TU-CD-207-12: Impact of Anatomical Noise On Detection Performance of Microcalcifications in Multi-Contrast Breast Imaging

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

Garrett, J; Ge, Y; Li, K

2015-06-15

Purpose: The anatomical noise power spectra (NPS) for differential phase contrast (DPC) and dark field (DF) imaging have recently been characterized using a power-law model with two parameters, alpha and beta, an innovative extension to the methodology used in x-ray attenuation based breast imaging such as mammography, DBT, or cone-beam CT. Beta values of 3.6, 2.6, and 1.3 have been measured for absorption, DPC, and DF respectively for cadaver breasts imaged in the coronal plane; these dramatic differences should be reflected in their detection performance. The purpose of this study was to determine the impact of anatomical noise on breastmore » calcification detection and compare the detection performance of the three contrast mechanisms of a multi-contrast x-ray imaging system. Methods: In our studies, a calcification image object was segmented out of the multi-contrast images of a cadaver breast specimen. 50 measured total NPS were measured from breast cadavers directly. The ideal model observer detectability was calculated for a range of doses (5–100%) and a range of calcification sizes (diameter = 0.25–2.5 mm). Results: Overall we found the highest average detectability corresponded to DPC imaging (7.4 for 1 mm calc.), with DF the next highest (3.8 for 1 mm calc.), and absorption the lowest (3.2 for 1 mm calc.). However, absorption imaging also showed the slowest dependence on dose of the three modalities due to the significant anatomical noise. DPC showed a peak detectability for calcifications ∼1.25 mm in diameter, DF showed a peak for calcifications around 0.75 mm in diameter, and absorption imaging had no such peak in the range explored. Conclusion: Understanding imaging performance for DPC and DF is critical to transition these modalities to the clinic. The results presented here offer new insight into how these modalities complement absorption imaging to maximize the likelihood of detecting early breast cancers. J. Garrett, Y. Ge, K. Li: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.« less

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

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.

A multi-modal stereo microscope based on a spatial light modulator.

PubMed

Lee, M P; Gibson, G M; Bowman, R; Bernet, S; Ritsch-Marte, M; Phillips, D B; Padgett, M J

2013-07-15

Spatial Light Modulators (SLMs) can emulate the classic microscopy techniques, including differential interference (DIC) contrast and (spiral) phase contrast. Their programmability entails the benefit of flexibility or the option to multiplex images, for single-shot quantitative imaging or for simultaneous multi-plane imaging (depth-of-field multiplexing). We report the development of a microscope sharing many of the previously demonstrated capabilities, within a holographic implementation of a stereo microscope. Furthermore, we use the SLM to combine stereo microscopy with a refocusing filter and with a darkfield filter. The instrument is built around a custom inverted microscope and equipped with an SLM which gives various imaging modes laterally displaced on the same camera chip. In addition, there is a wide angle camera for visualisation of a larger region of the sample.

In vivo confirmation of hydration based contrast mechanisms for terahertz medical imaging using MRI

NASA Astrophysics Data System (ADS)

Bajwa, Neha; Sung, Shijun; Garritano, James; Nowroozi, Bryan; Tewari, Priyamvada; Ennis, Daniel B.; Alger, Jeffery; Grundfest, Warren; Taylor, Zachary

2014-09-01

Terahertz (THz) detection has been proposed and applied to a variety of medical imaging applications in view of its unrivaled hydration profiling capabilities. Variations in tissue dielectric function have been demonstrated at THz frequencies to generate high contrast imagery of tissue, however, the source of image contrast remains to be verified using a modality with a comparable sensing scheme. To investigate the primary contrast mechanism, a pilot comparison study was performed in a burn wound rat model, widely known to create detectable gradients in tissue hydration through both injured and surrounding tissue. Parallel T2 weighted multi slice multi echo (T2w MSME) 7T Magnetic Resonance (MR) scans and THz surface reflectance maps were acquired of a full thickness skin burn in a rat model over a 5 hour time period. A comparison of uninjured and injured regions in the full thickness burn demonstrates a 3-fold increase in average T2 relaxation times and a 15% increase in average THz reflectivity, respectively. These results support the sensitivity and specificity of MRI for measuring in vivo burn tissue water content and the use of this modality to verify and understand the hydration sensing capabilities of THz imaging for acute assessments of the onset and evolution of diseases that affect the skin. A starting point for more sophisticated in vivo studies, this preliminary analysis may be used in the future to explore how and to what extent the release of unbound water affects imaging contrast in THz burn sensing.

Upconverting rare-earth nanoparticles with a paramagnetic lanthanide complex shell for upconversion fluorescent and magnetic resonance dual-modality imaging

NASA Astrophysics Data System (ADS)

Wang, Yan; Ji, Lei; Zhang, Bingbo; Yin, Peihao; Qiu, Yanyan; Song, Daqian; Zhou, Juying; Li, Qi

2013-05-01

Multi-modal imaging based on multifunctional nanoparticles is a promising alternative approach to improve the sensitivity of early cancer diagnosis. In this study, highly upconverting fluorescence and strong relaxivity rare-earth nanoparticles coated with paramagnetic lanthanide complex shells and polyethylene glycol (PEGylated UCNPs@DTPA-Gd3+) are synthesized as dual-modality imaging contrast agents (CAs) for upconverting fluorescent and magnetic resonance dual-modality imaging. PEGylated UCNPs@DTPA-Gd3+ with sizes in the range of 32-86 nm are colloidally stable. They exhibit higher longitudinal relaxivity and transverse relaxivity in water (r1 and r2 values are 7.4 and 27.8 s-1 per mM Gd3+, respectively) than does commercial Gd-DTPA (r1 and r2 values of 3.7 and 4.6 s-1 per mM Gd3+, respectively). They are found to be biocompatible. In vitro cancer cell imaging shows good imaging contrast of PEGylated UCNPs@DTPA-Gd3+. In vivo upconversion fluorescent imaging and T1-weighted MRI show excellent enhancement of both fluorescent and MR signals in the livers of mice administered PEGylated UCNPs@DTPA-Gd3+. All the experimental results indicate that the synthesized PEGylated UCNPs@DTPA-Gd3+ present great potential for biomedical upconversion of fluorescent and magnetic resonance dual-modality imaging applications.

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.

Phase congruency map driven brain tumour segmentation

NASA Astrophysics Data System (ADS)

Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

2015-03-01

Computer Aided Diagnostic (CAD) systems are already of proven value in healthcare, especially for surgical planning, nevertheless much remains to be done. Gliomas are the most common brain tumours (70%) in adults, with a survival time of just 2-3 months if detected at WHO grades III or higher. Such tumours are extremely variable, necessitating multi-modal Magnetic Resonance Images (MRI). The use of Gadolinium-based contrast agents is only relevant at later stages of the disease where it highlights the enhancing rim of the tumour. Currently, there is no single accepted method that can be used as a reference. There are three main challenges with such images: to decide whether there is tumour present and is so localize it; to construct a mask that separates healthy and diseased tissue; and to differentiate between the tumour core and the surrounding oedema. This paper presents two contributions. First, we develop tumour seed selection based on multiscale multi-modal texture feature vectors. Second, we develop a method based on a local phase congruency based feature map to drive level-set segmentation. The segmentations achieved with our method are more accurate than previously presented methods, particularly for challenging low grade tumours.

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.

Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

PubMed

Prastawa, Marcel; Bullitt, Elizabeth; Gerig, Guido

2009-04-01

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).

19 CFR 4.7a - Inward manifest; information required; alternative forms.

Code of Federal Regulations, 2010 CFR

2010-04-01

...., Directory of Standard Multi-Modal Carrier and Tariff Agent Codes, applicable supplements thereto and... acceptable (and the address of the foreign vendor, etc., must be a foreign address); by contrast, the...

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

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

Multi-Modal Hallucinations and Cognitive Function in Parkinson's Disease

PubMed Central

Katzen, Heather; Myerson, Connie; Papapetropoulos, Spiridon; Nahab, Fatta; Gallo, Bruno; Levin, Bonnie

2010-01-01

Background/Aims Hallucinations have been linked to a constellation of cognitive deficits in Parkinson's disease (PD), but it is not known whether multi-modal hallucinations are associated with greater neuropsychological dysfunction. Methods 152 idiopathic PD patients were categorized based on the presence or absence of hallucinations and then were further subdivided into visual-only (VHonly; n = 35) or multi-modal (VHplus; n = 12) hallucination groups. All participants underwent detailed neuropsychological assessment. Results Participants with hallucinations performed more poorly on select neuropsychological measures and exhibited more mood symptoms. There were no differences between VHonly and VHplus groups. Conclusions PD patients with multi-modal hallucinations are not at greater risk for neuropsychological impairment than those with single-modal hallucinations. PMID:20689283

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

Development of a platform for co-registered ultrasound and MR contrast imaging in vivo

NASA Astrophysics Data System (ADS)

Chandrana, Chaitanya; Bevan, Peter; Hudson, John; Pang, Ian; Burns, Peter; Plewes, Donald; Chopra, Rajiv

2011-02-01

Imaging of the microvasculature is often performed using contrast agents in combination with either ultrasound (US) or magnetic resonance (MR) imaging. Contrast agents are used to enhance medical imaging by highlighting microvascular properties and function. Dynamic signal changes arising from the passage of contrast agents through the microvasculature can be used to characterize different pathologies; however, comparisons across modalities are difficult due to differences in the interactions of contrast agents with the microvasculature. Better knowledge of the relationship of contrast enhancement patterns with both modalities could enable better characterization of tissue microvasculature. We developed a co-registration platform for multi-modal US and MR imaging using clinical imaging systems in order to study the relationship between US and MR contrast enhancement. A preliminary validation study was performed in phantoms to determine the registration accuracy of the platform. In phantoms, the in-plane registration accuracy was measured to be 0.2 ± 0.2 and 0.3 ± 0.2 mm, in the lateral and axial directions, respectively. The out-of-plane registration accuracy was estimated to be 0.5 mm ±0.1. Co-registered US and MR imaging was performed in a rabbit model to evaluate contrast kinetics in different tissue types after bolus injections of US and MR contrast agents. The arrival time of the contrast agent in the plane of imaging was relatively similar for both modalities. We studied three different tissue types: muscle, large vessels and fat. In US, the temporal kinetics of signal enhancement were not strongly dependent on tissue type. In MR, however, due to the different amounts of agent extravasation in each tissue type, tissue-specific contrast kinetics were observed. This study demonstrates the feasibility of performing in vivo co-registered contrast US and MR imaging to study the relationships of the enhancement patterns with each modality.

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

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

Richard Mazurchuk, PhD | Division of Cancer Prevention

Cancer.gov

Dr. Richard Mazurchuk received a BS in Physics and MS and PhD in Biophysics from SUNY Buffalo. His research focused on developing novel multi-modality imaging techniques, contrast (enhancing) agents and methods to assess the efficacy of experimental therapeutics. |

Contrast-enhanced photoacoustic tomography of human joints

NASA Astrophysics Data System (ADS)

Tian, Chao; Keswani, Rahul K.; Gandikota, Girish; Rosania, Gus R.; Wang, Xueding

2016-03-01

Photoacoustic tomography (PAT) provides a unique tool to diagnose inflammatory arthritis. However, the specificity and sensitivity of PAT based on endogenous contrasts is limited. The development of contrast enhanced PAT imaging modalities in combination with small molecule contrast agents could lead to improvements in diagnosis and treatment of joint disease. Accordingly, we adapted and tested a PAT clinical imaging system for imaging the human joints, in combination with a novel PAT contrast agent derived from an FDA-approved small molecule drug. Imaging results based on a photoacoustic and ultrasound (PA/US) dual-modality system revealed that this contrast-enhanced PAT imaging system may offer additional information beyond single-modality PA or US imaging system, for the imaging, diagnosis and assessment of inflammatory arthritis.

A gantry-based tri-modality system for bioluminescence tomography

PubMed Central

Yan, Han; Lin, Yuting; Barber, William C.; Unlu, Mehmet Burcin; Gulsen, Gultekin

2012-01-01

A gantry-based tri-modality system that combines bioluminescence (BLT), diffuse optical (DOT), and x-ray computed tomography (XCT) into the same setting is presented here. The purpose of this system is to perform bioluminescence tomography using a multi-modality imaging approach. As parts of this hybrid system, XCT and DOT provide anatomical information and background optical property maps. This structural and functional a priori information is used to guide and restrain bioluminescence reconstruction algorithm and ultimately improve the BLT results. The performance of the combined system is evaluated using multi-modality phantoms. In particular, a cylindrical heterogeneous multi-modality phantom that contains regions with higher optical absorption and x-ray attenuation is constructed. We showed that a 1.5 mm diameter bioluminescence inclusion can be localized accurately with the functional a priori information while its source strength can be recovered more accurately using both structural and the functional a priori information. PMID:22559540

Multi-Modal Intelligent Traffic Signal Systems (MMITSS) impacts assessment.

DOT National Transportation Integrated Search

2015-08-01

The study evaluates the potential network-wide impacts of the Multi-Modal Intelligent Transportation Signal System (MMITSS) based on a field data analysis utilizing data collected from a MMITSS prototype and a simulation analysis. The Intelligent Tra...

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.

ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

NASA Astrophysics Data System (ADS)

Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

2018-02-01

Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

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

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.

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.

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

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.

Exploring the complementarity of THz pulse imaging and DCE-MRIs: Toward a unified multi-channel classification and a deep learning framework.

PubMed

Yin, X-X; Zhang, Y; Cao, J; Wu, J-L; Hadjiloucas, S

2016-12-01

We provide a comprehensive account of recent advances in biomedical image analysis and classification from two complementary imaging modalities: terahertz (THz) pulse imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The work aims to highlight underlining commonalities in both data structures so that a common multi-channel data fusion framework can be developed. Signal pre-processing in both datasets is discussed briefly taking into consideration advances in multi-resolution analysis and model based fractional order calculus system identification. Developments in statistical signal processing using principal component and independent component analysis are also considered. These algorithms have been developed independently by the THz-pulse imaging and DCE-MRI communities, and there is scope to place them in a common multi-channel framework to provide better software standardization at the pre-processing de-noising stage. A comprehensive discussion of feature selection strategies is also provided and the importance of preserving textural information is highlighted. Feature extraction and classification methods taking into consideration recent advances in support vector machine (SVM) and extreme learning machine (ELM) classifiers and their complex extensions are presented. An outlook on Clifford algebra classifiers and deep learning techniques suitable to both types of datasets is also provided. The work points toward the direction of developing a new unified multi-channel signal processing framework for biomedical image analysis that will explore synergies from both sensing modalities for inferring disease proliferation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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 ...

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.

Noncontact Sleep Study by Multi-Modal Sensor Fusion.

PubMed

Chung, Ku-Young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-07-21

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner.

Noncontact Sleep Study by Multi-Modal Sensor Fusion

PubMed Central

Chung, Ku-young; Song, Kwangsub; Shin, Kangsoo; Sohn, Jinho; Cho, Seok Hyun; Chang, Joon-Hyuk

2017-01-01

Polysomnography (PSG) is considered as the gold standard for determining sleep stages, but due to the obtrusiveness of its sensor attachments, sleep stage classification algorithms using noninvasive sensors have been developed throughout the years. However, the previous studies have not yet been proven reliable. In addition, most of the products are designed for healthy customers rather than for patients with sleep disorder. We present a novel approach to classify sleep stages via low cost and noncontact multi-modal sensor fusion, which extracts sleep-related vital signals from radar signals and a sound-based context-awareness technique. This work is uniquely designed based on the PSG data of sleep disorder patients, which were received and certified by professionals at Hanyang University Hospital. The proposed algorithm further incorporates medical/statistical knowledge to determine personal-adjusted thresholds and devise post-processing. The efficiency of the proposed algorithm is highlighted by contrasting sleep stage classification performance between single sensor and sensor-fusion algorithms. To validate the possibility of commercializing this work, the classification results of this algorithm were compared with the commercialized sleep monitoring device, ResMed S+. The proposed algorithm was investigated with random patients following PSG examination, and results show a promising novel approach for determining sleep stages in a low cost and unobtrusive manner. PMID:28753994

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.

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

Rapid multi-modality preregistration based on SIFT descriptor.

PubMed

Chen, Jian; Tian, Jie

2006-01-01

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration.

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

[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.

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

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.

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…

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.

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

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.

Hybrid label-free multiphoton and optoacoustic microscopy (MPOM)

NASA Astrophysics Data System (ADS)

Soliman, Dominik; Tserevelakis, George J.; Omar, Murad; Ntziachristos, Vasilis

2015-07-01

Many biological applications require a simultaneous observation of different anatomical features. However, unless potentially harmful staining of the specimens is employed, individual microscopy techniques do generally not provide multi-contrast capabilities. We present a hybrid microscope integrating optoacoustic microscopy and multiphoton microscopy, including second-harmonic generation, into a single device. This combined multiphoton and optoacoustic microscope (MPOM) offers visualization of a broad range of structures by employing different contrast mechanisms and at the same time enables pure label-free imaging of biological systems. We investigate the relative performance of the two microscopy modalities and demonstrate their multi-contrast abilities through the label-free imaging of a zebrafish larva ex vivo, simultaneously visualizing muscles and pigments. This hybrid microscopy application bears great potential for developmental biology studies, enabling more comprehensive information to be obtained from biological specimens without the necessity of staining.

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

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.

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

Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L.; Assad, Albert; Abramson, Richard G.; Landman, Bennett A.

2017-02-01

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≍1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Multi-atlas Segmentation Enables Robust Multi-contrast MRI Spleen Segmentation for Splenomegaly.

PubMed

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L; Assad, Albert; Abramson, Richard G; Landman, Bennett A

2017-02-11

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≈1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

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.

Biocompatible and high-performance amino acids-capped MnWO4 nanocasting as a novel non-lanthanide contrast agent for X-ray computed tomography and T1-weighted magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Dong, Kai; Liu, Zhen; Liu, Jianhua; Huang, Sa; Li, Zhenhua; Yuan, Qinghai; Ren, Jinsong; Qu, Xiaogang

2014-01-01

In the present work, a novel non-lanthanide dual-modality contrast agent, manganese tungstate (MnWO4), has been successfully constructed by a facile and versatile hydrothermal route. With the merits of a high atomic number and a well-positioned K-edge energy of tungsten, our well-prepared non-lanthanide nanoprobes provide a higher contrast efficacy than routine iodine-based agents in clinics. Additionally, the presence of Mn in these nanoparticles endow them with excellent T1-weighted MR imaging capabilities. As an alternative to T2-weighted MRI and CT dual-modality contrast agents, the nanoprobes can provide a positive contrast signal, which prevents confusion with the dark signals from hemorrhage and blood clots. To the best of our knowledge, this is the first report that a non-lanthanide imaging nanoprobe is applied for CT and T1-weighted MRI simultaneously. Moreover, comparing with gadolinium-based T1-weighted MRI and CT dual-modality contrast agents that were associated with nephrogenic systemic fibrosis (NSF), our contrast agents have superior biocompatibility, which is proved by a detailed study of the pharmacokinetics, biodistribution, and in vivo toxicology. Together with excellent dispersibility, high biocompatibility and superior contrast efficacy, these nanoprobes provide detailed and complementary information from dual-modality imaging over traditional single-mode imaging and bring more opportunities to the new generation of non-lanthanide nanoparticulate-based contrast agents.In the present work, a novel non-lanthanide dual-modality contrast agent, manganese tungstate (MnWO4), has been successfully constructed by a facile and versatile hydrothermal route. With the merits of a high atomic number and a well-positioned K-edge energy of tungsten, our well-prepared non-lanthanide nanoprobes provide a higher contrast efficacy than routine iodine-based agents in clinics. Additionally, the presence of Mn in these nanoparticles endow them with excellent T1-weighted MR imaging capabilities. As an alternative to T2-weighted MRI and CT dual-modality contrast agents, the nanoprobes can provide a positive contrast signal, which prevents confusion with the dark signals from hemorrhage and blood clots. To the best of our knowledge, this is the first report that a non-lanthanide imaging nanoprobe is applied for CT and T1-weighted MRI simultaneously. Moreover, comparing with gadolinium-based T1-weighted MRI and CT dual-modality contrast agents that were associated with nephrogenic systemic fibrosis (NSF), our contrast agents have superior biocompatibility, which is proved by a detailed study of the pharmacokinetics, biodistribution, and in vivo toxicology. Together with excellent dispersibility, high biocompatibility and superior contrast efficacy, these nanoprobes provide detailed and complementary information from dual-modality imaging over traditional single-mode imaging and bring more opportunities to the new generation of non-lanthanide nanoparticulate-based contrast agents. Electronic supplementary information (ESI) available: TEM images of MnWO4 nanoparticles synthesized at pH = 7, 180 °C pH = 9, 180 °C pH = 6, 200 °C with various amino acid molecules as capped agents, survey XPS spectra, FTIR spectrum of glycine capped MnWO4 nanorods, photos of glycine capped MnWO4 nanorods in various solutions including PBS, DMEM cell medium, and FBS, in vivo coronal view CT images of a rat before and after intravenous injection of iobitridol at different timed intervals, in vivo CT imaging of the rat one month after intravenous injection of MnWO4 nanorods, CT values of the heart, liver, spleen and kidney of a rat before and after intravenous administration of MnWO4 nanorods and iobitridol at different time intervals, hematology analysis and blood biochemical assay. See DOI: 10.1039/c3nr05455a

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.

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

Cell segmentation in phase contrast microscopy images via semi-supervised classification over optics-related features.

PubMed

Su, Hang; Yin, Zhaozheng; Huh, Seungil; Kanade, Takeo

2013-10-01

Phase-contrast microscopy is one of the most common and convenient imaging modalities to observe long-term multi-cellular processes, which generates images by the interference of lights passing through transparent specimens and background medium with different retarded phases. Despite many years of study, computer-aided phase contrast microscopy analysis on cell behavior is challenged by image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose (1) a phase contrast microscopy image restoration method that produces phase retardation features, which are intrinsic features of phase contrast microscopy, and (2) a semi-supervised learning based algorithm for cell segmentation, which is a fundamental task for various cell behavior analysis. Specifically, the image formation process of phase contrast microscopy images is first computationally modeled with a dictionary of diffraction patterns; as a result, each pixel of a phase contrast microscopy image is represented by a linear combination of the bases, which we call phase retardation features. Images are then partitioned into phase-homogeneous atoms by clustering neighboring pixels with similar phase retardation features. Consequently, cell segmentation is performed via a semi-supervised classification technique over the phase-homogeneous atoms. Experiments demonstrate that the proposed approach produces quality segmentation of individual cells and outperforms previous approaches. Copyright © 2013 Elsevier B.V. All rights reserved.

New generation of magnetic and luminescent nanoparticles for in vivo real-time imaging

PubMed Central

Lacroix, Lise-Marie; Delpech, Fabien; Nayral, Céline; Lachaize, Sébastien; Chaudret, Bruno

2013-01-01

A new generation of optimized contrast agents is emerging, based on metallic nanoparticles (NPs) and semiconductor nanocrystals for, respectively, magnetic resonance imaging (MRI) and near-infrared (NIR) fluorescent imaging techniques. Compared with established contrast agents, such as iron oxide NPs or organic dyes, these NPs benefit from several advantages: their magnetic and optical properties can be tuned through size, shape and composition engineering, their efficiency can exceed by several orders of magnitude that of contrast agents clinically used, their surface can be modified to incorporate specific targeting agents and antifolding polymers to increase blood circulation time and tumour recognition, and they can possibly be integrated in complex architecture to yield multi-modal imaging agents. In this review, we will report the materials of choice based on the understanding of the basic physics of NIR and MRI techniques and their corresponding syntheses as NPs. Surface engineering, water transfer and specific targeting will be highlighted prior to their first use for in vivo real-time imaging. Highly efficient NPs that are safer and target specific are likely to enter clinical application in a near future. PMID:24427542

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

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

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.

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.

Implications of differences of echoic and iconic memory for the design of multimodal displays

NASA Astrophysics Data System (ADS)

Glaser, Daniel Shields

It has been well documented that dual-task performance is more accurate when each task is based on a different sensory modality. It is also well documented that the memory for each sense has unequal durations, particularly visual (iconic) and auditory (echoic) sensory memory. In this dissertation I address whether differences in sensory memory (e.g. iconic vs. echoic) duration have implications for the design of a multimodal display. Since echoic memory persists for seconds in contrast to iconic memory which persists only for milliseconds, one of my hypotheses was that in a visual-auditory dual task condition, performance will be better if the visual task is completed before the auditory task than vice versa. In Experiment 1 I investigated whether the ability to recall multi-modal stimuli is affected by recall order, with each mode being responded to separately. In Experiment 2, I investigated the effects of stimulus order and recall order on the ability to recall information from a multi-modal presentation. In Experiment 3 I investigated the effect of presentation order using a more realistic task. In Experiment 4 I investigated whether manipulating the presentation order of stimuli of different modalities improves humans' ability to combine the information from the two modalities in order to make decision based on pre-learned rules. As hypothesized, accuracy was greater when visual stimuli were responded to first and auditory stimuli second. Also as hypothesized, performance was improved by not presenting both sequences at the same time, limiting the perceptual load. Contrary to my expectations, overall performance was better when a visual sequence was presented before the audio sequence. Though presenting a visual sequence prior to an auditory sequence lengthens the visual retention interval, it also provides time for visual information to be recoded to a more robust form without disruption. Experiment 4 demonstrated that decision making requiring the integration of visual and auditory information is enhanced by reducing workload and promoting a strategic use of echoic memory. A framework for predicting Experiment 1-4 results is proposed and evaluated.

Nanox: a miniature mechanical stress rig designed for near-field X-ray diffraction imaging techniques.

PubMed

Gueninchault, N; Proudhon, H; Ludwig, W

2016-11-01

Multi-modal characterization of polycrystalline materials by combined use of three-dimensional (3D) X-ray diffraction and imaging techniques may be considered as the 3D equivalent of surface studies in the electron microscope combining diffraction and other imaging modalities. Since acquisition times at synchrotron sources are nowadays compatible with four-dimensional (time lapse) studies, suitable mechanical testing devices are needed which enable switching between these different imaging modalities over the course of a mechanical test. Here a specifically designed tensile device, fulfilling severe space constraints and permitting to switch between X-ray (holo)tomography, diffraction contrast tomography and topotomography, is presented. As a proof of concept the 3D characterization of an Al-Li alloy multicrystal by means of diffraction contrast tomography is presented, followed by repeated topotomography characterization of one selected grain at increasing levels of deformation. Signatures of slip bands and sudden lattice rotations inside the grain have been shown by means of in situ topography carried out during the load ramps, and diffraction spot peak broadening has been monitored throughout the experiment.

Nanox: a miniature mechanical stress rig designed for near-field X-ray diffraction imaging techniques

PubMed Central

Gueninchault, N.; Proudhon, H.; Ludwig, W.

2016-01-01

Multi-modal characterization of polycrystalline materials by combined use of three-dimensional (3D) X-ray diffraction and imaging techniques may be considered as the 3D equivalent of surface studies in the electron microscope combining diffraction and other imaging modalities. Since acquisition times at synchrotron sources are nowadays compatible with four-dimensional (time lapse) studies, suitable mechanical testing devices are needed which enable switching between these different imaging modalities over the course of a mechanical test. Here a specifically designed tensile device, fulfilling severe space constraints and permitting to switch between X-ray (holo)tomography, diffraction contrast tomography and topotomography, is presented. As a proof of concept the 3D characterization of an Al–Li alloy multicrystal by means of diffraction contrast tomography is presented, followed by repeated topotomography characterization of one selected grain at increasing levels of deformation. Signatures of slip bands and sudden lattice rotations inside the grain have been shown by means of in situ topography carried out during the load ramps, and diffraction spot peak broadening has been monitored throughout the experiment. PMID:27787253

A Brief Account of Nanoparticle Contrast Agents for Photoacoustic Imaging

PubMed Central

Pan, Dipanjan; Kim, Benjamin; Wang, Lihong V.; Lanza, Gregory M

2014-01-01

Photoacoustic imaging (PAI) is a hybrid, nonionizing modality offering excellent spatial resolution, deep penetration, and high soft tissue contrast. In PAI, signal is generated based on the absorption of laser-generated optical energy by endogenous tissues or exogenous contrast agents leading to acoustic emissions detected by an ultrasound transducer. Research in this area over the years has shown that PAI has the ability to provide both physiological and molecular imaging, which can be viewed alone or used in a hybrid modality fashion to extend the anatomic and hemodynamic sensitivities of clinical ultrasound. PAI may be performed using inherent contrast afforded by light absorbing molecules such as hemoglobin, myoglobin, and melanin or exogenous small molecule contrast agent such as near infrared dyes and porphyrins. However, this review summarizes the potential of exogenous nanoparticle-based agents for PAI applications including contrast based on gold particles, carbon nanotubes, and encapsulated copper compounds. PMID:23983210

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.

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.

T1-T2 dual-modal MRI of brain gliomas using PEGylated Gd-doped iron oxide nanoparticles.

PubMed

Xiao, Ning; Gu, Wei; Wang, Hao; Deng, Yunlong; Shi, Xin; Ye, Ling

2014-03-01

To overcome the negative contrast limitations of iron oxide-based contrast agents and to improve the biocompatibility of Gd-chelate contrast agents, PEGylated Gd-doped iron oxide (PEG-GdIO) NPs as a T1-T2 dual-modal contrast agent were synthesized by the polyol method. The transverse relaxivity (r2) and longitudinal relaxivity (r1) of PEG-GdIO were determined to be 66.9 and 65.9 mM(-1) s(-1), respectively. The high r1 value and low r2/r1 ratio make PEG-GdIO NPs suitable as a T1-T2 dual-modal contrast agent. The in vivo MRI demonstrated a brighter contrast enhancement in T1-weighted image and a simultaneous darken effect in T2-weighted MR image compared to the pre-contrast image in the region of glioma. Furthermore, the biocompatibility of PEG-GdIO NPs was confirmed by the in vitro MTT cytotoxicity and in vivo histological analyses (H&E). Therefore, PEG-GdIO NPs hold great potential in T1-T2 dual-modal imaging for the diagnosis of brain glioma. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Gold-manganese nanoparticles for targeted diagnostic and imaging

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

Murph, Simona Hunyadi

Imagine the possibility of non-invasive, non-radiation based Magnetic resonance imaging (MRI) in combating cardiac disease. Researchers at the Savannah River National Laboratory (SRNL) are developing a process that would use nanotechnology in a novel, targeted approach that would allow MRIs to be more descriptive and brighter, and to target specific organs. Researchers at SRNL have discovered a way to use multifunctional metallic gold-manganese nanoparticles to create a unique, targeted positive contrast agent. SRNL Senior Scientist Dr. Simona Hunyadi Murph says she first thought of using the nanoparticles for cardiac disease applications after learning that people who survive an infarct exhibitmore » up to 15 times higher rate of developing chronic heart failure, arrhythmias and/or sudden death compared to the general population. Without question, nanotechnology will revolutionize the future of technology. The development of functional nanomaterials with multi-detection modalities opens up new avenues for creating multi-purpose technologies for biomedical applications.« less

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...

Evaluating laser-driven Bremsstrahlung radiation sources for imaging and analysis of nuclear waste packages.

PubMed

Jones, Christopher P; Brenner, Ceri M; Stitt, Camilla A; Armstrong, Chris; Rusby, Dean R; Mirfayzi, Seyed R; Wilson, Lucy A; Alejo, Aarón; Ahmed, Hamad; Allott, Ric; Butler, Nicholas M H; Clarke, Robert J; Haddock, David; Hernandez-Gomez, Cristina; Higginson, Adam; Murphy, Christopher; Notley, Margaret; Paraskevoulakos, Charilaos; Jowsey, John; McKenna, Paul; Neely, David; Kar, Satya; Scott, Thomas B

2016-11-15

A small scale sample nuclear waste package, consisting of a 28mm diameter uranium penny encased in grout, was imaged by absorption contrast radiography using a single pulse exposure from an X-ray source driven by a high-power laser. The Vulcan laser was used to deliver a focused pulse of photons to a tantalum foil, in order to generate a bright burst of highly penetrating X-rays (with energy >500keV), with a source size of <0.5mm. BAS-TR and BAS-SR image plates were used for image capture, alongside a newly developed Thalium doped Caesium Iodide scintillator-based detector coupled to CCD chips. The uranium penny was clearly resolved to sub-mm accuracy over a 30cm(2) scan area from a single shot acquisition. In addition, neutron generation was demonstrated in situ with the X-ray beam, with a single shot, thus demonstrating the potential for multi-modal criticality testing of waste materials. This feasibility study successfully demonstrated non-destructive radiography of encapsulated, high density, nuclear material. With recent developments of high-power laser systems, to 10Hz operation, a laser-driven multi-modal beamline for waste monitoring applications is envisioned. Copyright © 2016. Published by Elsevier B.V.

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.

Multi-modality endoscopic imaging for the detection of colorectal cancer

NASA Astrophysics Data System (ADS)

Wall, Richard Andrew

Optical coherence tomography (OCT) is an imaging method that is considered the optical analog to ultrasound, using the technique of optical interferometry to construct two-dimensional depth-resolved images of tissue microstructure. With a resolution on the order of 10 um and a penetration depth of 1-2 mm in highly scattering tissue, fiber optics-coupled OCT is an ideal modality for the inspection of the mouse colon with its miniaturization capabilities. In the present study, the complementary modalities laser-induced fluorescence (LIF), which offers information on the biochemical makeup of the tissue, and surface magnifying chromoendoscopy, which offers high contrast surface visualization, are combined with OCT in endoscopic imaging systems for the greater specificity and sensitivity in the differentiation between normal and neoplastic tissue, and for the visualization of biomarkers which are indicative of early events in colorectal carcinogenesis. Oblique incidence reflectometry (OIR) also offers advantages, allowing the calculation of bulk tissue optical properties for use as a diagnostic tool. The study was broken up into three specific sections. First, a dual-modality OCTLIF imaging system was designed, capable of focusing light over 325-1300 nm using a reflective distal optics design. A dual-modality fluorescence-based SMC-OCT system was then designed and constructed, capable of resolving the stained mucosal crypt structure of the in vivo mouse colon. The SMC-OCT instrument's OIR capabilities were then modeled, as a modified version of the probe was used measure tissue scattering and absorption coefficients.

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.

Postmortem dynamic cerebral angiography for detecting aneurysm and bleeding sites in cases of subarachnoid hemorrhage.

PubMed

Inokuchi, Go; Yajima, Daisuke; Hayakawa, Mutsumi; Motomura, Ayumi; Chiba, Fumiko; Torimitsu, Suguru; Makino, Yohsuke; Iwase, Hirotaro

2014-12-01

One of the advantages of postmortem imaging is its ability to obtain diagnostic findings in a non-destructive manner when autopsy is either difficult or may destroy forensic evidence. In recent years, efforts have been made to incorporate computed tomography (CT) based postmortem angiography into forensic pathology; however, it is not currently clear how well the modality can determine sites of bleeding in cases of subarachnoid hemorrhage. Therefore, in this study, we investigated the utility of postmortem cerebral angiography using multi-detector row CT (MDCT) by injecting a contrast medium through a catheter inserted into the internal carotid and vertebral arteries of 10 subarachnoid hemorrhage cases. While postmortem MDCT angiography (PMCTA) was capable of detecting aneurysms in a non-destructive manner, it was sometimes difficult to identify the aneurysm and bleeding sites because of a large amount of contrast medium leaking into the extravascular space. To overcome this problem, we developed the novel contrast imaging method "dynamic cerebral angiography," which involves scanning the same area multiple times while injecting contrast medium to enable real-time observation of the contrasted vasculature. Using multiphase contrast images acquired by this method, we successfully captured the moment when contrast medium leaked from the hemorrhage site. This method will be useful for identifying exact bleeding sites on PMCTA.

Navigating the fifth dimension: new concepts in interactive multimodality and multidimensional image navigation

NASA Astrophysics Data System (ADS)

Ratib, Osman; Rosset, Antoine; Dahlbom, Magnus; Czernin, Johannes

2005-04-01

Display and interpretation of multi dimensional data obtained from the combination of 3D data acquired from different modalities (such as PET-CT) require complex software tools allowing the user to navigate and modify the different image parameters. With faster scanners it is now possible to acquire dynamic images of a beating heart or the transit of a contrast agent adding a fifth dimension to the data. We developed a DICOM-compliant software for real time navigation in very large sets of 5 dimensional data based on an intuitive multidimensional jog-wheel widely used by the video-editing industry. The software, provided under open source licensing, allows interactive, single-handed, navigation through 3D images while adjusting blending of image modalities, image contrast and intensity and the rate of cine display of dynamic images. In this study we focused our effort on the user interface and means for interactively navigating in these large data sets while easily and rapidly changing multiple parameters such as image position, contrast, intensity, blending of colors, magnification etc. Conventional mouse-driven user interface requiring the user to manipulate cursors and sliders on the screen are too cumbersome and slow. We evaluated several hardware devices and identified a category of multipurpose jogwheel device that is used in the video-editing industry that is particularly suitable for rapidly navigating in five dimensions while adjusting several display parameters interactively. The application of this tool will be demonstrated in cardiac PET-CT imaging and functional cardiac MRI studies.

