Multi-pinhole collimator design for small-object imaging with SiliSPECT: a high-resolution SPECT

NASA Astrophysics Data System (ADS)

Shokouhi, S.; Metzler, S. D.; Wilson, D. W.; Peterson, T. E.

2009-01-01

We have designed a multi-pinhole collimator for a dual-headed, stationary SPECT system that incorporates high-resolution silicon double-sided strip detectors. The compact camera design of our system enables imaging at source-collimator distances between 20 and 30 mm. Our analytical calculations show that using knife-edge pinholes with small-opening angles or cylindrically shaped pinholes in a focused, multi-pinhole configuration in combination with this camera geometry can generate narrow sensitivity profiles across the field of view that can be useful for imaging small objects at high sensitivity and resolution. The current prototype system uses two collimators each containing 127 cylindrically shaped pinholes that are focused toward a target volume. Our goal is imaging objects such as a mouse brain, which could find potential applications in molecular imaging.

Multi-Modality Phantom Development

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

Huber, Jennifer S.; Peng, Qiyu; Moses, William W.

2009-03-20

Multi-modality imaging has an increasing role in the diagnosis and treatment of a large number of diseases, particularly if both functional and anatomical information are acquired and accurately co-registered. Hence, there is a resulting need for multi modality phantoms in order to validate image co-registration and calibrate the imaging systems. We present our PET-ultrasound phantom development, including PET and ultrasound images of a simple prostate phantom. We use agar and gelatin mixed with a radioactive solution. We also present our development of custom multi-modality phantoms that are compatible with PET, transrectal ultrasound (TRUS), MRI and CT imaging. We describe bothmore » our selection of tissue mimicking materials and phantom construction procedures. These custom PET-TRUS-CT-MRI prostate phantoms use agargelatin radioactive mixtures with additional contrast agents and preservatives. We show multi-modality images of these custom prostate phantoms, as well as discuss phantom construction alternatives. Although we are currently focused on prostate imaging, this phantom development is applicable to many multi-modality imaging applications.« less

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

DOE PAGES

Ozturk, Hande; Yan, Hanfei; He, Yan; ...

2018-05-09

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

Multi-slice ptychography with large numerical aperture multilayer Laue lenses

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

Ozturk, Hande; Yan, Hanfei; He, Yan

Here, the highly convergent x-ray beam focused by multilayer Laue lenses with large numerical apertures is used as a three-dimensional (3D) probe to image layered structures with an axial separation larger than the depth of focus. Instead of collecting weakly scattered high-spatial-frequency signals, the depth-resolving power is provided purely by the intense central cone diverged from the focused beam. Using the multi-slice ptychography method combined with the on-the-fly scan scheme, two layers of nanoparticles separated by 10 μm are successfully reconstructed with 8.1 nm lateral resolution and with a dwell time as low as 0.05 s per scan point. Thismore » approach obtains high-resolution images with extended depth of field, which paves the way for multi-slice ptychography as a high throughput technique for high-resolution 3D imaging of thick samples.« less

A broadband terahertz ultrathin multi-focus lens

PubMed Central

He, Jingwen; Ye, Jiasheng; Wang, Xinke; Kan, Qiang; Zhang, Yan

2016-01-01

Ultrathin transmission metasurface devices are designed on the basis of the Yang-Gu amplitude-phase retrieval algorithm for focusing the terahertz (THz) radiation into four or nine spots with focal spacing of 2 or 3 mm at a frequency of 0.8 THz. The focal properties are experimentally investigated in detail, and the results agree well with the theoretical expectations. The designed THz multi-focus lens (TMFL) demonstrates a good focusing function over a broad frequency range from 0.3 to 1.1 THz. As a transmission-type device based on metasurface, the diffraction efficiency of the TMFL can be as high as 33.92% at the designed frequency. The imaging function of the TMFL is also demonstrated experimentally and clear images are obtained. The proposed method produces an ultrathin, low-cost, and broadband multi-focus lens for THz-band application PMID:27346430

Tomographic Imaging of a Forested Area By Airborne Multi-Baseline P-Band SAR.

PubMed

Frey, Othmar; Morsdorf, Felix; Meier, Erich

2008-09-24

In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic images is limited by several factors. In particular, the common Fourierbased focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. In this paper, a tomographic focusing method based on the time-domain back-projection algorithm is proposed, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. The tomographic focusing quality is assessed by analysing the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, several tomographic slices of a volume representing a forested area are given. The respective P-band tomographic data set consisting of eleven flight tracks has been acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR).

Acousto-optic tunable filter chromatic aberration analysis and reduction with auto-focus system

NASA Astrophysics Data System (ADS)

Wang, Yaoli; Chen, Yuanyuan

2018-07-01

An acousto-optic tunable filter (AOTF) displays optical band broadening and sidelobes as a result of the coupling between the acoustic wave and optical waves of different wavelengths. These features were analysed by wave-vector phase matching between the optical and acoustic waves. A crossed-line test board was imaged by an AOTF multi-spectral imaging system, showing image blurring in the direction of diffraction and image sharpness in the orthogonal direction produced by the greater bandwidth and sidelobes in the former direction. Applying the secondary-imaging principle and considering the wavelength-dependent refractive index, focal length varies over the broad wavelength range. An automatic focusing method is therefore proposed for use in AOTF multi-spectral imaging systems. A new method for image-sharpness evaluation, based on improved Structure Similarity Index Measurement (SSIM), is also proposed, based on the characteristics of the AOTF imaging system. Compared with the traditional gradient operator, as same as it, the new evaluation function realized the evaluation between different image quality, thus could achieve the automatic focusing for different multispectral images.

Multi-focal HIFU reduces cavitation in mild-hyperthermia.

PubMed

Chaplin, Vandiver; Caskey, Charles F

2017-01-01

Mild-hyperthermia therapy (40-45 °C) with high-intensity focused ultrasound (HIFU) is a technique being considered in a number of different treatments such as thermally activated drug delivery, immune-stimulation, and as a chemotherapy adjuvant. Mechanical damage and loss of cell viability associated with HIFU-induced acoustic cavitation may pose a risk during these treatments or may hinder their success. Here we present a method that achieves mild heating and reduces cavitation by using a multi-focused HIFU beam. We quantify cavitation level and temperature rise in multi-focal sonications and compare it to single-focus sonications at the transducer geometric focus. Continuous wave sonications were performed with the Sonalleve V2 transducer in gel phantoms and pork at 5, 10, 20, 40, 60, 80 acoustic watts for 30 s. Cavitation activity was measured with two ultrasound (US) imaging probes, both by computing the raw channel variance and using passive acoustic mapping (PAM). Temperature rise was measured with MR thermometry at 3 T. Cavitation and heating were compared for single- and multi-focal sonication geometries. Multi-focal sonications used four points equally spaced on a ring of either 4 mm or 8 mm diameter. Single-focus sonications were not steered. Multi-focal sonication generated distinct foci that were visible in MRI thermal maps in both phantoms and pork, and visible in PAM images in phantoms only. Cavitation activity (measured by channel variance) and mean PAM image value were highly correlated (r > 0.9). In phantoms, cavitation exponentially decreased over the 30-second sonication, consistent with depletion of cavitation nuclei. In pork, sporadic spikes signaling cavitation were observed with single focusing only. In both materials, the widest beam reduced average and peak cavitation level by a factor of two or more at each power tested when compared to a single focus. The widest beam reduced peak temperature by at least 10 °C at powers above 5 W, and created heating that was more spatially diffuse than single focus, resulting in more voxels in the mild heating (3-8 °C) range. Multi-focal HIFU can be used to achieve mild temperature elevation and reduce cavitation activity.

Semantic focusing allows fully automated single-layer slide scanning of cervical cytology slides.

PubMed

Lahrmann, Bernd; Valous, Nektarios A; Eisenmann, Urs; Wentzensen, Nicolas; Grabe, Niels

2013-01-01

Liquid-based cytology (LBC) in conjunction with Whole-Slide Imaging (WSI) enables the objective and sensitive and quantitative evaluation of biomarkers in cytology. However, the complex three-dimensional distribution of cells on LBC slides requires manual focusing, long scanning-times, and multi-layer scanning. Here, we present a solution that overcomes these limitations in two steps: first, we make sure that focus points are only set on cells. Secondly, we check the total slide focus quality. From a first analysis we detected that superficial dust can be separated from the cell layer (thin layer of cells on the glass slide) itself. Then we analyzed 2,295 individual focus points from 51 LBC slides stained for p16 and Ki67. Using the number of edges in a focus point image, specific color values and size-inclusion filters, focus points detecting cells could be distinguished from focus points on artifacts (accuracy 98.6%). Sharpness as total focus quality of a virtual LBC slide is computed from 5 sharpness features. We trained a multi-parameter SVM classifier on 1,600 images. On an independent validation set of 3,232 cell images we achieved an accuracy of 94.8% for classifying images as focused. Our results show that single-layer scanning of LBC slides is possible and how it can be achieved. We assembled focus point analysis and sharpness classification into a fully automatic, iterative workflow, free of user intervention, which performs repetitive slide scanning as necessary. On 400 LBC slides we achieved a scanning-time of 13.9±10.1 min with 29.1±15.5 focus points. In summary, the integration of semantic focus information into whole-slide imaging allows automatic high-quality imaging of LBC slides and subsequent biomarker analysis.

MultiFocus Polarization Microscope (MF-PolScope) for 3D polarization imaging of up to 25 focal planes simultaneously

PubMed Central

Abrahamsson, Sara; McQuilken, Molly; Mehta, Shalin B.; Verma, Amitabh; Larsch, Johannes; Ilic, Rob; Heintzmann, Rainer; Bargmann, Cornelia I.; Gladfelter, Amy S.; Oldenbourg, Rudolf

2015-01-01

We have developed an imaging system for 3D time-lapse polarization microscopy of living biological samples. Polarization imaging reveals the position, alignment and orientation of submicroscopic features in label-free as well as fluorescently labeled specimens. Optical anisotropies are calculated from a series of images where the sample is illuminated by light of different polarization states. Due to the number of images necessary to collect both multiple polarization states and multiple focal planes, 3D polarization imaging is most often prohibitively slow. Our MF-PolScope system employs multifocus optics to form an instantaneous 3D image of up to 25 simultaneous focal-planes. We describe this optical system and show examples of 3D multi-focus polarization imaging of biological samples, including a protein assembly study in budding yeast cells. PMID:25837112

A coaxially focused multi-mode beam for optical coherence tomography imaging with extended depth of focus (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yin, Biwei; Liang, Chia-Pin; Vuong, Barry; Tearney, Guillermo J.

2017-02-01

Conventional OCT images, obtained using a focused Gaussian beam have a lateral resolution of approximately 30 μm and a depth of focus (DOF) of 2-3 mm, defined as the confocal parameter (twice of Gaussian beam Rayleigh range). Improvement of lateral resolution without sacrificing imaging range requires techniques that can extend the DOF. Previously, we described a self-imaging wavefront division optical system that provided an estimated one order of magnitude DOF extension. In this study, we further investigate the properties of the coaxially focused multi-mode (CAFM) beam created by this self-imaging wavefront division optical system and demonstrate its feasibility for real-time biological tissue imaging. Gaussian beam and CAFM beam fiber optic probes with similar numerical apertures (objective NA≈0.5) were fabricated, providing lateral resolutions of approximately 2 μm. Rigorous lateral resolution characterization over depth was performed for both probes. The CAFM beam probe was found to be able to provide a DOF that was approximately one order of magnitude greater than that of Gaussian beam probe. By incorporating the CAFM beam fiber optic probe into a μOCT system with 1.5 μm axial resolution, we were able to acquire cross-sectional images of swine small intestine ex vivo, enabling the visualization of subcellular structures, providing high quality OCT images over more than a 300 μm depth range.

High Density Aerial Image Matching: State-Of and Future Prospects

NASA Astrophysics Data System (ADS)

Haala, N.; Cavegn, S.

2016-06-01

Ongoing innovations in matching algorithms are continuously improving the quality of geometric surface representations generated automatically from aerial images. This development motivated the launch of the joint ISPRS/EuroSDR project "Benchmark on High Density Aerial Image Matching", which aims on the evaluation of photogrammetric 3D data capture in view of the current developments in dense multi-view stereo-image matching. Originally, the test aimed on image based DSM computation from conventional aerial image flights for different landuse and image block configurations. The second phase then put an additional focus on high quality, high resolution 3D geometric data capture in complex urban areas. This includes both the extension of the test scenario to oblique aerial image flights as well as the generation of filtered point clouds as additional output of the respective multi-view reconstruction. The paper uses the preliminary outcomes of the benchmark to demonstrate the state-of-the-art in airborne image matching with a special focus of high quality geometric data capture in urban scenarios.

Multi-Focus Image Fusion Based on NSCT and NSST

NASA Astrophysics Data System (ADS)

Moonon, Altan-Ulzii; Hu, Jianwen

2015-12-01

In this paper, a multi-focus image fusion algorithm based on the nonsubsampled contourlet transform (NSCT) and the nonsubsampled shearlet transform (NSST) is proposed. The source images are first decomposed by the NSCT and NSST into low frequency coefficients and high frequency coefficients. Then, the average method is used to fuse low frequency coefficient of the NSCT. To obtain more accurate salience measurement, the high frequency coefficients of the NSST and NSCT are combined to measure salience. The high frequency coefficients of the NSCT with larger salience are selected as fused high frequency coefficients. Finally, the fused image is reconstructed by the inverse NSCT. We adopt three metrics (Q AB/F , Q e and Q w ) to evaluate the quality of fused images. The experimental results demonstrate that the proposed method outperforms other methods. It retains highly detailed edges and contours.

Multi-spectral confocal microendoscope for in-vivo imaging

NASA Astrophysics Data System (ADS)

Rouse, Andrew Robert

The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

Impact of multi-focused images on recognition of soft biometric traits

NASA Astrophysics Data System (ADS)

Chiesa, V.; Dugelay, J. L.

2016-09-01

In video surveillance semantic traits estimation as gender and age has always been debated topic because of the uncontrolled environment: while light or pose variations have been largely studied, defocused images are still rarely investigated. Recently the emergence of new technologies, as plenoptic cameras, yields to deal with these problems analyzing multi-focus images. Thanks to a microlens array arranged between the sensor and the main lens, light field cameras are able to record not only the RGB values but also the information related to the direction of light rays: the additional data make possible rendering the image with different focal plane after the acquisition. For our experiments, we use the GUC Light Field Face Database that includes pictures from the First Generation Lytro camera. Taking advantage of light field images, we explore the influence of defocusing on gender recognition and age estimation problems. Evaluations are computed on up-to-date and competitive technologies based on deep learning algorithms. After studying the relationship between focus and gender recognition and focus and age estimation, we compare the results obtained by images defocused by Lytro software with images blurred by more standard filters in order to explore the difference between defocusing and blurring effects. In addition we investigate the impact of deblurring on defocused images with the goal to better understand the different impacts of defocusing and standard blurring on gender and age estimation.

Image fusion based on Bandelet and sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Jiuxing; Zhang, Wei; Li, Xuzhi

2018-04-01

Bandelet transform could acquire geometric regular direction and geometric flow, sparse representation could represent signals with as little as possible atoms on over-complete dictionary, both of which could be used to image fusion. Therefore, a new fusion method is proposed based on Bandelet and Sparse Representation, to fuse Bandelet coefficients of multi-source images and obtain high quality fusion effects. The test are performed on remote sensing images and simulated multi-focus images, experimental results show that the performance of new method is better than tested methods according to objective evaluation indexes and subjective visual effects.

Instance annotation for multi-instance multi-label learning

Treesearch

F. Briggs; X.Z. Fern; R. Raich; Q. Lou

2013-01-01

Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels. For example, an image can be represented as a bag of segments and associated with a list of objects it contains. Prior work on MIML has focused on predicting label sets for previously unseen...

Magnetic Nanoparticles for Multi-Imaging and Drug Delivery

PubMed Central

Lee, Jae-Hyun; Kim, Ji-wook; Cheon, Jinwoo

2013-01-01

Various bio-medical applications of magnetic nanoparticles have been explored during the past few decades. As tools that hold great potential for advancing biological sciences, magnetic nanoparticles have been used as platform materials for enhanced magnetic resonance imaging (MRI) agents, biological separation and magnetic drug delivery systems, and magnetic hyperthermia treatment. Furthermore, approaches that integrate various imaging and bioactive moieties have been used in the design of multi-modality systems, which possess synergistically enhanced properties such as better imaging resolution and sensitivity, molecular recognition capabilities, stimulus responsive drug delivery with on-demand control, and spatio-temporally controlled cell signal activation. Below, recent studies that focus on the design and synthesis of multi-mode magnetic nanoparticles will be briefly reviewed and their potential applications in the imaging and therapy areas will be also discussed. PMID:23579479

Maximizing Science Return from Future Mars Missions with Onboard Image Analyses

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Morris, R. L.; Bandari, E. B.; Roush, T. L.

2000-01-01

We have developed two new techniques to enhance science return and to decrease returned data volume for near-term Mars missions: 1) multi-spectral image compression and 2) autonomous identification and fusion of in-focus regions in an image series.

Multi-anode microchannel arrays - New detectors for imaging and spectroscopy in space

NASA Technical Reports Server (NTRS)

Timothy, J. G.; Bybee, R. L.

1983-01-01

Consideration is given to the construction and operation of multi-anode microchannel array detector systems having formats as large as 256 x 1024 pixels. Such arrays are being developed for imaging and spectroscopy at soft X-ray, ultraviolet and visible wavelengths from balloons, sounding rockets and space probes. Both discrete-anode and coincidence-anode arrays are described. Two types of photocathode structures are evaluated: an opaque photocathode deposited directly on the curved-channel MCP and an activated cathode deposited on a proximity-focused mesh. Future work will include sensitivity optimization in the different wavelength regions and the development of detector tubes with semitransparent proximity-focused photocathodes.

3D-shape recognition and size measurement of irregular rough particles using multi-views interferometric out-of-focus imaging.

PubMed

Ouldarbi, L; Talbi, M; Coëtmellec, S; Lebrun, D; Gréhan, G; Perret, G; Brunel, M

2016-11-10

We realize simplified-tomography experiments on irregular rough particles using interferometric out-of-focus imaging. Using two angles of view, we determine the global 3D-shape, the dimensions, and the 3D-orientation of irregular rough particles whose morphologies belong to families such as sticks, plates, and crosses.

Measurement and correction of transverse chromatic offsets for multi-wavelength retinal microscopy in the living eye.

PubMed

Harmening, Wolf M; Tiruveedhula, Pavan; Roorda, Austin; Sincich, Lawrence C

2012-09-01

A special challenge arises when pursuing multi-wavelength imaging of retinal tissue in vivo, because the eye's optics must be used as the main focusing elements, and they introduce significant chromatic dispersion. Here we present an image-based method to measure and correct for the eye's transverse chromatic aberrations rapidly, non-invasively, and with high precision. We validate the technique against hyperacute psychophysical performance and the standard chromatic human eye model. In vivo correction of chromatic dispersion will enable confocal multi-wavelength images of the living retina to be aligned, and allow targeted chromatic stimulation of the photoreceptor mosaic to be performed accurately with sub-cellular resolution.

Measurement and correction of transverse chromatic offsets for multi-wavelength retinal microscopy in the living eye

PubMed Central

Harmening, Wolf M.; Tiruveedhula, Pavan; Roorda, Austin; Sincich, Lawrence C.

2012-01-01

A special challenge arises when pursuing multi-wavelength imaging of retinal tissue in vivo, because the eye’s optics must be used as the main focusing elements, and they introduce significant chromatic dispersion. Here we present an image-based method to measure and correct for the eye’s transverse chromatic aberrations rapidly, non-invasively, and with high precision. We validate the technique against hyperacute psychophysical performance and the standard chromatic human eye model. In vivo correction of chromatic dispersion will enable confocal multi-wavelength images of the living retina to be aligned, and allow targeted chromatic stimulation of the photoreceptor mosaic to be performed accurately with sub-cellular resolution. PMID:23024901

Multi-acoustic lens design methodology for a low cost C-scan photoacoustic imaging camera

NASA Astrophysics Data System (ADS)

Chinni, Bhargava; Han, Zichao; Brown, Nicholas; Vallejo, Pedro; Jacobs, Tess; Knox, Wayne; Dogra, Vikram; Rao, Navalgund

2016-03-01

We have designed and implemented a novel acoustic lens based focusing technology into a prototype photoacoustic imaging camera. All photoacoustically generated waves from laser exposed absorbers within a small volume get focused simultaneously by the lens onto an image plane. We use a multi-element ultrasound transducer array to capture the focused photoacoustic signals. Acoustic lens eliminates the need for expensive data acquisition hardware systems, is faster compared to electronic focusing and enables real-time image reconstruction. Using this photoacoustic imaging camera, we have imaged more than 150 several centimeter size ex-vivo human prostate, kidney and thyroid specimens with a millimeter resolution for cancer detection. In this paper, we share our lens design strategy and how we evaluate the resulting quality metrics (on and off axis point spread function, depth of field and modulation transfer function) through simulation. An advanced toolbox in MATLAB was adapted and used for simulating a two-dimensional gridded model that incorporates realistic photoacoustic signal generation and acoustic wave propagation through the lens with medium properties defined on each grid point. Two dimensional point spread functions have been generated and compared with experiments to demonstrate the utility of our design strategy. Finally we present results from work in progress on the use of two lens system aimed at further improving some of the quality metrics of our system.

[Joint correction for motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging].

PubMed

Wu, Wenchuan; Fang, Sheng; Guo, Hua

2014-06-01

Aiming at motion artifacts and off-resonance artifacts in multi-shot diffusion magnetic resonance imaging (MRI), we proposed a joint correction method in this paper to correct the two kinds of artifacts simultaneously without additional acquisition of navigation data and field map. We utilized the proposed method using multi-shot variable density spiral sequence to acquire MRI data and used auto-focusing technique for image deblurring. We also used direct method or iterative method to correct motion induced phase errors in the process of deblurring. In vivo MRI experiments demonstrated that the proposed method could effectively suppress motion artifacts and off-resonance artifacts and achieve images with fine structures. In addition, the scan time was not increased in applying the proposed method.

Liquid lens enabling real-time focus and tilt compensation for optical image stabilization in camera modules

NASA Astrophysics Data System (ADS)

Simon, Eric; Craen, Pierre; Gaton, Hilario; Jacques-Sermet, Olivier; Laune, Frédéric; Legrand, Julien; Maillard, Mathieu; Tallaron, Nicolas; Verplanck, Nicolas; Berge, Bruno

2010-05-01

A new generation of liquid lenses based on electrowetting has been developed, using a multi-electrode design, enabling to induce optical tilt and focus corrections in the same component. The basic principle is to rely on a conical shape for supporting the liquid interface, the conical shape insuring a restoring force for the liquid liquid interface to come at the center position. The multi-electrode design enables to induce an average tilt of the liquid liquid interface when a bias voltage is applied to the different electrodes. This tilt is reversible, vanishing when voltage bias is cancelled. Possible application of this new lens component is the realization of miniature camera featuring auto-focus and optical image stabilization (OIS) without any mobile mechanical part. Experimental measurements of actual performances of liquid lens component will be presented : focus and tilt amplitude, residual optical wave front error and response time.

Design and fabrication of a multi-focusing artificial compound eyes with negative meniscus substrate

NASA Astrophysics Data System (ADS)

Luo, Jiasai; Guo, Yongcai; Wang, Xin; Fan, Fenglian

2017-04-01

Miniaturized artificial compound eyes with a large field of view (FOV) have potential application in the area of micro-optical-electro-mechanical-system (MOEMS). A new non-uniform microlens array (MLA) on a negative meniscus substrate, fabricated by the melting photoresist method, was proposed in this paper. The multi-focusing MLA reduced the defocus effectively, which was caused by the uniform array on a spherical substrate. Moreover, like most ommatidia in compound eyes, each microlens of the multi-focusing MLA was arranged in one of the eleven concentric circles. In order to match with the multi-focusing MLA and avoid the total reflection, the negative meniscus substrate was fabricated by a homebuilt mold with a micro-hole array and polydimethylsiloxane coelomic compartment attached. The coelomic compartment is capable of offering an excellent injection environment without bubbles and impurities. Due to the direct 3D implementation of the MLA, rich available materials can be used by this method without substrate reshaping. As the molding material, the ultraviolet curing adhesive NOA81 can be cured within ten few seconds under ultraviolet which relieve intensive labor and protect the stereolithography apparatus effectively. The experimental results show that this new MLA has a better imaging performance, higher light usage efficiency and larger FOV because of the negative meniscus and multi-focusing MLA. Moreover, due to the homebuilt mold, more accurate geometrical parameters and shorter processing cycle were realized. Accordingly, together with an appropriate hardware, this MLA has diverse potential applications in medical imaging, military and machine vision.

Multi-scale learning based segmentation of glands in digital colonrectal pathology images.

PubMed

Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-02-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

Multi-scale learning based segmentation of glands in digital colonrectal pathology images

NASA Astrophysics Data System (ADS)

Gao, Yi; Liu, William; Arjun, Shipra; Zhu, Liangjia; Ratner, Vadim; Kurc, Tahsin; Saltz, Joel; Tannenbaum, Allen

2016-03-01

Digital histopathological images provide detailed spatial information of the tissue at micrometer resolution. Among the available contents in the pathology images, meso-scale information, such as the gland morphology, texture, and distribution, are useful diagnostic features. In this work, focusing on the colon-rectal cancer tissue samples, we propose a multi-scale learning based segmentation scheme for the glands in the colon-rectal digital pathology slides. The algorithm learns the gland and non-gland textures from a set of training images in various scales through a sparse dictionary representation. After the learning step, the dictionaries are used collectively to perform the classification and segmentation for the new image.

An overview of instrumentation for the Large Binocular Telescope

NASA Astrophysics Data System (ADS)

Wagner, R. Mark

2004-09-01

An overview of instrumentation for the Large Binocular Telescope is presented. Optical instrumentation includes the Large Binocular Camera (LBC), a pair of wide-field (27'x 27') UB/VRI optimized mosaic CCD imagers at the prime focus, and the Multi-Object Double Spectrograph (MODS), a pair of dual-beam blue-red optimized long-slit spectrographs mounted at the straight-through F/15 Gregorian focus incorporating multiple slit masks for multi-object spectroscopy over a 6\\arcmin\\ field and spectral resolutions of up to 8000. Infrared instrumentation includes the LBT Near-IR Spectroscopic Utility with Camera and Integral Field Unit for Extragalactic Research (LUCIFER), a modular near-infrared (0.9-2.5 μm) imager and spectrograph pair mounted at a bent interior focal station and designed for seeing-limited (FOV: 4'x 4') imaging, long-slit spectroscopy, and multi-object spectroscopy utilizing cooled slit masks and diffraction limited (FOV: 0'.5 x 0'.5) imaging and long-slit spectroscopy. Strategic instruments under development for the remaining two combined focal stations include an interferometric cryogenic beam combiner with near-infrared and thermal-infrared instruments for Fizeau imaging and nulling interferometry (LBTI) and an optical bench beam combiner with visible and near-infrared imagers utilizing multi-conjugate adaptive optics for high angular resolution and sensitivity (LINC/NIRVANA). In addition, a fiber-fed bench spectrograph (PEPSI) capable of ultra high resolution spectroscopy and spectropolarimetry (R = 40,000-300,000) will be available as a principal investigator instrument. The availability of all these instruments mounted simultaneously on the LBT permits unique science, flexible scheduling, and improved operational support.

Development and testing of a homogenous multi-wavelength LED light source

NASA Astrophysics Data System (ADS)

Bolton, Frank J.; Bernat, Amir; Jacques, Steven L.; Levitz, David

2017-03-01

Multispectral imaging of human tissue is a powerful method that allows for quantify scattering and absorption parameters of the tissue and differentiate tissue types or identify pathology. This method requires imaging at multiple wavelengths and then fitting the measured data to a model based on light transport theory. Earlier, a mobile phone based multi-spectral imaging system was developed to image the uterine cervix from the colposcopy geometry, outside the patient's body at a distance of 200-300 mm. Such imaging of a distance object has inherent challenges, as bright and homogenous illumination is required. Several solutions addressing this problem were developed, with varied degrees of success. In this paper, several multi-spectral illumination setups were developed and tested for brightness and uniformity. All setups were specifically designed with low cost in mind, utilizing a printed circuit board with surface-mounted LEDs. The three setups include: LEDs illuminating the target directly, LEDs illuminating focused by a 3D printed miniature lens array, and LEDs coupled to a mixing lens and focusing optical system. In order to compare the illumination uniformity and intensity performance two experiments were performed. Test results are presented, and various tradeoffs between the three system configurations are discussed. Test results are presented, and various tradeoffs between the three system configurations are discussed.

Multi-focus image fusion based on area-based standard deviation in dual tree contourlet transform domain

NASA Astrophysics Data System (ADS)

Dong, Min; Dong, Chenghui; Guo, Miao; Wang, Zhe; Mu, Xiaomin

2018-04-01

Multiresolution-based methods, such as wavelet and Contourlet are usually used to image fusion. This work presents a new image fusion frame-work by utilizing area-based standard deviation in dual tree Contourlet trans-form domain. Firstly, the pre-registered source images are decomposed with dual tree Contourlet transform; low-pass and high-pass coefficients are obtained. Then, the low-pass bands are fused with weighted average based on area standard deviation rather than the simple "averaging" rule. While the high-pass bands are merged with the "max-absolute' fusion rule. Finally, the modified low-pass and high-pass coefficients are used to reconstruct the final fused image. The major advantage of the proposed fusion method over conventional fusion is the approximately shift invariance and multidirectional selectivity of dual tree Contourlet transform. The proposed method is compared with wavelet- , Contourletbased methods and other the state-of-the art methods on common used multi focus images. Experiments demonstrate that the proposed fusion framework is feasible and effective, and it performs better in both subjective and objective evaluation.

Steganalysis feature improvement using expectation maximization

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M.; Peterson, Gilbert L.; Agaian, Sos S.

2007-04-01

Images and data files provide an excellent opportunity for concealing illegal or clandestine material. Currently, there are over 250 different tools which embed data into an image without causing noticeable changes to the image. From a forensics perspective, when a system is confiscated or an image of a system is generated the investigator needs a tool that can scan and accurately identify files suspected of containing malicious information. The identification process is termed the steganalysis problem which focuses on both blind identification, in which only normal images are available for training, and multi-class identification, in which both the clean and stego images at several embedding rates are available for training. In this paper an investigation of a clustering and classification technique (Expectation Maximization with mixture models) is used to determine if a digital image contains hidden information. The steganalysis problem is for both anomaly detection and multi-class detection. The various clusters represent clean images and stego images with between 1% and 10% embedding percentage. Based on the results it is concluded that the EM classification technique is highly suitable for both blind detection and the multi-class problem.

Implementation of total focusing method for phased array ultrasonic imaging on FPGA

NASA Astrophysics Data System (ADS)

Guo, JianQiang; Li, Xi; Gao, Xiaorong; Wang, Zeyong; Zhao, Quanke

2015-02-01

This paper describes a multi-FPGA imaging system dedicated for the real-time imaging using the Total Focusing Method (TFM) and Full Matrix Capture (FMC). The system was entirely described using Verilog HDL language and implemented on Altera Stratix IV GX FPGA development board. The whole algorithm process is to: establish a coordinate system of image and divide it into grids; calculate the complete acoustic distance of array element between transmitting array element and receiving array element, and transform it into index value; then index the sound pressure values from ROM and superimpose sound pressure values to get pixel value of one focus point; and calculate the pixel values of all focus points to get the final imaging. The imaging result shows that this algorithm has high SNR of defect imaging. And FPGA with parallel processing capability can provide high speed performance, so this system can provide the imaging interface, with complete function and good performance.

Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework

NASA Astrophysics Data System (ADS)

Chandakkar, Parag S.; Venkatesan, Ragav; Li, Baoxin

2013-02-01

Diabetic retinopathy (DR) is a vision-threatening complication from diabetes mellitus, a medical condition that is rising globally. Unfortunately, many patients are unaware of this complication because of absence of symptoms. Regular screening of DR is necessary to detect the condition for timely treatment. Content-based image retrieval, using archived and diagnosed fundus (retinal) camera DR images can improve screening efficiency of DR. This content-based image retrieval study focuses on two DR clinical findings, microaneurysm and neovascularization, which are clinical signs of non-proliferative and proliferative diabetic retinopathy. The authors propose a multi-class multiple-instance image retrieval framework which deploys a modified color correlogram and statistics of steerable Gaussian Filter responses, for retrieving clinically relevant images from a database of DR fundus image database.

Multi-frame image processing with panning cameras and moving subjects

NASA Astrophysics Data System (ADS)

Paolini, Aaron; Humphrey, John; Curt, Petersen; Kelmelis, Eric

2014-06-01

Imaging scenarios commonly involve erratic, unpredictable camera behavior or subjects that are prone to movement, complicating multi-frame image processing techniques. To address these issues, we developed three techniques that can be applied to multi-frame image processing algorithms in order to mitigate the adverse effects observed when cameras are panning or subjects within the scene are moving. We provide a detailed overview of the techniques and discuss the applicability of each to various movement types. In addition to this, we evaluated algorithm efficacy with demonstrated benefits using field test video, which has been processed using our commercially available surveillance product. Our results show that algorithm efficacy is significantly improved in common scenarios, expanding our software's operational scope. Our methods introduce little computational burden, enabling their use in real-time and low-power solutions, and are appropriate for long observation periods. Our test cases focus on imaging through turbulence, a common use case for multi-frame techniques. We present results of a field study designed to test the efficacy of these techniques under expanded use cases.

Generating description with multi-feature fusion and saliency maps of image

NASA Astrophysics Data System (ADS)

Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

2018-04-01

Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

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

Exploring plenoptic properties of correlation imaging with chaotic light

NASA Astrophysics Data System (ADS)

Pepe, Francesco V.; Vaccarelli, Ornella; Garuccio, Augusto; Scarcelli, Giuliano; D'Angelo, Milena

2017-11-01

In a setup illuminated by chaotic light, we consider different schemes that enable us to perform imaging by measuring second-order intensity correlations. The most relevant feature of the proposed protocols is the ability to perform plenoptic imaging, namely to reconstruct the geometrical path of light propagating in the system, by imaging both the object and the focusing element. This property allows us to encode, in a single data acquisition, both multi-perspective images of the scene and light distribution in different planes between the scene and the focusing element. We unveil the plenoptic property of three different setups, explore their refocusing potentialities and discuss their practical applications.

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

An overview of instrumentation for the Large Binocular Telescope

NASA Astrophysics Data System (ADS)

Wagner, R. Mark

2006-06-01

An overview of instrumentation for the Large Binocular Telescope is presented. Optical instrumentation includes the Large Binocular Camera (LBC), a pair of wide-field (27' × 27') mosaic CCD imagers at the prime focus, and the Multi-Object Double Spectrograph (MODS), a pair of dual-beam blue-red optimized long-slit spectrographs mounted at the straight-through F/15 Gregorian focus incorporating multiple slit masks for multi-object spectroscopy over a 6' field and spectral resolutions of up to 8000. Infrared instrumentation includes the LBT Near-IR Spectroscopic Utility with Camera and Integral Field Unit for Extragalactic Research (LUCIFER), a modular near-infrared (0.9-2.5 μm) imager and spectrograph pair mounted at a bent interior focal station and designed for seeing-limited (FOV: 4' × 4') imaging, long-slit spectroscopy, and multi-object spectroscopy utilizing cooled slit masks and diffraction limited (FOV: 0'.5 × 0'.5) imaging and long-slit spectroscopy. Strategic instruments under development for the remaining two combined focal stations include an interferometric cryogenic beam combiner with near-infrared and thermal-infrared instruments for Fizeau imaging and nulling interferometry (LBTI) and an optical bench near-infrared beam combiner utilizing multi-conjugate adaptive optics for high angular resolution and sensitivity (LINC-NIRVANA). In addition, a fiber-fed bench spectrograph (PEPSI) capable of ultra high resolution spectroscopy and spectropolarimetry (R = 40,000-300,000) will be available as a principal investigator instrument. The availability of all these instruments mounted simultaneously on the LBT permits unique science, flexible scheduling, and improved operational support.

