a better diagnostic tool to identify high-risk individuals and also more efficient methods for effective therapies to reduce such cardiovascular risk. However, additional studies are required in order to show that this approach can contribute to improved diagnostic and therapeutic of atherosclerotic disease.

Energy harvesting from coupled bending-twisting oscillations in carbon-fibre reinforced polymer laminates

NASA Astrophysics Data System (ADS)

Xie, Mengying; Zhang, Yan; Kraśny, Marcin J.; Rhead, Andrew; Bowen, Chris; Arafa, Mustafa

2018-07-01

The energy harvesting capability of resonant harvesting structures, such as piezoelectric cantilever beams, can be improved by utilizing coupled oscillations that generate favourable strain mode distributions. In this work, we present the first demonstration of the use of a laminated carbon fibre reinforced polymer to create cantilever beams that undergo coupled bending-twisting oscillations for energy harvesting applications. Piezoelectric layers that operate in bending and shear mode are attached to the bend-twist coupled beam surface at locations of maximum bending and torsional strains in the first mode of vibration to fully exploit the strain distribution along the beam. Modelling of this new bend-twist harvesting system is presented, which compares favourably with experimental results. It is demonstrated that the variety of bend and torsional modes of the harvesters can be utilized to create a harvester that operates over a wider range of frequencies and such multi-modal device architectures provides a unique approach to tune the frequency response of resonant harvesting systems.

Artificial redirection of sensation from prosthetic fingers to the phantom hand map on transradial amputees: vibrotactile versus mechanotactile sensory feedback.

PubMed

Antfolk, Christian; D'Alonzo, Marco; Controzzi, Marco; Lundborg, Göran; Rosén, Birgitta; Sebelius, Fredrik; Cipriani, Christian

2013-01-01

This work assesses the ability of transradial amputees to discriminate multi-site tactile stimuli in sensory discrimination tasks. It compares different sensory feedback modalities using an artificial hand prosthesis in: 1) a modality matched paradigm where pressure recorded on the five fingertips of the hand was fed back as pressure stimulation on five target points on the residual limb; and 2) a modality mismatched paradigm where the pressures were transformed into mechanical vibrations and fed back. Eight transradial amputees took part in the study and were divided in two groups based on the integrity of their phantom map; group A had a complete phantom map on the residual limb whereas group B had an incomplete or nonexisting map. The ability in localizing stimuli was compared with that of 10 healthy subjects using the vibration feedback and 11 healthy subjects using the pressure feedback (in a previous study), on their forearms, in similar experiments. Results demonstrate that pressure stimulation surpassed vibrotactile stimulation in multi-site sensory feedback discrimination. Furthermore, we demonstrate that subjects with a detailed phantom map had the best discrimination performance and even surpassed healthy participants for both feedback paradigms whereas group B had the worst performance overall. Finally, we show that placement of feedback devices on a complete phantom map improves multi-site sensory feedback discrimination, independently of the feedback modality.

A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.

PubMed

Lu, Pei; Xia, Jun; Li, Zhicheng; Xiong, Jing; Yang, Jian; Zhou, Shoujun; Wang, Lei; Chen, Mingyang; Wang, Cheng

2016-11-08

Accurate segmentation of blood vessels plays an important role in the computer-aided diagnosis and interventional treatment of vascular diseases. The statistical method is an important component of effective vessel segmentation; however, several limitations discourage the segmentation effect, i.e., dependence of the image modality, uneven contrast media, bias field, and overlapping intensity distribution of the object and background. In addition, the mixture models of the statistical methods are constructed relaying on the characteristics of the image histograms. Thus, it is a challenging issue for the traditional methods to be available in vessel segmentation from multi-modality angiographic images. To overcome these limitations, a flexible segmentation method with a fixed mixture model has been proposed for various angiography modalities. Our method mainly consists of three parts. Firstly, multi-scale filtering algorithm was used on the original images to enhance vessels and suppress noises. As a result, the filtered data achieved a new statistical characteristic. Secondly, a mixture model formed by three probabilistic distributions (two Exponential distributions and one Gaussian distribution) was built to fit the histogram curve of the filtered data, where the expectation maximization (EM) algorithm was used for parameters estimation. Finally, three-dimensional (3D) Markov random field (MRF) were employed to improve the accuracy of pixel-wise classification and posterior probability estimation. To quantitatively evaluate the performance of the proposed method, two phantoms simulating blood vessels with different tubular structures and noises have been devised. Meanwhile, four clinical angiographic data sets from different human organs have been used to qualitatively validate the method. To further test the performance, comparison tests between the proposed method and the traditional ones have been conducted on two different brain magnetic resonance angiography (MRA) data sets. The results of the phantoms were satisfying, e.g., the noise was greatly suppressed, the percentages of the misclassified voxels, i.e., the segmentation error ratios, were no more than 0.3%, and the Dice similarity coefficients (DSCs) were above 94%. According to the opinions of clinical vascular specialists, the vessels in various data sets were extracted with high accuracy since complete vessel trees were extracted while lesser non-vessels and background were falsely classified as vessel. In the comparison experiments, the proposed method showed its superiority in accuracy and robustness for extracting vascular structures from multi-modality angiographic images with complicated background noises. The experimental results demonstrated that our proposed method was available for various angiographic data. The main reason was that the constructed mixture probability model could unitarily classify vessel object from the multi-scale filtered data of various angiography images. The advantages of the proposed method lie in the following aspects: firstly, it can extract the vessels with poor angiography quality, since the multi-scale filtering algorithm can improve the vessel intensity in the circumstance such as uneven contrast media and bias field; secondly, it performed well for extracting the vessels in multi-modality angiographic images despite various signal-noises; and thirdly, it was implemented with better accuracy, and robustness than the traditional methods. Generally, these traits declare that the proposed method would have significant clinical application.

Generic functional requirements for a NASA general-purpose data base management system

NASA Technical Reports Server (NTRS)

Lohman, G. M.

1981-01-01

Generic functional requirements for a general-purpose, multi-mission data base management system (DBMS) for application to remotely sensed scientific data bases are detailed. The motivation for utilizing DBMS technology in this environment is explained. The major requirements include: (1) a DBMS for scientific observational data; (2) a multi-mission capability; (3) user-friendly; (4) extensive and integrated information about data; (5) robust languages for defining data structures and formats; (6) scientific data types and structures; (7) flexible physical access mechanisms; (8) ways of representing spatial relationships; (9) a high level nonprocedural interactive query and data manipulation language; (10) data base maintenance utilities; (11) high rate input/output and large data volume storage; and adaptability to a distributed data base and/or data base machine configuration. Detailed functions are specified in a top-down hierarchic fashion. Implementation, performance, and support requirements are also given.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Computer-assisted stereotactic neurological surgery: pre-planning and on-site real-time operating control and simulation system

NASA Astrophysics Data System (ADS)

Zamorano, Lucia J.; Jiang, Charlie Z. W.

1993-09-01

In this decade the concept and development of computer assisted stereotactic neurological surgery has improved dramatically. First, the computer network replaced the tape as the data transportation media. Second, newer systems include multi-modality image correlation and frameless stereotactics as an integral part of their functionality, and offer extensive assistance to the neurosurgeon from the preplanning stages to and throughout the operation itself. These are very important changes, and have spurred the development of many interesting techniques. Successful systems include the ISG and NSPS-3.0.

The year 2013 in the European Heart Journal--Cardiovascular Imaging: Part II.

PubMed

Plein, Sven; Edvardsen, Thor; Pierard, Luc A; Saraste, Antti; Knuuti, Juhani; Maurer, Gerald; Lancellotti, Patrizio

2014-08-01

The new multi-modality cardiovascular imaging journal, European Heart Journal - Cardiovascular Imaging, was created in 2012. Here we summarize the most important studies from the journal's second year in two articles. Part I of the review has summarized studies in myocardial function, myocardial ischaemia, and emerging techniques in cardiovascular imaging. Part II is focussed on valvular heart diseases, heart failure, cardiomyopathies, and congenital heart diseases. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.

Strategies for Multi-Modal Analysis

NASA Astrophysics Data System (ADS)

Hexemer, Alexander; Wang, Cheng; Pandolfi, Ronald; Kumar, Dinesh; Venkatakrishnan, Singanallur; Sethian, James; Camera Team

This section on soft materials will be dedicated to discuss the extraction of the chemical distribution and spatial arrangement of constituent elements and functional groups at multiple length scales and, thus, the examination of collective dynamics, transport, and electronic ordering phenomena. Traditional measures of structure in soft materials have relied heavily on scattering and imaging based techniques due to their capacity to measure nanoscale dimensions and their capacity to monitor structure under conditions of dynamic stress loading. Special attentions are planned to focus on the application of resonant x-ray scattering, contrast-varied neutron scattering, analytical transmission electron microscopy, and their combinations. This session aims to bring experts in both scattering and electron microscope fields to discuss recent advances in selectively characterizing structural architectures of complex soft materials, which have often multi-components with a wide range of length scales and multiple functionalities, and thus hopes to foster novel ideas to decipher a higher level of structural complexity in soft materials in future. CAMERA, Early Career Award.

Overview of multi-input frequency domain modal testing methods with an emphasis on sine testing

NASA Technical Reports Server (NTRS)

Rost, Robert W.; Brown, David L.

1988-01-01

An overview of the current state of the art multiple-input, multiple-output modal testing technology is discussed. A very brief review of the current time domain methods is given. A detailed review of frequency and spatial domain methods is presented with an emphasis on sine testing.

Towards an intelligent framework for multimodal affective data analysis.

PubMed

Poria, Soujanya; Cambria, Erik; Hussain, Amir; Huang, Guang-Bin

2015-03-01

An increasingly large amount of multimodal content is posted on social media websites such as YouTube and Facebook everyday. In order to cope with the growth of such so much multimodal data, there is an urgent need to develop an intelligent multi-modal analysis framework that can effectively extract information from multiple modalities. In this paper, we propose a novel multimodal information extraction agent, which infers and aggregates the semantic and affective information associated with user-generated multimodal data in contexts such as e-learning, e-health, automatic video content tagging and human-computer interaction. In particular, the developed intelligent agent adopts an ensemble feature extraction approach by exploiting the joint use of tri-modal (text, audio and video) features to enhance the multimodal information extraction process. In preliminary experiments using the eNTERFACE dataset, our proposed multi-modal system is shown to achieve an accuracy of 87.95%, outperforming the best state-of-the-art system by more than 10%, or in relative terms, a 56% reduction in error rate. Copyright © 2014 Elsevier Ltd. All rights reserved.

XML-based scripting of multimodality image presentations in multidisciplinary clinical conferences

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Allada, Vivekanand; Dahlbom, Magdalena; Marcus, Phillip; Fine, Ian; Lapstra, Lorelle

2002-05-01

We developed a multi-modality image presentation software for display and analysis of images and related data from different imaging modalities. The software is part of a cardiac image review and presentation platform that supports integration of digital images and data from digital and analog media such as videotapes, analog x-ray films and 35 mm cine films. The software supports standard DICOM image files as well as AVI and PDF data formats. The system is integrated in a digital conferencing room that includes projections of digital and analog sources, remote videoconferencing capabilities, and an electronic whiteboard. The goal of this pilot project is to: 1) develop a new paradigm for image and data management for presentation in a clinically meaningful sequence adapted to case-specific scenarios, 2) design and implement a multi-modality review and conferencing workstation using component technology and customizable 'plug-in' architecture to support complex review and diagnostic tasks applicable to all cardiac imaging modalities and 3) develop an XML-based scripting model of image and data presentation for clinical review and decision making during routine clinical tasks and multidisciplinary clinical conferences.

Enhancing transcranial direct current stimulation via motor imagery and kinesthetic illusion: crossing internal and external tools.

PubMed

Bodranghien, Florian; Manto, Mario; Lebon, Florent

2016-06-01

Transcranial direct current stimulation is a safe technique which is now part of the therapeutic armamentarium for the neuromodulation of motor functions and cognitive operations. It is currently considered that tDCS is an intervention that might promote functional recovery after a lesion in the central nervous system, thus reducing long-term disability and associated socio-economic burden. A recent study shows that kinesthetic illusion and motor imagery prolong the effects of tDCS on corticospinal excitability, overcoming one of the limitations of this intervention. Because changes in excitability anticipate changes in structural plasticity in the CNS, this interesting multi-modal approach might very soon find applications in neurorehabilitation.