Modeling the Development of Audiovisual Cue Integration in Speech Perception

PubMed Central

Getz, Laura M.; Nordeen, Elke R.; Vrabic, Sarah C.; Toscano, Joseph C.

2017-01-01

Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues. PMID:28335558

Modeling the Development of Audiovisual Cue Integration in Speech Perception.

PubMed

Getz, Laura M; Nordeen, Elke R; Vrabic, Sarah C; Toscano, Joseph C

2017-03-21

Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues.

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

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.

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.

In vivo tumor characterization using both MR and optical contrast agents with a hybrid MRI-DOT system

NASA Astrophysics Data System (ADS)

Lin, Yuting; Ghijsen, Michael; Thayer, David; Nalcioglu, Orhan; Gulsen, Gultekin

2011-03-01

Dynamic contrast enhanced MRI (DCE-MRI) has been proven to be the most sensitive modality in detecting breast lesions. Currently available MR contrast agent, Gd-DTPA, is a low molecular weight extracellular agent and can diffuse freely from the vascular space into interstitial space. Due to this reason, DCE-MRI has low sensitivity in differentiating benign and malignant tumors. Meanwhile, diffuse optical tomography (DOT) can be used to provide enhancement kinetics of an FDA approved optical contrast agent, ICG, which behaves like a large molecular weight optical agent due to its binding to albumin. The enhancement kinetics of ICG may have a potential to distinguish between the malignant and benign tumors and hence improve the specificity. Our group has developed a high speed hybrid MRI-DOT system. The DOT is a fully automated, MR-compatible, multi-frequency and multi-spectral imaging system. Fischer-344 rats bearing subcutaneous R3230 tumor are injected simultaneously with Gd-DTPA (0.1nmol/kg) and IC-Green (2.5mg/kg). The enhancement kinetics of both contrast agents are recorded simultaneously with this hybrid MRI-DOT system and evaluated for different tumors.

SU-E-J-110: A Novel Level Set Active Contour Algorithm for Multimodality Joint Segmentation/Registration Using the Jensen-Rényi Divergence.

PubMed

Markel, D; Naqa, I El; Freeman, C; Vallières, M

2012-06-01

To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. It was found that JR divergence when used for segmentation has an improved robustness to noise compared to using mutual information, or other entropy-based metrics. The MI metric failed at around 2/3 the noise power than the JR divergence. The JR divergence metric is useful for the task of joint segmentation/registration of multimodality images and shows improved results compared entropy based metric. The algorithm can be easily modified to incorporate non-intensity based images, which would allow applications into multi-modality and texture analysis. © 2012 American Association of Physicists in Medicine.

A Multi-Modal Digital Game-Based Learning Environment for Hospitalized Children with Chronic Illnesses.

ERIC Educational Resources Information Center

Chin, Jui-Chih; Tsuei, Mengping

2014-01-01

The aim of this study was to explore the digital game-based learning for children with chronic illnesses in the hospital settings. The design-based research and qualitative methods were applied. Three eight-year-old children with leukemia participated in this study. In the first phase, the multi-user game-based learning system was developed and…

Multi-segment detector array for hybrid reflection-mode ultrasound and optoacoustic tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Merčep, Elena; Burton, Neal C.; Deán-Ben, Xosé Luís.; Razansky, Daniel

2017-02-01

The complementary contrast of the optoacoustic (OA) and pulse-echo ultrasound (US) modalities makes the combined usage of these imaging technologies highly advantageous. Due to the different physical contrast mechanisms development of a detector array optimally suited for both modalities is one of the challenges to efficient implementation of a single OA-US imaging device. We demonstrate imaging performance of the first hybrid detector array whose novel design, incorporating array segments of linear and concave geometry, optimally supports image acquisition in both reflection-mode ultrasonography and optoacoustic tomography modes. Hybrid detector array has a total number of 256 elements and three segments of different geometry and variable pitch size: a central 128-element linear segment with pitch of 0.25mm, ideally suited for pulse-echo US imaging, and two external 64-elements segments with concave geometry and 0.6mm pitch optimized for OA image acquisition. Interleaved OA and US image acquisition with up to 25 fps is facilitated through a custom-made multiplexer unit. Spatial resolution of the transducer was characterized in numerical simulations and validated in phantom experiments and comprises 230 and 300 μm in the respective OA and US imaging modes. Imaging performance of the multi-segment detector array was experimentally shown in a series of imaging sessions with healthy volunteers. Employing mixed array geometries allows at the same time achieving excellent OA contrast with a large field of view, and US contrast for complementary structural features with reduced side-lobes and improved resolution. The newly designed hybrid detector array that comprises segments of linear and concave geometries optimally fulfills requirements for efficient US and OA imaging and may expand the applicability of the developed hybrid OPUS imaging technology and accelerate its clinical translation.

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.

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

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.

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform.

PubMed

Lai, Zongying; Zhang, Xinlin; Guo, Di; Du, Xiaofeng; Yang, Yonggui; Guo, Gang; Chen, Zhong; Qu, Xiaobo

2018-05-03

Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a ℓ 2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

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…

Preparation and characterization of alginate based-fluorescent magnetic nanoparticles for fluorescence/magnetic resonance multimodal imaging applications

NASA Astrophysics Data System (ADS)

Kwon, Yong-Su; Choi, Kee-Bong; Lim, Hyungjun; Lee, Sunghwi; Lee, Jae-Jong

2018-06-01

Simple and versatile methodologies have been reported that customize the surface of superparamagnetic iron oxide (SPIO) nanoparticles and impart additional fluorescence capabilities to these contrast agents. Herein, we present the rational design, synthesis, characterization, and biological applications of a new magnetic-based fluorescent probe. The dual modality imaging protocol was developed by labeling fluorophore with alginate natural polymers that have excellent biocompatibility and biodegradability, and using gelification method to form nanocomposites containing SPIO. The formation of alginate-based fluorescent magnetic (AFM) nanoparticles was observed in spherical and elliptical forms with a diameter of less than 500 nm by a transmission electron microscope (TEM). The fluorescent wavelength band in the range of 560 nm was also confirmed in the UV–visible spectrophotometer. In this study, we demonstrate that the multi-tasking design of AFM nanoparticles provides an ideal platform for building balanced dual-image probes of magnetic resonance imaging and optical imaging.

Bilateral filtering using the full noise covariance matrix applied to x-ray phase-contrast computed tomography.

PubMed

Allner, S; Koehler, T; Fehringer, A; Birnbacher, L; Willner, M; Pfeiffer, F; Noël, P B

2016-05-21

The purpose of this work is to develop an image-based de-noising algorithm that exploits complementary information and noise statistics from multi-modal images, as they emerge in x-ray tomography techniques, for instance grating-based phase-contrast CT and spectral CT. Among the noise reduction methods, image-based de-noising is one popular approach and the so-called bilateral filter is a well known algorithm for edge-preserving filtering. We developed a generalization of the bilateral filter for the case where the imaging system provides two or more perfectly aligned images. The proposed generalization is statistically motivated and takes the full second order noise statistics of these images into account. In particular, it includes a noise correlation between the images and spatial noise correlation within the same image. The novel generalized three-dimensional bilateral filter is applied to the attenuation and phase images created with filtered backprojection reconstructions from grating-based phase-contrast tomography. In comparison to established bilateral filters, we obtain improved noise reduction and at the same time a better preservation of edges in the images on the examples of a simulated soft-tissue phantom, a human cerebellum and a human artery sample. The applied full noise covariance is determined via cross-correlation of the image noise. The filter results yield an improved feature recovery based on enhanced noise suppression and edge preservation as shown here on the example of attenuation and phase images captured with grating-based phase-contrast computed tomography. This is supported by quantitative image analysis. Without being bound to phase-contrast imaging, this generalized filter is applicable to any kind of noise-afflicted image data with or without noise correlation. Therefore, it can be utilized in various imaging applications and fields.

Fluorescence-tagged amphiphilic brush copolymer encapsulated Gd2O3 core-shell nanostructures for enhanced T 1 contrast effect and fluorescent imaging

NASA Astrophysics Data System (ADS)

Wang, Fenghe; Peng, Erwin; Liu, Feng; Li, Pingjing; Fong Yau Li, Sam; Xue, Jun Min

2016-10-01

To obtain suitable T 1 contrast agents for magnetic resonance imaging (MRI) application, aqueous Gd2O3 nanoparticles (NPs) with high longitudinal relativity (r 1) are demanded. High quality Gd2O3 NPs are usually synthesized through a non-hydrolytic route which requires post-synthetic modification to render the NPs water soluble. The current challenge is to obtain aqueous Gd2O3 NPs with high colloidal stability and enhanced r 1 relaxivity. To overcome this challenge, fluorescence-tagged amphiphilic brush copolymer (AFCP) encapsulated Gd2O3 NPs were proposed as suitable T 1 contrast agents. Such a coating layer provided (i) superior aqueous stability, (ii) biocompatibility, as well as (iii) multi-modality (conjugation with fluorescence dye). The polymeric coating layer thickness was simply adjusted by varying the phase-transfer parameters. By reducing the coating thickness, i.e. the distance between the paramagnetic centre and surrounding water protons, the r 1 relaxivity could be enhanced. In contrast, a thicker polymeric layer coating prevents Gd3+ ions leakage, thus improving its biocompatibility. Therefore, it is important to strike a balance between the biocompatibility and the r 1 relaxivity behaviour. Lastly, by conjugating fluorescence moiety, an additional imaging modality was enabled, as demonstrated from the cell-labelling experiment.

3D widefield light microscope image reconstruction without dyes

NASA Astrophysics Data System (ADS)

Larkin, S.; Larson, J.; Holmes, C.; Vaicik, M.; Turturro, M.; Jurkevich, A.; Sinha, S.; Ezashi, T.; Papavasiliou, G.; Brey, E.; Holmes, T.

2015-03-01

3D image reconstruction using light microscope modalities without exogenous contrast agents is proposed and investigated as an approach to produce 3D images of biological samples for live imaging applications. Multimodality and multispectral imaging, used in concert with this 3D optical sectioning approach is also proposed as a way to further produce contrast that could be specific to components in the sample. The methods avoid usage of contrast agents. Contrast agents, such as fluorescent or absorbing dyes, can be toxic to cells or alter cell behavior. Current modes of producing 3D image sets from a light microscope, such as 3D deconvolution algorithms and confocal microscopy generally require contrast agents. Zernike phase contrast (ZPC), transmitted light brightfield (TLB), darkfield microscopy and others can produce contrast without dyes. Some of these modalities have not previously benefitted from 3D image reconstruction algorithms, however. The 3D image reconstruction algorithm is based on an underlying physical model of scattering potential, expressed as the sample's 3D absorption and phase quantities. The algorithm is based upon optimizing an objective function - the I-divergence - while solving for the 3D absorption and phase quantities. Unlike typical deconvolution algorithms, each microscope modality, such as ZPC or TLB, produces two output image sets instead of one. Contrast in the displayed image and 3D renderings is further enabled by treating the multispectral/multimodal data as a feature set in a mathematical formulation that uses the principal component method of statistics.

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.

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…

Switchable multi-wavelength fiber laser based on modal interference

NASA Astrophysics Data System (ADS)

Ma, Lin; Jiang, Sun; Qi, Yan-Hui; Kang, Ze-Xin; Jian, Shui-Sheng

2015-08-01

A comb fiber filter based on modal interference is proposed and demonstrated in this paper. Here two cascaded up-tapers are used to excite the cladding mode, and a core-offset jointing point is used to act as an interference component. Experimental results show that this kind of structure possesses a comb filter property in a range of the C-band. The measured extinction ratio is better than 12 dB with an insertion loss of about 11 dB. A switchable multi-wavelength erbium-doped fiber laser based on this novel comb filter is demonstrated. By adjusting the polarization controller, the output laser can be switched among single-, dual-, and three-wavelengths with a side mode suppression ratio of better than 45 dB.

Multi-scale volumetric cell and tissue imaging based on optical projection tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ban, Sungbea; Cho, Nam Hyun; Ryu, Yongjae; Jung, Sunwoo; Vavilin, Andrey; Min, Eunjung; Jung, Woonggyu

2016-04-01

Optical projection tomography is a new optical imaging method for visualizing small biological specimens in three dimension. The most important advantage of OPT is to fill the gap between MRI and confocal microscope for the specimen having the range of 1-10 mm. Thus, it has been mainly used for whole-mount small animals and developmental study since this imaging modality was developed. The ability of OPT delivering anatomical and functional information of relatively large tissue in 3D has made it a promising platform in biomedical research. Recently, the potential of OPT spans its coverage to cellular scale. Even though there are increasing demand to obtain better understanding of cellular dynamics, only few studies to visualize cellular structure, shape, size and functional morphology over tissue has been investigated in existing OPT system due to its limited field of view. In this study, we develop a novel optical imaging system for 3D cellular imaging with OPT integrated with dynamic focusing technique. Our tomographic setup has great potential to be used for identifying cell characteristic in tissue because it can provide selective contrast on dynamic focal plane allowing for fluorescence as well as absorption. While the dominant contrast of optical imaging technique is to use the fluorescence for detecting certain target only, the newly developed OPT system will offer considerable advantages over currently available method when imaging cellar molecular dynamics by permitting contrast variation. By achieving multi-contrast, it is expected for this new imaging system to play an important role in delivering better cytological information to pathologist.

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

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.

Ultrasound Contrast Agents

NASA Astrophysics Data System (ADS)

Cachard, Christian; Basset, Olivier

While the use of contrast agents in other imaging modalities (X ray, MRI, PET, …) has been routinely accepted for many years, the development and commercialization of contrast agents designed specifically for ultrasound imaging has occurred only very recently. As in the other imaging modalities, the injection of contrast agents during an ultrasound examination is intended to facilitate the detection and diagnosis of specific pathologies. Contrast agents efficiency is based on the backscattering of ultrasound by microbubbles. These microparticules are intravenously injected in the blood flow. After an introduction and generalities on ultrasound contrast agents (UCA) the microbubble physics in an acoustic field will be developed. Second, physics characteristics of contrast agents will be compared (bubbles with or without shell, gas nature, size distribution). Influence of acoustic pressure on the behaviour of the microparticules (linear, non linear and destruction) will be discussed. Finally, a review of specific imaging adapted to contrast agent properties as harmonic imaging, pulse inversion imaging will be presented.

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Contrast-based sensorless adaptive optics for retinal imaging.

PubMed

Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T O; He, Zheng; Metha, Andrew

2015-09-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes.

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.

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

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.

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

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.

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.

Materials Chemistry of Nanoultrasonic Biomedicine.

PubMed

Tang, Hailin; Zheng, Yuanyi; Chen, Yu

2017-03-01

As a special cross-disciplinary research frontier, nanoultrasonic biomedicine refers to the design and synthesis of nanomaterials to solve some critical issues of ultrasound (US)-based biomedicine. The concept of nanoultrasonic biomedicine can also overcome the drawbacks of traditional microbubbles and promote the generation of novel US-based contrast agents or synergistic agents for US theranostics. Here, we discuss the recent developments of material chemistry in advancing the nanoultrasonic biomedicine for diverse US-based bio-applications. We initially introduce the design principles of novel nanoplatforms for serving the nanoultrasonic biomedicine, from the viewpoint of synthetic material chemistry. Based on these principles and diverse US-based bio-application backgrounds, the representative proof-of-concept paradigms on this topic are clarified in detail, including nanodroplet vaporization for intelligent/responsive US imaging, multifunctional nano-contrast agents for US-based multi-modality imaging, activatable synergistic agents for US-based therapy, US-triggered on-demand drug releasing, US-enhanced gene transfection, US-based synergistic therapy on combating the cancer and potential toxicity issue of screening various nanosystems suitable for nanoultrasonic biomedicine. It is highly expected that this novel nanoultrasonic biomedicine and corresponding high performance in US imaging and therapy can significantly promote the generation of new sub-discipline of US-based biomedicine by rationally integrating material chemistry and theranostic nanomedicine with clinical US-based biomedicine. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Label-Free, High Resolution, Multi-Modal Light Microscopy for Discrimination of Live Stem Cell Differentiation Status.

PubMed

Zhang, Jing; Moradi, Emilia; Somekh, Michael G; Mather, Melissa L

2018-01-15

A label-free microscopy method for assessing the differentiation status of stem cells is presented with potential application for characterization of therapeutic stem cell populations. The microscopy system is capable of characterizing live cells based on the use of evanescent wave microscopy and quantitative phase contrast (QPC) microscopy. The capability of the microscopy system is demonstrated by studying the differentiation of live immortalised neonatal mouse neural stem cells over a 15 day time course. Metrics extracted from microscope images are assessed and images compared with results from endpoint immuno-staining studies to illustrate the system's performance. Results demonstrate the potential of the microscopy system as a valuable tool for cell biologists to readily identify the differentiation status of unlabelled live cells.

Construction of Silica-Based Micro/Nanoplatforms for Ultrasound Theranostic Biomedicine.

PubMed

Zhou, Yang; Han, Xiaoxia; Jing, Xiangxiang; Chen, Yu

2017-09-01

Ultrasound (US)-based biomedicine has been extensively explored for its applications in both diagnostic imaging and disease therapy. The fast development of theranostic nanomedicine significantly promotes the development of US-based biomedicine. This progress report summarizes and discusses the recent developments of rational design and fabrication of silica-based micro/nanoparticles for versatile US-based biomedical applications. The synthetic strategies and surface-engineering approaches of silica-based micro/nanoparticles are initially discussed, followed by detailed introduction on their US-based theranostic applications. They have been extensively explored in contrast-enhanced US imaging, US-based multi-modality imaging, synergistic high-intensity focused US (HIFU) ablation, sonosensitizer-enhanced sonodynamic therapy (SDT), as well as US-triggered chemotherapy. Their biological effects and biosafety have been briefly discussed to guarantee further clinical translation. Based on the high biocompatibility, versatile composition/structure and high performance in US-based theranostic biomedicine, these silica-based theranostic agents are expected to pave a new way for achieving efficient US-based theranostics of disease by taking the specific advantages of material science, nanotechnology and US-based biomedicine. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development and Application of Multifunctional Lanthanide-Doped Nanoparticles in Medical Imaging

NASA Astrophysics Data System (ADS)

Pedraza, Francisco J., III

Medical imaging has become one of the most important tools of modern medicine soon after it was developed. Presently, several imaging modalities are available to clinicians for the detection of skeletal fractures and functional abnormalities of organs and tissues; and also an excellent tool during surgical procedures. Unfortunately, each imaging technique possesses its own strengths and inherent limitations which can be mitigated via the use of multiple imaging modalities and imaging probes. Through the use of multiple imaging modalities, it is possible to gather complementary information for a more reliable diagnosis. Each imaging technique requires its own imaging probes, providing selectivity and improved contrast. However, conventional contrast agents are incapable of providing what the new generation of multifunctional nanomaterials offer. In addition to improved selectivity and contrast, multifunctional materials possess therapeutic capabilities such as photo-thermal therapy and controlled drug delivery. Lanthanide-based nanomaterials are viable candidates for multimodal imaging agents due to possessing multifunctional capabilities, optical and chemical stability, and an intense tunable emission. This doctoral dissertation will delve into the development of lanthanide-based nanoparticles by proposing a novel multifunctional contrast agent for Near Infrared Fluorescence Imaging and Magnetic Resonance Imaging. Furthermore, the study of surface modification effects on upconversion emission and nanoparticle-cell interactions was performed. Results presented will confirm the potential application of multifunctional lanthanide-based nanomaterials as multimodal imaging probes.

Comparison of the application of B-mode and strain elastography ultrasound in the estimation of lymph node metastasis of papillary thyroid carcinoma based on a radiomics approach.

PubMed

Liu, Tongtong; Ge, Xifeng; Yu, Jinhua; Guo, Yi; Wang, Yuanyuan; Wang, Wenping; Cui, Ligang

2018-06-21

B-mode ultrasound (B-US) and strain elastography ultrasound (SE-US) images have a potential to distinguish thyroid tumor with different lymph node (LN) status. The purpose of our study is to investigate whether the application of multi-modality images including B-US and SE-US can improve the discriminability of thyroid tumor with LN metastasis based on a radiomics approach. Ultrasound (US) images including B-US and SE-US images of 75 papillary thyroid carcinoma (PTC) cases were retrospectively collected. A radiomics approach was developed in this study to estimate LNs status of PTC patients. The approach included image segmentation, quantitative feature extraction, feature selection and classification. Three feature sets were extracted from B-US, SE-US, and multi-modality containing B-US and SE-US. They were used to evaluate the contribution of different modalities. A total of 684 radiomics features have been extracted in our study. We used sparse representation coefficient-based feature selection method with 10-bootstrap to reduce the dimension of feature sets. Support vector machine with leave-one-out cross-validation was used to build the model for estimating LN status. Using features extracted from both B-US and SE-US, the radiomics-based model produced an area under the receiver operating characteristic curve (AUC) [Formula: see text] 0.90, accuracy (ACC) [Formula: see text] 0.85, sensitivity (SENS) [Formula: see text] 0.77 and specificity (SPEC) [Formula: see text] 0.88, which was better than using features extracted from B-US or SE-US separately. Multi-modality images provided more information in radiomics study. Combining use of B-US and SE-US could improve the LN metastasis estimation accuracy for PTC patients.

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.

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.

Novel delivery approaches for cancer therapeutics.

PubMed

Mitra, Ashim K; Agrahari, Vibhuti; Mandal, Abhirup; Cholkar, Kishore; Natarajan, Chandramouli; Shah, Sujay; Joseph, Mary; Trinh, Hoang M; Vaishya, Ravi; Yang, Xiaoyan; Hao, Yi; Khurana, Varun; Pal, Dhananjay

2015-12-10

Currently, a majority of cancer treatment strategies are based on the removal of tumor mass mainly by surgery. Chemical and physical treatments such as chemo- and radiotherapies have also made a major contribution in inhibiting rapid growth of malignant cells. Furthermore, these approaches are often combined to enhance therapeutic indices. It is widely known that surgery, chemo- and radiotherapy also inhibit normal cells growth. In addition, these treatment modalities are associated with severe side effects and high toxicity which in turn lead to low quality of life. This review encompasses novel strategies for more effective chemotherapeutic delivery aiming to generate better prognosis. Currently, cancer treatment is a highly dynamic field and significant advances are being made in the development of novel cancer treatment strategies. In contrast to conventional cancer therapeutics, novel approaches such as ligand or receptor based targeting, triggered release, intracellular drug targeting, gene delivery, cancer stem cell therapy, magnetic drug targeting and ultrasound-mediated drug delivery, have added new modalities for cancer treatment. These approaches have led to selective detection of malignant cells leading to their eradication with minimal side effects. Lowering multi-drug resistance and involving influx transportation in targeted drug delivery to cancer cells can also contribute significantly in the therapeutic interventions in cancer. Copyright © 2015 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

Contrast-based sensorless adaptive optics for retinal imaging

PubMed Central

Zhou, Xiaolin; Bedggood, Phillip; Bui, Bang; Nguyen, Christine T.O.; He, Zheng; Metha, Andrew

2015-01-01

Conventional adaptive optics ophthalmoscopes use wavefront sensing methods to characterize ocular aberrations for real-time correction. However, there are important situations in which the wavefront sensing step is susceptible to difficulties that affect the accuracy of the correction. To circumvent these, wavefront sensorless adaptive optics (or non-wavefront sensing AO; NS-AO) imaging has recently been developed and has been applied to point-scanning based retinal imaging modalities. In this study we show, for the first time, contrast-based NS-AO ophthalmoscopy for full-frame in vivo imaging of human and animal eyes. We suggest a robust image quality metric that could be used for any imaging modality, and test its performance against other metrics using (physical) model eyes. PMID:26417525

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.

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.

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.

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.

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.

Blind identification of full-field vibration modes from video measurements with phase-based video motion magnification

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Dorn, Charles; Mancini, Tyler; Talken, Zachary; Kenyon, Garrett; Farrar, Charles; Mascareñas, David

2017-02-01

Experimental or operational modal analysis traditionally requires physically-attached wired or wireless sensors for vibration measurement of structures. This instrumentation can result in mass-loading on lightweight structures, and is costly and time-consuming to install and maintain on large civil structures, especially for long-term applications (e.g., structural health monitoring) that require significant maintenance for cabling (wired sensors) or periodic replacement of the energy supply (wireless sensors). Moreover, these sensors are typically placed at a limited number of discrete locations, providing low spatial sensing resolution that is hardly sufficient for modal-based damage localization, or model correlation and updating for larger-scale structures. Non-contact measurement methods such as scanning laser vibrometers provide high-resolution sensing capacity without the mass-loading effect; however, they make sequential measurements that require considerable acquisition time. As an alternative non-contact method, digital video cameras are relatively low-cost, agile, and provide high spatial resolution, simultaneous, measurements. Combined with vision based algorithms (e.g., image correlation, optical flow), video camera based measurements have been successfully used for vibration measurements and subsequent modal analysis, based on techniques such as the digital image correlation (DIC) and the point-tracking. However, they typically require speckle pattern or high-contrast markers to be placed on the surface of structures, which poses challenges when the measurement area is large or inaccessible. This work explores advanced computer vision and video processing algorithms to develop a novel video measurement and vision-based operational (output-only) modal analysis method that alleviate the need of structural surface preparation associated with existing vision-based methods and can be implemented in a relatively efficient and autonomous manner with little user supervision and calibration. First a multi-scale image processing method is applied on the frames of the video of a vibrating structure to extract the local pixel phases that encode local structural vibration, establishing a full-field spatiotemporal motion matrix. Then a high-spatial dimensional, yet low-modal-dimensional, over-complete model is used to represent the extracted full-field motion matrix using modal superposition, which is physically connected and manipulated by a family of unsupervised learning models and techniques, respectively. Thus, the proposed method is able to blindly extract modal frequencies, damping ratios, and full-field (as many points as the pixel number of the video frame) mode shapes from line of sight video measurements of the structure. The method is validated by laboratory experiments on a bench-scale building structure and a cantilever beam. Its ability for output (video measurements)-only identification and visualization of the weakly-excited mode is demonstrated and several issues with its implementation are discussed.

An albumin-based gold nanocomposites as potential dual mode CT/MRI contrast agent

NASA Astrophysics Data System (ADS)

Zhao, Wenjing; Chen, Lina; Wang, Zhiming; Huang, Yuankui; Jia, Nengqin

2018-02-01

In pursuit of the biological detection applications, recent years have witnessed the prosperity of novel multi-modal nanoprobes. In this study, biocompatible bovine serum albumin (BSA)-coated gold nanoparticles (Au NPs) containing Gd (III) as the contrast agent for both X-ray CT and T1-weighted MR imaging is reported. Firstly, the Au NPs with BSA coating (Au@BSA) was prepared through a moderate one-pot reduction route in the presence of hydrazine hydrate as reducer. Sequentially, the BSA coating enables modification of diethylenetriaminepentaacetic acid (DTPA) as well as targeting reagent hyaluronic acid (HA), and further chelation of Gd (III) ions led to the formation of biomimetic nanoagent HA-targeted Gd-Au NPs (HA-targeted Au@BSA-Gd-DTPA). Several techniques were used to thoroughly characterize the formed HA-targeted Gd-Au NPs. As expected, the as-prepared nanoagent with mean diameter of 13.82 nm exhibits not only good colloid stablility and water dispersibility, but also satisfying low cytotoxicity and hemocompatibility in the tested concentration range. Additionally, for the CT phantoms, the obtained nanocomplex shows an improved contrast in CT scanning than that of Au@BSA as well as small molecule iodine-based CT contrast agents such as iopromide. Meanwhile, for the T1-weighted MRI images, there is a linear increase of contrast with concentration of Gd for the two cases of HA-targeted Gd-Au NPs and Magnevist. Strikingly, the nanoagent we explored displays a relatively higher r1 relaxivity than that of commercial MR contrast agents. Therefore, this newly constructed nanoagent could be used as contrast agents for synergistically enhanced X-ray CT and MR phantoms, holding promising potential for future biomedical applications.

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.

Poly(acrylic acid) Bridged Gadolinium Metal-Organic Framework-Gold Nanoparticle Composites as Contrast Agents for Computed Tomography and Magnetic Resonance Bimodal Imaging

PubMed Central

Tian, Chixia; Zhu, Liping; Lin, Feng; Boyes, Stephen G.

2015-01-01

Imaging contrast agents for magnetic resonance imaging (MRI) and computed tomography (CT) have received significant attention in the development of techniques for early-stage cancer diagnosis. Gadolinium (Gd) (III), which has seven unpaired electrons and a large magnetic moment, can dramatically influence the water proton relaxation and hence exhibits excellent MRI contrast. On the other hand, gold (Au), which has a high atomic number and high x-ray attenuation coefficient, is an ideal contrast agent candidate for x-ray based CT imaging. Gd metal organic framework (MOF) nanoparticles with tunable size, high Gd (III) loading and multivalency can potentially overcome the limitations of clinically utilized Gd chelate contrast agents. In this work, we report for the first time the integration of GdMOF nanoparticles with gold nanoparticles (AuNPs) for the preparation of a MRI/CT bimodal imaging agent. Highly stable hybrid GdMOF/AuNPs composites have been prepared by using poly(acrylic acid) as a bridge between the GdMOF nanoparticles and AuNPs. The hybrid nanocomposites were then evaluated in MRI and CT imaging. The results revealed high longitudinal relaxivity in MRI and excellent CT imaging performance. Therefore, these GdMOF/AuNPs hybrid nanocomposites potentially provide a new platform for the development of multi-modal imaging probes. PMID:26147906

Development of magneto-plasmonic nanoparticles for multimodal image-guided therapy to the brain.

PubMed

Tomitaka, Asahi; Arami, Hamed; Raymond, Andrea; Yndart, Adriana; Kaushik, Ajeet; Jayant, Rahul Dev; Takemura, Yasushi; Cai, Yong; Toborek, Michal; Nair, Madhavan

2017-01-05

Magneto-plasmonic nanoparticles are one of the emerging multi-functional materials in the field of nanomedicine. Their potential for targeting and multi-modal imaging is highly attractive. In this study, magnetic core/gold shell (MNP@Au) magneto-plasmonic nanoparticles were synthesized by citrate reduction of Au ions on magnetic nanoparticle seeds. Hydrodynamic size and optical properties of magneto-plasmonic nanoparticles synthesized with the variation of Au ions and reducing agent concentrations were evaluated. The synthesized magneto-plasmonic nanoparticles exhibited superparamagnetic properties, and their magnetic properties contributed to the concentration-dependent contrast in magnetic resonance imaging (MRI). The imaging contrast from the gold shell part of the magneto-plasmonic nanoparticles was also confirmed by X-ray computed tomography (CT). The transmigration study of the magneto-plasmonic nanoparticles using an in vitro blood-brain barrier (BBB) model proved enhanced transmigration efficiency without disrupting the integrity of the BBB, and showed potential to be used for brain diseases and neurological disorders.

Simultaneous multi-scale microscopy as a potential dedicated tool for intra-operative parathyroid identification during thyroid surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

De Montigny, Étienne; Goulamhoussen, Nadir; Madore, Wendy-Julie; Strupler, Mathias; Maniakas, Anastasios; Ayad, Tareck; Boudoux, Caroline

2016-02-01

While thyroidectomy is considered a safe surgery, dedicated tools facilitating tissue identification during surgery could improve its outcome. The most common complication following surgery is hypocalcaemia, which results from iatrogenic removal or damage to parathyroid glands. This research project aims at developing and validating an instrument based on optical microscopy modalities to identify tissues in real time during surgery. Our approach is based on a combination of reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) to obtain multi-scale morphological contrast images. The orthogonal field of views provide information to navigate through the sample. To allow simultaneous, synchronized video-rate imaging in both modalities, we designed and built a dual-band wavelength-swept laser which scans a 30 nm band centered at 780 nm and a 90 nm band centered at 1310 nm. We built an imaging setup integrating a custom-made objective lens and a double-clad fibre coupler optimized for confocal microscopy. It features high resolutions in RCM (2µm lateral and 20 µm axial) in a 500 µm x 500 µm field-of-view and a larger field-of-view of 2 mm (lateral) x 5 mm (axial) with 20 µm lateral and axial resolutions in OCT. Imaging of ex vivo animal samples is demonstrated on a bench-top system. Tissues that are visually difficult to distinguish from each other intra-operatively such as parathyroid gland, lymph nodes and adipose tissue are imaged to show the potential of this approach in differentiating neck tissues. We will also provide an update on our ongoing clinical pilot study on patients undergoing thyroidectomy.

Fully integrated optical coherence tomography, ultrasound, and indocyanine green based fluorescence tri-modality system for intravascular imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Li, Yan; Jing, Joseph C.; Qu, Yueqiao; Miao, Yusi; Ma, Teng; Yu, Mingyue; Zhou, Qifa; Chen, Zhongping

2017-02-01

The rupture of atherosclerotic plaques is the leading cause of acute coronary events, so accurate assessment of plaque is critical. A large lipid pool, thin fibrous cap, and inflammatory reaction are the crucial characteristics for identifying vulnerable plaques. In our study, a tri-modality imaging system for intravascular imaging was designed and implemented. The tri-modality imaging system with a 1-mm probe diameter is able to simultaneously acquire optical coherence tomography (OCT), intravascular ultrasound (IVUS), and fluorescence imaging. Moreover, for fluorescence imaging, we used the FDA-approved indocyanine green (ICG) dye as the contrast agent to target lipid-loaded macrophages. Firstly, IVUS is used as the first step for identifying plaque since IVUS enables the visualization of the layered structures of the artery wall. Due to low soft-tissue contrast, IVUS only provides initial identification of the lipid plaque. Then OCT is used for differentiating fibrosis and lipid pool based on its relatively higher soft tissue contrast and high sensitivity/specificity. Last, fluorescence imaging is used for identifying inflammatory reaction to further confirm whether the plaque is vulnerable or not. Ex vivo experiment of a male New Zealand white rabbit aorta was performed to validate the performance of our tri-modality system. H and E histology results of the rabbit aorta were also presented to check assessment accuracy. The miniature tri-modality probe, together with the use of ICG dye suggest that the system is of great potential for providing a more accurate assessment of vulnerable plaques in clinical applications.

Ultrasound guidance to perform intra-articular injection of gadolinium-based contrast material for magnetic resonance arthrography as an alternative to fluoroscopy: the time is now.

PubMed

Messina, Carmelo; Banfi, Giuseppe; Aliprandi, Alberto; Mauri, Giovanni; Secchi, Francesco; Sardanelli, Francesco; Sconfienza, Luca Maria

2016-05-01

Magnetic resonance (MR) imaging has been definitively established as the reference standard in the evaluation of joints in the body. Similarly, magnetic resonance arthrography has emerged as a technique that has been proven to increase significantly the diagnostic performance if compared with conventional MR imaging, especially when dealing with fibrocartilage and articular cartilage abnormalities. Diluted gadolinium can be injected in the joint space using different approaches: under palpation using anatomic landmarks or using an imaging guidance, such as fluoroscopy, computed tomography, or ultrasound. Fluoroscopy has been traditionally used, but the involvement of ionizing radiation should represent a remarkable limitation of this modality. Conversely, ultrasound has emerged as a feasible, cheap, quick, and radiation-free modality that can be used to inject joints, with comparable accuracy of fluoroscopy. In the present paper, we discuss the advantages and disadvantages of using fluoroscopy or ultrasound in injecting gadolinium-based contrast agents in joints to perform magnetic resonance arthrography, also in view of the new EuroSAFE Imaging initiative promoted by the European Society of Radiology and the recent updates to the European Atomic Energy Community 2013/59 directive on the medical use of ionizing radiation. • Intra-articular contrast agent injection can be performed using different imaging modalities • Fluoroscopy is widely used, but uses ionizing radiation • Ultrasound is an accurate, quick, and radiation-free modality for joint injection • X-rays should be avoided when other radiation-free modalities can be used.

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

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.

Increasing knowledge of best practices for occupational therapists treating post-stroke unilateral spatial neglect: results of a knowledge-translation intervention study.

PubMed

Petzold, Anita; Korner-Bitensky, Nicol; Salbach, Nancy M; Ahmed, Sara; Menon, Anita; Ogourtsova, Tatiana

2012-02-01

The aim of this study was to investigate: (i) the feasibility of delivering a multi-modal knowledge translation intervention specific to the management of acute post-stroke unilateral spatial neglect; and (ii) the impact of the knowledge translation intervention on occupational therapists' knowledge of evidence-based unilateral spatial neglect problem identification, assessment and treatment, and self-efficacy related to evidence-based practice implementation. A 3-period (pre-post) repeated measures design. Acute care occupational therapists treating patients with post-stroke unilateral spatial neglect were recruited from two major Canadian cities. Participants completed two pre-intervention assessments, took part in a day-long interactive multi-modal knowledge translation intervention and a subsequent 8-week follow-up, and completed a post-intervention assessment. Knowledge of evidence-based problem identification, assessment and treatment of unilateral spatial neglect, and self-efficacy to perform evidence-based practice activities were measured using standard scales. The intervention was tested on 20 occupational therapists. Results indicate a significant improvement in knowledge of best practice unilateral spatial neglect management (p < 0.000) and evidence-based practice self-efficacy in carrying out evidence-based practice activities (p < 0.045) post-intervention. Use of a multi-modal knowledge translation intervention is feasible and can significantly improve occupational therapists' knowledge of unilateral spatial neglect best practices and self-efficacy. The findings should help advance best practices specific to the management of post-stroke unilateral spatial neglect as well as informing knowledge translation studies in other areas of practice.