An overview of instrumentation for the Large Binocular Telescope

NASA Astrophysics Data System (ADS)

Wagner, R. Mark

2008-07-01

An overview of instrumentation for the Large Binocular Telescope is presented. Optical instrumentation includes the Large Binocular Camera (LBC), a pair of wide-field (27' × 27') mosaic CCD imagers at the prime focus, and the Multi-Object Double Spectrograph (MODS), a pair of dual-beam blue-red optimized long-slit spectrographs mounted at the straight-through F/15 Gregorian focus incorporating multiple slit masks for multi-object spectroscopy over a 6 field and spectral resolutions of up to 8000. Infrared instrumentation includes the LBT Near-IR Spectroscopic Utility with Camera and Integral Field Unit for Extragalactic Research (LUCIFER), a modular near-infrared (0.9-2.5 μm) imager and spectrograph pair mounted at a bent interior focal station and designed for seeing-limited (FOV: 4' × 4') imaging, long-slit spectroscopy, and multi-object spectroscopy utilizing cooled slit masks and diffraction limited (FOV: 0.5' × 0.5') imaging and long-slit spectroscopy. Strategic instruments under development for the remaining two combined focal stations include an interferometric cryogenic beam combiner with near-infrared and thermal-infrared instruments for Fizeau imaging and nulling interferometry (LBTI) and an optical bench near-infrared beam combiner utilizing multi-conjugate adaptive optics for high angular resolution and sensitivity (LINC-NIRVANA). In addition, a fiber-fed bench spectrograph (PEPSI) capable of ultra high resolution spectroscopy and spectropolarimetry (R = 40,000-300,000) will be available as a principal investigator instrument. The availability of all these instruments mounted simultaneously on the LBT permits unique science, flexible scheduling, and improved operational support.

MO-E-12A-01: Quantitative Imaging: Techniques, Applications, and Challenges

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

Jackson, E; Jeraj, R; McNitt-Gray, M

The first symposium in the Quantitative Imaging Track focused on the introduction of quantitative imaging (QI) by illustrating the potential of QI in diagnostic and therapeutic applications in research and patient care, highlighting key challenges in implementation of such QI applications, and reviewing QI efforts of selected national and international agencies and organizations, including the FDA, NCI, NIST, and RSNA. This second QI symposium will focus more specifically on the techniques, applications, and challenges of QI. The first talk of the session will focus on modalityagnostic challenges of QI, beginning with challenges of the development and implementation of QI applicationsmore » in single-center, single-vendor settings and progressing to the challenges encountered in the most general setting of multi-center, multi-vendor settings. The subsequent three talks will focus on specific QI challenges and opportunities in the modalityspecific settings of CT, PET/CT, and MR. Each talk will provide information on modality-specific QI techniques, applications, and challenges, including current efforts focused on solutions to such challenges. Learning Objectives: Understand key general challenges of QI application development and implementation, regardless of modality. Understand selected QI techniques and applications in CT, PET/CT, and MR. Understand challenges, and potential solutions for such challenges, for the applications presented for each modality.« less

High-intensity focused ultrasound ablation assisted using color Doppler imaging for the treatment of hepatocellular carcinomas.

PubMed

Fukuda, Hiroyuki; Numata, Kazushi; Nozaki, Akito; Kondo, Masaaki; Morimoto, Manabu; Maeda, Shin; Tanaka, Katsuaki; Ohto, Masao; Ito, Ryu; Ishibashi, Yoshiharu; Oshima, Noriyoshi; Ito, Ayao; Zhu, Hui; Wang, Zhi-Biao

2013-12-01

We evaluated the usefulness of color Doppler flow imaging to compensate for the inadequate resolution of the ultrasound (US) monitoring during high-intensity focused ultrasound (HIFU) for the treatment of hepatocellular carcinoma (HCC). US-guided HIFU ablation assisted using color Doppler flow imaging was performed in 11 patients with small HCC (<3 lesions, <3 cm in diameter). The HIFU system (Chongqing Haifu Tech) was used under US guidance. Color Doppler sonographic studies were performed using an HIFU 6150S US imaging unit system and a 2.7-MHz electronic convex probe. The color Doppler images were used because of the influence of multi-reflections and the emergence of hyperecho. In 1 of the 11 patients, multi-reflections were responsible for the poor visualization of the tumor. In 10 cases, the tumor was poorly visualized because of the emergence of a hyperecho. In these cases, the ability to identify the original tumor location on the monitor by referencing the color Doppler images of the portal vein and the hepatic vein was very useful. HIFU treatments were successfully performed in all 11 patients with the assistance of color Doppler imaging. Color Doppler imaging is useful for the treatment of HCC using HIFU, compensating for the occasionally poor visualization provided by B-mode conventional US imaging.

Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

PubMed

Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

2018-09-01

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

Investigation of Parallax Issues for Multi-Lens Multispectral Camera Band Co-Registration

NASA Astrophysics Data System (ADS)

Jhan, J. P.; Rau, J. Y.; Haala, N.; Cramer, M.

2017-08-01

The multi-lens multispectral cameras (MSCs), such as Micasense Rededge and Parrot Sequoia, can record multispectral information by each separated lenses. With their lightweight and small size, which making they are more suitable for mounting on an Unmanned Aerial System (UAS) to collect high spatial images for vegetation investigation. However, due to the multi-sensor geometry of multi-lens structure induces significant band misregistration effects in original image, performing band co-registration is necessary in order to obtain accurate spectral information. A robust and adaptive band-to-band image transform (RABBIT) is proposed to perform band co-registration of multi-lens MSCs. First is to obtain the camera rig information from camera system calibration, and utilizes the calibrated results for performing image transformation and lens distortion correction. Since the calibration uncertainty leads to different amount of systematic errors, the last step is to optimize the results in order to acquire a better co-registration accuracy. Due to the potential issues of parallax that will cause significant band misregistration effects when images are closer to the targets, four datasets thus acquired from Rededge and Sequoia were applied to evaluate the performance of RABBIT, including aerial and close-range imagery. From the results of aerial images, it shows that RABBIT can achieve sub-pixel accuracy level that is suitable for the band co-registration purpose of any multi-lens MSC. In addition, the results of close-range images also has same performance, if we focus on the band co-registration on specific target for 3D modelling, or when the target has equal distance to the camera.

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

Multi-Contrast Imaging and Digital Refocusing on a Mobile Microscope with a Domed LED Array.

PubMed

Phillips, Zachary F; D'Ambrosio, Michael V; Tian, Lei; Rulison, Jared J; Patel, Hurshal S; Sadras, Nitin; Gande, Aditya V; Switz, Neil A; Fletcher, Daniel A; Waller, Laura

2015-01-01

We demonstrate the design and application of an add-on device for improving the diagnostic and research capabilities of CellScope--a low-cost, smartphone-based point-of-care microscope. We replace the single LED illumination of the original CellScope with a programmable domed LED array. By leveraging recent advances in computational illumination, this new device enables simultaneous multi-contrast imaging with brightfield, darkfield, and phase imaging modes. Further, we scan through illumination angles to capture lightfield datasets, which can be used to recover 3D intensity and phase images without any hardware changes. This digital refocusing procedure can be used for either 3D imaging or software-only focus correction, reducing the need for precise mechanical focusing during field experiments. All acquisition and processing is performed on the mobile phone and controlled through a smartphone application, making the computational microscope compact and portable. Using multiple samples and different objective magnifications, we demonstrate that the performance of our device is comparable to that of a commercial microscope. This unique device platform extends the field imaging capabilities of CellScope, opening up new clinical and research possibilities.

Multi-Contrast Imaging and Digital Refocusing on a Mobile Microscope with a Domed LED Array

PubMed Central

Phillips, Zachary F.; D'Ambrosio, Michael V.; Tian, Lei; Rulison, Jared J.; Patel, Hurshal S.; Sadras, Nitin; Gande, Aditya V.; Switz, Neil A.; Fletcher, Daniel A.; Waller, Laura

2015-01-01

We demonstrate the design and application of an add-on device for improving the diagnostic and research capabilities of CellScope—a low-cost, smartphone-based point-of-care microscope. We replace the single LED illumination of the original CellScope with a programmable domed LED array. By leveraging recent advances in computational illumination, this new device enables simultaneous multi-contrast imaging with brightfield, darkfield, and phase imaging modes. Further, we scan through illumination angles to capture lightfield datasets, which can be used to recover 3D intensity and phase images without any hardware changes. This digital refocusing procedure can be used for either 3D imaging or software-only focus correction, reducing the need for precise mechanical focusing during field experiments. All acquisition and processing is performed on the mobile phone and controlled through a smartphone application, making the computational microscope compact and portable. Using multiple samples and different objective magnifications, we demonstrate that the performance of our device is comparable to that of a commercial microscope. This unique device platform extends the field imaging capabilities of CellScope, opening up new clinical and research possibilities. PMID:25969980

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.

Extracellular Bio-imaging of Acetylcholine-stimulated PC12 Cells Using a Calcium and Potassium Multi-ion Image Sensor.

PubMed

Matsuba, Sota; Kato, Ryo; Okumura, Koichi; Sawada, Kazuaki; Hattori, Toshiaki

2018-01-01

In biochemistry, Ca 2+ and K + play essential roles to control signal transduction. Much interest has been focused on ion-imaging, which facilitates understanding of their ion flux dynamics. In this paper, we report a calcium and potassium multi-ion image sensor and its application to living cells (PC12). The multi-ion sensor had two selective plasticized poly(vinyl chloride) membranes containing ionophores. Each region on the sensor responded to only the corresponding ion. The multi-ion sensor has many advantages including not only label-free and real-time measurement but also simultaneous detection of Ca 2+ and K + . Cultured PC12 cells treated with nerve growth factor were prepared, and a practical observation for the cells was conducted with the sensor. After the PC12 cells were stimulated by acetylcholine, only the extracellular Ca 2+ concentration increased while there was no increase in the extracellular K + concentration. Through the practical observation, we demonstrated that the sensor was helpful for analyzing the cell events with changing Ca 2+ and/or K + concentration.

Coherent beam control through inhomogeneous media in multi-photon microscopy

NASA Astrophysics Data System (ADS)

Paudel, Hari Prasad

Multi-photon fluorescence microscopy has become a primary tool for high-resolution deep tissue imaging because of its sensitivity to ballistic excitation photons in comparison to scattered excitation photons. The imaging depth of multi-photon microscopes in tissue imaging is limited primarily by background fluorescence that is generated by scattered light due to the random fluctuations in refractive index inside the media, and by reduced intensity in the ballistic focal volume due to aberrations within the tissue and at its interface. We built two multi-photon adaptive optics (AO) correction systems, one for combating scattering and aberration problems, and another for compensating interface aberrations. For scattering correction a MEMS segmented deformable mirror (SDM) was inserted at a plane conjugate to the objective back-pupil plane. The SDM can pre-compensate for light scattering by coherent combination of the scattered light to make an apparent focus even at a depths where negligible ballistic light remains (i.e. ballistic limit). This problem was approached by investigating the spatial and temporal focusing characteristics of a broad-band light source through strongly scattering media. A new model was developed for coherent focus enhancement through or inside the strongly media based on the initial speckle contrast. A layer of fluorescent beads under a mouse skull was imaged using an iterative coherent beam control method in the prototype two-photon microscope to demonstrate the technique. We also adapted an AO correction system to an existing in three-photon microscope in a collaborator lab at Cornell University. In the second AO correction approach a continuous deformable mirror (CDM) is placed at a plane conjugate to the plane of an interface aberration. We demonstrated that this "Conjugate AO" technique yields a large field-of-view (FOV) advantage in comparison to Pupil AO. Further, we showed that the extended FOV in conjugate AO is maintained over a relatively large axial misalignment of the conjugate planes of the CDM and the aberrating interface. This dissertation advances the field of microscopy by providing new models and techniques for imaging deeply within strongly scattering tissue, and by describing new adaptive optics approaches to extending imaging FOV due to sample aberrations.

Skin condition measurement by using multispectral imaging system (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jung, Geunho; Kim, Sungchul; Kim, Jae Gwan

2017-02-01

There are a number of commercially available low level light therapy (LLLT) devices in a market, and face whitening or wrinkle reduction is one of targets in LLLT. The facial improvement could be known simply by visual observation of face, but it cannot provide either quantitative data or recognize a subtle change. Clinical diagnostic instruments such as mexameter can provide a quantitative data, but it costs too high for home users. Therefore, we designed a low cost multi-spectral imaging device by adding additional LEDs (470nm, 640nm, white LED, 905nm) to a commercial USB microscope which has two LEDs (395nm, 940nm) as light sources. Among various LLLT skin treatments, we focused on getting melanin and wrinkle information. For melanin index measurements, multi-spectral images of nevus were acquired and melanin index values from color image (conventional method) and from multi-spectral images were compared. The results showed that multi-spectral analysis of melanin index can visualize nevus with a different depth and concentration. A cross section of wrinkle on skin resembles a wedge which can be a source of high frequency components when the skin image is Fourier transformed into a spatial frequency domain map. In that case, the entropy value of the spatial frequency map can represent the frequency distribution which is related with the amount and thickness of wrinkle. Entropy values from multi-spectral images can potentially separate the percentage of thin and shallow wrinkle from thick and deep wrinkle. From the results, we found that this low cost multi-spectral imaging system could be beneficial for home users of LLLT by providing the treatment efficacy in a quantitative way.

Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

NASA Astrophysics Data System (ADS)

Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

2017-12-01

This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

The year 2012 in the European Heart Journal-Cardiovascular Imaging: Part I.

PubMed

Edvardsen, Thor; Plein, Sven; Saraste, Antti; Knuuti, Juhani; Maurer, Gerald; Lancellotti, Patrizio

2013-06-01

The new multi-modality cardiovascular imaging journal, European Heart Journal - Cardiovascular Imaging, was started in 2012. During its first year, the new Journal has published an impressive collection of cardiovascular studies utilizing all cardiovascular imaging modalities. We will summarize the most important studies from its first year in two articles. The present 'Part I' of the review will focus on studies in myocardial function, myocardial ischaemia, and emerging techniques in cardiovascular imaging.

An overview of instrumentation for the Large Binocular Telescope

NASA Astrophysics Data System (ADS)

Wagner, R. Mark

2010-07-01

An overview of instrumentation for the Large Binocular Telescope is presented. Optical instrumentation includes the Large Binocular Camera (LBC), a pair of wide-field (27 × 27) mosaic CCD imagers at the prime focus, and the Multi-Object Double Spectrograph (MODS), a pair of dual-beam blue-red optimized long-slit spectrographs mounted at the straight-through F/15 Gregorian focus incorporating multiple slit masks for multi-object spectroscopy over a 6 field and spectral resolutions of up to 8000. Infrared instrumentation includes the LBT Near-IR Spectroscopic Utility with Camera and Integral Field Unit for Extragalactic Research (LUCIFER), a modular near-infrared (0.9-2.5 μm) imager and spectrograph pair mounted at a bent interior focal station and designed for seeing-limited (FOV: 4 × 4) imaging, long-slit spectroscopy, and multi-object spectroscopy utilizing cooled slit masks and diffraction limited (FOV: 0.5 × 0.5) imaging and long-slit spectroscopy. Strategic instruments under development for the remaining two combined focal stations include an interferometric cryogenic beam combiner with near-infrared and thermal-infrared instruments for Fizeau imaging and nulling interferometry (LBTI) and an optical bench near-infrared beam combiner utilizing multi-conjugate adaptive optics for high angular resolution and sensitivity (LINC-NIRVANA). In addition, a fiber-fed bench spectrograph (PEPSI) capable of ultra high resolution spectroscopy and spectropolarimetry (R = 40,000-300,000) will be available as a principal investigator instrument. The availability of all these instruments mounted simultaneously on the LBT permits unique science, flexible scheduling, and improved operational support. Over the past two years the LBC and the first LUCIFER instrument have been brought into routine scientific operation and MODS1 commissioning is set to begin in the fall of 2010.

MO-DE-202-01: Image-Guided Focused Ultrasound Surgery and Therapy

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

Farahani, K.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

Targeting Neuronal-like Metabolism of Metastatic Tumor Cells as a Novel Therapy for Breast Cancer Brain Metastasis

DTIC Science & Technology

2017-03-01

Contribution to Project: Ian primarily focuses on developing tissue imaging pipeline and perform imaging data analysis . Funding Support: Partially...3D ReconsTruction), a multi-faceted image analysis pipeline , permitting quantitative interrogation of functional implications of heterogeneous... analysis pipeline , to observe and quantify phenotypic metastatic landscape heterogeneity in situ with spatial and molecular resolution. Our implementation

Network Access to Visual Information: A Study of Costs and Uses.

ERIC Educational Resources Information Center

Besser, Howard

This paper summarizes a subset of the findings of a study of digital image distribution that focused on the Museum Educational Site Licensing (MESL) project--the first large-scale multi-institutional project to explore digital delivery of art images and accompanying text/metadata from disparate sources. This Mellon Foundation-sponsored study…

Compact multi-band fluorescent microscope with an electrically tunable lens for autofocusing

PubMed Central

Wang, Zhaojun; Lei, Ming; Yao, Baoli; Cai, Yanan; Liang, Yansheng; Yang, Yanlong; Yang, Xibin; Li, Hui; Xiong, Daxi

2015-01-01

Autofocusing is a routine technique in redressing focus drift that occurs in time-lapse microscopic image acquisition. To date, most automatic microscopes are designed on the distance detection scheme to fulfill the autofocusing operation, which may suffer from the low contrast of the reflected signal due to the refractive index mismatch at the water/glass interface. To achieve high autofocusing speed with minimal motion artifacts, we developed a compact multi-band fluorescent microscope with an electrically tunable lens (ETL) device for autofocusing. A modified searching algorithm based on equidistant scanning and curve fitting is proposed, which no longer requires a single-peak focus curve and then efficiently restrains the impact of external disturbance. This technique enables us to achieve an autofocusing time of down to 170 ms and the reproductivity of over 97%. The imaging head of the microscope has dimensions of 12 cm × 12 cm × 6 cm. This portable instrument can easily fit inside standard incubators for real-time imaging of living specimens. PMID:26601001

Enhancing the imaging quality and fabrication efficiency of bionic compound eyes using a sandwich structure

NASA Astrophysics Data System (ADS)

Luo, Jiasai; Guo, Yongcai; Wang, Xin

2018-06-01

This paper puts forward a novel method for fabrication of sandwich-structured BCE using a detachable micro-hole array (MHA) prepared by 3D printing. Compared with most traditional methods, 3D printing enables effective implementation of direct micro-fabrication for curved BCE without the pattern transfer and substrate reshaping process. This 3D fabrication method allows rapid fabrication of the curved BCE and automatic assembly of the detachable MHA using a custom-built mold under negative pressure. The formation of a multi-focusing micro-lens array (MLA) was realized by adjusting the parameters of the curved detachable MHA. The imaging performance was effectively enhanced by the sandwich structure that consist of the multi-focusing MLA, the outer detachable MHA and the inner solidified MHA. This method is suitable for mass production due to its advantages as a time-saving, cost-effective and simple process. Optical design software was used to analyze the optical properties, and an imaging simulation was performed.

Photometric Calibration and Image Stitching for a Large Field of View Multi-Camera System

PubMed Central

Lu, Yu; Wang, Keyi; Fan, Gongshu

2016-01-01

A new compact large field of view (FOV) multi-camera system is introduced. The camera is based on seven tiny complementary metal-oxide-semiconductor sensor modules covering over 160° × 160° FOV. Although image stitching has been studied extensively, sensor and lens differences have not been considered in previous multi-camera devices. In this study, we have calibrated the photometric characteristics of the multi-camera device. Lenses were not mounted on the sensor in the process of radiometric response calibration to eliminate the influence of the focusing effect of uniform light from an integrating sphere. Linearity range of the radiometric response, non-linearity response characteristics, sensitivity, and dark current of the camera response function are presented. The R, G, and B channels have different responses for the same illuminance. Vignetting artifact patterns have been tested. The actual luminance of the object is retrieved by sensor calibration results, and is used to blend images to make panoramas reflect the objective luminance more objectively. This compensates for the limitation of stitching images that are more realistic only through the smoothing method. The dynamic range limitation of can be resolved by using multiple cameras that cover a large field of view instead of a single image sensor with a wide-angle lens. The dynamic range is expanded by 48-fold in this system. We can obtain seven images in one shot with this multi-camera system, at 13 frames per second. PMID:27077857

Multi-Sensor Registration of Earth Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Cole-Rhodes, Arlene; Eastman, Roger; Johnson, Kisha; Morisette, Jeffrey; Netanyahu, Nathan S.; Stone, Harold S.; Zavorin, Ilya; Zukor, Dorothy (Technical Monitor)

2001-01-01

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

Multi-contrast light profile microscopy for the depth-resolved imaging of the properties of multi-ply thin films.

PubMed

Power, J F

2009-06-01

Light profile microscopy (LPM) is a direct method for the spectral depth imaging of thin film cross-sections on the micrometer scale. LPM uses a perpendicular viewing configuration that directly images a source beam propagated through a thin film. Images are formed in dark field contrast, which is highly sensitive to subtle interfacial structures that are invisible to reference methods. The independent focusing of illumination and imaging systems allows multiple registered optical sources to be hosted on a single platform. These features make LPM a powerful multi-contrast (MC) imaging technique, demonstrated in this work with six modes of imaging in a single instrument, based on (1) broad-band elastic scatter; (2) laser excited wideband luminescence; (3) coherent elastic scatter; (4) Raman scatter (three channels with RGB illumination); (5) wavelength resolved luminescence; and (6) spectral broadband scatter, resolved in immediate succession. MC-LPM integrates Raman images with a wider optical and morphological picture of the sample than prior art microprobes. Currently, MC-LPM resolves images at an effective spectral resolution better than 9 cm(-1), at a spatial resolution approaching 1 microm, with optics that operate in air at half the maximum numerical aperture of the prior art microprobes.

Multi-photon vertical cross-sectional imaging with a dynamically-balanced thin-film PZT z-axis microactuator.

PubMed

Choi, Jongsoo; Duan, Xiyu; Li, Haijun; Wang, Thomas D; Oldham, Kenn R

2017-10-01

Use of a thin-film piezoelectric microactuator for axial scanning during multi-photon vertical cross-sectional imaging is described. The actuator uses thin-film lead-zirconate-titanate (PZT) to generate upward displacement of a central mirror platform, micro-machined from a silicon-on-insulator (SOI) wafer to dimensions compatible with endoscopic imaging instruments. Device modeling in this paper focuses on existence of frequencies near device resonance producing vertical motion with minimal off-axis tilt even in the presence of multiple vibration modes and non-uniformity in fabrication outcomes. Operation near rear resonance permits large stroke lengths at low voltages relative to other vertical microactuators. Highly uniform vertical motion of the mirror platform is a key requirement for vertical cross-sectional imaging in the remote scan architecture being used for multi-photon instrument prototyping. The stage is installed in a benchtop testbed in combination with an electrostatic mirror that performs in-plane scanning. Vertical sectional images are acquired from 15 μm diameter beads and excised mouse colon tissue.

MISR INTEX-B Products

Atmospheric Science Data Center

2016-11-25

... scales and assess their impact on air quality and climate. Phase B will be performed March 1-31, 2006 and it will focus on Mexico City pollution outflow. The Multi-angle Imaging SpectroRadiometer (MISR) team ...

Calibration for single multi-mode fiber digital scanning microscopy imaging system

NASA Astrophysics Data System (ADS)

Yin, Zhe; Liu, Guodong; Liu, Bingguo; Gan, Yu; Zhuang, Zhitao; Chen, Fengdong

2015-11-01

Single multimode fiber (MMF) digital scanning imaging system is a development tendency of modern endoscope. We concentrate on the calibration method of the imaging system. Calibration method comprises two processes, forming scanning focused spots and calibrating the couple factors varied with positions. Adaptive parallel coordinate algorithm (APC) is adopted to form the focused spots at the multimode fiber (MMF) output. Compare with other algorithm, APC contains many merits, i.e. rapid speed, small amount calculations and no iterations. The ratio of the optics power captured by MMF to the intensity of the focused spots is called couple factor. We setup the calibration experimental system to form the scanning focused spots and calculate the couple factors for different object positions. The experimental result the couple factor is higher in the center than the edge.

Omni-focal refractive focus correction technology as a substitute for bi/multi-focal intraocular lenses, contact lenses, and spectacles

NASA Astrophysics Data System (ADS)

Ben Yaish, Shai; Zlotnik, Alex; Raveh, Ido; Yehezkel, Oren; Belkin, Michael; Lahav, Karen; Zalevsky, Zeev

2009-02-01

We present novel technology for extension in depth of focus of imaging lenses for use in ophthalmic lenses correcting myopia, hyperopia with regular/irregular astigmatism and presbyopia. This technology produces continuous focus without appreciable loss of energy. It is incorporated as a coating or engraving on the surface for spectacles, contact or intraocular lenses. It was fabricated and tested in simulations and in clinical trials. From the various testing this technology seems to provide a satisfactory single-lens solution. Obtained performance is apparently better than those of existing multi/bifocal lenses and it is modular enough to provide solution to various ophthalmic applications.

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

Direct fusion of geostationary meteorological satellite visible and infrared images based on thermal physical properties.

PubMed

Han, Lei; Wulie, Buzha; Yang, Yiling; Wang, Hongqing

2015-01-05

This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion.

Direct Fusion of Geostationary Meteorological Satellite Visible and Infrared Images Based on Thermal Physical Properties

PubMed Central

Han, Lei; Wulie, Buzha; Yang, Yiling; Wang, Hongqing

2015-01-01

This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion. PMID:25569749

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

Matsutani, Takaomi; Taya, Masaki; Ikuta, Takashi

A parallel image detection system using an annular pupil for electron optics were developed to realize an increase in the depth of focus, aberration-free imaging and separation of amplitude and phase images under scanning transmission electron microscopy (STEM). Apertures for annular pupils able to suppress high-energy electron scattering were developed using a focused ion beam (FIB) technique. The annular apertures were designed with outer diameter of oe 40 {mu}m and inner diameter of oe32 {mu}m. A taper angle varying from 20 deg. to 1 deg. was applied to the slits of the annular apertures to suppress the influence of high-energymore » electron scattering. Each azimuth angle image on scintillator was detected by a multi-anode photomultiplier tube assembly through 40 optical fibers bundled in a ring shape. To focus the image appearing on the scintillator on optical fibers, an optical lens relay system attached with CCD camera was developed. The system enables the taking of 40 images simultaneously from different scattered directions.« less

Development of solid tunable optics for ultra-miniature imaging systems

NASA Astrophysics Data System (ADS)

Yongchao, Zou

This thesis focuses on the optimal design, fabrication and testing of solid tunable optics and exploring their applications in miniature imaging systems. It starts with the numerical modelling of such lenses, followed by the optimum design method and alignment tolerance analysis. A miniature solid tunable lens driven by a piezo actuator is then developed. To solve the problem of limited maximum optical power and tuning range in conventional lens designs, a novel multi-element solid tunable lens is proposed and developed. Inspired by the Alvarez principle, a novel miniature solid tunable dual-focus lens, which is designed using freeform surfaces and driven by one micro-electro-mechanical-systems (MEMS) rotary actuator, is demonstrated. To explore the applications of these miniature solid tunable lenses, a miniature adjustable-focus endoscope and one compact adjustable-focus camera module are developed. The adjustable-focus capability of these two miniature imaging systems is fully proved by electrically focusing targets placed at different positions.

Multi-sensor millimeter-wave system for hidden objects detection by non-collaborative screening

NASA Astrophysics Data System (ADS)

Zouaoui, Rhalem; Czarny, Romain; Diaz, Frédéric; Khy, Antoine; Lamarque, Thierry

2011-05-01

In this work, we present the development of a multi-sensor system for the detection of objects concealed under clothes using passive and active millimeter-wave (mmW) technologies. This study concerns both the optimization of a commercial passive mmW imager at 94 GHz using a phase mask and the development of an active mmW detector at 77 GHz based on synthetic aperture radar (SAR). A first wide-field inspection is done by the passive imager while the person is walking. If a suspicious area is detected, the active imager is switched-on and focused on this area in order to obtain more accurate data (shape of the object, nature of the material ...).

Automatic Registration of GF4 Pms: a High Resolution Multi-Spectral Sensor on Board a Satellite on Geostationary Orbit

NASA Astrophysics Data System (ADS)

Gao, M.; Li, J.

2018-04-01

Geometric correction is an important preprocessing process in the application of GF4 PMS image. The method of geometric correction that is based on the manual selection of geometric control points is time-consuming and laborious. The more common method, based on a reference image, is automatic image registration. This method involves several steps and parameters. For the multi-spectral sensor GF4 PMS, it is necessary for us to identify the best combination of parameters and steps. This study mainly focuses on the following issues: necessity of Rational Polynomial Coefficients (RPC) correction before automatic registration, base band in the automatic registration and configuration of GF4 PMS spatial resolution.

Multi-parametric monitoring and assessment of high-intensity focused ultrasound (HIFU) boiling by harmonic motion imaging for focused ultrasound (HMIFU): an ex vivo feasibility study

NASA Astrophysics Data System (ADS)

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.

2014-03-01

Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.

Multi-parametric monitoring and assessment of High Intensity Focused Ultrasound (HIFU) boiling by Harmonic Motion Imaging for Focused Ultrasound (HMIFU): An ex vivo feasibility study

PubMed Central

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E.

2014-01-01

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase-shift during high energy HIFU treatment with tissue boiling. Forty three (n=43) thermal lesions were formed in ex vivo canine liver specimens (n=28). Two dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10-s, 20-s and 30-s HIFU durations at three different acoustic powers of 8, 10, and 11W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and Passive Cavitation Detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δφ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite unpredictable changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property change throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes. PMID:24556974

Multi-parametric monitoring and assessment of high-intensity focused ultrasound (HIFU) boiling by harmonic motion imaging for focused ultrasound (HMIFU): an ex vivo feasibility study.

PubMed

Hou, Gary Y; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa E

2014-03-07

Harmonic motion imaging for focused ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and change in relative phase shift during high energy HIFU treatment with tissue boiling. Forty three (n = 43) thermal lesions were formed in ex vivo canine liver specimens (n = 28). Two-dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10 s, 20 s and 30 s HIFU durations at three different acoustic powers of 8, 10, and 11 W, which were selected and verified as treatment parameters capable of inducing boiling using both thermocouple and passive cavitation detection (PCD) measurements. Although a steady decrease in the displacement, compressive strain, and relative change in the focal phase shift (Δϕ) were obtained in numerous cases, indicating an overall increase in relative stiffness, the study outcomes also showed that during boiling, a reverse lesion-to-background displacement contrast was detected, indicating potential change in tissue absorption, geometrical change and/or, mechanical gelatification or pulverization. Following treatment, corresponding 2D HMI displacement images of the thermal lesions also mapped consistent discrepancy in the lesion-to-background displacement contrast. Despite the expectedly chaotic changes in acoustic properties with boiling, the relative change in phase shift showed a consistent decrease, indicating its robustness to monitor biomechanical properties independent of the acoustic property changes throughout the HIFU treatment. In addition, the 2D HMI displacement images confirmed and indicated the increase in the thermal lesion size with treatment duration, which was validated against pathology. In conclusion, multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU boiling, some of which were independent of the acoustic parameter changes.

Development of methods for the analysis of multi-mode TFM images

NASA Astrophysics Data System (ADS)

Sy, K.; Bredif, P.; Iakovleva, E.; Roy, O.; Lesselier, D.

2018-05-01

TFM (Total Focusing Method) is an advanced post-processing imaging algorithm of ultrasonic array data that shows good potential in defect detection and characterization. It can be employed using an infinite number of paths between transducer and focusing point. Depending upon the geometry and the characteristics of the defect in a given part, there are not the same modes that are appropriate for the defect reconstruction. Furthermore, non-physical indications can be observed, prone to misinterpretation. These imaging artifacts are due to the coexistence of several contributions involving several modes of propagation and interactions with possible defects and/or the geometry of the part. Two methods for filtering artifacts and reducing the number of TFM images are developed and illustrated.

Multi-modality molecular imaging: pre-clinical laboratory configuration

NASA Astrophysics Data System (ADS)

Wu, Yanjun; Wellen, Jeremy W.; Sarkar, Susanta K.

2006-02-01

In recent years, the prevalence of in vivo molecular imaging applications has rapidly increased. Here we report on the construction of a multi-modality imaging facility in a pharmaceutical setting that is expected to further advance existing capabilities for in vivo imaging of drug distribution and the interaction with their target. The imaging instrumentation in our facility includes a microPET scanner, a four wavelength time-domain optical imaging scanner, a 9.4T/30cm MRI scanner and a SPECT/X-ray CT scanner. An electronics shop and a computer room dedicated to image analysis are additional features of the facility. The layout of the facility was designed with a central animal preparation room surrounded by separate laboratory rooms for each of the major imaging modalities to accommodate the work-flow of simultaneous in vivo imaging experiments. This report will focus on the design of and anticipated applications for our microPET and optical imaging laboratory spaces. Additionally, we will discuss efforts to maximize the daily throughput of animal scans through development of efficient experimental work-flows and the use of multiple animals in a single scanning session.

Retinal projection type super multi-view head-mounted display

NASA Astrophysics Data System (ADS)

Takahashi, Hideya; Ito, Yutaka; Nakata, Seigo; Yamada, Kenji

2014-02-01

We propose a retinal projection type super multi-view head-mounted display (HMD). The smooth motion parallax provided by the super multi-view technique enables a precise superposition of virtual 3D images on the real scene. Moreover, if a viewer focuses one's eyes on the displayed 3D image, the stimulus for the accommodation of the human eye is produced naturally. Therefore, although proposed HMD is a monocular HMD, it provides observers with natural 3D images. The proposed HMD consists of an image projection optical system and a holographic optical element (HOE). The HOE is used as a combiner, and also works as a condenser lens to implement the Maxwellian view. Some parallax images are projected onto the HOE, and converged on the pupil, and then projected onto the retina. In order to verify the effectiveness of the proposed HMD, we constructed the prototype HMD. In the prototype HMD, the number of parallax images and the number of convergent points on the pupil is three. The distance between adjacent convergent points is 2 mm. We displayed virtual images at the distance from 20 cm to 200 cm in front of the pupil, and confirmed the accommodation. This paper describes the principle of proposed HMD, and also describes the experimental result.

The Influence of Organizational Image on College Selection: What Students Seek in Institutions of Higher Education

ERIC Educational Resources Information Center

Pampaloni, Andrea M.

2010-01-01

Colleges and universities rely on their image to attract new members. This study focuses on the decision-making process of students preparing to apply to college. High school students were surveyed at college open houses to identify the factors most influential to their college application decision-making. A multi-methods analysis found that…

X-ray Diffraction and Multi-Frame Phase Contrast Imaging Diagnostics for IMPULSE at the Advanced Photon Source

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

Iverson, Adam; Carlson, Carl; Young, Jason

2013-07-08

The diagnostic needs of any dynamic loading platform present unique technical challenges that must be addressed in order to accurately measure in situ material properties in an extreme environment. The IMPULSE platform (IMPact system for Ultrafast Synchrotron Experiments) at the Advanced Photon Source (APS) is no exception and, in fact, may be more challenging, as the imaging diagnostics must be synchronized to both the experiment and the 60 ps wide x-ray bunches produced at APS. The technical challenges of time-resolved x-ray diffraction imaging and high-resolution multi-frame phase contrast imaging (PCI) are described in this paper. Example data from recent IMPULSEmore » experiments are shown to illustrate the advances and evolution of these diagnostics with a focus on comparing the performance of two intensified CCD cameras and their suitability for multi-frame PCI. The continued development of these diagnostics is fundamentally important to IMPULSE and many other loading platforms and will benefit future facilities such as the Dynamic Compression Sector at APS and MaRIE at Los Alamos National Laboratory.« less

Navy-wide Personnel Survey (NPS) 2005: Summary of Survey Results

DTIC Science & Technology

2008-11-01

Personnel Survey Strategy. The NPS focuses on quality of work life topics including satisfaction with Navy life, work climate, morale, organizational...commitment, leadership, communication, job security, Navy image, fairness, detailing, duty assignments, job satisfaction , career development...Ph.D. Director v Summary The Navy Personnel Survey (NPS) is a multi-faceted survey that focuses on topics such as satisfaction with Navy

Technical overview of the millimeter-wave imaging reflectometer on the DIII-D tokamak (invited)

DOE PAGES

Muscatello, Christopher M.; Domier, Calvin W.; Hu, Xing; ...

2014-07-22

The two-dimensional mm-wave imaging reflectometer (MIR) on DIII-D is a multi-faceted device for diagnosing electron density fluctuations in fusion plasmas. Its multi-channel, multi-frequency capabilities and high sensitivity permit visualization and quantitative diagnosis of density perturbations, including correlation length, wavenumber, mode propagation velocity, and dispersion. The two-dimensional capabilities of MIR are made possible with twelve vertically separated sightlines and four-frequency operation (corresponding to four radial channels). The 48-channel DIII-D MIR system has a tunable source that can be stepped in 500 µs increments over a range of 56 to 74 GHz. An innovative optical design keeps both on-axis and off-axis channelsmore » focused at the cutoff surface, permitting imaging over an extended poloidal region. As a result, the integrity of the MIR optical design is confirmed by comparing Gaussian beam calculations to laboratory measurements of the transmitter beam pattern and receiver antenna patterns.« less

Viewpoints on Medical Image Processing: From Science to Application

PubMed Central

Deserno (né Lehmann), Thomas M.; Handels, Heinz; Maier-Hein (né Fritzsche), Klaus H.; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-01-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment. PMID:24078804

Viewpoints on Medical Image Processing: From Science to Application.