The Age-ility Project (Phase 1): Structural and functional imaging and electrophysiological data repository.

PubMed

Karayanidis, Frini; Keuken, Max C; Wong, Aaron; Rennie, Jaime L; de Hollander, Gilles; Cooper, Patrick S; Ross Fulham, W; Lenroot, Rhoshel; Parsons, Mark; Phillips, Natalie; Michie, Patricia T; Forstmann, Birte U

2016-01-01

Our understanding of the complex interplay between structural and functional organisation of brain networks is being advanced by the development of novel multi-modal analyses approaches. The Age-ility Project (Phase 1) data repository offers open access to structural MRI, diffusion MRI, and resting-state fMRI scans, as well as resting-state EEG recorded from the same community participants (n=131, 15-35 y, 66 male). Raw imaging and electrophysiological data as well as essential demographics are made available via the NITRC website. All data have been reviewed for artifacts using a rigorous quality control protocol and detailed case notes are provided. Copyright © 2015. Published by Elsevier Inc.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

NASA Astrophysics Data System (ADS)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

[Preliminary study of rabbit experiment modality for evaluating cardiac fatigue].

PubMed

Yan, Xiaobo; Luo, Linmei; Liu, Leichu; Xiao, Shouzhong; Deng, Suyuan; Xiang, Lingli; Zhang, Cong

2013-04-01

This paper presents a preliminary study of rabbit experiment modality incorporating a new indicator for evaluating cardiac function changes, providing a basis for subsequent study of cardiac fatigue. Using only biochemical indicators, such as troponins, is difficult to make a distinction between exercise-induced cardiac fatigue (EICF) and exercise-induced cardiac damage (EICD). Therefore, some new indicators are needed to evaluate cardiac fatigue synthetically. In our study, we used New Zealand white rabbits to conduct a multi-step swimming experiments with load. We made the rabbits reach an exhaustive state to evaluate whether the amplitude ratio of the first to second heart sound (S1/S2) and heart rate (HR) during the exhaustive exercise would be decreased and whether they would be able to recover after the exhaustive exercise for 24 hours. During the first phase of swimming, S1/S2 and HR were increased, and then decreased at exhaustive state. They were recovered after the exhaustive exercise for 24 hours. Overloading led to deaths of three rabbis, and new phenomena from overloading and related to this kind of death were observed. The experiments proved that Multi-steps swimming experiments with loads by using New Zealand white rabbit is useful for studying cardiac fatigue and premonition of sudden cardiac death.

Single-Step Assembly of Multi-Modal Imaging Nanocarriers: MRI and Long-Wavelength Fluorescence Imaging

PubMed Central

Pinkerton, Nathalie M.; Gindy, Marian E.; Calero-DdelC, Victoria L.; Wolfson, Theodore; Pagels, Robert F.; Adler, Derek; Gao, Dayuan; Li, Shike; Wang, Ruobing; Zevon, Margot; Yao, Nan; Pacheco, Carlos; Therien, Michael J.; Rinaldi, Carlos; Sinko, Patrick J.

2015-01-01

MRI and NIR-active, multi-modal Composite NanoCarriers (CNCs) are prepared using a simple, one-step process, Flash NanoPrecipitation (FNP). The FNP process allows for the independent control of the hydrodynamic diameter, co-core excipient and NIR dye loading, and iron oxide-based nanocrystal (IONC) content of the CNCs. In the controlled precipitation process, 10 nm IONCs are encapsulated into poly(ethylene glycol) stabilized CNCs to make biocompatible T2 contrast agents. By adjusting the formulation, CNC size is tuned between 80 and 360 nm. Holding the CNC size constant at an intensity weighted average diameter of 99 ± 3 nm (PDI width 28 nm), the particle relaxivity varies linearly with encapsulated IONC content ranging from 66 to 533 mM-1s-1 for CNCs formulated with 4 to 16 wt% IONC. To demonstrate the use of CNCs as in vivo MRI contrast agents, CNCs are surface functionalized with liver targeting hydroxyl groups. The CNCs enable the detection of 0.8 mm3 non-small cell lung cancer metastases in mice livers via MRI. Incorporating the hydrophobic, NIR dye PZn3 into CNCs enables complementary visualization with long-wavelength fluorescence at 800 nm. In vivo imaging demonstrates the ability of CNCs to act both as MRI and fluorescent imaging agents. PMID:25925128

A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems

PubMed Central

Park, Kyeonghwan; Kim, Seung Mok; Eom, Won-Jin; Kim, Jae Joon

2017-01-01

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors. PMID:28368355

A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems.

PubMed

Park, Kyeonghwan; Kim, Seung Mok; Eom, Won-Jin; Kim, Jae Joon

2017-04-03

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors.

MSN anti-cancer nanomedicines: chemotherapy enhancement, overcoming of drug resistance, and metastasis inhibition.

PubMed

He, Qianjun; Shi, Jianlin

2014-01-22

In the anti-cancer war, there are three main obstacles resulting in high mortality and recurrence rate of cancers: the severe toxic side effect of anti-cancer drugs to normal tissues due to the lack of tumor-selectivity, the multi-drug resistance (MDR) to free chemotherapeutic drugs and the deadly metastases of cancer cells. The development of state-of-art nanomedicines based on mesoporous silica nanoparticles (MSNs) is expected to overcome the above three main obstacles. In the view of the fast development of anti-cancer strategy, this review highlights the most recent advances of MSN anti-cancer nanomedicines in enhancing chemotherapeutic efficacy, overcoming the MDR and inhibiting metastasis. Furthermore, we give an outlook of the future development of MSNs-based anti-cancer nanomedicines, and propose several innovative and forward-looking anti-cancer strategies, including tumor tissue-cell-nuclear successionally targeted drug delivery strategy, tumor cell-selective nuclear-targeted drug delivery strategy, multi-targeting and multi-drug strategy, chemo-/radio-/photodynamic-/ultrasound-/thermo-combined multi-modal therapy by virtue of functionalized hollow/rattle-structured MSNs. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids

PubMed Central

Ali, S. M.; Mehmood, C. A; Khan, B.; Jawad, M.; Farid, U; Jadoon, J. K.; Ali, M.; Tareen, N. K.; Usman, S.; Majid, M.; Anwar, S. M.

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion. PMID:27314229

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

PubMed

Ali, S M; Mehmood, C A; Khan, B; Jawad, M; Farid, U; Jadoon, J K; Ali, M; Tareen, N K; Usman, S; Majid, M; Anwar, S M

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

Multifunctional spaces in slum settlements and their relation to activity pattern case study of Kampung Sangkrah, Surakarta

NASA Astrophysics Data System (ADS)

Shobirin, Abyzhar; Ramadhanty, Almira Husna; Hardiana, Ana

2018-02-01

Surakarta is a rapidly urbanized city and it causes the limitation of the availability of land within its urban area. This entangled problem is resulting in the development of slum settlements that spread across the city. One of the slum concentration areas is located on Pepe riverbanks downstream area that belongs to Kampung Sangkrah administrative boundaries. Slum settlements are characterized as a densely-populated area lacking of, or absence of, open space. This condition forces slum inhabitants to effectively use their available spaces, even multi-functionally. This research aims to observe how slum inhabitants multi-functionally use the spaces around their houses and determine the typology of multifunctional space and also the factors that influence it. To understand this phenomenon, this research used activity pattern perspectives. The scope of observation covers in-house (internal) space utilizations and neighborhood-level (external) space utilization. The data used for this research were collected primarily through site observations and interviews, using sampling to conduct data collection for in-house activities and space utilization. The analysis was conducted using descriptive method qualitatively. The research concluded that there are three types of multifunctional space utilization within slum settlements, and the utilization of spaces, whether internal or external utilization also varies depending on the inhabitants' economic-related activities.

Short-Term Memory in Mathematics-Proficient and Mathematics-Disabled Students as a Function of Input-Modality/Output-Modality Pairings.

ERIC Educational Resources Information Center

Webster, Raymond E.

1980-01-01

A significant two-way input modality by output modality interaction suggested that short term memory capacity among the groups differed as a function of the modality used to present the items in combination with the output response required. (Author/CL)

Evaluating the efficacy of an integrated motivational interviewing and multi-modal exercise intervention for youth with major depression: Healthy Body, Healthy Mind randomised controlled trial protocol.

PubMed

Nasstasia, Yasmina; Baker, Amanda L; Halpin, Sean A; Hides, Leanne; Lewin, Terry J; Kelly, Brian J; Callister, Robin

2018-03-01

Recent meta-analytic reviews suggest exercise can reduce depression severity among adults with major depressive disorder (MDD); however, efficacy studies with depressed youth are limited. Few studies have investigated the efficacy of multi-modal exercise interventions in this population, addressed treatment engagement, or explored the differential effects of exercise on depressive symptom profiles. This paper describes the study protocol and recruitment pattern for an assessor blinded, two-arm randomised controlled trial investigating the efficacy of an integrated motivational interviewing (MI) and multi-modal exercise intervention in youth diagnosed with MDD. Associations between depressive symptom profiles (cognitive, somatic and affective) and psychological, physiological (fitness), and biological (blood biomarker) outcomes will also be examined. Participants aged 15-25 years with current MDD were recruited. Eligible participants were randomised and stratified according to gender and depression severity to either an immediate or delayed (control) group. The immediate group received a brief MI intervention followed by a 12-week small group exercise intervention (3 times per week for 1 h), all delivered by personal trainers. The delayed control group received the same intervention 12-weeks later. Both groups were reassessed at mid-treatment or mid-control, post-treatment or post-control, and follow-up (12 weeks post-treatment). 68 participants were recruited and randomly allocated to an intervention group. This trial will increase our understanding of the efficacy of multi-modal exercise interventions for depression and the specific effects of exercise on depressive symptom profiles. It also offers a novel contribution by addressing treatment engagement in exercise efficacy trials in youth with MDD.

X-ray digital imaging petrography of lunar mare soils: modal analyses of minerals and glasses

NASA Technical Reports Server (NTRS)

Taylor, L. A.; Patchen, A.; Taylor, D. H.; Chambers, J. G.; McKay, D. S.

1996-01-01

It is essential that accurate modal (i.e., volume) percentages of the various mineral and glass phases in lunar soils be used for addressing and resolving the effects of space weathering upon reflectance spectra, as well as for their calibration such data are also required for evaluating the resource potential of lunar minerals for use at a lunar base. However, these data are largely lacking. Particle-counting information for lunar soils, originally obtained to study formational processes, does not provide these necessary data, including the percentages of minerals locked in multi-phase lithic fragments and fused-soil particles, such as agglutinates. We have developed a technique for modal analyses, sensu stricto, of lunar soils, using digital imaging of X-ray maps obtained with an energy-dispersive spectrometer mounted on an electron microprobe. A suite of nine soils (90 to 150 micrometers size fraction) from the Apollo 11, 12, 15, and 17 mare sites was used for this study. This is the first collection of such modal data on soils from all Apollo mare sites. The abundances of free-mineral fragments in the mare soils are greater for immature and submature soils than for mature soils, largely because of the formation of agglutinitic glass as maturity progresses. In considerations of resource utilization at a lunar base, the best lunar soils to use for mineral beneficiation (i.e., most free-mineral fragments) have maturities near the immature/submature boundary (Is/FeO approximately or = 30), not the mature soils with their complications due to extensive agglutination. The particle data obtained from the nine mare soils confirm the generalizations for lunar soils predicted by L.A. Taylor and D.S. McKay (1992, Lunar Planet Sci. Conf. 23rd, pp. 1411-1412 [Abstract]).

IMAGES: A digital computer program for interactive modal analysis and gain estimation for eigensystem synthesis

NASA Technical Reports Server (NTRS)

Jones, R. L.

1984-01-01

An interactive digital computer program for modal analysis and gain estimation for eigensystem synthesis was written. Both mathematical and operation considerations are described; however, the mathematical presentation is limited to those concepts essential to the operational capability of the program. The program is capable of both modal and spectral synthesis of multi-input control systems. It is user friendly, has scratchpad capability and dynamic memory, and can be used to design either state or output feedback systems.

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1991-01-01

New methods were developed for efficient aeroservoelastic analysis and optimization. The main target was to develop a method for investigating large structural variations using a single set of modal coordinates. This task was accomplished by basing the structural modal coordinates on normal modes calculated with a set of fictitious masses loading the locations of anticipated structural changes. The following subject areas are covered: (1) modal coordinates for aeroelastic analysis with large local structural variations; and (2) time simulation of flutter with large stiffness changes.