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.

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.

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

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.

Thermal-to-visible face recognition using partial least squares.

PubMed

Hu, Shuowen; Choi, Jonghyun; Chan, Alex L; Schwartz, William Robson

2015-03-01

Although visible face recognition has been an active area of research for several decades, cross-modal face recognition has only been explored by the biometrics community relatively recently. Thermal-to-visible face recognition is one of the most difficult cross-modal face recognition challenges, because of the difference in phenomenology between the thermal and visible imaging modalities. We address the cross-modal recognition problem using a partial least squares (PLS) regression-based approach consisting of preprocessing, feature extraction, and PLS model building. The preprocessing and feature extraction stages are designed to reduce the modality gap between the thermal and visible facial signatures, and facilitate the subsequent one-vs-all PLS-based model building. We incorporate multi-modal information into the PLS model building stage to enhance cross-modal recognition. The performance of the proposed recognition algorithm is evaluated on three challenging datasets containing visible and thermal imagery acquired under different experimental scenarios: time-lapse, physical tasks, mental tasks, and subject-to-camera range. These scenarios represent difficult challenges relevant to real-world applications. We demonstrate that the proposed method performs robustly for the examined scenarios.

Retrospective Analysis of Communication Events - Understanding the Dynamics of Collaborative Multi-Party Discourse

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

Cowell, Andrew J.; Haack, Jereme N.; McColgin, Dave W.

2006-06-08

This research is aimed at understanding the dynamics of collaborative multi-party discourse across multiple communication modalities. Before we can truly make sig-nificant strides in devising collaborative communication systems, there is a need to understand how typical users utilize com-putationally supported communications mechanisms such as email, instant mes-saging, video conferencing, chat rooms, etc., both singularly and in conjunction with traditional means of communication such as face-to-face meetings, telephone calls and postal mail. Attempting to un-derstand an individual’s communications profile with access to only a single modal-ity is challenging at best and often futile. Here, we discuss the development of RACE –more » Retrospective Analysis of Com-munications Events – a test-bed prototype to investigate issues relating to multi-modal multi-party discourse.« less

Estimation of cardiac output and pulmonary vascular resistance by contrast echocardiography transit time measurement: a prospective pilot study.

PubMed

Choi, Brian G; Sanai, Reza; Yang, Benjamin; Young, Heather A; Mazhari, Ramesh; Reiner, Jonathan S; Lewis, Jannet F

2014-10-31

Studies with other imaging modalities have demonstrated a relationship between contrast transit and cardiac output (CO) and pulmonary vascular resistance (PVR). We tested the hypothesis that the transit time during contrast echocardiography could accurately estimate both CO and PVR compared to right heart catheterization (RHC). 27 patients scheduled for RHC had 2D-echocardiogram immediately prior to RHC. 3 ml of DEFINITY contrast followed by a 10 ml saline flush was injected, and a multi-cycle echo clip was acquired from the beginning of injection to opacification of the left ventricle. 2D-echo based calculations of CO and PVR along with the DEFINITY-based transit time calculations were subsequently correlated with the RHC-determined CO and PVR. The transit time from full opacification of the right ventricle to full opacification of the left ventricle inversely correlated with CO (r=-0.61, p<0.001). The transit time from peak opacification of the right ventricle to first appearance in the left ventricle moderately correlated with PVR (r=0.46, p<0.01). Previously described echocardiographic methods for the determination of CO (Huntsman method) and PVR (Abbas and Haddad methods) did not correlate with RHC-determined values (p = 0.20 for CO, p = 0.18 and p = 0.22 for PVR, respectively). The contrast transit time method demonstrated reliable intra- (p<0.0001) and inter-observer correlation (p<0.001). We describe a novel method for the quantification of CO and estimation of PVR using contrast echocardiography transit time. This technique adds to the methodologies used for noninvasive hemodynamic assessment, but requires further validation to determine overall applicability.

Automatic segmentation and quantification of the cardiac structures from non-contrast-enhanced cardiac CT scans

NASA Astrophysics Data System (ADS)

Shahzad, Rahil; Bos, Daniel; Budde, Ricardo P. J.; Pellikaan, Karlijn; Niessen, Wiro J.; van der Lugt, Aad; van Walsum, Theo

2017-05-01

Early structural changes to the heart, including the chambers and the coronary arteries, provide important information on pre-clinical heart disease like cardiac failure. Currently, contrast-enhanced cardiac computed tomography angiography (CCTA) is the preferred modality for the visualization of the cardiac chambers and the coronaries. In clinical practice not every patient undergoes a CCTA scan; many patients receive only a non-contrast-enhanced calcium scoring CT scan (CTCS), which has less radiation dose and does not require the administration of contrast agent. Quantifying cardiac structures in such images is challenging, as they lack the contrast present in CCTA scans. Such quantification would however be relevant, as it enables population based studies with only a CTCS scan. The purpose of this work is therefore to investigate the feasibility of automatic segmentation and quantification of cardiac structures viz whole heart, left atrium, left ventricle, right atrium, right ventricle and aortic root from CTCS scans. A fully automatic multi-atlas-based segmentation approach is used to segment the cardiac structures. Results show that the segmentation overlap between the automatic method and that of the reference standard have a Dice similarity coefficient of 0.91 on average for the cardiac chambers. The mean surface-to-surface distance error over all the cardiac structures is 1.4+/- 1.7 mm. The automatically obtained cardiac chamber volumes using the CTCS scans have an excellent correlation when compared to the volumes in corresponding CCTA scans, a Pearson correlation coefficient (R) of 0.95 is obtained. Our fully automatic method enables large-scale assessment of cardiac structures on non-contrast-enhanced CT scans.

A Pictorial Review of Hepatobiliary Magnetic Resonance Imaging With Hepatocyte-Specific Contrast Agents: Uses, Findings, and Pitfalls of Gadoxetate Disodium and Gadobenate Dimeglumine.

PubMed

Scali, Elena P; Walshe, Triona; Tiwari, Hina Arif; Harris, Alison C; Chang, Silvia D

2017-08-01

Magnetic resonance imaging (MRI) has a well-established role as a highly specific and accurate modality for characterizing benign and malignant focal liver lesions. In particular, contrast-enhanced MRI using hepatocyte-specific contrast agents (HSCAs) improves lesion detection and characterization compared to other imaging modalities and MRI techniques. In this pictorial review, the mechanism of action of gadolinium-based MRI contrast agents, with a focus on HSCAs, is described. The clinical indications, protocols, and emerging uses of the 2 commercially available combined contrast agents available in the United States, gadoxetate disodium and gadobenate dimeglumine, are discussed. The MRI features of these agents are compared with examples of focal hepatic masses, many of which have been obtained within the same patient therefore allowing direct lesion comparison. Finally, the pitfalls in the use of combined contrast agents in liver MRI are highlighted. Copyright © 2016 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

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.

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

α-Information Based Registration of Dynamic Scans for Magnetic Resonance Cystography

PubMed Central

Han, Hao; Lin, Qin; Li, Lihong; Duan, Chaijie; Lu, Hongbing; Li, Haifang; Yan, Zengmin; Fitzgerald, John

2015-01-01

To continue our effort on developing magnetic resonance (MR) cystography, we introduce a novel non–rigid 3D registration method to compensate for bladder wall motion and deformation in dynamic MR scans, which are impaired by relatively low signal–to–noise ratio in each time frame. The registration method is developed on the similarity measure of α–information, which has the potential of achieving higher registration accuracy than the commonly-used mutual information (MI) measure for either mono-modality or multi-modality image registration. The α–information metric was also demonstrated to be superior to both the mean squares and the cross-correlation metrics in multi-modality scenarios. The proposed α–registration method was applied for bladder motion compensation via real patient studies, and its effect to the automatic and accurate segmentation of bladder wall was also evaluated. Compared with the prevailing MI-based image registration approach, the presented α–information based registration was more effective to capture the bladder wall motion and deformation, which ensured the success of the following bladder wall segmentation to achieve the goal of evaluating the entire bladder wall for detection and diagnosis of abnormality. PMID:26087506

Multi-modal trip planning system : Northeastern Illinois Regional Transportation Authority.

DOT National Transportation Integrated Search

2013-01-01

This report evaluates the Multi-Modal Trip Planner System (MMTPS) implemented by the Northeastern Illinois Regional Transportation Authority (RTA) against the specific functional objectives enumerated by the Federal Transit Administration (FTA) in it...

Near-IR multi-modal imaging of natural occlusal lesions

NASA Astrophysics Data System (ADS)

Lee, Dustin; Fried, Daniel; Darling, Cynthia L.

2009-02-01

Reflectance and transillumination imaging show demineralization with high contrast in the near-IR. The objective of this study is to use lesion size and contrast acquired in reflectance and transillumination near-infrared imaging modes to estimate the severity of natural occlusal caries lesions. Previous studies have shown that near-infrared (NIR) light can be used to effectively image artificial carious lesions. However, its efficacy on natural lesions requires further exploration. Fifty extracted teeth with varying amounts of occlusal decay were examined using a NIR imaging system operating at 1310-nm. Image analysis software was used to calculate contrast values between sound and carious tooth structure. After imaging, teeth were histologically sampled at 1-mm intervals in order to determine lesion depth. Lesion contrast in transillumination mode significantly increased with lesion depth (p<0.001), while lesion contrast in reflectance mode did not increase. The lesion area demonstrated a significant increase with lesion severity in both imaging modes. These results suggest that lesion contrast and area can be used to estimate lesion severity in NIR images.

Non-invasive coronary angiography: the clinical value of multi-slice computed tomography in the assessment of patients with prior coronary bypass surgery. Evaluating grafts and native vessels.

PubMed

von Kiedrowski, Helge; Wiemer, Marcus; Franzke, Krista; Preuss, Rainer; Vaske, Bernhard; Butz, Thomas; Oldenburg, Olaf; Bitter, Thomas; Mahmood, Khalid; Burchert, Wolfram; Horstkotte, Dieter; Langer, Christoph

2009-02-01

Contrast enhanced multi-slice computed tomography (MSCT) is the leading modality in non-invasive coronary angiography (CTA) today. We investigated MSCT based assessment of coronary artery bypass grafts (CABG) by analyzing assets and drawbacks of CTA in order to define demands on latest technology. In a clinical setting 39 CABG patients (69.2 +/- 1.4 years; male n = 36) underwent CTA (collimation 16 x 0.75 mm, contrast medium 100 ml; 320 mAs, 120 KV). Ninety-seven CABG (61 venous, 36 arterial grafts) were evaluated. A subgroup of 18 patients underwent additional invasive coronary angiography (CA). CTA for CABG assessment resulted in an overall sensitivity (sens.) of 100%, specificity (spec.) of 92.4% and positive and negative predictive values (PPV, NPV) of 60% and 100%, respectively. CABG anastomoses showed slightly inferior diagnostic accuracy than other CABG segments. Limitations in imaging quality caused 21% unevaluable segments of the CABG anastomoses. Evaluation of native vessel segments proximal and distal to the anastomoses resulted in a sens, spec, PPV and NPV of 57.5, 94.6, 92 and 67.3%, respectively. With 28.5% unevaluable segments, the native vessel segments showed serious limitations in imaging quality. Radiation exposure was 9.88 +/- 3.20 mSv (9.69 +/- 3.25 mSv male; 12.08 +/- 1.35 mSv female). 16-slice MSCT based CABG assessment offers sufficient diagnostic accuracy. However, focussing on the bypass anastomoses and the native revascularized coronary arteries, clinical value is limited.

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

Simultaneous surface and depth neural activity recording with graphene transistor-based dual-modality probes.

PubMed

Du, Mingde; Xu, Xianchen; Yang, Long; Guo, Yichuan; Guan, Shouliang; Shi, Jidong; Wang, Jinfen; Fang, Ying

2018-05-15

Subdural surface and penetrating depth probes are widely applied to record neural activities from the cortical surface and intracortical locations of the brain, respectively. Simultaneous surface and depth neural activity recording is essential to understand the linkage between the two modalities. Here, we develop flexible dual-modality neural probes based on graphene transistors. The neural probes exhibit stable electrical performance even under 90° bending because of the excellent mechanical properties of graphene, and thus allow multi-site recording from the subdural surface of rat cortex. In addition, finite element analysis was carried out to investigate the mechanical interactions between probe and cortex tissue during intracortical implantation. Based on the simulation results, a sharp tip angle of π/6 was chosen to facilitate tissue penetration of the neural probes. Accordingly, the graphene transistor-based dual-modality neural probes have been successfully applied for simultaneous surface and depth recording of epileptiform activity of rat brain in vivo. Our results show that graphene transistor-based dual-modality neural probes can serve as a facile and versatile tool to study tempo-spatial patterns of neural activities. Copyright © 2018 Elsevier B.V. All rights reserved.

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 Traveler Information System - Gateway 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...

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...

[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.

Dual modality virtual colonoscopy workstation: design, implementation, and preliminary evaluation

NASA Astrophysics Data System (ADS)

Chen, Dongqing; Meissner, Michael

2006-03-01

The aim of this study is to develop a virtual colonoscopy (VC) workstation that supports both CT (computed tomography) and MR (magnetic resonance) imaging procedures. The workflow should be optimized and be able to take advantage of both image modalities. The technological break through is at the real-time volume rendering of spatial-intensity-inhomogeneous MR images to achieve high quality 3D endoluminal view. VC aims at visualizing CT or MR tomography images for detection of colonic polyp and lesion. It is also called as CT/MR colonography based on the imaging modality that is employed. The published results of large scale clinical trial demonstrated more than 90% of sensitivity on polyp detection for certain CT colonography (CTC) workstation. A drawback of the CT colonoscopy is the radiation exposure. MR colonography (MRC) is free from the X-ray radiation. It achieved almost 100% specificity for polyp detection in published trials. The better tissue contrast in MR image allows the accurate diagnosis of inflammatory bowel disease also, which is usually difficult in CTC. At present, most of the VC workstations are designed for CT examination. They are not able to display multi-sequence MR series concurrently in a single application. The automatic correlation between 2D and 3D view is not available due to the difficulty of 3D model building for MR images. This study aims at enhancing a commercial VC product that was successfully used for CTC to equally support dark-lumen protocol MR procedure also.

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.

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.

Brain-based decoding of mentally imagined film clips and sounds reveals experience-based information patterns in film professionals.

PubMed

de Borst, Aline W; Valente, Giancarlo; Jääskeläinen, Iiro P; Tikka, Pia

2016-04-01

In the perceptual domain, it has been shown that the human brain is strongly shaped through experience, leading to expertise in highly-skilled professionals. What has remained unclear is whether specialization also shapes brain networks underlying mental imagery. In our fMRI study, we aimed to uncover modality-specific mental imagery specialization of film experts. Using multi-voxel pattern analysis we decoded from brain activity of professional cinematographers and sound designers whether they were imagining sounds or images of particular film clips. In each expert group distinct multi-voxel patterns, specific for the modality of their expertise, were found during classification of imagery modality. These patterns were mainly localized in the occipito-temporal and parietal cortex for cinematographers and in the auditory cortex for sound designers. We also found generalized patterns across perception and imagery that were distinct for the two expert groups: they involved frontal cortex for the cinematographers and temporal cortex for the sound designers. Notably, the mental representations of film clips and sounds of cinematographers contained information that went beyond modality-specificity. We were able to successfully decode the implicit presence of film genre from brain activity during mental imagery in cinematographers. The results extend existing neuroimaging literature on expertise into the domain of mental imagery and show that experience in visual versus auditory imagery can alter the representation of information in modality-specific association cortices. Copyright © 2016 Elsevier Inc. All rights reserved.

Multi-modality image registration for effective thermographic fever screening

NASA Astrophysics Data System (ADS)

Dwith, C. Y. N.; Ghassemi, Pejhman; Pfefer, Joshua; Casamento, Jon; Wang, Quanzeng

2017-02-01

Fever screening based on infrared thermographs (IRTs) is a viable mass screening approach during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome (SARS), for temperature monitoring in public places like hospitals and airports. IRTs have been found to be powerful, quick and non-invasive methods for detecting elevated temperatures. Moreover, regions medially adjacent to the inner canthi (called the canthi regions in this paper) are preferred sites for fever screening. Accurate localization of the canthi regions can be achieved through multi-modality registration of infrared (IR) and white-light images. Here we propose a registration method through a coarse-fine registration strategy using different registration models based on landmarks and edge detection on eye contours. We have evaluated the registration accuracy to be within +/- 2.7 mm, which enables accurate localization of the canthi regions.

Nonlinear Reduced-Order Simulation Using Stress-Free and Pre-Stressed Modal Bases

NASA Technical Reports Server (NTRS)

Przekop, Adam; Stover, Michael A.; Rizzi, Stephen A.

2009-01-01

A study is undertaken to determine the advantages and disadvantages associated with application of stress-free and pre-stressed modal bases in a reduced-order finite-element-based nonlinear simulation. A planar beam is chosen as an application example and its response due to combined thermal and random pressure loadings is examined. Combinations of two random pressure levels and two thermal conditions are investigated. The latter consists of an ambient temperature condition and an elevated temperature condition in the post-buckled regime. It is found that stress-free normal modes establish a broadly applicable modal basis yielding accurate results for all the loading regimes considered. In contrast, the range of applicability for a thermally pre-stressed modal basis is found to be limited. The behavior is explained by scrutinizing the coupling found in the linear stiffness and the effect this coupling has on the structural response characteristics under the range of loading conditions considered.

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.

Super-contrast photoacoustic resonance imaging

NASA Astrophysics Data System (ADS)

Gao, Fei; Zhang, Ruochong; Feng, Xiaohua; Liu, Siyu; Zheng, Yuanjin

2018-02-01

In this paper, a new imaging modality, named photoacoustic resonance imaging (PARI), is proposed and experimentally demonstrated. Being distinct from conventional single nanosecond laser pulse induced wideband PA signal, the proposed PARI method utilizes multi-burst modulated laser source to induce PA resonant signal with enhanced signal strength and narrower bandwidth. Moreover, imaging contrast could be clearly improved than conventional single-pulse laser based PA imaging by selecting optimum modulation frequency of the laser source, which originates from physical properties of different materials beyond the optical absorption coefficient. Specifically, the imaging steps is as follows: 1: Perform conventional PA imaging by modulating the laser source as a short pulse to identify the location of the target and the background. 2: Shine modulated laser beam on the background and target respectively to characterize their individual resonance frequency by sweeping the modulation frequency of the CW laser source. 3: Select the resonance frequency of the target as the modulation frequency of the laser source, perform imaging and get the first PARI image. Then choose the resonance frequency of the background as the modulation frequency of the laser source, perform imaging and get the second PARI image. 4: subtract the first PARI image from the second PARI image, then we get the contrast-enhanced PARI results over the conventional PA imaging in step 1. Experimental validation on phantoms have been performed to show the merits of the proposed PARI method with much improved image contrast.

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.

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.

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.

Theory and preliminary experimental verification of quantitative edge illumination x-ray phase contrast tomography.

PubMed

Hagen, C K; Diemoz, P C; Endrizzi, M; Rigon, L; Dreossi, D; Arfelli, F; Lopez, F C M; Longo, R; Olivo, A

2014-04-07

X-ray phase contrast imaging (XPCi) methods are sensitive to phase in addition to attenuation effects and, therefore, can achieve improved image contrast for weakly attenuating materials, such as often encountered in biomedical applications. Several XPCi methods exist, most of which have already been implemented in computed tomographic (CT) modality, thus allowing volumetric imaging. The Edge Illumination (EI) XPCi method had, until now, not been implemented as a CT modality. This article provides indications that quantitative 3D maps of an object's phase and attenuation can be reconstructed from EI XPCi measurements. Moreover, a theory for the reconstruction of combined phase and attenuation maps is presented. Both reconstruction strategies find applications in tissue characterisation and the identification of faint, weakly attenuating details. Experimental results for wires of known materials and for a biological object validate the theory and confirm the superiority of the phase over conventional, attenuation-based image contrast.

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 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 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 fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

PubMed

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Probabilistic sparse matching for robust 3D/3D fusion in minimally invasive surgery.

PubMed

Neumann, Dominik; Grbic, Sasa; John, Matthias; Navab, Nassir; Hornegger, Joachim; Ionasec, Razvan

2015-01-01

Classical surgery is being overtaken by minimally invasive and transcatheter procedures. As there is no direct view or access to the affected anatomy, advanced imaging techniques such as 3D C-arm computed tomography (CT) and C-arm fluoroscopy are routinely used in clinical practice for intraoperative guidance. However, due to constraints regarding acquisition time and device configuration, intraoperative modalities have limited soft tissue image quality and reliable assessment of the cardiac anatomy typically requires contrast agent, which is harmful to the patient and requires complex acquisition protocols. We propose a probabilistic sparse matching approach to fuse high-quality preoperative CT images and nongated, noncontrast intraoperative C-arm CT images by utilizing robust machine learning and numerical optimization techniques. Thus, high-quality patient-specific models can be extracted from the preoperative CT and mapped to the intraoperative imaging environment to guide minimally invasive procedures. Extensive quantitative experiments on 95 clinical datasets demonstrate that our model-based fusion approach has an average execution time of 1.56 s, while the accuracy of 5.48 mm between the anchor anatomy in both images lies within expert user confidence intervals. In direct comparison with image-to-image registration based on an open-source state-of-the-art medical imaging library and a recently proposed quasi-global, knowledge-driven multi-modal fusion approach for thoracic-abdominal images, our model-based method exhibits superior performance in terms of registration accuracy and robustness with respect to both target anatomy and anchor anatomy alignment errors.

Methylene blue microbubbles as a model dual-modality contrast agent for ultrasound and activatable photoacoustic imaging

NASA Astrophysics Data System (ADS)

Jeon, Mansik; Song, Wentao; Huynh, Elizabeth; Kim, Jungho; Kim, Jeesu; Helfield, Brandon L.; Leung, Ben Y. C.; Goertz, David E.; Zheng, Gang; Oh, Jungtaek; Lovell, Jonathan F.; Kim, Chulhong

2014-01-01

Ultrasound and photoacoustic imaging are highly complementary modalities since both use ultrasonic detection for operation. Increasingly, photoacoustic and ultrasound have been integrated in terms of hardware instrumentation. To generate a broadly accessible dual-modality contrast agent, we generated microbubbles (a standard ultrasound contrast agent) in a solution of methylene blue (a standard photoacoustic dye). This MB2 solution was formed effectively and was optimized as a dual-modality contrast solution. As microbubble concentration increased (with methylene blue concentration constant), photoacoustic signal was attenuated in the MB2 solution. When methylene blue concentration increased (with microbubble concentration held constant), no ultrasonic interference was observed. Using an MB2 solution that strongly attenuated all photoacoustic signal, high powered ultrasound could be used to burst the microbubbles and dramatically enhance photoacoustic contrast (>800-fold increase), providing a new method for spatiotemporal control of photoacoustic signal generation.

Methylene blue microbubbles as a model dual-modality contrast agent for ultrasound and activatable photoacoustic imaging.

PubMed

Jeon, Mansik; Song, Wentao; Huynh, Elizabeth; Kim, Jungho; Kim, Jeesu; Helfield, Brandon L; Leung, Ben Y C; Goertz, David E; Zheng, Gang; Oh, Jungtaek; Lovell, Jonathan F; Kim, Chulhong

2014-01-01

Ultrasound and photoacoustic imaging are highly complementary modalities since both use ultrasonic detection for operation. Increasingly, photoacoustic and ultrasound have been integrated in terms of hardware instrumentation. To generate a broadly accessible dual-modality contrast agent, we generated microbubbles (a standard ultrasound contrast agent) in a solution of methylene blue (a standard photoacoustic dye). This MB2 solution was formed effectively and was optimized as a dual-modality contrast solution. As microbubble concentration increased (with methylene blue concentration constant), photoacoustic signal was attenuated in the MB2 solution. When methylene blue concentration increased (with microbubble concentration held constant), no ultrasonic interference was observed. Using an MB2 solution that strongly attenuated all photoacoustic signal, high powered ultrasound could be used to burst the microbubbles and dramatically enhance photoacoustic contrast (>800-fold increase), providing a new method for spatiotemporal control of photoacoustic signal generation.

Integrated photoacoustic microscopy, optical coherence tomography, and fluorescence microscopy for multimodal chorioretinal imaging

NASA Astrophysics Data System (ADS)

Tian, Chao; Zhang, Wei; Nguyen, Van Phuc; Huang, Ziyi; Wang, Xueding; Paulus, Yannis M.

2018-02-01

Current clinical available retinal imaging techniques have limitations, including limited depth of penetration or requirement for the invasive injection of exogenous contrast agents. Here, we developed a novel multimodal imaging system for high-speed, high-resolution retinal imaging of larger animals, such as rabbits. The system integrates three state-of-the-art imaging modalities, including photoacoustic microscopy (PAM), optical coherence tomography (OCT), and fluorescence microscopy (FM). In vivo experimental results of rabbit eyes show that the PAM is able to visualize laser-induced retinal burns and distinguish individual eye blood vessels using a laser exposure dose of 80 nJ, which is well below the American National Standards Institute (ANSI) safety limit 160 nJ. The OCT can discern different retinal layers and visualize laser burns and choroidal detachments. The novel multi-modal imaging platform holds great promise in ophthalmic imaging.

Combining Video, Audio and Lexical Indicators of Affect in Spontaneous Conversation via Particle Filtering

PubMed Central

Savran, Arman; Cao, Houwei; Shah, Miraj; Nenkova, Ani; Verma, Ragini

2013-01-01

We present experiments on fusing facial video, audio and lexical indicators for affect estimation during dyadic conversations. We use temporal statistics of texture descriptors extracted from facial video, a combination of various acoustic features, and lexical features to create regression based affect estimators for each modality. The single modality regressors are then combined using particle filtering, by treating these independent regression outputs as measurements of the affect states in a Bayesian filtering framework, where previous observations provide prediction about the current state by means of learned affect dynamics. Tested on the Audio-visual Emotion Recognition Challenge dataset, our single modality estimators achieve substantially higher scores than the official baseline method for every dimension of affect. Our filtering-based multi-modality fusion achieves correlation performance of 0.344 (baseline: 0.136) and 0.280 (baseline: 0.096) for the fully continuous and word level sub challenges, respectively. PMID:25300451

Combining Video, Audio and Lexical Indicators of Affect in Spontaneous Conversation via Particle Filtering.

PubMed

Savran, Arman; Cao, Houwei; Shah, Miraj; Nenkova, Ani; Verma, Ragini

2012-01-01

We present experiments on fusing facial video, audio and lexical indicators for affect estimation during dyadic conversations. We use temporal statistics of texture descriptors extracted from facial video, a combination of various acoustic features, and lexical features to create regression based affect estimators for each modality. The single modality regressors are then combined using particle filtering, by treating these independent regression outputs as measurements of the affect states in a Bayesian filtering framework, where previous observations provide prediction about the current state by means of learned affect dynamics. Tested on the Audio-visual Emotion Recognition Challenge dataset, our single modality estimators achieve substantially higher scores than the official baseline method for every dimension of affect. Our filtering-based multi-modality fusion achieves correlation performance of 0.344 (baseline: 0.136) and 0.280 (baseline: 0.096) for the fully continuous and word level sub challenges, respectively.

Dynamic characteristics of the blisk with synchronized switch damping based on negative capacitor

NASA Astrophysics Data System (ADS)

Liu, J.; Li, L.; Huang, X.; Jezequel, L.

2017-10-01

In this paper, we propose a method to suppress the vibration of the integral bladed disk ('blisk' for short) in aero-engines using synchronized switch damping based on negative capacitor (SSDNC). Different from the classical piezoelectric shunt damping, SSDNC is a type of nonlinear piezoelectric damping. A multi-harmonic balance method combined with the alternating frequency/time method (MHBM-AFT) is used to predict and further analyze the dynamic characteristics of the electromechanical system, and an arc-length continuation technique is used to improve the convergence of the method. In order to validate the algorithm as well as to recognize the characteristics of the system with SSDNC, a two degree-of-freedom (2-DOF) system with SSDNC is studied at first. The nonlinear complex modal information is calculated and compared with those of the corresponding system with a linear RL shunt circuit. The results indicate that the natural frequencies and modal damping ratio do not change with the modal amplitude, which means that SSDNC has the same modal damping corresponding to different system energy levels. In addition, SSDNC can improve the damping level of all the modes nearly without affecting the natural frequencies of the system. Then, the forced response of the blisk with SSDNC in the frequency domain is calculated and analyzed, including a tuned blisk, which is excited by the traveling wave excitation with a single harmonic and multi-harmonic, and a mistuned blisk, which is excited by traveling wave excitation with a single harmonic and multi-harmonic. We present two advantages of the SSDNC technique when compared with piezoelectric shunt damping. First, SSDNC can suppress the vibration of the blisk under a multi-harmonic wideband the traveling wave, and second, the vibration suppression performance of SSDNC is insensitive to the mistuning of mechanical parameters of the blisk. The results will be of great significance in overcoming the problem of the amplitude magnification induced by the inevitable mistuning of the blisk in aero-engines.

DMD-based LED-illumination super-resolution and optical sectioning microscopy.

PubMed

Dan, Dan; Lei, Ming; Yao, Baoli; Wang, Wen; Winterhalder, Martin; Zumbusch, Andreas; Qi, Yujiao; Xia, Liang; Yan, Shaohui; Yang, Yanlong; Gao, Peng; Ye, Tong; Zhao, Wei

2013-01-01

Super-resolution three-dimensional (3D) optical microscopy has incomparable advantages over other high-resolution microscopic technologies, such as electron microscopy and atomic force microscopy, in the study of biological molecules, pathways and events in live cells and tissues. We present a novel approach of structured illumination microscopy (SIM) by using a digital micromirror device (DMD) for fringe projection and a low-coherence LED light for illumination. The lateral resolution of 90 nm and the optical sectioning depth of 120 μm were achieved. The maximum acquisition speed for 3D imaging in the optical sectioning mode was 1.6×10(7) pixels/second, which was mainly limited by the sensitivity and speed of the CCD camera. In contrast to other SIM techniques, the DMD-based LED-illumination SIM is cost-effective, ease of multi-wavelength switchable and speckle-noise-free. The 2D super-resolution and 3D optical sectioning modalities can be easily switched and applied to either fluorescent or non-fluorescent specimens.

DMD-based LED-illumination Super-resolution and optical sectioning microscopy

PubMed Central

Dan, Dan; Lei, Ming; Yao, Baoli; Wang, Wen; Winterhalder, Martin; Zumbusch, Andreas; Qi, Yujiao; Xia, Liang; Yan, Shaohui; Yang, Yanlong; Gao, Peng; Ye, Tong; Zhao, Wei

2013-01-01

Super-resolution three-dimensional (3D) optical microscopy has incomparable advantages over other high-resolution microscopic technologies, such as electron microscopy and atomic force microscopy, in the study of biological molecules, pathways and events in live cells and tissues. We present a novel approach of structured illumination microscopy (SIM) by using a digital micromirror device (DMD) for fringe projection and a low-coherence LED light for illumination. The lateral resolution of 90 nm and the optical sectioning depth of 120 μm were achieved. The maximum acquisition speed for 3D imaging in the optical sectioning mode was 1.6×107 pixels/second, which was mainly limited by the sensitivity and speed of the CCD camera. In contrast to other SIM techniques, the DMD-based LED-illumination SIM is cost-effective, ease of multi-wavelength switchable and speckle-noise-free. The 2D super-resolution and 3D optical sectioning modalities can be easily switched and applied to either fluorescent or non-fluorescent specimens. PMID:23346373

Dual-modality NIRF-MRI cubosomes and hexosomes: High throughput formulation and in vivo biodistribution.

PubMed

Tran, Nhiem; Bye, Nicole; Moffat, Bradford A; Wright, David K; Cuddihy, Andrew; Hinton, Tracey M; Hawley, Adrian M; Reynolds, Nicholas P; Waddington, Lynne J; Mulet, Xavier; Turnley, Ann M; Morganti-Kossmann, M Cristina; Muir, Benjamin W

2017-02-01

Engineered nanoparticles with multiple complementary imaging modalities are of great benefit to the rapid treatment and diagnosis of disease in various organs. Herein, we report the formulation of cubosomes and hexosomes that carry multiple amphiphilic imaging contrast agents in their self-assembled lipid bilayers. This is the first report of the use of both near infrared fluorescent (NIRF) imaging and gadolinium lipid based magnetic resonance (MR) imaging modalities in cubosomes and hexosomes. High-throughput screening was used to rapidly optimize formulations with desirable nano-architectures and low in vitro cytotoxicity. The dual-modal imaging nanoparticles in vivo biodistribution and organ specific contrast enhancement were then studied. The NIRF in vivo imaging results indicated accumulation of both cubosomes and hexosomes in the liver and spleen of mice up to 20h post-injection. Remarkably, the biodistribution of the nanoparticle formulations was affected by the mesophase (i.e. cubic or hexagonal), a finding of significant importance for the future use of these compounds, with hexosomes showing higher accumulation in the spleen than the liver compared to cubosomes. Furthermore, in vivo MRI data of animals injected with either type of lyotropic liquid crystal nanoparticle displayed enhanced contrast in the liver and spleen. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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

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 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 data fusion using source separation: Two effective models based on ICA and IVA and their properties

PubMed Central

Adali, Tülay; Levin-Schwartz, Yuri; Calhoun, Vince D.

2015-01-01

Fusion of information from multiple sets of data in order to extract a set of features that are most useful and relevant for the given task is inherent to many problems we deal with today. Since, usually, very little is known about the actual interaction among the datasets, it is highly desirable to minimize the underlying assumptions. This has been the main reason for the growing importance of data-driven methods, and in particular of independent component analysis (ICA) as it provides useful decompositions with a simple generative model and using only the assumption of statistical independence. A recent extension of ICA, independent vector analysis (IVA) generalizes ICA to multiple datasets by exploiting the statistical dependence across the datasets, and hence, as we discuss in this paper, provides an attractive solution to fusion of data from multiple datasets along with ICA. In this paper, we focus on two multivariate solutions for multi-modal data fusion that let multiple modalities fully interact for the estimation of underlying features that jointly report on all modalities. One solution is the Joint ICA model that has found wide application in medical imaging, and the second one is the the Transposed IVA model introduced here as a generalization of an approach based on multi-set canonical correlation analysis. In the discussion, we emphasize the role of diversity in the decompositions achieved by these two models, present their properties and implementation details to enable the user make informed decisions on the selection of a model along with its associated parameters. Discussions are supported by simulation results to help highlight the main issues in the implementation of these methods. PMID:26525830

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.

Techniques for efficient, real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware.

PubMed

Levin, David; Aladl, Usaf; Germano, Guido; Slomka, Piotr

2005-09-01

We exploit consumer graphics hardware to perform real-time processing and visualization of high-resolution, 4D cardiac data. We have implemented real-time, realistic volume rendering, interactive 4D motion segmentation of cardiac data, visualization of multi-modality cardiac data and 3D display of multiple series cardiac MRI. We show that an ATI Radeon 9700 Pro can render a 512x512x128 cardiac Computed Tomography (CT) study at 0.9 to 60 frames per second (fps) depending on rendering parameters and that 4D motion based segmentation can be performed in real-time. We conclude that real-time rendering and processing of cardiac data can be implemented on consumer graphics cards.

Determination of the critical bending speeds of a multy-rotor shaft from the vibration signal analysis

NASA Astrophysics Data System (ADS)

Crâştiu, I.; Nyaguly, E.; Deac, S.; Gozman-Pop, C.; Bârgău, A.; Bereteu, L.

2018-01-01

The purpose of this paper is the development and validation of an impulse excitation technique to determine flexural critical speeds of a single rotor shaft and multy-rotor shaft. The experimental measurement of the vibroacoustic response is carried out by using a condenser microphone as a transducer. By the means of Modal Analysis using Finite Element Method (FEM), the natural frequencies and shape modes of one rotor and three rotor specimens are determined. The vibration responses of the specimens, in simple supported conditions, are carried out using algorithms based on Fast Fourier Transform (FFT). To validate the results of the modal parameters estimated using Finite Element Analysis (FEA) these are compared with experimental ones.

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.