PubMed

Deserno Né Lehmann, Thomas M; Handels, Heinz; Maier-Hein Né Fritzsche, Klaus H; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-05-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment.

Arcsecond and Sub-arcsedond Imaging with X-ray Multi-Image Interferometer and Imager for (very) small sattelites

NASA Astrophysics Data System (ADS)

Hayashida, K.; Kawabata, T.; Nakajima, H.; Inoue, S.; Tsunemi, H.

2017-10-01

The best angular resolution of 0.5 arcsec is realized with the X-ray mirror onborad the Chandra satellite. Nevertheless, further better or comparable resolution is anticipated to be difficult in near future. In fact, the goal of ATHENA telescope is 5 arcsec in the angular resolution. We propose a new type of X-ray interferometer consisting simply of an X-ray absorption grating and an X-ray spectral imaging detector, such as X-ray CCDs or new generation CMOS detectors, by stacking the multi images created with the Talbot interferenece (Hayashida et al. 2016). This system, now we call Multi Image X-ray Interferometer Module (MIXIM) enables arcseconds resolution with very small satellites of 50cm size, and sub-arcseconds resolution with small sattellites. We have performed ground experiments, in which a micro-focus X-ray source, grating with pitch of 4.8μm, and 30 μm pixel detector placed about 1m from the source. We obtained the self-image (interferometirc fringe) of the grating for wide band pass around 10keV. This result corresponds to about 2 arcsec resolution for parrallel beam incidence. The MIXIM is usefull for high angular resolution imaging of relatively bright sources. Search for super massive black holes and resolving AGN torus would be the targets of this system.

An efficient sampling algorithm for uncertain abnormal data detection in biomedical image processing and disease prediction.

PubMed

Liu, Fei; Zhang, Xi; Jia, Yan

2015-01-01

In this paper, we propose a computer information processing algorithm that can be used for biomedical image processing and disease prediction. A biomedical image is considered a data object in a multi-dimensional space. Each dimension is a feature that can be used for disease diagnosis. We introduce a new concept of the top (k1,k2) outlier. It can be used to detect abnormal data objects in the multi-dimensional space. This technique focuses on uncertain space, where each data object has several possible instances with distinct probabilities. We design an efficient sampling algorithm for the top (k1,k2) outlier in uncertain space. Some improvement techniques are used for acceleration. Experiments show our methods' high accuracy and high efficiency.

Commissioning Results on the JWST Testbed Telescope

NASA Technical Reports Server (NTRS)

Dean, Bruce H.; Acton, D. Scott

2006-01-01

The one-meter 18 segment JWST Testbed Telescope (TBT) has been developed at Ball Aerospace to facilitate commissioning operations for the JWST Observatory. Eight different commissioning activities were tested on the TBT: telescope focus sweep, segment ID and Search, image array, global alignment, image stacking, coarse phasing, fine phasing, and multi-field phasing. This paper describes recent commissioning results from experiments performed on the TBT.

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging

PubMed Central

Cua, Michelle; Wahl, Daniel J.; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J.; Jian, Yifan; Sarunic, Marinko V.

2016-01-01

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems. PMID:27599635

Coherence-Gated Sensorless Adaptive Optics Multiphoton Retinal Imaging.

PubMed

Cua, Michelle; Wahl, Daniel J; Zhao, Yuan; Lee, Sujin; Bonora, Stefano; Zawadzki, Robert J; Jian, Yifan; Sarunic, Marinko V

2016-09-07

Multiphoton microscopy enables imaging deep into scattering tissues. The efficient generation of non-linear optical effects is related to both the pulse duration (typically on the order of femtoseconds) and the size of the focused spot. Aberrations introduced by refractive index inhomogeneity in the sample distort the wavefront and enlarge the focal spot, which reduces the multiphoton signal. Traditional approaches to adaptive optics wavefront correction are not effective in thick or multi-layered scattering media. In this report, we present sensorless adaptive optics (SAO) using low-coherence interferometric detection of the excitation light for depth-resolved aberration correction of two-photon excited fluorescence (TPEF) in biological tissue. We demonstrate coherence-gated SAO TPEF using a transmissive multi-actuator adaptive lens for in vivo imaging in a mouse retina. This configuration has significant potential for reducing the laser power required for adaptive optics multiphoton imaging, and for facilitating integration with existing systems.

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. |

Super-resolution mapping using multi-viewing CHRIS/PROBA data

NASA Astrophysics Data System (ADS)

Dwivedi, Manish; Kumar, Vinay

2016-04-01

High-spatial resolution Remote Sensing (RS) data provides detailed information which ensures high-definition visual image analysis of earth surface features. These data sets also support improved information extraction capabilities at a fine scale. In order to improve the spatial resolution of coarser resolution RS data, the Super Resolution Reconstruction (SRR) technique has become widely acknowledged which focused on multi-angular image sequences. In this study multi-angle CHRIS/PROBA data of Kutch area is used for SR image reconstruction to enhance the spatial resolution from 18 m to 6m in the hope to obtain a better land cover classification. Various SR approaches like Projection onto Convex Sets (POCS), Robust, Iterative Back Projection (IBP), Non-Uniform Interpolation and Structure-Adaptive Normalized Convolution (SANC) chosen for this study. Subjective assessment through visual interpretation shows substantial improvement in land cover details. Quantitative measures including peak signal to noise ratio and structural similarity are used for the evaluation of the image quality. It was observed that SANC SR technique using Vandewalle algorithm for the low resolution image registration outperformed the other techniques. After that SVM based classifier is used for the classification of SRR and data resampled to 6m spatial resolution using bi-cubic interpolation. A comparative analysis is carried out between classified data of bicubic interpolated and SR derived images of CHRIS/PROBA and SR derived classified data have shown a significant improvement of 10-12% in the overall accuracy. The results demonstrated that SR methods is able to improve spatial detail of multi-angle images as well as the classification accuracy.

NICMOS status and plans

NASA Technical Reports Server (NTRS)

Thompson, Rodger I.

1997-01-01

Near Infrared Camera and Multi-Object Spectrometer (NICMOS) has been in orbit for about 8 months. This is a report on its current status and future plans. Also included are some comments on particular aspects of data analysis concerning dark subtraction, shading, and removal of cosmic rays. At present NICMOS provides excellent images of high scientific content. Most of the observations utilize cameras 1 and 2 which are in excellent focus. Camera 3 is not yet within the range of the focus adjustment mechanism, but its current images are still quite excellent. In this paper we will present the status of various aspects of the NICMOS instrument.

Retinal axial focusing and multi-layer imaging with a liquid crystal adaptive optics camera

NASA Astrophysics Data System (ADS)

Liu, Rui-Xue; Zheng, Xian-Liang; Li, Da-Yu; Xia, Ming-Liang; Hu, Li-Fa; Cao, Zhao-Liang; Mu, Quan-Quan; Xuan, Li

2014-09-01

With the help of adaptive optics (AO) technology, cellular level imaging of living human retina can be achieved. Aiming to reduce distressing feelings and to avoid potential drug induced diseases, we attempted to image retina with dilated pupil and froze accommodation without drugs. An optimized liquid crystal adaptive optics camera was adopted for retinal imaging. A novel eye stared system was used for stimulating accommodation and fixating imaging area. Illumination sources and imaging camera kept linkage for focusing and imaging different layers. Four subjects with diverse degree of myopia were imaged. Based on the optical properties of the human eye, the eye stared system reduced the defocus to less than the typical ocular depth of focus. In this way, the illumination light can be projected on certain retina layer precisely. Since that the defocus had been compensated by the eye stared system, the adopted 512 × 512 liquid crystal spatial light modulator (LC-SLM) corrector provided the crucial spatial fidelity to fully compensate high-order aberrations. The Strehl ratio of a subject with -8 diopter myopia was improved to 0.78, which was nearly close to diffraction-limited imaging. By finely adjusting the axial displacement of illumination sources and imaging camera, cone photoreceptors, blood vessels and nerve fiber layer were clearly imaged successfully.

Examining multi-component DNA-templated nanostructures as imaging agents

NASA Astrophysics Data System (ADS)

Jaganathan, Hamsa

2011-12-01

Magnetic resonance imaging (MRI) is the leading non-invasive tool for disease imaging and diagnosis. Although MRI exhibits high spatial resolution for anatomical features, the contrast resolution is low. Imaging agents serve as an aid to distinguish different types of tissues within images. Gadolinium chelates, which are considered first generation designs, can be toxic to health, while ultra-small, superparamagnetic nanoparticles (NPs) have low tissue-targeting efficiency and rapid bio-distribution, resulting to an inadequate detection of the MRI signal and enhancement of image contrast. In order to improve the utility of MRI agents, the challenge in composition and structure needs to be addressed. One-dimensional (1D), superparamagnetic nanostructures have been reported to enhance magnetic and in vivo properties and therefore has a potential to improve contrast enhancement in MRI images. In this dissertation, the structure of 1D, multi-component NP chains, scaffolded on DNA, were pre-clinically examined as potential MRI agents. First, research was focused on characterizing and understanding the mechanism of proton relaxation for DNA-templated NP chains using nuclear magnetic resonance (NMR) spectrometry. Proton relaxation and transverse relaxivity were higher in multi-component NP chains compared to disperse NPs, indicating the arrangement of NPs on a 1D structure improved proton relaxation sensitivity. Second, in vitro evaluation for potential issues in toxicity and contrast efficiency in tissue environments using a 3 Tesla clinical MRI scanner was performed. Cell uptake of DNA-templated NP chains was enhanced after encapsulating the nanostructure with layers of polyelectrolytes and targeting ligands. Compared to dispersed NPs, DNA-templated NP chains improved MRI contrast in both the epithelial basement membrane and colon cancer tumors scaffolds. The last part of the project was focused on developing a novel MRI agent that detects changes in DNA methylation levels. The findings from this dissertation suggest that the structural arrangement of NPs on DNA significantly influenced their function and utility as MRI agents.

Multifractal modeling, segmentation, prediction, and statistical validation of posterior fossa tumors

NASA Astrophysics Data System (ADS)

Islam, Atiq; Iftekharuddin, Khan M.; Ogg, Robert J.; Laningham, Fred H.; Sivakumar, Bhuvaneswari

2008-03-01

In this paper, we characterize the tumor texture in pediatric brain magnetic resonance images (MRIs) and exploit these features for automatic segmentation of posterior fossa (PF) tumors. We focus on PF tumor because of the prevalence of such tumor in pediatric patients. Due to varying appearance in MRI, we propose to model the tumor texture with a multi-fractal process, such as a multi-fractional Brownian motion (mBm). In mBm, the time-varying Holder exponent provides flexibility in modeling irregular tumor texture. We develop a detailed mathematical framework for mBm in two-dimension and propose a novel algorithm to estimate the multi-fractal structure of tissue texture in brain MRI based on wavelet coefficients. This wavelet based multi-fractal feature along with MR image intensity and a regular fractal feature obtained using our existing piecewise-triangular-prism-surface-area (PTPSA) method, are fused in segmenting PF tumor and non-tumor regions in brain T1, T2, and FLAIR MR images respectively. We also demonstrate a non-patient-specific automated tumor prediction scheme based on these image features. We experimentally show the tumor discriminating power of our novel multi-fractal texture along with intensity and fractal features in automated tumor segmentation and statistical prediction. To evaluate the performance of our tumor prediction scheme, we obtain ROCs and demonstrate how sharply the curves reach the specificity of 1.0 sacrificing minimal sensitivity. Experimental results show the effectiveness of our proposed techniques in automatic detection of PF tumors in pediatric MRIs.

Dynamic clustering detection through multi-valued descriptors of dermoscopic images.

PubMed

Cozza, Valentina; Guarracino, Maria Rosario; Maddalena, Lucia; Baroni, Adone

2011-09-10

This paper introduces a dynamic clustering methodology based on multi-valued descriptors of dermoscopic images. The main idea is to support medical diagnosis to decide if pigmented skin lesions belonging to an uncertain set are nearer to malignant melanoma or to benign nevi. Melanoma is the most deadly skin cancer, and early diagnosis is a current challenge for clinicians. Most data analysis algorithms for skin lesions discrimination focus on segmentation and extraction of features of categorical or numerical type. As an alternative approach, this paper introduces two new concepts: first, it considers multi-valued data that scalar variables not only describe but also intervals or histogram variables; second, it introduces a dynamic clustering method based on Wasserstein distance to compare multi-valued data. The overall strategy of analysis can be summarized into the following steps: first, a segmentation of dermoscopic images allows to identify a set of multi-valued descriptors; second, we performed a discriminant analysis on a set of images where there is an a priori classification so that it is possible to detect which features discriminate the benign and malignant lesions; and third, we performed the proposed dynamic clustering method on the uncertain cases, which need to be associated to one of the two previously mentioned groups. Results based on clinical data show that the grading of specific descriptors associated to dermoscopic characteristics provides a novel way to characterize uncertain lesions that can help the dermatologist's diagnosis. Copyright © 2011 John Wiley & Sons, Ltd.

Display technologies for augmented reality

NASA Astrophysics Data System (ADS)

Lee, Byoungho; Lee, Seungjae; Jang, Changwon; Hong, Jong-Young; Li, Gang

2018-02-01

With the virtue of rapid progress in optics, sensors, and computer science, we are witnessing that commercial products or prototypes for augmented reality (AR) are penetrating into the consumer markets. AR is spotlighted as expected to provide much more immersive and realistic experience than ordinary displays. However, there are several barriers to be overcome for successful commercialization of AR. Here, we explore challenging and important topics for AR such as image combiners, enhancement of display performance, and focus cue reproduction. Image combiners are essential to integrate virtual images with real-world. Display performance (e.g. field of view and resolution) is important for more immersive experience and focus cue reproduction may mitigate visual fatigue caused by vergence-accommodation conflict. We also demonstrate emerging technologies to overcome these issues: index-matched anisotropic crystal lens (IMACL), retinal projection displays, and 3D display with focus cues. For image combiners, a novel optical element called IMACL provides relatively wide field of view. Retinal projection displays may enhance field of view and resolution of AR displays. Focus cues could be reconstructed via multi-layer displays and holographic displays. Experimental results of our prototypes are explained.

Underwater video enhancement using multi-camera super-resolution

NASA Astrophysics Data System (ADS)

Quevedo, E.; Delory, E.; Callicó, G. M.; Tobajas, F.; Sarmiento, R.

2017-12-01

Image spatial resolution is critical in several fields such as medicine, communications or satellite, and underwater applications. While a large variety of techniques for image restoration and enhancement has been proposed in the literature, this paper focuses on a novel Super-Resolution fusion algorithm based on a Multi-Camera environment that permits to enhance the quality of underwater video sequences without significantly increasing computation. In order to compare the quality enhancement, two objective quality metrics have been used: PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity) index. Results have shown that the proposed method enhances the objective quality of several underwater sequences, avoiding the appearance of undesirable artifacts, with respect to basic fusion Super-Resolution algorithms.

Multi-focus beam shaping of high power multimode lasers

NASA Astrophysics Data System (ADS)

Laskin, Alexander; Volpp, Joerg; Laskin, Vadim; Ostrun, Aleksei

2017-08-01

Beam shaping of powerful multimode fiber lasers, fiber-coupled solid-state and diode lasers is of great importance for improvements of industrial laser applications. Welding, cladding with millimetre scale working spots benefit from "inverseGauss" intensity profiles; performance of thick metal sheet cutting, deep penetration welding can be enhanced when distributing the laser energy along the optical axis as more efficient usage of laser energy, higher edge quality and reduction of the heat affected zone can be achieved. Building of beam shaping optics for multimode lasers encounters physical limitations due to the low beam spatial coherence of multimode fiber-coupled lasers resulting in big Beam Parameter Products (BPP) or M² values. The laser radiation emerging from a multimode fiber presents a mixture of wavefronts. The fiber end can be considered as a light source which optical properties are intermediate between a Lambertian source and a single mode laser beam. Imaging of the fiber end, using a collimator and a focusing objective, is a robust and widely used beam delivery approach. Beam shaping solutions are suggested in form of optics combining fiber end imaging and geometrical separation of focused spots either perpendicular to or along the optical axis. Thus, energy of high power lasers is distributed among multiple foci. In order to provide reliable operation with multi-kW lasers and avoid damages the optics are designed as refractive elements with smooth optical surfaces. The paper presents descriptions of multi-focus optics as well as examples of intensity profile measurements of beam caustics and application results.

Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network.

PubMed

Pham, Tuyen Danh; Lee, Dong Eun; Park, Kang Ryoung

2017-07-08

Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods.

Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network

PubMed Central

Pham, Tuyen Danh; Lee, Dong Eun; Park, Kang Ryoung

2017-01-01

Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods. PMID:28698466

Sentinel-2: State of the Image Quality Calibration at the End of the Commissioning

NASA Astrophysics Data System (ADS)

Tremas, Thierry; Lonjou, Vincent; Lacherade, Sophie; Gaudel-Vacaresse, Angelique; Languille, Florie

2016-08-01

This article summarizes the activity of CNES during the In Orbit Calibration Phase of Sentinel 2A as well as the transfer of production of GIPP (Ground Image Processing Parameters) from CNES to ESRIN. The state of the main calibration parameters and performances, few months before PDGS is declared fully operational, are listed and explained.In radiometry a special attention is paid to the absolute calibration using the on-board diffuser, and the vicarious calibration methods using instrumented or statistically well characterized sites and inter- comparisons with other sensors. Regarding geometry, the presentation focuses on the performances of absolute location with and without reference points. The requirements of multi-band and multi-temporal registration are exposed. Finally, the construction and the rule of the GRI (Ground Reference Images) in the future are explained.

Response normalization and blur adaptation: Data and multi-scale model

PubMed Central

Elliott, Sarah L.; Georgeson, Mark A.; Webster, Michael A.

2011-01-01

Adapting to blurred or sharpened images alters perceived blur of a focused image (M. A. Webster, M. A. Georgeson, & S. M. Webster, 2002). We asked whether blur adaptation results in (a) renormalization of perceived focus or (b) a repulsion aftereffect. Images were checkerboards or 2-D Gaussian noise, whose amplitude spectra had (log–log) slopes from −2 (strongly blurred) to 0 (strongly sharpened). Observers adjusted the spectral slope of a comparison image to match different test slopes after adaptation to blurred or sharpened images. Results did not show repulsion effects but were consistent with some renormalization. Test blur levels at and near a blurred or sharpened adaptation level were matched by more focused slopes (closer to 1/f) but with little or no change in appearance after adaptation to focused (1/f) images. A model of contrast adaptation and blur coding by multiple-scale spatial filters predicts these blur aftereffects and those of Webster et al. (2002). A key proposal is that observers are pre-adapted to natural spectra, and blurred or sharpened spectra induce changes in the state of adaptation. The model illustrates how norms might be encoded and recalibrated in the visual system even when they are represented only implicitly by the distribution of responses across multiple channels. PMID:21307174

Rice Crop Monitoring Using Microwave and Optical Remotely Sensed Image Data

NASA Astrophysics Data System (ADS)

Suga, Y.; Konishi, T.; Takeuchi, S.; Kitano, Y.; Ito, S.

Hiroshima Institute of Technology HIT is operating the direct down-links of microwave and optical satellite data in Japan This study focuses on the validation for rice crop monitoring using microwave and optical remotely sensed image data acquired by satellites referring to ground truth data such as height of crop ratio of crop vegetation cover and leaf area index in the test sites of Japan ENVISAT-1 ASAR data has a capability to capture regularly and to monitor during the rice growing cycle by alternating cross polarization mode images However ASAR data is influenced by several parameters such as landcover structure direction and alignment of rice crop fields in the test sites In this study the validation was carried out combined with microwave and optical satellite image data and ground truth data regarding rice crop fields to investigate the above parameters Multi-temporal multi-direction descending and ascending and multi-angle ASAR alternating cross polarization mode images were used to investigate rice crop growing cycle LANDSAT data were used to detect landcover structure direction and alignment of rice crop fields corresponding to the backscatter of ASAR As the result of this study it was indicated that rice crop growth can be precisely monitored using multiple remotely sensed data and ground truth data considering with spatial spectral temporal and radiometric resolutions

Imaging Techniques for Dense 3D reconstruction of Swimming Aquatic Life using Multi-view Stereo

NASA Astrophysics Data System (ADS)

Daily, David; Kiser, Jillian; McQueen, Sarah

2016-11-01

Understanding the movement characteristics of how various species of fish swim is an important step to uncovering how they propel themselves through the water. Previous methods have focused on profile capture methods or sparse 3D manual feature point tracking. This research uses an array of 30 cameras to automatically track hundreds of points on a fish as they swim in 3D using multi-view stereo. Blacktip sharks, sting rays, puffer fish, turtles and more were imaged in collaboration with the National Aquarium in Baltimore, Maryland using the multi-view stereo technique. The processes for data collection, camera synchronization, feature point extraction, 3D reconstruction, 3D alignment, biological considerations, and lessons learned will be presented. Preliminary results of the 3D reconstructions will be shown and future research into mathematically characterizing various bio-locomotive maneuvers will be discussed.

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.

One-step production of multilayered microparticles by tri-axial electro-flow focusing

NASA Astrophysics Data System (ADS)

Si, Ting; Feng, Hanxin; Li, Yang; Luo, Xisheng; Xu, Ronald

2014-03-01

Microencapsulation of drugs and imaging agents in the same carrier is of great significance for simultaneous detection and treatment of diseases. In this work, we have developed a tri-axial electro-flow focusing (TEFF) device using three needles with a novel concentric arrangement to one-step form multilayered microparticles. The TEFF process can be characterized as a multi-fluidic compound cone-jet configuration in the core of a high-speed coflowing gas stream under an axial electric field. The tri-axial liquid jet eventually breaks up into multilayered droplets. To validate the method, the effect of main process parameters on characteristics of the cone and the jet has been studied experimentally. The applied electric field can dramatically promote the stability of the compound cone and enhance the atomization of compound liquid jets. Microparticles with both three-layer, double-layer and single-layer structures have been obtained. The results show that the TEFF technique has great benefits in fabricating multilayered microparticles at smaller scales. This method will be able to one-step encapsulate multiple therapeutic and imaging agents for biomedical applications such as multi-modal imaging, drug delivery and biomedicine.

Modeling and Correcting the Time-Dependent ACS PSF

NASA Technical Reports Server (NTRS)

Rhodes, Jason; Massey, Richard; Albert, Justin; Taylor, James E.; Koekemoer, Anton M.; Leauthaud, Alexie

2006-01-01

The ability to accurately measure the shapes of faint objects in images taken with the Advanced Camera for Surveys (ACS) on the Hubble Space Telescope (HST) depends upon detailed knowledge of the Point Spread Function (PSF). We show that thermal fluctuations cause the PSF of the ACS Wide Field Camera (WFC) to vary over time. We describe a modified version of the TinyTim PSF modeling software to create artificial grids of stars across the ACS field of view at a range of telescope focus values. These models closely resemble the stars in real ACS images. Using 10 bright stars in a real image, we have been able to measure HST s apparent focus at the time of the exposure. TinyTim can then be used to model the PSF at any position on the ACS field of view. This obviates the need for images of dense stellar fields at different focus values, or interpolation between the few observed stars. We show that residual differences between our TinyTim models and real data are likely due to the effects of Charge Transfer Efficiency (CTE) degradation. Furthermore, we discuss stochastic noise that is added to the shape of point sources when distortion is removed, and we present MultiDrizzle parameters that are optimal for weak lensing science. Specifically, we find that reducing the MultiDrizzle output pixel scale and choosing a Gaussian kernel significantly stabilizes the resulting PSF after image combination, while still eliminating cosmic rays/bad pixels, and correcting the large geometric distortion in the ACS. We discuss future plans, which include more detailed study of the effects of CTE degradation on object shapes and releasing our TinyTim models to the astronomical community.

Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed. PMID:29123476

Ad Hoc Network Architecture for Multi-Media Networks

DTIC Science & Technology

2007-12-01

sensor network . Video traffic is modeled and simulations are performed via the use of the Sun Small Programmable Object Technology (Sun SPOT) Java...characteristics of video traffic must be studied and understood. This thesis focuses on evaluating the possibility of routing video images over a wireless

High-intensity focused ultrasound (HIFU) array system for image-guided ablative therapy (IGAT)

NASA Astrophysics Data System (ADS)

Kaczkowski, Peter J.; Keilman, George W.; Cunitz, Bryan W.; Martin, Roy W.; Vaezy, Shahram; Crum, Lawrence A.

2003-06-01

Recent interest in using High Intensity Focused Ultrasound (HIFU) for surgical applications such as hemostasis and tissue necrosis has stimulated the development of image-guided systems for non-invasive HIFU therapy. Seeking an all-ultrasound therapeutic modality, we have developed a clinical HIFU system comprising an integrated applicator that permits precisely registered HIFU therapy delivery and high quality ultrasound imaging using two separate arrays, a multi-channel signal generator and RF amplifier system, and a software program that provides the clinician with a graphical overlay of the ultrasound image and therapeutic protocol controls. Electronic phasing of a 32 element 2 MHz HIFU annular array allows adjusting the focus within the range of about 4 to 12 cm from the face. A central opening in the HIFU transducer permits mounting a commercial medical imaging scanhead (ATL P7-4) that is held in place within a special housing. This mechanical fixture ensures precise coaxial registration between the HIFU transducer and the image plane of the imaging probe. Recent enhancements include development of an acoustic lens using numerical simulations for use with a 5-element array. Our image-guided therapy system is very flexible and enables exploration of a variety of new HIFU therapy delivery and monitoring approaches in the search for safe, effective, and efficient treatment protocols.

Advanced human machine interaction for an image interpretation workstation

NASA Astrophysics Data System (ADS)

Maier, S.; Martin, M.; van de Camp, F.; Peinsipp-Byma, E.; Beyerer, J.

2016-05-01

In recent years, many new interaction technologies have been developed that enhance the usability of computer systems and allow for novel types of interaction. The areas of application for these technologies have mostly been in gaming and entertainment. However, in professional environments, there are especially demanding tasks that would greatly benefit from improved human machine interfaces as well as an overall improved user experience. We, therefore, envisioned and built an image-interpretation-workstation of the future, a multi-monitor workplace comprised of four screens. Each screen is dedicated to a complex software product such as a geo-information system to provide geographic context, an image annotation tool, software to generate standardized reports and a tool to aid in the identification of objects. Using self-developed systems for hand tracking, pointing gestures and head pose estimation in addition to touchscreens, face identification, and speech recognition systems we created a novel approach to this complex task. For example, head pose information is used to save the position of the mouse cursor on the currently focused screen and to restore it as soon as the same screen is focused again while hand gestures allow for intuitive manipulation of 3d objects in mid-air. While the primary focus is on the task of image interpretation, all of the technologies involved provide generic ways of efficiently interacting with a multi-screen setup and could be utilized in other fields as well. In preliminary experiments, we received promising feedback from users in the military and started to tailor the functionality to their needs

Asymptotics of action variables near semi-toric singularities

NASA Astrophysics Data System (ADS)

Wacheux, Christophe

2015-12-01

The presence of focus-focus singularities in semi-toric integrables Hamiltonian systems is one of the reasons why there cannot exist global Action-Angle coordinates on such systems. At focus-focus critical points, the Liouville-Arnold-Mineur theorem does not apply. In particular, the affine structure of the image of the moment map around has non-trivial monodromy. In this article, we establish that the singular behavior and the multi-valuedness of the Action integrals is given by a complex logarithm. This extends a previous result by San Vũ Ngọc to any dimension. We also calculate the monodromy matrix for these systems.

Digital sun sensor multi-spot operation.

PubMed

Rufino, Giancarlo; Grassi, Michele

2012-11-28

The operation and test of a multi-spot digital sun sensor for precise sun-line determination is described. The image forming system consists of an opaque mask with multiple pinhole apertures producing multiple, simultaneous, spot-like images of the sun on the focal plane. The sun-line precision can be improved by averaging multiple simultaneous measures. Nevertheless, the sensor operation on a wide field of view requires acquiring and processing images in which the number of sun spots and the related intensity level are largely variable. To this end, a reliable and robust image acquisition procedure based on a variable shutter time has been considered as well as a calibration function exploiting also the knowledge of the sun-spot array size. Main focus of the present paper is the experimental validation of the wide field of view operation of the sensor by using a sensor prototype and a laboratory test facility. Results demonstrate that it is possible to keep high measurement precision also for large off-boresight angles.

Shape priors for segmentation of the cervix region within uterine cervix images

NASA Astrophysics Data System (ADS)

Lotenberg, Shelly; Gordon, Shiri; Greenspan, Hayit

2008-03-01

The work focuses on a unique medical repository of digital Uterine Cervix images ("Cervigrams") collected by the National Cancer Institute (NCI), National Institute of Health, in longitudinal multi-year studies. NCI together with the National Library of Medicine is developing a unique web-based database of the digitized cervix images to study the evolution of lesions related to cervical cancer. Tools are needed for the automated analysis of the cervigram content to support the cancer research. In recent works, a multi-stage automated system for segmenting and labeling regions of medical and anatomical interest within the cervigrams was developed. The current paper concentrates on incorporating prior-shape information in the cervix region segmentation task. In accordance with the fact that human experts mark the cervix region as circular or elliptical, two shape models (and corresponding methods) are suggested. The shape models are embedded within an active contour framework that relies on image features. Experiments indicate that incorporation of the prior shape information augments previous results.

Towards a More Efficient Detection of Earthquake Induced FAÇADE Damages Using Oblique Uav Imagery

NASA Astrophysics Data System (ADS)

Duarte, D.; Nex, F.; Kerle, N.; Vosselman, G.

2017-08-01

Urban search and rescue (USaR) teams require a fast and thorough building damage assessment, to focus their rescue efforts accordingly. Unmanned aerial vehicles (UAV) are able to capture relevant data in a short time frame and survey otherwise inaccessible areas after a disaster, and have thus been identified as useful when coupled with RGB cameras for façade damage detection. Existing literature focuses on the extraction of 3D and/or image features as cues for damage. However, little attention has been given to the efficiency of the proposed methods which hinders its use in an urban search and rescue context. The framework proposed in this paper aims at a more efficient façade damage detection using UAV multi-view imagery. This was achieved directing all damage classification computations only to the image regions containing the façades, hence discarding the irrelevant areas of the acquired images and consequently reducing the time needed for such task. To accomplish this, a three-step approach is proposed: i) building extraction from the sparse point cloud computed from the nadir images collected in an initial flight; ii) use of the latter as proxy for façade location in the oblique images captured in subsequent flights, and iii) selection of the façade image regions to be fed to a damage classification routine. The results show that the proposed framework successfully reduces the extracted façade image regions to be assessed for damage 6 fold, hence increasing the efficiency of subsequent damage detection routines. The framework was tested on a set of UAV multi-view images over a neighborhood of the city of L'Aquila, Italy, affected in 2009 by an earthquake.

Module for multiphoton high-resolution hyperspectral imaging and spectroscopy

NASA Astrophysics Data System (ADS)

Zeytunyan, Aram; Baldacchini, Tommaso; Zadoyan, Ruben

2018-02-01

We developed a module for dual-output, dual-wavelength lasers that facilitates multiphoton imaging and spectroscopy experiments and enables hyperspectral imaging with spectral resolution up to 5 cm-1. High spectral resolution is achieved by employing spectral focusing. Specifically, two sets of grating pairs are used to control the chirps in each laser beam. In contrast with the approach that uses fixed-length glass rods, grating pairs allow matching the spectral resolution and the linewidths of the Raman lines of interest. To demonstrate the performance of the module, we report the results of spectral focusing CARS and SRS microscopy experiments for various test samples and Raman shifts. The developed module can be used for a variety of multimodal imaging and spectroscopy applications, such as single- and multi-color two-photon fluorescence, second harmonic generation, third harmonic generation, pump-probe, transient absorption, and others.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

System geometry optimization for molecular breast tomosynthesis with focusing multi-pinhole collimators

NASA Astrophysics Data System (ADS)

van Roosmalen, Jarno; Beekman, Freek J.; Goorden, Marlies C.

2018-01-01

Imaging of 99mTc-labelled tracers is gaining popularity for detecting breast tumours. Recently, we proposed a novel design for molecular breast tomosynthesis (MBT) based on two sliding focusing multi-pinhole collimators that scan a modestly compressed breast. Simulation studies indicate that MBT has the potential to improve the tumour-to-background contrast-to-noise ratio significantly over state-of-the-art planar molecular breast imaging. The aim of the present paper is to optimize the collimator-detector geometry of MBT. Using analytical models, we first optimized sensitivity at different fixed system resolutions (ranging from 5 to 12 mm) by tuning the pinhole diameters and the distance between breast and detector for a whole series of automatically generated multi-pinhole designs. We evaluated both MBT with a conventional continuous crystal detector with 3.2 mm intrinsic resolution and with a pixelated detector with 1.6 mm pixels. Subsequently, full system simulations of a breast phantom containing several lesions were performed for the optimized geometry at each system resolution for both types of detector. From these simulations, we found that tumour-to-background contrast-to-noise ratio was highest for systems in the 7 mm-10 mm system resolution range over which it hardly varied. No significant differences between the two detector types were found.

High-speed laser photoacoustic imaging system combined with a digital ultrasonic imaging platform

NASA Astrophysics Data System (ADS)

Zeng, Lvming; Liu, Guodong; Ji, Xuanrong; Ren, Zhong; Huang, Zhen

2009-07-01

As a new field of combined ultrasound/photoacoustic imaging in biomedical photonics research, we present and demonstrate a high-speed laser photoacoustic imaging system combined with digital ultrasound imaging platform. In the prototype system, a new B-mode digital ultrasonic imaging system is modified as the hardware platform with 384 vertical transducer elements. The centre resonance frequency of the piezoelectric transducer is 5.0 MHz with greater than 70% pulse-echo -6dB fractional bandwidth. The modular instrument of PCI-6541 is used as the hardware control centre of the testing system, which features 32 high-speed channels to build low-skew and multi-channel system. The digital photoacoustic data is transported into computer for subsequent reconstruction at 25 MHz clock frequency. Meantime, the software system for controlling and analyzing is correspondingly explored with LabVIEW language on virtual instrument platform. In the breast tissue experiment, the reconstructed image agrees well with the original sample, and the spatial resolution of the system can reach 0.2 mm with multi-element synthetic aperture focusing technique. Therefore, the system and method may have a significant value in improving early detecting level of cancer in the breast and other organs.

A head-mounted compressive three-dimensional display system with polarization-dependent focus switching

NASA Astrophysics Data System (ADS)

Lee, Chang-Kun; Moon, Seokil; Lee, Byounghyo; Jeong, Youngmo; Lee, Byoungho

2016-10-01

A head-mounted compressive three-dimensional (3D) display system is proposed by combining polarization beam splitter (PBS), fast switching polarization rotator and micro display with high pixel density. According to the polarization state of the image controlled by polarization rotator, optical path of image in the PBS can be divided into transmitted and reflected components. Since optical paths of each image are spatially separated, it is possible to independently focus both images at different depth positions. Transmitted p-polarized and reflected s-polarized images can be focused by convex lens and mirror, respectively. When the focal lengths of the convex lens and mirror are properly determined, two image planes can be located in intended positions. The geometrical relationship is easily modulated by replacement of the components. The fast switching of polarization realizes the real-time operation of multi-focal image planes with a single display panel. Since it is possible to conserve the device characteristic of single panel, the high image quality, reliability and uniformity can be retained. For generating 3D images, layer images for compressive light field display between two image planes are calculated. Since the display panel with high pixel density is adopted, high quality 3D images are reconstructed. In addition, image degradation by diffraction between physically stacked display panels can be mitigated. Simple optical configuration of the proposed system is implemented and the feasibility of the proposed method is verified through experiments.

Blood-Brain Barrier Closure Time After Controlled Ultrasound-Induced Opening Is Independent of Opening Volume.