An investigation into non-invasive physical activity recognition using smartphones.

PubMed

Kelly, Daniel; Caulfield, Brian

2012-01-01

Technology utilized to automatically monitor Activities of Daily Living (ADL) could be a key component in identifying deviations from normal functional profiles and providing feedback on interventions aimed at improving health. However, if activity recognition systems are to be implemented in real world scenarios such as health and wellness monitoring, the activity sensing modality must unobtrusively fit the human environment rather than forcing humans to adhere to sensor specific conditions. Modern smart phones represent a ubiquitous computing device which has already undergone mainstream adoption. In this paper, we investigate the feasibility of using a modern smartphone, with limited placement constraints, as the sensing modality for an activity recognition system. A dataset of 4 subjects performing 7 activities, using varying sensor placement conditions, is utilized to investigate this. Initial experiments show that a decision tree classifier performs activity classification with precision and recall scores of 0.75 and 0.73 respectively. More importantly, as part of this initial experiment, 3 main problems, and subsequently 3 solutions, relating to unconstrained sensor placement were identified. Using our proposed solutions, classification precision and recall scores were improved by +13% and +14.6% respectively.

Integrating Iris and Signature Traits for Personal Authentication Using User-Specific Weighting

PubMed Central

Viriri, Serestina; Tapamo, Jules R.

2012-01-01

Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%. PMID:22666032

Imaging bio-distribution of a topically applied dermatological cream on minipig skin using fluorescence lifetime imaging microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Alex, Aneesh; Chaney, Eric J.; Criley, Jennifer M.; Spillman, Darold R.; Hutchison, Phaedra B.; Li, Joanne; Marjanovic, Marina; Frey, Steve; Cook, Steven; Boppart, Stephen A.; Arp, Zane A.

2017-02-01

Currently there is a lack of in vivo techniques to evaluate the spatial bio-distribution of dermal drugs over time without the need to take multiple serial biopsies. To address this gap, we investigated the use of multi-photon optical imaging methods to non-invasively track drug distribution on miniature pig (Species: Sus scrofa, Strain: Göttingen) skin in vivo. Minipig skin is the standard comparative research model to human skin, and is anatomically and functionally similar. We employed fluorescence lifetime imaging microscopy (FLIM) to visualize the spatial distribution and residency time of a topically applied experimental dermatological cream. This was made possible by the endogenous fluorescent optical properties of the experimental drug (fluorescence lifetime > 3000 ps). Two different drug formulations were applied on 2 minipigs for 7 consecutive days, with the control creams applied on the contralateral side, followed by 7 days of post-application monitoring using a multi-modal optical imaging system (MPTflex-CARS, JenLab, Germany). FLIM images were obtained from the treated regions 24 hr post-application from day 1 to day 14 that allowed visualization of cellular and sub-cellular features associated with different dermal layers non-invasively to a depth of 200 µm. Five punch biopsies per animal were obtained from the corresponding treated regions between days 8 and 14 for bioanalytical analysis and comparison with results obtained using FLIM. In conclusion, utilization of non-invasive optical biopsy methods for dermal drug evaluation can provide true longitudinal monitoring of drug spatial distribution, remove sampling limitations, and be more time-efficient compared to traditional methods.

Cross-Modal Correspondence Among Vision, Audition, and Touch in Natural Objects: An Investigation of the Perceptual Properties of Wood.

PubMed

Kanaya, Shoko; Kariya, Kenji; Fujisaki, Waka

2016-10-01

Certain systematic relationships are often assumed between information conveyed from multiple sensory modalities; for instance, a small figure and a high pitch may be perceived as more harmonious. This phenomenon, termed cross-modal correspondence, may result from correlations between multi-sensory signals learned in daily experience of the natural environment. If so, we would observe cross-modal correspondences not only in the perception of artificial stimuli but also in perception of natural objects. To test this hypothesis, we reanalyzed data collected previously in our laboratory examining perceptions of the material properties of wood using vision, audition, and touch. We compared participant evaluations of three perceptual properties (surface brightness, sharpness of sound, and smoothness) of the wood blocks obtained separately via vision, audition, and touch. Significant positive correlations were identified for all properties in the audition-touch comparison, and for two of the three properties regarding in the vision-touch comparison. By contrast, no properties exhibited significant positive correlations in the vision-audition comparison. These results suggest that we learn correlations between multi-sensory signals through experience; however, the strength of this statistical learning is apparently dependent on the particular combination of sensory modalities involved. © The Author(s) 2016.

Rapid fabricating technique for multi-layered human hepatic cell sheets by forceful contraction of the fibroblast monolayer.

PubMed

Sakai, Yusuke; Koike, Makiko; Hasegawa, Hideko; Yamanouchi, Kosho; Soyama, Akihiko; Takatsuki, Mitsuhisa; Kuroki, Tamotsu; Ohashi, Kazuo; Okano, Teruo; Eguchi, Susumu

2013-01-01

Cell sheet engineering is attracting attention from investigators in various fields, from basic research scientists to clinicians focused on regenerative medicine. However, hepatocytes have a limited proliferation potential in vitro, and it generally takes a several days to form a sheet morphology and multi-layered sheets. We herein report our rapid and efficient technique for generating multi-layered human hepatic cell (HepaRG® cell) sheets using pre-cultured fibroblast monolayers derived from human skin (TIG-118 cells) as a feeder layer on a temperature-responsive culture dish. Multi-layered TIG-118/HepaRG cell sheets with a thick morphology were harvested on day 4 of culturing HepaRG cells by forceful contraction of the TIG-118 cells, and the resulting sheet could be easily handled. In addition, the human albumin and alpha 1-antitrypsin synthesis activities of TIG-118/HepaRG cells were approximately 1.2 and 1.3 times higher than those of HepaRG cells, respectively. Therefore, this technique is considered to be a promising modality for rapidly fabricating multi-layered human hepatocyte sheets from cells with limited proliferation potential, and the engineered cell sheet could be used for cell transplantation with highly specific functions.

New bone post-processing tools in forensic imaging: a multi-reader feasibility study to evaluate detection time and diagnostic accuracy in rib fracture assessment.

PubMed

Glemser, Philip A; Pfleiderer, Michael; Heger, Anna; Tremper, Jan; Krauskopf, Astrid; Schlemmer, Heinz-Peter; Yen, Kathrin; Simons, David

2017-03-01

The aim of this multi-reader feasibility study was to evaluate new post-processing CT imaging tools in rib fracture assessment of forensic cases by analyzing detection time and diagnostic accuracy. Thirty autopsy cases (20 with and 10 without rib fractures in autopsy) were randomly selected and included in this study. All cases received a native whole body CT scan prior to the autopsy procedure, which included dissection and careful evaluation of each rib. In addition to standard transverse sections (modality A), CT images were subjected to a reconstruction algorithm to compute axial labelling of the ribs (modality B) as well as "unfolding" visualizations of the rib cage (modality C, "eagle tool"). Three radiologists with different clinical and forensic experience who were blinded to autopsy results evaluated all cases in a random manner of modality and case. Rib fracture assessment of each reader was evaluated compared to autopsy and a CT consensus read as radiologic reference. A detailed evaluation of relevant test parameters revealed a better accordance to the CT consensus read as to the autopsy. Modality C was the significantly quickest rib fracture detection modality despite slightly reduced statistic test parameters compared to modalities A and B. Modern CT post-processing software is able to shorten reading time and to increase sensitivity and specificity compared to standard autopsy alone. The eagle tool as an easy to use tool is suited for an initial rib fracture screening prior to autopsy and can therefore be beneficial for forensic pathologists.

Multi-modal anatomical optical coherence tomography and CT for in vivo dynamic upper airway imaging

NASA Astrophysics Data System (ADS)

Balakrishnan, Santosh; Bu, Ruofei; Price, Hillel; Zdanski, Carlton; Oldenburg, Amy L.

2017-02-01

We describe a novel, multi-modal imaging protocol for validating quantitative dynamic airway imaging performed using anatomical Optical Coherence Tomography (aOCT). The aOCT system consists of a catheter-based aOCT probe that is deployed via a bronchoscope, while a programmable ventilator is used to control airway pressure. This setup is employed on the bed of a Siemens Biograph CT system capable of performing respiratory-gated acquisitions. In this arrangement the position of the aOCT catheter may be visualized with CT to aid in co-registration. Utilizing this setup we investigate multiple respiratory pressure parameters with aOCT, and respiratory-gated CT, on both ex vivo porcine trachea and live, anesthetized pigs. This acquisition protocol has enabled real-time measurement of airway deformation with simultaneous measurement of pressure under physiologically relevant static and dynamic conditions- inspiratory peak or peak positive airway pressures of 10-40 cm H2O, and 20-30 breaths per minute for dynamic studies. We subsequently compare the airway cross sectional areas (CSA) obtained from aOCT and CT, including the change in CSA at different stages of the breathing cycle for dynamic studies, and the CSA at different peak positive airway pressures for static studies. This approach has allowed us to improve our acquisition methodology and to validate aOCT measurements of the dynamic airway for the first time. We believe that this protocol will prove invaluable for aOCT system development and greatly facilitate translation of OCT systems for airway imaging into the clinical setting.

Multi-instance multi-label distance metric learning for genome-wide protein function prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Song, Hengjie; Wu, Qingyao

2016-08-01

Multi-instance multi-label (MIML) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with not only multiple instances but also multiple class labels. To find an appropriate MIML learning method for genome-wide protein function prediction, many studies in the literature attempted to optimize objective functions in which dissimilarity between instances is measured using the Euclidean distance. But in many real applications, Euclidean distance may be unable to capture the intrinsic similarity/dissimilarity in feature space and label space. Unlike other previous approaches, in this paper, we propose to learn a multi-instance multi-label distance metric learning framework (MIMLDML) for genome-wide protein function prediction. Specifically, we learn a Mahalanobis distance to preserve and utilize the intrinsic geometric information of both feature space and label space for MIML learning. In addition, we try to deal with the sparsely labeled data by giving weight to the labeled data. Extensive experiments on seven real-world organisms covering the biological three-domain system (i.e., archaea, bacteria, and eukaryote; Woese et al., 1990) show that the MIMLDML algorithm is superior to most state-of-the-art MIML learning algorithms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Designing Microstructures/Structures for Desired Functional Material and Local Fields

DTIC Science & Technology

2015-12-02

utilized to engineer multifunctional soft materials for multi-sensing, multi- actuating , human-machine interfaces. [3] Establish a theoretical framework...model for surface elasticity, (ii) derived a new type of Maxwell stress in soft materials due to quantum mechanical-elasticity coupling and...elucidated its ramification in engineering multifunctional soft materials, and (iii) demonstrated the possibility of concurrent magnetoelectricity and

The assessment of function. Part II: clinical perspective of a javelin thrower with low back and groin pain

PubMed Central

Reiman, Michael P; Manske, Robert C

2012-01-01

Assessment of an individual’s functional ability can be complex. This assessment should also be individualized and adaptable to changes in functional status. In the first article of this series, we operationally defined function, discussed the construct of function, examined the evidence as it relates to assessment methods of various aspects of function, and explored the multi-dimensional nature of the concept of function. In this case report, we aim to demonstrate the utilization of a multi-dimensional assessment method (functional performance testing) as it relates to a high-level athlete presenting with pain in the low back and groin. It is our intent to demonstrate how the clinician should continually adapt their assessment dependent on the current functional abilities of the patients. PMID:23633887

Efficacy of a modern neuroscience approach versus usual care evidence-based physiotherapy on pain, disability and brain characteristics in chronic spinal pain patients: protocol of a randomized clinical trial

PubMed Central

2014-01-01

Background Among the multiple conservative modalities, physiotherapy is a commonly utilized treatment modality in managing chronic non-specific spinal pain. Despite the scientific progresses with regard to pain and motor control neuroscience, treatment of chronic spinal pain (CSP) often tends to stick to a peripheral biomechanical model, without targeting brain mechanisms. With a view to enhance clinical efficacy of existing physiotherapeutic treatments for CSP, the development of clinical strategies targeted at ‘training the brain’ is to be pursued. Promising proof-of-principle results have been reported for the effectiveness of a modern neuroscience approach to CSP when compared to usual care, but confirmation is required in a larger, multi-center trial with appropriate evidence-based control intervention and long-term follow-up. The aim of this study is to assess the effectiveness of a modern neuroscience approach, compared to usual care evidence-based physiotherapy, for reducing pain and improving functioning in patients with CSP. A secondary objective entails examining the effectiveness of the modern neuroscience approach versus usual care physiotherapy for normalizing brain gray matter in patients with CSP. Methods/Design The study is a multi-center, triple-blind, two-arm (1:1) randomized clinical trial with 1-year follow-up. 120 CSP patients will be randomly allocated to either the experimental (receiving pain neuroscience education followed by cognition-targeted motor control training) or the control group (receiving usual care physiotherapy), each comprising of 3 months treatment. The main outcome measures are pain (including symptoms and indices of central sensitization) and self-reported disability. Secondary outcome measures include brain gray matter structure, motor control, muscle properties, and psychosocial correlates. Clinical assessment and brain imaging will be performed at baseline, post-treatment and at 1-year follow-up. Web-based questionnaires will be completed at baseline, after the first 3 treatment sessions, post-treatment, and at 6 and 12-months follow-up. Discussion Findings may provide empirical evidence on: (1) the effectiveness of a modern neuroscience approach to CSP for reducing pain and improving functioning, (2) the effectiveness of a modern neuroscience approach for normalizing brain gray matter in CSP patients, and (3) factors associated with therapy success. Hence, this trial might contribute towards refining guidelines for good clinical practice and might be used as a basis for health authorities’ recommendations. Trial registration ClinicalTrials.gov Identifier: NCT02098005. PMID:24885889

Multimodal 3D cancer-mimicking optical phantom

PubMed Central

Smith, Gennifer T.; Lurie, Kristen L.; Zlatev, Dimitar V.; Liao, Joseph C.; Ellerbee Bowden, Audrey K.