Collaboration of Miniature Multi-Modal Mobile Smart Robots over a Network

DTIC Science & Technology

2015-08-14

theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The views...theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The...independently evolving research directions based on physics-based models of mechanical, electromechanical and electronic devices, operational constraints

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

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 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

A Review of Intravascular Ultrasound–Based Multimodal Intravascular Imaging: The Synergistic Approach to Characterizing Vulnerable Plaques

PubMed Central

Ma, Teng; Zhou, Bill; Hsiai, Tzung K.; Shung, K. Kirk

2015-01-01

Catheter-based intravascular imaging modalities are being developed to visualize pathologies in coronary arteries, such as high-risk vulnerable atherosclerotic plaques known as thin-cap fibroatheroma, to guide therapeutic strategy at preventing heart attacks. Mounting evidences have shown three distinctive histopathological features—the presence of a thin fibrous cap, a lipid-rich necrotic core, and numerous infiltrating macrophages—are key markers of increased vulnerability in atherosclerotic plaques. To visualize these changes, the majority of catheter-based imaging modalities used intravascular ultrasound (IVUS) as the technical foundation and integrated emerging intravascular imaging techniques to enhance the characterization of vulnerable plaques. However, no current imaging technology is the unequivocal “gold standard” for the diagnosis of vulnerable atherosclerotic plaques. Each intravascular imaging technology possesses its own unique features that yield valuable information although encumbered by inherent limitations not seen in other modalities. In this context, the aim of this review is to discuss current scientific innovations, technical challenges, and prospective strategies in the development of IVUS-based multi-modality intravascular imaging systems aimed at assessing atherosclerotic plaque vulnerability. PMID:26400676

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

A multi-image approach to CADx of breast cancer with integration into PACS

NASA Astrophysics Data System (ADS)

Elter, Matthias; Wittenberg, Thomas; Schulz-Wendtland, Rüdiger; Deserno, Thomas M.

2009-02-01

While screening mammography is accepted as the most adequate technique for the early detection of breast cancer, its low positive predictive value leads to many breast biopsies performed on benign lesions. Therefore, we have previously developed a knowledge-based system for computer-aided diagnosis (CADx) of mammographic lesions. It supports the radiologist in the discrimination of benign and malignant lesions. So far, our approach operates on the lesion level and employs the paradigm of content-based image retrieval (CBIR). Similar lesions with known diagnosis are retrieved automatically from a library of references. However, radiologists base their diagnostic decisions on additional resources, such as related mammographic projections, other modalities (e.g. ultrasound, MRI), and clinical data. Nonetheless, most CADx systems disregard the relation between the craniocaudal (CC) and mediolateral-oblique (MLO) views of conventional mammography. Therefore, we extend our approach to the full case level: (i) Multi-frame features are developed that jointly describe a lesion in different views of mammography. Taking into account the geometric relation between different images, these features can also be extracted from multi-modal data; (ii) the CADx system architecture is extended appropriately; (iii) the CADx system is integrated into the radiology information system (RIS) and the picture archiving and communication system (PACS). Here, the framework for image retrieval in medical applications (IRMA) is used to support access to the patient's health care record. Of particular interest is the application of the proposed CADx system to digital breast tomosynthesis (DBT), which has the potential to succeed digital mammography as the standard technique for breast cancer screening. The proposed system is a natural extension of CADx approaches that integrate only two modalities. However, we are still collecting a large enough database of breast lesions with images from multiple modalities to evaluate the benefits of the proposed approach on.

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...

Novel Multistatic Adaptive Microwave Imaging Methods for Early Breast Cancer Detection

NASA Astrophysics Data System (ADS)

Xie, Yao; Guo, Bin; Li, Jian; Stoica, Petre

2006-12-01

Multistatic adaptive microwave imaging (MAMI) methods are presented and compared for early breast cancer detection. Due to the significant contrast between the dielectric properties of normal and malignant breast tissues, developing microwave imaging techniques for early breast cancer detection has attracted much interest lately. MAMI is one of the microwave imaging modalities and employs multiple antennas that take turns to transmit ultra-wideband (UWB) pulses while all antennas are used to receive the reflected signals. MAMI can be considered as a special case of the multi-input multi-output (MIMO) radar with the multiple transmitted waveforms being either UWB pulses or zeros. Since the UWB pulses transmitted by different antennas are displaced in time, the multiple transmitted waveforms are orthogonal to each other. The challenge to microwave imaging is to improve resolution and suppress strong interferences caused by the breast skin, nipple, and so forth. The MAMI methods we investigate herein utilize the data-adaptive robust Capon beamformer (RCB) to achieve high resolution and interference suppression. We will demonstrate the effectiveness of our proposed methods for breast cancer detection via numerical examples with data simulated using the finite-difference time-domain method based on a 3D realistic breast model.

PSMA-Targeted Nano-Conjugates as Dual-Modality (MRI/PET) Imaging Probes for the Non-Invasive Detection of Prostate Cancer

DTIC Science & Technology

2009-10-01

be made. Currently, iodine based compounds are used to enhance contrast of CT which have the limitations of short imaging window due to rapid...number compared to conventionally used iodine compounds . Nanoparticle based CT contrast agents have been demonstrated for vascular imaging, which...constructs with gamma or positron emitting isotopes through a covalent attachment of a bifunctional chelator to the nanoparticles surface. However, in

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.

Multi-Modal Traveler Information System - Lessons Learned

DOT National Transportation Integrated Search

1997-05-19

The purpose of this working paper is to provide an information base of lessons learned from activities similar to the design of the Gary Chicago Milwaukee (GCM) Corridor Architecture and the Gateway Traveler Information System (TIS). Many similar act...

Multi-Modal Traveler Information System - Cellular 911-State of the Practice

DOT National Transportation Integrated Search

1997-05-19

Working paper evaluates the implemented public 911 and private non-911 cellular : based emergency centers around the country, and within the : Gary-Chicago-Milwaukee (GCM) Corridor and documents the impact, implications and : experiences of switching...

A highly sensitive x-ray imaging modality for hepatocellular carcinoma detection in vitro

NASA Astrophysics Data System (ADS)

Rand, Danielle; Walsh, Edward G.; Derdak, Zoltan; Wands, Jack R.; Rose-Petruck, Christoph

2015-01-01

Innovations that improve sensitivity and reduce cost are of paramount importance in diagnostic imaging. The novel x-ray imaging modality called spatial frequency heterodyne imaging (SFHI) is based on a linear arrangement of x-ray source, tissue, and x-ray detector, much like that of a conventional x-ray imaging apparatus. However, SFHI rests on a complete paradigm reversal compared to conventional x-ray absorption-based radiology: while scattered x-rays are carefully rejected in absorption-based x-ray radiology to enhance the image contrast, SFHI forms images exclusively from x-rays scattered by the tissue. In this study we use numerical processing to produce x-ray scatter images of hepatocellular carcinoma labeled with a nanoparticle contrast agent. We subsequently compare the sensitivity of SFHI in this application to that of both conventional x-ray imaging and magnetic resonance imaging (MRI). Although SFHI is still in the early stages of its development, our results show that the sensitivity of SFHI is an order of magnitude greater than that of absorption-based x-ray imaging and approximately equal to that of MRI. As x-ray imaging modalities typically have lower installation and service costs compared to MRI, SFHI could become a cost effective alternative to MRI, particularly in areas of the world with inadequate availability of MRI facilities.

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.

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.

Experimentally enhanced model-based deconvolution of propagation-based phase-contrast data

NASA Astrophysics Data System (ADS)

Pichotka, M.; Palma, K.; Hasn, S.; Jakubek, J.; Vavrik, D.

2016-12-01

In recent years phase-contrast has become a much investigated modality in radiographic imaging. The radiographic setups employed in phase-contrast imaging are typically rather costly and complex, e.g. high performance Talbot-Laue interferometers operated at synchrotron light sources. In-line phase-contrast imaging states the most pedestrian approach towards phase-contrast enhancement. Utilizing small angle deflection within the imaged sample and the entailed interference of the deflected and un-deflected beam during spatial propagation, in-line phase-contrast imaging only requires a well collimated X-ray source with a high contrast & high resolution detector. Employing high magnification the above conditions are intrinsically fulfilled in cone-beam micro-tomography. As opposed of 2D imaging, where contrast enhancement is generally considered beneficial, in tomographic modalities the in-line phase-contrast effect can be quite a nuisance since it renders the inverse problem posed by tomographic reconstruction inconsistent, thus causing reconstruction artifacts. We present an experimentally enhanced model-based approach to disentangle absorption and in-line phase-contrast. The approach employs comparison of transmission data to a system model computed iteratively on-line. By comparison of the forward model to absorption data acquired in continuous rotation strong local deviations of the data residual are successively identified as likely candidates for in-line phase-contrast. By inducing minimal vibrations (few mrad) to the sample around the peaks of such deviations the transmission signal can be decomposed into a constant absorptive fraction and an oscillating signal caused by phase-contrast which again allows to generate separate maps for absorption and phase-contrast. The contributions of phase-contrast and the corresponding artifacts are subsequently removed from the tomographic dataset. In principle, if a 3D handling of the sample is available, this method also allows to track discontinuities throughout the volume and therefore states a powerful tool in 3D defectoscopy.

(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

Utilizing Multi-Modal Literacies in Middle Grades Science

ERIC Educational Resources Information Center

Saurino, Dan; Ogletree, Tamra; Saurino, Penelope

2010-01-01

The nature of literacy is changing. Increased student use of computer-mediated, digital, and visual communication spans our understanding of adolescent multi-modal capabilities that reach beyond the traditional conventions of linear speech and written text in the science curriculum. Advancing technology opens doors to learning that involve…

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

PubMed

Pycinski, Bartlomiej; Czajkowska, Joanna; Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

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

Autofluorescence spectroscopy for multimodal tissues characterization in colitis-associated cancer murine model

NASA Astrophysics Data System (ADS)

Dorez, Hugo; Sablong, Raphaël.; Canaple, Laurence; Saint-Jalmes, Hervé; Gaillard, Sophie; Moussata, Driffa; Beuf, Olivier

2015-07-01

The purpose of this research project is to assess mice colon wall, using three optical modalities (conventional endoscopy, confocal endomicroscopy and optical spectroscopy) and endoluminal MRI. The study is done in the context of inflammatory bowel disease and colorectal cancer that represent 13% of new cases of cancer, every year in western countries. An optical spectroscopic bench (autofluorescence and reflectance) was developed with a flexible fiber probe. This latter has been combined with a mini multi-purpose rigid endoscope and a confocal endomicroscope. The optical modalities were first used in vivo on SWISS mice. Then, a specific optical a phantom (containing two layers of distinct fluorophores) was developed in order to evaluate our two-channel spectroscopic probe as a basic depth-sensitive measurement tool. The preliminary results show the feasibility to combine such modalities in the same in vivo protocol. Conventional endoscopy is useful to depict inflammation along colon wall. Confocal endomicroscopy provides high-contrasted images of microvascularization. Measured optical spectra both depend on biochemical tissue content and layered structure of the medium. The light collected from one channel is not similar to the other, in terms of intensity and spectroscopic profile as the interaction with the medium observed volume is different. A comparative analysis of the spectra based on our in vitro model exhibits a strong correlation between simple index extracted from spectral data and two main phantom characteristics (fluorophore concentrations and superficial layer thickness). This work suggests that this technique could contribute to assess tissues alterations through autofluorescence spectroscopic measurement under endoscopy.

Impact of screening colonoscopy on outcomes in colorectal cancer.

PubMed

Matsuda, Takahisa; Ono, Akiko; Kakugawa, Yasuo; Matsumoto, Minori; Saito, Yutaka

2015-10-01

Colorectal cancer is one of the most common cancers in both men and women worldwide and a good candidate for screening programs. There are two modalities of colorectal cancer screening: (i) population-based screening and (ii) opportunistic screening. The first one is based on organized, well-coordinated, monitored and established programs with a systematic invitation covering the entire target population. In contrast, opportunistic screening tests are offered to people who are being examined for other reasons. Recently, a variety of colorectal cancer screening tests have become available; each country should make a choice, based on national demographics and resources, on the screening method to be used. Fecal occult blood test, especially the fecal immunochemical test, would be the best modality for decreasing colorectal cancer mortality through population-based screening. In contrast, if the aim includes the early detection of colorectal cancer and adenomas, endoscopic methods are more appropriate. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Registers in Infant Phonation.

PubMed

Buder, Eugene H; McDaniel, Valerie F; Bene, Edina R; Ladmirault, Jennifer; Oller, D Kimbrough

2018-04-09

The primary vocal registers of modal, falsetto, and fry have been studied in adults but not per se in infancy. The vocal ligament is thought to play a critical role in the modal-falsetto contrast but is still developing during infancy (Tateya and Tateya, 2015). 41 Cover tissues are also implicated in the modal-fry contrast, but the low fundamental frequency (f o ) cutoff of 70 Hz, shared between genders, suggests a psychoacoustic basis for the contrast. Buder, Chorna, Oller, and Robinson (2008) 6 used the labels of "loft," "modal," and "pulse" for distinct vibratory regimes that appear to be identifiable based on spectrographic inspection of harmonic structure and auditory judgments in infants, but this work did not supply acoustic measurements to verify which of these nominally labeled regimes resembled adult registers. In this report, we identify clear transitions between registers within infant vocalizations and measure these registers and their transitions for f o and relative harmonic amplitudes (H1-H2). By selectively sampling first-year vocalizations, this manuscript quantifies acoustic patterns that correspond to vocal fold vibration types not previously cataloged in infancy. Results support a developmental basis for vocal registers, revealing that a well-developed ligament is not needed for loft-modal quality shifts as seen in harmonic amplitude measures. Results also reveal that a distinctively pulsatile register can occur in infants at a much higher f o than expected on psychoacoustic grounds. Overall results are consistent with cover tissues in infancy that are, for vibratory purposes, highly compliant and readily detached. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

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.

Hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic imaging

NASA Astrophysics Data System (ADS)

Chen, Zhenyue; Deán-Ben, Xosé Luís.; Gottschalk, Sven; Razansky, Daniel

2018-02-01

Fluorescence imaging is widely employed in all fields of cell and molecular biology due to its high sensitivity, high contrast and ease of implementation. However, the low spatial resolution and lack of depth information, especially in strongly-scattering samples, restrict its applicability for deep-tissue imaging applications. On the other hand, optoacoustic imaging is known to deliver a unique set of capabilities such as high spatial and temporal resolution in three dimensions, deep penetration and spectrally-enriched imaging contrast. Since fluorescent substances can generate contrast in both modalities, simultaneous fluorescence and optoacoustic readings can provide new capabilities for functional and molecular imaging of living organisms. Optoacoustic images can further serve as valuable anatomical references based on endogenous hemoglobin contrast. Herein, we propose a hybrid system for in vivo real-time planar fluorescence and volumetric optoacoustic tomography, both operating in reflection mode, which synergistically combines the advantages of stand-alone systems. Validation of the spatial resolution and sensitivity of the system were first carried out in tissue mimicking phantoms while in vivo imaging was further demonstrated by tracking perfusion of an optical contrast agent in a mouse brain in the hybrid imaging mode. Experimental results show that the proposed system effectively exploits the contrast mechanisms of both imaging modalities, making it especially useful for accurate monitoring of fluorescence-based signal dynamics in highly scattering samples.

A modified commercial ultrasound scanner used for in vivo photoacoustic imaging of nude mice injected with non-targeted contrast agents

NASA Astrophysics Data System (ADS)

Jankovic, Ladislav; Shahzad, Khalid; Wang, Yao; Burcher, Michael; Scholle, Frank-Detlef; Hauff, Peter; Mofina, Sabine; Skobe, Mihaela

2008-02-01

Photoacoustic (PA) experiments were performed using a modified commercial ultrasound scanner equipped with an array transducer and a Nd:YAG pumped OPO laser. The contrast agent SIDAG (Bayer Schering Pharma AG, Germany), used to enhance the optical absorption, demonstrated an expected pharmacokinetic behavior of the dye in the tumor and in the bladder of the nude mice. A typical behavior in the tumor consisted of an initial linear increase in PA signal followed by an exponential decay. PA signal approached the pre-injection level after about one hour following the dye injection, which was consistent with the behavior for such contrast agents when used in other imaging modalities, such as fluorescence imaging. The in-vivo spectral PA data from the mouse bladder, conducted 1.5 hours after the dye injection, clearly demonstrated presence of the dye. The multi-spectral PA data was obtained at 760nm, 784nm and 850nm laser excitations. The PA intensities obtained at these three wavelengths accurately matched the dye absorption spectrum. In addition, in the kidney, a clearance organ for this contrast agent, both in-vivo and ex-vivo results demonstrated a significant increase (~ 40%) in the ratio of PA signal at 760nm (the peak of the dye absorption) relative to the signal at 850nm (<1% absorption), indicating significant amounts of the dye in this organ. Our initial results confirm the desired photoacoustic properties of the contrast agent, indicating its great potential to be used for imaging with a commercial array-based ultrasound scanner.

Biological fiducial point based registration for multiple brain tissues reconstructed from different imaging modalities

NASA Astrophysics Data System (ADS)

Wu, Huiqun; Zhou, Gangping; Geng, Xingyun; Zhang, Xiaofeng; Jiang, Kui; Tang, Lemin; Zhou, Guomin; Dong, Jiancheng

2013-10-01

With the development of computer aided navigation system, more and more tissues shall be reconstructed to provide more useful information for surgical pathway planning. In this study, we aimed to propose a registration framework for different reconstructed tissues from multi-modalities based on some fiducial points on lateral ventricles. A male patient with brain lesion was admitted and his brain scans were performed by different modalities. Then, the different brain tissues were segmented in different modality with relevant suitable algorithms. Marching cubes were calculated for three dimensional reconstructions, and then the rendered tissues were imported to a common coordinate system for registration. Four pairs of fiducial markers were selected to calculate the rotation and translation matrix using least-square measure method. The registration results were satisfied in a glioblastoma surgery planning as it provides the spatial relationship between tumors and surrounding fibers as well as vessels. Hence, our framework is of potential value for clinicians to plan surgery.

Imaging and machine learning techniques for diagnosis of Alzheimer's disease.

PubMed

Mirzaei, Golrokh; Adeli, Anahita; Adeli, Hojjat

2016-12-01

Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection techniques have been defined to be the key to an accurate diagnosis. This paper presents a state-of-the-art review of the research performed on the diagnosis of AD based on imaging and machine learning techniques. Different segmentation and machine learning techniques used for the diagnosis of AD are reviewed including thresholding, supervised and unsupervised learning, probabilistic techniques, Atlas-based approaches, and fusion of different image modalities. More recent and powerful classification techniques such as the enhanced probabilistic neural network of Ahmadlou and Adeli should be investigated with the goal of improving the diagnosis accuracy. A combination of different image modalities can help improve the diagnosis accuracy rate. Research is needed on the combination of modalities to discover multi-modal biomarkers.

Rule-based fuzzy vector median filters for 3D phase contrast MRI segmentation

NASA Astrophysics Data System (ADS)

Sundareswaran, Kartik S.; Frakes, David H.; Yoganathan, Ajit P.

2008-02-01

Recent technological advances have contributed to the advent of phase contrast magnetic resonance imaging (PCMRI) as standard practice in clinical environments. In particular, decreased scan times have made using the modality more feasible. PCMRI is now a common tool for flow quantification, and for more complex vector field analyses that target the early detection of problematic flow conditions. Segmentation is one component of this type of application that can impact the accuracy of the final product dramatically. Vascular segmentation, in general, is a long-standing problem that has received significant attention. Segmentation in the context of PCMRI data, however, has been explored less and can benefit from object-based image processing techniques that incorporate fluids specific information. Here we present a fuzzy rule-based adaptive vector median filtering (FAVMF) algorithm that in combination with active contour modeling facilitates high-quality PCMRI segmentation while mitigating the effects of noise. The FAVMF technique was tested on 111 synthetically generated PC MRI slices and on 15 patients with congenital heart disease. The results were compared to other multi-dimensional filters namely the adaptive vector median filter, the adaptive vector directional filter, and the scalar low pass filter commonly used in PC MRI applications. FAVMF significantly outperformed the standard filtering methods (p < 0.0001). Two conclusions can be drawn from these results: a) Filtering should be performed after vessel segmentation of PC MRI; b) Vector based filtering methods should be used instead of scalar techniques.

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…

Macromolecular and Dendrimer Based Magnetic Resonance Contrast Agents

PubMed Central

Bumb, Ambika; Brechbiel, Martin W.; Choyke, Peter

2010-01-01

Magnetic resonance imaging (MRI) is a powerful imaging modality that can provide an assessment of function or molecular expression in tandem with anatomic detail. Over the last 20–25 years, a number of gadolinium based MR contrast agents have been developed to enhance signal by altering proton relaxation properties. This review explores a range of these agents from small molecule chelates, such as Gd-DTPA and Gd-DOTA, to macromolecular structures composed of albumin, polylysine, polysaccharides (dextran, inulin, starch), poly(ethylene glycol), copolymers of cystamine and cystine with GD-DTPA, and various dendritic structures based on polyamidoamine and polylysine (Gadomers). The synthesis, structure, biodistribution and targeting of dendrimer-based MR contrast agents are also discussed. PMID:20590365

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.

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.

Economic Analysis Framework for Freight Transportation Based on Florida Statewide Multi-Modal Freight Model

DOT National Transportation Integrated Search

2018-02-01

Freight transportation plays a vital role in local and regional economy. The markets and businesses from different regions and locations can be connected through freight movements. But it is difficult to quantify the economic contribution of freight ...

Targeted delivery of cancer-specific multimodal contrast agents for intraoperative detection of tumor boundaries and therapeutic margins

NASA Astrophysics Data System (ADS)

Xu, Ronald X.; Xu, Jeff S.; Huang, Jiwei; Tweedle, Michael F.; Schmidt, Carl; Povoski, Stephen P.; Martin, Edward W.

2010-02-01

Background: Accurate assessment of tumor boundaries and intraoperative detection of therapeutic margins are important oncologic principles for minimal recurrence rates and improved long-term outcomes. However, many existing cancer imaging tools are based on preoperative image acquisition and do not provide real-time intraoperative information that supports critical decision-making in the operating room. Method: Poly lactic-co-glycolic acid (PLGA) microbubbles (MBs) and nanobubbles (NBs) were synthesized by a modified double emulsion method. The MB and NB surfaces were conjugated with CC49 antibody to target TAG-72 antigen, a human glycoprotein complex expressed in many epithelial-derived cancers. Multiple imaging agents were encapsulated in MBs and NBs for multimodal imaging. Both one-step and multi-step cancer targeting strategies were explored. Active MBs/NBs were also fabricated for therapeutic margin assessment in cancer ablation therapies. Results: The multimodal contrast agents and the cancer-targeting strategies were tested on tissue simulating phantoms, LS174 colon cancer cell cultures, and cancer xenograft nude mice. Concurrent multimodal imaging was demonstrated using fluorescence and ultrasound imaging modalities. Technical feasibility of using active MBs and portable imaging tools such as ultrasound for intraoperative therapeutic margin assessment was demonstrated in a biological tissue model. Conclusion: The cancer-specific multimodal contrast agents described in this paper have the potential for intraoperative detection of tumor boundaries and therapeutic margins.

A Mobile, Map-Based Tasking Interface for Human-Robot Interaction

DTIC Science & Technology

2010-12-01

A MOBILE, MAP-BASED TASKING INTERFACE FOR HUMAN-ROBOT INTERACTION By Eli R. Hooten Thesis Submitted to the Faculty of the Graduate School of...SUBTITLE A Mobile, Map-Based Tasking Interface for Human-Robot Interaction 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...3 II.1 Interactive Modalities and Multi-Touch . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 II.2

Photoacoustic/ultrasound dual-modality contrast agent and its application to thermotherapy.

PubMed

Wang, Yu-Hsin; Liao, Ai-Ho; Chen, Jui-Hao; Wang, Churng-Ren Chris; Li, Pai-Chi

2012-04-01

This study investigates a photoacoustic/ultrasound dual-modality contrast agent, including extending its applications from image-contrast enhancement to combined diagnosis and therapy with site-specific targeting. The contrast agent comprises albumin-shelled microbubbles with encapsulated gold nanorods (AuMBs). The gas-filled microbubbles, whose diameters range from submicrometer to several micrometers, are not only echogenic but also can serve as drug-delivery vehicles. The gold nanorods are used to enhance the generation of both photoacoustic and photothermal signals. The optical absorption peak of the gold nanorods is tuned to 760 nm and is invariant after microbubble encapsulation. Dual-modality contrast enhancement is first described here, and the applications to cellular targeting and laser-induced thermotherapy in a phantom are demonstrated. Photoacoustic imaging can be used to monitor temperature increases during the treatment. The targeting capability of AuMBs was verified, and the temperature increased by 26°C for a laser power of 980 mW, demonstrating the potential of combined diagnosis and therapy with the dual-modality agent. Targeted photo- or acoustic-mediated delivery is also possible.

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.

A flexible data fusion architecture for persistent surveillance using ultra-low-power wireless sensor networks

NASA Astrophysics Data System (ADS)

Hanson, Jeffrey A.; McLaughlin, Keith L.; Sereno, Thomas J.

2011-06-01

We have developed a flexible, target-driven, multi-modal, physics-based fusion architecture that efficiently searches sensor detections for targets and rejects clutter while controlling the combinatoric problems that commonly arise in datadriven fusion systems. The informational constraints imposed by long lifetime requirements make systems vulnerable to false alarms. We demonstrate that our data fusion system significantly reduces false alarms while maintaining high sensitivity to threats. In addition, mission goals can vary substantially in terms of targets-of-interest, required characterization, acceptable latency, and false alarm rates. Our fusion architecture provides the flexibility to match these trade-offs with mission requirements unlike many conventional systems that require significant modifications for each new mission. We illustrate our data fusion performance with case studies that span many of the potential mission scenarios including border surveillance, base security, and infrastructure protection. In these studies, we deployed multi-modal sensor nodes - including geophones, magnetometers, accelerometers and PIR sensors - with low-power processing algorithms and low-bandwidth wireless mesh networking to create networks capable of multi-year operation. The results show our data fusion architecture maintains high sensitivities while suppressing most false alarms for a variety of environments and targets.

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.

Fetal Implications of Diagnostic Radiation Exposure During Pregnancy: Evidence-based Recommendations.

PubMed

Rimawi, Bassam H; Green, Victoria; Lindsay, Michael

2016-06-01

The purpose of this article is to review the fetal and long-term implications of diagnostic radiation exposure during pregnancy. Evidence-based recommendations for radiologic imaging modalities utilizing exposure of diagnostic radiation during pregnancy, including conventional screen-film mammography, digital mammography, tomosynthesis, and contrast-enhanced mammography are described.

Improvement of Speckle Contrast Image Processing by an Efficient Algorithm.

PubMed

Steimers, A; Farnung, W; Kohl-Bareis, M

2016-01-01

We demonstrate an efficient algorithm for the temporal and spatial based calculation of speckle contrast for the imaging of blood flow by laser speckle contrast analysis (LASCA). It reduces the numerical complexity of necessary calculations, facilitates a multi-core and many-core implementation of the speckle analysis and enables an independence of temporal or spatial resolution and SNR. The new algorithm was evaluated for both spatial and temporal based analysis of speckle patterns with different image sizes and amounts of recruited pixels as sequential, multi-core and many-core code.

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.

Artifact mitigation of ptychography integrated with on-the-fly scanning probe microscopy

DOE PAGES

Huang, Xiaojing; Yan, Hanfei; Ge, Mingyuan; ...

2017-07-11

In this paper, we report our experiences with conducting ptychography simultaneously with the X-ray fluorescence measurement using the on-the-fly mode for efficient multi-modality imaging. We demonstrate that the periodic artifact inherent to the raster scan pattern can be mitigated using a sufficiently fine scan step size to provide an overlap ratio of >70%. This allows us to obtain transmitted phase contrast images with enhanced spatial resolution from ptychography while maintaining the fluorescence imaging with continuous-motion scans on pixelated grids. Lastly, this capability will greatly improve the competence and throughput of scanning probe X-ray microscopy.

Multimodal Image Registration through Simultaneous Segmentation.

PubMed

Aganj, Iman; Fischl, Bruce

2017-11-01

Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. In this work, we introduce a new non-information-theoretical method for pairwise multimodal image registration, in which the error of segmentation - using both images - is considered as the registration cost function. We empirically evaluate our method via rigid registration of multi-contrast brain magnetic resonance images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods.

PET/MRI – Technical Review

PubMed Central

Muzic, Raymond F.; DiFilippo, Frank P.

2015-01-01

PET/MR is a hybrid imaging technology with the potential to combine the molecular and functional information of PET with the soft-tissue contrast of MR. Herein we review the technical features and challenges of putting these different technologies together. We emphasize the conceptual to make the material accessible to a wide audience. We begin by reviewing PET/CT, a more mature multi-modality imaging technology, to provide a basis for comparison to the history of PET/MR development. We discuss the motivation and challenges of PET/MR and different approaches that have been used to meet the challenges. We conclude with a speculation about the future of this exciting imaging method. PMID:25497909

Development and implementation of an integrated, multi-modality, user-centered interactive dietary change program

PubMed Central

Glasgow, Russell E.; Christiansen, Steve; Smith, K. Sabina; Stevens, Victor J.; Toobert, Deborah J.

2009-01-01

Computer-tailored behavior change programs offer the potential for reaching large populations at a much lower cost than individual or group-based programs. However, few of these programs to date appear to integrate behavioral theory with user choice, or combine different electronic modalities. We describe the development of an integrated CD-ROM and interactive voice response dietary change intervention that combines behavioral problem-solving theory with a high degree of user choice. The program, WISE CHOICES, is being evaluated as part of an ongoing trial. This paper describes the program development, emphasizing how user preferences are accommodated, and presents implementation and user satisfaction data. The program was successfully implemented; the linkages among the central database, the CD-ROM and the automated telephone components were robust, and participants liked the program almost as well as a counselor-delivered dietary change condition. Multi-modality programs that emphasize the strengths of each approach appear to be feasible. Future research is needed to determine the program impact and cost-effectiveness compared with counselor-delivered intervention. PMID:18711204

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

Cloudwave: distributed processing of "big data" from electrophysiological recordings for epilepsy clinical research using Hadoop.

PubMed

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical "big data" consisting of more than 100 multi-channel signals with recordings from each patient generating 5-10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a "private cloud". Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with "montages" for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave).

Cloudwave: Distributed Processing of “Big Data” from Electrophysiological Recordings for Epilepsy Clinical Research Using Hadoop

PubMed Central

Jayapandian, Catherine P.; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D.; Zhang, Guo-Qiang; Sahoo, Satya S.

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50–60 million persons worldwide. Multi-modal electrophysiological data, such as electroencephalography (EEG) and electrocardiography (EKG), are central to effective patient care and clinical research in epilepsy. Electrophysiological data is an example of clinical “big data” consisting of more than 100 multi-channel signals with recordings from each patient generating 5–10GB of data. Current approaches to store and analyze signal data using standalone tools, such as Nihon Kohden neurology software, are inadequate to meet the growing volume of data and the need for supporting multi-center collaborative studies with real time and interactive access. We introduce the Cloudwave platform in this paper that features a Web-based intuitive signal analysis interface integrated with a Hadoop-based data processing module implemented on clinical data stored in a “private cloud”. Cloudwave has been developed as part of the National Institute of Neurological Disorders and Strokes (NINDS) funded multi-center Prevention and Risk Identification of SUDEP Mortality (PRISM) project. The Cloudwave visualization interface provides real-time rendering of multi-modal signals with “montages” for EEG feature characterization over 2TB of patient data generated at the Case University Hospital Epilepsy Monitoring Unit. Results from performance evaluation of the Cloudwave Hadoop data processing module demonstrate one order of magnitude improvement in performance over 77GB of patient data. (Cloudwave project: http://prism.case.edu/prism/index.php/Cloudwave) PMID:24551370

A Highly Sensitive X-ray Imaging Modality for Hepatocellular Carcinoma Detection in Vitro

PubMed Central

Rand, Danielle; Walsh, Edward G.; Derdak, Zoltan; Wands, Jack R.; Rose-Petruck, Christoph

2015-01-01

Innovations that improve sensitivity and reduce cost are of paramount importance in diagnostic imaging. The novel x-ray imaging modality called Spatial Frequency Heterodyne Imaging (SFHI) is based on a linear arrangement of x-ray source, tissue, and x-ray detector, much like that of a conventional x-ray imaging apparatus. However, SFHI rests on a complete paradigm reversal compared to conventional x-ray absorption-based radiology: while scattered x-rays are carefully rejected in absorption-based x-ray radiology to enhance the image contrast, SFHI forms images exclusively from x-rays scattered by the tissue. In this study we use numerical processing to produce x-ray scatter images of Hepatocellular Carcinoma (HCC) labeled with a nanoparticle contrast agent. We subsequently compare the sensitivity of SFHI in this application to that of both conventional x-ray imaging and Magnetic Resonance Imaging (MRI). Although SFHI is still in the early stages of its development, our results show that the sensitivity of SFHI is an order of magnitude greater than that of absorption-based x-ray imaging and approximately equal to that of MRI. As x-ray imaging modalities typically have lower installation and service costs compared to MRI, SFHI could become a cost effective alternative to MRI, particularly in areas of the world with inadequate availability of MRI facilities. PMID:25559398

A highly sensitive x-ray imaging modality for hepatocellular carcinoma detection in vitro

DOE PAGES

Rand, Danielle; Walsh, Edward G.; Derdak, Zoltan; ...

2015-01-05

Innovations that improve sensitivity and reduce cost are of paramount importance in diagnostic imaging. The novel x-ray imaging modality called Spatial Frequency Heterodyne Imaging (SFHI) is based on a linear arrangement of x-ray source, tissue, and x-ray detector, much like that of a conventional x-ray imaging apparatus. However, SFHI rests on a complete paradigm reversal compared to conventional x-ray absorption-based radiology: while scattered x-rays are carefully rejected in absorption-based x-ray radiology to enhance the image contrast, SFHI forms images exclusively from x-rays scattered by the tissue. Here in this study we use numerical processing to produce x-ray scatter images ofmore » Hepatocellular Carcinoma (HCC) labeled with a nanoparticle contrast agent. We subsequently compare the sensitivity of SFHI in this application to that of both conventional x-ray imaging and Magnetic Resonance Imaging (MRI). Although SFHI is still in the early stages of its development, our results show that the sensitivity of SFHI is an order of magnitude greater than that of absorption-based x-ray imaging and approximately equal to that of MRI. Lastly, as x-ray imaging modalities typically have lower installation and service costs compared to MRI, SFHI could become a cost effective alternative to MRI, particularly in areas of the world with inadequate availability of MRI facilities.« less

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.

Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home

PubMed Central

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-01-01

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second. PMID:24335727

Fall risk assessment and early-warning for toddler behaviors at home.

PubMed

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-12-10

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second.

SU-G-JeP2-02: A Unifying Multi-Atlas Approach to Electron Density Mapping Using Multi-Parametric MRI for Radiation Treatment Planning

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

Ren, S; Tianjin University, Tianjin; Hara, W

Purpose: MRI has a number of advantages over CT as a primary modality for radiation treatment planning (RTP). However, one key bottleneck problem still remains, which is the lack of electron density information in MRI. In the work, a reliable method to map electron density is developed by leveraging the differential contrast of multi-parametric MRI. Methods: We propose a probabilistic Bayesian approach for electron density mapping based on T1 and T2-weighted MRI, using multiple patients as atlases. For each voxel, we compute two conditional probabilities: (1) electron density given its image intensity on T1 and T2-weighted MR images, and (2)more » electron density given its geometric location in a reference anatomy. The two sources of information (image intensity and spatial location) are combined into a unifying posterior probability density function using the Bayesian formalism. The mean value of the posterior probability density function provides the estimated electron density. Results: We evaluated the method on 10 head and neck patients and performed leave-one-out cross validation (9 patients as atlases and remaining 1 as test). The proposed method significantly reduced the errors in electron density estimation, with a mean absolute HU error of 138, compared with 193 for the T1-weighted intensity approach and 261 without density correction. For bone detection (HU>200), the proposed method had an accuracy of 84% and a sensitivity of 73% at specificity of 90% (AUC = 87%). In comparison, the AUC for bone detection is 73% and 50% using the intensity approach and without density correction, respectively. Conclusion: The proposed unifying method provides accurate electron density estimation and bone detection based on multi-parametric MRI of the head with highly heterogeneous anatomy. This could allow for accurate dose calculation and reference image generation for patient setup in MRI-based radiation treatment planning.« less

High frame-rate MR-guided near-infrared tomography system to monitor breast hemodynamics

NASA Astrophysics Data System (ADS)

Li, Zhiqiu; Jiang, Shudong; Krishnaswamy, Venkataramanan; Davis, Scott C.; Srinivasan, Subhadra; Paulsen, Keith D.; Pogue, Brian W.