PubMed

O'Reilly, Meaghan A; Hough, Olivia; Hynynen, Kullervo

2017-03-01

Microbubble-mediated focused ultrasound (US) opening of the blood-brain barrier (BBB) has shown promising results for the treatment of brain tumors and conditions such as Alzheimer disease. Practical clinical implementation of focused US treatments would aim to treat a substantial portion of the brain; thus, the safety of opening large volumes must be investigated. This study investigated whether the opened volume affects the time for the BBB to be restored after treatment. Sprague Dawley rats (n = 5) received bilateral focused US treatments. One hemisphere received a single sonication, and the contralateral hemisphere was targeted with 4 overlapping foci. Contrast-enhanced T1-weighted magnetic resonance imaging was used to assess the integrity of the BBB at 0, 6, and 24 hours after focused US. At time 0, there was no significant difference in the mean enhancement between the single- and multi-point sonications (mean ± SD, 29.7% ± 18.4% versus 29.7% ± 24.1%; P = .9975). The mean cross-sectional area of the BBB opening resulting from the multi-point sonication was approximately 3.5-fold larger than that of the single-point case (14.2 ± 4.7 versus 4.1 ± 3.3 mm 2 ; P < .0001). The opened volumes in 9 of 10 hemispheres were closed by 6 hours after focused US. The remaining treatment location had substantially reduced enhancement at 6 hours and was closed by 24 hours. Histologic analysis revealed small morphologic changes associated with this location. T2-weighted images at 6 and 24 hours showed no signs of edema. T2*-weighted images obtained at 6 hours also showed no signs hemorrhage in any animal. The time for the BBB to close after focused US was independent of the opening volume on the time scale investigated. No differences in treatment effects were observable by magnetic resonance imaging follow-up between larger- and smaller-volume sonications, suggesting that larger-volume BBB opening can be performed safely. © 2017 by the American Institute of Ultrasound in Medicine.

UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

NASA Astrophysics Data System (ADS)

Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

2015-06-01

Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

Analysis of multi-channel microscopy: Spectral self-interference, multi-detector confocal and 4Pi systems

NASA Astrophysics Data System (ADS)

Davis, Brynmor J.

Fluorescence microscopy is an important and ubiquitous tool in biological imaging due to the high specificity with which fluorescent molecules can be attached to an organism and the subsequent nondestructive in-vivo imaging allowed. Focused-light microscopies allow three-dimensional fluorescence imaging but their resolution is restricted by diffraction. This effect is particularly limiting in the axial dimension as the diffraction-limited focal volume produced by a lens is more extensive along the optical axis than perpendicular to it. Approaches such as confocal microscopy and 4Pi microscopy have been developed to improve the axial resolution. Spectral Self-Interference Fluorescence Microscopy (SSFM) is another high-axial-resolution technique and is the principal subject of this dissertation. Nanometer-precision localization of a single fluorescent layer has been demonstrated using SSFM. This accuracy compares favorably with the axial resolutions given by confocal and 4Pi systems at similar operating parameters (these resolutions are approximately 350nm and 80nm respectively). This theoretical work analyzes the expected performance of the SSFM system when imaging a general object, i.e. an arbitrary fluorophore density function rather than a single layer. An existing model of SSFM is used in simulations to characterize the system's resolution. Several statistically-based reconstruction methods are applied to show that the expected resolution for SSFM is similar to 4Pi microscopy for a general object but does give very high localization accuracy when the object is known to consist of a limited number of layers. SSFM is then analyzed in a linear systems framework and shown to have strong connections, both physically and mathematically, to a multi-channel 4Pi microscope. Fourier-domain analysis confirms that SSFM cannot be expected to outperform this multi-channel 4Pi instrument. Differences between the channels in spatial-scanning, multi-channel microscopies are then exploited to show that such instruments can operate at a sub-Nyquist scanning rate but still produce images largely free of aliasing effects. Multi-channel analysis is also used to show how light typically discarded in confocal and 4Pi systems can be collected and usefully incorporated into the measured image.

Multi-focused microlens array optimization and light field imaging study based on Monte Carlo method.

PubMed

Li, Tian-Jiao; Li, Sai; Yuan, Yuan; Liu, Yu-Dong; Xu, Chuan-Long; Shuai, Yong; Tan, He-Ping

2017-04-03

Plenoptic cameras are used for capturing flames in studies of high-temperature phenomena. However, simulations of plenoptic camera models can be used prior to the experiment improve experimental efficiency and reduce cost. In this work, microlens arrays, which are based on the established light field camera model, are optimized into a hexagonal structure with three types of microlenses. With this improved plenoptic camera model, light field imaging of static objects and flame are simulated using the calibrated parameters of the Raytrix camera (R29). The optimized models improve the image resolution, imaging screen utilization, and shooting range of depth of field.

A method of extracting speed-dependent vector correlations from 2 + 1 REMPI ion images.

PubMed

Wei, Wei; Wallace, Colin J; Grubb, Michael P; North, Simon W

2017-07-07

We present analytical expressions for extracting Dixon's bipolar moments in the semi-classical limit from experimental anisotropy parameters of sliced or reconstructed non-sliced images. The current method focuses on images generated by 2 + 1 REMPI (Resonance Enhanced Multi-photon Ionization) and is a necessary extension of our previously published 1 + 1 REMPI equations. Two approaches for applying the new equations, direct inversion and forward convolution, are presented. As demonstration of the new method, bipolar moments were extracted from images of carbonyl sulfide (OCS) photodissociation at 230 nm and NO 2 photodissociation at 355 nm, and the results are consistent with previous publications.

Transform- and multi-domain deep learning for single-frame rapid autofocusing in whole slide imaging.

PubMed

Jiang, Shaowei; Liao, Jun; Bian, Zichao; Guo, Kaikai; Zhang, Yongbing; Zheng, Guoan

2018-04-01

A whole slide imaging (WSI) system has recently been approved for primary diagnostic use in the US. The image quality and system throughput of WSI is largely determined by the autofocusing process. Traditional approaches acquire multiple images along the optical axis and maximize a figure of merit for autofocusing. Here we explore the use of deep convolution neural networks (CNNs) to predict the focal position of the acquired image without axial scanning. We investigate the autofocusing performance with three illumination settings: incoherent Kohler illumination, partially coherent illumination with two plane waves, and one-plane-wave illumination. We acquire ~130,000 images with different defocus distances as the training data set. Different defocus distances lead to different spatial features of the captured images. However, solely relying on the spatial information leads to a relatively bad performance of the autofocusing process. It is better to extract defocus features from transform domains of the acquired image. For incoherent illumination, the Fourier cutoff frequency is directly related to the defocus distance. Similarly, autocorrelation peaks are directly related to the defocus distance for two-plane-wave illumination. In our implementation, we use the spatial image, the Fourier spectrum, the autocorrelation of the spatial image, and combinations thereof as the inputs for the CNNs. We show that the information from the transform domains can improve the performance and robustness of the autofocusing process. The resulting focusing error is ~0.5 µm, which is within the 0.8-µm depth-of-field range. The reported approach requires little hardware modification for conventional WSI systems and the images can be captured on the fly without focus map surveying. It may find applications in WSI and time-lapse microscopy. The transform- and multi-domain approaches may also provide new insights for developing microscopy-related deep-learning networks. We have made our training and testing data set (~12 GB) open-source for the broad research community.

Wide-field computational imaging of pathology slides using lens-free on-chip microscopy.

PubMed

Greenbaum, Alon; Zhang, Yibo; Feizi, Alborz; Chung, Ping-Luen; Luo, Wei; Kandukuri, Shivani R; Ozcan, Aydogan

2014-12-17

Optical examination of microscale features in pathology slides is one of the gold standards to diagnose disease. However, the use of conventional light microscopes is partially limited owing to their relatively high cost, bulkiness of lens-based optics, small field of view (FOV), and requirements for lateral scanning and three-dimensional (3D) focus adjustment. We illustrate the performance of a computational lens-free, holographic on-chip microscope that uses the transport-of-intensity equation, multi-height iterative phase retrieval, and rotational field transformations to perform wide-FOV imaging of pathology samples with comparable image quality to a traditional transmission lens-based microscope. The holographically reconstructed image can be digitally focused at any depth within the object FOV (after image capture) without the need for mechanical focus adjustment and is also digitally corrected for artifacts arising from uncontrolled tilting and height variations between the sample and sensor planes. Using this lens-free on-chip microscope, we successfully imaged invasive carcinoma cells within human breast sections, Papanicolaou smears revealing a high-grade squamous intraepithelial lesion, and sickle cell anemia blood smears over a FOV of 20.5 mm(2). The resulting wide-field lens-free images had sufficient image resolution and contrast for clinical evaluation, as demonstrated by a pathologist's blinded diagnosis of breast cancer tissue samples, achieving an overall accuracy of ~99%. By providing high-resolution images of large-area pathology samples with 3D digital focus adjustment, lens-free on-chip microscopy can be useful in resource-limited and point-of-care settings. Copyright © 2014, American Association for the Advancement of Science.

Development and Validation of a Monte Carlo Simulation Tool for Multi-Pinhole SPECT

PubMed Central

Mok, Greta S. P.; Du, Yong; Wang, Yuchuan; Frey, Eric C.; Tsui, Benjamin M. W.

2011-01-01

Purpose In this work, we developed and validated a Monte Carlo simulation (MCS) tool for investigation and evaluation of multi-pinhole (MPH) SPECT imaging. Procedures This tool was based on a combination of the SimSET and MCNP codes. Photon attenuation and scatter in the object, as well as penetration and scatter through the collimator detector, are modeled in this tool. It allows accurate and efficient simulation of MPH SPECT with focused pinhole apertures and user-specified photon energy, aperture material, and imaging geometry. The MCS method was validated by comparing the point response function (PRF), detection efficiency (DE), and image profiles obtained from point sources and phantom experiments. A prototype single-pinhole collimator and focused four- and five-pinhole collimators fitted on a small animal imager were used for the experimental validations. We have also compared computational speed among various simulation tools for MPH SPECT, including SimSET-MCNP, MCNP, SimSET-GATE, and GATE for simulating projections of a hot sphere phantom. Results We found good agreement between the MCS and experimental results for PRF, DE, and image profiles, indicating the validity of the simulation method. The relative computational speeds for SimSET-MCNP, MCNP, SimSET-GATE, and GATE are 1: 2.73: 3.54: 7.34, respectively, for 120-view simulations. We also demonstrated the application of this MCS tool in small animal imaging by generating a set of low-noise MPH projection data of a 3D digital mouse whole body phantom. Conclusions The new method is useful for studying MPH collimator designs, data acquisition protocols, image reconstructions, and compensation techniques. It also has great potential to be applied for modeling the collimator-detector response with penetration and scatter effects for MPH in the quantitative reconstruction method. PMID:19779896

A 3D THz image processing methodology for a fully integrated, semi-automatic and near real-time operational system

NASA Astrophysics Data System (ADS)

Brook, A.; Cristofani, E.; Vandewal, M.; Matheis, C.; Jonuscheit, J.; Beigang, R.

2012-05-01

The present study proposes a fully integrated, semi-automatic and near real-time mode-operated image processing methodology developed for Frequency-Modulated Continuous-Wave (FMCW) THz images with the center frequencies around: 100 GHz and 300 GHz. The quality control of aeronautics composite multi-layered materials and structures using Non-Destructive Testing is the main focus of this work. Image processing is applied on the 3-D images to extract useful information. The data is processed by extracting areas of interest. The detected areas are subjected to image analysis for more particular investigation managed by a spatial model. Finally, the post-processing stage examines and evaluates the spatial accuracy of the extracted information.

Compact plane illumination plugin device to enable light sheet fluorescence imaging of multi-cellular organisms on an inverted wide-field microscope

PubMed Central

Guan, Zeyi; Lee, Juhyun; Jiang, Hao; Dong, Siyan; Jen, Nelson; Hsiai, Tzung; Ho, Chih-Ming; Fei, Peng

2015-01-01

We developed a compact plane illumination plugin (PIP) device which enabled plane illumination and light sheet fluorescence imaging on a conventional inverted microscope. The PIP device allowed the integration of microscope with tunable laser sheet profile, fast image acquisition, and 3-D scanning. The device is both compact, measuring approximately 15 by 5 by 5 cm, and cost-effective, since we employed consumer electronics and an inexpensive device molding method. We demonstrated that PIP provided significant contrast and resolution enhancement to conventional microscopy through imaging different multi-cellular fluorescent structures, including 3-D branched cells in vitro and live zebrafish embryos. Imaging with the integration of PIP greatly reduced out-of-focus contamination and generated sharper contrast in acquired 2-D plane images when compared with the stand-alone inverted microscope. As a result, the dynamic fluid domain of the beating zebrafish heart was clearly segmented and the functional monitoring of the heart was achieved. Furthermore, the enhanced axial resolution established by thin plane illumination of PIP enabled the 3-D reconstruction of the branched cellular structures, which leads to the improvement on the functionality of the wide field microscopy. PMID:26819828

Compact plane illumination plugin device to enable light sheet fluorescence imaging of multi-cellular organisms on an inverted wide-field microscope.

PubMed

Guan, Zeyi; Lee, Juhyun; Jiang, Hao; Dong, Siyan; Jen, Nelson; Hsiai, Tzung; Ho, Chih-Ming; Fei, Peng

2016-01-01

We developed a compact plane illumination plugin (PIP) device which enabled plane illumination and light sheet fluorescence imaging on a conventional inverted microscope. The PIP device allowed the integration of microscope with tunable laser sheet profile, fast image acquisition, and 3-D scanning. The device is both compact, measuring approximately 15 by 5 by 5 cm, and cost-effective, since we employed consumer electronics and an inexpensive device molding method. We demonstrated that PIP provided significant contrast and resolution enhancement to conventional microscopy through imaging different multi-cellular fluorescent structures, including 3-D branched cells in vitro and live zebrafish embryos. Imaging with the integration of PIP greatly reduced out-of-focus contamination and generated sharper contrast in acquired 2-D plane images when compared with the stand-alone inverted microscope. As a result, the dynamic fluid domain of the beating zebrafish heart was clearly segmented and the functional monitoring of the heart was achieved. Furthermore, the enhanced axial resolution established by thin plane illumination of PIP enabled the 3-D reconstruction of the branched cellular structures, which leads to the improvement on the functionality of the wide field microscopy.

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…

Multi-parametric monitoring of high intensity focused ultrasound (HIFU) treatment using harmonic motion imaging for focused ultrasound (HMIFU)

NASA Astrophysics Data System (ADS)

Hou, Gary Y.; Marquet, Fabrice; Wang, Shutao; Konofagou, Elisa

2012-11-01

Harmonic Motion Imaging for Focused Ultrasound (HMIFU) is a recently developed high-intensity focused ultrasound (HIFU) treatment monitoring method with feasibilities demonstrated in vitro and in vivo. Here, a multi-parametric study is performed to investigate both elastic and acoustics-independent viscoelastic tissue changes using the Harmonic Motion Imaging (HMI) displacement, axial compressive strain and relative phase-shift during high energy HIFU where tissue boiling occurs. Forty three (n=18) thermal lesions were formed in ex vivo canine liver specimens. Two dimensional (2D) transverse HMI displacement maps were also obtained before and after lesion formation. The same method was repeated in 10-, 20-and 30-s HIFU durations at three different acoustic powers of 8, 10, and 11W. For the 10-, 20-, and 30-s treatment cases, a steady decrease in the displacement (-8.67±4.80, -14.44±7.77, 24.03±12.11μm), compressive strain -0.16±0.06, -0.71±0.30, -0.68±0.36 %, and phase shift +1.80±6.80, -15.80±9.44, -18.62±13.14 ° were obtained, respectively, indicating overall increase of relative stiffness and decrease of the viscosity-to-stiffness ratio during heating. After treatment, 2D HMI displacement images of the thermal lesions showed an increased lesion-to-background contrast of 1.34±0.19, 1.98±0.30, 2.26±0.80 and lesion size of 40.95±8.06, 47.6±4.87, and 52.23±2.19 mm2, respectively, which was validated again with pathology 25.17±6.99, 42.17±1.77, 47.17±3.10 mm2. Additionally, studies also investigated the performance of mutli-parametric monitoring under the influence of boiling and attenuation change due to tissue boiling, where discrepancies were found such as deteriorated displacement SNR and reversed lesion-to-background displacement contrast with indication on possible increase in attenuation and tissue gelatification or pulverization. Despite the challenge of the boiling mechanism, the relative phase shift served as consist biomechanical tissue response independent of changes in acoustic properties throughout the HIFU treatment. In addition, the 2D HMI displacement images were able to confirm and quantify the change in dimensions of the thermal lesion site. Therefore, the multi-parametric HMIFU was shown capable of monitoring and mapping tissue viscoelastic response changes during and after HIFU treatment.

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification.

PubMed

Zhou, Tao; Li, Zhaofu; Pan, Jianjun

2018-01-27

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively.

Ultra-high spatial resolution multi-energy CT using photon counting detector technology

NASA Astrophysics Data System (ADS)

Leng, S.; Gutjahr, R.; Ferrero, A.; Kappler, S.; Henning, A.; Halaweish, A.; Zhou, W.; Montoya, J.; McCollough, C.

2017-03-01

Two ultra-high-resolution (UHR) imaging modes, each with two energy thresholds, were implemented on a research, whole-body photon-counting-detector (PCD) CT scanner, referred to as sharp and UHR, respectively. The UHR mode has a pixel size of 0.25 mm at iso-center for both energy thresholds, with a collimation of 32 × 0.25 mm. The sharp mode has a 0.25 mm pixel for the low-energy threshold and 0.5 mm for the high-energy threshold, with a collimation of 48 × 0.25 mm. Kidney stones with mixed mineral composition and lung nodules with different shapes were scanned using both modes, and with the standard imaging mode, referred to as macro mode (0.5 mm pixel and 32 × 0.5 mm collimation). Evaluation and comparison of the three modes focused on the ability to accurately delineate anatomic structures using the high-spatial resolution capability and the ability to quantify stone composition using the multi-energy capability. The low-energy threshold images of the sharp and UHR modes showed better shape and texture information due to the achieved higher spatial resolution, although noise was also higher. No noticeable benefit was shown in multi-energy analysis using UHR compared to standard resolution (macro mode) when standard doses were used. This was due to excessive noise in the higher resolution images. However, UHR scans at higher dose showed improvement in multi-energy analysis over macro mode with regular dose. To fully take advantage of the higher spatial resolution in multi-energy analysis, either increased radiation dose, or application of noise reduction techniques, is needed.

Multi-core and GPU accelerated simulation of a radial star target imaged with equivalent t-number circular and Gaussian pupils

NASA Astrophysics Data System (ADS)

Greynolds, Alan W.

2013-09-01

Results from the GelOE optical engineering software are presented for the through-focus, monochromatic coherent and polychromatic incoherent imaging of a radial "star" target for equivalent t-number circular and Gaussian pupils. The FFT-based simulations are carried out using OpenMP threading on a multi-core desktop computer, with and without the aid of a many-core NVIDIA GPU accessing its cuFFT library. It is found that a custom FFT optimized for the 12-core host has similar performance to a simply implemented 256-core GPU FFT. A more sophisticated version of the latter but tuned to reduce overhead on a 448-core GPU is 20 to 28 times faster than a basic FFT implementation running on one CPU core.

Alignment of x-ray tube focal spots for spectral measurement.

PubMed

Nishizawa, K; Maekoshi, H; Kamiya, Y; Kobayashi, Y; Ohara, K; Sakuma, S

1982-01-01

A general method to align a diagnostic x-ray machine for x-ray spectrum measurement purpose was theoretically and experimentally investigated by means of the optical alignment of focal pinhole images. Focal pinhole images were obtained by using a multi-pinholed lead plate. the vertical plane, including the central axis and tube axis, was decided upon by observing the symmetry of focal images. the central axis was designated as a line through the center of focus parallel to the target surface lying in the vertical plane. A method to determine the manipulation of the central axis in any direction is presented.

MO-DE-202-00: Image-Guided Interventions: Advances in Intraoperative Imaging, Guidance, and An Emerging Role for Medical Physics in Surgery

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

NONE

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-03: Image-Guided Surgery and Interventions in the Advanced Multimodality Image-Guided Operating (AMIGO) Suite

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

Kapur, T.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-02: Advances in Image Registration and Reconstruction for Image-Guided Neurosurgery

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

Siewerdsen, J.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

A multi-element high intensity focused ultrasound transducer: Design, fabrication, and testing

NASA Astrophysics Data System (ADS)

Vaezy, Shahram; Held, Robert; Miller, Blake; Fleury, Gerard

2004-05-01

The goal of this project is to develop an intra-cavity image-guided high intensity focused ultrasound (HIFU) device using piezocomposite technology and commercially available ultrasound imaging. The HIFU array, manufactured by Imasonic Corporation, is an 11-element annular phased array, with a focal length range of 30-60 mm, and operating frequency of 3 MHz (bandwidth of 1 MHz). The imaging probe (C9-5, Philips) is configured such that the focal axis of the HIFU beam was within the image plane. The array includes six complete central rings and five side-truncated peripheral rings, all with the natural radius of curvature of 50 mm. Impedance of all elements is approximately 50 ohms (10% accuracy for real and imaginary parts). Cross coupling between adjacent elements is less than, -40 dB. High power measurements showed more than 75% efficiency, at surface intensity of 2.66 W/cm2. Schlieren imaging showed effective focusing at all focal lengths (30-60 mm). The image-guided HIFU device requires water or hydrogel coupling, and possibly water cooling. The results of the full characterization for lesion formation in tissue-mimicking phantoms and biological tissues will be presented. Possible applications include uterine fibroids, abnormal uterine bleeding, and intraoperative hemostasis of occult hemorrhage.

Multi-access laser communications terminal

NASA Technical Reports Server (NTRS)

1992-01-01

The Optical Multi-Access (OMA) Terminal is capable of establishing up to six simultaneous high-data-rate communication links between low-Earth-orbit satellites and a host satellite at synchronous orbit with only one 16-inch-diameter antenna on the synchronous satellite. The advantage over equivalent RF systems in space weight, power, and swept volume is great when applied to NASA satellite communications networks. A photograph of the 3-channel prototype constructed under the present contract to demonstrate the feasibility of the concept is presented. The telescope has a 10-inch clear aperture and a 22 deg full field of view. It consists of 4 refractive elements to achieve a telecentric focus, i.e., the focused beam is normal to the focal plane at all field angles. This feature permits image pick-up optics in the focal plane to track satellite images without tilting their optic axes to accommodate field angle. The geometry of the imager-pick-up concept and the coordinate system of the swinging arm and disk mechanism for image pick-up are shown. Optics in the arm relay the telescope focus to a communications and tracking receiver and introduce the transmitted beacon beam on a path collinear with the receive path. The electronic circuits for the communications and tracking receivers are contained on the arm and disk assemblies and relay signals to an associated PC-based operator's console for control of the arm and disk motor drive through a flexible cable which permits +/- 240 deg travel for each arm and disk assembly. Power supplies and laser transmitters are mounted in the cradle for the telescope. A single-mode fiber in the cable is used to carry the laser transmitter signal to the arm optics. The promise of the optical multi-access terminal towards which the prototype effort worked is shown. The emphasis in the prototype development was the demonstration of the unique aspect of the concept, and where possible, cost avoidance compromises were implemented in areas already proven on other programs. The design details are described in section 2, the prototype test results in section 3, additional development required in section 4, and conclusions in section 5.

MO-DE-202-04: Multimodality Image-Guided Surgery and Intervention: For the Rest of Us

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

Shekhar, R.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

PubMed

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method.

Multi-Task Linear Programming Discriminant Analysis for the Identification of Progressive MCI Individuals

PubMed Central

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method. PMID:24820966

Multi-resolution simulation of focused ultrasound propagation through ovine skull from a single-element transducer

NASA Astrophysics Data System (ADS)

Yoon, Kyungho; Lee, Wonhye; Croce, Phillip; Cammalleri, Amanda; Yoo, Seung-Schik

2018-05-01

Transcranial focused ultrasound (tFUS) is emerging as a non-invasive brain stimulation modality. Complicated interactions between acoustic pressure waves and osseous tissue introduce many challenges in the accurate targeting of an acoustic focus through the cranium. Image-guidance accompanied by a numerical simulation is desired to predict the intracranial acoustic propagation through the skull; however, such simulations typically demand heavy computation, which warrants an expedited processing method to provide on-site feedback for the user in guiding the acoustic focus to a particular brain region. In this paper, we present a multi-resolution simulation method based on the finite-difference time-domain formulation to model the transcranial propagation of acoustic waves from a single-element transducer (250 kHz). The multi-resolution approach improved computational efficiency by providing the flexibility in adjusting the spatial resolution. The simulation was also accelerated by utilizing parallelized computation through the graphic processing unit. To evaluate the accuracy of the method, we measured the actual acoustic fields through ex vivo sheep skulls with different sonication incident angles. The measured acoustic fields were compared to the simulation results in terms of focal location, dimensions, and pressure levels. The computational efficiency of the presented method was also assessed by comparing simulation speeds at various combinations of resolution grid settings. The multi-resolution grids consisting of 0.5 and 1.0 mm resolutions gave acceptable accuracy (under 3 mm in terms of focal position and dimension, less than 5% difference in peak pressure ratio) with a speed compatible with semi real-time user feedback (within 30 s). The proposed multi-resolution approach may serve as a novel tool for simulation-based guidance for tFUS applications.

Multi-resolution simulation of focused ultrasound propagation through ovine skull from a single-element transducer.

PubMed

Yoon, Kyungho; Lee, Wonhye; Croce, Phillip; Cammalleri, Amanda; Yoo, Seung-Schik

2018-05-10

Transcranial focused ultrasound (tFUS) is emerging as a non-invasive brain stimulation modality. Complicated interactions between acoustic pressure waves and osseous tissue introduce many challenges in the accurate targeting of an acoustic focus through the cranium. Image-guidance accompanied by a numerical simulation is desired to predict the intracranial acoustic propagation through the skull; however, such simulations typically demand heavy computation, which warrants an expedited processing method to provide on-site feedback for the user in guiding the acoustic focus to a particular brain region. In this paper, we present a multi-resolution simulation method based on the finite-difference time-domain formulation to model the transcranial propagation of acoustic waves from a single-element transducer (250 kHz). The multi-resolution approach improved computational efficiency by providing the flexibility in adjusting the spatial resolution. The simulation was also accelerated by utilizing parallelized computation through the graphic processing unit. To evaluate the accuracy of the method, we measured the actual acoustic fields through ex vivo sheep skulls with different sonication incident angles. The measured acoustic fields were compared to the simulation results in terms of focal location, dimensions, and pressure levels. The computational efficiency of the presented method was also assessed by comparing simulation speeds at various combinations of resolution grid settings. The multi-resolution grids consisting of 0.5 and 1.0 mm resolutions gave acceptable accuracy (under 3 mm in terms of focal position and dimension, less than 5% difference in peak pressure ratio) with a speed compatible with semi real-time user feedback (within 30 s). The proposed multi-resolution approach may serve as a novel tool for simulation-based guidance for tFUS applications.

Functional Imaging of the Lungs with Gas Agents

PubMed Central

Kruger, Stanley J.; Nagle, Scott K.; Couch, Marcus J.; Ohno, Yoshiharu; Albert, Mitchell; Fain, Sean B.

2015-01-01

This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI) – hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas – and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multi-detector computed tomography (CT). However, MRI also offers capabilities for fast multi-spectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultra-short echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. Relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease (COPD), asthma, and cystic fibrosis (CF) in both adults and children. PMID:26218920

Qualification of a multi-diagnostic detonator-output characterization procedure utilizing PMMA witness blocks

NASA Astrophysics Data System (ADS)

Biss, Matthew; Murphy, Michael; Lieber, Mark

2017-06-01

Experiments were conducted in an effort to qualify a multi-diagnostic characterization procedure for the performance output of a detonator when fired into a poly(methyl methacrylate) (PMMA) witness block. A suite of optical diagnostics were utilized in combination to both bound the shock wave interaction state at the detonator/PMMA interface and characterize the nature of the shock wave decay in PMMA. The diagnostics included the Shock Wave Image Framing Technique (SWIFT), a photocathode tube streak camera, and photonic Doppler velocimetry (PDV). High-precision, optically clear witness blocks permitted dynamic flow visualization of the shock wave in PMMA via focused shadowgraphy. SWIFT- and streak-imaging diagnostics captured the spatiotemporally evolving shock wave, providing a two-dimensional temporally discrete image set and a one-dimensional temporally continuous image, respectively. PDV provided the temporal velocity history of the detonator output along the detonator axis. Through combination of the results obtained, a bound was able to be placed on the interface condition and a more-physical profile representing the shock wave decay in PMMA for an exploding-bridgewire detonator was achieved.

Radiology and Enterprise Medical Imaging Extensions (REMIX).

PubMed

Erdal, Barbaros S; Prevedello, Luciano M; Qian, Songyue; Demirer, Mutlu; Little, Kevin; Ryu, John; O'Donnell, Thomas; White, Richard D

2018-02-01

Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of "big imaging data," as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence. These capabilities, along with documentation and guidance, explaining how to interact with a commercial system (e.g., PACS, EHR, commercial database) that currently exists in clinical environments, are to be made freely available.

Retinex Preprocessing for Improved Multi-Spectral Image Classification

NASA Technical Reports Server (NTRS)

Thompson, B.; Rahman, Z.; Park, S.

2000-01-01

The goal of multi-image classification is to identify and label "similar regions" within a scene. The ability to correctly classify a remotely sensed multi-image of a scene is affected by the ability of the classification process to adequately compensate for the effects of atmospheric variations and sensor anomalies. Better classification may be obtained if the multi-image is preprocessed before classification, so as to reduce the adverse effects of image formation. In this paper, we discuss the overall impact on multi-spectral image classification when the retinex image enhancement algorithm is used to preprocess multi-spectral images. The retinex is a multi-purpose image enhancement algorithm that performs dynamic range compression, reduces the dependence on lighting conditions, and generally enhances apparent spatial resolution. The retinex has been successfully applied to the enhancement of many different types of grayscale and color images. We show in this paper that retinex preprocessing improves the spatial structure of multi-spectral images and thus provides better within-class variations than would otherwise be obtained without the preprocessing. For a series of multi-spectral images obtained with diffuse and direct lighting, we show that without retinex preprocessing the class spectral signatures vary substantially with the lighting conditions. Whereas multi-dimensional clustering without preprocessing produced one-class homogeneous regions, the classification on the preprocessed images produced multi-class non-homogeneous regions. This lack of homogeneity is explained by the interaction between different agronomic treatments applied to the regions: the preprocessed images are closer to ground truth. The principle advantage that the retinex offers is that for different lighting conditions classifications derived from the retinex preprocessed images look remarkably "similar", and thus more consistent, whereas classifications derived from the original images, without preprocessing, are much less similar.

Fast Image Subtraction Using Multi-cores and GPUs

NASA Astrophysics Data System (ADS)

Hartung, Steven; Shukla, H.

2013-01-01

Many important image processing techniques in astronomy require a massive number of computations per pixel. Among them is an image differencing technique known as Optimal Image Subtraction (OIS), which is very useful for detecting and characterizing transient phenomena. Like many image processing routines, OIS computations increase proportionally with the number of pixels being processed, and the number of pixels in need of processing is increasing rapidly. Utilizing many-core graphical processing unit (GPU) technology in a hybrid conjunction with multi-core CPU and computer clustering technologies, this work presents a new astronomy image processing pipeline architecture. The chosen OIS implementation focuses on the 2nd order spatially-varying kernel with the Dirac delta function basis, a powerful image differencing method that has seen limited deployment in part because of the heavy computational burden. This tool can process standard image calibration and OIS differencing in a fashion that is scalable with the increasing data volume. It employs several parallel processing technologies in a hierarchical fashion in order to best utilize each of their strengths. The Linux/Unix based application can operate on a single computer, or on an MPI configured cluster, with or without GPU hardware. With GPU hardware available, even low-cost commercial video cards, the OIS convolution and subtraction times for large images can be accelerated by up to three orders of magnitude.

Three-Photon Luminescence of Gold Nanorods and Its Applications for High Contrast Tissue and Deep In Vivo Brain Imaging

PubMed Central

Wang, Shaowei; Xi, Wang; Cai, Fuhong; Zhao, Xinyuan; Xu, Zhengping; Qian, Jun; He, Sailing

2015-01-01

Gold nanoparticles can be used as contrast agents for bio-imaging applications. Here we studied multi-photon luminescence (MPL) of gold nanorods (GNRs), under the excitation of femtosecond (fs) lasers. GNRs functionalized with polyethylene glycol (PEG) molecules have high chemical and optical stability, and can be used as multi-photon luminescent nanoprobes for deep in vivo imaging of live animals. We have found that the depth of in vivo imaging is dependent upon the transmission and focal capability of the excitation light interacting with the GNRs. Our study focused on the comparison of MPL from GNRs with two different aspect ratios, as well as their ex vivo and in vivo imaging effects under 760 nm and 1000 nm excitation, respectively. Both of these wavelengths were located at an optically transparent window of biological tissue (700-1000 nm). PEGylated GNRs, which were intravenously injected into mice via the tail vein and accumulated in major organs and tumor tissue, showed high image contrast due to distinct three-photon luminescence (3PL) signals upon irradiation of a 1000 nm fs laser. Concerning in vivo mouse brain imaging, the 3PL imaging depth of GNRs under 1000 nm fs excitation could reach 600 μm, which was approximately 170 μm deeper than the two-photon luminescence (2PL) imaging depth of GNRs with a fs excitation of 760 nm. PMID:25553113

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

Rice crop growth monitoring using ENVISAT-1/ASAR AP mode

NASA Astrophysics Data System (ADS)

Konishi, Tomohisa; Suga, Yuzo; Omatu, Shigeru; Takeuchi, Shoji; Asonuma, Kazuyoshi

2007-10-01

Hiroshima Institute of Technology (HIT) is operating the direct down-links of microwave and optical earth observation satellite data in Japan. This study focuses on the validation for rice crop monitoring using microwave remotely sensed image data acquired by ENIVISAT-1 referring to ground truth data such as height of rice crop, vegetation cover rate and leaf area index in the test sites of Hiroshima district, the western part of Japan. ENVISAT-1/ASAR data has the capabilities for the monitoring of the rice crop growing cycle by using alternating cross polarization mode images. However, ASAR data is influenced by several parameters such as land cover structure, direction and alignment of rice crop fields in the test sites. In this study, the validation was carried out to be combined with microwave image data and ground truth data regarding rice crop fields to investigate the above parameters. Multi-temporal, multi-direction (descending and ascending) and multi-angle ASAR alternating cross polarization mode images were used to investigate during the rice crop growing cycle. On the other hand, LANDSAT-7/ETM+ data were used to detect land cover structure, direction and alignment of rice crop fields corresponding to the backscatter of ASAR. Finally, the extraction of rice planted area was attempted by using multi-temporal ASAR AP mode data such as VV/VH and HH/HV. As the result of this study, it is clear that the estimated rice planted area coincides with the existing statistical data for area of the rice crop field. In addition, HH/HV is more effective than VV/VH in the rice planted area extraction.

Smartphone based hand-held quantitative phase microscope using the transport of intensity equation method.

PubMed

Meng, Xin; Huang, Huachuan; Yan, Keding; Tian, Xiaolin; Yu, Wei; Cui, Haoyang; Kong, Yan; Xue, Liang; Liu, Cheng; Wang, Shouyu

2016-12-20

In order to realize high contrast imaging with portable devices for potential mobile healthcare, we demonstrate a hand-held smartphone based quantitative phase microscope using the transport of intensity equation method. With a cost-effective illumination source and compact microscope system, multi-focal images of samples can be captured by the smartphone's camera via manual focusing. Phase retrieval is performed using a self-developed Android application, which calculates sample phases from multi-plane intensities via solving the Poisson equation. We test the portable microscope using a random phase plate with known phases, and to further demonstrate its performance, a red blood cell smear, a Pap smear and monocot root and broad bean epidermis sections are also successfully imaged. Considering its advantages as an accurate, high-contrast, cost-effective and field-portable device, the smartphone based hand-held quantitative phase microscope is a promising tool which can be adopted in the future in remote healthcare and medical diagnosis.

Fourier Domain Iterative Approach to Optical Sectioning of 3d Translucent Objects for Ophthalmology Purposes

NASA Astrophysics Data System (ADS)

Razguli, A. V.; Iroshnikov, N. G.; Larichev, A. V.; Romanenko, T. E.; Goncharov, A. S.

2017-05-01

In this paper we deal with the problem of optical sectioning. This is a post processing step while investigating of 3D translucent medical objects based on rapid refocusing of the imaging system by the adaptive optics technique. Each image, captured in focal plane, can be represented as the sum of in-focus true section and out-of-focus images of the neighboring sections of the depth that are undesirable in the subsequent reconstruction of 3D object. The problem of optical sectioning under consideration is to elaborate a robust approach capable of obtaining a stack of cross section images purified from such distortions. For a typical sectioning statement arising in ophthalmology we propose a local iterative method in Fourier spectral plane. Compared to the non-local constant parameter selection for the whole spectral domain, the method demonstrates both improved sectioning results and a good level of scalability when implemented on multi-core CPUs.