2016-01-01

Three-dimensional (3D) organ-mimicking phantoms provide realistic imaging environments for testing various aspects of optical systems, including for evaluating new probe designs, characterizing the diagnostic potential of new technologies, and assessing novel image processing algorithms prior to validation in real tissue. We introduce and characterize the use of a new material, Dragon Skin (Smooth-On Inc.), and fabrication technique, air-brushing, for fabrication of a 3D phantom that mimics the appearance of a real organ under multiple imaging modalities. We demonstrate the utility of the material and technique by fabricating the first 3D, hollow bladder phantom with realistic normal and multi-stage pathology features suitable for endoscopic detection using the gold standard imaging technique, white light cystoscopy (WLC), as well as the complementary imaging modalities of optical coherence tomography and blue light cystoscopy, which are aimed at improving the sensitivity and specificity of WLC to bladder cancer detection. The flexibility of the material and technique used for phantom construction allowed for the representation of a wide range of diseased tissue states, ranging from inflammation (benign) to high-grade cancerous lesions. Such phantoms can serve as important tools for trainee education and evaluation of new endoscopic instrumentation. PMID:26977369

Linear fitting of multi-threshold counting data with a pixel-array detector for spectral X-ray imaging

PubMed Central

Muir, Ryan D.; Pogranichney, Nicholas R.; Muir, J. Lewis; Sullivan, Shane Z.; Battaile, Kevin P.; Mulichak, Anne M.; Toth, Scott J.; Keefe, Lisa J.; Simpson, Garth J.

2014-01-01

Experiments and modeling are described to perform spectral fitting of multi-threshold counting measurements on a pixel-array detector. An analytical model was developed for describing the probability density function of detected voltage in X-ray photon-counting arrays, utilizing fractional photon counting to account for edge/corner effects from voltage plumes that spread across multiple pixels. Each pixel was mathematically calibrated by fitting the detected voltage distributions to the model at both 13.5 keV and 15.0 keV X-ray energies. The model and established pixel responses were then exploited to statistically recover images of X-ray intensity as a function of X-ray energy in a simulated multi-wavelength and multi-counting threshold experiment. PMID:25178010

Linear fitting of multi-threshold counting data with a pixel-array detector for spectral X-ray imaging.

PubMed

Muir, Ryan D; Pogranichney, Nicholas R; Muir, J Lewis; Sullivan, Shane Z; Battaile, Kevin P; Mulichak, Anne M; Toth, Scott J; Keefe, Lisa J; Simpson, Garth J

2014-09-01

Experiments and modeling are described to perform spectral fitting of multi-threshold counting measurements on a pixel-array detector. An analytical model was developed for describing the probability density function of detected voltage in X-ray photon-counting arrays, utilizing fractional photon counting to account for edge/corner effects from voltage plumes that spread across multiple pixels. Each pixel was mathematically calibrated by fitting the detected voltage distributions to the model at both 13.5 keV and 15.0 keV X-ray energies. The model and established pixel responses were then exploited to statistically recover images of X-ray intensity as a function of X-ray energy in a simulated multi-wavelength and multi-counting threshold experiment.

Contrasting Olfaction, Vision, and Audition as Predictors of Cognitive Change and Impairment in Non-Demented Older Adults

PubMed Central

MacDonald, Stuart W.S.; Keller, Connor J.C.; Brewster, Paul W.H.; Dixon, Roger A.

2017-01-01

Objective This study examines the relative utility of a particular class of non-invasive functional biomarkers -- sensory functions -- for detecting those at risk of cognitive decline and impairment. Three central research objectives were examined including whether: (1) olfactory function, vision, and audition exhibited significant longitudinal declines in non-demented older adults, (2) multi-wave change for these sensory function indicators predicted risk of mild cognitive impairment, and (3) change within persons for each sensory measure shared dynamic time-varying associations with within-person change in cognitive functioning. Method A longitudinal sample (n=408) from the Victoria Longitudinal Study was assembled. Three cognitive status subgroups were identified: not impaired cognitively (NIC), single assessment mild cognitive impairment (SA-MCI), and multiple assessment mild cognitive impairment (MA-MCI). Results We tested independent predictive associations, contrasting change in sensory function as predictors of cognitive decline and impairment, utilizing both linear mixed models and logistic regression analysis. Olfaction and, to a lesser extent, vision were identified as the most robust predictors of cognitive status and decline; audition showed little predictive influence. Conclusions These findings underscore the potential utility of deficits in olfactory function, in particular, as an early marker of age- and pathology-related cognitive decline. Functional biomarkers may represent potential candidates for use in the early stages of a multi-step screening approach for detecting those at risk of cognitive impairment, as well as for targeted intervention. PMID:29809033

Photogrammetry Toolbox Reference Manual

NASA Technical Reports Server (NTRS)

Liu, Tianshu; Burner, Alpheus W.

2014-01-01

Specialized photogrammetric and image processing MATLAB functions useful for wind tunnel and other ground-based testing of aerospace structures are described. These functions include single view and multi-view photogrammetric solutions, basic image processing to determine image coordinates, 2D and 3D coordinate transformations and least squares solutions, spatial and radiometric camera calibration, epipolar relations, and various supporting utility functions.

Multi-modal spectroscopic imaging with synchrotron light to study mechanisms of brain disease

NASA Astrophysics Data System (ADS)

Summers, Kelly L.; Fimognari, Nicholas; Hollings, Ashley; Kiernan, Mitchell; Lam, Virginie; Tidy, Rebecca J.; Takechi, Ryu; George, Graham N.; Pickering, Ingrid J.; Mamo, John C.; Harris, Hugh H.; Hackett, Mark J.

2017-04-01

The international health care costs associated with Alzheimer's disease (AD) and dementia have been predicted to reach $2 trillion USD by 2030. As such, there is urgent need to develop new treatments and diagnostic methods to stem an international health crisis. A major limitation to therapy and diagnostic development is the lack of complete understanding about the disease mechanisms. Spectroscopic methods at synchrotron light sources, such as FTIR, XRF, and XAS, offer a "multi-modal imaging platform" to reveal a wealth of important biochemical information in situ within ex vivo tissue sections, to increase our understanding of disease mechanisms.

Results from the commissioning of a multi-modal endoscope for ultrasound and time of flight PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bugalho, Ricardo

2015-07-01

The EndoTOFPET-US collaboration has developed a multi-modal imaging system combining Ultrasound with Time-of-Flight Positron Emission Tomography into an endoscopic imaging device. The objective of the project is to obtain a coincidence time resolution of about 200 ps FWHM and to achieve about 1 mm spatial resolution of the PET system, while integrating all the components in a very compact detector suitable for endoscopic use. This scanner aims to be exploited for diagnostic and surgical oncology, as well as being instrumental in the clinical test of new biomarkers especially targeted for prostate and pancreatic cancer. (authors)

Multi-detector CT imaging in the postoperative orthopedic patient with metal hardware.

PubMed

Vande Berg, Bruno; Malghem, Jacques; Maldague, Baudouin; Lecouvet, Frederic

2006-12-01

Multi-detector CT imaging (MDCT) becomes routine imaging modality in the assessment of the postoperative orthopedic patients with metallic instrumentation that degrades image quality at MR imaging. This article reviews the physical basis and CT appearance of such metal-related artifacts. It also addresses the clinical value of MDCT in postoperative orthopedic patients with emphasis on fracture healing, spinal fusion or arthrodesis, and joint replacement. MDCT imaging shows limitations in the assessment of the bone marrow cavity and of the soft tissues for which MR imaging remains the imaging modality of choice despite metal-related anatomic distortions and signal alteration.

Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.

PubMed

Argelaguet, Ricard; Velten, Britta; Arnol, Damien; Dietrich, Sascha; Zenz, Thorsten; Marioni, John C; Buettner, Florian; Huber, Wolfgang; Stegle, Oliver

2018-06-20

Multi-omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi-Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi-omics data sets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy-chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single-cell multi-omics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

PubMed

Gerhard, Stephan; Daducci, Alessandro; Lemkaddem, Alia; Meuli, Reto; Thiran, Jean-Philippe; Hagmann, Patric

2011-01-01

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech

PubMed Central

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances. PMID:26925010

The Connectome Viewer Toolkit: An Open Source Framework to Manage, Analyze, and Visualize Connectomes

PubMed Central

Gerhard, Stephan; Daducci, Alessandro; Lemkaddem, Alia; Meuli, Reto; Thiran, Jean-Philippe; Hagmann, Patric

2011-01-01

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit – a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/ PMID:21713110

A multi-modal training programme to improve physical activity, physical fitness and perceived physical ability in obese children.

PubMed

Morano, Milena; Colella, Dario; Rutigliano, Irene; Fiore, Pietro; Pettoello-Mantovani, Massimo; Campanozzi, Angelo

2014-01-01

Actual and perceived physical abilities are important correlates of physical activity (PA) and fitness, but little research has explored these relationships over time in obese children. This study was designed: (a) to assess the feasibility of a multi-modal training programme promoting changes in PA, fundamental motor skills and real and perceived physical abilities of obese children; and (b) to explore cross-sectional and longitudinal relationships between real and perceived physical competence in boys and girls. Forty-one participants (9.2 ± 1.2 years) were assessed before and after an 8-month intervention with respect to body composition, physical fitness, self-reported PA and perceived physical ability. After treatment, obese children reported improvements in the body mass index, PA levels, gross motor performance and actual and perceived physical abilities. Real and perceived physical competence was correlated in boys, but not in girls. Results indicate that a multi-modal programme focused on actual and perceived physical competence as associated with the gradual increase in the volume of activity might be an effective strategy to improve adherence of the participants and to increase the lifelong exercise skills of obese children.

Enhancing image classification models with multi-modal biomarkers

NASA Astrophysics Data System (ADS)

Caban, Jesus J.; Liao, David; Yao, Jianhua; Mollura, Daniel J.; Gochuico, Bernadette; Yoo, Terry

2011-03-01

Currently, most computer-aided diagnosis (CAD) systems rely on image analysis and statistical models to diagnose, quantify, and monitor the progression of a particular disease. In general, CAD systems have proven to be effective at providing quantitative measurements and assisting physicians during the decision-making process. As the need for more flexible and effective CADs continues to grow, questions about how to enhance their accuracy have surged. In this paper, we show how statistical image models can be augmented with multi-modal physiological values to create more robust, stable, and accurate CAD systems. In particular, this paper demonstrates how highly correlated blood and EKG features can be treated as biomarkers and used to enhance image classification models designed to automatically score subjects with pulmonary fibrosis. In our results, a 3-5% improvement was observed when comparing the accuracy of CADs that use multi-modal biomarkers with those that only used image features. Our results show that lab values such as Erythrocyte Sedimentation Rate and Fibrinogen, as well as EKG measurements such as QRS and I:40, are statistically significant and can provide valuable insights about the severity of the pulmonary fibrosis disease.