2011-02-01

A near-infrared (NIR) tomography system with spectral-encoded sources at two wavelength bands was built to quantify the temporal contrast at 20 Hz bandwidth, while imaging breast tissue. The NIR system was integrated with a magnetic resonance (MR) machine through a custom breast coil interface, and both NIR data and MR images were acquired simultaneously. MR images provided breast tissue structural information for NIR reconstruction. Acquisition of finger pulse oximeter (PO) plethysmogram was synchronized with the NIR system in the experiment to offer a frequency-locked reference. The recovered absorption coefficients of the breast at two wavelengths showed identical temporal frequency as the PO output, proving this multi-modality design can recover the small pulsatile variation of absorption property in breast tissue related to the heartbeat. And it also showed the system's ability on novel contrast imaging of fast flow signals in deep tissue.

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.

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…

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

Miniature all-optical probe for photoacoustic and ultrasound dual-modality imaging

NASA Astrophysics Data System (ADS)

Li, Guangyao; Guo, Zhendong; Chen, Sung-Liang

2018-02-01

Photoacoustic (PA) imaging forms an image based on optical absorption contrasts with ultrasound (US) resolution. In contrast, US imaging is based on acoustic backscattering to provide structural information. In this study, we develop a miniature all-optical probe for high-resolution PA-US dual-modality imaging over a large imaging depth range. The probe employs three individual optical fibers (F1-F3) to achieve optical generation and detection of acoustic waves for both PA and US modalities. To offer wide-angle laser illumination, fiber F1 with a large numerical aperture (NA) is used for PA excitation. On the other hand, wide-angle US waves are generated by laser illumination on an optically absorbing composite film which is coated on the end face of fiber F2. Both the excited PA and backscattered US waves are detected by a Fabry-Pérot cavity on the tip of fiber F3 for wide-angle acoustic detection. The wide angular features of the three optical fibers make large-NA synthetic aperture focusing technique possible and thus high-resolution PA and US imaging. The probe diameter is less than 2 mm. Over a depth range of 4 mm, lateral resolutions of PA and US imaging are 104-154 μm and 64-112 μm, respectively, and axial resolutions of PA and US imaging are 72-117 μm and 31-67 μm, respectively. To show the imaging capability of the probe, phantom imaging with both PA and US contrasts is demonstrated. The results show that the probe has potential for endoscopic and intravascular imaging applications that require PA and US contrast with high resolution.

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

The transformation of multi-sensory experiences into memories during sleep.

PubMed

Rothschild, Gideon

2018-03-26

Our everyday lives present us with a continuous stream of multi-modal sensory inputs. While most of this information is soon forgotten, sensory information associated with salient experiences can leave long-lasting memories in our minds. Extensive human and animal research has established that the hippocampus is critically involved in this process of memory formation and consolidation. However, the underlying mechanistic details are still only partially understood. Specifically, the hippocampus has often been suggested to encode information during experience, temporarily store it, and gradually transfer this information to the cortex during sleep. In rodents, ample evidence has supported this notion in the context of spatial memory, yet whether this process adequately describes the consolidation of multi-sensory experiences into memories is unclear. Here, focusing on rodent studies, I examine how multi-sensory experiences are consolidated into long term memories by hippocampal and cortical circuits during sleep. I propose that in contrast to the classical model of memory consolidation, the cortex is a "fast learner" that has a rapid and instructive role in shaping hippocampal-dependent memory consolidation. The proposed model may offer mechanistic insight into memory biasing using sensory cues during sleep. Copyright © 2018 Elsevier Inc. All rights reserved.

Drug related webpages classification using images and text information based on multi-kernel learning

NASA Astrophysics Data System (ADS)

Hu, Ruiguang; Xiao, Liping; Zheng, Wenjuan

2015-12-01

In this paper, multi-kernel learning(MKL) is used for drug-related webpages classification. First, body text and image-label text are extracted through HTML parsing, and valid images are chosen by the FOCARSS algorithm. Second, text based BOW model is used to generate text representation, and image-based BOW model is used to generate images representation. Last, text and images representation are fused with a few methods. Experimental results demonstrate that the classification accuracy of MKL is higher than those of all other fusion methods in decision level and feature level, and much higher than the accuracy of single-modal classification.

Characteristic sounds facilitate visual search.

PubMed

Iordanescu, Lucica; Guzman-Martinez, Emmanuel; Grabowecky, Marcia; Suzuki, Satoru

2008-06-01

In a natural environment, objects that we look for often make characteristic sounds. A hiding cat may meow, or the keys in the cluttered drawer may jingle when moved. Using a visual search paradigm, we demonstrated that characteristic sounds facilitated visual localization of objects, even when the sounds carried no location information. For example, finding a cat was faster when participants heard a meow sound. In contrast, sounds had no effect when participants searched for names rather than pictures of objects. For example, hearing "meow" did not facilitate localization of the word cat. These results suggest that characteristic sounds cross-modally enhance visual (rather than conceptual) processing of the corresponding objects. Our behavioral demonstration of object-based cross-modal enhancement complements the extensive literature on space-based cross-modal interactions. When looking for your keys next time, you might want to play jingling sounds.

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

Integration of heterogeneous data for classification in hyperspectral satellite imagery

NASA Astrophysics Data System (ADS)

Benedetto, J.; Czaja, W.; Dobrosotskaya, J.; Doster, T.; Duke, K.; Gillis, D.

2012-06-01

As new remote sensing modalities emerge, it becomes increasingly important to nd more suitable algorithms for fusion and integration of dierent data types for the purposes of target/anomaly detection and classication. Typical techniques that deal with this problem are based on performing detection/classication/segmentation separately in chosen modalities, and then integrating the resulting outcomes into a more complete picture. In this paper we provide a broad analysis of a new approach, based on creating fused representations of the multi- modal data, which then can be subjected to analysis by means of the state-of-the-art classiers or detectors. In this scenario we shall consider the hyperspectral imagery combined with spatial information. Our approach involves machine learning techniques based on analysis of joint data-dependent graphs and their associated diusion kernels. Then, the signicant eigenvectors of the derived fused graph Laplace operator form the new representation, which provides integrated features from the heterogeneous input data. We compare these fused approaches with analysis of integrated outputs of spatial and spectral graph methods.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

Mechanically assisted 3D ultrasound for pre-operative assessment and guiding percutaneous treatment of focal liver tumors

NASA Astrophysics Data System (ADS)

Sadeghi Neshat, Hamid; Bax, Jeffery; Barker, Kevin; Gardi, Lori; Chedalavada, Jason; Kakani, Nirmal; Fenster, Aaron

2014-03-01

Image-guided percutaneous ablation is the standard treatment for focal liver tumors deemed inoperable and is commonly used to maintain eligibility for patients on transplant waitlists. Radiofrequency (RFA), microwave (MWA) and cryoablation technologies are all delivered via one or a number of needle-shaped probes inserted directly into the tumor. Planning is mostly based on contrast CT/MRI. While intra-procedural CT is commonly used to confirm the intended probe placement, 2D ultrasound (US) remains the main, and in some centers the only imaging modality used for needle guidance. Corresponding intraoperative 2D US with planning and other intra-procedural imaging modalities is essential for accurate needle placement. However, identification of matching features of interest among these images is often challenging given the limited field-of-view (FOV) and low quality of 2D US images. We have developed a passive tracking arm with a motorized scan-head and software tools to improve guiding capabilities of conventional US by large FOV 3D US scans that provides more anatomical landmarks that can facilitate registration of US with both planning and intra-procedural images. The tracker arm is used to scan the whole liver with a high geometrical accuracy that facilitates multi-modality landmark based image registration. Software tools are provided to assist with the segmentation of the ablation probes and tumors, find the 2D view that best shows the probe(s) from a 3D US image, and to identify the corresponding image from planning CT scans. In this paper, evaluation results from laboratory testing and a phase 1 clinical trial for planning and guiding RFA and MWA procedures using the developed system will be presented. Early clinical results show a comparable performance to intra-procedural CT that suggests 3D US as a cost-effective alternative with no side-effects in centers where CT is not available.

Design of Open Content Social Learning That Increases Learning Efficiency and Engagement Based on Open Pedagogy

ERIC Educational Resources Information Center

John, Benneaser; Thavavel, V.; Jayaraj, Jayakumar; Muthukumar, A.; Jeevanandam, Poornaselvan Kittu

2016-01-01

Academic writing skills are crucial when students, e.g., in teacher education programs, write their undergraduate theses. A multi-modal web-based and self-regulated learning resource on academic writing was developed, using texts, hypertext, moving images, podcasts and templates. A study, using surveys and a focus group, showed that students used…

Simulation tools for analyzer-based x-ray phase contrast imaging system with a conventional x-ray source

NASA Astrophysics Data System (ADS)

Caudevilla, Oriol; Zhou, Wei; Stoupin, Stanislav; Verman, Boris; Brankov, J. G.

2016-09-01

Analyzer-based X-ray phase contrast imaging (ABI) belongs to a broader family of phase-contrast (PC) X-ray imaging modalities. Unlike the conventional X-ray radiography, which measures only X-ray absorption, in PC imaging one can also measures the X-rays deflection induced by the object refractive properties. It has been shown that refraction imaging provides better contrast when imaging the soft tissue, which is of great interest in medical imaging applications. In this paper, we introduce a simulation tool specifically designed to simulate the analyzer-based X-ray phase contrast imaging system with a conventional polychromatic X-ray source. By utilizing ray tracing and basic physical principles of diffraction theory our simulation tool can predicting the X-ray beam profile shape, the energy content, the total throughput (photon count) at the detector. In addition we can evaluate imaging system point-spread function for various system configurations.

Gamma-Ray imaging for nuclear security and safety: Towards 3-D gamma-ray vision

NASA Astrophysics Data System (ADS)

Vetter, Kai; Barnowksi, Ross; Haefner, Andrew; Joshi, Tenzing H. Y.; Pavlovsky, Ryan; Quiter, Brian J.

2018-01-01

The development of portable gamma-ray imaging instruments in combination with the recent advances in sensor and related computer vision technologies enable unprecedented capabilities in the detection, localization, and mapping of radiological and nuclear materials in complex environments relevant for nuclear security and safety. Though multi-modal imaging has been established in medicine and biomedical imaging for some time, the potential of multi-modal data fusion for radiological localization and mapping problems in complex indoor and outdoor environments remains to be explored in detail. In contrast to the well-defined settings in medical or biological imaging associated with small field-of-view and well-constrained extension of the radiation field, in many radiological search and mapping scenarios, the radiation fields are not constrained and objects and sources are not necessarily known prior to the measurement. The ability to fuse radiological with contextual or scene data in three dimensions, in analog to radiological and functional imaging with anatomical fusion in medicine, provides new capabilities enhancing image clarity, context, quantitative estimates, and visualization of the data products. We have developed new means to register and fuse gamma-ray imaging with contextual data from portable or moving platforms. These developments enhance detection and mapping capabilities as well as provide unprecedented visualization of complex radiation fields, moving us one step closer to the realization of gamma-ray vision in three dimensions.

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.

Multi-contrast MRI registration of carotid arteries based on cross-sectional images and lumen boundaries

NASA Astrophysics Data System (ADS)

Wu, Yu-Xia; Zhang, Xi; Xu, Xiao-Pan; Liu, Yang; Zhang, Guo-Peng; Li, Bao-Juan; Chen, Hui-Jun; Lu, Hong-Bing

2017-02-01

Ischemic stroke has great correlation with carotid atherosclerosis and is mostly caused by vulnerable plaques. It's particularly important to analysis the components of plaques for the detection of vulnerable plaques. Recently plaque analysis based on multi-contrast magnetic resonance imaging has attracted great attention. Though multi-contrast MR imaging has potentials in enhanced demonstration of carotid wall, its performance is hampered by the misalignment of different imaging sequences. In this study, a coarse-to-fine registration strategy based on cross-sectional images and wall boundaries is proposed to solve the problem. It includes two steps: a rigid step using the iterative closest points to register the centerlines of carotid artery extracted from multi-contrast MR images, and a non-rigid step using the thin plate spline to register the lumen boundaries of carotid artery. In the rigid step, the centerline was extracted by tracking the crosssectional images along the vessel direction calculated by Hessian matrix. In the non-rigid step, a shape context descriptor is introduced to find corresponding points of two similar boundaries. In addition, the deterministic annealing technique is used to find a globally optimized solution. The proposed strategy was evaluated by newly developed three-dimensional, fast and high resolution multi-contrast black blood MR imaging. Quantitative validation indicated that after registration, the overlap of two boundaries from different sequences is 95%, and their mean surface distance is 0.12 mm. In conclusion, the proposed algorithm has improved the accuracy of registration effectively for further component analysis of carotid plaques.

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.

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

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.

Cross-modal enhancement of speech detection in young and older adults: does signal content matter?

PubMed

Tye-Murray, Nancy; Spehar, Brent; Myerson, Joel; Sommers, Mitchell S; Hale, Sandra

2011-01-01

The purpose of the present study was to examine the effects of age and visual content on cross-modal enhancement of auditory speech detection. Visual content consisted of three clearly distinct types of visual information: an unaltered video clip of a talker's face, a low-contrast version of the same clip, and a mouth-like Lissajous figure. It was hypothesized that both young and older adults would exhibit reduced enhancement as visual content diverged from the original clip of the talker's face, but that the decrease would be greater for older participants. Nineteen young adults and 19 older adults were asked to detect a single spoken syllable (/ba/) in speech-shaped noise, and the level of the signal was adaptively varied to establish the signal-to-noise ratio (SNR) at threshold. There was an auditory-only baseline condition and three audiovisual conditions in which the syllable was accompanied by one of the three visual signals (the unaltered clip of the talker's face, the low-contrast version of that clip, or the Lissajous figure). For each audiovisual condition, the SNR at threshold was compared with the SNR at threshold for the auditory-only condition to measure the amount of cross-modal enhancement. Young adults exhibited significant cross-modal enhancement with all three types of visual stimuli, with the greatest amount of enhancement observed for the unaltered clip of the talker's face. Older adults, in contrast, exhibited significant cross-modal enhancement only with the unaltered face. Results of this study suggest that visual signal content affects cross-modal enhancement of speech detection in both young and older adults. They also support a hypothesized age-related deficit in processing low-contrast visual speech stimuli, even in older adults with normal contrast sensitivity.

Gadolinium-Based Contrast Agents for MR Cancer Imaging

PubMed Central

Zhou, Zhuxian; Lu, Zheng-Rong

2013-01-01

Magnetic resonance imaging (MRI) is a clinical imaging modality effective for anatomical and functional imaging of diseased soft tissues, including solid tumors. MRI contrast agents have been routinely used for detecting tumor at an early stage. Gadolinium based contrast agents are the most commonly used contrast agents in clinical MRI. There have been significant efforts to design and develop novel Gd(III) contrast agents with high relaxivity, low toxicity and specific tumor binding. The relaxivity of the Gd(III) contrast agents can be increased by proper chemical modification. The toxicity of Gd(III) contrast agents can be reduced by increasing the agents’ thermodynamic and kinetic stability, as well as optimizing their pharmacokinetic properties. The increasing knowledge in the field of cancer genomics and biology provides an opportunity for designing tumor-specific contrast agents. Various new Gd(III) chelates have been designed and evaluated in animal models for more effective cancer MRI. This review outlines the design and development, physicochemical properties, and in vivo properties of several classes of Gd(III)-based MR contrast agents for tumor imaging. PMID:23047730

Gold nanoshelled liquid perfluorocarbon nanocapsules for combined dual modal ultrasound/CT imaging and photothermal therapy of cancer.

PubMed

Ke, Hengte; Yue, Xiuli; Wang, Jinrui; Xing, Sen; Zhang, Qian; Dai, Zhifei; Tian, Jie; Wang, Shumin; Jin, Yushen

2014-03-26

The integration of multimodal contrast-enhanced diagnostic imaging and therapeutic capabilities could utilize imaging guided therapy to plan the treatment strategy based on the diagnostic results and to guide/monitor the therapeutic procedures. Herein, gold nanoshelled perfluorooctylbromide (PFOB) nanocapsules with PEGylation (PGsP NCs) are constructed by oil-in-water emulsion method to form polymeric PFOB nanocapsules, followed by the formation of PEGylated gold nanoshell on the surface. PGsP NCs could not only provide excellent contrast enhancement for dual modal ultrasound and CT imaging in vitro and in vivo, but also serve as efficient photoabsorbers for photothermal ablation of tumors on xenografted nude mouse model. To our best knowledge, this is the first report of gold nanoshell serving as both CT contrast agents and photoabsorbers for photothermal therapy. The novel multifunctional nanomedicine would be of great value to offer more comprehensive diagnostic information to guide more accurate and effective cancer therapy. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Photoacoustic phasoscopy super-contrast imaging

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

Gao, Fei; Feng, Xiaohua; Zheng, Yuanjin, E-mail: yjzheng@ntu.edu.sg

2014-05-26

Phasoscopy is a recently proposed concept correlating electromagnetic (EM) absorption and scattering properties based on energy conservation. Phase information can be extracted from EM absorption induced acoustic wave and scattered EM wave for biological tissue characterization. In this paper, an imaging modality, termed photoacoustic phasoscopy imaging (PAPS), is proposed and verified experimentally based on phasoscopy concept with laser illumination. Both endogenous photoacoustic wave and scattered photons are collected simultaneously to extract the phase information. The PAPS images are then reconstructed on vessel-mimicking phantom and ex vivo porcine tissues to show significantly improved contrast than conventional photoacoustic imaging.

Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

NASA Astrophysics Data System (ADS)

Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

2015-03-01

Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

Preparation of biomimetic nano-structured films with multi-scale roughness

NASA Astrophysics Data System (ADS)

Shelemin, A.; Nikitin, D.; Choukourov, A.; Kylián, O.; Kousal, J.; Khalakhan, I.; Melnichuk, I.; Slavínská, D.; Biederman, H.

2016-06-01

Biomimetic nano-structured films are valuable materials in various applications. In this study we introduce a fully vacuum-based approach for fabrication of such films. The method combines deposition of nanoparticles (NPs) by gas aggregation source and deposition of overcoat thin film that fixes the nanoparticles on a surface. This leads to the formation of nanorough surfaces which, depending on the chemical nature of the overcoat, may range from superhydrophilic to superhydrophobic. In addition, it is shown that by proper adjustment of the amount of NPs it is possible to tailor adhesive force on superhydrophobic surfaces. Finally, the possibility to produce NPs in a wide range of their size (45-240 nm in this study) makes it possible to produce surfaces not only with single scale roughness, but also with bi-modal or even multi-modal character. Such surfaces were found to be superhydrophobic with negligible water contact angle hysteresis and hence truly slippery.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

PubMed Central

Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

Purpose A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. Methods We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. Results The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. Conclusion The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers. PMID:27434396

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.

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

Cross-modal decoupling in temporal attention.

PubMed

Mühlberg, Stefanie; Oriolo, Giovanni; Soto-Faraco, Salvador

2014-06-01

Prior studies have repeatedly reported behavioural benefits to events occurring at attended, compared to unattended, points in time. It has been suggested that, as for spatial orienting, temporal orienting of attention spreads across sensory modalities in a synergistic fashion. However, the consequences of cross-modal temporal orienting of attention remain poorly understood. One challenge is that the passage of time leads to an increase in event predictability throughout a trial, thus making it difficult to interpret possible effects (or lack thereof). Here we used a design that avoids complete temporal predictability to investigate whether attending to a sensory modality (vision or touch) at a point in time confers beneficial access to events in the other, non-attended, sensory modality (touch or vision, respectively). In contrast to previous studies and to what happens with spatial attention, we found that events in one (unattended) modality do not automatically benefit from happening at the time point when another modality is expected. Instead, it seems that attention can be deployed in time with relative independence for different sensory modalities. Based on these findings, we argue that temporal orienting of attention can be cross-modally decoupled in order to flexibly react according to the environmental demands, and that the efficiency of this selective decoupling unfolds in time. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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

Ultrasound-aided high-resolution biophotonic imaging

NASA Astrophysics Data System (ADS)

Wang, Lihong V.

2003-10-01

We develop novel biophotonic imaging for early-cancer detection, a grand challenge in cancer research, using nonionizing electromagnetic and ultrasonic waves. Unlike ionizing x-ray radiation, nonionizing electromagnetic waves such as optical waves are safe for biomedical applications and reveal new contrast mechanisms and functional information. For example, our spectroscopic oblique-incidence reflectometry can detect skin cancers based on functional hemoglobin parameters and cell nuclear size with 95% accuracy. Unfortunately, electromagnetic waves in the nonionizing spectral region do not penetrate biological tissue in straight paths as do x-rays. Consequently, high-resolution tomography based on nonionizing electromagnetic waves alone, as demonstrated by our Mueller optical coherence tomography, is limited to superficial tissue imaging. Ultrasonic imaging, on the contrary, furnishes good imaging resolution but has poor contrast in early-stage tumors and has strong speckle artifacts as well. We developed ultrasound-mediated imaging modalities by combining electromagnetic and ultrasonic waves synergistically. The hybrid modalities yield speckle-free electromagnetic-contrast at ultrasonic resolution in relatively large biological tissue. In ultrasound-modulated (acousto)-optical tomography, a focused ultrasonic wave encodes diffuse laser light in scattering biological tissue. In photo-acoustic (thermo-acoustic) tomography, a low-energy laser (RF) pulse induces ultrasonic waves in biological tissue due to thermoelastic expansion.

The relative efficacy of three recovery modalities after professional rugby league matches.

PubMed

Webb, Nicholas P; Harris, Nigel K; Cronin, John B; Walker, Craig

2013-09-01

This study investigated the relative efficacy of postgame recovery modalities on jump height performance and subjective ratings of muscle soreness and muscle damage at 1, 18, and 42 hours after professional rugby league competition games. Twenty-one professional rugby league players performed 3 different postmatch recovery modalities: cold water immersion (CWI), contrast water therapy (CWT), and active recovery (ACT). The effects of the recovery treatments were analyzed with mixed modeling including a covariate (fatigue score) to adjust for changes in the intensity of each match on the postmatch values of the dependent variables of interest. Standardization of effects was used to make magnitude-based inferences, presented as mean with ±90% confidence limits. Cold water immersion and CWT clearly recovered jump height performance (CWI 2.3 ± 3.7%; CWT 3.5 ± 4.1%), reduced muscle soreness (CWI -0.95 ± 0.37; CWT -0.55 ± 0.37), and decreased creatine kinase (CWI -11.0 ± 15.1%; CWT 18.2 ± 20.1%) by 42 hours postgame compared with ACT. Contrast water therapy was however clearly more effective compared with CWI on the recovery of muscle soreness and creatine kinase by 42 hours postgame. Based on these findings, CWT recovery is recommended postmatch for team rugby sports.

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.

Multi-modality imaging of tumor phenotype and response to therapy

NASA Astrophysics Data System (ADS)

Nyflot, Matthew J.

2011-12-01

Imaging and radiation oncology have historically been closely linked. However, the vast majority of techniques used in the clinic involve anatomical imaging. Biological imaging offers the potential for innovation in the areas of cancer diagnosis and staging, radiotherapy target definition, and treatment response assessment. Some relevant imaging techniques are FDG PET (for imaging cellular metabolism), FLT PET (proliferation), CuATSM PET (hypoxia), and contrast-enhanced CT (vasculature and perfusion). Here, a technique for quantitative spatial correlation of tumor phenotype is presented for FDG PET, FLT PET, and CuATSM PET images. Additionally, multimodality imaging of treatment response with FLT PET, CuATSM, and dynamic contrast-enhanced CT is presented, in a trial of patients receiving an antiangiogenic agent (Avastin) combined with cisplatin and radiotherapy. Results are also presented for translational applications in animal models, including quantitative assessment of proliferative response to cetuximab with FLT PET and quantification of vascular volume with a blood-pool contrast agent (Fenestra). These techniques have clear applications to radiobiological research and optimized treatment strategies, and may eventually be used for personalized therapy for patients.

Compressive power spectrum sensing for vibration-based output-only system identification of structural systems in the presence of noise

NASA Astrophysics Data System (ADS)

Tau Siesakul, Bamrung; Gkoktsi, Kyriaki; Giaralis, Agathoklis

2015-05-01

Motivated by the need to reduce monetary and energy consumption costs of wireless sensor networks in undertaking output-only/operational modal analysis of engineering structures, this paper considers a multi-coset analog-toinformation converter for structural system identification from acceleration response signals of white noise excited linear damped structures sampled at sub-Nyquist rates. The underlying natural frequencies, peak gains in the frequency domain, and critical damping ratios of the vibrating structures are estimated directly from the sub-Nyquist measurements and, therefore, the computationally demanding signal reconstruction step is by-passed. This is accomplished by first employing a power spectrum blind sampling (PSBS) technique for multi-band wide sense stationary stochastic processes in conjunction with deterministic non-uniform multi-coset sampling patterns derived from solving a weighted least square optimization problem. Next, modal properties are derived by the standard frequency domain peak picking algorithm. Special attention is focused on assessing the potential of the adopted PSBS technique, which poses no sparsity requirements to the sensed signals, to derive accurate estimates of modal structural system properties from noisy sub- Nyquist measurements. To this aim, sub-Nyquist sampled acceleration response signals corrupted by various levels of additive white noise pertaining to a benchmark space truss structure with closely spaced natural frequencies are obtained within an efficient Monte Carlo simulation-based framework. Accurate estimates of natural frequencies and reasonable estimates of local peak spectral ordinates and critical damping ratios are derived from measurements sampled at about 70% below the Nyquist rate and for SNR as low as 0db demonstrating that the adopted approach enjoys noise immunity.

Micro-CT of rodents: state-of-the-art and future perspectives

PubMed Central

Clark, D. P.; Badea, C. T.

2014-01-01

Micron-scale computed tomography (micro-CT) is an essential tool for phenotyping and for elucidating diseases and their therapies. This work is focused on preclinical micro-CT imaging, reviewing relevant principles, technologies, and applications. Commonly, micro-CT provides high-resolution anatomic information, either on its own or in conjunction with lower-resolution functional imaging modalities such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT). More recently, however, advanced applications of micro-CT produce functional information by translating clinical applications to model systems (e.g. measuring cardiac functional metrics) and by pioneering new ones (e.g. measuring tumor vascular permeability with nanoparticle contrast agents). The primary limitations of micro-CT imaging are the associated radiation dose and relatively poor soft tissue contrast. We review several image reconstruction strategies based on iterative, statistical, and gradient sparsity regularization, demonstrating that high image quality is achievable with low radiation dose given ever more powerful computational resources. We also review two contrast mechanisms under intense development. The first is spectral contrast for quantitative material discrimination in combination with passive or actively targeted nanoparticle contrast agents. The second is phase contrast which measures refraction in biological tissues for improved contrast and potentially reduced radiation dose relative to standard absorption imaging. These technological advancements promise to develop micro-CT into a commonplace, functional and even molecular imaging modality. PMID:24974176

On using the Hilbert transform for blind identification of complex modes: A practical approach

NASA Astrophysics Data System (ADS)

Antunes, Jose; Debut, Vincent; Piteau, Pilippe; Delaune, Xavier; Borsoi, Laurent

2018-01-01

The modal identification of dynamical systems under operational conditions, when subjected to wide-band unmeasured excitations, is today a viable alternative to more traditional modal identification approaches based on processing sets of measured FRFs or impulse responses. Among current techniques for performing operational modal identification, the so-called blind identification methods are the subject of considerable investigation. In particular, the SOBI (Second-Order Blind Identification) method was found to be quite efficient. SOBI was originally developed for systems with normal modes. To address systems with complex modes, various extension approaches have been proposed, in particular: (a) Using a first-order state-space formulation for the system dynamics; (b) Building complex analytic signals from the measured responses using the Hilbert transform. In this paper we further explore the latter option, which is conceptually interesting while preserving the model order and size. Focus is on applicability of the SOBI technique for extracting the modal responses from analytic signals built from a set of vibratory responses. The novelty of this work is to propose a straightforward computational procedure for obtaining the complex cross-correlation response matrix to be used for the modal identification procedure. After clarifying subtle aspects of the general theoretical framework, we demonstrate that the correlation matrix of the analytic responses can be computed through a Hilbert transform of the real correlation matrix, so that the actual time-domain responses are no longer required for modal identification purposes. The numerical validation of the proposed technique is presented based on time-domain simulations of a conceptual physical multi-modal system, designed to display modes ranging from normal to highly complex, while keeping modal damping low and nearly independent of the modal complexity, and which can prove very interesting in test bench applications. Numerical results for complex modal identifications are presented, and the quality of the identified modal matrix and modal responses, extracted using the complex SOBI technique and implementing the proposed formulation, is assessed.

Development of a Hybrid Optical Biopsy Probe to Improve Prostate Cancer Diagnosis

DTIC Science & Technology

2012-06-01

can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for the study are (1) light...which collect light scattering and auto-fluorescence from the prostate tissue, into a transrectal- ultrasound , needle - biopsy probe. In the...probe can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for the study were

Development of a Hybrid Optical Biopsy Probe to Improve Prostate Cancer Diagnosis

DTIC Science & Technology

2011-06-01

integrated needle probe can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for... needle probe can be developed for guiding needle biopsy for prostate cancer diagnosis. Multi-modal optical measurements to be utilized for the study...tissue, into a transrectal- ultrasound , needle - biopsy probe. In the development phase, documentation to obtain IRB approval for ex vivo human prostate

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.

Characteristic sounds facilitate visual search

PubMed Central

Iordanescu, Lucica; Guzman-Martinez, Emmanuel; Grabowecky, Marcia; Suzuki, Satoru

2009-01-01

In a natural environment, objects that we look for often make characteristic sounds. A hiding cat may meow, or the keys in the cluttered drawer may jingle when moved. Using a visual search paradigm, we demonstrated that characteristic sounds facilitated visual localization of objects, even when the sounds carried no location information. For example, finding a cat was faster when participants heard a meow sound. In contrast, sounds had no effect when participants searched for names rather than pictures of objects. For example, hearing “meow” did not facilitate localization of the word cat. These results suggest that characteristic sounds cross-modally enhance visual (rather than conceptual) processing of the corresponding objects. Our behavioral demonstration of object-based cross-modal enhancement complements the extensive literature on space-based cross-modal interactions. When looking for your keys next time, you might want to play jingling sounds. PMID:18567253

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

PubMed

Sauwen, N; Acou, M; Van Cauter, S; Sima, D M; Veraart, J; Maes, F; Himmelreich, U; Achten, E; Van Huffel, S

2016-01-01

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

Knowledge Engineering Aspects of Affective Bi-Modal Educational Applications

NASA Astrophysics Data System (ADS)

Alepis, Efthymios; Virvou, Maria; Kabassi, Katerina

This paper analyses the knowledge and software engineering aspects of educational applications that provide affective bi-modal human-computer interaction. For this purpose, a system that provides affective interaction based on evidence from two different modes has been developed. More specifically, the system's inferences about students' emotions are based on user input evidence from the keyboard and the microphone. Evidence from these two modes is combined by a user modelling component that incorporates user stereotypes as well as a multi criteria decision making theory. The mechanism that integrates the inferences from the two modes has been based on the results of two empirical studies that were conducted in the context of knowledge engineering of the system. The evaluation of the developed system showed significant improvements in the recognition of the emotional states of users.

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.

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

In vivo evaluation of (64)Cu-labeled magnetic nanoparticles as a dual-modality PET/MR imaging agent.

PubMed

Glaus, Charles; Rossin, Raffaella; Welch, Michael J; Bao, Gang

2010-04-21

A novel nanoparticle-based dual-modality positron emission tomograph/magnetic resonance imaging (PET/MRI) contrast agent was developed. The probe consisted of a superparamagnetic iron oxide (SPIO) core coated with PEGylated phospholipids. The chelator 1,4,7,10-tetraazacyclo-dodecane-1,4,7,10-tetraacetic acid (DOTA) was conjugated to PEG termini to allow labeling with positron-emitting (64)Cu. Radiolabeling with (64)Cu at high yield and high purity was readily achieved. The (64)Cu-SPIO probes produced strong MR and PET signals and were stable in mouse serum for 24 h at 37 degrees C. Biodistribution and in vivo PET/CT imaging studies of the probes showed a circulation half-life of 143 min and high initial blood retention with moderate liver uptake, making them an attractive contrast agent for disease studies.

Imaging Modalities Relevant to Intracranial Pressure Assessment in Astronauts: A Case-Based Discussion

NASA Technical Reports Server (NTRS)

Sargsyan, Ashot E.; Kramer, Larry A.; Hamilton, Douglas R.; Hamilton, Douglas R.; Fogarty, Jennifer; Polk, J. D.

2010-01-01

Introduction: Intracranial pressure (ICP) elevation has been inferred or documented in a number of space crewmembers. Recent advances in noninvasive imaging technology offer new possibilities for ICP assessment. Most International Space Station (ISS) partner agencies have adopted a battery of occupational health monitoring tests including magnetic resonance imaging (MRI) pre- and postflight, and high-resolution sonography of the orbital structures in all mission phases including during flight. We hypothesize that joint consideration of data from the two techniques has the potential to improve quality and continuity of crewmember monitoring and care. Methods: Specially designed MRI and sonographic protocols were used to image eyes and optic nerves (ON) including the meningeal sheaths. Specific crewmembers multi-modality imaging data were analyzed to identify points of mutual validation as well as unique features of complementary nature. Results and Conclusion: Magnetic resonance imaging (MRI) and high-resolution sonography are both tomographic methods, however images obtained by the two modalities are based on different physical phenomena and use different acquisition principles. Consideration of the images acquired by these two modalities allows cross-validating findings related to the volume and fluid content of the ON subarachnoid space, shape of the globe, and other anatomical features of the orbit. Each of the imaging modalities also has unique advantages, making them complementary techniques.

Antibiofouling polymer coated gold nanoparticles as a dual modal contrast agent for X-ray and photoacoustic imaging

NASA Astrophysics Data System (ADS)

Huang, Guojia; Yuan, Yi; Xing, Da

2011-01-01

X-ray is one of the most useful diagnostic tools in hospitals in terms of frequency of use and cost, while photoacoustic (PA) imaging is a rapidly emerging non-invasive imaging technology that integrates the merits of high optical contrast with high ultrasound resolution. In this study, for the first time, we used gold nanoparticles (GNPs) as a dual modal contrast agent for X-ray and PA imaging. Soft gelatin phantoms with embedded tumor simulators of GNPs in various concentrations are clearly shown in both X-ray and PA imaging. With GNPs as a dual modal contrast agent, X-ray can fast detect the position of tumor and provide morphological information, whereas PA imaging has important potential applications in the image guided therapy of superficial tumors such as breast cancer, melanoma and Merkel cell carcinoma.

Contrast-enhanced spectral mammography vs. mammography and MRI - clinical performance in a multi-reader evaluation.

PubMed

Fallenberg, Eva M; Schmitzberger, Florian F; Amer, Heba; Ingold-Heppner, Barbara; Balleyguier, Corinne; Diekmann, Felix; Engelken, Florian; Mann, Ritse M; Renz, Diane M; Bick, Ulrich; Hamm, Bernd; Dromain, Clarisse

2017-07-01

To compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) to digital mammography (MG) and magnetic resonance imaging (MRI) in a prospective two-centre, multi-reader study. One hundred seventy-eight women (mean age 53 years) with invasive breast cancer and/or DCIS were included after ethics board approval. MG, CESM and CESM + MG were evaluated by three blinded radiologists based on amended ACR BI-RADS criteria. MRI was assessed by another group of three readers. Receiver-operating characteristic (ROC) curves were compared. Size measurements for the 70 lesions detected by all readers in each modality were correlated with pathology. Reading results for 604 lesions were available (273 malignant, 4 high-risk, 327 benign). The area under the ROC curve was significantly larger for CESM alone (0.84) and CESM + MG (0.83) compared to MG (0.76) (largest advantage in dense breasts) while it was not significantly different from MRI (0.85). Pearson correlation coefficients for size comparison were 0.61 for MG, 0.69 for CESM, 0.70 for CESM + MG and 0.79 for MRI. This study showed that CESM, alone and in combination with MG, is as accurate as MRI but is superior to MG for lesion detection. Patients with dense breasts benefitted most from CESM with the smallest additional dose compared to MG. • CESM has comparable diagnostic performance (ROC-AUC) to MRI for breast cancer diagnostics. • CESM in combination with MG does not improve diagnostic performance. • CESM has lower sensitivity but higher specificity than MRI. • Sensitivity differences are more pronounced in dense and not significant in non-dense breasts. • CESM and MRI are significantly superior to MG, particularly in dense breasts.

Access-enabling architectures : new hybrid multi-modal spatial prototypes towards resource and social sustainability : USDOT Region V Regional University Transportation Center final report.

DOT National Transportation Integrated Search

2016-12-19

The efforts of this project aim to capture and engage these potentials through a design-research method that incorporates a top down, data-driven approach with bottom-up stakeholder perspectives to develop prototypical scenario-based design solutions...