Multislice spiral CT simulator for dynamic cardiopulmonary studies

NASA Astrophysics Data System (ADS)

De Francesco, Silvia; Ferreira da Silva, Augusto M.

2002-04-01

We've developed a Multi-slice Spiral CT Simulator modeling the acquisition process of a real tomograph over a 4-dimensional phantom (4D MCAT) of the human thorax. The simulator allows us to visually characterize artifacts due to insufficient temporal sampling and a priori evaluate the quality of the images obtained in cardio-pulmonary studies (both with single-/multi-slice and ECG gated acquisition processes). The simulating environment allows both for conventional and spiral scanning modes and includes a model of noise in the acquisition process. In case of spiral scanning, reconstruction facilities include longitudinal interpolation methods (360LI and 180LI both for single and multi-slice). Then, the reconstruction of the section is performed through FBP. The reconstructed images/volumes are affected by distortion due to insufficient temporal sampling of the moving object. The developed simulating environment allows us to investigate the nature of the distortion characterizing it qualitatively and quantitatively (using, for example, Herman's measures). Much of our work is focused on the determination of adequate temporal sampling and sinogram regularization techniques. At the moment, the simulator model is limited to the case of multi-slice tomograph, being planned as a next step of development the extension to cone beam or area detectors.

Sensitivity images for multi-view ultrasonic array inspection

NASA Astrophysics Data System (ADS)

Budyn, Nicolas; Bevan, Rhodri; Croxford, Anthony J.; Zhang, Jie; Wilcox, Paul D.; Kashubin, Artem; Cawley, Peter

2018-04-01

The multi-view total focusing method (TFM) is an imaging technique for ultrasonic full matrix array data that typically exploits ray paths with zero, one or two internal reflections in the inspected object and for all combinations of longitudinal and transverse modes. The fusion of this vast quantity of views is expected to increase the reliability of ultrasonic inspection; however, it is not trivial to determine which views and which areas are the most suited for the detection of a given type and orientation of defect. This work introduces sensitivity images that give the expected response of a defect in any part of the inspected object and for any view. These images are based on a ray-based analytical forward model. They can be used to determine which views and which areas lead to the highest probability of detection of the defect. They can also be used for quantitatively analyzing the effects of the parameters of the inspection (probe angle and position, for example) on the overall probability of detection. Finally, they can be used to rescale TFM images so that the different views have comparable amplitudes. This methodology is applied to experimental data and discussed.

Maximizing the Biochemical Resolving Power of Fluorescence Microscopy

PubMed Central

Esposito, Alessandro; Popleteeva, Marina; Venkitaraman, Ashok R.

2013-01-01

Most recent advances in fluorescence microscopy have focused on achieving spatial resolutions below the diffraction limit. However, the inherent capability of fluorescence microscopy to non-invasively resolve different biochemical or physical environments in biological samples has not yet been formally described, because an adequate and general theoretical framework is lacking. Here, we develop a mathematical characterization of the biochemical resolution in fluorescence detection with Fisher information analysis. To improve the precision and the resolution of quantitative imaging methods, we demonstrate strategies for the optimization of fluorescence lifetime, fluorescence anisotropy and hyperspectral detection, as well as different multi-dimensional techniques. We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. These strategies enable the optimal use of the information content available within the limited photon-budget typically available in fluorescence microscopy. This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can maximize the biochemical resolving power of fluorescence microscopy, an approach we term Hyper Dimensional Imaging Microscopy (HDIM). Our work provides a theoretical framework for the description of the biochemical resolution in fluorescence microscopy, irrespective of spatial resolution, and for the development of a new class of microscopes that exploit multi-parametric detection systems. PMID:24204821

Development and evaluation of multi-energy PbO dosimeter for quality assurance of image-guide radiation therapy devices

NASA Astrophysics Data System (ADS)

Kim, Kyo-Tae; Heo, Ye-Ji; Han, Moo-Jae; Oh, Kyung-Min; Lee, Young-Kyu; Kim, Shin-Wook; Park, Sung-Kwang

2017-04-01

In radiation therapy, accurate radiotherapy treatment plan (RTP) reproduction is necessary to optimize the clinical results. Thus, attempts have recently been made to ensure high RTP reproducibility using image-guide radiation therapy (IGRT) technology. However, the clinical use of digital X-ray equipment requires extended quality assurance (QA) for those devices, since the IGRT device quality determines the precision of intensity-modulated radiation therapy. The study described in this paper was focused on developing a multi-energy PbO dosimeter for IGRT device QA. The Schottky-type polycrystalline PbO dosimeter with a Au/PbO/ITO structure was evaluated by comparing its response coincidence, dose linearity, measurement reproducibility, linear attenuation coefficient, and percent depth dose with those of Si diode and standard ionization chamber dosimeters.

Optimization of PET-MR Registrations for Nonhuman Primates Using Mutual Information Measures: A Multi-Transform Method (MTM)

PubMed Central

Sandiego, Christine M.; Weinzimmer, David; Carson, Richard E.

2012-01-01

An important step in PET brain kinetic analysis is the registration of functional data to an anatomical MR image. Typically, PET-MR registrations in nonhuman primate neuroreceptor studies used PET images acquired early post-injection, (e.g., 0–10 min) to closely resemble the subject’s MR image. However, a substantial fraction of these registrations (~25%) fail due to the differences in kinetics and distribution for various radiotracer studies and conditions (e.g., blocking studies). The Multi-Transform Method (MTM) was developed to improve the success of registrations between PET and MR images. Two algorithms were evaluated, MTM-I and MTM-II. The approach involves creating multiple transformations by registering PET images of different time intervals, from a dynamic study, to a single reference (i.e., MR image) (MTM-I) or to multiple reference images (i.e., MR and PET images pre-registered to the MR) (MTM-II). Normalized mutual information was used to compute similarity between the transformed PET images and the reference image(s) to choose the optimal transformation. This final transformation is used to map the dynamic dataset into the animal’s anatomical MR space, required for kinetic analysis. The chosen transformed from MTM-I and MTM-II were evaluated using visual rating scores to assess the quality of spatial alignment between the resliced PET and reference. One hundred twenty PET datasets involving eleven different tracers from 3 different scanners were used to evaluate the MTM algorithms. Studies were performed with baboons and rhesus monkeys on the HR+, HRRT, and Focus-220. Successful transformations increased from 77.5%, 85.8%, to 96.7% using the 0–10 min method, MTM-I, and MTM-II, respectively, based on visual rating scores. The Multi-Transform Methods proved to be a robust technique for PET-MR registrations for a wide range of PET studies. PMID:22926293

HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening.

PubMed

Charoenkwan, Phasit; Hwang, Eric; Cutler, Robert W; Lee, Hua-Chin; Ko, Li-Wei; Huang, Hui-Ling; Ho, Shinn-Ying

2013-01-01

High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images. We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable MatLab project at http://iclab.life.nctu.edu.tw/HCS-Neurons. Few automatic methods focus on analyzing multi-neuron images collected from HCS used in drug discovery. We provided an automatic HCS-based method for generating accurate classifiers to classify neurons based on their phenotypic changes upon drug treatments. The proposed HCS-neurons method is helpful in identifying and classifying chemical or biological molecules that alter the morphology of a group of neurons in HCS.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

An algorithm for pavement crack detection based on multiscale space

NASA Astrophysics Data System (ADS)

Liu, Xiang-long; Li, Qing-quan

2006-10-01

Conventional human-visual and manual field pavement crack detection method and approaches are very costly, time-consuming, dangerous, labor-intensive and subjective. They possess various drawbacks such as having a high degree of variability of the measure results, being unable to provide meaningful quantitative information and almost always leading to inconsistencies in crack details over space and across evaluation, and with long-periodic measurement. With the development of the public transportation and the growth of the Material Flow System, the conventional method can far from meet the demands of it, thereby, the automatic pavement state data gathering and data analyzing system come to the focus of the vocation's attention, and developments in computer technology, digital image acquisition, image processing and multi-sensors technology made the system possible, but the complexity of the image processing always made the data processing and data analyzing come to the bottle-neck of the whole system. According to the above description, a robust and high-efficient parallel pavement crack detection algorithm based on Multi-Scale Space is proposed in this paper. The proposed method is based on the facts that: (1) the crack pixels in pavement images are darker than their surroundings and continuous; (2) the threshold values of gray-level pavement images are strongly related with the mean value and standard deviation of the pixel-grey intensities. The Multi-Scale Space method is used to improve the data processing speed and minimize the effectiveness caused by image noise. Experiment results demonstrate that the advantages are remarkable: (1) it can correctly discover tiny cracks, even from very noise pavement image; (2) the efficiency and accuracy of the proposed algorithm are superior; (3) its application-dependent nature can simplify the design of the entire system.

3D Modeling from Multi-views Images for Cultural Heritage in Wat-Pho, Thailand

NASA Astrophysics Data System (ADS)

Soontranon, N.; Srestasathiern, P.; Lawawirojwong, S.

2015-08-01

In Thailand, there are several types of (tangible) cultural heritages. This work focuses on 3D modeling of the heritage objects from multi-views images. The images are acquired by using a DSLR camera which costs around 1,500 (camera and lens). Comparing with a 3D laser scanner, the camera is cheaper and lighter than the 3D scanner. Hence, the camera is available for public users and convenient for accessing narrow areas. The acquired images consist of various sculptures and architectures in Wat-Pho which is a Buddhist temple located behind the Grand Palace (Bangkok, Thailand). Wat-Pho is known as temple of the reclining Buddha and the birthplace of traditional Thai massage. To compute the 3D models, a diagram is separated into following steps; Data acquisition, Image matching, Image calibration and orientation, Dense matching and Point cloud processing. For the initial work, small heritages less than 3 meters height are considered for the experimental results. A set of multi-views images of an interested object is used as input data for 3D modeling. In our experiments, 3D models are obtained from MICMAC (open source) software developed by IGN, France. The output of 3D models will be represented by using standard formats of 3D point clouds and triangulated surfaces such as .ply, .off, .obj, etc. To compute for the efficient 3D models, post-processing techniques are required for the final results e.g. noise reduction, surface simplification and reconstruction. The reconstructed 3D models can be provided for public access such as website, DVD, printed materials. The high accurate 3D models can also be used as reference data of the heritage objects that must be restored due to deterioration of a lifetime, natural disasters, etc.

Super-resolution imaging using multi- electrode CMUTs: theoretical design and simulation using point targets.

PubMed

You, Wei; Cretu, Edmond; Rohling, Robert

2013-11-01

This paper investigates a low computational cost, super-resolution ultrasound imaging method that leverages the asymmetric vibration mode of CMUTs. Instead of focusing on the broadband received signal on the entire CMUT membrane, we utilize the differential signal received on the left and right part of the membrane obtained by a multi-electrode CMUT structure. The differential signal reflects the asymmetric vibration mode of the CMUT cell excited by the nonuniform acoustic pressure field impinging on the membrane, and has a resonant component in immersion. To improve the resolution, we propose an imaging method as follows: a set of manifold matrices of CMUT responses for multiple focal directions are constructed off-line with a grid of hypothetical point targets. During the subsequent imaging process, the array sequentially steers to multiple angles, and the amplitudes (weights) of all hypothetical targets at each angle are estimated in a maximum a posteriori (MAP) process with the manifold matrix corresponding to that angle. Then, the weight vector undergoes a directional pruning process to remove the false estimation at other angles caused by the side lobe energy. Ultrasound imaging simulation is performed on ring and linear arrays with a simulation program adapted with a multi-electrode CMUT structure capable of obtaining both average and differential received signals. Because the differential signals from all receiving channels form a more distinctive temporal pattern than the average signals, better MAP estimation results are expected than using the average signals. The imaging simulation shows that using differential signals alone or in combination with the average signals produces better lateral resolution than the traditional phased array or using the average signals alone. This study is an exploration into the potential benefits of asymmetric CMUT responses for super-resolution imaging.

High resolution x-ray and gamma ray imaging using diffraction lenses with mechanically bent crystals

DOEpatents

Smither, Robert K [Hinsdale, IL

2008-12-23

A method for high spatial resolution imaging of a plurality of sources of x-ray and gamma-ray radiation is provided. High quality mechanically bent diffracting crystals of 0.1 mm radial width are used for focusing the radiation and directing the radiation to an array of detectors which is used for analyzing their addition to collect data as to the location of the source of radiation. A computer is used for converting the data to an image. The invention also provides for the use of a multi-component high resolution detector array and for narrow source and detector apertures.

A programmable light engine for quantitative single molecule TIRF and HILO imaging.

PubMed

van 't Hoff, Marcel; de Sars, Vincent; Oheim, Martin

2008-10-27

We report on a simple yet powerful implementation of objective-type total internal reflection fluorescence (TIRF) and highly inclined and laminated optical sheet (HILO, a type of dark-field) illumination. Instead of focusing the illuminating laser beam to a single spot close to the edge of the microscope objective, we are scanning during the acquisition of a fluorescence image the focused spot in a circular orbit, thereby illuminating the sample from various directions. We measure parameters relevant for quantitative image analysis during fluorescence image acquisition by capturing an image of the excitation light distribution in an equivalent objective backfocal plane (BFP). Operating at scan rates above 1 MHz, our programmable light engine allows directional averaging by circular spinning the spot even for sub-millisecond exposure times. We show that restoring the symmetry of TIRF/HILO illumination reduces scattering and produces an evenly lit field-of-view that affords on-line analysis of evanescnt-field excited fluorescence without pre-processing. Utilizing crossed acousto-optical deflectors, our device generates arbitrary intensity profiles in BFP, permitting variable-angle, multi-color illumination, or objective lenses to be rapidly exchanged.

Magnetoacoustic microscopic imaging of conductive objects and nanoparticles distribution

NASA Astrophysics Data System (ADS)

Liu, Siyu; Zhang, Ruochong; Luo, Yunqi; Zheng, Yuanjin

2017-09-01

Magnetoacoustic tomography has been demonstrated as a powerful and low-cost multi-wave imaging modality. However, due to limited spatial resolution and detection efficiency of magnetoacoustic signal, full potential of the magnetoacoustic imaging remains to be tapped. Here we report a high-resolution magnetoacoustic microscopy method, where magnetic stimulation is provided by a compact solenoid resonance coil connected with a matching network, and acoustic reception is realized by using a high-frequency focused ultrasound transducer. Scanning the magnetoacoustic microscopy system perpendicularly to the acoustic axis of the focused transducer would generate a two-dimensional microscopic image with acoustically determined lateral resolution. It is analyzed theoretically and demonstrated experimentally that magnetoacoustic generation in this microscopic system depends on the conductivity profile of conductive objects and localized distribution of superparamagnetic iron magnetic nanoparticles, based on two different but related implementations. The lateral resolution is characterized. Directional nature of magnetoacoustic vibration and imaging sensitivity for mapping magnetic nanoparticles are also discussed. The proposed microscopy system offers a high-resolution method that could potentially map intrinsic conductivity distribution in biological tissue and extraneous magnetic nanoparticles.

Extending the fundamental imaging-depth limit of multi-photon microscopy by imaging with photo-activatable fluorophores.

PubMed

Chen, Zhixing; Wei, Lu; Zhu, Xinxin; Min, Wei

2012-08-13

It is highly desirable to be able to optically probe biological activities deep inside live organisms. By employing a spatially confined excitation via a nonlinear transition, multiphoton fluorescence microscopy has become indispensable for imaging scattering samples. However, as the incident laser power drops exponentially with imaging depth due to scattering loss, the out-of-focus fluorescence eventually overwhelms the in-focal signal. The resulting loss of imaging contrast defines a fundamental imaging-depth limit, which cannot be overcome by increasing excitation intensity. Herein we propose to significantly extend this depth limit by multiphoton activation and imaging (MPAI) of photo-activatable fluorophores. The imaging contrast is drastically improved due to the created disparity of bright-dark quantum states in space. We demonstrate this new principle by both analytical theory and experiments on tissue phantoms labeled with synthetic caged fluorescein dye or genetically encodable photoactivatable GFP.

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.

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

Evoking Emotions and Unpacking Layered Histories through Young Children's Illustrations of Racial Bus Segregation

ERIC Educational Resources Information Center

Kuby, Candace R.

2013-01-01

Drawing on theories of multi-modality and critical visual literacy, this article focuses on images that five-and six year-olds painted in a class-made book, Voice on the Bus, about racial segregation. The article discusses how children used illustrations to convey their understandings of Rosa Parks' bus arrest in Alabama. A post-structural view…

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…

Visualization of evolving laser-generated structures by frequency domain tomography

NASA Astrophysics Data System (ADS)

Chang, Yenyu; Li, Zhengyan; Wang, Xiaoming; Zgadzaj, Rafal; Downer, Michael

2011-10-01

We introduce frequency domain tomography (FDT) for single-shot visualization of time-evolving refractive index structures (e.g. laser wakefields, nonlinear index structures) moving at light-speed. Previous researchers demonstrated single-shot frequency domain holography (FDH), in which a probe-reference pulse pair co- propagates with the laser-generated structure, to obtain snapshot-like images. However, in FDH, information about the structure's evolution is averaged. To visualize an evolving structure, we use several frequency domain streak cameras (FDSCs), in each of which a probe-reference pulse pair propagates at an angle to the propagation direction of the laser-generated structure. The combination of several FDSCs constitutes the FDT system. We will present experimental results for a 4-probe FDT system that has imaged the whole-beam self-focusing of a pump pulse propagating through glass in a single laser shot. Combining temporal and angle multiplexing methods, we successfully processed data from four probe pulses in one spectrometer in a single-shot. The output of data processing is a multi-frame movie of the self- focusing pulse. Our results promise the possibility of visualizing evolving laser wakefield structures that underlie laser-plasma accelerators used for multi-GeV electron acceleration.

The Slope Imaging Multi-Polarization Photon-Counting Lidar: Development and Performance Results

NASA Technical Reports Server (NTRS)

Dabney, Phillip

2010-01-01

The Slope Imaging Multi-polarization Photon-counting Lidar is an airborne instrument developed to demonstrate laser altimetry measurement methods that will enable more efficient observations of topography and surface properties from space. The instrument was developed through the NASA Earth Science Technology Office Instrument Incubator Program with a focus on cryosphere remote sensing. The SIMPL transmitter is an 11 KHz, 1064 nm, plane-polarized micropulse laser transmitter that is frequency doubled to 532 nm and split into four push-broom beams. The receiver employs single-photon, polarimetric ranging at 532 and 1064 nm using Single Photon Counting Modules in order to achieve simultaneous sampling of surface elevation, slope, roughness and depolarizing scattering properties, the latter used to differentiate surface types. Data acquired over ice-covered Lake Erie in February, 2009 are documenting SIMPL s measurement performance and capabilities, demonstrating differentiation of open water and several ice cover types. ICESat-2 will employ several of the technologies advanced by SIMPL, including micropulse, single photon ranging in a multi-beam, push-broom configuration operating at 532 nm.

Light field measurement based on the single-lens coherent diffraction imaging

NASA Astrophysics Data System (ADS)

Shen, Cheng; Tan, Jiubin; Liu, Zhengjun

2018-01-01

Plenoptic camera and holography are popular light field measurement techniques. However, the low resolution or the complex apparatus hinders their widespread application. In this paper, we put forward a new light field measurement scheme. The lens is introduced into coherent diffraction imaging to operate an optical transform, extended fractional Fourier transform. Combined with the multi-image phase retrieval algorithm, the scheme is proved to hold several advantages. It gets rid of the support requirement and is much easier to implement while keeping a high resolution by making full use of the detector plane. Also, it is verified that our scheme has a superiority over the direct lens focusing imaging in amplitude measurement accuracy and phase retrieval ability.

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

Developing an Automated Science Analysis System for Mars Surface Exploration for MSL and Beyond

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Hart, S. D.; Shi, X.; Siegel, V. L.

2004-01-01

We are developing an automated science analysis system that could be utilized by robotic or human explorers on Mars (or even in remote locations on Earth) to improve the quality and quantity of science data returned. Three components of this system (our rock, layer, and horizon detectors) [1] have been incorporated into the JPL CLARITY system for possible use by MSL and future Mars robotic missions. Two other components include a multi-spectral image compression (SPEC) algorithm for pancam-type images with multiple filters and image fusion algorithms that identify the in focus regions of individual images in an image focal series [2]. Recently, we have been working to combine image and spectral data, and other knowledge to identify both rocks and minerals. Here we present our progress on developing an igneous rock detection system.

Accuracy of Shack-Hartmann wavefront sensor using a coherent wound fibre image bundle

NASA Astrophysics Data System (ADS)

Zheng, Jessica R.; Goodwin, Michael; Lawrence, Jon

2018-03-01

Shack-Hartmannwavefront sensors using wound fibre image bundles are desired for multi-object adaptive optical systems to provide large multiplex positioned by Starbugs. The use of a large-sized wound fibre image bundle provides the flexibility to use more sub-apertures wavefront sensor for ELTs. These compact wavefront sensors take advantage of large focal surfaces such as the Giant Magellan Telescope. The focus of this paper is to study the wound fibre image bundle structure defects effect on the centroid measurement accuracy of a Shack-Hartmann wavefront sensor. We use the first moment centroid method to estimate the centroid of a focused Gaussian beam sampled by a simulated bundle. Spot estimation accuracy with wound fibre image bundle and its structure impact on wavefront measurement accuracy statistics are addressed. Our results show that when the measurement signal-to-noise ratio is high, the centroid measurement accuracy is dominated by the wound fibre image bundle structure, e.g. tile angle and gap spacing. For the measurement with low signal-to-noise ratio, its accuracy is influenced by the read noise of the detector instead of the wound fibre image bundle structure defects. We demonstrate this both with simulation and experimentally. We provide a statistical model of the centroid and wavefront error of a wound fibre image bundle found through experiment.

Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

PubMed

Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

2014-01-01

The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

The design and application of a multi-band IR imager

NASA Astrophysics Data System (ADS)

Li, Lijuan

2018-02-01

Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

Multifaceted free-space image distributor for optical interconnects in massively parrallel processing

NASA Astrophysics Data System (ADS)

Zhao, Feng; Frietman, Edward E. E.; Han, Zhong; Chen, Ray T.

1999-04-01

A characteristic feature of a conventional von Neumann computer is that computing power is delivered by a single processing unit. Although increasing the clock frequency improves the performance of the computer, the switching speed of the semiconductor devices and the finite speed at which electrical signals propagate along the bus set the boundaries. Architectures containing large numbers of nodes can solve this performance dilemma, with the comment that main obstacles in designing such systems are caused by difficulties to come up with solutions that guarantee efficient communications among the nodes. Exchanging data becomes really a bottleneck should al nodes be connected by a shared resource. Only optics, due to its inherent parallelism, could solve that bottleneck. Here, we explore a multi-faceted free space image distributor to be used in optical interconnects in massively parallel processing. In this paper, physical and optical models of the image distributor are focused on from diffraction theory of light wave to optical simulations. the general features and the performance of the image distributor are also described. The new structure of an image distributor and the simulations for it are discussed. From the digital simulation and experiment, it is found that the multi-faceted free space image distributing technique is quite suitable for free space optical interconnection in massively parallel processing and new structure of the multifaceted free space image distributor would perform better.

Modular "plug-and-play" capsules for multi-capsule environment in the gastrointestinal tract.

PubMed

Phee, S J; Ting, E K; Lin, L; Huynh, V A; Kencana, A P; Wong, K J; Tan, S L

2009-01-01

The invention of wireless capsule endoscopy has opened new ways of diagnosing and treating diseases in the gastrointestinal tract. Current wireless capsules can perform simple operations such as imaging and data collection (like temperature, pressure, and pH) in the gastrointestinal tract. Researchers are now focusing on adding more sophisticated functions such as drug delivery, surgical clips/tags deployment, and tissue samples collection. The finite on-board power on these capsules is one of the factors that limits the functionalities of these wireless capsules. Thus multiple application-specific capsules would be needed to complete an endoscopic operation. This would give rise to a multi-capsule environment. Having a modular "plug-and-play" capsule design would facilitate doctors in configuring multiple application-specific capsules, e.g. tagging capsule, for use in the gastrointestinal tract. This multi-capsule environment also has the advantage of reducing power consumption through asymmetric multi-hop communication.

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network

PubMed Central

Qu, Xiaobo; He, Yifan

2018-01-01

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods. PMID:29509666

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

PubMed

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

The Parsec-Scale Morphology of Southern GPS Sources

NASA Astrophysics Data System (ADS)

Edwards, P. G.; Tingay, S. J.

2016-12-01

Multi-frequency, multi-epoch ATCA observations of a sample of AGN resulted in the identification of nine new candidate Giga-hertz Peaked Spectrum sources. Here, we present Long Baseline Array observations at 4.8 GHz of the four candidates with no previously published VLBI image, and consider these together with previously published VLBI images of the other five sources. We find core-jet or compact double morphologies dominate, with further observations required to distinguish between these two possibilities for some sources. One of the nine candidates, PKS 1831-711, displays appreciable variability, suggesting its GPS spectrum is more ephemeral in nature. We focus in particular on the apparent relationship between a narrow spectral width and `compact double' parsec-scale morphology, finding further examples, but also exceptions to this trend. An examination of the VLBI morphologies high-redshift (z > 3) sub-class of GPS sources suggests that core-jet morphologies predominate in this class.

Multi-frequency tapping-mode atomic force microscopy beyond three eigenmodes in ambient air

PubMed Central

An, Sangmin; Long, Christian J

2014-01-01

Summary We present an exploratory study of multimodal tapping-mode atomic force microscopy driving more than three cantilever eigenmodes. We present tetramodal (4-eigenmode) imaging experiments conducted on a thin polytetrafluoroethylene (PTFE) film and computational simulations of pentamodal (5-eigenmode) cantilever dynamics and spectroscopy, focusing on the case of large amplitude ratios between the fundamental eigenmode and the higher eigenmodes. We discuss the dynamic complexities of the tip response in time and frequency space, as well as the average amplitude and phase response. We also illustrate typical images and spectroscopy curves and provide a very brief description of the observed contrast. Overall, our findings are promising in that they help to open the door to increasing sophistication and greater versatility in multi-frequency AFM through the incorporation of a larger number of driven eigenmodes, and in highlighting specific future research opportunities. PMID:25383276

Detection systems for mass spectrometry imaging: a perspective on novel developments with a focus on active pixel detectors.

PubMed

Jungmann, Julia H; Heeren, Ron M A

2013-01-15

Instrumental developments for imaging and individual particle detection for biomolecular mass spectrometry (imaging) and fundamental atomic and molecular physics studies are reviewed. Ion-counting detectors, array detection systems and high mass detectors for mass spectrometry (imaging) are treated. State-of-the-art detection systems for multi-dimensional ion, electron and photon detection are highlighted. Their application and performance in three different imaging modes--integrated, selected and spectral image detection--are described. Electro-optical and microchannel-plate-based systems are contrasted. The analytical capabilities of solid-state pixel detectors--both charge coupled device (CCD) and complementary metal oxide semiconductor (CMOS) chips--are introduced. The Medipix/Timepix detector family is described as an example of a CMOS hybrid active pixel sensor. Alternative imaging methods for particle detection and their potential for future applications are investigated. Copyright © 2012 John Wiley & Sons, Ltd.

Accessing Multi-Dimensional Images and Data Cubes in the Virtual Observatory

NASA Astrophysics Data System (ADS)

Tody, Douglas; Plante, R. L.; Berriman, G. B.; Cresitello-Dittmar, M.; Good, J.; Graham, M.; Greene, G.; Hanisch, R. J.; Jenness, T.; Lazio, J.; Norris, P.; Pevunova, O.; Rots, A. H.

2014-01-01

Telescopes across the spectrum are routinely producing multi-dimensional images and datasets, such as Doppler velocity cubes, polarization datasets, and time-resolved “movies.” Examples of current telescopes producing such multi-dimensional images include the JVLA, ALMA, and the IFU instruments on large optical and near-infrared wavelength telescopes. In the near future, both the LSST and JWST will also produce such multi-dimensional images routinely. High-energy instruments such as Chandra produce event datasets that are also a form of multi-dimensional data, in effect being a very sparse multi-dimensional image. Ensuring that the data sets produced by these telescopes can be both discovered and accessed by the community is essential and is part of the mission of the Virtual Observatory (VO). The Virtual Astronomical Observatory (VAO, http://www.usvao.org/), in conjunction with its international partners in the International Virtual Observatory Alliance (IVOA), has developed a protocol and an initial demonstration service designed for the publication, discovery, and access of arbitrarily large multi-dimensional images. The protocol describing multi-dimensional images is the Simple Image Access Protocol, version 2, which provides the minimal set of metadata required to characterize a multi-dimensional image for its discovery and access. A companion Image Data Model formally defines the semantics and structure of multi-dimensional images independently of how they are serialized, while providing capabilities such as support for sparse data that are essential to deal effectively with large cubes. A prototype data access service has been deployed and tested, using a suite of multi-dimensional images from a variety of telescopes. The prototype has demonstrated the capability to discover and remotely access multi-dimensional data via standard VO protocols. The prototype informs the specification of a protocol that will be submitted to the IVOA for approval, with an operational data cube service to be delivered in mid-2014. An associated user-installable VO data service framework will provide the capabilities required to publish VO-compatible multi-dimensional images or data cubes.

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification

PubMed Central

Pan, Jianjun

2018-01-01

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively. PMID:29382073

Analyzing soil erosion using a multi-temporal UAV data set after one year of active agriculture in Navarra, Spain

NASA Astrophysics Data System (ADS)

Anders, Niels; Keesstra, Saskia; Masselink, Rens

2014-05-01

Unmanned Aerial System (UAS) are becoming popular tools in the geosciences due to improving technology and processing/analysis techniques. They can potentially fill the gap between spaceborne or manned aircraft remote sensing and terrestrial remote sensing, both in terms of spatial and temporal resolution. In this study we analyze a multi-temporal data set that was acquired with a fixed-wing UAS in an agricultural catchment (2 sq. km) in Navarra, Spain. The goal of this study is to register soil erosion activity after one year of agricultural activity. The aircraft was equipped with a Panasonic GX1 16MP pocket camera with a 20 mm lens to capture normal JPEG RGB images. The data set consisted of two sets of imagery acquired in the end of February in 2013 and 2014 after harvesting. The raw images were processed using Agisoft Photoscan Pro which includes the structure-from-motion (SfM) and multi-view stereopsis (MVS) algorithms producing digital surface models and orthophotos of both data sets. A discussion is presented that is focused on the suitability of multi-temporal UAS data and SfM/MVS processing for quantifying soil loss, mapping the distribution of eroded materials and analyzing re-occurrences of rill patterns after plowing.

Distinguishing human normal or cancerous esophagus tissue ex vivo using multiphoton microscopy

NASA Astrophysics Data System (ADS)

Liu, N. R.; Chen, G. N.; Wu, S. S.; Chen, R.

2014-02-01

Application of multiphoton microscopy (MPM) to clinical cancer research has greatly developed over the last few years. In this paper, we mainly focus on two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) for investigating esophageal cancer. We chiefly discuss the SHG/TPEF image and spectral characteristics of normal and cancerous esophagus submucosa with the combined multi-channel imaging mode and Lambda mode of a multiphoton microscope (LSM 510 META). Great differences can be detected, such as collagen content and morphology, glandular-shaped cancer cells, TPEF/SHG intensity ratio, and so on, which demonstrate that the multiphoton imaging technique has the potential ability for minimally-invasive early cancer diagnosis.

Segmentation of Vasculature from Fluorescently Labeled Endothelial Cells in Multi-Photon Microscopy Images.

PubMed

Bates, Russell; Irving, Benjamin; Markelc, Bostjan; Kaeppler, Jakob; Brown, Graham; Muschel, Ruth J; Brady, Sir Michael; Grau, Vicente; Schnabel, Julia A

2017-08-09

Vasculature is known to be of key biological significance, especially in the study of tumors. As such, considerable effort has been focused on the automated segmentation of vasculature in medical and pre-clinical images. The majority of vascular segmentation methods focus on bloodpool labeling methods, however, particularly in the study of tumors it is of particular interest to be able to visualize both perfused and non-perfused vasculature. Imaging vasculature by highlighting the endothelium provides a way to separate the morphology of vasculature from the potentially confounding factor of perfusion. Here we present a method for the segmentation of tumor vasculature in 3D fluorescence microscopy images using signals from the endothelial and surrounding cells. We show that our method can provide complete and semantically meaningful segmentations of complex vasculature using a supervoxel-Markov Random Field approach. We show that in terms of extracting meaningful segmentations of the vasculature, our method out-performs both a state-ofthe- art method, specific to these data, as well as more classical vasculature segmentation methods.

Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework

PubMed Central

Grigis, Antoine; Goyard, David; Cherbonnier, Robin; Gareau, Thomas; Papadopoulos Orfanos, Dimitri; Chauvat, Nicolas; Di Mascio, Adrien; Schumann, Gunter; Spooren, Will; Murphy, Declan; Frouin, Vincent

2017-01-01

In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts. PMID:28360851

Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework.

PubMed

Grigis, Antoine; Goyard, David; Cherbonnier, Robin; Gareau, Thomas; Papadopoulos Orfanos, Dimitri; Chauvat, Nicolas; Di Mascio, Adrien; Schumann, Gunter; Spooren, Will; Murphy, Declan; Frouin, Vincent

2017-01-01

In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts.

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images

PubMed Central

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections. PMID:29875639

MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images.

PubMed

Varando, Gherardo; Benavides-Piccione, Ruth; Muñoz, Alberto; Kastanauskaite, Asta; Bielza, Concha; Larrañaga, Pedro; DeFelipe, Javier

2018-01-01

The development of 3D visualization and reconstruction methods to analyse microscopic structures at different levels of resolutions is of great importance to define brain microorganization and connectivity. MultiMap is a new tool that allows the visualization, 3D segmentation and quantification of fluorescent structures selectively in the neuropil from large stacks of confocal microscopy images. The major contribution of this tool is the posibility to easily navigate and create regions of interest of any shape and size within a large brain area that will be automatically 3D segmented and quantified to determine the density of puncta in the neuropil. As a proof of concept, we focused on the analysis of glutamatergic and GABAergic presynaptic axon terminals in the mouse hippocampal region to demonstrate its use as a tool to provide putative excitatory and inhibitory synaptic maps. The segmentation and quantification method has been validated over expert labeled images of the mouse hippocampus and over two benchmark datasets, obtaining comparable results to the expert detections.

Multi-focus image fusion algorithm using NSCT and MPCNN

NASA Astrophysics Data System (ADS)

Liu, Kang; Wang, Lianli

2018-04-01

Based on nonsubsampled contourlet transform (NSCT) and modified pulse coupled neural network (MPCNN), the paper proposes an effective method of image fusion. Firstly, the paper decomposes the source image into the low-frequency components and high-frequency components using NSCT, and then processes the low-frequency components by regional statistical fusion rules. For high-frequency components, the paper calculates the spatial frequency (SF), which is input into MPCNN model to get relevant coefficients according to the fire-mapping image of MPCNN. At last, the paper restructures the final image by inverse transformation of low-frequency and high-frequency components. Compared with the wavelet transformation (WT) and the traditional NSCT algorithm, experimental results indicate that the method proposed in this paper achieves an improvement both in human visual perception and objective evaluation. It indicates that the method is effective, practical and good performance.

Fluorescence hyperspectral imaging technique for foreign substance detection on fresh-cut lettuce.

PubMed

Mo, Changyeun; Kim, Giyoung; Kim, Moon S; Lim, Jongguk; Cho, Hyunjeong; Barnaby, Jinyoung Yang; Cho, Byoung-Kwan

2017-09-01

Non-destructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed to detect worms on fresh-cut lettuce. The optimal wavebands for detecting the worms were investigated using the one-way ANOVA and correlation analyses. The worm detection imaging algorithms, RSI-I (492-626)/492 , provided a prediction accuracy of 99.0%. The fluorescence HSI techniques indicated that the spectral images with a pixel size of 1 × 1 mm had the best classification accuracy for worms. The overall results demonstrate that fluorescence HSI techniques have the potential to detect worms on fresh-cut lettuce. In the future, we will focus on developing a multi-spectral imaging system to detect foreign substances such as worms, slugs and earthworms on fresh-cut lettuce. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

EIT image regularization by a new Multi-Objective Simulated Annealing algorithm.