Smoking Cessation: Uni-Modal and Multi-Modal Hypnotic and Non-Hypnotic Approaches.

ERIC Educational Resources Information Center

Habicht, Manuela H.

A survey of Queensland's population in 1993 determined that 24% of the adults were smokers. National data compiled in 1992 indicated that 72% of the drug-related deaths were related to tobacco use. In light of the need for effective smoking cessation approaches, a literature review was undertaken to determine the efficacy of hypnotic and…

77 FR 20097 - Intent To Prepare an Environmental Impact Statement for the Georgia Multi-Modal Passenger Terminal

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-03

... Smart, Federal Transit Administration, 230 Peachtree Street NW., Suite 800, Atlanta, GA 30327. Telephone: 404-865-5607. Email: brian.smart@dot.gov . SUPPLEMENTARY INFORMATION: In accordance with Section 6002...-city, regional and local modal services. At the same time, the Gulch creates a large void in the...

Separation of fNIRS Signals into Functional and Systemic Components Based on Differences in Hemodynamic Modalities

PubMed Central

Yamada, Toru; Umeyama, Shinji; Matsuda, Keiji

2012-01-01

In conventional functional near-infrared spectroscopy (fNIRS), systemic physiological fluctuations evoked by a body's motion and psychophysiological changes often contaminate fNIRS signals. We propose a novel method for separating functional and systemic signals based on their hemodynamic differences. Considering their physiological origins, we assumed a negative and positive linear relationship between oxy- and deoxyhemoglobin changes of functional and systemic signals, respectively. Their coefficients are determined by an empirical procedure. The proposed method was compared to conventional and multi-distance NIRS. The results were as follows: (1) Nonfunctional tasks evoked substantial oxyhemoglobin changes, and comparatively smaller deoxyhemoglobin changes, in the same direction by conventional NIRS. The systemic components estimated by the proposed method were similar to the above finding. The estimated functional components were very small. (2) During finger-tapping tasks, laterality in the functional component was more distinctive using our proposed method than that by conventional fNIRS. The systemic component indicated task-evoked changes, regardless of the finger used to perform the task. (3) For all tasks, the functional components were highly coincident with signals estimated by multi-distance NIRS. These results strongly suggest that the functional component obtained by the proposed method originates in the cerebral cortical layer. We believe that the proposed method could improve the reliability of fNIRS measurements without any modification in commercially available instruments. PMID:23185590

Medical information, communication, and archiving system (MICAS): Phase II integration and acceptance testing

NASA Astrophysics Data System (ADS)

Smith, Edward M.; Wandtke, John; Robinson, Arvin E.

1999-07-01

The Medical Information, Communication and Archive System (MICAS) is a multi-modality integrated image management system that is seamlessly integrated with the Radiology Information System (RIS). This project was initiated in the summer of 1995 with the first phase being installed during the first half of 1997 and the second phase installed during the summer of 1998. Phase II enhancements include a permanent archive, automated workflow including modality worklist, study caches, NT diagnostic workstations with all components adhering to Digital Imaging and Communications in Medicine (DICOM) standards. This multi-vendor phased approach to PACS implementation is designed as an enterprise-wide PACS to provide images and reports throughout our healthcare network. MICAS demonstrates that aa multi-vendor open system phased approach to PACS is feasible, cost-effective, and has significant advantages over a single vendor implementation.

Joint modality fusion and temporal context exploitation for semantic video analysis

NASA Astrophysics Data System (ADS)

Papadopoulos, Georgios Th; Mezaris, Vasileios; Kompatsiaris, Ioannis; Strintzis, Michael G.

2011-12-01

In this paper, a multi-modal context-aware approach to semantic video analysis is presented. Overall, the examined video sequence is initially segmented into shots and for every resulting shot appropriate color, motion and audio features are extracted. Then, Hidden Markov Models (HMMs) are employed for performing an initial association of each shot with the semantic classes that are of interest separately for each modality. Subsequently, a graphical modeling-based approach is proposed for jointly performing modality fusion and temporal context exploitation. Novelties of this work include the combined use of contextual information and multi-modal fusion, and the development of a new representation for providing motion distribution information to HMMs. Specifically, an integrated Bayesian Network is introduced for simultaneously performing information fusion of the individual modality analysis results and exploitation of temporal context, contrary to the usual practice of performing each task separately. Contextual information is in the form of temporal relations among the supported classes. Additionally, a new computationally efficient method for providing motion energy distribution-related information to HMMs, which supports the incorporation of motion characteristics from previous frames to the currently examined one, is presented. The final outcome of this overall video analysis framework is the association of a semantic class with every shot. Experimental results as well as comparative evaluation from the application of the proposed approach to four datasets belonging to the domains of tennis, news and volleyball broadcast video are presented.

Whole-body diffusion-weighted MR image stitching and alignment to anatomical MRI

NASA Astrophysics Data System (ADS)

Ceranka, Jakub; Polfliet, Mathias; Lecouvet, Frederic; Michoux, Nicolas; Vandemeulebroucke, Jef

2017-02-01

Whole-body diffusion-weighted (WB-DW) MRI in combination with anatomical MRI has shown a great poten- tial in bone and soft tissue tumour detection, evaluation of lymph nodes and treatment response assessment. Because of the vast body coverage, whole-body MRI is acquired in separate stations, which are subsequently combined into a whole-body image. However, inter-station and inter-modality image misalignments can occur due to image distortions and patient motion during acquisition, which may lead to inaccurate representations of patient anatomy and hinder visual assessment. Automated and accurate whole-body image formation and alignment of the multi-modal MRI images is therefore crucial. We investigated several registration approaches for the formation or stitching of the whole-body image stations, followed by a deformable alignment of the multi- modal whole-body images. We compared a pairwise approach, where diffusion-weighted (DW) image stations were sequentially aligned to a reference station (pelvis), to a groupwise approach, where all stations were simultaneously mapped to a common reference space while minimizing the overall transformation. For each, a choice of input images and corresponding metrics was investigated. Performance was evaluated by assessing the quality of the obtained whole-body images, and by verifying the accuracy of the alignment with whole-body anatomical sequences. The groupwise registration approach provided the best compromise between the formation of WB- DW images and multi-modal alignment. The fully automated method was found to be robust, making its use in the clinic feasible.

Investigating common coding of observed and executed actions in the monkey brain using cross-modal multi-variate fMRI classification.

PubMed

Fiave, Prosper Agbesi; Sharma, Saloni; Jastorff, Jan; Nelissen, Koen

2018-05-19

Mirror neurons are generally described as a neural substrate hosting shared representations of actions, by simulating or 'mirroring' the actions of others onto the observer's own motor system. Since single neuron recordings are rarely feasible in humans, it has been argued that cross-modal multi-variate pattern analysis (MVPA) of non-invasive fMRI data is a suitable technique to investigate common coding of observed and executed actions, allowing researchers to infer the presence of mirror neurons in the human brain. In an effort to close the gap between monkey electrophysiology and human fMRI data with respect to the mirror neuron system, here we tested this proposal for the first time in the monkey. Rhesus monkeys either performed reach-and-grasp or reach-and-touch motor acts with their right hand in the dark or observed videos of human actors performing similar motor acts. Unimodal decoding showed that both executed or observed motor acts could be decoded from numerous brain regions. Specific portions of rostral parietal, premotor and motor cortices, previously shown to house mirror neurons, in addition to somatosensory regions, yielded significant asymmetric action-specific cross-modal decoding. These results validate the use of cross-modal multi-variate fMRI analyses to probe the representations of own and others' actions in the primate brain and support the proposed mapping of others' actions onto the observer's own motor cortices. Copyright © 2018 Elsevier Inc. All rights reserved.

Prevention of Serious Conduct Problems in Youth with Attention Deficit/Hyperactivity Disorder

PubMed Central

Villodas, Miguel T.; Pfiffner, Linda J.; McBurnett, Keith

2013-01-01

The purpose of this review is to discuss issues in the prevention of serious conduct problems among children and adolescents with Attention Deficit/Hyperactivity Disorder (ADHD). We begin by reviewing research on the common genetic and environmental etiological factors, developmental trajectories, characteristics, and impairments associated with ADHD and comorbid Oppositional Defiant and Conduct Disorders. Next, we present empirically-based models for intervention with children and adolescents with ADHD that are at risk of developing serious conduct problems and detail the evidence supporting these models. Researchers have demonstrated the utility of medication and psychosocial intervention approaches to treat youth with these problems, but current evidence appears to support the superiority of multi-modal treatments that include both approaches. Future directions for researchers are discussed. PMID:23082741

The utility of visual analogs of central auditory tests in the differential diagnosis of (central) auditory processing disorder and attention deficit hyperactivity disorder.

PubMed

Bellis, Teri James; Billiet, Cassie; Ross, Jody

2011-09-01

Cacace and McFarland (2005) have suggested that the addition of cross-modal analogs will improve the diagnostic specificity of (C)APD (central auditory processing disorder) by ensuring that deficits observed are due to the auditory nature of the stimulus and not to supra-modal or other confounds. Others (e.g., Musiek et al, 2005) have expressed concern about the use of such analogs in diagnosing (C)APD given the uncertainty as to the degree to which cross-modal measures truly are analogous and emphasize the nonmodularity of the CANs (central auditory nervous system) and its function, which precludes modality specificity of (C)APD. To date, no studies have examined the clinical utility of cross-modal (e.g., visual) analogs of central auditory tests in the differential diagnosis of (C)APD. This study investigated performance of children diagnosed with (C)APD, children diagnosed with ADHD (attention deficit hyperactivity disorder), and typically developing children on three diagnostic tests of central auditory function and their corresponding visual analogs. The study sought to determine whether deficits observed in the (C)APD group were restricted to the auditory modality and the degree to which the addition of visual analogs aids in the ability to differentiate among groups. An experimental repeated measures design was employed. Participants consisted of three groups of right-handed children (normal control, n=10; ADHD, n=10; (C)APD, n=7) with normal and symmetrical hearing sensitivity, normal or corrected-to-normal visual acuity, and no family or personal history of disorders unrelated to their primary diagnosis. Participants in Groups 2 and 3 met current diagnostic criteria for ADHD and (C)APD. Visual analogs of three tests in common clinical use for the diagnosis of (C)APD were used (Dichotic Digits [Musiek, 1983]; Frequency Patterns [Pinheiro and Ptacek, 1971]; and Duration Patterns [Pinheiro and Musiek, 1985]). Participants underwent two 1 hr test sessions separated by at least 1 wk. Order of sessions (auditory, visual) and tests within each session were counterbalanced across participants. ANCOVAs (analyses of covariance) were used to examine effects of group, modality, and laterality (Dichotic/Dichoptic Digits) or response condition (auditory and visual patterning). In addition, planned univariate ANCOVAs were used to examine effects of group on intratest comparison measures (REA, HLD [Humming-Labeling Differential]). Children with both ADHD and (C)APD performed more poorly overall than typically developing children on all tasks, with the (C)APD group exhibiting the poorest performance on the auditory and visual patterns tests but the ADHD and (C)APD group performing similarly on the Dichotic/Dichoptic Digits task. However, each of the auditory and visual intratest comparison measures, when taken individually, was able to distinguish the (C)APD group from both the normal control and ADHD groups, whose performance did not differ from one another. Results underscore the importance of intratest comparison measures in the interpretation of central auditory tests (American Speech-Language-Hearing Association [ASHA], 2005 ; American Academy of Audiology [AAA], 2010). Results also support the "non-modular" view of (C)APD in which cross-modal deficits would be predicted based on shared neuroanatomical substrates. Finally, this study demonstrates that auditory tests alone are sufficient to distinguish (C)APD from supra-modal disorders, with cross-modal analogs adding little if anything to the differential diagnostic process. American Academy of Audiology.

[Who benefits from systemic therapy with a reflecting team?].

PubMed

Höger, C; Temme, M; Geiken, G

1994-03-01

In an evaluation study we investigated the effectiveness of the reflecting team approach compared to eclectic child psychiatric treatment in an outpatient setting and the indications for each type of treatment. The relationship between treatment outcome and diagnostic data obtained with the Multi-axial Classification Scheme was examined in 22 families treated with the reflecting team approach and in a second group of families matched on all important sociodemographic and diagnostic variables but receiving eclectic treatment. No difference was found between the two groups regarding symptom improvement or changes in family functioning. Regarding satisfaction with treatment, the reflecting team approach was superior to the eclectic modality. In the reflecting team group parental mental disorder and inadequate intra-familial communication (according to the new fifth axis of the Multi-axial Classification Scheme) had a negative effect on outcome.