Designing a Website to Support Students' Academic Writing Process

ERIC Educational Resources Information Center

Åberg, Eva Svärdemo; Ståhle, Ylva; Engdahl, Ingrid; Knutes-Nyqvist, Helen

2016-01-01

Academic writing skills are crucial when students, e.g., in teacher education programs, write their undergraduate theses. A multi-modal web-based and self-regulated learning resource on academic writing was developed, using texts, hypertext, moving images, podcasts and templates. A study, using surveys and a focus group, showed that students used…

Continuity and Change in Literacy Practices: A Move towards Multiliteracies

ERIC Educational Resources Information Center

Kitson, Lisbeth; Fletcher, Margaret; Kearney, Judith

2007-01-01

In this paper we present findings from an empirical study-in-progress that investigates how a teacher integrates technology, specifically an Interactive Whiteboard (IWB), to teach multiliterate practices when reading multi-modal texts. This research was a collaboration between a teacher and a team of university-based researchers as they used…

A layered abduction model of perception: Integrating bottom-up and top-down processing in a multi-sense agent

NASA Technical Reports Server (NTRS)

Josephson, John R.

1989-01-01

A layered-abduction model of perception is presented which unifies bottom-up and top-down processing in a single logical and information-processing framework. The process of interpreting the input from each sense is broken down into discrete layers of interpretation, where at each layer a best explanation hypothesis is formed of the data presented by the layer or layers below, with the help of information available laterally and from above. The formation of this hypothesis is treated as a problem of abductive inference, similar to diagnosis and theory formation. Thus this model brings a knowledge-based problem-solving approach to the analysis of perception, treating perception as a kind of compiled cognition. The bottom-up passing of information from layer to layer defines channels of information flow, which separate and converge in a specific way for any specific sense modality. Multi-modal perception occurs where channels converge from more than one sense. This model has not yet been implemented, though it is based on systems which have been successful in medical and mechanical diagnosis and medical test interpretation.

Hybrid parameter identification of a multi-modal underwater soft robot.

PubMed

Giorgio-Serchi, F; Arienti, A; Corucci, F; Giorelli, M; Laschi, C

2017-02-28

We introduce an octopus-inspired, underwater, soft-bodied robot capable of performing waterborne pulsed-jet propulsion and benthic legged-locomotion. This vehicle consists for as much as 80% of its volume of rubber-like materials so that structural flexibility is exploited as a key element during both modes of locomotion. The high bodily softness, the unconventional morphology and the non-stationary nature of its propulsion mechanisms require dynamic characterization of this robot to be dealt with by ad hoc techniques. We perform parameter identification by resorting to a hybrid optimization approach where the characterization of the dual ambulatory strategies of the robot is performed in a segregated fashion. A least squares-based method coupled with a genetic algorithm-based method is employed for the swimming and the crawling phases, respectively. The outcomes bring evidence that compartmentalized parameter identification represents a viable protocol for multi-modal vehicles characterization. However, the use of static thrust recordings as the input signal in the dynamic determination of shape-changing self-propelled vehicles is responsible for the critical underestimation of the quadratic drag coefficient.

Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery

PubMed Central

Fuerst, Bernhard; Tateno, Keisuke; Johnson, Alex; Fotouhi, Javad; Osgood, Greg; Tombari, Federico; Navab, Nassir

2017-01-01

Orthopaedic surgeons are still following the decades old workflow of using dozens of two-dimensional fluoroscopic images to drill through complex 3D structures, e.g. pelvis. This Letter presents a mixed reality support system, which incorporates multi-modal data fusion and model-based surgical tool tracking for creating a mixed reality environment supporting screw placement in orthopaedic surgery. A red–green–blue–depth camera is rigidly attached to a mobile C-arm and is calibrated to the cone-beam computed tomography (CBCT) imaging space via iterative closest point algorithm. This allows real-time automatic fusion of reconstructed surface and/or 3D point clouds and synthetic fluoroscopic images obtained through CBCT imaging. An adapted 3D model-based tracking algorithm with automatic tool segmentation allows for tracking of the surgical tools occluded by hand. This proposed interactive 3D mixed reality environment provides an intuitive understanding of the surgical site and supports surgeons in quickly localising the entry point and orienting the surgical tool during screw placement. The authors validate the augmentation by measuring target registration error and also evaluate the tracking accuracy in the presence of partial occlusion. PMID:29184659

Gold standards and expert panels: a pulmonary nodule case study with challenges and solutions

NASA Astrophysics Data System (ADS)

Miller, Dave P.; O'Shaughnessy, Kathryn F.; Wood, Susan A.; Castellino, Ronald A.

2004-05-01

Comparative evaluations of reader performance using different modalities, e.g. CT with computer-aided detection (CAD) vs. CT without CAD, generally require a "truth" definition based on a gold standard. There are many situations in which a true invariant gold standard is impractical or impossible to obtain. For instance, small pulmonary nodules are generally not assessed by biopsy or resection. In such cases, it is common to use a unanimous consensus or majority agreement from an expert panel as a reference standard for actionability in lieu of the unknown gold standard for disease. Nonetheless, there are three major concerns about expert panel reference standards: (1) actionability is not synonymous with disease (2) it may be possible to obtain different conclusions about which modality is better using different rules (e.g. majority vs. unanimous consensus), and (3) the variability associated with the panelists is not formally captured in the p-values or confidence intervals that are generally produced for estimating the extent to which one modality is superior to the other. A multi-reader-multi-case (MRMC) receiver operating characteristic (ROC) study was performed using 90 cases, 15 readers, and a reference truth based on 3 experienced panelists. The primary analyses were conducted using a reference truth of unanimous consensus regarding actionability (3 out of 3 panelists). To assess the three concerns noted above: (1) additional data from the original radiology reports were compared to the panel (2) the complete analysis was repeated using different definitions of truth, and (3) bootstrap analyses were conducted in which new truth panels were constructed by picking 1, 2, or 3 panelists at random. The definition of the reference truth affected the results for each modality (CT with CAD and CT without CAD) considered by itself, but the effects were similar, so the primary analysis comparing the modalities was robust to the choice of the reference truth.

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.

Analysis of microvascular perfusion with multi-dimensional complete ensemble empirical mode decomposition with adaptive noise algorithm: Processing of laser speckle contrast images recorded in healthy subjects, at rest and during acetylcholine stimulation.

PubMed

Humeau-Heurtier, Anne; Marche, Pauline; Dubois, Severine; Mahe, Guillaume

2015-01-01

Laser speckle contrast imaging (LSCI) is a full-field imaging modality to monitor microvascular blood flow. It is able to give images with high temporal and spatial resolutions. However, when the skin is studied, the interpretation of the bidimensional data may be difficult. This is why an averaging of the perfusion values in regions of interest is often performed and the result is followed in time, reducing the data to monodimensional time series. In order to avoid such a procedure (that leads to a loss of the spatial resolution), we propose to extract patterns from LSCI data and to compare these patterns for two physiological states in healthy subjects: at rest and at the peak of acetylcholine-induced perfusion peak. For this purpose, the recent multi-dimensional complete ensemble empirical mode decomposition with adaptive noise (MCEEMDAN) algorithm is applied to LSCI data. The results show that the intrinsic mode functions and residue given by MCEEMDAN show different patterns for the two physiological states. The images, as bidimensional data, can therefore be processed to reveal microvascular perfusion patterns, hidden in the images themselves. This work is therefore a feasibility study before analyzing data in patients with microvascular dysfunctions.

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.

An assessment of multimodal imaging of subsurface text in mummy cartonnage using surrogate papyrus phantoms

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

Gibson, Adam; Piquette, Kathryn E.; Bergmann, Uwe

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to providemore » robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. Finally, the tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation.« less

An assessment of multimodal imaging of subsurface text in mummy cartonnage using surrogate papyrus phantoms

DOE PAGES

Gibson, Adam; Piquette, Kathryn E.; Bergmann, Uwe; ...

2018-02-26

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to providemore » robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. Finally, the tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation.« less

Modality-independent representations of small quantities based on brain activation patterns.

PubMed

Damarla, Saudamini Roy; Cherkassky, Vladimir L; Just, Marcel Adam

2016-04-01

Machine learning or MVPA (Multi Voxel Pattern Analysis) studies have shown that the neural representation of quantities of objects can be decoded from fMRI patterns, in cases where the quantities were visually displayed. Here we apply these techniques to investigate whether neural representations of quantities depicted in one modality (say, visual) can be decoded from brain activation patterns evoked by quantities depicted in the other modality (say, auditory). The main finding demonstrated, for the first time, that quantities of dots were decodable by a classifier that was trained on the neural patterns evoked by quantities of auditory tones, and vice-versa. The representations that were common across modalities were mainly right-lateralized in frontal and parietal regions. A second finding was that the neural patterns in parietal cortex that represent quantities were common across participants. These findings demonstrate a common neuronal foundation for the representation of quantities across sensory modalities and participants and provide insight into the role of parietal cortex in the representation of quantity information. © 2016 Wiley Periodicals, Inc.

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

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.

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

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.

2D and 3D X-ray phase retrieval of multi-material objects using a single defocus distance.

PubMed

Beltran, M A; Paganin, D M; Uesugi, K; Kitchen, M J

2010-03-29

A method of tomographic phase retrieval is developed for multi-material objects whose components each has a distinct complex refractive index. The phase-retrieval algorithm, based on the Transport-of-Intensity equation, utilizes propagation-based X-ray phase contrast images acquired at a single defocus distance for each tomographic projection. The method requires a priori knowledge of the complex refractive index for each material present in the sample, together with the total projected thickness of the object at each orientation. The requirement of only a single defocus distance per projection simplifies the experimental setup and imposes no additional dose compared to conventional tomography. The algorithm was implemented using phase contrast data acquired at the SPring-8 Synchrotron facility in Japan. The three-dimensional (3D) complex refractive index distribution of a multi-material test object was quantitatively reconstructed using a single X-ray phase-contrast image per projection. The technique is robust in the presence of noise, compared to conventional absorption based tomography.

The English Modals and Their Equivalents in Serbo-Croatian, with Pedagogical Material. New Studies Series, Volume 1.

ERIC Educational Resources Information Center

Kalogjera, Damir; Vilke, Mirjana

Part of a 20-year Yugoslav Serbocroatian-English Contrastive Project, this study is intended to make students, teachers, textbook writers, and scholars aware of elements in the system of English modals that might cause difficulties to the native Serbocroatian-speaking learner of English. An eclectic method of contrastive analysis consisting of…

[Pay attention to the application of the international intraocular retinoblastoma classification and sequential multiple modality treatment].

PubMed

Fan, X Q

2017-08-11

Retinoblastoma (RB) is the most common intraocular malignancy in childhood. It may seriously affect vision, and even threaten the life. The early diagnosis rate of RB in China remains low, and the majority of patients are at late phase with high rates of enucleation and mortality. The International Intraocular Retinoblastoma Classification and TNM staging system are guidances for therapeutic choices and bases for prognosis evaluation. Based on the sequential multi-method treatment modality, chemotherapy combined with local therapy is the mainstream in dealing with RB, which may maximize the results of eye saving and even vision retaining. New therapeutic techniques including supra-selective ophthalmic artery interventional chemotherapy and intravitreal chemotherapy can further improve the efficacy of treatment, especially the eye salvage rate. The overall level of RB treatment should be improved by promoting the international staging, new therapeutic techniques, and the sequential multiple modality treatment. (Chin J Ophthalmol, 2017, 53: 561 - 565) .

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.

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.

Multi-photon microscopy with a low-cost and highly efficient Cr:LiCAF laser

PubMed Central

Sakadić, Sava; Demirbas, Umit; Mempel, Thorsten R.; Moore, Anna; Ruvinskaya, Svetlana; Boas, David A.; Sennaroglu, Alphan; Kartner, Franz X.; Fujimoto, James G.

2009-01-01

Multi-photon microscopy (MPM) is a powerful tool for biomedical imaging, enabling molecular contrast and integrated structural and functional imaging on the cellular and subcellular level. However, the cost and complexity of femtosecond laser sources that are required in MPM are significant hurdles to widespread adoption of this important imaging modality. In this work, we describe femtosecond diode pumped Cr:LiCAF laser technology as a low cost alternative to femtosecond Ti:Sapphire lasers for MPM. Using single mode pump diodes which cost only $150 each, a diode pumped Cr:LiCAF laser generates ~70-fs duration, 1.8-nJ pulses at ~800 nm wavelengths, with a repetition rate of 100 MHz and average output power of 180 mW. Representative examples of MPM imaging in neuroscience, immunology, endocrinology and cancer research using Cr:LiCAF laser technology are presented. These studies demonstrate the potential of this laser source for use in a broad range of MPM applications. PMID:19065223

Design of graded refractive index profile for silica multimode optical fibers with improved effective modal bandwidth for short-distance laser-based multi-Gigabit data transmission over "O"-band

NASA Astrophysics Data System (ADS)

Bourdine, Anton V.; Zhukov, Alexander E.

2017-04-01

High bit rate laser-based data transmission over silica optical fibers with enlarged core diameter in comparison with standard singlemode fibers is found variety infocommunication applications. Since IEEE 802.3z standard was ratified on 1998 this technique started to be widely used for short-range in-premises distributed multi-Gigabit networks based on new generation laser optimized multimode fibers 50/125 of Cat. OM2…OM4. Nowadays it becomes to be in demand for on-board cable systems and industrial network applications requiring 1Gps and more bit rates over fibers with extremely enlarged core diameter up to 100 μm. This work presents an alternative method for design the special refractive index profiles of silica few-mode fibers with extremely enlarged core diameter, that provides modal bandwidth enhancing under a few-mode regime of laser-based data optical transmission. Here some results are presented concerning with refractive index profile synthesis for few-mode fibers with reduced differential mode delay for "O"-band central region, as well as computed differential mode delay spectral curves corresponding to profiles for fibers 50/125 and 100/125 for in-premises and on-board/industrial cable systems.

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

An antibody based approach for multi-coloring osteogenic and chondrogenic proteins in tissue engineered constructs.

PubMed

Leferink, Anne M; Reis, Diogo Santos; van Blitterswijk, Clemens A; Moroni, Lorenzo

2018-04-11

When tissue engineering strategies rely on the combination of three-dimensional (3D) polymeric or ceramic scaffolds with cells to culture implantable tissue constructs in vitro, it is desirable to monitor tissue growth and cell fate to be able to more rationally predict the quality and success of the construct upon implantation. Such a 3D construct is often referred to as a 'black-box' since the properties of the scaffolds material limit the applicability of most imaging modalities to assess important construct parameters. These parameters include the number of cells, the amount and type of tissue formed and the distribution of cells and tissue throughout the construct. Immunolabeling enables the spatial and temporal identification of multiple tissue types within one scaffold without the need to sacrifice the construct. In this report, we concisely review the applicability of antibodies (Abs) and their conjugation chemistries in tissue engineered constructs. With some preliminary experiments, we show an efficient conjugation strategy to couple extracellular matrix Abs to fluorophores. The conjugated probes proved to be effective in determining the presence of collagen type I and type II on electrospun and additive manufactured 3D scaffolds seeded with adult human bone marrow derived mesenchymal stromal cells. The conjugation chemistry applied in our proof of concept study is expected to be applicable in the coupling of any other fluorophore or particle to the Abs. This could ultimately lead to a library of probes to permit high-contrast imaging by several imaging modalities.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

PubMed

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

Concurrent emotional pictures modulate temporal order judgments of spatially separated audio-tactile stimuli.

PubMed

Jia, Lina; Shi, Zhuanghua; Zang, Xuelian; Müller, Hermann J

2013-11-06

Although attention can be captured toward high-arousal stimuli, little is known about how perceiving emotion in one modality influences the temporal processing of non-emotional stimuli in other modalities. We addressed this issue by presenting observers spatially uninformative emotional pictures while they performed an audio-tactile temporal-order judgment (TOJ) task. In Experiment 1, audio-tactile stimuli were presented at the same location straight ahead of the participants, who had to judge "which modality came first?". In Experiments 2 and 3, the audio-tactile stimuli were delivered one to the left and the other to the right side, and participants had to judge "which side came first?". We found both negative and positive high-arousal pictures to significantly bias TOJs towards the tactile and away from the auditory event when the audio-tactile stimuli were spatially separated; by contrast, there was no such bias when the audio-tactile stimuli originated from the same location. To further examine whether this bias is attributable to the emotional meanings conveyed by the pictures or to their high arousal effect, we compared and contrasted the influences of near-body threat vs. remote threat (emotional) pictures on audio-tactile TOJs in Experiment 3. The bias manifested only in the near-body threat condition. Taken together, the findings indicate that visual stimuli conveying meanings of near-body interaction activate a sensorimotor functional link prioritizing the processing of tactile over auditory signals when these signals are spatially separated. In contrast, audio-tactile signals from the same location engender strong crossmodal integration, thus counteracting modality-based attentional shifts induced by the emotional pictures. © 2013 Published by Elsevier B.V.

Lumbar spinal stenosis CAD from clinical MRM and MRI based on inter- and intra-context features with a two-level classifier

NASA Astrophysics Data System (ADS)

Koh, Jaehan; Alomari, Raja S.; Chaudhary, Vipin; Dhillon, Gurmeet

2011-03-01

An imaging test has an important role in the diagnosis of lumbar abnormalities since it allows to examine the internal structure of soft tissues and bony elements without the need of an unnecessary surgery and recovery time. For the past decade, among various imaging modalities, magnetic resonance imaging (MRI) has taken the significant part of the clinical evaluation of the lumbar spine. This is mainly due to technological advancements that lead to the improvement of imaging devices in spatial resolution, contrast resolution, and multi-planar capabilities. In addition, noninvasive nature of MRI makes it easy to diagnose many common causes of low back pain such as disc herniation, spinal stenosis, and degenerative disc diseases. In this paper, we propose a method to diagnose lumbar spinal stenosis (LSS), a narrowing of the spinal canal, from magnetic resonance myelography (MRM) images. Our method segments the thecal sac in the preprocessing stage, generates the features based on inter- and intra-context information, and diagnoses lumbar disc stenosis. Experiments with 55 subjects show that our method achieves 91.3% diagnostic accuracy. In the future, we plan to test our method on more subjects.

Indocyanine Green Loaded Reduced Graphene Oxide for In Vivo Photoacoustic/Fluorescence Dual-Modality Tumor Imaging

NASA Astrophysics Data System (ADS)

Chen, Jingqin; Liu, Chengbo; Zeng, Guang; You, Yujia; Wang, Huina; Gong, Xiaojing; Zheng, Rongqin; Kim, Jeesu; Kim, Chulhong; Song, Liang

2016-02-01

Multimodality imaging based on multifunctional nanocomposites holds great promise to fundamentally augment the capability of biomedical imaging. Specifically, photoacoustic and fluorescence dual-modality imaging is gaining much interest because of their non-invasiveness and the complementary nature of the two modalities in terms of imaging resolution, depth, sensitivity, and speed. Herein, using a green and facile method, we synthesize indocyanine green (ICG) loaded, polyethylene glycol (PEG)ylated, reduced nano-graphene oxide nanocomposite (rNGO-PEG/ICG) as a new type of fluorescence and photoacoustic dual-modality imaging contrast. The nanocomposite is shown to have minimal toxicity and excellent photoacoustic/fluorescence signals both in vitro and in vivo. Compared with free ICG, the nanocomposite is demonstrated to possess greater stability, longer blood circulation time, and superior passive tumor targeting capability. In vivo study shows that the circulation time of rNGO-PEG/ICG in the mouse body can sustain up to 6 h upon intravenous injection; while after 1 day, no obvious accumulation of rNGO-PEG/ICG is found in any major organs except the tumor regions. The demonstrated high fluorescence/photoacoustic dual contrasts, together with its low toxicity and excellent circulation life time, suggest that the synthesized rNGO-PEG/ICG can be a promising candidate for further translational studies on both the early diagnosis and image-guided therapy/surgery of cancer.

Tissue-like phantoms

DOEpatents

Frangioni, John V.; De Grand, Alec M.

2007-10-30

The invention is based, in part, on the discovery that by combining certain components one can generate a tissue-like phantom that mimics any desired tissue, is simple and inexpensive to prepare, and is stable over many weeks or months. In addition, new multi-modal imaging objects (e.g., beads) can be inserted into the phantoms to mimic tissue pathologies, such as cancer, or merely to serve as calibration standards. These objects can be imaged using one, two, or more (e.g., four) different imaging modalities (e.g., x-ray computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), and near-infrared (NIR) fluorescence) simultaneously.

Sensor chip and apparatus for tactile and/or flow sensing

NASA Technical Reports Server (NTRS)

Liu, Chang (Inventor); Chen, Jack (Inventor); Engel, Jonathan (Inventor)

2008-01-01

A sensor chip, comprising a flexible, polymer-based substrate, and at least one microfabricated sensor disposed on the substrate and including a conductive element. The at least one sensor comprises at least one of a tactile sensor and a flow sensor. Other embodiments of the present invention include sensors and/or multi-modal sensor nodes.

49 CFR Appendix A to Part 611 - Description of Measures Used for Project Evaluation.

Code of Federal Regulations, 2012 CFR

2012-10-01

... alternative, travelers projected to shift to transit because of the new start project, and non-transit users... measure will be based on a multi-modal measure of perceived travel times faced by all users of the..., and level of commitment of each proposed source of local match, including inter-governmental grants...

Information Systems for Subject Specialists: A Multi-Modal Approach to Indexing and Classification.

ERIC Educational Resources Information Center

Swift, D.F.; And Others

A fundamental problem in the two broad approaches to indexing in the social sciences--providing structure using preferred terms, cross references, and groupings of sets of materials, or compiling a concordance of an author's terms based on occurrence, leaving users free to impose their own structure--is that different indexers and users focus on…

Sensor chip and apparatus for tactile and/or flow sensing

NASA Technical Reports Server (NTRS)

Liu, Chang (Inventor); Chen, Jack (Inventor); Engel, Jonathan (Inventor)

2009-01-01

A sensor chip, comprising a flexible, polymer-based substrate, and at least one microfabricated sensor disposed on the substrate and including a conductive element. The at least one sensor comprises at least one of a tactile sensor and a flow sensor. Other embodiments of the present invention include sensors and/or multi-modal sensor nodes.

Business Intelligence Basics: Multi-Modal Means of Analyzing Data Can Produce Actionable Results

ERIC Educational Resources Information Center

Mills, Lane

2008-01-01

School systems face many decisions in developing and maintaining learning environments that create success for all students. From district operations to the classroom, district leaders implement solutions and take action based on the information they have at hand. While there is no shortage of data, turning that data into useful information is as…

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

Imaging of Rabbit VX-2 Hepatic Cancer by Cold and Thermal Neutron Radiography

NASA Astrophysics Data System (ADS)

Tsuchiya, Yoshinori; Matsubayashi, Masahito; Takeda, Tohoru; Lwin, Thet Thet; Wu, Jin; Yoneyama, Akio; Matsumura, Akira; Hori, Tomiei; Itai, Yuji

2003-11-01

Neutron radiography is based on differences in neutron mass attenuation coefficients among the elements and is a non-destructive imaging method. To investigate biomedical applications of neutron radiography, imaging of rabbit VX-2 liver cancer was performed using thermal and cold neutron radiography with a neutron imaging plate. Hepatic vessels and VX-2 tumor were clearly observed by neutron radiography, especially by cold neutron imaging. The image contrast of this modality was better than that of absorption-contrast X-ray radiography.

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

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

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

Neural correlates of free recall of "famous events" in a "hypermnestic" individual as compared to an age- and education-matched reference group.

PubMed

Fehr, Thorsten; Staniloiu, Angelica; Markowitsch, Hans J; Erhard, Peter; Herrmann, Manfred

2018-06-19

Memory performance of an individual (within the age range: 50-55 years old) showing superior memory abilities (protagonist PR) was compared to an age- and education-matched reference group in a historical facts ("famous events") retrieval task. Contrasting task versus baseline performance both PR and the reference group showed fMRI activation patterns in parietal and occipital brain regions. The reference group additionally demonstrated activation patterns in cingulate gyrus, whereas PR showed additional widespread activation patterns comprising frontal and cerebellar brain regions. The direct comparison between PR and the reference group revealed larger fMRI contrasts for PR in right frontal, superior temporal and cerebellar brain regions. It was concluded that PR generally recruits brain regions as normal memory performers do, but in a more elaborate way, and furthermore, that he applied a memory-strategy that potentially includes executively driven multi-modal transcoding of information and recruitment of implicit memory resources.

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.

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.

Non-invasive continuous imaging of drug release from soy-based skin equivalent using wide-field interferometry

NASA Astrophysics Data System (ADS)

Gabai, Haniel; Baranes-Zeevi, Maya; Zilberman, Meital; Shaked, Natan T.

2013-04-01

We propose an off-axis interferometric imaging system as a simple and unique modality for continuous, non-contact and non-invasive wide-field imaging and characterization of drug release from its polymeric device used in biomedicine. In contrast to the current gold-standard methods in this field, usually based on chromatographic and spectroscopic techniques, our method requires no user intervention during the experiment, and only one test-tube is prepared. We experimentally demonstrate imaging and characterization of drug release from soy-based protein matrix, used as skin equivalent for wound dressing with controlled anesthetic, Bupivacaine drug release. Our preliminary results demonstrate the high potential of our method as a simple and low-cost modality for wide-field imaging and characterization of drug release from drug delivery devices.

Computational Assessment of Blood Flow Heterogeneity in Peritoneal Dialysis Patients' Cardiac Ventricles

PubMed Central

Kharche, Sanjay R.; So, Aaron; Salerno, Fabio; Lee, Ting-Yim; Ellis, Chris; Goldman, Daniel; McIntyre, Christopher W.

2018-01-01

Dialysis prolongs life but augments cardiovascular mortality. Imaging data suggests that dialysis increases myocardial blood flow (BF) heterogeneity, but its causes remain poorly understood. A biophysical model of human coronary vasculature was used to explain the imaging observations, and highlight causes of coronary BF heterogeneity. Post-dialysis CT images from patients under control, pharmacological stress (adenosine), therapy (cooled dialysate), and adenosine and cooled dialysate conditions were obtained. The data presented disparate phenotypes. To dissect vascular mechanisms, a 3D human vasculature model based on known experimental coronary morphometry and a space filling algorithm was implemented. Steady state simulations were performed to investigate the effects of altered aortic pressure and blood vessel diameters on myocardial BF heterogeneity. Imaging showed that stress and therapy potentially increased mean and total BF, while reducing heterogeneity. BF histograms of one patient showed multi-modality. Using the model, it was found that total coronary BF increased as coronary perfusion pressure was increased. BF heterogeneity was differentially affected by large or small vessel blocking. BF heterogeneity was found to be inversely related to small blood vessel diameters. Simulation of large artery stenosis indicates that BF became heterogeneous (increase relative dispersion) and gave multi-modal histograms. The total transmural BF as well as transmural BF heterogeneity reduced due to large artery stenosis, generating large patches of very low BF regions downstream. Blocking of arteries at various orders showed that blocking larger arteries results in multi-modal BF histograms and large patches of low BF, whereas smaller artery blocking results in augmented relative dispersion and fractal dimension. Transmural heterogeneity was also affected. Finally, the effects of augmented aortic pressure in the presence of blood vessel blocking shows differential effects on BF heterogeneity as well as transmural BF. Improved aortic blood pressure may improve total BF. Stress and therapy may be effective if they dilate small vessels. A potential cause for the observed complex BF distributions (multi-modal BF histograms) may indicate existing large vessel stenosis. The intuitive BF heterogeneity methods used can be readily used in clinical studies. Further development of the model and methods will permit personalized assessment of patient BF status. PMID:29867555

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.

Contrast echocardiography: new agents.

PubMed

Miller, Andrew P; Nanda, Navin C

2004-04-01

In this report, we review the history, rationale, current status and future directions of contrast agents in echocardiography. First, we discuss the historic development of contrast agents through a review of important physical principles of microbubbles in ultrasonography. Second, we identify attributes of an ideal contrast agent and review those that are currently available or in the "pipeline" for clinical use. Third, we review indications for contrast echocardiography, including endocardial border detection, perfusion quantification and reperfusion assessment, and validate these observations by comparisons with other imaging modalities. Then, we briefly review different methodologies of performing a contrast study, including interrupted, real-time and a hybrid modality. Finally, we identify novel future applications of the newest contrast agents. These newer concepts in contrast echocardiography should form a foundation for nearly limitless application of echocardiography in improved anatomical assessment, perfusion imaging and even special applications, such as detection of vascular inflammation and site-specific drug delivery.

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

DOE PAGES

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.; ...

2016-02-05

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

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

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

An extremely simple macroscale electronic skin realized by deep machine learning.

PubMed

Sohn, Kee-Sun; Chung, Jiyong; Cho, Min-Young; Timilsina, Suman; Park, Woon Bae; Pyo, Myungho; Shin, Namsoo; Sohn, Keemin; Kim, Ji Sik

2017-09-11

Complicated structures consisting of multi-layers with a multi-modal array of device components, i.e., so-called patterned multi-layers, and their corresponding circuit designs for signal readout and addressing are used to achieve a macroscale electronic skin (e-skin). In contrast to this common approach, we realized an extremely simple macroscale e-skin only by employing a single-layered piezoresistive MWCNT-PDMS composite film with neither nano-, micro-, nor macro-patterns. It is the deep machine learning that made it possible to let such a simple bulky material play the role of a smart sensory device. A deep neural network (DNN) enabled us to process electrical resistance change induced by applied pressure and thereby to instantaneously evaluate the pressure level and the exact position under pressure. The great potential of this revolutionary concept for the attainment of pressure-distribution sensing on a macroscale area could expand its use to not only e-skin applications but to other high-end applications such as touch panels, portable flexible keyboard, sign language interpreting globes, safety diagnosis of social infrastructures, and the diagnosis of motility and peristalsis disorders in the gastrointestinal tract.

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.

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.

Quantitative breast tissue characterization using grating-based x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

Willner, M.; Herzen, J.; Grandl, S.; Auweter, S.; Mayr, D.; Hipp, A.; Chabior, M.; Sarapata, A.; Achterhold, K.; Zanette, I.; Weitkamp, T.; Sztrókay, A.; Hellerhoff, K.; Reiser, M.; Pfeiffer, F.

2014-04-01

X-ray phase-contrast imaging has received growing interest in recent years due to its high capability in visualizing soft tissue. Breast imaging became the focus of particular attention as it is considered the most promising candidate for a first clinical application of this contrast modality. In this study, we investigate quantitative breast tissue characterization using grating-based phase-contrast computed tomography (CT) at conventional polychromatic x-ray sources. Different breast specimens have been scanned at a laboratory phase-contrast imaging setup and were correlated to histopathology. Ascertained tumor types include phylloides tumor, fibroadenoma and infiltrating lobular carcinoma. Identified tissue types comprising adipose, fibroglandular and tumor tissue have been analyzed in terms of phase-contrast Hounsfield units and are compared to high-quality, high-resolution data obtained with monochromatic synchrotron radiation, as well as calculated values based on tabulated tissue properties. The results give a good impression of the method’s prospects and limitations for potential tumor detection and the associated demands on such a phase-contrast breast CT system. Furthermore, the evaluated quantitative tissue values serve as a reference for simulations and the design of dedicated phantoms for phase-contrast mammography.

VIGAN: Missing View Imputation with Generative Adversarial Networks.

PubMed

Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo

2017-01-01

In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.

Multi-grid finite element method used for enhancing the reconstruction accuracy in Cerenkov luminescence tomography

NASA Astrophysics Data System (ADS)

Guo, Hongbo; He, Xiaowei; Liu, Muhan; Zhang, Zeyu; Hu, Zhenhua; Tian, Jie

2017-03-01

Cerenkov luminescence tomography (CLT), as a promising optical molecular imaging modality, can be applied to cancer diagnostic and therapeutic. Most researches about CLT reconstruction are based on the finite element method (FEM) framework. However, the quality of FEM mesh grid is still a vital factor to restrict the accuracy of the CLT reconstruction result. In this paper, we proposed a multi-grid finite element method framework, which was able to improve the accuracy of reconstruction. Meanwhile, the multilevel scheme adaptive algebraic reconstruction technique (MLS-AART) based on a modified iterative algorithm was applied to improve the reconstruction accuracy. In numerical simulation experiments, the feasibility of our proposed method were evaluated. Results showed that the multi-grid strategy could obtain 3D spatial information of Cerenkov source more accurately compared with the traditional single-grid FEM.

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.

Enhancing sound absorption and transmission through flexible multi-layer micro-perforated structures.

PubMed

Bravo, Teresa; Maury, Cédric; Pinhède, Cédric

2013-11-01

Theoretical and experimental results are presented into the sound absorption and transmission properties of multi-layer structures made up of thin micro-perforated panels (ML-MPPs). The objective is to improve both the absorption and insulation performances of ML-MPPs through impedance boundary optimization. A fully coupled modal formulation is introduced that predicts the effect of the structural resonances onto the normal incidence absorption coefficient and transmission loss of ML-MPPs. This model is assessed against standing wave tube measurements and simulations based on impedance translation method for two double-layer MPP configurations of relevance in building acoustics and aeronautics. Optimal impedance relationships are proposed that ensure simultaneous maximization of both the absorption and the transmission loss under normal incidence. Exhaustive optimization of the double-layer MPPs is performed to assess the absorption and/or transmission performances with respect to the impedance criterion. It is investigated how the panel volumetric resonances modify the excess dissipation that can be achieved from non-modal optimization of ML-MPPs.

Nucleophosmin integrates within the nucleolus via multi-modal interactions with proteins displaying R-rich linear motifs and rRNA.

PubMed

Mitrea, Diana M; Cika, Jaclyn A; Guy, Clifford S; Ban, David; Banerjee, Priya R; Stanley, Christopher B; Nourse, Amanda; Deniz, Ashok A; Kriwacki, Richard W

2016-02-02

The nucleolus is a membrane-less organelle formed through liquid-liquid phase separation of its components from the surrounding nucleoplasm. Here, we show that nucleophosmin (NPM1) integrates within the nucleolus via a multi-modal mechanism involving multivalent interactions with proteins containing arginine-rich linear motifs (R-motifs) and ribosomal RNA (rRNA). Importantly, these R-motifs are found in canonical nucleolar localization signals. Based on a novel combination of biophysical approaches, we propose a model for the molecular organization within liquid-like droplets formed by the N-terminal domain of NPM1 and R-motif peptides, thus providing insights into the structural organization of the nucleolus. We identify multivalency of acidic tracts and folded nucleic acid binding domains, mediated by N-terminal domain oligomerization, as structural features required for phase separation of NPM1 with other nucleolar components in vitro and for localization within mammalian nucleoli. We propose that one mechanism of nucleolar localization involves phase separation of proteins within the nucleolus.

Highly stable multi-wavelength erbium-doped fiber linear laser based on modal interference

NASA Astrophysics Data System (ADS)

Herrera-Piad, L. A.; Jauregui-Vazquez, D.; Lopez-Dieguez, Y.; Estudillo-Ayala, J. M.; Hernandez-Garcia, J. C.; Sierra-Hernandez, J. M.; Bianchetti, M.; Rojas-Laguna, R.

2018-03-01

We report a linear fiber laser cavity based on an all-fiber Fabry-Perot interferometer and bi-tapered optical fiber for multi-wavelength emission generation. Curvature and strain are used to operate the laser system and the number of lines as well, the emission regions are stronger related to the physical effect applied, due to the phase alteration between the multiple fiber optic modes involved. The original laser emissions present zero wavelength variations, minimal power fluctuations and small spacing mode (1 nm). Additionally, a nonlinear fiber was employed trying to improve the performance of the multiple lasing lines. This system offers a low implementation cost, compactness and good laser parameters.

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.

Nanomaterials for In Vivo Imaging.

PubMed

Smith, Bryan Ronain; Gambhir, Sanjiv Sam

2017-02-08

In vivo imaging, which enables us to peer deeply within living subjects, is producing tremendous opportunities both for clinical diagnostics and as a research tool. Contrast material is often required to clearly visualize the functional architecture of physiological structures. Recent advances in nanomaterials are becoming pivotal to generate the high-resolution, high-contrast images needed for accurate, precision diagnostics. Nanomaterials are playing major roles in imaging by delivering large imaging payloads, yielding improved sensitivity, multiplexing capacity, and modularity of design. Indeed, for several imaging modalities, nanomaterials are now not simply ancillary contrast entities, but are instead the original and sole source of image signal that make possible the modality's existence. We address the physicochemical makeup/design of nanomaterials through the lens of the physical properties that produce contrast signal for the cognate imaging modality-we stratify nanomaterials on the basis of their (i) magnetic, (ii) optical, (iii) acoustic, and/or (iv) nuclear properties. We evaluate them for their ability to provide relevant information under preclinical and clinical circumstances, their in vivo safety profiles (which are being incorporated into their chemical design), their modularity in being fused to create multimodal nanomaterials (spanning multiple different physical imaging modalities and therapeutic/theranostic capabilities), their key properties, and critically their likelihood to be clinically translated.

Recent Trends in Antibody-based Oncologic Imaging

PubMed Central

Kaur, Sukhwinder; Venktaraman, Ganesh; Jain, Maneesh; Senapati, Shantibhusan; Garg, Pradeep K.; Batra, Surinder K.