PubMed

Castro Martins, Thiago; Sales Guerra Tsuzuki, Marcos

2015-01-01

Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

Histotripsy Thrombolysis on Retracted Clots

PubMed Central

Zhang, Xi; Owens, Gabe E.; Cain, Charles A.; Gurm, Hitinder S.; Macoskey, Jonathan; Xu, Zhen

2016-01-01

Retracted blood clots have been previously recognized to be more resistant to drug-based thrombolysis methods, even with ultrasound and microbubble enhancements. Microtripsy, a new histotripsy approach, has been investigated as a non-invasive, drug-free, and image-guided method that uses ultrasound to break up clots with improved treatment accuracy and a lower risk of vessel damage when compared to the traditional histotripsy thrombolysis approach. Unlike drug-mediated thrombolysis, which is dependent on the permeation of the thrombolytic agents into the clot, microtripsy controls acoustic cavitation to fractionate clots. We hypothesize that microtripsy thrombolysis is effective on retracted clots and that the treatment efficacy can be enhanced using strategies incorporating electronic focal steering. To test our hypothesis, retracted clots were prepared in vitro and the mechanical properties were quantitatively characterized. Microtripsy thrombolysis was applied on the retracted clots in an in vitro flow model using three different strategies: single-focus, electronically-steered multi-focus, and a dual-pass multi-focus strategy. Results show that microtripsy was used to successfully generate a flow channel through the retracted clot and the flow was restored. The multi-focus and the dual-pass treatments incorporating the electronic focal steering significantly increased the recanalized flow channel size compared to the single-focus treatments. The dual-pass treatments achieved a restored flow rate up to 324 mL/min without cavitation contacting the vessel wall. The clot debris particles generated from microtripsy thrombolysis remained within the safe range. The results in this study show the potential of microtripsy thrombolysis for retracted clot recanalization with the enhancement of electronic focal steering. PMID:27166017

The stress-reducing effects of art in pediatric health care: art preferences of healthy children and hospitalized children.

PubMed

Eisen, Sarajane L; Ulrich, Roger S; Shepley, Mardelle M; Varni, James W; Sherman, Sandra

2008-09-01

Art is assumed to possess therapeutic benefits of healing for children, as part of patient-focused design in health care. Since the psychological and physiological well-being of children in health care settings is extremely important in contributing to the healing process, it is vitally important to identify what type of art supports stress reduction. Based on adult studies, nature art was anticipated to be the most preferred and to have stress-reducing effects on pediatric patients. Nature art refers to art images dominated by natural vegetation, flowers or water. The objective of this study was to investigate what type of art image children prefer, and what type of art image has potentially stress-reducing effects on children in hospitals. This study used a three-phase, multi-method approach with children aged 5-17 years: a focus group study (129 participants), a randomized study (48 participants), and a quasi-experimental study design (48 participants). Findings were evaluated from three phases.

Eyecup scope—optical recordings of light stimulus-evoked fluorescence signals in the retina

PubMed Central

Hausselt, Susanne E.; Breuninger, Tobias; Castell, Xavier; Denk, Winfried; Margolis, David J.; Detwiler, Peter B.

2009-01-01

Dendritic signals play an essential role in processing visual information in the retina. To study them in neurites too small for electrical recording, we developed an instrument that combines a multi-photon (MP) microscope with a through-the-objective high-resolution visual stimulator. An upright microscope was designed that uses the objective lens for both MP imaging and delivery of visual stimuli to functionally intact retinal explants or eyecup preparations. The stimulator consists of a miniature liquid-crystal-on-silicon display coupled into the optical path of an infrared-excitation laser-scanning microscope. A pair of custom-made dichroic filters allows light from the excitation laser and three spectral bands (‘colors’) from the stimulator to reach the retina, leaving two intermediate bands for fluorescence imaging. Special optics allow displacement of the stimulator focus relative to the imaging focus. Spatially resolved changes in calcium-indicator fluorescence in response to visual stimuli were recorded in dendrites of different types of mammalian retinal neurons. PMID:19023590

Star polymer-based unimolecular micelles and their application in bio-imaging and diagnosis.

PubMed

Jin, Xin; Sun, Pei; Tong, Gangsheng; Zhu, Xinyuan

2018-02-03

As a novel kind of polymer with covalently linked core-shell structure, star polymers behave in nanostructure in aqueous medium at all concentration range, as unimolecular micelles at high dilution condition and multi-micelle aggregates in other situations. The unique morphologies endow star polymers with excellent stability and functions, making them a promising platform for bio-application. A variety of functions including imaging and therapeutics can be achieved through rational structure design of star polymers, and the existence of plentiful end-groups on shell offers the opportunity for further modification. In the last decades, star polymers have become an attracting platform on fabrication of novel nano-systems for bio-imaging and diagnosis. Focusing on the specific topology and physicochemical properties of star polymers, we have reviewed recent development of star polymer-based unimolecular micelles and their bio-application in imaging and diagnosis. The main content of this review summarizes the synthesis of integrated architecture of star polymers and their self-assembly behavior in aqueous medium, focusing especially on the recent advances on their bio-imaging application and diagnosis use. Finally, we conclude with remarks and give some outlooks for further exploration in this field. Copyright © 2018 Elsevier Ltd. All rights reserved.

SU-D-213-03: Towards An Optimized 3D Scintillation Dosimetry Tool for Quality Assurance of Dynamic Radiotherapy Techniques

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

Rilling, M; Centre de Recherche sur le Cancer, Hôtel-Dieu de Québec, Quebec City, QC; Département de radio-oncologie, CHU de Québec, Quebec City, QC

2015-06-15

Purpose: The purpose of this work is to simulate a multi-focus plenoptic camera used as the measuring device in a real-time three-dimensional scintillation dosimeter. Simulating and optimizing this realistic optical system will bridge the technological gap between concept validation and a clinically viable tool that can provide highly efficient, accurate and precise measurements for dynamic radiotherapy techniques. Methods: The experimental prototype, previously developed for proof of concept purposes, uses an off-the-shelf multi-focus plenoptic camera. With an array of interleaved microlenses of different focal lengths, this camera records spatial and angular information of light emitted by a plastic scintillator volume. Themore » three distinct microlens focal lengths were determined experimentally for use as baseline parameters by measuring image-to-object magnification for different distances in object space. A simulated plenoptic system was implemented using the non-sequential ray tracing software Zemax: this tool allows complete simulation of multiple optical paths by modeling interactions at interfaces such as scatter, diffraction, reflection and refraction. The active sensor was modeled based on the camera manufacturer specifications by a 2048×2048, 5 µm-pixel pitch sensor. Planar light sources, simulating the plastic scintillator volume, were employed for ray tracing simulations. Results: The microlens focal lengths were determined to be 384, 327 and 290 µm. A realistic multi-focus plenoptic system, with independently defined and optimizable specifications, was fully simulated. A f/2.9 and 54 mm-focal length Double Gauss objective was modeled as the system’s main lens. A three-focal length hexagonal microlens array of 250-µm thickness was designed, acting as an image-relay system between the main lens and sensor. Conclusion: Simulation of a fully modeled multi-focus plenoptic camera enables the decoupled optimization of the main lens and microlens specifications. This work leads the way to improving the 3D dosimeter’s achievable resolution, efficiency and build for providing a quality assurance tool fully meeting clinical needs. M.R. is financially supported by a Master’s Canada Graduate Scholarship from the NSERC. This research is also supported by the NSERC Industrial Research Chair in Optical Design.« less

Non-invasive MRI detection of individual pellets in the human stomach.

PubMed

Knörgen, Manfred; Spielmann, Rolf Peter; Abdalla, Ahmed; Metz, Hendrik; Mäder, Karsten

2010-01-01

MRI is a powerful and non-invasive method to follow the fate of oral drug delivery systems in humans. Until now, most MRI studies focused on monolithic dosage forms (tablets and capsules). Small-sized multi-particulate drug delivery systems are very difficult to detect due to the poor differentiation between the delivery system and the food. A new approach was developed to overcome the described difficulties and permit the selective imaging of small multi-particulate dosage forms within the stomach. We took advantage of the different sensitivities to susceptibility artefacts of T(2)-weighted spin-echo sequences and T(2)-weighted gradient echo pulse sequences. Using a combination of both methods within a breath hold followed by a specific mathematical image analysis involving co-registration, motion correction, voxel-by-voxel comparison of the maps from different pulse sequences and graphic 2D-/3D-presentation, we were able to obtain pictures with a high sensitivity due to susceptibility effects caused by a 1% magnetite load. By means of the new imaging sequence, single pellets as small as 1mm can be detected with high selectivity within surrounding heterogeneous food in the human stomach. The developed method greatly expands the use of MRI to study the fate of oral multi-particulate drug delivery systems and their food dependency in men. Copyright 2009 Elsevier B.V. All rights reserved.

Fully refocused multi-shot spatiotemporally encoded MRI: robust imaging in the presence of metallic implants.

PubMed

Ben-Eliezer, Noam; Solomon, Eddy; Harel, Elad; Nevo, Nava; Frydman, Lucio

2012-12-01

An approach has been recently introduced for acquiring arbitrary 2D NMR spectra or images in a single scan, based on the use of frequency-swept RF pulses for the sequential excitation and acquisition of the spins response. This spatiotemporal-encoding (SPEN) approach enables a unique, voxel-by-voxel refocusing of all frequency shifts in the sample, for all instants throughout the data acquisition. The present study investigates the use of this full-refocusing aspect of SPEN-based imaging in the multi-shot MRI of objects, subject to sizable field inhomogeneities that complicate conventional imaging approaches. 2D MRI experiments were performed at 7 T on phantoms and on mice in vivo, focusing on imaging in proximity to metallic objects. Fully refocused SPEN-based spin echo imaging sequences were implemented, using both Cartesian and back-projection trajectories, and compared with k-space encoded spin echo imaging schemes collected on identical samples under equal bandwidths and acquisition timing conditions. In all cases assayed, the fully refocused spatiotemporally encoded experiments evidenced a ca. 50 % reduction in signal dephasing in the proximity of the metal, as compared to analogous results stemming from the k-space encoded spin echo counterparts. The results in this study suggest that SPEN-based acquisition schemes carry the potential to overcome strong field inhomogeneities, of the kind that currently preclude high-field, high-resolution tissue characterizations in the neighborhood of metallic implants.

Automated microscopy system for detection and genetic characterization of fetal nucleated red blood cells on slides

NASA Astrophysics Data System (ADS)

Ravkin, Ilya; Temov, Vladimir

1998-04-01

The detection and genetic analysis of fetal cells in maternal blood will permit noninvasive prenatal screening for genetic defects. Applied Imaging has developed and is currently evaluating a system for semiautomatic detection of fetal nucleated red blood cells on slides and acquisition of their DNA probe FISH images. The specimens are blood smears from pregnant women (9 - 16 weeks gestation) enriched for nucleated red blood cells (NRBC). The cells are identified by using labeled monoclonal antibodies directed to different types of hemoglobin chains (gamma, epsilon); the nuclei are stained with DAPI. The Applied Imaging system has been implemented with both Olympus BX and Nikon Eclipse series microscopes which were equipped with transmission and fluorescence optics. The system includes the following motorized components: stage, focus, transmission, and fluorescence filter wheels. A video camera with light integration (COHU 4910) permits low light imaging. The software capabilities include scanning, relocation, autofocusing, feature extraction, facilities for operator review, and data analysis. Detection of fetal NRBCs is achieved by employing a combination of brightfield and fluorescence images of nuclear and cytoplasmic markers. The brightfield and fluorescence images are all obtained with a single multi-bandpass dichroic mirror. A Z-stack of DNA probe FISH images is acquired by moving focus and switching excitation filters. This stack is combined to produce an enhanced image for presentation and spot counting.

The image evaluation of iterative motion correction reconstruction algorithm PROPELLER T2-weighted imaging compared with MultiVane T2-weighted imaging

NASA Astrophysics Data System (ADS)

Lee, Suk-Jun; Yu, Seung-Man

2017-08-01

The purpose of this study was to evaluate the usefulness and clinical applications of MultiVaneXD which was applying iterative motion correction reconstruction algorithm T2-weighted images compared with MultiVane images taken with a 3T MRI. A total of 20 patients with suspected pathologies of the liver and pancreatic-biliary system based on clinical and laboratory findings underwent upper abdominal MRI, acquired using the MultiVane and MultiVaneXD techniques. Two reviewers analyzed the MultiVane and MultiVaneXD T2-weighted images qualitatively and quantitatively. Each reviewer evaluated vessel conspicuity by observing motion artifacts and the sharpness of the portal vein, hepatic vein, and upper organs. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated by one reviewer for quantitative analysis. The interclass correlation coefficient was evaluated to measure inter-observer reliability. There were significant differences between MultiVane and MultiVaneXD in motion artifact evaluation. Furthermore, MultiVane was given a better score than MultiVaneXD in abdominal organ sharpness and vessel conspicuity, but the difference was insignificant. The reliability coefficient values were over 0.8 in every evaluation. MultiVaneXD (2.12) showed a higher value than did MultiVane (1.98), but the difference was insignificant ( p = 0.135). MultiVaneXD is a motion correction method that is more advanced than MultiVane, and it produced an increased SNR, resulting in a greater ability to detect focal abdominal lesions.

On the creation of high spatial resolution imaging spectroscopy data from multi-temporal low spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yao, Wei; van Aardt, Jan; Messinger, David

2017-05-01

The Hyperspectral Infrared Imager (HyspIRI) mission aims to provide global imaging spectroscopy data to the benefit of especially ecosystem studies. The onboard spectrometer will collect radiance spectra from the visible to short wave infrared (VSWIR) regions (400-2500 nm). The mission calls for fine spectral resolution (10 nm band width) and as such will enable scientists to perform material characterization, species classification, and even sub-pixel mapping. However, the global coverage requirement results in a relatively low spatial resolution (GSD 30m), which restricts applications to objects of similar scales. We therefore have focused on the assessment of sub-pixel vegetation structure from spectroscopy data in past studies. In this study, we investigate the development or reconstruction of higher spatial resolution imaging spectroscopy data via fusion of multi-temporal data sets to address the drawbacks implicit in low spatial resolution imagery. The projected temporal resolution of the HyspIRI VSWIR instrument is 15 days, which implies that we have access to as many as six data sets for an area over the course of a growth season. Previous studies have shown that select vegetation structural parameters, e.g., leaf area index (LAI) and gross ecosystem production (GEP), are relatively constant in summer and winter for temperate forests; we therefore consider the data sets collected in summer to be from a similar, stable forest structure. The first step, prior to fusion, involves registration of the multi-temporal data. A data fusion algorithm then can be applied to the pre-processed data sets. The approach hinges on an algorithm that has been widely applied to fuse RGB images. Ideally, if we have four images of a scene which all meet the following requirements - i) they are captured with the same camera configurations; ii) the pixel size of each image is x; and iii) at least r2 images are aligned on a grid of x/r - then a high-resolution image, with a pixel size of x/r, can be reconstructed from the multi-temporal set. The algorithm was applied to data from NASA's classic Airborne Visible and Infrared Imaging Spectrometer (AVIRIS-C; GSD 18m), collected between 2013-2015 (summer and fall) over our study area (NEON's Southwest Pacific Domain; Fresno, CA) to generate higher spatial resolution imagery (GSD 9m). The reconstructed data set was validated via comparison to NEON's imaging spectrometer (NIS) data (GSD 1m). The results showed that algorithm worked well with the AVIRIS-C data and could be applied to the HyspIRI data.

Effect of inter-tissue inductive coupling on multi-frequency imaging of intracranial hemorrhage by magnetic induction tomography

NASA Astrophysics Data System (ADS)

Xiao, Zhili; Tan, Chao; Dong, Feng

2017-08-01

Magnetic induction tomography (MIT) is a promising technique for continuous monitoring of intracranial hemorrhage due to its contactless nature, low cost and capacity to penetrate the high-resistivity skull. The inter-tissue inductive coupling increases with frequency, which may lead to errors in multi-frequency imaging at high frequency. The effect of inter-tissue inductive coupling was investigated to improve the multi-frequency imaging of hemorrhage. An analytical model of inter-tissue inductive coupling based on the equivalent circuit was established. A set of new multi-frequency decomposition equations separating the phase shift of hemorrhage from other brain tissues was derived by employing the coupling information to improve the multi-frequency imaging of intracranial hemorrhage. The decomposition error and imaging error are both decreased after considering the inter-tissue inductive coupling information. The study reveals that the introduction of inter-tissue inductive coupling can reduce the errors of multi-frequency imaging, promoting the development of intracranial hemorrhage monitoring by multi-frequency MIT.

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

PubMed Central

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

2008-01-01

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

Detecting early stage pressure ulcer on dark skin using multispectral imager

NASA Astrophysics Data System (ADS)

Kong, Linghua; Sprigle, Stephen; Yi, Dingrong; Wang, Chao; Wang, Fengtao; Liu, Fuhan; Wang, Jiwu; Zhao, Futing

2009-10-01

This paper introduces a novel idea, innovative technology in building multi spectral imaging based device. The benefit from them is people can have low cost, handheld and standing alone device which makes acquire multi spectral images real time with just a snapshot. The paper for the first time publishes some images got from such prototyped miniaturized multi spectral imager.

A target field design of open multi-purpose RF coil for musculoskeletal MR imaging at 3T.

PubMed

Gao, Fei; Zhang, Rui; Zhou, Diange; Wang, Xiaoying; Huang, Kefu; Zhang, Jue

2016-10-01

Musculoskeletal MR imaging under multi-angle situations plays an increasingly important role in assessing joint and muscle tissues system. However, there are still limitations due to the closed structures of most conventional RF coils. In this study, a time-harmonic target-field method was employed to design open multi-purpose coil (OMC) for multi-angle musculoskeletal MR imaging. The phantom imaging results suggested that the proposed OMC could achieve homogeneously distributed magnetic field and high signal-to-noise ratio (SNR) of 239.04±0.83 in the region of interest (ROI). The maximum temperature in the heating hazard test was 16°C lower than the standard regulation, which indicated the security of the designed OMC. Furthermore, to demonstrate the effectiveness of the proposed OMC for musculoskeletal MR imaging, especially for multi-angle imaging, a healthy volunteer was examined for MR imaging of elbow, ankle and knee using OMC. The in vivo imaging results showed that the proposed OMC is effective for MR imaging of musculoskeletal tissues at different body parts, with satisfied B1 field homogeneity and SNR. Moreover, the open structure of the OMC could provide a large joint movement region. The proposed open multi-purpose coil is feasible for musculoskeletal MR imaging, and potentially, it is more suitable for the evaluation of musculoskeletal tissues under multi-angle conditions. Copyright © 2016. Published by Elsevier Inc.

Initial clinical testing of a multi-spectral imaging system built on a smartphone platform

NASA Astrophysics Data System (ADS)

Mink, Jonah W.; Wexler, Shraga; Bolton, Frank J.; Hummel, Charles; Kahn, Bruce S.; Levitz, David

2016-03-01

Multi-spectral imaging systems are often expensive and bulky. An innovative multi-spectral imaging system was fitted onto a mobile colposcope, an imaging system built around a smartphone in order to image the uterine cervix from outside the body. The multi-spectral mobile colposcope (MSMC) acquires images at different wavelengths. This paper presents the clinical testing of MSMC imaging (technical validation of the MSMC system is described elsewhere 1 ). Patients who were referred to colposcopy following abnormal screening test (Pap or HPV DNA test) according to the standard of care were enrolled. Multi-spectral image sets of the cervix were acquired, consisting of images from the various wavelengths. Image acquisition took 1-2 sec. Areas suspected for dysplasia under white light imaging were biopsied, according to the standard of care. Biopsied sites were recorded on a clockface map of the cervix. Following the procedure, MSMC data was processed from the sites of biopsied sites. To date, the initial histopathological results are still outstanding. Qualitatively, structures in the cervical images were sharper at lower wavelengths than higher wavelengths. Patients tolerated imaging well. The result suggests MSMC holds promise for cervical imaging.

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

PubMed Central

Calhoun, Vince D; Sui, Jing

2016-01-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. PMID:27347565

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

PubMed

Calhoun, Vince D; Sui, Jing

2016-05-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

Real-time blind image deconvolution based on coordinated framework of FPGA and DSP

NASA Astrophysics Data System (ADS)

Wang, Ze; Li, Hang; Zhou, Hua; Liu, Hongjun

2015-10-01

Image restoration takes a crucial place in several important application domains. With the increasing of computation requirement as the algorithms become much more complexity, there has been a significant rise in the need for accelerating implementation. In this paper, we focus on an efficient real-time image processing system for blind iterative deconvolution method by means of the Richardson-Lucy (R-L) algorithm. We study the characteristics of algorithm, and an image restoration processing system based on the coordinated framework of FPGA and DSP (CoFD) is presented. Single precision floating-point processing units with small-scale cascade and special FFT/IFFT processing modules are adopted to guarantee the accuracy of the processing. Finally, Comparing experiments are done. The system could process a blurred image of 128×128 pixels within 32 milliseconds, and is up to three or four times faster than the traditional multi-DSPs systems.

Development of multi-mission satellite data systems at the German Remote Sensing Data Centre

NASA Astrophysics Data System (ADS)

Lotz-Iwen, H. J.; Markwitz, W.; Schreier, G.

1998-11-01

This paper focuses on conceptual aspects of the access to multi-mission remote sensing data by online catalogue and information systems. The system ISIS of the German Remote Sensing Data Centre is described as an example of a user interface to earth observation data. ISIS has been designed to support international scientific research as well as operational applications by offering online access to the database via public networks. It provides catalogue retrieval, visualisation and transfer of image data, and is integrated in international activities dedicated to catalogue and archive interoperability. Finally, an outlook is given on international projects dealing with access to remote sensing data in distributed archives.

Development of a fast multi-line x-ray CT detector for NDT

NASA Astrophysics Data System (ADS)

Hofmann, T.; Nachtrab, F.; Schlechter, T.; Neubauer, H.; Mühlbauer, J.; Schröpfer, S.; Ernst, J.; Firsching, M.; Schweiger, T.; Oberst, M.; Meyer, A.; Uhlmann, N.

2015-04-01

Typical X-ray detectors for non-destructive testing (NDT) are line detectors or area detectors, like e.g. flat panel detectors. Multi-line detectors are currently only available in medical Computed Tomography (CT) scanners. Compared to flat panel detectors, line and multi-line detectors can achieve much higher frame rates. This allows time-resolved 3D CT scans of an object under investigation. Also, an improved image quality can be achieved due to reduced scattered radiation from object and detector themselves. Another benefit of line and multi-line detectors is that very wide detectors can be assembled easily, while flat panel detectors are usually limited to an imaging field with a size of approx. 40 × 40 cm2 at maximum. The big disadvantage of line detectors is the limited number of object slices that can be scanned simultaneously. This leads to long scan times for large objects. Volume scans with a multi-line detector are much faster, but with almost similar image quality. Due to the promising properties of multi-line detectors their application outside of medical CT would also be very interesting for NDT. However, medical CT multi-line detectors are optimized for the scanning of human bodies. Many non-medical applications require higher spatial resolutions and/or higher X-ray energies. For those non-medical applications we are developing a fast multi-line X-ray detector.In the scope of this work, we present the current state of the development of the novel detector, which includes several outstanding properties like an adjustable curved design for variable focus-detector-distances, conserving nearly uniform perpendicular irradiation over the entire detector width. Basis of the detector is a specifically designed, radiation hard CMOS imaging sensor with a pixel pitch of 200 μ m. Each pixel has an automatic in-pixel gain adjustment, which allows for both: a very high sensitivity and a wide dynamic range. The final detector is planned to have 256 lines of pixels. By using a modular assembly of the detector, the width can be chosen as multiples of 512 pixels. With a frame rate of up to 300 frames/s (full resolution) or 1200 frame/s (analog binning to 400 μ m pixel pitch) time-resolved 3D CT applications become possible. Two versions of the detector are in development, one with a high resolution scintillator and one with a thick, structured and very efficient scintillator (pitch 400 μ m). This way the detector can even work with X-ray energies up to 450 kVp.

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.

Five Micron High Resolution MALDI Mass Spectrometry Imaging with Simple, Interchangeable, Multi-Resolution Optical System

DOE PAGES

Feenstra, Adam D.; Dueñas, Maria Emilia; Lee, Young Jin

2017-01-03

High-spatial resolution mass spectrometry imaging (MSI) is crucial for the mapping of chemical distributions at the cellular and subcellular level. Here in this work, we improved our previous laser optical system for matrix-assisted laser desorption ionization (MALDI)-MSI, from ~9 μm practical laser spot size to a practical laser spot size of ~4 μm, thereby allowing for 5 μm resolution imaging without oversampling. This is accomplished through a combination of spatial filtering, beam expansion, and reduction of the final focal length. Most importantly, the new laser optics system allows for simple modification of the spot size solely through the interchanging ofmore » the beam expander component. Using 10×, 5×, and no beam expander, we could routinely change between ~4, ~7, and ~45 μm laser spot size, in less than 5 min. We applied this multi-resolution MALDI-MSI system to a single maize root tissue section with three different spatial resolutions of 5, 10, and 50 μm and compared the differences in imaging quality and signal sensitivity. Lastly, we also demonstrated the difference in depth of focus between the optical systems with 10× and 5× beam expanders.« less

Five Micron High Resolution MALDI Mass Spectrometry Imaging with Simple, Interchangeable, Multi-Resolution Optical System

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

Feenstra, Adam D.; Dueñas, Maria Emilia; Lee, Young Jin

High-spatial resolution mass spectrometry imaging (MSI) is crucial for the mapping of chemical distributions at the cellular and subcellular level. Here in this work, we improved our previous laser optical system for matrix-assisted laser desorption ionization (MALDI)-MSI, from ~9 μm practical laser spot size to a practical laser spot size of ~4 μm, thereby allowing for 5 μm resolution imaging without oversampling. This is accomplished through a combination of spatial filtering, beam expansion, and reduction of the final focal length. Most importantly, the new laser optics system allows for simple modification of the spot size solely through the interchanging ofmore » the beam expander component. Using 10×, 5×, and no beam expander, we could routinely change between ~4, ~7, and ~45 μm laser spot size, in less than 5 min. We applied this multi-resolution MALDI-MSI system to a single maize root tissue section with three different spatial resolutions of 5, 10, and 50 μm and compared the differences in imaging quality and signal sensitivity. Lastly, we also demonstrated the difference in depth of focus between the optical systems with 10× and 5× beam expanders.« less

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.

Preliminary Evaluation of a Commercial 360 Multi-Camera Rig for Photogrammetric Purposes

NASA Astrophysics Data System (ADS)

Teppati Losè, L.; Chiabrando, F.; Spanò, A.

2018-05-01

The research presented in this paper is focused on a preliminary evaluation of a 360 multi-camera rig: the possibilities to use the images acquired by the system in a photogrammetric workflow and for the creation of spherical images are investigated and different tests and analyses are reported. Particular attention is dedicated to different operative approaches for the estimation of the interior orientation parameters of the cameras, both from an operative and theoretical point of view. The consistency of the six cameras that compose the 360 system was in depth analysed adopting a self-calibration approach in a commercial photogrammetric software solution. A 3D calibration field was projected and created, and several topographic measurements were performed in order to have a set of control points to enhance and control the photogrammetric process. The influence of the interior parameters of the six cameras were analyse both in the different phases of the photogrammetric workflow (reprojection errors on the single tie point, dense cloud generation, geometrical description of the surveyed object, etc.), both in the stitching of the different images into a single spherical panorama (some consideration on the influence of the camera parameters on the overall quality of the spherical image are reported also in these section).

High-resolution multi-channel seismic images of the Queen Charlotte Fault system offshore southeastern Alaska

NASA Astrophysics Data System (ADS)

Miller, N. C.; Brothers, D. S.; Kluesner, J.; Balster-Gee, A.; Ten Brink, U. S.; Andrews, B. D.; Haeussler, P. J.; Watt, J. T.; Dartnell, P.; East, A. E.

2016-12-01

We present high-resolution multi-channel seismic (MCS) images of fault structure and sedimentary stratigraphy along the southeastern Alaska margin, where the northern Queen Charlotte Fault (QCF) cuts the shelf-edge and slope. The QCF is a dominantly strike slip system that forms the boundary between the Pacific (PA) and North American (NA) plates offshore western Canada and southeastern Alaska. The data were collected using a 64 channel, 200 m digital streamer and a 0.75-3 kJ sparker source aboard the R/V Norseman in August 2016. The survey was designed to cross a seafloor fault trace recently imaged by multibeam sonar (see adjacent poster by Brothers et al.) and to extend the subsurface information landward and seaward from the fault. Analysis of these MCS and multibeam data focus on addressing key questions that have significant implications for the kinematic and geodynamic history of the fault, including: Is the imaged surface fault in multibeam sonar the only recently-active fault trace? What is the shallow fault zone width and structure, is the internal structure of the recently-discovered pull-apart basin a dynamically developing structure? How does sediment thickness vary along the margin and how does this variation affect the fault expression? Can previous glacial sequences be identified in the stratigraphy?

Multi-technique hybrid imaging in PET/CT and PET/MR: what does the future hold?

PubMed

de Galiza Barbosa, F; Delso, G; Ter Voert, E E G W; Huellner, M W; Herrmann, K; Veit-Haibach, P

2016-07-01

Integrated positron-emission tomography and computed tomography (PET/CT) is one of the most important imaging techniques to have emerged in oncological practice in the last decade. Hybrid imaging, in general, remains a rapidly growing field, not only in developing countries, but also in western industrialised healthcare systems. A great deal of technological development and research is focused on improving hybrid imaging technology further and introducing new techniques, e.g., integrated PET and magnetic resonance imaging (PET/MRI). Additionally, there are several new PET tracers on the horizon, which have the potential to broaden clinical applications in hybrid imaging for diagnosis as well as therapy. This article aims to highlight some of the major technical and clinical advances that are currently taking place in PET/CT and PET/MRI that will potentially maintain the position of hybrid techniques at the forefront of medical imaging technologies. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

HIGH SPEED KERR CELL FRAMING CAMERA

DOEpatents

Goss, W.C.; Gilley, L.F.

1964-01-01

The present invention relates to a high speed camera utilizing a Kerr cell shutter and a novel optical delay system having no moving parts. The camera can selectively photograph at least 6 frames within 9 x 10/sup -8/ seconds during any such time interval of an occurring event. The invention utilizes particularly an optical system which views and transmits 6 images of an event to a multi-channeled optical delay relay system. The delay relay system has optical paths of successively increased length in whole multiples of the first channel optical path length, into which optical paths the 6 images are transmitted. The successively delayed images are accepted from the exit of the delay relay system by an optical image focusing means, which in turn directs the images into a Kerr cell shutter disposed to intercept the image paths. A camera is disposed to simultaneously view and record the 6 images during a single exposure of the Kerr cell shutter. (AEC)

Multifunctional Inorganic Nanoparticles: Recent Progress in Thermal Therapy and Imaging

PubMed Central

Cherukula, Kondareddy; Manickavasagam Lekshmi, Kamali; Uthaman, Saji; Cho, Kihyun; Cho, Chong-Su; Park, In-Kyu

2016-01-01

Nanotechnology has enabled the development of many alternative anti-cancer approaches, such as thermal therapies, which cause minimal damage to healthy cells. Current challenges in cancer treatment are the identification of the diseased area and its efficient treatment without generating many side effects. Image-guided therapies can be a useful tool to diagnose and treat the diseased tissue and they offer therapy and imaging using a single nanostructure. The present review mainly focuses on recent advances in the field of thermal therapy and imaging integrated with multifunctional inorganic nanoparticles. The main heating sources for heat-induced therapies are the surface plasmon resonance (SPR) in the near infrared region and alternating magnetic fields (AMFs). The different families of inorganic nanoparticles employed for SPR- and AMF-based thermal therapies and imaging are described. Furthermore, inorganic nanomaterials developed for multimodal therapies with different and multi-imaging modalities are presented in detail. Finally, relevant clinical perspectives and the future scope of inorganic nanoparticles in image-guided therapies are discussed. PMID:28335204

[Research Progress of Multi-Model Medical Image Fusion at Feature Level].

PubMed

Zhang, Junjie; Zhou, Tao; Lu, Huiling; Wang, Huiqun

2016-04-01

Medical image fusion realizes advantage integration of functional images and anatomical images.This article discusses the research progress of multi-model medical image fusion at feature level.We firstly describe the principle of medical image fusion at feature level.Then we analyze and summarize fuzzy sets,rough sets,D-S evidence theory,artificial neural network,principal component analysis and other fusion methods’ applications in medical image fusion and get summery.Lastly,we in this article indicate present problems and the research direction of multi-model medical images in the future.

Inner-volume echo volumar imaging (IVEVI) for robust fetal brain imaging.

PubMed

Nunes, Rita G; Ferrazzi, Giulio; Price, Anthony N; Hutter, Jana; Gaspar, Andreia S; Rutherford, Mary A; Hajnal, Joseph V

2018-07-01

Fetal functional MRI studies using conventional 2-dimensional single-shot echo-planar imaging sequences may require discarding a large data fraction as a result of fetal and maternal motion. Increasing the temporal resolution using echo volumar imaging (EVI) could provide an effective alternative strategy. Echo volumar imaging was combined with inner volume (IV) imaging (IVEVI) to locally excite the fetal brain and acquire full 3-dimensional images, fast enough to freeze most fetal head motion. IVEVI was implemented by modifying a standard multi-echo echo-planar imaging sequence. A spin echo with orthogonal excitation and refocusing ensured localized excitation. To introduce T2* weighting and to save time, the k-space center was shifted relative to the spin echo. Both single and multi-shot variants were tested. Acoustic noise was controlled by adjusting the amplitude and switching frequency of the readout gradient. Image-based shimming was used to minimize B 0 inhomogeneities within the fetal brain. The sequence was first validated in an adult. Eight fetuses were scanned using single-shot IVEVI at a 3.5 × 3.5 × 5.0 mm 3 resolution with a readout duration of 383 ms. Multishot IVEVI showed reduced geometric distortions along the second phase-encode direction. Fetal EVI remains challenging. Although effective echo times comparable to the T2* values of fetal cortical gray matter at 3 T could be achieved, controlling acoustic noise required longer readouts, leading to substantial distortions in single-shot images. Although multishot variants enabled us to reduce susceptibility-induced geometric distortions, sensitivity to motion was increased. Future studies should therefore focus on improvements to multishot variants. Magn Reson Med 80:279-285, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Histotripsy Thrombolysis on Retracted Clots.

PubMed

Zhang, Xi; Owens, Gabe E; Cain, Charles A; Gurm, Hitinder S; Macoskey, Jonathan; Xu, Zhen

2016-08-01

Retracted blood clots have been previously recognized to be more resistant to drug-based thrombolysis methods, even with ultrasound and microbubble enhancements. Microtripsy, a new histotripsy approach, has been investigated as a non-invasive, drug-free and image-guided method that uses ultrasound to break up clots with improved treatment accuracy and a lower risk of vessel damage compared with the traditional histotripsy thrombolysis approach. Unlike drug-mediated thrombolysis, which is dependent on the permeation of the thrombolytic agents into the clot, microtripsy controls acoustic cavitation to fractionate clots. We hypothesize that microtripsy thrombolysis is effective on retracted clots and that the treatment efficacy can be enhanced using strategies incorporating electronic focal steering. To test our hypothesis, retracted clots were prepared in vitro and the mechanical properties were quantitatively characterized. Microtripsy thrombolysis was applied on the retracted clots in an in vitro flow model using three different strategies: single-focus, electronically-steered multi-focus and dual-pass multi-focus. Results show that microtripsy was used to successfully generate a flow channel through the retracted clot and the flow was restored. The multi-focus and the dual-pass treatments incorporating the electronic focal steering significantly increased the recanalized flow channel size compared to the single-focus treatments. The dual-pass treatments achieved a restored flow rate up to 324 mL/min without cavitation contacting the vessel wall. The clot debris particles generated from microtripsy thrombolysis remained within the safe range. The results of this study show the potential of microtripsy thrombolysis for retracted clot recanalization with the enhancement of electronic focal steering. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

The evaluation of single-view and multi-view fusion 3D echocardiography using image-driven segmentation and tracking.