Intraoperative utilization of advanced imaging modalities in a complex kidney stone case: a pilot case study.

PubMed

Christiansen, Andrew R; Shorti, Rami M; Smith, Cory D; Prows, William C; Bishoff, Jay T

2018-05-01

Despite the increasing use of advanced 3D imaging techniques and 3D printing, these techniques have not yet been comprehensively compared in a surgical setting. The purpose of this study is to explore the effectiveness of five different advanced imaging modalities during a complex renal surgical procedure. A patient with a horseshoe kidney and multiple large, symptomatic stones that had failed Extracorporeal Shock Wave Lithotripsy (ESWL) and ureteroscopy treatment was used for this evaluation. CT data were used to generate five different imaging modalities, including a 3D printed model, three different volume rendered models, and a geometric CAD model. A survey was used to evaluate the quality and breadth of the imaging modalities during four different phases of the laparoscopic procedure. In the case of a complex kidney procedure, the CAD model, 3D print, volume render on an autostereoscopic 3D display, interactive and basic volume render models demonstrated added insight and complemented the surgical procedure. CAD manual segmentation allowed tissue layers and/or kidney stones to be made colorful and semi-transparent, allowing easier navigation through abnormal vasculature. The 3D print allowed for simultaneous visualization of renal pelvis and surrounding vasculature. Our preliminary exploration indicates that various advanced imaging modalities, when properly utilized and supported during surgery, can be useful in complementing the CT data and laparoscopic display. This study suggests that various imaging modalities, such as ones utilized in this case, can be beneficial intraoperatively depending on the surgical step involved and may be more helpful than 3D printed models. We also present factors to consider when evaluating advanced imaging modalities during complex surgery.

Multi-test cervical cancer diagnosis with missing data estimation

NASA Astrophysics Data System (ADS)

Xu, Tao; Huang, Xiaolei; Kim, Edward; Long, L. Rodney; Antani, Sameer

2015-03-01

Cervical cancer is a leading most common type of cancer for women worldwide. Existing screening programs for cervical cancer suffer from low sensitivity. Using images of the cervix (cervigrams) as an aid in detecting pre-cancerous changes to the cervix has good potential to improve sensitivity and help reduce the number of cervical cancer cases. In this paper, we present a method that utilizes multi-modality information extracted from multiple tests of a patient's visit to classify the patient visit to be either low-risk or high-risk. Our algorithm integrates image features and text features to make a diagnosis. We also present two strategies to estimate the missing values in text features: Image Classifier Supervised Mean Imputation (ICSMI) and Image Classifier Supervised Linear Interpolation (ICSLI). We evaluate our method on a large medical dataset and compare it with several alternative approaches. The results show that the proposed method with ICSLI strategy achieves the best result of 83.03% specificity and 76.36% sensitivity. When higher specificity is desired, our method can achieve 90% specificity with 62.12% sensitivity.

Methods to mitigate data truncation artifacts in multi-contrast tomosynthesis image reconstructions

NASA Astrophysics Data System (ADS)

Garrett, John; Ge, Yongshuai; Li, Ke; Chen, Guang-Hong

2015-03-01

Differential phase contrast imaging is a promising new image modality that utilizes the refraction rather than the absorption of x-rays to image an object. A Talbot-Lau interferometer may be used to permit differential phase contrast imaging with a conventional medical x-ray source and detector. However, the current size of the gratings fabricated for these interferometers are often relatively small. As a result, data truncation image artifacts are often observed in a tomographic acquisition and reconstruction. When data are truncated in x-ray absorption imaging, the methods have been introduced to mitigate the truncation artifacts. However, the same strategy to mitigate absorption truncation artifacts may not be appropriate for differential phase contrast or dark field tomographic imaging. In this work, several new methods to mitigate data truncation artifacts in a multi-contrast imaging system have been proposed and evaluated for tomosynthesis data acquisitions. The proposed methods were validated using experimental data acquired for a bovine udder as well as several cadaver breast specimens using a benchtop system at our facility.

Preclinical Evaluation of Novel Dendritic Cell-Based Prostate Cancer Vaccines

DTIC Science & Technology

2008-01-01

relative to other activation modalities(1). Hence the chimeric CD40 was named inducible CD40 (iCD40). The high utility of iCD40-activated DCs (iCD40...recent published (1) studies have suggested a new method to promote DC function in vivo, manipulation of a chimeric inducible CD40. While we have...number of HLA alleles using peptide candidate approach. This precluded the development of immunoassays for direct measurements of PSMA-specific Th

ON THE BIOMECHANICS OF HEART VALVE FUNCTION

PubMed Central

Sacks, Michael S.; Merryman, W. David; Schmidt, David E.

2009-01-01

Heart valves (HVs) are fluidic control components of the heart that ensure unidirectional blood flow during the cardiac cycle. However, this description does not adequately describe the biomechanical ramifications of their function in that their mechanics are multi-modal. Moreover, they must replicate their cyclic function over an entire lifetime, with an estimated total functional demand of least 3×109 cycles. The focus of the present review is on the functional biomechanics of heart valves. Thus, the focus of the present review is on functional biomechanics, referring primarily to biosolid as well as several key biofluid mechanical aspects underlying heart valve physiological function. Specifically, we refer to the mechanical behaviors of the extra-cellular matrix structural proteins, underlying cellular function, and their integrated relation to the major aspects of valvular hemodynamic function. While we focus on the work from the author’s laboratories, relevant works of other investigators have been included whenever appropriate. We conclude with a summary of important future trends. PMID:19540499

Endocrine radionuclide scintigraphy with fusion single photon emission computed tomography/computed tomography

PubMed Central

Wong, Ka-Kit; Gandhi, Arpit; Viglianti, Benjamin L; Fig, Lorraine M; Rubello, Domenico; Gross, Milton D

2016-01-01

AIM: To review the benefits of single photon emission computed tomography (SPECT)/computed tomography (CT) hybrid imaging for diagnosis of various endocrine disorders. METHODS: We performed MEDLINE and PubMed searches using the terms: “SPECT/CT”; “functional anatomic mapping”; “transmission emission tomography”; “parathyroid adenoma”; “thyroid cancer”; “neuroendocrine tumor”; “adrenal”; “pheochromocytoma”; “paraganglioma”; in order to identify relevant articles published in English during the years 2003 to 2015. Reference lists from the articles were reviewed to identify additional pertinent articles. Retrieved manuscripts (case reports, reviews, meta-analyses and abstracts) concerning the application of SPECT/CT to endocrine imaging were analyzed to provide a descriptive synthesis of the utility of this technology. RESULTS: The emergence of hybrid SPECT/CT camera technology now allows simultaneous acquisition of combined multi-modality imaging, with seamless fusion of three-dimensional volume datasets. The usefulness of combining functional information to depict the bio-distribution of radiotracers that map cellular processes of the endocrine system and tumors of endocrine origin, with anatomy derived from CT, has improved the diagnostic capability of scintigraphy for a range of disorders of endocrine gland function. The literature describes benefits of SPECT/CT for 99mTc-sestamibi parathyroid scintigraphy and 99mTc-pertechnetate thyroid scintigraphy, 123I- or 131I-radioiodine for staging of differentiated thyroid carcinoma, 111In- and 99mTc- labeled somatostatin receptor analogues for detection of neuroendocrine tumors, 131I-norcholesterol (NP-59) scans for assessment of adrenal cortical hyperfunction, and 123I- or 131I-metaiodobenzylguanidine imaging for evaluation of pheochromocytoma and paraganglioma. CONCLUSION: SPECT/CT exploits the synergism between the functional information from radiopharmaceutical imaging and anatomy from CT, translating to improved diagnostic accuracy and meaningful impact on patient care. PMID:27358692

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

PubMed

Deligianni, Fani; Centeno, Maria; Carmichael, David W; Clayden, Jonathan D

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity.

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands

PubMed Central

Deligianni, Fani; Centeno, Maria; Carmichael, David W.; Clayden, Jonathan D.

2014-01-01

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity. PMID:25221467

Development of multi-class, multi-criteria bicycle traffic assignment models and solution algorithms

DOT National Transportation Integrated Search

2015-08-31

Cycling is gaining popularity both as a mode of travel in urban communities and as an alternative mode to private motorized vehicles due to its wide range of benefits (health, environmental, and economical). However, this change in modal share is not...

Utilization of a radiology-centric search engine.

PubMed

Sharpe, Richard E; Sharpe, Megan; Siegel, Eliot; Siddiqui, Khan

2010-04-01

Internet-based search engines have become a significant component of medical practice. Physicians increasingly rely on information available from search engines as a means to improve patient care, provide better education, and enhance research. Specialized search engines have emerged to more efficiently meet the needs of physicians. Details about the ways in which radiologists utilize search engines have not been documented. The authors categorized every 25th search query in a radiology-centric vertical search engine by radiologic subspecialty, imaging modality, geographic location of access, time of day, use of abbreviations, misspellings, and search language. Musculoskeletal and neurologic imagings were the most frequently searched subspecialties. The least frequently searched were breast imaging, pediatric imaging, and nuclear medicine. Magnetic resonance imaging and computed tomography were the most frequently searched modalities. A majority of searches were initiated in North America, but all continents were represented. Searches occurred 24 h/day in converted local times, with a majority occurring during the normal business day. Misspellings and abbreviations were common. Almost all searches were performed in English. Search engine utilization trends are likely to mirror trends in diagnostic imaging in the region from which searches originate. Internet searching appears to function as a real-time clinical decision-making tool, a research tool, and an educational resource. A more thorough understanding of search utilization patterns can be obtained by analyzing phrases as actually entered as well as the geographic location and time of origination. This knowledge may contribute to the development of more efficient and personalized search engines.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

Mitii™ ABI: study protocol of a randomised controlled trial of a web-based multi-modal training program for children and adolescents with an Acquired Brain Injury (ABI).

PubMed

Boyd, Roslyn N; Baque, Emmah; Piovesana, Adina; Ross, Stephanie; Ziviani, Jenny; Sakzewski, Leanne; Barber, Lee; Lloyd, Owen; McKinlay, Lynne; Whittingham, Koa; Smith, Anthony C; Rose, Stephen; Fiori, Simona; Cunnington, Ross; Ware, Robert; Lewis, Melinda; Comans, Tracy A; Scuffham, Paul A

2015-08-19

Acquired brain injury (ABI) refers to multiple disabilities arising from damage to the brain acquired after birth. Children with an ABI may experience physical, cognitive, social and emotional-behavioural impairments which can impact their ability to participate in activities of daily living (ADL). Recent developments in technology have led to the emergence of internet-delivered therapy programs. "Move it to improve it" (Mitii™) is a web-based multi-modal therapy that comprises upper limb (UL) and cognitive training within the context of meaningful physical activity. The proposed study aims to compare the efficacy of Mitii™ to usual care to improve ADL motor and processing skills, gross motor capacity, UL and executive functioning in a randomised waitlist controlled trial. Sixty independently ambulant children (30 in each group) at least 12 months post ABI will be recruited to participate in this trial. Children will be matched in pairs at baseline and randomly allocated to receive either 20 weeks of Mitii™ training (30 min per day, six days a week, with a potential total dose of 60 h) immediately, or be waitlisted for 20 weeks. Outcomes will be assessed at baseline, immediately post-intervention and at 20 weeks post-intervention. The primary outcomes will be the Assessment of Motor and Process Skills and 30 s repetition maximum of functional strength exercises (sit-to-stand, step-ups and half kneel to stand). Measures of body structure and functions, activity, participation and quality of life will assess the efficacy of Mitii™ across all domains of the International Classification of Functioning, Disability and Health framework. A subset of children will undertake three tesla (3T) magnetic resonance imaging scans to evaluate functional neurovascular changes, structural imaging, diffusion imaging and resting state functional connectivity before and after intervention. Mitii™ provides an alternative approach to deliver intensive therapy for children with an ABI in the convenience of the home environment. If Mitii™ is found to be effective, it may offer an accessible and inexpensive intervention option to increase therapy dose. ANZCTR12613000403730.