2011-01-01

Antibodies, with their unmatched ability for selective binding to any target, are considered as potentially the most specific probes for imaging. Their clinical utility, however, has been limited chiefly due to their slow clearance from the circulation, longer retention in non-targeted tissues and the extensive optimization required for each antibody-tracer. The development of newer contrast agents, combined with improved conjugation strategies and novel engineered forms of antibodies (diabodies, minibodies, single chain variable fragments, and nanobodies), have triggered a new wave of antibody-based imaging approaches. Apart from their conventional use with nuclear imaging probes, antibodies and their modified forms are increasingly being employed with non-radioisotopic contrast agents (MRI and ultrasound) as well as newer imaging modalities, such as quantum dots, near infra red (NIR) probes, nanoshells and surface enhanced Raman spectroscopy (SERS). The review article provides new developments in the usage of antibodies and their modified forms in conjunction with probes of various imaging modalities such as nuclear imaging, optical imaging, ultrasound, MRI, SERS and nanoshells in preclinical and clinical studies on the diagnosis, prognosis and therapeutic responses of cancer. PMID:22104729

Multimodal computational microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

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

2016-12-01

Transport of intensity equation (TIE) is a powerful tool for phase retrieval and quantitative phase imaging, which requires intensity measurements only at axially closely spaced planes without a separate reference beam. It does not require coherent illumination and works well on conventional bright-field microscopes. The quantitative phase reconstructed by TIE gives valuable information that has been encoded in the complex wave field by passage through a sample of interest. Such information may provide tremendous flexibility to emulate various microscopy modalities computationally without requiring specialized hardware components. We develop a requisite theory to describe such a hybrid computational multimodal imaging system, which yields quantitative phase, Zernike phase contrast, differential interference contrast, and light field moment imaging, simultaneously. It makes the various observations for biomedical samples easy. Then we 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 postprocessing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

Gold nanoclusters as contrast agents for fluorescent and X-ray dual-modality imaging.

PubMed

Zhang, Aili; Tu, Yu; Qin, Songbing; Li, Yan; Zhou, Juying; Chen, Na; Lu, Qiang; Zhang, Bingbo

2012-04-15

Multimodal imaging technique is an alternative approach to improve sensitivity of early cancer diagnosis. In this study, highly fluorescent and strong X-ray absorption coefficient gold nanoclusters (Au NCs) are synthesized as dual-modality imaging contrast agents (CAs) for fluorescent and X-ray dual-modality imaging. The experimental results show that the as-prepared Au NCs are well constructed with ultrasmall sizes, reliable fluorescent emission, high computed tomography (CT) value and fine biocompatibility. In vivo imaging results indicate that the obtained Au NCs are capable of fluorescent and X-ray enhanced imaging. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

In-vacuum multi-modal monochromator for synchrotron-based hard x-ray micro-imaging

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

Renier, M., E-mail: renier@esrf.fr; Rack, A.; Valade, J. P.

2016-07-27

The original monochromator design we present consists in a high-vacuum vessel comprising three monochromators mounted side-by-side: a Lauë/Lauë, a Bragg/Bragg, and a double-multilayer monochromator. The selection of one monochromator type is done remotely by sliding laterally the crystal support in the monochromator vessel. In this way, exotic combinations such as Lauë/Bragg are also possible. Installation and commissioning of the new monochromator at ESRF beamline ID19 was carried out 2013-2014 (the multilayers not being installed yet). Beamline ID19 offers not only superb beam characteristics for phase-contrast imaging with a high level of sensitivity but also compared to other synchrotron X-ray imagingmore » facilities a large beam of currently up to 7 cm × 1.3 cm. A wide energy range can be accessed in a fixed-exit mode (depending on the optics chosen the accessible energy range is between 10 keV and 200 keV). A beryllium exit window (10 cm × 10 cm active opening) completes the monochromator assembly.« less

From Grey Scale B-Mode to Elastosonography: Multimodal Ultrasound Imaging in Meningioma Surgery-Pictorial Essay and Literature Review.

PubMed

Prada, Francesco; Del Bene, Massimiliano; Moiraghi, Alessandro; Casali, Cecilia; Legnani, Federico Giuseppe; Saladino, Andrea; Perin, Alessandro; Vetrano, Ignazio Gaspare; Mattei, Luca; Richetta, Carla; Saini, Marco; DiMeco, Francesco

2015-01-01

The main goal in meningioma surgery is to achieve complete tumor removal, when possible, while improving or preserving patient neurological functions. Intraoperative imaging guidance is one fundamental tool for such achievement. In this regard, intra-operative ultrasound (ioUS) is a reliable solution to obtain real-time information during surgery and it has been applied in many different aspect of neurosurgery. In the last years, different ioUS modalities have been described: B-mode, Fusion Imaging with pre-operative acquired MRI, Doppler, contrast enhanced ultrasound (CEUS), and elastosonography. In this paper, we present our US based multimodal approach in meningioma surgery. We describe all the most relevant ioUS modalities and their intraoperative application to obtain precise and specific information regarding the lesion for a tailored approach in meningioma surgery. For each modality, we perform a review of the literature accompanied by a pictorial essay based on our routinely use of ioUS for meningioma resection.

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...

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Dual-modality single particle orientation and rotational tracking of intracellular transport of nanocargos.

PubMed

Sun, Wei; Gu, Yan; Wang, Gufeng; Fang, Ning

2012-01-17

The single particle orientation and rotational tracking (SPORT) technique was introduced recently to follow the rotational motion of plasmonic gold nanorod under a differential interference contrast (DIC) microscope. In biological studies, however, cellular activities usually involve a multiplicity of molecules; thus, tracking the motion of a single molecule/object is insufficient. Fluorescence-based techniques have long been used to follow the spatial and temporal distributions of biomolecules of interest thanks to the availability of multiplexing fluorescent probes. To know the type and number of molecules and the timing of their involvement in a biological process under investigation by SPORT, we constructed a dual-modality DIC/fluorescence microscope to simultaneously image fluorescently tagged biomolecules and plasmonic nanoprobes in living cells. With the dual-modality SPORT technique, the microtubule-based intracellular transport can be unambiguously identified while the dynamic orientation of nanometer-sized cargos can be monitored at video rate. Furthermore, the active transport on the microtubule can be easily separated from the diffusion before the nanocargo docks on the microtubule or after it undocks from the microtubule. The potential of dual-modality SPORT is demonstrated for shedding new light on unresolved questions in intracellular transport.

Multi-modal porous microstructure for high temperature fuel cell application

NASA Astrophysics Data System (ADS)

Wejrzanowski, T.; Haj Ibrahim, S.; Cwieka, K.; Loeffler, M.; Milewski, J.; Zschech, E.; Lee, C.-G.

2018-01-01

In this study, the effect of microstructure of porous nickel electrode on the performance of high temperature fuel cell is investigated and presented based on a molten carbonate fuel cell (MCFC) cathode. The cathode materials are fabricated from slurry consisting of nickel powder and polymeric binder/solvent mixture, using the tape casting method. The final pore structure is shaped through modifying the slurry composition - with or without the addition of porogen(s). The manufactured materials are extensively characterized by various techniques involving: micro-computed tomography (micro-XCT), scanning electron microscopy (SEM), mercury porosimetry, BET and Archimedes method. Tomographic images are also analyzed and quantified to reveal the evolution of pore space due to nickel in situ oxidation to NiO, and infiltration by the electrolyte. Single-cell performance tests are carried out under MCFC operation conditions to estimate the performance of the manufactured materials. It is found that the multi-modal microstructure of MCFC cathode results in a significant enhancement of the power density generated by the reference cell. To give greater insight into the understanding of the effect of microstructure on the properties of the cathode, a model based on 3D tomography image transformation is proposed.

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography

PubMed Central

Jiao, Shuliang; Zhang, Hao F.

2013-01-01

Both the clinical diagnosis and fundamental investigation of major ocular diseases greatly benefit from various non-invasive ophthalmic imaging technologies. Existing retinal imaging modalities, such as fundus photography1, confocal scanning laser ophthalmoscopy (cSLO)2, and optical coherence tomography (OCT)3, have significant contributions in monitoring disease onsets and progressions, and developing new therapeutic strategies. However, they predominantly rely on the back-reflected photons from the retina. As a consequence, the optical absorption properties of the retina, which are usually strongly associated with retinal pathophysiology status, are inaccessible by the traditional imaging technologies. Photoacoustic ophthalmoscopy (PAOM) is an emerging retinal imaging modality that permits the detection of the optical absorption contrasts in the eye with a high sensitivity4-7 . In PAOM nanosecond laser pulses are delivered through the pupil and scanned across the posterior eye to induce photoacoustic (PA) signals, which are detected by an unfocused ultrasonic transducer attached to the eyelid. Because of the strong optical absorption of hemoglobin and melanin, PAOM is capable of non-invasively imaging the retinal and choroidal vasculatures, and the retinal pigment epithelium (RPE) melanin at high contrasts 6,7. More importantly, based on the well-developed spectroscopic photoacoustic imaging5,8 , PAOM has the potential to map the hemoglobin oxygen saturation in retinal vessels, which can be critical in studying the physiology and pathology of several blinding diseases 9 such as diabetic retinopathy and neovascular age-related macular degeneration. Moreover, being the only existing optical-absorption-based ophthalmic imaging modality, PAOM can be integrated with well-established clinical ophthalmic imaging techniques to achieve more comprehensive anatomic and functional evaluations of the eye based on multiple optical contrasts6,10 . In this work, we integrate PAOM and spectral-domain OCT (SD-OCT) for simultaneously in vivo retinal imaging of rat, where both optical absorption and scattering properties of the retina are revealed. The system configuration, system alignment and imaging acquisition are presented. PMID:23354081

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.

[Non-contrast time-resolved magnetic resonance angiography combining high resolution multiple phase echo planar imaging based signal targeting and alternating radiofrequency contrast inherent inflow enhanced multi phase angiography combining spatial resolution echo planar imaging based signal targeting and alternating radiofrequency in intracranial arteries].

PubMed

Nakamura, Masanobu; Yoneyama, Masami; Tabuchi, Takashi; Takemura, Atsushi; Obara, Makoto; Sawano, Seishi

2012-01-01

Detailed information on anatomy and hemodynamics in cerebrovascular disorders such as AVM and Moyamoya disease is mandatory for defined diagnosis and treatment planning. Arterial spin labeling technique has come to be applied to magnetic resonance angiography (MRA) and perfusion imaging in recent years. However, those non-contrast techniques are mostly limited to single frame images. Recently we have proposed a non-contrast time-resolved MRA technique termed contrast inherent inflow enhanced multi phase angiography combining spatial resolution echo planar imaging based signal targeting and alternating radiofrequency (CINEMA-STAR). CINEMA-STAR can extract the blood flow in the major intracranial arteries at an interval of 70 ms and thus permits us to observe vascular construction in full by preparing MIP images of axial acquisitions with high spatial resolution. This preliminary study demonstrates the usefulness of the CINEMA-STAR technique in evaluating the cerebral vasculature.

Engineering of Nanoscale Contrast Agents for Optical Coherence Tomography.

PubMed

Gordon, Andrew Y; Jayagopal, Ashwath

2014-01-30

Optical coherence tomography has emerged as valuable imaging modalityin ophthalmology and other fields by enabling high-resolution three-dimensional imaging of tissue. In this paper, we review recent progress in the field of contrast-enhanced optical coherence tomography (OCT). We discuss exogenous and endogenous sources of OCT contrast, focusing on their use with standard OCT systems as well as emerging OCT-based imaging modalities. We include advances in the processing of OCT data that generate improved tissue contrast, including spectroscopic OCT (SOCT), as well as work utilizing secondary light sources and/or detection mechanisms to create and detect enhanced contrast, including photothermal OCT (PTOCT) and photoacoustic OCT (PAOCT). Finally, we conclude with a discussion of the translational potential of these developments as well as barriers to their clinical use.

Use of 3-D digital subtraction rotational angiography during cardiac catheterization of infants and adults with congenital heart diseases.

PubMed

Surendran, Sushitha; Waller, B Rush; Elijovich, Lucas; Agrawal, Vijaykumar; Kuhls-Gilcrist, Andrew; Johnson, Jason; Fagan, Thomas; Sathanandam, Shyam K

2017-10-01

To compare image quality, radiation and contrast doses required to obtain 3D-Digital subtraction rotational angiography (3D-DSRA) with 3D-Digital rotational angiography (3D-DRA) in infants (children ≤ 2 years of age) and adults with congenital heart diseases (ACHD). 3D-DRA can be performed with radiation doses comparable to bi-plane cine-angiography. However, 3D-DRA in infants requires a large contrast volume. The resolution of 3D-DRA performed in ACHD patients is limited by their soft tissue density. We hypothesized that the use of 3D-DSRA could help alleviate these concerns. Radiation (DAP) and contrast doses required to obtain 3D-DSRA was compared with 3D-DRA in 15 age-, size-, and intervention-matched infants and 15 ACHD patients. The diagnostic quality and utility of these two modalities were scored by 4 qualified independent observers. Both in infants and adults, the median contrast volume for 3D-DSRA was lower than 3D-DRA (0.98 vs. 1.81 mL/kg; P < 0.001 and 0.92 vs. 1.4 mL/kg; P < 0.001, respectively) with an increased DAP (median: 188 vs. 128 cGy cm 2 ; P = 0.068 and 659 vs. 427 cGy cm 2 ; P = 0.045, respectively). The diagnostic quality and utility scores for rotational-angiography, and 3D-reconstruction were superior for 3D-DSRA (score = 94 vs. 80%, P = 0.03 and 90 vs.79%, P = 0.01, respectively) and equivalent for multi-planar-reformation and 3D-roadmapping in ACHD patients compared with 3D-DRA. All scores for both modalities were equivalent for infants. 3D-DSRA can be acquired using lower contrast volume with a mildly higher radiation dose than 3D-DRA in infants and ACHD patients. The diagnostic quality and utility scores for 3D-DSRA were higher in ACHD patients and equivalent for infants compared with 3D-DRA. © 2017 Wiley Periodicals, Inc.

Self-assembled dual-modality contrast agents for non-invasive stem cell tracking via near-infrared fluorescence and magnetic resonance imaging.

PubMed

Liu, Hong; Tan, Yan; Xie, Lisi; Yang, Lei; Zhao, Jing; Bai, Jingxuan; Huang, Ping; Zhan, Wugen; Wan, Qian; Zou, Chao; Han, Yali; Wang, Zhiyong

2016-09-15

Stem cells hold great promise for treating various diseases. However, one of the main drawbacks of stem cell therapy is the lack of non-invasive image-tracking technologies. Although magnetic resonance imaging (MRI) and near-infrared fluorescence (NIRF) imaging have been employed to analyse cellular and subcellular events via the assistance of contrast agents, the sensitivity and temporal resolution of MRI and the spatial resolution of NIRF are still shortcomings. In this study, superparamagnetic iron oxide nanocrystals and IR-780 dyes were co-encapsulated in stearic acid-modified polyethylenimine to form a dual-modality contrast agent with nano-size and positive charge. These resulting agents efficiently labelled stem cells and did not influence the cellular viability and differentiation. Moreover, the labelled cells showed the advantages of dual-modality imaging in vivo. Copyright © 2016 Elsevier Inc. All rights reserved.

NOTE: A positive contrast, tri-modality tissue marker for breast tumour localization

NASA Astrophysics Data System (ADS)

Li, Yangmei; Xiong Wang, Jian; Holloway, Claire; Plewes, Donald B.

2007-02-01

A new interstitial breast localization marker is proposed which exhibits positive contrast in T1-weighted MRI, ultrasound and x-ray mammography. Unlike previous markers which provide MRI contrast on the basis of a susceptibility-induced signal void, this marker provides a clear positive contrast without any loss of signal or spatial distortion. The marker is composed of 400 µm diameter copper microspheres suspended in a Gd-DTPA-doped gel matrix. Optimal contrast in T1-weighted spoiled gradient recalled MRI was found to occur with the addition of 10 mM Gd-DTPA. Ultrasound contrast was generated on the basis of scattering from the copper microspheres. X-ray contrast was provided by the high x-ray attenuation properties of the copper microspheres. The study demonstrates potential suitability of the marker for use as a breast localization marker based on ex vivo studies of chicken breast.

Efficient brain lesion segmentation using multi-modality tissue-based feature selection and support vector machines.

PubMed

Fiot, Jean-Baptiste; Cohen, Laurent D; Raniga, Parnesh; Fripp, Jurgen

2013-09-01

Support vector machines (SVM) are machine learning techniques that have been used for segmentation and classification of medical images, including segmentation of white matter hyper-intensities (WMH). Current approaches using SVM for WMH segmentation extract features from the brain and classify these followed by complex post-processing steps to remove false positives. The method presented in this paper combines advanced pre-processing, tissue-based feature selection and SVM classification to obtain efficient and accurate WMH segmentation. Features from 125 patients, generated from up to four MR modalities [T1-w, T2-w, proton-density and fluid attenuated inversion recovery(FLAIR)], differing neighbourhood sizes and the use of multi-scale features were compared. We found that although using all four modalities gave the best overall classification (average Dice scores of 0.54  ±  0.12, 0.72  ±  0.06 and 0.82  ±  0.06 respectively for small, moderate and severe lesion loads); this was not significantly different (p = 0.50) from using just T1-w and FLAIR sequences (Dice scores of 0.52  ±  0.13, 0.71  ±  0.08 and 0.81  ±  0.07). Furthermore, there was a negligible difference between using 5 × 5 × 5 and 3 × 3 × 3 features (p = 0.93). Finally, we show that careful consideration of features and pre-processing techniques not only saves storage space and computation time but also leads to more efficient classification, which outperforms the one based on all features with post-processing. Copyright © 2013 John Wiley & Sons, Ltd.

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.

A Stimulus-Independent Hybrid BCI Based on Motor Imagery and Somatosensory Attentional Orientation.

PubMed

Yao, Lin; Sheng, Xinjun; Zhang, Dingguo; Jiang, Ning; Mrachacz-Kersting, Natalie; Zhu, Xiangyang; Farina, Dario

2017-09-01

Distinctive EEG signals from the motor and somatosensory cortex are generated during mental tasks of motor imagery (MI) and somatosensory attentional orientation (SAO). In this paper, we hypothesize that a combination of these two signal modalities provides improvements in a brain-computer interface (BCI) performance with respect to using the two methods separately, and generate novel types of multi-class BCI systems. Thirty two subjects were randomly divided into a Control-Group and a Hybrid-Group. In the Control-Group, the subjects performed left and right hand motor imagery (i.e., L-MI and R-MI). In the Hybrid-Group, the subjects performed the four mental tasks (i.e., L-MI, R-MI, L-SAO, and R-SAO). The results indicate that combining two of the tasks in a hybrid manner (such as L-SAO and R-MI) resulted in a significantly greater classification accuracy than when using two MI tasks. The hybrid modality reached 86.1% classification accuracy on average, with a 7.70% increase with respect to MI ( ), and 7.21% to SAO ( ) alone. Moreover, all 16 subjects in the hybrid modality reached at least 70% accuracy, which is considered the threshold for BCI illiteracy. In addition to the two-class results, the classification accuracy was 68.1% and 54.1% for the three-class and four-class hybrid BCI. Combining the induced brain signals from motor and somatosensory cortex, the proposed stimulus-independent hybrid BCI has shown improved performance with respect to individual modalities, reducing the portion of BCI-illiterate subjects, and provided novel types of multi-class BCIs.

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.

Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

PubMed

Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

2017-04-01

Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Decision-Level Fusion of Spatially Scattered Multi-Modal Data for Nondestructive Inspection of Surface Defects

PubMed Central

Heideklang, René; Shokouhi, Parisa

2016-01-01

This article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique’s robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method is adequate. PMID:26784200

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.

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.

Improved estimation of random vibration loads in launch vehicles

NASA Technical Reports Server (NTRS)

Mehta, R.; Erwin, E.; Suryanarayan, S.; Krishna, Murali M. R.

1993-01-01

Random vibration induced load is an important component of the total design load environment for payload and launch vehicle components and their support structures. The current approach to random vibration load estimation is based, particularly at the preliminary design stage, on the use of Miles' equation which assumes a single degree-of-freedom (DOF) system and white noise excitation. This paper examines the implications of the use of multi-DOF system models and response calculation based on numerical integration using the actual excitation spectra for random vibration load estimation. The analytical study presented considers a two-DOF system and brings out the effects of modal mass, damping and frequency ratios on the random vibration load factor. The results indicate that load estimates based on the Miles' equation can be significantly different from the more accurate estimates based on multi-DOF models.

Reconstructing White Walls: Multi-View Multi-Shot 3d Reconstruction of Textureless Surfaces

NASA Astrophysics Data System (ADS)

Ley, Andreas; Hänsch, Ronny; Hellwich, Olaf

2016-06-01

The reconstruction of the 3D geometry of a scene based on image sequences has been a very active field of research for decades. Nevertheless, there are still existing challenges in particular for homogeneous parts of objects. This paper proposes a solution to enhance the 3D reconstruction of weakly-textured surfaces by using standard cameras as well as a standard multi-view stereo pipeline. The underlying idea of the proposed method is based on improving the signal-to-noise ratio in weakly-textured regions while adaptively amplifying the local contrast to make better use of the limited numerical range in 8-bit images. Based on this premise, multiple shots per viewpoint are used to suppress statistically uncorrelated noise and enhance low-contrast texture. By only changing the image acquisition and adding a preprocessing step, a tremendous increase of up to 300% in completeness of the 3D reconstruction is achieved.

A nanocomposite of Au-AgI core/shell dimer as a dual-modality contrast agent for x-ray computed tomography and photoacoustic imaging

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

Orza, Anamaria; Wu, Hui; Li, Yuancheng

Purpose: To develop a core/shell nanodimer of gold (core) and silver iodine (shell) as a dual-modal contrast-enhancing agent for biomarker targeted x-ray computed tomography (CT) and photoacoustic imaging (PAI) applications. Methods: The gold and silver iodine core/shell nanodimer (Au/AgICSD) was prepared by fusing together components of gold, silver, and iodine. The physicochemical properties of Au/AgICSD were then characterized using different optical and imaging techniques (e.g., HR- transmission electron microscope, scanning transmission electron microscope, x-ray photoelectron spectroscopy, energy-dispersive x-ray spectroscopy, Z-potential, and UV-vis). The CT and PAI contrast-enhancing effects were tested and then compared with a clinically used CT contrast agentmore » and Au nanoparticles. To confer biocompatibility and the capability for efficient biomarker targeting, the surface of the Au/AgICSD nanodimer was modified with the amphiphilic diblock polymer and then functionalized with transferrin for targeting transferrin receptor that is overexpressed in various cancer cells. Cytotoxicity of the prepared Au/AgICSD nanodimer was also tested with both normal and cancer cell lines. Results: The characterizations of prepared Au/AgI core/shell nanostructure confirmed the formation of Au/AgICSD nanodimers. Au/AgICSD nanodimer is stable in physiological conditions for in vivo applications. Au/AgICSD nanodimer exhibited higher contrast enhancement in both CT and PAI for dual-modality imaging. Moreover, transferrin functionalized Au/AgICSD nanodimer showed specific binding to the tumor cells that have a high level of expression of the transferrin receptor. Conclusions: The developed Au/AgICSD nanodimer can be used as a potential biomarker targeted dual-modal contrast agent for both or combined CT and PAI molecular imaging.« less

MMX-I: A data-processing software for multi-modal X-ray imaging and tomography

NASA Astrophysics Data System (ADS)

Bergamaschi, A.; Medjoubi, K.; Messaoudi, C.; Marco, S.; Somogyi, A.

2017-06-01

Scanning hard X-ray imaging allows simultaneous acquisition of multimodal information, including X-ray fluorescence, absorption, phase and dark-field contrasts, providing structural and chemical details of the samples. Combining these scanning techniques with the infrastructure developed for fast data acquisition at Synchrotron Soleil permits to perform multimodal imaging and tomography during routine user experiments at the Nanoscopium beamline. A main challenge of such imaging techniques is the online processing and analysis of the generated very large volume (several hundreds of Giga Bytes) multimodal data-sets. This is especially important for the wide user community foreseen at the user oriented Nanoscopium beamline (e.g. from the fields of Biology, Life Sciences, Geology, Geobiology), having no experience in such data-handling. MMX-I is a new multi-platform open-source freeware for the processing and reconstruction of scanning multi-technique X-ray imaging and tomographic datasets. The MMX-I project aims to offer, both expert users and beginners, the possibility of processing and analysing raw data, either on-site or off-site. Therefore we have developed a multi-platform (Mac, Windows and Linux 64bit) data processing tool, which is easy to install, comprehensive, intuitive, extendable and user-friendly. MMX-I is now routinely used by the Nanoscopium user community and has demonstrated its performance in treating big data.

Three-dimensional multi bioluminescent sources reconstruction based on adaptive finite element method

NASA Astrophysics Data System (ADS)

Ma, Xibo; Tian, Jie; Zhang, Bo; Zhang, Xing; Xue, Zhenwen; Dong, Di; Han, Dong

2011-03-01

Among many optical molecular imaging modalities, bioluminescence imaging (BLI) has more and more wide application in tumor detection and evaluation of pharmacodynamics, toxicity, pharmacokinetics because of its noninvasive molecular and cellular level detection ability, high sensitivity and low cost in comparison with other imaging technologies. However, BLI can not present the accurate location and intensity of the inner bioluminescence sources such as in the bone, liver or lung etc. Bioluminescent tomography (BLT) shows its advantage in determining the bioluminescence source distribution inside a small animal or phantom. Considering the deficiency of two-dimensional imaging modality, we developed three-dimensional tomography to reconstruct the information of the bioluminescence source distribution in transgenic mOC-Luc mice bone with the boundary measured data. In this paper, to study the osteocalcin (OC) accumulation in transgenic mOC-Luc mice bone, a BLT reconstruction method based on multilevel adaptive finite element (FEM) algorithm was used for localizing and quantifying multi bioluminescence sources. Optical and anatomical information of the tissues are incorporated as a priori knowledge in this method, which can reduce the ill-posedness of BLT. The data was acquired by the dual modality BLT and Micro CT prototype system that was developed by us. Through temperature control and absolute intensity calibration, a relative accurate intensity can be calculated. The location of the OC accumulation was reconstructed, which was coherent with the principle of bone differentiation. This result also was testified by ex vivo experiment in the black 96-plate well using the BLI system and the chemiluminescence apparatus.

Secure fingerprint identification based on structural and microangiographic optical coherence tomography.

PubMed

Liu, Xuan; Zaki, Farzana; Wang, Yahui; Huang, Qiongdan; Mei, Xin; Wang, Jiangjun

2017-03-10

Optical coherence tomography (OCT) allows noncontact acquisition of fingerprints and hence is a highly promising technology in the field of biometrics. OCT can be used to acquire both structural and microangiographic images of fingerprints. Microangiographic OCT derives its contrast from the blood flow in the vasculature of viable skin tissue, and microangiographic fingerprint imaging is inherently immune to fake fingerprint attack. Therefore, dual-modality (structural and microangiographic) OCT imaging of fingerprints will enable more secure acquisition of biometric data, which has not been investigated before. Our study on fingerprint identification based on structural and microangiographic OCT imaging is, we believe, highly innovative. In this study, we performed OCT imaging study for fingerprint acquisition, and demonstrated the capability of dual-modality OCT imaging for the identification of fake fingerprints.

Bayesian Inference on the Radio-quietness of Gamma-ray Pulsars

NASA Astrophysics Data System (ADS)

Yu, Hoi-Fung; Hui, Chung Yue; Kong, Albert K. H.; Takata, Jumpei

2018-04-01

For the first time we demonstrate using a robust Bayesian approach to analyze the populations of radio-quiet (RQ) and radio-loud (RL) gamma-ray pulsars. We quantify their differences and obtain their distributions of the radio-cone opening half-angle δ and the magnetic inclination angle α by Bayesian inference. In contrast to the conventional frequentist point estimations that might be non-representative when the distribution is highly skewed or multi-modal, which is often the case when data points are scarce, Bayesian statistics displays the complete posterior distribution that the uncertainties can be readily obtained regardless of the skewness and modality. We found that the spin period, the magnetic field strength at the light cylinder, the spin-down power, the gamma-ray-to-X-ray flux ratio, and the spectral curvature significance of the two groups of pulsars exhibit significant differences at the 99% level. Using Bayesian inference, we are able to infer the values and uncertainties of δ and α from the distribution of RQ and RL pulsars. We found that δ is between 10° and 35° and the distribution of α is skewed toward large values.

Core/shell Fe3O4/Gd2O3 nanocubes as T1-T2 dual modal MRI contrast agents

NASA Astrophysics Data System (ADS)

Li, Fenfen; Zhi, Debo; Luo, Yufeng; Zhang, Jiqian; Nan, Xiang; Zhang, Yunjiao; Zhou, Wei; Qiu, Bensheng; Wen, Longping; Liang, Gaolin

2016-06-01

T1-T2 dual modal magnetic resonance imaging (MRI) has attracted considerable interest because it offers complementary diagnostic information, leading to more precise diagnosis. To date, a number of nanostructures have been reported as T1-T2 dual modal MR contrast agents (CAs). However, hybrids of nanocubes with both iron and gadolinium (Gd) elements as T1-T2 dual modal CAs have not been reported. Herein, we report the synthesis of novel core/shell Fe3O4/Gd2O3 nanocubes as T1-T2 dual-modal CAs and their application for enhanced T1-T2 MR imaging of rat livers. A relaxivity study at 1.5 T indicated that our Fe3O4/Gd2O3 nanocubes have an r1 value of 45.24 mM-1 s-1 and an r2 value of 186.51 mM-1 s-1, which were about two folds of those of Gd2O3 nanoparticles and Fe3O4 nanocubes, respectively. In vivo MR imaging of rats showed both T1-positive and T2-negative contrast enhancements in the livers. We envision that our Fe3O4/Gd2O3 nanocubes could be applied as T1-T2 dual modal MR CAs for a wide range of theranostic applications in the near future.T1-T2 dual modal magnetic resonance imaging (MRI) has attracted considerable interest because it offers complementary diagnostic information, leading to more precise diagnosis. To date, a number of nanostructures have been reported as T1-T2 dual modal MR contrast agents (CAs). However, hybrids of nanocubes with both iron and gadolinium (Gd) elements as T1-T2 dual modal CAs have not been reported. Herein, we report the synthesis of novel core/shell Fe3O4/Gd2O3 nanocubes as T1-T2 dual-modal CAs and their application for enhanced T1-T2 MR imaging of rat livers. A relaxivity study at 1.5 T indicated that our Fe3O4/Gd2O3 nanocubes have an r1 value of 45.24 mM-1 s-1 and an r2 value of 186.51 mM-1 s-1, which were about two folds of those of Gd2O3 nanoparticles and Fe3O4 nanocubes, respectively. In vivo MR imaging of rats showed both T1-positive and T2-negative contrast enhancements in the livers. We envision that our Fe3O4/Gd2O3 nanocubes could be applied as T1-T2 dual modal MR CAs for a wide range of theranostic applications in the near future. Electronic supplementary information (ESI) available: Scheme S1, Fig. S1-S8, and Tables S1, S2. See DOI: 10.1039/c6nr02620f

Interventional multispectral photoacoustic imaging with a clinical linear array ultrasound probe for guiding nerve blocks

NASA Astrophysics Data System (ADS)

Xia, Wenfeng; West, Simeon J.; Nikitichev, Daniil I.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

2016-03-01

Accurate identification of tissue structures such as nerves and blood vessels is critically important for interventional procedures such as nerve blocks. Ultrasound imaging is widely used as a guidance modality to visualize anatomical structures in real-time. However, identification of nerves and small blood vessels can be very challenging, and accidental intra-neural or intra-vascular injections can result in significant complications. Multi-spectral photoacoustic imaging can provide high sensitivity and specificity for discriminating hemoglobin- and lipid-rich tissues. However, conventional surface-illumination-based photoacoustic systems suffer from limited sensitivity at large depths. In this study, for the first time, an interventional multispectral photoacoustic imaging (IMPA) system was used to image nerves in a swine model in vivo. Pulsed excitation light with wavelengths in the ranges of 750 - 900 nm and 1150 - 1300 nm was delivered inside the body through an optical fiber positioned within the cannula of an injection needle. Ultrasound waves were received at the tissue surface using a clinical linear array imaging probe. Co-registered B-mode ultrasound images were acquired using the same imaging probe. Nerve identification was performed using a combination of B-mode ultrasound imaging and electrical stimulation. Using a linear model, spectral-unmixing of the photoacoustic data was performed to provide image contrast for oxygenated and de-oxygenated hemoglobin, water and lipids. Good correspondence between a known nerve location and a lipid-rich region in the photoacoustic images was observed. The results indicate that IMPA is a promising modality for guiding nerve blocks and other interventional procedures. Challenges involved with clinical translation are discussed.

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.

Optical mesoscopy without the scatter: broadband multispectral optoacoustic mesoscopy

PubMed Central

Chekkoury, Andrei; Gateau, Jérôme; Driessen, Wouter; Symvoulidis, Panagiotis; Bézière, Nicolas; Feuchtinger, Annette; Walch, Axel; Ntziachristos, Vasilis

2015-01-01

Optical mesoscopy extends the capabilities of biological visualization beyond the limited penetration depth achieved by microscopy. However, imaging of opaque organisms or tissues larger than a few hundred micrometers requires invasive tissue sectioning or chemical treatment of the specimen for clearing photon scattering, an invasive process that is regardless limited with depth. We developed previously unreported broadband optoacoustic mesoscopy as a tomographic modality to enable imaging of optical contrast through several millimeters of tissue, without the need for chemical treatment of tissues. We show that the unique combination of three-dimensional projections over a broad 500 kHz–40 MHz frequency range combined with multi-wavelength illumination is necessary to render broadband multispectral optoacoustic mesoscopy (2B-MSOM) superior to previous optical or optoacoustic mesoscopy implementations. PMID:26417486

A Module-Based Approach to Foster and Document the Intercultural Process before and during the Residence Abroad

ERIC Educational Resources Information Center

Penman, C.; Ratz, S.

2015-01-01

This article contributes to the debate on what form of preparation and support can enhance the intercultural student experience during a Year Abroad. It presents a credit-bearing and multi-modal module at a UK university designed to both prepare students prior to departure through a series of workshops and activities on an e-portfolio and help…

Beyond Attendance: A Multi-Modal Understanding of Arts Participation. Based on the 2008 Survey of Public Participation in the Arts. Research Report #54

ERIC Educational Resources Information Center

Novak-Leonard, Jennifer L.; Brown, Alan S.

2011-01-01

First conducted in 1982, the National Endowment for the Arts' (NEA's) Survey of Public Participation in the Arts (SPPA) serves as the longest-standing resource for studying U.S. adult levels of arts attendance, personal arts creation and performance, and arts participation through electronic media. The environment in which arts organizations…

Unexpected Self-Expression and the Limits of Narrative Inquiry: Exploring Unconscious Dynamics in a Community-Based Digital Storytelling Workshop

ERIC Educational Resources Information Center

Brushwood Rose, Chloe; Granger, Colette A.

2013-01-01

This study explores the tension between self-knowledge and self-expression, and how it manifests in the processes of storytelling that unfold in digital storytelling workshops offered to new immigrant women living in Toronto, Canada. Both in their multi-modal complexity and in the significant shifts from their original telling, the digital stories…

Relational Reasoning about Numbers and Operations--Foundation for Calculation Strategy Use in Multi-Digit Multiplication and Division

ERIC Educational Resources Information Center

Schulz, Andreas

2018-01-01

Theoretical analysis of whole number-based calculation strategies and digit-based algorithms for multi-digit multiplication and division reveals that strategy use includes two kinds of reasoning: reasoning about the relations between numbers and reasoning about the relations between operations. In contrast, algorithms aim to reduce the necessary…

The role of tactile sensation in online and offline hierarchical control of multi-finger force synergy.

PubMed

Koh, Kyung; Kwon, Hyun Joon; Yoon, Bum Chul; Cho, Yongseok; Shin, Joon-Ho; Hahn, Jin-Oh; Miller, Ross H; Kim, Yoon Hyuk; Shim, Jae Kun

2015-09-01

The hand, one of the most versatile but mechanically redundant parts of the human body, must overcome imperfect motor commands and inherent noise in both the sensory and motor systems in order to produce desired motor actions. For example, it is nearly impossible to produce a perfectly consistent note during a single violin stroke or to produce the exact same note over multiple strokes, which we denote online and offline control, respectively. To overcome these challenges, the central nervous system synergistically integrates multiple sensory modalities and coordinates multiple motor effectors. Among these sensory modalities, tactile sensation plays an important role in manual motor tasks by providing hand-object contact information. The purpose of this study was to investigate the role of tactile feedback in individual finger actions and multi-finger interactions during constant force production tasks. We developed analytical techniques for the linear decomposition of the overall variance in the motor system in both online and offline control. We removed tactile feedback from the fingers and demonstrated that tactile sensors played a critical role in the online control of synergistic interactions between fingers. In contrast, the same sensors did not contribute to offline control. We also demonstrated that when tactile feedback was removed from the fingers, the combined motor output of individual fingers did not change while individual finger behaviors did. This finding supports the idea of hierarchical control where individual fingers at the lower level work together to stabilize the performance of combined motor output at the higher level.