PubMed

Rajpoot, Kashif; Grau, Vicente; Noble, J Alison; Becher, Harald; Szmigielski, Cezary

2011-08-01

Real-time 3D echocardiography (RT3DE) promises a more objective and complete cardiac functional analysis by dynamic 3D image acquisition. Despite several efforts towards automation of left ventricle (LV) segmentation and tracking, these remain challenging research problems due to the poor-quality nature of acquired images usually containing missing anatomical information, speckle noise, and limited field-of-view (FOV). Recently, multi-view fusion 3D echocardiography has been introduced as acquiring multiple conventional single-view RT3DE images with small probe movements and fusing them together after alignment. This concept of multi-view fusion helps to improve image quality and anatomical information and extends the FOV. We now take this work further by comparing single-view and multi-view fused images in a systematic study. In order to better illustrate the differences, this work evaluates image quality and information content of single-view and multi-view fused images using image-driven LV endocardial segmentation and tracking. The image-driven methods were utilized to fully exploit image quality and anatomical information present in the image, thus purposely not including any high-level constraints like prior shape or motion knowledge in the analysis approaches. Experiments show that multi-view fused images are better suited for LV segmentation and tracking, while relatively more failures and errors were observed on single-view images. Copyright © 2011 Elsevier B.V. All rights reserved.

Low-Income, African American and American Indian Children's Viewpoints on Body Image Assessment Tools and Body Satisfaction: A Mixed Methods Study.

PubMed

Heidelberger, Lindsay; Smith, Chery

2018-03-03

Objectives Pediatric obesity is complicated by many factors including psychological issues, such as body dissatisfaction. Body image assessment tools are used with children to measure their acceptance of their body shape or image. Limited research has been conducted with African American and American Indian children to understand their opinions on assessment tools created. This study investigated: (a) children's perception about body image and (b) differences between two body image instruments among low-income, multi-ethnic children. Methods This study uses mixed methodology including focus groups (qualitative) and body image assessment instruments (quantitative). Fifty-one children participated (25 girls, 26 boys); 53% of children identified as African American and 47% as American Indian. The average age was 10.4 years. Open coding methods were used by identify themes from focus group data. SPSS was used for quantitative analysis. Results Children preferred the Figure Rating Scale (FRS/silhouette) instrument over the Children's Body Image Scale (CBIS/photo) because their body parts and facial features were more detailed. Children formed their body image perception with influence from their parents and the media. Children verbalized that they have experienced negative consequences related to poor body image including disordered eating habits, depression, and bullying. Healthy weight children are also aware of weight-related bullying that obese and overweight children face. Conclusions for Practice Children prefer that the images on a body image assessment tool have detailed facial features and are clothed. Further research into body image assessment tools for use with African American and American Indian children is needed.

Autofocusing in digital holography using deep learning

NASA Astrophysics Data System (ADS)

Ren, Zhenbo; Xu, Zhimin; Lam, Edmund Y.

2018-02-01

In digital holography, it is critical to know the distance in order to reconstruct the multi-sectional object. This autofocusing is traditionally solved by reconstructing a stack of in-focus and out-of-focus images and using some focus metric, such as entropy or variance, to calculate the sharpness of each reconstructed image. Then the distance corresponding to the sharpest image is determined as the focal position. This method is effective but computationally demanding and time-consuming. To get an accurate estimation, one has to reconstruct many images. Sometimes after a coarse search, a refinement is needed. To overcome this problem in autofocusing, we propose to use deep learning, i.e., a convolutional neural network (CNN), to solve this problem. Autofocusing is viewed as a classification problem, in which the true distance is transferred as a label. To estimate the distance is equated to labeling a hologram correctly. To train such an algorithm, totally 1000 holograms are captured under the same environment, i.e., exposure time, incident angle, object, except the distance. There are 5 labels corresponding to 5 distances. These data are randomly split into three datasets to train, validate and test a CNN network. Experimental results show that the trained network is capable of predicting the distance without reconstructing or knowing any physical parameters about the setup. The prediction time using this method is far less than traditional autofocusing methods.

High-speed bioimaging with frequency-division-multiplexed fluorescence confocal microscopy

NASA Astrophysics Data System (ADS)

Mikami, Hideharu; Harmon, Jeffrey; Ozeki, Yasuyuki; Goda, Keisuke

2017-04-01

We present methods of fluorescence confocal microscopy that enable unprecedentedly high frame rate of > 10,000 fps. The methods are based on a frequency-division multiplexing technique, which was originally developed in the field of communication engineering. Specifically, we achieved a broad bandwidth ( 400 MHz) of detection signals using a dual- AOD method and overcame limitations in frame rate, due to a scanning device, by using a multi-line focusing method, resulting in a significant increase in frame rate. The methods have potential biomedical applications such as observation of sub-millisecond dynamics in biological tissues, in-vivo three-dimensional imaging, and fluorescence imaging flow cytometry.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-aperture microoptical system for close-up imaging

NASA Astrophysics Data System (ADS)

Berlich, René; Brückner, Andreas; Leitel, Robert; Oberdörster, Alexander; Wippermann, Frank; Bräuer, Andreas

2014-09-01

Modern applications in biomedical imaging, machine vision and security engineering require close-up optical systems with high resolution. Combined with the need for miniaturization and fast image acquisition of extended object fields, the design and fabrication of respective devices is extremely challenging. Standard commercial imaging solutions rely on bulky setups or depend on scanning techniques in order to meet the stringent requirements. Recently, our group has proposed a novel, multi-aperture approach based on parallel image transfer in order to overcome these constraints. It exploits state of the art microoptical manufacturing techniques on wafer level in order to create a compact, cost-effective system with a large field of view. However, initial prototypes have so far been subject to various limitations regarding their manufacturing, reliability and applicability. In this work, we demonstrate the optical design and fabrication of an advanced system, which overcomes these restrictions. In particular, a revised optical design facilitates a more efficient and economical fabrication process and inherently improves system reliability. An additional customized front side illumination module provides homogeneous white light illumination over the entire field of view while maintaining a high degree of compactness. Moreover, the complete imaging assembly is mounted on a positioning system. In combination with an extended working range, this allows for adjustment of the system's focus location. The final optical design is capable of capturing an object field of 36x24 mm2 with a resolution of 150 cycles/mm. Finally, we present experimental results of the respective prototype that demonstrate its enhanced capabilities.

Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging.

PubMed

Falahati, Farshad; Westman, Eric; Simmons, Andrew

2014-01-01

Machine learning algorithms and multivariate data analysis methods have been widely utilized in the field of Alzheimer's disease (AD) research in recent years. Advances in medical imaging and medical image analysis have provided a means to generate and extract valuable neuroimaging information. Automatic classification techniques provide tools to analyze this information and observe inherent disease-related patterns in the data. In particular, these classifiers have been used to discriminate AD patients from healthy control subjects and to predict conversion from mild cognitive impairment to AD. In this paper, recent studies are reviewed that have used machine learning and multivariate analysis in the field of AD research. The main focus is on studies that used structural magnetic resonance imaging (MRI), but studies that included positron emission tomography and cerebrospinal fluid biomarkers in addition to MRI are also considered. A wide variety of materials and methods has been employed in different studies, resulting in a range of different outcomes. Influential factors such as classifiers, feature extraction algorithms, feature selection methods, validation approaches, and cohort properties are reviewed, as well as key MRI-based and multi-modal based studies. Current and future trends are discussed.

The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective.

PubMed

Pirpinia, Kleopatra; Bosman, Peter A N; Loo, Claudette E; Winter-Warnars, Gonneke; Janssen, Natasja N Y; Scholten, Astrid N; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2017-06-23

Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance information reduced to 7.3 mm with guidance information, but also providing a Pareto front that exhibits an intuitively sensible interplay between weights, objectives, and registration outcome, allowing outcome selection.

SW-MW infrared spectrometer for lunar mission

NASA Astrophysics Data System (ADS)

Banerjee, Arup; Biswas, Amiya; Joshi, Shaunak; Kumar, Ankush; Rehman, Sami; Sharma, Satish; Somani, Sandip; Bhati, Sunil; Karelia, Jitendra; Saxena, Anish; Chowdhury, Arup R.

2016-04-01

SW-MW Imaging Infrared Spectrometer, the Hyperspectral optical imaging instrument is envisaged to map geomorphology and mineralogy of lunar surface. The instrument is designed to image the electro-magnetic energy emanating from moon's surface with high spectral and spatial resolution for the mission duration from an altitude of 100 km. It is designed to cover 0.8 to 5 μm in 250 spectral bands with GSD 80m and swath 20km. Primarily, there are three basic optical segments in the spectrometer. They are fore optics, dispersing element and focusing elements. The payload is designed around a custom developed multi-blaze convex grating optimized for system throughput. The considerations for optimization are lunar radiation, instrument background, optical throughput, and detector sensitivity. HgCdTe (cooled using a rotary stirling cooler) based detector array (500x256 elements, 30μm) is being custom developed for the spectrometer. Stray light background flux is minimized using a multi-band filter cooled to cryogenic temperature. Mechanical system realization is being performed considering requirements such as structural, opto-mechanical, thermal, and alignment. The entire EOM is planned to be maintained at 240K to reduce and control instrument background. Al based mirror, grating, and EOM housing is being developed to maintain structural requirements along with opto- mechanical and thermal. Multi-tier radiative isolation and multi-stage radiative cooling approach is selected for maintaining the EOM temperature. EOM along with precision electronics packages are planned to be placed on the outer and inner side of Anti-sun side (ASS) deck. Power and Cooler drive electronics packages are planned to be placed on bottom side of ASS panel. Cooler drive electronics is being custom developed to maintain the detector temperature within 100mK during the imaging phase. Low noise detector electronics development is critical for maintaining the NETD requirements at different target temperatures. Subsequent segments of the paper bring out system design aspects and trade-off analyses.

The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective

NASA Astrophysics Data System (ADS)

Pirpinia, Kleopatra; Bosman, Peter A. N.; E Loo, Claudette; Winter-Warnars, Gonneke; Y Janssen, Natasja N.; Scholten, Astrid N.; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2017-07-01

Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance information reduced to 7.3 mm with guidance information, but also providing a Pareto front that exhibits an intuitively sensible interplay between weights, objectives, and registration outcome, allowing outcome selection.

Methodology for quantitative rapid multi-tracer PET tumor characterizations.

PubMed

Kadrmas, Dan J; Hoffman, John M

2013-10-04

Positron emission tomography (PET) can image a wide variety of functional and physiological parameters in vivo using different radiotracers. As more is learned about the molecular basis for disease and treatment, the potential value of molecular imaging for characterizing and monitoring disease status has increased. Characterizing multiple aspects of tumor physiology by imaging multiple PET tracers in a single patient provides additional complementary information, and there is a significant body of literature supporting the potential value of multi-tracer PET imaging in oncology. However, imaging multiple PET tracers in a single patient presents a number of challenges. A number of techniques are under development for rapidly imaging multiple PET tracers in a single scan, where signal-recovery processing algorithms are employed to recover various imaging endpoints for each tracer. Dynamic imaging is generally used with tracer injections staggered in time, and kinetic constraints are utilized to estimate each tracers' contribution to the multi-tracer imaging signal. This article summarizes past and ongoing work in multi-tracer PET tumor imaging, and then organizes and describes the main algorithmic approaches for achieving multi-tracer PET signal-recovery. While significant advances have been made, the complexity of the approach necessitates protocol design, optimization, and testing for each particular tracer combination and application. Rapid multi-tracer PET techniques have great potential for both research and clinical cancer imaging applications, and continued research in this area is warranted.

Methodology for Quantitative Rapid Multi-Tracer PET Tumor Characterizations

PubMed Central

Kadrmas, Dan J.; Hoffman, John M.

2013-01-01

Positron emission tomography (PET) can image a wide variety of functional and physiological parameters in vivo using different radiotracers. As more is learned about the molecular basis for disease and treatment, the potential value of molecular imaging for characterizing and monitoring disease status has increased. Characterizing multiple aspects of tumor physiology by imaging multiple PET tracers in a single patient provides additional complementary information, and there is a significant body of literature supporting the potential value of multi-tracer PET imaging in oncology. However, imaging multiple PET tracers in a single patient presents a number of challenges. A number of techniques are under development for rapidly imaging multiple PET tracers in a single scan, where signal-recovery processing algorithms are employed to recover various imaging endpoints for each tracer. Dynamic imaging is generally used with tracer injections staggered in time, and kinetic constraints are utilized to estimate each tracers' contribution to the multi-tracer imaging signal. This article summarizes past and ongoing work in multi-tracer PET tumor imaging, and then organizes and describes the main algorithmic approaches for achieving multi-tracer PET signal-recovery. While significant advances have been made, the complexity of the approach necessitates protocol design, optimization, and testing for each particular tracer combination and application. Rapid multi-tracer PET techniques have great potential for both research and clinical cancer imaging applications, and continued research in this area is warranted. PMID:24312149

A Real Time System for Multi-Sensor Image Analysis through Pyramidal Segmentation

DTIC Science & Technology

1992-01-30

A Real Time Syte for M~ulti- sensor Image Analysis S. E I0 through Pyramidal Segmentation/ / c •) L. Rudin, S. Osher, G. Koepfler, J.9. Morel 7. ytu...experiments with reconnaissance photography, multi- sensor satellite imagery, medical CT and MRI multi-band data have shown a great practi- cal potential...C ,SF _/ -- / WSM iS-I-0-d41-40450 $tltwt, kw" I (nor.- . Z-97- A real-time system for multi- sensor image analysis through pyramidal segmentation

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

Multi-scale Observation of Biological Interactions of Nanocarriers: from Nano to Macro

PubMed Central

Jin, Su-Eon; Bae, Jin Woo; Hong, Seungpyo

2010-01-01

Microscopic observations have played a key role in recent advancements in nanotechnology-based biomedical sciences. In particular, multi-scale observation is necessary to fully understand the nano-bio interfaces where a large amount of unprecedented phenomena have been reported. This review describes how to address the physicochemical and biological interactions of nanocarriers within the biological environments using microscopic tools. The imaging techniques are categorized based on the size scale of detection. For observation of the nano-scale biological interactions of nanocarriers, we discuss atomic force microscopy (AFM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). For the micro to macro-scale (in vitro and in vivo) observation, we focus on confocal laser scanning microscopy (CLSM) as well as in vivo imaging systems such as magnetic resonance imaging (MRI), superconducting quantum interference devices (SQUIDs), and IVIS®. Additionally, recently developed combined techniques such as AFM-CLSM, correlative Light and Electron Microscopy (CLEM), and SEM-spectroscopy are also discussed. In this review, we describe how each technique helps elucidate certain physicochemical and biological activities of nanocarriers such as dendrimers, polymers, liposomes, and polymeric/inorganic nanoparticles, thus providing a toolbox for bioengineers, pharmaceutical scientists, biologists, and research clinicians. PMID:20232368

Seafloor Topographic Analysis in Staged Ocean Resource Exploration

NASA Astrophysics Data System (ADS)

Ikeda, M.; Okawa, M.; Osawa, K.; Kadoshima, K.; Asakawa, E.; Sumi, T.

2017-12-01

J-MARES (Research and Development Partnership for Next Generation Technology of Marine Resources Survey, JAPAN) has been designing a low-expense and high-efficiency exploration system for seafloor hydrothermal massive sulfide deposits in "Cross-ministerial Strategic Innovation Promotion Program (SIP)" granted by the Cabinet Office, Government of Japan since 2014. We designed a method to focus mineral deposit prospective area in multi-stages (the regional survey, semi-detail survey and detail survey) by extracted topographic features of some well-known seafloor massive sulfide deposits from seafloor topographic analysis using seafloor topographic data acquired by the bathymetric survey. We applied this procedure to an area of interest more than 100km x 100km over Okinawa Trough, including some known seafloor massive sulfide deposits. In Addition, we tried to create a three-dimensional model of seafloor topography by SfM (Structure from Motion) technique using multiple image data of Chimney distributed around well-known seafloor massive sulfide deposit taken with Hi-Vision camera mounted on ROV in detail survey such as geophysical exploration. Topographic features of Chimney was extracted by measuring created three-dimensional model. As the result, it was possible to estimate shape of seafloor sulfide such as Chimney to be mined by three-dimensional model created from image data taken with camera mounted on ROV. In this presentation, we will discuss about focusing mineral deposit prospective area in multi-stages by seafloor topographic analysis using seafloor topographic data in exploration system for seafloor massive sulfide deposit and also discuss about three-dimensional model of seafloor topography created from seafloor image data taken with ROV.

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

PubMed

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

2017-02-01

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

Gamma-Ray Focusing Optics for Small Animal Imaging

NASA Technical Reports Server (NTRS)

Pivovaroff, M. J.; Barber, W. C.; Craig, W. W.; Hasegawa, B. H.; Ramsey, B. D.; Taylor, C.

2004-01-01

There is a well-established need for high-resolution radionuclide imaging techniques that provide non-invasive measurement of physiological function in small animals. We, therefore, have begun developing a small animal radionuclide imaging system using grazing incidence mirrors to focus low-energy gamma-rays emitted by I-125, and other radionuclides. Our initial prototype optic, fabricated from thermally-formed glass, demonstrated a resolution of 1500 microns, consistent with the performance predicted by detailed simulations. More recently, we have begun constructing mirrors using a replication technique that reduces low spatial frequency errors in the mirror surface, greatly improving the resolution. Each technique offers particular advantages: e.g., multilayer coatings are easily deposited on glass, while superior resolution is possible with replicated optics. Scaling the results from our prototype optics, which only have a few nested shells, to system where the lens has a full complement of several tens of nested shells, a sensitivity of approx. 1 cps/micro Ci is possible, with the exact number dependent on system magnification and radionuclide species. (Higher levels of efficiency can be obtained with multi-optic imaging systems.) The gamma-ray lens will achieve a resolution as good as 100 microns, independent of the final sensitivity. The combination of high spatial resolution and modest sensitivity will enable in vivo single photon emission imaging studies in small animals.

Design of small confocal endo-microscopic probe working under multiwavelength environment

NASA Astrophysics Data System (ADS)

Kim, Young-Duk; Ahn, MyoungKi; Gweon, Dae-Gab

2010-02-01

Recently, optical imaging system is widely used in medical purpose. By using optical imaging system specific diseases can be easily diagnosed at early stage because optical imaging system has high resolution performance and various imaging method. These methods are used to get high resolution image of human body and can be used to verify whether the cell is infected by virus. Confocal microscope is one of the famous imaging systems which is used for in-vivo imaging. Because most of diseases are accompanied with cellular level changes, doctors can diagnosis at early stage by observing the cellular image of human organ. Current research is focused in the development of endo-microscope that has great advantage in accessibility to human body. In this research, I designed small probe that is connected to confocal microscope through optical fiber bundle and work as endo-microscope. And this small probe is mainly designed to correct chromatic aberration to use various laser sources for both fluorescence type and reflection type confocal images. By using two kinds of laser sources at the same time we demonstrated multi-modality confocal endo-microscope.

Development of multi-dimensional body image scale for malaysian female adolescents

PubMed Central

Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs. PMID:20126371

Development of multi-dimensional body image scale for malaysian female adolescents.

PubMed

Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

High resolution multiplexed functional imaging in live embryos (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xu, Dongli; Zhou, Weibin; Peng, Leilei

2017-02-01

Fourier multiplexed fluorescence lifetime imaging (FmFLIM) scanning laser optical tomography (FmFLIM-SLOT) combines FmFLIM and Scanning laser optical tomography (SLOT) to perform multiplexed 3D FLIM imaging of live embryos. The system had demonstrate multiplexed functional imaging of zebrafish embryos genetically express Foster Resonant Energy Transfer (FRET) sensors. However, previous system has a 20 micron resolution because the focused Gaussian beam diverges quickly from the focused plane, makes it difficult to achieve high resolution imaging over a long projection depth. Here, we present a high-resolution FmFLIM-SLOT system with achromatic Bessel beam, which achieves 3 micron resolution in 3D deep tissue imaging. In Bessel-FmFLIM-SLOT, multiple laser excitation lines are firstly intensity modulated by a Michelson interferometer with a spinning polygon mirror optical delay line, which enables Fourier multiplexed multi-channel lifetime measurements. Then, a spatial light modulator and a prism are used to transform the modulated Gaussian laser beam to an achromatic Bessel beam. The achromatic Bessel beam scans across the whole specimen with equal angular intervals as sample rotated. After tomography reconstruction and the frequency domain lifetime analysis method, both the 3D intensity and lifetime image of multiple excitation-emission can be obtained. Using Bessel-FmFLIM-SLOT system, we performed cellular-resolution FLIM tomography imaging of live zebrafish embryo. Genetically expressed FRET sensors in these embryo will allow non-invasive observation of multiple biochemical processes in vivo.

Multi-energy spectral CT: adding value in emergency body imaging.

PubMed

Punjabi, Gopal V

2018-04-01

Most vendors offer scanners capable of dual- or multi-energy computed tomography (CT) imaging. Advantages of multi-energy CT scanning include superior tissue characterization, detection of subtle iodine uptake differences, and opportunities to reduce contrast dose. However, utilization of this technology in the emergency department (ED) remains low. The purpose of this pictorial essay is to illustrate the value of multi-energy CT scanning in emergency body imaging.

A multi-plate velocity-map imaging design for high-resolution photoelectron spectroscopy

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

Kregel, Steven J.; Thurston, Glen K.; Zhou, Jia

A velocity map imaging (VMI) setup consisting of multiple electrodes with three adjustable voltage parameters, designed for slow electron velocity map imaging applications, is presented. The motivations for this design are discussed in terms of parameters that influence the VMI resolution and functionality. Particularly, this VMI has two tunable potentials used to adjust for optimal focus, yielding good VMI focus across a relatively large energy range. It also allows for larger interaction volumes without significant sacrifice to the resolution via a smaller electric gradient at the interaction region. All the electrodes in this VMI have the same dimensions for practicalitymore » and flexibility, allowing for relatively easy modifications to suit different experimental needs. We have coupled this VMI to a cryogenic ion trap mass spectrometer that has a flexible source design. The performance is demonstrated with the photoelectron spectra of S- and CS 2 -. The latter has a long vibrational progression in the ground state, and the temperature dependence of the vibronic features is probed by changing the temperature of the ion trap.« less

A multi-plate velocity-map imaging design for high-resolution photoelectron spectroscopy

DOE PAGES

Kregel, Steven J.; Thurston, Glen K.; Zhou, Jia; ...

2017-09-01

A velocity map imaging (VMI) setup consisting of multiple electrodes with three adjustable voltage parameters, designed for slow electron velocity map imaging applications, is presented. The motivations for this design are discussed in terms of parameters that influence the VMI resolution and functionality. Particularly, this VMI has two tunable potentials used to adjust for optimal focus, yielding good VMI focus across a relatively large energy range. It also allows for larger interaction volumes without significant sacrifice to the resolution via a smaller electric gradient at the interaction region. All the electrodes in this VMI have the same dimensions for practicalitymore » and flexibility, allowing for relatively easy modifications to suit different experimental needs. We have coupled this VMI to a cryogenic ion trap mass spectrometer that has a flexible source design. The performance is demonstrated with the photoelectron spectra of S- and CS 2 -. The latter has a long vibrational progression in the ground state, and the temperature dependence of the vibronic features is probed by changing the temperature of the ion trap.« less

Can multi-slice or navigator-gated R2* MRI replace single-slice breath-hold acquisition for hepatic iron quantification?

PubMed

Loeffler, Ralf B; McCarville, M Beth; Wagstaff, Anne W; Smeltzer, Matthew P; Krafft, Axel J; Song, Ruitian; Hankins, Jane S; Hillenbrand, Claudia M

2017-01-01

Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be interchangeably used in existing R2*-HIC calibrations.

SU-C-BRA-01: Interactive Auto-Segmentation for Bowel in Online Adaptive MRI-Guided Radiation Therapy by Using a Multi-Region Labeling Algorithm

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

Lu, Y; Chen, I; Kashani, R

Purpose: In MRI-guided online adaptive radiation therapy, re-contouring of bowel is time-consuming and can impact the overall time of patients on table. The study aims to auto-segment bowel on volumetric MR images by using an interactive multi-region labeling algorithm. Methods: 5 Patients with locally advanced pancreatic cancer underwent fractionated radiotherapy (18–25 fractions each, total 118 fractions) on an MRI-guided radiation therapy system with a 0.35 Tesla magnet and three Co-60 sources. At each fraction, a volumetric MR image of the patient was acquired when the patient was in the treatment position. An interactive two-dimensional multi-region labeling technique based on graphmore » cut solver was applied on several typical MRI images to segment the large bowel and small bowel, followed by a shape based contour interpolation for generating entire bowel contours along all image slices. The resulted contours were compared with the physician’s manual contouring by using metrics of Dice coefficient and Hausdorff distance. Results: Image data sets from the first 5 fractions of each patient were selected (total of 25 image data sets) for the segmentation test. The algorithm segmented the large and small bowel effectively and efficiently. All bowel segments were successfully identified, auto-contoured and matched with manual contours. The time cost by the algorithm for each image slice was within 30 seconds. For large bowel, the calculated Dice coefficients and Hausdorff distances (mean±std) were 0.77±0.07 and 13.13±5.01mm, respectively; for small bowel, the corresponding metrics were 0.73±0.08and 14.15±4.72mm, respectively. Conclusion: The preliminary results demonstrated the potential of the proposed algorithm in auto-segmenting large and small bowel on low field MRI images in MRI-guided adaptive radiation therapy. Further work will be focused on improving its segmentation accuracy and lessening human interaction.« less

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure.

PubMed

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-05-11

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

PubMed Central

Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

2017-01-01

Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures. PMID:28772879

Towards designing an optical-flow based colonoscopy tracking algorithm: a comparative study

NASA Astrophysics Data System (ADS)

Liu, Jianfei; Subramanian, Kalpathi R.; Yoo, Terry S.

2013-03-01

Automatic co-alignment of optical and virtual colonoscopy images can supplement traditional endoscopic procedures, by providing more complete information of clinical value to the gastroenterologist. In this work, we present a comparative analysis of our optical flow based technique for colonoscopy tracking, in relation to current state of the art methods, in terms of tracking accuracy, system stability, and computational efficiency. Our optical-flow based colonoscopy tracking algorithm starts with computing multi-scale dense and sparse optical flow fields to measure image displacements. Camera motion parameters are then determined from optical flow fields by employing a Focus of Expansion (FOE) constrained egomotion estimation scheme. We analyze the design choices involved in the three major components of our algorithm: dense optical flow, sparse optical flow, and egomotion estimation. Brox's optical flow method,1 due to its high accuracy, was used to compare and evaluate our multi-scale dense optical flow scheme. SIFT6 and Harris-affine features7 were used to assess the accuracy of the multi-scale sparse optical flow, because of their wide use in tracking applications; the FOE-constrained egomotion estimation was compared with collinear,2 image deformation10 and image derivative4 based egomotion estimation methods, to understand the stability of our tracking system. Two virtual colonoscopy (VC) image sequences were used in the study, since the exact camera parameters(for each frame) were known; dense optical flow results indicated that Brox's method was superior to multi-scale dense optical flow in estimating camera rotational velocities, but the final tracking errors were comparable, viz., 6mm vs. 8mm after the VC camera traveled 110mm. Our approach was computationally more efficient, averaging 7.2 sec. vs. 38 sec. per frame. SIFT and Harris affine features resulted in tracking errors of up to 70mm, while our sparse optical flow error was 6mm. The comparison among egomotion estimation algorithms showed that our FOE-constrained egomotion estimation method achieved the optimal balance between tracking accuracy and robustness. The comparative study demonstrated that our optical-flow based colonoscopy tracking algorithm maintains good accuracy and stability for routine use in clinical practice.

Multiple energy synchrotron biomedical imaging system

NASA Astrophysics Data System (ADS)

Bassey, B.; Martinson, M.; Samadi, N.; Belev, G.; Karanfil, C.; Qi, P.; Chapman, D.

2016-12-01

A multiple energy imaging system that can extract multiple endogenous or induced contrast materials as well as water and bone images would be ideal for imaging of biological subjects. The continuous spectrum available from synchrotron light facilities provides a nearly perfect source for multiple energy x-ray imaging. A novel multiple energy x-ray imaging system, which prepares a horizontally focused polychromatic x-ray beam, has been developed at the BioMedical Imaging and Therapy bend magnet beamline at the Canadian Light Source. The imaging system is made up of a cylindrically bent Laue single silicon (5,1,1) crystal monochromator, scanning and positioning stages for the subjects, flat panel (area) detector, and a data acquisition and control system. Depending on the crystal’s bent radius, reflection type, and the horizontal beam width of the filtered synchrotron radiation (20-50 keV) used, the size and spectral energy range of the focused beam prepared varied. For example, with a bent radius of 95 cm, a (1,1,1) type reflection and a 50 mm wide beam, a 0.5 mm wide focused beam of spectral energy range 27 keV-43 keV was obtained. This spectral energy range covers the K-edges of iodine (33.17 keV), xenon (34.56 keV), cesium (35.99 keV), and barium (37.44 keV) some of these elements are used as biomedical and clinical contrast agents. Using the developed imaging system, a test subject composed of iodine, xenon, cesium, and barium along with water and bone were imaged and their projected concentrations successfully extracted. The estimated dose rate to test subjects imaged at a ring current of 200 mA is 8.7 mGy s-1, corresponding to a cumulative dose of 1.3 Gy and a dose of 26.1 mGy per image. Potential biomedical applications of the imaging system will include projection imaging that requires any of the extracted elements as a contrast agent and multi-contrast K-edge imaging.

Focused Impedance Method (FIM) and Pigeon Hole Imaging (PHI) for localized measurements - a review

NASA Astrophysics Data System (ADS)

Siddique-e Rabbani, K.

2010-04-01

This paper summarises up to date development in Focused Impedance Method (FIM) initiated by us. It basically involves taking the sum of two orthogonal tetra-polar impedance measurements around a common central region, giving a localized enhanced sensitivity. Although the basic idea requires 8 electrodes, versions with 6- and 4-electrodes were subsequently conceived and developed. The focusing effect has been verified in 2D and 3D phantoms and through numerical analysis. Dynamic stomach emptying, and ventilation of localized lung regions have been studied successfully suggesting further applications in monitoring of gastric acid secretion, artificial respiration, bladder emptying, etc. Multi-frequency FIM may help identify some diseases and disorders including certain cancers. FIM, being much simpler and having less number of electrodes, appears to have the potential to replace EIT for applications involving large and shallow organs. An enhancement of 6-electrode FIM led to Pigeon Hole Imaging (PHI) in a square matrix through backprojection in two orthogonal directions, good for localising of one or two well separated objects.

Molecular breast tomosynthesis with scanning focus multi-pinhole cameras

NASA Astrophysics Data System (ADS)

van Roosmalen, Jarno; Goorden, Marlies C.; Beekman, Freek J.

2016-08-01

Planar molecular breast imaging (MBI) is rapidly gaining in popularity in diagnostic oncology. To add 3D capabilities, we introduce a novel molecular breast tomosynthesis (MBT) scanner concept based on multi-pinhole collimation. In our design, the patient lies prone with the pendant breast lightly compressed between transparent plates. Integrated webcams view the breast through these plates and allow the operator to designate the scan volume (e.g. a whole breast or a suspected region). The breast is then scanned by translating focusing multi-pinhole plates and NaI(Tl) gamma detectors together in a sequence that optimizes count yield from the volume-of-interest. With simulations, we compared MBT with existing planar MBI. In a breast phantom containing different lesions, MBT improved tumour-to-background contrast-to-noise ratio (CNR) over planar MBI by 12% and 111% for 4.0 and 6.0 mm lesions respectively in case of whole breast scanning. For the same lesions, much larger CNR improvements of 92% and 241% over planar MBI were found in a scan that focused on a breast region containing several lesions. MBT resolved 3.0 mm rods in a Derenzo resolution phantom in the transverse plane compared to 2.5 mm rods distinguished by planar MBI. While planar MBI cannot provide depth information, MBT offered 4.0 mm depth resolution. Our simulations indicate that besides offering 3D localization of increased tracer uptake, multi-pinhole MBT can significantly increase tumour-to-background CNR compared to planar MBI. These properties could be promising for better estimating the position, extend and shape of lesions and distinguishing between single and multiple lesions.

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

PubMed

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8 months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. PMID:25541188

Dynamically re-configurable CMOS imagers for an active vision system

NASA Technical Reports Server (NTRS)

Yang, Guang (Inventor); Pain, Bedabrata (Inventor)

2005-01-01

A vision system is disclosed. The system includes a pixel array, at least one multi-resolution window operation circuit, and a pixel averaging circuit. The pixel array has an array of pixels configured to receive light signals from an image having at least one tracking target. The multi-resolution window operation circuits are configured to process the image. Each of the multi-resolution window operation circuits processes each tracking target within a particular multi-resolution window. The pixel averaging circuit is configured to sample and average pixels within the particular multi-resolution window.

A new multi-spectral feature level image fusion method for human interpretation

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-03-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in a three-task experiment using MSSF against two established methods: averaging and principle components analysis (PCA), and against its two source bands, visible and infrared. The three tasks that we studied were: (1) simple target detection, (2) spatial orientation, and (3) camouflaged target detection. MSSF proved superior to the other fusion methods in all three tests; MSSF also outperformed the source images in the spatial orientation and camouflaged target detection tasks. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Phase Diversity Applied to Sunspot Observations

NASA Astrophysics Data System (ADS)

Tritschler, A.; Schmidt, W.; Knolker, M.

We present preliminary results of a multi-colour phase diversity experiment carried out with the Multichannel Filter System of the Vacuum Tower Telescope at the Observatorio del Teide on Tenerife. We apply phase-diversity imaging to a time sequence of sunspot filtergrams taken in three continuum bands and correct the seeing influence for each image. A newly developed phase diversity device allowing for the projection of both the focused and the defocused image onto a single CCD chip was used in one of the wavelength channels. With the information about the wavefront obtained by the image reconstruction algorithm the restoration of the other two bands can be performed as well. The processed and restored data set will then be used to derive the temperature and proper motion of the umbral dots. Data analysis is still under way, and final results will be given in a forthcoming article.

The Advanced Gamma-ray Imaging System (AGIS): Schwarzschild-Couder (SC) Telescope Mechanical and Optical System Design

NASA Astrophysics Data System (ADS)

Byrum, Karen L.; Vassiliev, V.; AGIS Collaboration

2010-03-01

AGIS is a concept for the next-generation ground-based gamma-ray observatory. It will be an array of 36 imaging atmospheric Cherenkov telescopes (IACTs) sensitive in the energy range from 50 GeV to 200 TeV. The required improvements in sensitivity, angular resolution, and reliability of operation relative to the present generation instruments imposes demanding technological and cost requirements on the design of AGIS telescopes. In this submission, we outline the status of the development of the optical and mechanical systems for a novel Schwarzschild-Couder two-mirror aplanatic telescope. This design can provide a field of view and angular resolution significantly better to those offered by the traditional Davies-Cotton optics utilized in present-day IACTs. Other benefits of the novel design include isochronous focusing and compatibility with cost-effective, high quantum efficiency image sensors such as multi-anode PMTs, silicon PMTs (SiPMs), or image intensifiers.

Stereo Imaging Miniature Endoscope with Single Imaging Chip and Conjugated Multi-Bandpass Filters

NASA Technical Reports Server (NTRS)

Shahinian, Hrayr Karnig (Inventor); Bae, Youngsam (Inventor); White, Victor E. (Inventor); Shcheglov, Kirill V. (Inventor); Manohara, Harish M. (Inventor); Kowalczyk, Robert S. (Inventor)

2018-01-01

A dual objective endoscope for insertion into a cavity of a body for providing a stereoscopic image of a region of interest inside of the body including an imaging device at the distal end for obtaining optical images of the region of interest (ROI), and processing the optical images for forming video signals for wired and/or wireless transmission and display of 3D images on a rendering device. The imaging device includes a focal plane detector array (FPA) for obtaining the optical images of the ROI, and processing circuits behind the FPA. The processing circuits convert the optical images into the video signals. The imaging device includes right and left pupil for receiving a right and left images through a right and left conjugated multi-band pass filters. Illuminators illuminate the ROI through a multi-band pass filter having three right and three left pass bands that are matched to the right and left conjugated multi-band pass filters. A full color image is collected after three or six sequential illuminations with the red, green and blue lights.

The NuSTAR Mission: Implementation and Science Prospects

NASA Technical Reports Server (NTRS)

Zhang, William W.

2009-01-01

NuSTAR is NASA's next X-ray observatory scheduled to be launched in 2011. It will have two multi-layered X-ray mirror assemblies capable of focusing X-rays in the band of 5 to 80 keV, providing unprecedented detection and imaging sensitivity in a band that only coded-mask or collimated detection has been possible. In this talk I will describe the instrumentation and the prospects of using it to perform various kinds of astronomical studies.