Neural network for intelligent query of an FBI forensic database

NASA Astrophysics Data System (ADS)

Uvanni, Lee A.; Rainey, Timothy G.; Balasubramanian, Uma; Brettle, Dean W.; Weingard, Fred; Sibert, Robert W.; Birnbaum, Eric

1997-02-01

Examiner is an automated fired cartridge case identification system utilizing a dual-use neural network pattern recognition technology, called the statistical-multiple object detection and location system (S-MODALS) developed by Booz(DOT)Allen & Hamilton, Inc. in conjunction with Rome Laboratory. S-MODALS was originally designed for automatic target recognition (ATR) of tactical and strategic military targets using multisensor fusion [electro-optical (EO), infrared (IR), and synthetic aperture radar (SAR)] sensors. Since S-MODALS is a learning system readily adaptable to problem domains other than automatic target recognition, the pattern matching problem of microscopic marks for firearms evidence was analyzed using S-MODALS. The physics; phenomenology; discrimination and search strategies; robustness requirements; error level and confidence level propagation that apply to the pattern matching problem of military targets were found to be applicable to the ballistic domain as well. The Examiner system uses S-MODALS to rank a set of queried cartridge case images from the most similar to the least similar image in reference to an investigative fired cartridge case image. The paper presents three independent tests and evaluation studies of the Examiner system utilizing the S-MODALS technology for the Federal Bureau of Investigation.

Multiset singular value decomposition for joint analysis of multi-modal data: application to fingerprint analysis

NASA Astrophysics Data System (ADS)

Emge, Darren K.; Adalı, Tülay

2014-06-01

As the availability and use of imaging methodologies continues to increase, there is a fundamental need to jointly analyze data that is collected from multiple modalities. This analysis is further complicated when, the size or resolution of the images differ, implying that the observation lengths of each of modality can be highly varying. To address this expanding landscape, we introduce the multiset singular value decomposition (MSVD), which can perform a joint analysis on any number of modalities regardless of their individual observation lengths. Through simulations, the inter modal relationships across the different modalities which are revealed by the MSVD are shown. We apply the MSVD to forensic fingerprint analysis, showing that MSVD joint analysis successfully identifies relevant similarities for further analysis, significantly reducing the processing time required. This reduction, takes this technique from a laboratory method to a useful forensic tool with applications across the law enforcement and security regimes.

The Blended Finite Element Method for Multi-fluid Plasma Modeling

DTIC Science & Technology

2016-07-01

Briefing Charts 3. DATES COVERED (From - To) 07 June 2016 - 01 July 2016 4. TITLE AND SUBTITLE The Blended Finite Element Method for Multi-fluid Plasma...BLENDED FINITE ELEMENT METHOD FOR MULTI-FLUID PLASMA MODELING Éder M. Sousa1, Uri Shumlak2 1ERC INC., IN-SPACE PROPULSION BRANCH (RQRS) AIR FORCE RESEARCH...MULTI-FLUID PLASMA MODEL 2 BLENDED FINITE ELEMENT METHOD Blended Finite Element Method Nodal Continuous Galerkin Modal Discontinuous Galerkin Model

A 24-Week Multi-Modality Exercise Program Improves Executive Control in Older Adults with a Self-Reported Cognitive Complaint: Evidence from the Antisaccade Task.

PubMed

Heath, Matthew; Shellington, Erin; Titheridge, Sam; Gill, Dawn P; Petrella, Robert J

2017-01-01

Exercise programs involving aerobic and resistance training (i.e., multiple-modality) have shown promise in improving cognition and executive control in older adults at risk, or experiencing, cognitive decline. It is, however, unclear whether cognitive training within a multiple-modality program elicits an additive benefit to executive/cognitive processes. This is an important question to resolve in order to identify optimal training programs that delay, or ameliorate, executive deficits in persons at risk for further cognitive decline. In the present study, individuals with a self-reported cognitive complaint (SCC) participated in a 24-week multiple-modality (i.e., the M2 group) exercise intervention program. In addition, a separate group of individuals with a SCC completed the same aerobic and resistance training as the M2 group but also completed a cognitive-based stepping task (i.e., multiple-modality, mind-motor intervention: M4 group). Notably, pre- and post-intervention executive control was examined via the antisaccade task (i.e., eye movement mirror-symmetrical to a target). Antisaccades are an ideal tool for the study of individuals with subtle executive deficits because of its hands- and language-free nature and because the task's neural mechanisms are linked to neuropathology in cognitive decline (i.e., prefrontal cortex). Results showed that M2 and M4 group antisaccade reaction times reliably decreased from pre- to post-intervention and the magnitude of the decrease was consistent across groups. Thus, multi-modality exercise training improved executive performance in persons with a SCC independent of mind-motor training. Accordingly, we propose that multiple-modality training provides a sufficient intervention to improve executive control in persons with a SCC.

3-D-Gaze-Based Robotic Grasping Through Mimicking Human Visuomotor Function for People With Motion Impairments.

PubMed

Li, Songpo; Zhang, Xiaoli; Webb, Jeremy D

2017-12-01

The goal of this paper is to achieve a novel 3-D-gaze-based human-robot-interaction modality, with which a user with motion impairment can intuitively express what tasks he/she wants the robot to do by directly looking at the object of interest in the real world. Toward this goal, we investigate 1) the technology to accurately sense where a person is looking in real environments and 2) the method to interpret the human gaze and convert it into an effective interaction modality. Looking at a specific object reflects what a person is thinking related to that object, and the gaze location contains essential information for object manipulation. A novel gaze vector method is developed to accurately estimate the 3-D coordinates of the object being looked at in real environments, and a novel interpretation framework that mimics human visuomotor functions is designed to increase the control capability of gaze in object grasping tasks. High tracking accuracy was achieved using the gaze vector method. Participants successfully controlled a robotic arm for object grasping by directly looking at the target object. Human 3-D gaze can be effectively employed as an intuitive interaction modality for robotic object manipulation. It is the first time that 3-D gaze is utilized in a real environment to command a robot for a practical application. Three-dimensional gaze tracking is promising as an intuitive alternative for human-robot interaction especially for disabled and elderly people who cannot handle the conventional interaction modalities.

Neonatal brain resting-state functional connectivity imaging modalities.

PubMed

Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza

2018-06-01

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

Multi-Modal Surrogates for Retrieving and Making Sense of Videos: Is Synchronization between the Multiple Modalities Optimal?

ERIC Educational Resources Information Center

Song, Yaxiao

2010-01-01

Video surrogates can help people quickly make sense of the content of a video before downloading or seeking more detailed information. Visual and audio features of a video are primary information carriers and might become important components of video retrieval and video sense-making. In the past decades, most research and development efforts on…

Interactive natural language acquisition in a multi-modal recurrent neural architecture

NASA Astrophysics Data System (ADS)

Heinrich, Stefan; Wermter, Stefan

2018-01-01

For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

Accurate Learning with Few Atlases (ALFA): an algorithm for MRI neonatal brain extraction and comparison with 11 publicly available methods.

PubMed

Serag, Ahmed; Blesa, Manuel; Moore, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Wilkinson, A G; Macnaught, Gillian; Semple, Scott I; Boardman, James P

2016-03-24

Accurate whole-brain segmentation, or brain extraction, of magnetic resonance imaging (MRI) is a critical first step in most neuroimage analysis pipelines. The majority of brain extraction algorithms have been developed and evaluated for adult data and their validity for neonatal brain extraction, which presents age-specific challenges for this task, has not been established. We developed a novel method for brain extraction of multi-modal neonatal brain MR images, named ALFA (Accurate Learning with Few Atlases). The method uses a new sparsity-based atlas selection strategy that requires a very limited number of atlases 'uniformly' distributed in the low-dimensional data space, combined with a machine learning based label fusion technique. The performance of the method for brain extraction from multi-modal data of 50 newborns is evaluated and compared with results obtained using eleven publicly available brain extraction methods. ALFA outperformed the eleven compared methods providing robust and accurate brain extraction results across different modalities. As ALFA can learn from partially labelled datasets, it can be used to segment large-scale datasets efficiently. ALFA could also be applied to other imaging modalities and other stages across the life course.

On modal cross-coupling in the asymptotic modal limit

NASA Astrophysics Data System (ADS)

Culver, Dean; Dowell, Earl

2018-03-01

The conditions under which significant modal cross-coupling occurs in dynamical systems responding to high-frequency, broadband forcing that excites many modes is studied. The modal overlap factor plays a key role in the analysis of these systems as the modal density (the ratio of number of modes to the frequency bandwidth) becomes large. The modal overlap factor is effectively the ratio of the width of a resonant peak (the damping ratio times the resonant frequency) to the average frequency interval between resonant peaks (or rather, the inverse of the modal density). It is shown that this parameter largely determines whether substantial modal cross-coupling occurs in a given system's response. Here, two prototypical systems are considered. The first is a simple rectangular plate whose significant modal cross-coupling is the exception rather than the norm. The second is a pair of rectangular plates attached at a point where significant modal cross-coupling is more likely to occur. We show that, for certain cases of modal density and damping, non-negligible cross coupling occurs in both systems. Under similar circumstances, the constraint force between the two plates in the latter system becomes broadband. The implications of this for using Asymptotic Modal Analysis (AMA) in multi-component systems are discussed.

Phase partitioning and volatility of secondary organic aerosol components formed from α-pinene ozonolysis and OH oxidation: the importance of accretion products and other low volatility compounds

DOE PAGES

Lopez-Hilfiker, F. D.; Mohr, C.; Ehn, M.; ...

2015-07-16

We measured a large suite of gas- and particle-phase multi-functional organic compounds with a Filter Inlet for Gases and AEROsols (FIGAERO) coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) developed at the University of Washington. The instrument was deployed on environmental simulation chambers to study monoterpene oxidation as a secondary organic aerosol (SOA) source. We focus here on results from experiments utilizing an ionization method most selective towards acids (acetate negative ion proton transfer), but our conclusions are based on more general physical and chemical properties of the SOA. Hundreds of compounds were observed in both gas andmore » particle phases, the latter being detected by temperature-programmed thermal desorption of collected particles. Particulate organic compounds detected by the FIGAERO–HR-ToF-CIMS are highly correlated with, and explain at least 25–50 % of, the organic aerosol mass measured by an Aerodyne aerosol mass spectrometer (AMS). Reproducible multi-modal structures in the thermograms for individual compounds of a given elemental composition reveal a significant SOA mass contribution from high molecular weight organics and/or oligomers (i.e., multi-phase accretion reaction products). Approximately 50 % of the HR-ToF-CIMS particle-phase mass is associated with compounds having effective vapor pressures 4 or more orders of magnitude lower than commonly measured monoterpene oxidation products. The relative importance of these accretion-type and other extremely low volatility products appears to vary with photochemical conditions. We present a desorption-temperature-based framework for apportionment of thermogram signals into volatility bins. The volatility-based apportionment greatly improves agreement between measured and modeled gas-particle partitioning for select major and minor components of the SOA, consistent with thermal decomposition during desorption causing the conversion of lower volatility components into the detected higher volatility compounds.« less

Phase partitioning and volatility of secondary organic aerosol components formed from α-pinene ozonolysis and OH oxidation: the importance of accretion products and other low volatility compounds

DOE PAGES

Lopez-Hilfiker, F. D.; Mohr, C.; Ehn, M.; ...

2015-02-18

We measured a large suite of gas and particle phase multi-functional organic compounds with a Filter Inlet for Gases and AEROsols (FIGAERO) coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) developed at the University of Washington. The instrument was deployed on environmental simulation chambers to study monoterpene oxidation as a secondary organic aerosol (SOA) source. We focus here on results from experiments utilizing an ionization method most selective towards acids (acetate negative ion proton transfer), but our conclusions are based on more general physical and chemical properties of the SOA. Hundreds of compounds were observed in both gasmore » and particle phases, the latter being detected upon temperature programmed thermal desorption of collected particles. Particulate organic compounds detected by the FIGAERO HR-ToF-CIMS are highly correlated with, and explain at least 25–50% of, the organic aerosol mass measured by an Aerodyne Aerosol Mass Spectrometer (AMS). Reproducible multi-modal structures in the thermograms for individual compounds of a given elemental composition reveal a significant SOA mass contribution from large molecular weight organics and/or oligomers (i.e. multi-phase accretion reaction products). Approximately 50% of the HR-ToF-CIMS particle phase mass is associated with compounds having effective vapor pressures 4 or more orders of magnitude lower than commonly measured monoterpene oxidation products. The relative importance of these accretion-type and other extremely low volatility products appears to vary with photochemical conditions. We present a desorption temperature based framework for apportionment of thermogram signals into volatility bins. The volatility-based apportionment greatly improves agreement between measured and modeled gas–particle partitioning for select major and minor components of the SOA, consistent with thermal decomposition during desorption causing the conversion of lower volatility components into the detected higher volatility compounds.« less

Gut vagal sensory signaling regulates hippocampus function through multi-order pathways.