Aging and Emotion Recognition: Not Just a Losing Matter

PubMed Central

Sze, Jocelyn A.; Goodkind, Madeleine S.; Gyurak, Anett; Levenson, Robert W.

2013-01-01

Past studies on emotion recognition and aging have found evidence of age-related decline when emotion recognition was assessed by having participants detect single emotions depicted in static images of full or partial (e.g., eye region) faces. These tests afford good experimental control but do not capture the dynamic nature of real-world emotion recognition, which is often characterized by continuous emotional judgments and dynamic multi-modal stimuli. Research suggests that older adults often perform better under conditions that better mimic real-world social contexts. We assessed emotion recognition in young, middle-aged, and older adults using two traditional methods (single emotion judgments of static images of faces and eyes) and an additional method in which participants made continuous emotion judgments of dynamic, multi-modal stimuli (videotaped interactions between young, middle-aged, and older couples). Results revealed an age by test interaction. Largely consistent with prior research, we found some evidence that older adults performed worse than young adults when judging single emotions from images of faces (for sad and disgust faces only) and eyes (for older eyes only), with middle-aged adults falling in between. In contrast, older adults did better than young adults on the test involving continuous emotion judgments of dyadic interactions, with middle-aged adults falling in between. In tests in which target stimuli differed in age, emotion recognition was not facilitated by an age match between participant and target. These findings are discussed in terms of theoretical and methodological implications for the study of aging and emotional processing. PMID:22823183

Observation, Identification, and Impact of Multi-Modal Plasma Responses to Applied Magnetic Perturbations

NASA Astrophysics Data System (ADS)

Logan, Nikolas

2015-11-01

Experiments on DIII-D have demonstrated that multiple kink modes with comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n=2, in good agreement with ideal MHD models. In contrast to a single-mode model, the structure of the response measured using poloidally distributed magnetic sensors changes when varying the applied poloidal spectrum. This is most readily evident in that different spectra of applied fields can independently excite inboard and outboard magnetic responses, which are identified as distinct plasma modes by IPEC modeling. The outboard magnetic response is correlated with the plasma pressure and consistent with the long wavelength perturbations of the least stable, pressure driven kinks calculated by DCON and used in IPEC. The models show the structure of the pressure driven modes extends throughout the bad curvature region and into the plasma core. The inboard plasma response is correlated with the edge current profile and requires the inclusion of multiple kink modes with greater stability, including opposite helicity modes, to replicate the experimental observations in the models. IPEC reveals the resulting mode structure to be highly localized in the plasma edge. Scans of the applied spectrum show this response induces the transport that influences the density pump-out, as well as the toroidal rotation drag observed in experiment and modeled using PENT. The classification of these two mode types establishes a new multi-modal paradigm for n=2 plasma response and guides the understanding needed to optimize 3D fields for independent control of stability and transport. Supported by US DOE contract DE-AC02-09CH11466.

Classifying magnetic resonance image modalities with convolutional neural networks

NASA Astrophysics Data System (ADS)

Remedios, Samuel; Pham, Dzung L.; Butman, John A.; Roy, Snehashis

2018-02-01

Magnetic Resonance (MR) imaging allows the acquisition of images with different contrast properties depending on the acquisition protocol and the magnetic properties of tissues. Many MR brain image processing techniques, such as tissue segmentation, require multiple MR contrasts as inputs, and each contrast is treated differently. Thus it is advantageous to automate the identification of image contrasts for various purposes, such as facilitating image processing pipelines, and managing and maintaining large databases via content-based image retrieval (CBIR). Most automated CBIR techniques focus on a two-step process: extracting features from data and classifying the image based on these features. We present a novel 3D deep convolutional neural network (CNN)- based method for MR image contrast classification. The proposed CNN automatically identifies the MR contrast of an input brain image volume. Specifically, we explored three classification problems: (1) identify T1-weighted (T1-w), T2-weighted (T2-w), and fluid-attenuated inversion recovery (FLAIR) contrasts, (2) identify pre vs postcontrast T1, (3) identify pre vs post-contrast FLAIR. A total of 3418 image volumes acquired from multiple sites and multiple scanners were used. To evaluate each task, the proposed model was trained on 2137 images and tested on the remaining 1281 images. Results showed that image volumes were correctly classified with 97.57% accuracy.

Cross-modal Association between Auditory and Visuospatial Information in Mandarin Tone Perception in Noise by Native and Non-native Perceivers.

PubMed

Hannah, Beverly; Wang, Yue; Jongman, Allard; Sereno, Joan A; Cao, Jiguo; Nie, Yunlong

2017-01-01

Speech perception involves multiple input modalities. Research has indicated that perceivers establish cross-modal associations between auditory and visuospatial events to aid perception. Such intermodal relations can be particularly beneficial for speech development and learning, where infants and non-native perceivers need additional resources to acquire and process new sounds. This study examines how facial articulatory cues and co-speech hand gestures mimicking pitch contours in space affect non-native Mandarin tone perception. Native English as well as Mandarin perceivers identified tones embedded in noise with either congruent or incongruent Auditory-Facial (AF) and Auditory-FacialGestural (AFG) inputs. Native Mandarin results showed the expected ceiling-level performance in the congruent AF and AFG conditions. In the incongruent conditions, while AF identification was primarily auditory-based, AFG identification was partially based on gestures, demonstrating the use of gestures as valid cues in tone identification. The English perceivers' performance was poor in the congruent AF condition, but improved significantly in AFG. While the incongruent AF identification showed some reliance on facial information, incongruent AFG identification relied more on gestural than auditory-facial information. These results indicate positive effects of facial and especially gestural input on non-native tone perception, suggesting that cross-modal (visuospatial) resources can be recruited to aid auditory perception when phonetic demands are high. The current findings may inform patterns of tone acquisition and development, suggesting how multi-modal speech enhancement principles may be applied to facilitate speech learning.

Cross-modal Association between Auditory and Visuospatial Information in Mandarin Tone Perception in Noise by Native and Non-native Perceivers

PubMed Central

Hannah, Beverly; Wang, Yue; Jongman, Allard; Sereno, Joan A.; Cao, Jiguo; Nie, Yunlong

2017-01-01

Speech perception involves multiple input modalities. Research has indicated that perceivers establish cross-modal associations between auditory and visuospatial events to aid perception. Such intermodal relations can be particularly beneficial for speech development and learning, where infants and non-native perceivers need additional resources to acquire and process new sounds. This study examines how facial articulatory cues and co-speech hand gestures mimicking pitch contours in space affect non-native Mandarin tone perception. Native English as well as Mandarin perceivers identified tones embedded in noise with either congruent or incongruent Auditory-Facial (AF) and Auditory-FacialGestural (AFG) inputs. Native Mandarin results showed the expected ceiling-level performance in the congruent AF and AFG conditions. In the incongruent conditions, while AF identification was primarily auditory-based, AFG identification was partially based on gestures, demonstrating the use of gestures as valid cues in tone identification. The English perceivers’ performance was poor in the congruent AF condition, but improved significantly in AFG. While the incongruent AF identification showed some reliance on facial information, incongruent AFG identification relied more on gestural than auditory-facial information. These results indicate positive effects of facial and especially gestural input on non-native tone perception, suggesting that cross-modal (visuospatial) resources can be recruited to aid auditory perception when phonetic demands are high. The current findings may inform patterns of tone acquisition and development, suggesting how multi-modal speech enhancement principles may be applied to facilitate speech learning. PMID:29255435

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.

Real-time photoacoustic and ultrasound dual-modality imaging system facilitated with graphics processing unit and code parallel optimization.

PubMed

Yuan, Jie; Xu, Guan; Yu, Yao; Zhou, Yu; Carson, Paul L; Wang, Xueding; Liu, Xiaojun

2013-08-01

Photoacoustic tomography (PAT) offers structural and functional imaging of living biological tissue with highly sensitive optical absorption contrast and excellent spatial resolution comparable to medical ultrasound (US) imaging. We report the development of a fully integrated PAT and US dual-modality imaging system, which performs signal scanning, image reconstruction, and display for both photoacoustic (PA) and US imaging all in a truly real-time manner. The back-projection (BP) algorithm for PA image reconstruction is optimized to reduce the computational cost and facilitate parallel computation on a state of the art graphics processing unit (GPU) card. For the first time, PAT and US imaging of the same object can be conducted simultaneously and continuously, at a real-time frame rate, presently limited by the laser repetition rate of 10 Hz. Noninvasive PAT and US imaging of human peripheral joints in vivo were achieved, demonstrating the satisfactory image quality realized with this system. Another experiment, simultaneous PAT and US imaging of contrast agent flowing through an artificial vessel, was conducted to verify the performance of this system for imaging fast biological events. The GPU-based image reconstruction software code for this dual-modality system is open source and available for download from http://sourceforge.net/projects/patrealtime.

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

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.

MRMC analysis of agreement studies

NASA Astrophysics Data System (ADS)

Gallas, Brandon D.; Anam, Amrita; Chen, Weijie; Wunderlich, Adam; Zhang, Zhiwei

2016-03-01

The purpose of this work is to present and evaluate methods based on U-statistics to compare intra- or inter-reader agreement across different imaging modalities. We apply these methods to multi-reader multi-case (MRMC) studies. We measure reader-averaged agreement and estimate its variance accounting for the variability from readers and cases (an MRMC analysis). In our application, pathologists (readers) evaluate patient tissue mounted on glass slides (cases) in two ways. They evaluate the slides on a microscope (reference modality) and they evaluate digital scans of the slides on a computer display (new modality). In the current work, we consider concordance as the agreement measure, but many of the concepts outlined here apply to other agreement measures. Concordance is the probability that two readers rank two cases in the same order. Concordance can be estimated with a U-statistic and thus it has some nice properties: it is unbiased, asymptotically normal, and its variance is given by an explicit formula. Another property of a U-statistic is that it is symmetric in its inputs; it doesn't matter which reader is listed first or which case is listed first, the result is the same. Using this property and a few tricks while building the U-statistic kernel for concordance, we get a mathematically tractable problem and efficient software. Simulations show that our variance and covariance estimates are unbiased.

DeepFruits: A Fruit Detection System Using Deep Neural Networks

PubMed Central

Sa, Inkyu; Ge, Zongyuan; Dayoub, Feras; Upcroft, Ben; Perez, Tristan; McCool, Chris

2016-01-01

This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it is a key element for fruit yield estimation and automated harvesting. Recent work in deep neural networks has led to the development of a state-of-the-art object detector termed Faster Region-based CNN (Faster R-CNN). We adapt this model, through transfer learning, for the task of fruit detection using imagery obtained from two modalities: colour (RGB) and Near-Infrared (NIR). Early and late fusion methods are explored for combining the multi-modal (RGB and NIR) information. This leads to a novel multi-modal Faster R-CNN model, which achieves state-of-the-art results compared to prior work with the F1 score, which takes into account both precision and recall performances improving from 0.807 to 0.838 for the detection of sweet pepper. In addition to improved accuracy, this approach is also much quicker to deploy for new fruits, as it requires bounding box annotation rather than pixel-level annotation (annotating bounding boxes is approximately an order of magnitude quicker to perform). The model is retrained to perform the detection of seven fruits, with the entire process taking four hours to annotate and train the new model per fruit. PMID:27527168

DeepFruits: A Fruit Detection System Using Deep Neural Networks.

PubMed

Sa, Inkyu; Ge, Zongyuan; Dayoub, Feras; Upcroft, Ben; Perez, Tristan; McCool, Chris

2016-08-03

This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable fruit detection system, which is a vital element of an autonomous agricultural robotic platform; it is a key element for fruit yield estimation and automated harvesting. Recent work in deep neural networks has led to the development of a state-of-the-art object detector termed Faster Region-based CNN (Faster R-CNN). We adapt this model, through transfer learning, for the task of fruit detection using imagery obtained from two modalities: colour (RGB) and Near-Infrared (NIR). Early and late fusion methods are explored for combining the multi-modal (RGB and NIR) information. This leads to a novel multi-modal Faster R-CNN model, which achieves state-of-the-art results compared to prior work with the F1 score, which takes into account both precision and recall performances improving from 0 . 807 to 0 . 838 for the detection of sweet pepper. In addition to improved accuracy, this approach is also much quicker to deploy for new fruits, as it requires bounding box annotation rather than pixel-level annotation (annotating bounding boxes is approximately an order of magnitude quicker to perform). The model is retrained to perform the detection of seven fruits, with the entire process taking four hours to annotate and train the new model per fruit.

Nanoparticles for cancer imaging: The good, the bad, and the promise

PubMed Central

Chapman, Sandra; Dobrovolskaia, Marina; Farahani, Keyvan; Goodwin, Andrew; Joshi, Amit; Lee, Hakho; Meade, Thomas; Pomper, Martin; Ptak, Krzysztof; Rao, Jianghong; Singh, Ravi; Sridhar, Srinivas; Stern, Stephan; Wang, Andrew; Weaver, John B.; Woloschak, Gayle; Yang, Lily

2014-01-01

Summary Recent advances in molecular imaging and nanotechnology are providing new opportunities for biomedical imaging with great promise for the development of novel imaging agents. The unique optical, magnetic, and chemical properties of materials at the scale of nanometers allow the creation of imaging probes with better contrast enhancement, increased sensitivity, controlled biodistribution, better spatial and temporal information, multi-functionality and multi-modal imaging across MRI, PET, SPECT, and ultrasound. These features could ultimately translate to clinical advantages such as earlier detection, real time assessment of disease progression and personalized medicine. However, several years of investigation into the application of these materials to cancer research has revealed challenges that have delayed the successful application of these agents to the field of biomedical imaging. Understanding these challenges is critical to take full advantage of the benefits offered by nano-sized imaging agents. Therefore, this article presents the lessons learned and challenges encountered by a group of leading researchers in this field, and suggests ways forward to develop nanoparticle probes for cancer imaging. Published by Elsevier Ltd. PMID:25419228

Design and implementation of a novel modal space active force control concept for spatial multi-DOF parallel robotic manipulators actuated by electrical actuators.

PubMed

Yang, Chifu; Zhao, Jinsong; Li, Liyi; Agrawal, Sunil K

2018-01-01

Robotic spine brace based on parallel-actuated robotic system is a new device for treatment and sensing of scoliosis, however, the strong dynamic coupling and anisotropy problem of parallel manipulators result in accuracy loss of rehabilitation force control, including big error in direction and value of force. A novel active force control strategy named modal space force control is proposed to solve these problems. Considering the electrical driven system and contact environment, the mathematical model of spatial parallel manipulator is built. The strong dynamic coupling problem in force field is described via experiments as well as the anisotropy problem of work space of parallel manipulators. The effects of dynamic coupling on control design and performances are discussed, and the influences of anisotropy on accuracy are also addressed. With mass/inertia matrix and stiffness matrix of parallel manipulators, a modal matrix can be calculated by using eigenvalue decomposition. Making use of the orthogonality of modal matrix with mass matrix of parallel manipulators, the strong coupled dynamic equations expressed in work space or joint space of parallel manipulator may be transformed into decoupled equations formulated in modal space. According to this property, each force control channel is independent of others in the modal space, thus we proposed modal space force control concept which means the force controller is designed in modal space. A modal space active force control is designed and implemented with only a simple PID controller employed as exampled control method to show the differences, uniqueness, and benefits of modal space force control. Simulation and experimental results show that the proposed modal space force control concept can effectively overcome the effects of the strong dynamic coupling and anisotropy problem in the physical space, and modal space force control is thus a very useful control framework, which is better than the current joint space control and work space control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Stochastic HKMDHE: A multi-objective contrast enhancement algorithm

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Mukhopadhyay, Sabyasachi; Maity, Srideep; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2018-02-01

This contribution proposes a novel extension of the existing `Hyper Kurtosis based Modified Duo-Histogram Equalization' (HKMDHE) algorithm, for multi-objective contrast enhancement of biomedical images. A novel modified objective function has been formulated by joint optimization of the individual histogram equalization objectives. The optimal adequacy of the proposed methodology with respect to image quality metrics such as brightness preserving abilities, peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSIM) and universal image quality metric has been experimentally validated. The performance analysis of the proposed Stochastic HKMDHE with existing histogram equalization methodologies like Global Histogram Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) has been given for comparative evaluation.

Development and Evaluation of New Algorithms for the Retrieval of Wind and Internal Wave Parameters from Shipborne Marine Radar Data

DTIC Science & Technology

2012-12-01

traditional buoy measurements , which are based on the analysis of the buoy motion using accelerometer and tilt sensors, is the capacity to detect multi-modal...the radar- based estimates slightly overestimate the measured data. Fig. 6.33 shows a time series of p-p-distances and corresponding water depths as...32 3.5 Time series of wind speed and direction measurements from ship anemome- ters 1 and 2 from

Contrast-enhanced [18F] fluorodeoxyglucose-positron emission tomography-computed tomography as an initial imaging modality in patients presenting with metastatic malignancy of undefined primary origin.

PubMed

Jain, Avani; Srivastava, Madhur Kumar; Pawaskar, Alok Suresh; Shelley, Simon; Elangovan, Indirani; Jain, Hasmukh; Pandey, Somnath; Kalal, Shilpa; Amalachandran, Jaykanth

2015-01-01

To evaluate the advantages of contrast enhanced F-18-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-contrast enhanced CT [CECT]) when used as an initial imaging modality in patients presenting with metastatic malignancy of undefined primary origin (MUO). A total of 243 patients with fine needle aspiration cytology/biopsy proven MUO were included in this prospective study. Patients who were thoroughly evaluated for primary or primary tumor was detected by any other investigation were excluded from the analysis. Totally, 163 patients with pathological diagnosis of malignancy but no apparent sites of the primary tumor were finally selected for analysis. The site of probable primary malignancy suggested by PET-CECT was confirmed by biopsy/follow-up. PET-CECT suggested probable site of primary in 128/163 (78.52%) patients. In 30/35 remaining patients, primary tumor was not detected even after extensive work-up. In 5 patients, where PET-CECT was negative, primary was found on further extensive investigations or follow-up. The sensitivity, specificity, positive predictive value and negative predictive value of the study were 95.76%, 66.67%, 88.28% and 85.71% respectively. F-18 FDG PET-CECT aptly serves the purpose of initial imaging modality owing to high sensitivity, negative and positive predictive value. PET-CECT not only surveys the whole body for the primary malignancy but also stages the disease accurately. Use of contrast improves the diagnostic utility of modality as well as help in staging of the primary tumor. Although benefits of using PET-CECT as initial diagnostic modality are obvious from this study, there is a need for a larger study comparing conventional methods for diagnosing primary in patients with MUO versus PET-CECT.

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…

Flow Cytometry with Gold Nanoparticles and their Clusters as scattering Contrast Agents: FDTD Simulation of Light-Cell Interaction

PubMed Central

Tanev, Stoyan; Sun, Wenbo; Pond, James; Tuchin, Valery V.; Zharov, Vladimir P.

2010-01-01

The formulation of the Finite-Difference Time-Domain (FDTD) approach is presented in the framework of its potential applications to in vivo flow cytometry based on light scattering. The consideration is focused on comparison of light scattering by a single biological cell alone in controlled refractive index matching conditions and by cells labeled by gold nanoparticles. The optical schematics including phase contrast (OPCM) microscopy as a prospective modality for in vivo flow cytometry is also analyzed. The validation of the FDTD approach for the simulation of flow cytometry may open a new avenue in the development of advanced cytometric techniques based on scattering effects from nanoscale targets. PMID:19670359

Molecular Imaging: Current Status and Emerging Strategies

PubMed Central

Pysz, Marybeth A.; Gambhir, Sanjiv S.; Willmann, Jürgen K.

2011-01-01

In vivo molecular imaging has a great potential to impact medicine by detecting diseases in early stages (screening), identifying extent of disease, selecting disease- and patient-specific therapeutic treatment (personalized medicine), applying a directed or targeted therapy, and measuring molecular-specific effects of treatment. Current clinical molecular imaging approaches primarily use PET- or SPECT-based techniques. In ongoing preclinical research novel molecular targets of different diseases are identified and, sophisticated and multifunctional contrast agents for imaging these molecular targets are developed along with new technologies and instrumentation for multimodality molecular imaging. Contrast-enhanced molecular ultrasound with molecularly-targeted contrast microbubbles is explored as a clinically translatable molecular imaging strategy for screening, diagnosing, and monitoring diseases at the molecular level. Optical imaging with fluorescent molecular probes and ultrasound imaging with molecularly-targeted microbubbles are attractive strategies since they provide real-time imaging, are relatively inexpensive, produce images with high spatial resolution, and do not involve exposure to ionizing irradiation. Raman spectroscopy/microscopy has emerged as a molecular optical imaging strategy for ultrasensitive detection of multiple biomolecules/biochemicals with both in vivo and ex vivo versatility. Photoacoustic imaging is a hybrid of optical and ultrasound modalities involving optically-excitable molecularly-targeted contrast agents and quantitative detection of resulting oscillatory contrast agent movement with ultrasound. Current preclinical findings and advances in instrumentation such as endoscopes and microcatheters suggest that these molecular imaging modalities have numerous clinical applications and will be translated into clinical use in the near future. PMID:20541650

Inducing fluorescence of uranyl acetate as a dual-purpose contrast agent for correlative light-electron microscopy with nanometre precision.

PubMed

Tuijtel, Maarten W; Mulder, Aat A; Posthuma, Clara C; van der Hoeven, Barbara; Koster, Abraham J; Bárcena, Montserrat; Faas, Frank G A; Sharp, Thomas H

2017-09-05

Correlative light-electron microscopy (CLEM) combines the high spatial resolution of transmission electron microscopy (TEM) with the capability of fluorescence light microscopy (FLM) to locate rare or transient cellular events within a large field of view. CLEM is therefore a powerful technique to study cellular processes. Aligning images derived from both imaging modalities is a prerequisite to correlate the two microscopy data sets, and poor alignment can limit interpretability of the data. Here, we describe how uranyl acetate, a commonly-used contrast agent for TEM, can be induced to fluoresce brightly at cryogenic temperatures (-195 °C) and imaged by cryoFLM using standard filter sets. This dual-purpose contrast agent can be used as a general tool for CLEM, whereby the equivalent staining allows direct correlation between fluorescence and TEM images. We demonstrate the potential of this approach by performing multi-colour CLEM of cells containing equine arteritis virus proteins tagged with either green- or red-fluorescent protein, and achieve high-precision localization of virus-induced intracellular membrane modifications. Using uranyl acetate as a dual-purpose contrast agent, we achieve an image alignment precision of ~30 nm, twice as accurate as when using fiducial beads, which will be essential for combining TEM with the evolving field of super-resolution light microscopy.

Dual-mode imaging with radiolabeled gold nanorods

NASA Astrophysics Data System (ADS)

Agarwal, Ashish; Shao, Xia; Rajian, Justin R.; Zhang, Huanan; Chamberland, David L.; Kotov, Nicholas A.; Wang, Xueding

2011-05-01

Many nanoparticle contrast agents have difficulties with deep tissue and near-bone imaging due to limited penetration of visible photons in the body and mineralized tissues. We are looking into the possibility of mediating this problem while retaining the capabilities of the high spatial resolution associated with optical imaging. As such, the potential combination of emerging photoacoustic imaging and nuclear imaging in monitoring of antirheumatic drug delivery by using a newly developed dual-modality contrast agent is investigated. The contrast agent is composed of gold nanorods (GNRs) conjugated to the tumor necrosis factor (TNF-α) antibody and is subsequently radiolabeled by 125I. ELISA experiments designed to test TNF-α binding are performed to prove the specificity and biological activity of the radiolabeled conjugated contrast agent. Photoacoustic and nuclear imaging are performed to visualize the distribution of GNRs in articular tissues of the rat tail joints in situ. Findings from the two imaging modalities correspond well with each other in all experiments. Our system can image GNRs down to a concentration of 10 pM in biological tissues and with a radioactive label of 5 μCi. This study demonstrates the potential of combining photoacoustic and nuclear imaging modalities through one targeted contrast agent for noninvasive monitoring of drug delivery as well as deep and mineralized tissue imaging.

Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.

PubMed

Han, Dongfeng; Bayouth, John; Song, Qi; Taurani, Aakant; Sonka, Milan; Buatti, John; Wu, Xiaodong

2011-01-01

Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we have proposed a general framework to use both PET and CT images simultaneously for tumor segmentation. Our method utilizes the strength of each imaging modality: the superior contrast of PET and the superior spatial resolution of CT. We formulate this problem as a Markov Random Field (MRF) based segmentation of the image pair with a regularized term that penalizes the segmentation difference between PET and CT. Our method simulates the clinical practice of delineating tumor simultaneously using both PET and CT, and is able to concurrently segment tumor from both modalities, achieving globally optimal solutions in low-order polynomial time by a single maximum flow computation. The method was evaluated on clinically relevant tumor segmentation problems. The results showed that our method can effectively make use of both PET and CT image information, yielding segmentation accuracy of 0.85 in Dice similarity coefficient and the average median hausdorff distance (HD) of 6.4 mm, which is 10% (resp., 16%) improvement compared to the graph cuts method solely using the PET (resp., CT) images.

On new non-modal hydrodynamic stability modes and resulting non-exponential growth rates - a Lie symmetry approach

NASA Astrophysics Data System (ADS)

Oberlack, Martin; Nold, Andreas; Sanjon, Cedric Wilfried; Wang, Yongqi; Hau, Jan

2016-11-01

Classical hydrodynamic stability theory for laminar shear flows, no matter if considering long-term stability or transient growth, is based on the normal-mode ansatz, or, in other words, on an exponential function in space (stream-wise direction) and time. Recently, it became clear that the normal mode ansatz and the resulting Orr-Sommerfeld equation is based on essentially three fundamental symmetries of the linearized Euler and Navier-Stokes equations: translation in space and time and scaling of the dependent variable. Further, Kelvin-mode of linear shear flows seemed to be an exception in this context as it admits a fourth symmetry resulting in the classical Kelvin mode which is rather different from normal-mode. However, very recently it was discovered that most of the classical canonical shear flows such as linear shear, Couette, plane and round Poiseuille, Taylor-Couette, Lamb-Ossen vortex or asymptotic suction boundary layer admit more symmetries. This, in turn, led to new problem specific non-modal ansatz functions. In contrast to the exponential growth rate in time of the modal-ansatz, the new non-modal ansatz functions usually lead to an algebraic growth or decay rate, while for the asymptotic suction boundary layer a double-exponential growth or decay is observed.

Nucleophosmin integrates within the nucleolus via multi-modal interactions with proteins displaying R-rich linear motifs and rRNA

PubMed Central

Mitrea, Diana M; Cika, Jaclyn A; Guy, Clifford S; Ban, David; Banerjee, Priya R; Stanley, Christopher B; Nourse, Amanda; Deniz, Ashok A; Kriwacki, Richard W

2016-01-01

The nucleolus is a membrane-less organelle formed through liquid-liquid phase separation of its components from the surrounding nucleoplasm. Here, we show that nucleophosmin (NPM1) integrates within the nucleolus via a multi-modal mechanism involving multivalent interactions with proteins containing arginine-rich linear motifs (R-motifs) and ribosomal RNA (rRNA). Importantly, these R-motifs are found in canonical nucleolar localization signals. Based on a novel combination of biophysical approaches, we propose a model for the molecular organization within liquid-like droplets formed by the N-terminal domain of NPM1 and R-motif peptides, thus providing insights into the structural organization of the nucleolus. We identify multivalency of acidic tracts and folded nucleic acid binding domains, mediated by N-terminal domain oligomerization, as structural features required for phase separation of NPM1 with other nucleolar components in vitro and for localization within mammalian nucleoli. We propose that one mechanism of nucleolar localization involves phase separation of proteins within the nucleolus. DOI: http://dx.doi.org/10.7554/eLife.13571.001 PMID:26836305

An intelligent multi-media human-computer dialogue system

NASA Technical Reports Server (NTRS)

Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.

1988-01-01

Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.

Nucleophosmin integrates within the nucleolus via multi-modal interactions with proteins displaying R-rich linear motifs and rRNA

DOE PAGES

Mitrea, Diana M.; Cika, Jaclyn A.; Guy, Clifford S.; ...

2016-02-02

In this study, the nucleolus is a membrane-less organelle formed through liquid-liquid phase separation of its components from the surrounding nucleoplasm. Here, we show that nucleophosmin (NPM1) integrates within the nucleolus via a multi-modal mechanism involving multivalent interactions with proteins containing arginine-rich linear motifs (R-motifs) and ribosomal RNA (rRNA). Importantly, these R-motifs are found in canonical nucleolar localization signals. Based on a novel combination of biophysical approaches, we propose a model for the molecular organization within liquid-like droplets formed by the N-terminal domain of NPM1 and R-motif peptides, thus providing insights into the structural organization of the nucleolus. We identifymore » multivalency of acidic tracts and folded nucleic acid binding domains, mediated by N-terminal domain oligomerization, as structural features required for phase separation of NPM1 with other nucleolar components in vitro and for localization within mammalian nucleoli. We propose that one mechanism of nucleolar localization involves phase separation of proteins within the nucleolus.« less

Accounting for correlation in network meta-analysis with multi-arm trials.

PubMed

Franchini, A J; Dias, S; Ades, A E; Jansen, J P; Welton, N J

2012-06-01

Multi-arm trials (trials with more than two arms) are particularly valuable forms of evidence for network meta-analysis (NMA). Trial results are available either as arm-level summaries, where effect measures are reported for each arm, or as contrast-level summaries, where the differences in effect between arms compare with the control arm chosen for the trial. We show that likelihood-based inference in both contrast-level and arm-level formats is identical if there are only two-arm trials, but that if there are multi-arm trials, results from the contrast-level format will be incorrect unless correlations are accounted for in the likelihood. We review Bayesian and frequentist software for NMA with multi-arm trials that can account for this correlation and give an illustrative example of the difference in estimates that can be introduced if the correlations are not incorporated. We discuss methods of imputing correlations when they cannot be derived from the reported results and urge trialists to report the standard error for the control arm even if only contrast-level summaries are reported. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Modality-specificity of sensory aging in vision and audition: evidence from event-related potentials.

PubMed

Ceponiene, R; Westerfield, M; Torki, M; Townsend, J

2008-06-18

Major accounts of aging implicate changes in processing external stimulus information. Little is known about differential effects of auditory and visual sensory aging, and the mechanisms of sensory aging are still poorly understood. Using event-related potentials (ERPs) elicited by unattended stimuli in younger (M=25.5 yrs) and older (M=71.3 yrs) subjects, this study examined mechanisms of sensory aging under minimized attention conditions. Auditory and visual modalities were examined to address modality-specificity vs. generality of sensory aging. Between-modality differences were robust. The earlier-latency responses (P1, N1) were unaffected in the auditory modality but were diminished in the visual modality. The auditory N2 and early visual N2 were diminished. Two similarities between the modalities were age-related enhancements in the late P2 range and positive behavior-early N2 correlation, the latter suggesting that N2 may reflect long-latency inhibition of irrelevant stimuli. Since there is no evidence for salient differences in neuro-biological aging between the two sensory regions, the observed between-modality differences are best explained by the differential reliance of auditory and visual systems on attention. Visual sensory processing relies on facilitation by visuo-spatial attention, withdrawal of which appears to be more disadvantageous in older populations. In contrast, auditory processing is equipped with powerful inhibitory capacities. However, when the whole auditory modality is unattended, thalamo-cortical gating deficits may not manifest in the elderly. In contrast, ERP indices of longer-latency, stimulus-level inhibitory modulation appear to diminish with age.

Evaluation of thermo-triggered drug release in intramuscular-transplanted tumors using thermosensitive polymer-modified liposomes and MRI.

PubMed

Kokuryo, Daisuke; Nakashima, Seiji; Ozaki, Fuminori; Yuba, Eiji; Chuang, Kai-Hsiang; Aoshima, Sadahito; Ishizaka, Yukihito; Saga, Tsuneo; Kono, Kenji; Aoki, Ichio

2015-01-01

Multi-modal thermo-sensitive polymer-modified liposomes (MTPLs) containing an anticancer drug, MR contrast agent, and fluorescent dye have been investigated as "theranostic" nanodevices that can be used to monitor drug delivery in cancer therapy. Here, we measured the physical characteristics of MTPLs, observed the dynamics of MTPLs in vivo, visualized heat-triggered drug release using MRI, and evaluated the treatment effects of the MTPLs with and without heating. In vitro experiments demonstrated that the MTPLs released drugs at temperatures above 41°C. In vivo MTPLs accumulated in tumor tissue, with the accumulation maximized for 4-12hours. MR signal in the tumor was significantly elevated after mild heating for 15 minutes, indicating release of the contrast agent from the MTPLs was facilitated by heat-triggering. Tumor size after treatment with MTPLs and heating was significantly smaller than those of the control groups. In conclusion, MTPLs with MRI are useful for low-invasive cancer theranostics. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

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.

Isometric multimodal photoacoustic microscopy based on optically transparent micro-ring ultrasonic detection.

PubMed

Dong, Biqin; Li, Hao; Zhang, Zhen; Zhang, Kevin; Chen, Siyu; Sun, Cheng; Zhang, Hao F

2015-01-01

Photoacoustic microscopy (PAM) is an attractive imaging tool complementary to established optical microscopic modalities by providing additional molecular specificities through imaging optical absorption contrast. While the development of optical resolution photoacoustic microscopy (ORPAM) offers high lateral resolution, the acoustically-determined axial resolution is limited due to the constraint in ultrasonic detection bandwidth. ORPAM with isometric spatial resolution along both axial and lateral direction is yet to be developed. Although recently developed sophisticated optical illumination and reconstruction methods offer improved axial resolution in ORPAM, the image acquisition procedures are rather complicated, limiting their capabilities for high-speed imaging and being easily integrated with established optical microscopic modalities. Here we report an isometric ORPAM based on an optically transparent micro-ring resonator ultrasonic detector and a commercial inverted microscope platform. Owing to the superior spatial resolution and the ease of integrating our ORPAM with established microscopic modalities, single cell imaging with extrinsic fluorescence staining, intrinsic autofluorescence, and optical absorption can be achieved simultaneously. This technique holds promise to greatly improve the accessibility of PAM to the broader biomedical researchers.

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.

Future Directions in Medical Physics: Models, Technology, and Translation to Medicine

NASA Astrophysics Data System (ADS)

Siewerdsen, Jeffrey

The application of physics in medicine has been integral to major advances in diagnostic and therapeutic medicine. Two primary areas represent the mainstay of medical physics research in the last century: in radiation therapy, physicists have propelled advances in conformal radiation treatment and high-precision image guidance; and in diagnostic imaging, physicists have advanced an arsenal of multi-modality imaging that includes CT, MRI, ultrasound, and PET as indispensible tools for noninvasive screening, diagnosis, and assessment of treatment response. In addition to their role in building such technologically rich fields of medicine, physicists have also become integral to daily clinical practice in these areas. The future suggests new opportunities for multi-disciplinary research bridging physics, biology, engineering, and computer science, and collaboration in medical physics carries a strong capacity for identification of significant clinical needs, access to clinical data, and translation of technologies to clinical studies. In radiation therapy, for example, the extraction of knowledge from large datasets on treatment delivery, image-based phenotypes, genomic profile, and treatment outcome will require innovation in computational modeling and connection with medical physics for the curation of large datasets. Similarly in imaging physics, the demand for new imaging technology capable of measuring physical and biological processes over orders of magnitude in scale (from molecules to whole organ systems) and exploiting new contrast mechanisms for greater sensitivity to molecular agents and subtle functional / morphological change will benefit from multi-disciplinary collaboration in physics, biology, and engineering. Also in surgery and interventional radiology, where needs for increased precision and patient safety meet constraints in cost and workflow, development of new technologies for imaging, image registration, and robotic assistance can leverage collaboration in physics, biomedical engineering, and computer science. In each area, there is major opportunity for multi-disciplinary collaboration with medical physics to accelerate the translation of such technologies to clinical use. Research supported by the National Institutes of Health, Siemens Healthcare, and Carestream Health.

An interactive online robotics course.

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

Wedeward, Kevin; Bruder, Steven B. H.

Attempting to convey concepts and ideas in the subject area of robotic manipulators from within the confines of a static two-dimensional printed page can prove quite challenging to even the most gifted of authors. The inherently dynamic and multi-dimensional nature of the subject matter seems better suited to a medium of conveyance wherein a student is allowed to interactively explore topics in this multi-disciplinary field. This article describes the initial development of an online robotics course 'textbook' which seeks to leverage recent advances in Web-based technologies to enhance the learning experience in ways not possible with printed materials. The pedagogicalmore » approach employed herein is that of multi-modal reinforcement wherein key concepts are first described in words, conveyed visually, and finally reinforced by soliciting student interaction.« less

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.