PubMed

Suarez, Andrea N; Hsu, Ted M; Liu, Clarissa M; Noble, Emily E; Cortella, Alyssa M; Nakamoto, Emily M; Hahn, Joel D; de Lartigue, Guillaume; Kanoski, Scott E

2018-06-05

The vagus nerve is the primary means of neural communication between the gastrointestinal (GI) tract and the brain. Vagally mediated GI signals activate the hippocampus (HPC), a brain region classically linked with memory function. However, the endogenous relevance of GI-derived vagal HPC communication is unknown. Here we utilize a saporin (SAP)-based lesioning procedure to reveal that selective GI vagal sensory/afferent ablation in rats impairs HPC-dependent episodic and spatial memory, effects associated with reduced HPC neurotrophic and neurogenesis markers. To determine the neural pathways connecting the gut to the HPC, we utilize monosynaptic and multisynaptic virus-based tracing methods to identify the medial septum as a relay connecting the medial nucleus tractus solitarius (where GI vagal afferents synapse) to dorsal HPC glutamatergic neurons. We conclude that endogenous GI-derived vagal sensory signaling promotes HPC-dependent memory function via a multi-order brainstem-septal pathway, thereby identifying a previously unknown role for the gut-brain axis in memory control.

RNAV STAR Procedural Adherence

NASA Technical Reports Server (NTRS)

Stewart, Michael J.; Matthews, Bryan L.

2017-01-01

In this exploratory archival study we mined the performance of 24 major US airports area navigation standard terminal arrival routes (RNAV STARs) over the preceding three years. Overlaying radar track data on top of RNAV STAR routes provided a comparison between aircraft flight paths and the waypoint positions and altitude restrictions. NASA Ames Supercomputing resources were utilized to perform the data mining and processing. We investigated STARs by lateral transition path (full-lateral), vertical restrictions (full-lateral/full-vertical), and skipped waypoints (skips). In addition, we graphed altitudes and their frequencies of occurrence for altitude restrictions. Full-lateral compliance was generally greater than Full-lateral/full-vertical, but the delta between the rates was not always consistent. Full-lateral/full-vertical usage medians of the 2016 procedures ranged from 0 in KDEN (Denver) to 21 in KMEM (Memphis). Waypoint skips ranged from 0 to nearly 100 for specific waypoints. Altitudes restrictions were sometimes missed by systemic amounts in 1000 ft. increments from the restriction, creating multi-modal distributions. Other times, altitude misses looked to be more normally distributed around the restriction. This work is a preliminary investigation into the objective performance of instrument procedures and provides a framework to track how procedural concepts and design intervention function. In addition, this tool may aid in providing acceptability metrics as well as risk assessment information.

Presentation planning using an integrated knowledge base

NASA Technical Reports Server (NTRS)

Arens, Yigal; Miller, Lawrence; Sondheimer, Norman

1988-01-01

A description is given of user interface research aimed at bringing together multiple input and output modes in a way that handles mixed mode input (commands, menus, forms, natural language), interacts with a diverse collection of underlying software utilities in a uniform way, and presents the results through a combination of output modes including natural language text, maps, charts and graphs. The system, Integrated Interfaces, derives much of its ability to interact uniformly with the user and the underlying services and to build its presentations, from the information present in a central knowledge base. This knowledge base integrates models of the application domain (Navy ships in the Pacific region, in the current demonstration version); the structure of visual displays and their graphical features; the underlying services (data bases and expert systems); and interface functions. The emphasis is on a presentation planner that uses the knowledge base to produce multi-modal output. There has been a flurry of recent work in user interface management systems. (Several recent examples are listed in the references). Existing work is characterized by an attempt to relieve the software designer of the burden of handcrafting an interface for each application. The work has generally focused on intelligently handling input. This paper deals with the other end of the pipeline - presentations.

An adaptive learning control system for large flexible structures

NASA Technical Reports Server (NTRS)

Thau, F. E.

1985-01-01

The objective of the research has been to study the design of adaptive/learning control systems for the control of large flexible structures. In the first activity an adaptive/learning control methodology for flexible space structures was investigated. The approach was based on using a modal model of the flexible structure dynamics and an output-error identification scheme to identify modal parameters. In the second activity, a least-squares identification scheme was proposed for estimating both modal parameters and modal-to-actuator and modal-to-sensor shape functions. The technique was applied to experimental data obtained from the NASA Langley beam experiment. In the third activity, a separable nonlinear least-squares approach was developed for estimating the number of excited modes, shape functions, modal parameters, and modal amplitude and velocity time functions for a flexible structure. In the final research activity, a dual-adaptive control strategy was developed for regulating the modal dynamics and identifying modal parameters of a flexible structure. A min-max approach was used for finding an input to provide modal parameter identification while not exceeding reasonable bounds on modal displacement.

Emotion Perception from Face, Voice, and Touch: Comparisons and Convergence

PubMed Central

Schirmer, Annett; Adolphs, Ralph

2017-01-01

Historically, research on emotion perception has focused on facial expressions, and findings from this modality have come to dominate our thinking about other modalities. Here, we examine emotion perception through a wider lens by comparing facial with vocal and tactile processing. We review stimulus characteristics and ensuing behavioral and brain responses, and show that audition and touch do not simply duplicate visual mechanisms. Each modality provides a distinct input channel and engages partly non-overlapping neuroanatomical systems with different processing specializations (e.g., specific emotions versus affect). Moreover, processing of signals across the different modalities converges, first into multi- and later into amodal representations that enable holistic emotion judgments. PMID:28173998

An adaptive multi-feature segmentation model for infrared image

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

2016-04-01

Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

APEX_SCOPE: A graphical user interface for visualization of multi-modal data in inter-disciplinary studies.

PubMed

Kanbar, Lara J; Shalish, Wissam; Precup, Doina; Brown, Karen; Sant'Anna, Guilherme M; Kearney, Robert E

2017-07-01

In multi-disciplinary studies, different forms of data are often collected for analysis. For example, APEX, a study on the automated prediction of extubation readiness in extremely preterm infants, collects clinical parameters and cardiorespiratory signals. A variety of cardiorespiratory metrics are computed from these signals and used to assign a cardiorespiratory pattern at each time. In such a situation, exploratory analysis requires a visualization tool capable of displaying these different types of acquired and computed signals in an integrated environment. Thus, we developed APEX_SCOPE, a graphical tool for the visualization of multi-modal data comprising cardiorespiratory signals, automated cardiorespiratory metrics, automated respiratory patterns, manually classified respiratory patterns, and manual annotations by clinicians during data acquisition. This MATLAB-based application provides a means for collaborators to view combinations of signals to promote discussion, generate hypotheses and develop features.

GPU accelerated dynamic functional connectivity analysis for functional MRI data.

PubMed

Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu

2015-07-01

Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo

PubMed Central

Yang, Joon-Mo; Favazza, Christopher; Chen, Ruimin; Yao, Junjie; Cai, Xin; Maslov, Konstantin; Zhou, Qifa; Shung, K. Kirk; Wang, Lihong V.

2013-01-01

Presently, clinicians routinely apply ultrasound endoscopy in a variety of interventional procedures which provide treatment solutions for diseased organs. Ultrasound endoscopy not only produces high resolution images, it is also safe for clinical use and broadly applicable. However, for soft tissue imaging, its mechanical wave-based image contrast fundamentally limits its ability to provide physiologically-specific functional information. By contrast, photoacoustic endoscopy possesses a unique combination of functional optical contrast and high spatial resolution at clinically-relevant depths, ideal for soft tissue imaging. With these attributes, photoacoustic endoscopy can overcome the current limitations of ultrasound endoscopy. Moreover, the benefits of photoacoustic imaging do not come at the expense of existing ultrasound functions; photoacoustic endoscopy systems are inherently compatible with ultrasound imaging, enabling multi-modality imaging with complementary contrast. Here, we present simultaneous photoacoustic and ultrasonic dual-mode endoscopy and demonstrate its ability to image internal organs in vivo, illustrating its potential clinical application. PMID:22797808

A low-power multi-modal body sensor network with application to epileptic seizure monitoring.

PubMed

Altini, Marco; Del Din, Silvia; Patel, Shyamal; Schachter, Steven; Penders, Julien; Bonato, Paolo

2011-01-01

Monitoring patients' physiological signals during their daily activities in the home environment is one of the challenge of the health care. New ultra-low-power wireless technologies could help to achieve this goal. In this paper we present a low-power, multi-modal, wearable sensor platform for the simultaneous recording of activity and physiological data. First we provide a description of the wearable sensor platform, and its characteristics with respect to power consumption. Second we present the preliminary results of the comparison between our sensors and a reference system, on healthy subjects, to test the reliability of the detected physiological (electrocardiogram and respiration) and electromyography signals.

Validation of a new modal performance measure for flexible controllers design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simo, J.B.; Tahan, S.A.; Kamwa, I.

1996-05-01

A new modal performance measure for power system stabilizer (PSS) optimization is proposed in this paper. The new method is based on modifying the square envelopes of oscillating modes, in order to take into account their damping ratios while minimizing the performance index. This criteria is applied to flexible controllers optimal design, on a multi-input-multi-output (MIMO) reduced-order model of a prototype power system. The multivariable model includes four generators, each having one input and one output. Linear time-response simulation and transient stability analysis with a nonlinear package confirm the superiority of the proposed criteria and illustrate its effectiveness in decentralizedmore » control.« less

Multi-modal cockpit interface for improved airport surface operations

NASA Technical Reports Server (NTRS)

Arthur, Jarvis J. (Inventor); Bailey, Randall E. (Inventor); Prinzel, III, Lawrence J. (Inventor); Kramer, Lynda J. (Inventor); Williams, Steven P. (Inventor)

2010-01-01

A system for multi-modal cockpit interface during surface operation of an aircraft comprises a head tracking device, a processing element, and a full-color head worn display. The processing element is configured to receive head position information from the head tracking device, to receive current location information of the aircraft, and to render a virtual airport scene corresponding to the head position information and the current aircraft location. The full-color head worn display is configured to receive the virtual airport scene from the processing element and to display the virtual airport scene. The current location information may be received from one of a global positioning system or an inertial navigation system.

The Changing Conduct of Geoscience in a Data Intensive World (Ian McHarg Medal Lecture)

NASA Astrophysics Data System (ADS)

Fox, P.

2012-04-01

Electronic facilitation of scientific research (often called eResearch or eScience) is increasingly prevelant in geosciences. Among the consequences of new and diversifying means of complex (*) data generation is that as many branches of science have become data-intensive (so-called fourth paradigm), they in turn broaden their long-tail distributions - smaller volume, but often complex data, will always lead to excellent science. There are many familar informatics functions that enable the conduct of science (by specialists or non-specialists) in this new regime. For example, the need for any user to be able to discover relations among and between the results of data analyses and informational queries. Unfortunately, true science exploration, for example visual discovery, over complex data remains more of an art form than an easily conducted practice. In general, the resource costs of creating useful visualizations has been increasing. Less than 10 years ago, it was assessed that data-centric science required a rough split between the time to generate, analyze, and publish data and the science based on that data. Today however, the visualization and analysis component has become a bottleneck, requiring considerably more of the overall effort and this trend will continue. Potentially even worse, is the choice to simplify analyses to 'get the work out'. Extra effort to make data understandable, something that should be routine, is now consuming considerable resources that could be used for many other purposes. It is now time to change that trend. This contribution lays out informatics paths for truly 'exploratory' conduct of science cast in the present and rapidly changing reality of Web/Internet-based data and software infrastructures. A logical consequence of these paths is that the people working in this new mode of research, i.e. data scientists, require additional and different education to become effective and routine users of new informatics capabilities. One goal is to achieve the same fluency that researchers may have in lab techniques, instrument utilization, model development and use, etc. Thus, in conclusion, curriculum and skill requirements for data scientists will be presented and discussed. * complex/ intensive = large volume, multi-scale, multi-modal, multi-dimensional, multi-disciplinary, and heterogeneous structure.