Fusion of multi-spectral and panchromatic images based on 2D-PWVD and SSIM

NASA Astrophysics Data System (ADS)

Tan, Dongjie; Liu, Yi; Hou, Ruonan; Xue, Bindang

2016-03-01

A combined method using 2D pseudo Wigner-Ville distribution (2D-PWVD) and structural similarity(SSIM) index is proposed for fusion of low resolution multi-spectral (MS) image and high resolution panchromatic (PAN) image. First, the intensity component of multi-spectral image is extracted with generalized IHS transform. Then, the spectrum diagrams of the intensity components of multi-spectral image and panchromatic image are obtained with 2D-PWVD. Different fusion rules are designed for different frequency information of the spectrum diagrams. SSIM index is used to evaluate the high frequency information of the spectrum diagrams for assigning the weights in the fusion processing adaptively. After the new spectrum diagram is achieved according to the fusion rule, the final fusion image can be obtained by inverse 2D-PWVD and inverse GIHS transform. Experimental results show that, the proposed method can obtain high quality fusion images.

Image-guided thoracic surgery in the hybrid operation room.

PubMed

Ujiie, Hideki; Effat, Andrew; Yasufuku, Kazuhiro

2017-01-01

There has been an increase in the use of image-guided technology to facilitate minimally invasive therapy. The next generation of minimally invasive therapy is focused on advancement and translation of novel image-guided technologies in therapeutic interventions, including surgery, interventional pulmonology, radiation therapy, and interventional laser therapy. To establish the efficacy of different minimally invasive therapies, we have developed a hybrid operating room, known as the guided therapeutics operating room (GTx OR) at the Toronto General Hospital. The GTx OR is equipped with multi-modality image-guidance systems, which features a dual source-dual energy computed tomography (CT) scanner, a robotic cone-beam CT (CBCT)/fluoroscopy, high-performance endobronchial ultrasound system, endoscopic surgery system, near-infrared (NIR) fluorescence imaging system, and navigation tracking systems. The novel multimodality image-guidance systems allow physicians to quickly, and accurately image patients while they are on the operating table. This yield improved outcomes since physicians are able to use image guidance during their procedures, and carry out innovative multi-modality therapeutics. Multiple preclinical translational studies pertaining to innovative minimally invasive technology is being developed in our guided therapeutics laboratory (GTx Lab). The GTx Lab is equipped with similar technology, and multimodality image-guidance systems as the GTx OR, and acts as an appropriate platform for translation of research into human clinical trials. Through the GTx Lab, we are able to perform basic research, such as the development of image-guided technologies, preclinical model testing, as well as preclinical imaging, and then translate that research into the GTx OR. This OR allows for the utilization of new technologies in cancer therapy, including molecular imaging, and other innovative imaging modalities, and therefore enables a better quality of life for patients, both during and after the procedure. In this article, we describe capabilities of the GTx systems, and discuss the first-in-human technologies used, and evaluated in GTx OR.

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

PubMed Central

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

2017-01-01

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

Multi-resolutional shape features via non-Euclidean wavelets: Applications to statistical analysis of cortical thickness

PubMed Central

Kim, Won Hwa; Singh, Vikas; Chung, Moo K.; Hinrichs, Chris; Pachauri, Deepti; Okonkwo, Ozioma C.; Johnson, Sterling C.

2014-01-01

Statistical analysis on arbitrary surface meshes such as the cortical surface is an important approach to understanding brain diseases such as Alzheimer’s disease (AD). Surface analysis may be able to identify specific cortical patterns that relate to certain disease characteristics or exhibit differences between groups. Our goal in this paper is to make group analysis of signals on surfaces more sensitive. To do this, we derive multi-scale shape descriptors that characterize the signal around each mesh vertex, i.e., its local context, at varying levels of resolution. In order to define such a shape descriptor, we make use of recent results from harmonic analysis that extend traditional continuous wavelet theory from the Euclidean to a non-Euclidean setting (i.e., a graph, mesh or network). Using this descriptor, we conduct experiments on two different datasets, the Alzheimer’s Disease NeuroImaging Initiative (ADNI) data and images acquired at the Wisconsin Alzheimer’s Disease Research Center (W-ADRC), focusing on individuals labeled as having Alzheimer’s disease (AD), mild cognitive impairment (MCI) and healthy controls. In particular, we contrast traditional univariate methods with our multi-resolution approach which show increased sensitivity and improved statistical power to detect a group-level effects. We also provide an open source implementation. PMID:24614060

Deep multi-spectral ensemble learning for electronic cleansing in dual-energy CT colonography

NASA Astrophysics Data System (ADS)

Tachibana, Rie; Näppi, Janne J.; Hironaka, Toru; Kim, Se Hyung; Yoshida, Hiroyuki

2017-03-01

We developed a novel electronic cleansing (EC) method for dual-energy CT colonography (DE-CTC) based on an ensemble deep convolution neural network (DCNN) and multi-spectral multi-slice image patches. In the method, an ensemble DCNN is used to classify each voxel of a DE-CTC image volume into five classes: luminal air, soft tissue, tagged fecal materials, and partial-volume boundaries between air and tagging and those between soft tissue and tagging. Each DCNN acts as a voxel classifier, where an input image patch centered at the voxel is generated as input to the DCNNs. An image patch has three channels that are mapped from a region-of-interest containing the image plane of the voxel and the two adjacent image planes. Six different types of spectral input image datasets were derived using two dual-energy CT images, two virtual monochromatic images, and two material images. An ensemble DCNN was constructed by use of a meta-classifier that combines the output of multiple DCNNs, each of which was trained with a different type of multi-spectral image patches. The electronically cleansed CTC images were calculated by removal of regions classified as other than soft tissue, followed by a colon surface reconstruction. For pilot evaluation, 359 volumes of interest (VOIs) representing sources of subtraction artifacts observed in current EC schemes were sampled from 30 clinical CTC cases. Preliminary results showed that the ensemble DCNN can yield high accuracy in labeling of the VOIs, indicating that deep learning of multi-spectral EC with multi-slice imaging could accurately remove residual fecal materials from CTC images without generating major EC artifacts.

Buildings Change Detection Based on Shape Matching for Multi-Resolution Remote Sensing Imagery

NASA Astrophysics Data System (ADS)

Abdessetar, M.; Zhong, Y.

2017-09-01

Buildings change detection has the ability to quantify the temporal effect, on urban area, for urban evolution study or damage assessment in disaster cases. In this context, changes analysis might involve the utilization of the available satellite images with different resolutions for quick responses. In this paper, to avoid using traditional method with image resampling outcomes and salt-pepper effect, building change detection based on shape matching is proposed for multi-resolution remote sensing images. Since the object's shape can be extracted from remote sensing imagery and the shapes of corresponding objects in multi-scale images are similar, it is practical for detecting buildings changes in multi-scale imagery using shape analysis. Therefore, the proposed methodology can deal with different pixel size for identifying new and demolished buildings in urban area using geometric properties of objects of interest. After rectifying the desired multi-dates and multi-resolutions images, by image to image registration with optimal RMS value, objects based image classification is performed to extract buildings shape from the images. Next, Centroid-Coincident Matching is conducted, on the extracted building shapes, based on the Euclidean distance measurement between shapes centroid (from shape T0 to shape T1 and vice versa), in order to define corresponding building objects. Then, New and Demolished buildings are identified based on the obtained distances those are greater than RMS value (No match in the same location).

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles

PubMed Central

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-01-01

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions. PMID:28029145

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles.

PubMed

Wang, Xuan; Liu, Jinghong; Zhou, Qianfei

2016-12-25

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions.

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

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM).

PubMed

Gao, Hao; Yu, Hengyong; Osher, Stanley; Wang, Ge

2011-11-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations.

RAMTaB: Robust Alignment of Multi-Tag Bioimages

PubMed Central

Raza, Shan-e-Ahmed; Humayun, Ahmad; Abouna, Sylvie; Nattkemper, Tim W.; Epstein, David B. A.; Khan, Michael; Rajpoot, Nasir M.

2012-01-01

Background In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images. Methodology/Principal Findings We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies. Conclusions For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks. PMID:22363510

Extra-cardiac findings in cardiovascular magnetic resonance: what the imaging cardiologist needs to know.

PubMed

Rodrigues, Jonathan C L; Lyen, Stephen M; Loughborough, William; Amadu, Antonio Matteo; Baritussio, Anna; Dastidar, Amardeep Ghosh; Manghat, Nathan E; Bucciarelli-Ducci, Chiara

2016-05-09

Cardiovascular magnetic resonance (CMR) is an established non-invasive technique to comprehensively assess cardiovascular structure and function in a variety of acquired and inherited cardiac conditions. A significant amount of the neck, thorax and upper abdomen are imaged at the time of routine clinical CMR, particularly in the initial multi-slice axial and coronal images. The discovery of unsuspected disease at the time of imaging has ethical, financial and medico-legal implications. Extra-cardiac findings at the time of CMR are common, can be important and can change clinical management. Certain patient groups undergoing CMR are at particular risk of important extra-cardiac findings as several of the cardiovascular risk factors for atherosclerosis are also risk factors for malignancy. Furthermore, the presence of certain extra-cardiac findings may contribute to the interpretation of the primary cardiac pathology as some cardiac conditions have multi-systemic extra-cardiac involvement. The aim of this review is to give an overview of the type of extra-cardiac findings that may become apparent on CMR, subdivided by anatomical location. We focus on normal variant anatomy that may mimic disease, common incidental extra-cardiac findings and important imaging signs that help distinguish sinister pathology from benign disease. We also aim to provide a framework to the approach and potential further diagnostic work-up of incidental extra-cardiac findings discovered at the time of CMR. However, it is beyond the scope of this review to discuss and determine the clinical significance of extracardiac findings at CMR.

Implementation and performance of the metrology system for the multi-object optical and near-infrared spectrograph MOONS

NASA Astrophysics Data System (ADS)

Drass, Holger; Vanzi, Leonardo; Torres-Torriti, Miguel; Dünner, Rolando; Shen, Tzu-Chiang; Belmar, Francisco; Dauvin, Lousie; Staig, Tomás.; Antognini, Jonathan; Flores, Mauricio; Luco, Yerko; Béchet, Clémentine; Boettger, David; Beard, Steven; Montgomery, David; Watson, Stephen; Cabral, Alexandre; Hayati, Mahmoud; Abreu, Manuel; Rees, Phil; Cirasuolo, Michele; Taylor, William; Fairley, Alasdair

2016-08-01

The Multi-Object Optical and Near-infrared Spectrograph (MOONS) will cover the Very Large Telescope's (VLT) field of view with 1000 fibres. The fibres will be mounted on fibre positioning units (FPU) implemented as two-DOF robot arms to ensure a homogeneous coverage of the 500 square arcmin field of view. To accurately and fast determine the position of the 1000 fibres a metrology system has been designed. This paper presents the hardware and software design and performance of the metrology system. The metrology system is based on the analysis of images taken by a circular array of 12 cameras located close to the VLTs derotator ring around the Nasmyth focus. The system includes 24 individually adjustable lamps. The fibre positions are measured through dedicated metrology targets mounted on top of the FPUs and fiducial markers connected to the FPU support plate which are imaged at the same time. A flexible pipeline based on VLT standards is used to process the images. The position accuracy was determined to 5 μm in the central region of the images. Including the outer regions the overall positioning accuracy is 25 μm. The MOONS metrology system is fully set up with a working prototype. The results in parts of the images are already excellent. By using upcoming hardware and improving the calibration it is expected to fulfil the accuracy requirement over the complete field of view for all metrology cameras.

Automated reconstruction of standing posture panoramas from multi-sector long limb x-ray images

NASA Astrophysics Data System (ADS)

Miller, Linzey; Trier, Caroline; Ben-Zikri, Yehuda K.; Linte, Cristian A.

2016-03-01

Due to the digital X-ray imaging system's limited field of view, several individual sector images are required to capture the posture of an individual in standing position. These images are then "stitched together" to reconstruct the standing posture. We have created an image processing application that automates the stitching, therefore minimizing user input, optimizing workflow, and reducing human error. The application begins with pre-processing the input images by removing artifacts, filtering out isolated noisy regions, and amplifying a seamless bone edge. The resulting binary images are then registered together using a rigid-body intensity based registration algorithm. The identified registration transformations are then used to map the original sector images into the panorama image. Our method focuses primarily on the use of the anatomical content of the images to generate the panoramas as opposed to using external markers employed to aid with the alignment process. Currently, results show robust edge detection prior to registration and we have tested our approach by comparing the resulting automatically-stitched panoramas to the manually stitched panoramas in terms of registration parameters, target registration error of homologous markers, and the homogeneity of the digitally subtracted automatically- and manually-stitched images using 26 patient datasets.

Discrimination of coastal wetland environments in the Amazon region based on multi-polarized L-band airborne Synthetic Aperture Radar imagery

NASA Astrophysics Data System (ADS)

Souza-Filho, Pedro Walfir M.; Paradella, Waldir R.; Rodrigues, Suzan W. P.; Costa, Francisco R.; Mura, José C.; Gonçalves, Fabrício D.

2011-11-01

This study assessed the use of multi-polarized L-band images for the identification of coastal wetland environments in the Amazon coast region of northern Brazil. Data were acquired with a SAR R99B sensor from the Amazon Surveillance System (SIVAM) on board a Brazilian Air Force jet. Flights took place in the framework of the 2005 MAPSAR simulation campaign, a German-Brazilian feasibility study focusing on a L-band SAR satellite. Information retrieval was based on the recognition of the interaction between a radar signal and shallow-water morphology in intertidal areas, coastal dunes, mangroves, marshes and the coastal plateau. Regarding the performance of polarizations, VV was superior for recognizing intertidal area morphology under low spring tide conditions; HH for mapping coastal environments covered with forest and scrub vegetation such as mangrove and vegetated dunes, and HV was suitable for distinguishing transition zones between mangroves and coastal plateau. The statistical results for the classification maps expressed by kappa index and general accuracy were 83.3% and 0.734 for the multi-polarized color composition (R-HH, G-HV, B-VV), 80.7% and 0.694% for HH, 79.7% and 0.673% for VV, and 77.9% and 0.645% for HV amplitude image. The results indicate that use of multi-polarized L-band SAR is a valuable source of information aiming at the identification and discrimination of distinct geomorphic targets in tropical wetlands.

Inter-subject FDG PET Brain Networks Exhibit Multi-scale Community Structure with Different Normalization Techniques.

PubMed

Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A

2018-07-01

Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p < 0.00001); however, community structure is similar at network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.

A Silicon SPECT System for Molecular Imaging of the Mouse Brain.

PubMed

Shokouhi, Sepideh; Fritz, Mark A; McDonald, Benjamin S; Durko, Heather L; Furenlid, Lars R; Wilson, Donald W; Peterson, Todd E

2007-01-01

We previously demonstrated the feasibility of using silicon double-sided strip detectors (DSSDs) for SPECT imaging of the activity distribution of iodine-125 using a 300-micrometer thick detector. Based on this experience, we now have developed fully customized silicon DSSDs and associated readout electronics with the intent of developing a multi-pinhole SPECT system. Each DSSD has a 60.4 mm × 60.4 mm active area and is 1 mm thick. The strip pitch is 59 micrometers, and the readout of the 1024 strips on each side gives rise to a detector with over one million pixels. Combining four high-resolution DSSDs into a SPECT system offers an unprecedented space-bandwidth product for the imaging of single-photon emitters. The system consists of two camera heads with two silicon detectors stacked one behind the other in each head. The collimator has a focused pinhole system with cylindrical-shaped pinholes that are laser-drilled in a 250 μm tungsten plate. The unique ability to collect projection data at two magnifications simultaneously allows for multiplexed data at high resolution to be combined with lower magnification data with little or no multiplexing. With the current multi-pinhole collimator design, our SPECT system will be capable of offering high spatial resolution, sensitivity and angular sampling for small field-of-view applications, such as molecular imaging of the mouse brain.

Impact of hypoxia and the metabolic microenvironment on radiotherapy of solid tumors. Introduction of a multi-institutional research project.

PubMed

Zips, Daniel; Adam, Markus; Flentje, Michael; Haase, Axel; Molls, Michael; Mueller-Klieser, Wolfgang; Petersen, Cordula; Philbrook, Christine; Schmitt, Peter; Thews, Oliver; Walenta, Stefan; Baumann, Michael

2004-10-01

Recent developments in imaging technology and tumor biology have led to new techniques to detect hypoxia and related alterations of the metabolic microenvironment in tumors. However, whether these new methods can predict radiobiological hypoxia and outcome after fractionated radiotherapy still awaits experimental evaluation. The present article will introduce a multi-institutional research project addressing the impact of hypoxia and the metabolic microenvironment on radiotherapy of solid tumors. The four laboratories involved are situated at the universities of Dresden, Mainz, Munich and Würzburg, Germany. The joint scientific project started to collect data obtained on a set of ten different human tumor xenografts growing in nude mice by applying various imaging techniques to detect tumor hypoxia and related parameters of the metabolic microenvironment. These techniques include magnetic resonance imaging and spectroscopy, metabolic mapping with quantitative bioluminescence and single-photon imaging, histological multiparameter analysis of biochemical hypoxia, perfusion and vasculature, and immunohistochemistry of factors related to angiogenesis, invasion and metastasis. To evaluate the different methods, baseline functional radiobiological data including radiobiological hypoxic fraction and outcome after fractionated irradiation will be determined. Besides increasing our understanding of tumor biology, the project will focus on new, clinically applicable strategies for microenvironment profiling and will help to identify those patients that might benefit from targeted interventions to improve tumor oxygenation.

An enhanced multi-view vertical line locus matching algorithm of object space ground primitives based on positioning consistency for aerial and space images

NASA Astrophysics Data System (ADS)

Zhang, Ka; Sheng, Yehua; Wang, Meizhen; Fu, Suxia

2018-05-01

The traditional multi-view vertical line locus (TMVLL) matching method is an object-space-based method that is commonly used to directly acquire spatial 3D coordinates of ground objects in photogrammetry. However, the TMVLL method can only obtain one elevation and lacks an accurate means of validating the matching results. In this paper, we propose an enhanced multi-view vertical line locus (EMVLL) matching algorithm based on positioning consistency for aerial or space images. The algorithm involves three components: confirming candidate pixels of the ground primitive in the base image, multi-view image matching based on the object space constraints for all candidate pixels, and validating the consistency of the object space coordinates with the multi-view matching result. The proposed algorithm was tested using actual aerial images and space images. Experimental results show that the EMVLL method successfully solves the problems associated with the TMVLL method, and has greater reliability, accuracy and computing efficiency.

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-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

Multispectral image fusion for target detection

NASA Astrophysics Data System (ADS)

Leviner, Marom; Maltz, Masha

2009-09-01

Various different methods to perform multi-spectral image fusion have been suggested, mostly on the pixel level. However, the jury is still out on the benefits of a fused image compared to its source images. We present here a new multi-spectral image fusion method, multi-spectral segmentation fusion (MSSF), which uses a feature level processing paradigm. To test our method, we compared human observer performance in an experiment using MSSF against two established methods: Averaging and Principle Components Analysis (PCA), and against its two source bands, visible and infrared. The task that we studied was: target detection in the cluttered environment. MSSF proved superior to the other fusion methods. Based on these findings, current speculation about the circumstances in which multi-spectral image fusion in general and specific fusion methods in particular would be superior to using the original image sources can be further addressed.

Highlights lecture EANM 2016: "Embracing molecular imaging and multi-modal imaging: a smart move for nuclear medicine towards personalized medicine".

PubMed

Aboagye, Eric O; Kraeber-Bodéré, Françoise

2017-08-01

The 2016 EANM Congress took place in Barcelona, Spain, from 15 to 19 October under the leadership of Prof. Wim Oyen, chair of the EANM Scientific Committee. With more than 6,000 participants, this congress was the most important European event in nuclear medicine, bringing together a multidisciplinary community involved in the different fields of nuclear medicine. There were over 600 oral and 1,200 poster or e-Poster presentations with an overwhelming focus on development and application of imaging for personalized care, which is timely for the community. Beyond FDG PET, major highlights included progress in the use of PSMA and SSTR receptor-targeted radiopharmaceuticals and associated theranostics in oncology. Innovations in radiopharmaceuticals for imaging pathologies of the brain and cardiovascular system, as well as infection and inflammation, were also highlighted. In the areas of physics and instrumentation, multimodality imaging and radiomics were highlighted as promising areas of research.

Depth estimation and camera calibration of a focused plenoptic camera for visual odometry

NASA Astrophysics Data System (ADS)

Zeller, Niclas; Quint, Franz; Stilla, Uwe

2016-08-01

This paper presents new and improved methods of depth estimation and camera calibration for visual odometry with a focused plenoptic camera. For depth estimation we adapt an algorithm previously used in structure-from-motion approaches to work with images of a focused plenoptic camera. In the raw image of a plenoptic camera, scene patches are recorded in several micro-images under slightly different angles. This leads to a multi-view stereo-problem. To reduce the complexity, we divide this into multiple binocular stereo problems. For each pixel with sufficient gradient we estimate a virtual (uncalibrated) depth based on local intensity error minimization. The estimated depth is characterized by the variance of the estimate and is subsequently updated with the estimates from other micro-images. Updating is performed in a Kalman-like fashion. The result of depth estimation in a single image of the plenoptic camera is a probabilistic depth map, where each depth pixel consists of an estimated virtual depth and a corresponding variance. Since the resulting image of the plenoptic camera contains two plains: the optical image and the depth map, camera calibration is divided into two separate sub-problems. The optical path is calibrated based on a traditional calibration method. For calibrating the depth map we introduce two novel model based methods, which define the relation of the virtual depth, which has been estimated based on the light-field image, and the metric object distance. These two methods are compared to a well known curve fitting approach. Both model based methods show significant advantages compared to the curve fitting method. For visual odometry we fuse the probabilistic depth map gained from one shot of the plenoptic camera with the depth data gained by finding stereo correspondences between subsequent synthesized intensity images of the plenoptic camera. These images can be synthesized totally focused and thus finding stereo correspondences is enhanced. In contrast to monocular visual odometry approaches, due to the calibration of the individual depth maps, the scale of the scene can be observed. Furthermore, due to the light-field information better tracking capabilities compared to the monocular case can be expected. As result, the depth information gained by the plenoptic camera based visual odometry algorithm proposed in this paper has superior accuracy and reliability compared to the depth estimated from a single light-field image.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Multi-photon excited luminescence of magnetic FePt core-shell nanoparticles.

PubMed

Seemann, K M; Kuhn, B

2014-07-01

We present magnetic FePt nanoparticles with a hydrophilic, inert, and biocompatible silico-tungsten oxide shell. The particles can be functionalized, optically detected, and optically manipulated. To show the functionalization the fluorescent dye NOPS was bound to the FePt core-shell nanoparticles with propyl-triethoxy-silane linkers and fluorescence of the labeled particles were observed in ethanol (EtOH). In aqueous dispersion the NOPS fluorescence is quenched making them invisible using 1-photon excitation. However, we observe bright luminescence of labeled and even unlabeled magnetic core-shell nanoparticles with multi-photon excitation. Luminescence can be detected in the near ultraviolet and the full visible spectral range by near infrared multi-photon excitation. For optical manipulation, we were able to drag clusters of particles, and maybe also single particles, by a focused laser beam that acts as optical tweezers by inducing an electric dipole in the insulated metal nanoparticles. In a first application, we show that the luminescence of the core-shell nanoparticles is bright enough for in vivo multi-photon imaging in the mouse neocortex down to cortical layer 5.

Flaw investigation in a multi-layered, multi-material composite: Using air-coupled ultrasonic resonance imaging

NASA Astrophysics Data System (ADS)

Livings, R. A.; Dayal, V.; Barnard, D. J.; Hsu, D. K.

2012-05-01

Ceramic tiles are the main ingredient of a multi-material, multi-layered composite being considered for the modernization of tank armors. The high stiffness, low attenuation, and precise dimensions of these uniform tiles make them remarkable resonators when driven to vibrate. Defects in the tile, during manufacture or after usage, are expected to change the resonance frequencies and resonance images of the tile. The comparison of the resonance frequencies and resonance images of a pristine tile/lay-up to a defective tile/lay-up will thus be a quantitative damage metric. By examining the vibrational behavior of these tiles and the composite lay-up with Finite Element Modeling and analytical plate vibration equations, the development of a new Nondestructive Evaluation technique is possible. This study examines the development of the Air-Coupled Ultrasonic Resonance Imaging technique as applied to a hexagonal ceramic tile and a multi-material, multi-layered composite.

Multi-frame partially saturated images blind deconvolution

NASA Astrophysics Data System (ADS)

Ye, Pengzhao; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

2016-12-01

When blurred images have saturated or over-exposed pixels, conventional blind deconvolution approaches often fail to estimate accurate point spread function (PSF) and will introduce local ringing artifacts. In this paper, we propose a method to deal with the problem under the modified multi-frame blind deconvolution framework. First, in the kernel estimation step, a light streak detection scheme using multi-frame blurred images is incorporated into the regularization constraint. Second, we deal with image regions affected by the saturated pixels separately by modeling a weighted matrix during each multi-frame deconvolution iteration process. Both synthetic and real-world examples show that more accurate PSFs can be estimated and restored images have richer details and less negative effects compared to state of art methods.

MMX-I: data-processing software for multimodal X-ray imaging and tomography.

PubMed

Bergamaschi, Antoine; Medjoubi, Kadda; Messaoudi, Cédric; Marco, Sergio; Somogyi, Andrea

2016-05-01

A new multi-platform freeware has been developed for the processing and reconstruction of scanning multi-technique X-ray imaging and tomography datasets. The software platform aims to treat different scanning imaging techniques: X-ray fluorescence, phase, absorption and dark field and any of their combinations, thus providing an easy-to-use data processing tool for the X-ray imaging user community. A dedicated data input stream copes with the input and management of large datasets (several hundred GB) collected during a typical multi-technique fast scan at the Nanoscopium beamline and even on a standard PC. To the authors' knowledge, this is the first software tool that aims at treating all of the modalities of scanning multi-technique imaging and tomography experiments.

An overview of instrumentation for the Large Binocular Telescope

NASA Astrophysics Data System (ADS)

Wagner, R. Mark

2012-09-01

An overview of instrumentation for the Large Binocular Telescope (LBT) is presented. Optical instrumentation includes the Large Binocular Camera (LBC), a pair of wide-field (27' x 27') mosaic CCD imagers at the prime focus, and the Multi-Object Double Spectrograph (MODS), a pair of dual-beam blue-red optimized long-slit spectrographs mounted at the left and right direct F/15 Gregorian foci incorporating multiple slit masks for multi-object spectroscopy over a 6' field and spectral resolutions of up to 2000. Infrared instrumentation includes the LBT Near-IR Spectroscopic Utility with Camera and Integral Field Unit for Extragalactic Research (LUCI), a modular near-infrared (0.9-2.5 μm) imager and spectrograph pair mounted at the left and right front bent F/15 Gregorian foci and designed for seeing-limited (FOV: 4' × 4') imaging, long-slit spectroscopy, and multiobject spectroscopy utilizing cooled slit masks and diffraction limited (FOV: 0'.5 × 0'.5) imaging and long-slit spectroscopy. Strategic instruments under development that can utilize the full 23-m baseline of the LBT include an interferometric cryogenic beam combiner with near-infrared and thermal-infrared instruments for Fizeau imaging and nulling interferometry (LBTI) and an optical bench near-infrared beam combiner utilizing multi-conjugate adaptive optics for high angular resolution and sensitivity (LINC-NIRVANA). LBTI is currently undergoing commissioning on the LBT and utilizing the installed adaptive secondary mirrors in both single- sided and two-sided beam combination modes. In addition, a fiber-fed bench spectrograph (PEPSI) capable of ultra high resolution spectroscopy and spectropolarimetry (R = 40,000-300,000) will be available as a principal investigator instrument. Over the past four years the LBC pair, LUCI1, and MODS1 have been commissioned and are now scheduled for routine partner science observations. The delivery of both LUCI2 and MODS2 is anticipated before the end of 2012. The availability of all these instruments mounted simultaneously on the LBT permits unique science, flexible scheduling, and improved operational support.

Model observer for assessing digital breast tomosynthesis for multi-lesion detection in the presence of anatomical noise

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.; Miner Haygood, Tamara; Park, Subok

2018-02-01

Model observers are widely used in task-based assessments of medical image quality. The presence of multiple abnormalities in a single set of images, such as in multifocal multicentric breast cancer (MFMC), has an immense clinical impact on treatment planning and survival outcomes. Detecting multiple breast tumors is challenging as MFMC is relatively uncommon, and human observers do not know the number or locations of tumors a priori. Digital breast tomosynthesis (DBT), in which an x-ray beam sweeps over a limited angular range across the breast, has the potential to improve the detection of multiple tumors. However, prior studies of DBT image quality all focus on unifocal breast cancers. In this study, we extended our 2D multi-lesion (ML) channelized Hotelling observer (CHO) into a 3D ML-CHO that detects multiple lesions from volumetric imaging data. Then we employed the 3D ML-CHO to identify optimal DBT acquisition geometries for detection of MFMC. Digital breast phantoms with multiple embedded synthetic lesions were scanned by simulated DBT scanners of different geometries (wide/narrow angular span, different number of projections per scan) to simulate MFMC cases. With new implementations of 3D partial least squares (PLS) and modified Laguerre-Gauss (LG) channels, the 3D ML-CHO made detection decisions based upon the overall information from individual DBT slices and their correlations. Our evaluation results show that: (1) the 3D ML-CHO could achieve good detection performance with a small number of channels, and 3D PLS channels on average outperform the counterpart LG channels; (2) incorporating locally varying anatomical backgrounds and their correlations as in the 3D ML-CHO is essential for multi-lesion detection; (3) the most effective DBT geometry for detection of MFMC may vary when the task of clinical interest changes, and a given DBT geometry may not yield images that are equally informative for detecting MF, MC, and unifocal cancers.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

Synthesis multi-projector content for multi-projector three dimension display using a layered representation

NASA Astrophysics Data System (ADS)

Qin, Chen; Ren, Bin; Guo, Longfei; Dou, Wenhua

2014-11-01

Multi-projector three dimension display is a promising multi-view glass-free three dimension (3D) display technology, can produce full colour high definition 3D images on its screen. One key problem of multi-projector 3D display is how to acquire the source images of projector array while avoiding pseudoscopic problem. This paper analysis the displaying characteristics of multi-projector 3D display first and then propose a projector content synthetic method using tetrahedral transform. A 3D video format that based on stereo image pair and associated disparity map is presented, it is well suit for any type of multi-projector 3D display and has advantage in saving storage usage. Experiment results show that our method solved the pseudoscopic problem.

Tone mapping infrared images using conditional filtering-based multi-scale retinex

NASA Astrophysics Data System (ADS)

Luo, Haibo; Xu, Lingyun; Hui, Bin; Chang, Zheng

2015-10-01

Tone mapping can be used to compress the dynamic range of the image data such that it can be fitted within the range of the reproduction media and human vision. The original infrared images that captured with infrared focal plane arrays (IFPA) are high dynamic images, so tone mapping infrared images is an important component in the infrared imaging systems, and it has become an active topic in recent years. In this paper, we present a tone mapping framework using multi-scale retinex. Firstly, a Conditional Gaussian Filter (CGF) was designed to suppress "halo" effect. Secondly, original infrared image is decomposed into a set of images that represent the mean of the image at different spatial resolutions by applying CGF of different scale. And then, a set of images that represent the multi-scale details of original image is produced by dividing the original image pointwise by the decomposed image. Thirdly, the final detail image is reconstructed by weighted sum of the multi-scale detail images together. Finally, histogram scaling and clipping is adopted to remove outliers and scale the detail image, 0.1% of the pixels are clipped at both extremities of the histogram. Experimental results show that the proposed algorithm efficiently increases the local contrast while preventing "halo" effect and provides a good rendition of visual effect.

Control of Formation-Flying Multi-Element Space Interferometers with Direct Interferometer-Output Feedback

NASA Technical Reports Server (NTRS)

Lu, Hui-Ling; Cheng, H. L.; Lyon, Richard G.; Carpenter, Kenneth G.

2007-01-01

The long-baseline space interferometer concept involving formation flying of multiple spacecraft holds great promise as future space missions for high-resolution imagery. A major challenge of obtaining high-quality interferometric synthesized images from long-baseline space interferometers is to accurately control these spacecraft and their optics payloads in the specified configuration. Our research focuses on the determination of the optical errors to achieve fine control of long-baseline space interferometers without resorting to additional sensing equipment. We present a suite of estimation tools that can effectively extract from the raw interferometric image relative x/y, piston translational and tip/tilt deviations at the exit pupil aperture. The use of these error estimates in achieving control of the interferometer elements is demonstrated using simulated as well as laboratory-collected interferometric stellar images.

Control of Formation-Flying Multi-Element Space Interferometers with Direct Interferometer-Output Feedback

NASA Technical Reports Server (NTRS)

Lu, Hui-Ling; Cheng, Victor H. L.; Lyon, Richard G.; Carpenter, Kenneth G.

2007-01-01

The long-baseline space interferometer concept involving formation flying of multiple spacecrafts holds great promise as future space missions for high-resolution imagery. A major challenge of obtaining high-quality interferometric synthesized images from long-baseline space interferometers is to accurately control these spacecraft and their optics payloads in the specified configuration. Our research focuses on the determination of the optical errors to achieve fine control of long-baseline space interferometers without resorting to additional sensing equipment. We present a suite of estimation tools that can effectively extract from the raw interferometric image relative x/y, piston translational and tip/tilt deviations at the exit pupil aperture. The use of these error estimates in achieving control of the interferometer elements is demonstrated using simulated as well as laboratory-collected interferometric stellar images.

Topography of the Martian Impact Crater Tooting

NASA Technical Reports Server (NTRS)

Mouginis-Mark, P. J.; Garbeil, H.; Boyce, J. M.

2009-01-01

Tooting crater is approx.29 km in diameter, is located at 23.4degN, 207.5degE, and is classified as a multi-layered ejecta crater [1]. Our mapping last year identified several challenges that can now be addressed with HiRISE and CTX images, but specifically the third dimension of units. To address the distribution of ponded sediments, lobate flows, and volatile-bearing units within the crater cavity, we have focused this year on creating digital elevation models (DEMs) for the crater and ejecta blanket from stereo CTX and HiRISE images. These DEMs have a spatial resolution of approx.50 m for CTX data, and 2 m for HiRISE data. Each DEM is referenced to all of the available individual MOLA data points within an image, which number approx.5,000 and 800 respectively for the two data types

Multi-channel automotive night vision system

NASA Astrophysics Data System (ADS)

Lu, Gang; Wang, Li-jun; Zhang, Yi

2013-09-01

A four-channel automotive night vision system is designed and developed .It is consist of the four active near-infrared cameras and an Mulit-channel image processing display unit,cameras were placed in the automobile front, left, right and rear of the system .The system uses near-infrared laser light source，the laser light beam is collimated, the light source contains a thermoelectric cooler (TEC),It can be synchronized with the camera focusing, also has an automatic light intensity adjustment, and thus can ensure the image quality. The principle of composition of the system is description in detail,on this basis, beam collimation,the LD driving and LD temperature control of near-infrared laser light source,four-channel image processing display are discussed.The system can be used in driver assistance, car BLIS, car parking assist system and car alarm system in day and night.

Orientation of airborne laser scanning point clouds with multi-view, multi-scale image blocks.

PubMed

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters.

Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks

PubMed Central

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters. PMID:22454569

Threshold multi-secret sharing scheme based on phase-shifting interferometry

NASA Astrophysics Data System (ADS)

Deng, Xiaopeng; Wen, Wei; Shi, Zhengang

2017-03-01

A threshold multi-secret sharing scheme is proposed based on phase-shifting interferometry. The K secret images to be shared are firstly encoded by using Fourier transformation, respectively. Then, these encoded images are shared into many shadow images based on recording principle of the phase-shifting interferometry. In the recovering stage, the secret images can be restored by combining any 2 K + 1 or more shadow images, while any 2 K or fewer shadow images cannot obtain any information about the secret images. As a result, a (2 K + 1 , N) threshold multi-secret sharing scheme can be implemented. Simulation results are presented to demonstrate the feasibility of the proposed method.

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multi-Image Registration for an Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn; Rahman, Zia-Ur; Jobson, Daniel; Woodell, Glenn

2002-01-01

An Enhanced Vision System (EVS) utilizing multi-sensor image fusion is currently under development at the NASA Langley Research Center. The EVS will provide enhanced images of the flight environment to assist pilots in poor visibility conditions. Multi-spectral images obtained from a short wave infrared (SWIR), a long wave infrared (LWIR), and a color visible band CCD camera, are enhanced and fused using the Retinex algorithm. The images from the different sensors do not have a uniform data structure: the three sensors not only operate at different wavelengths, but they also have different spatial resolutions, optical fields of view (FOV), and bore-sighting inaccuracies. Thus, in order to perform image fusion, the images must first be co-registered. Image registration is the task of aligning images taken at different times, from different sensors, or from different viewpoints, so that all corresponding points in the images match. In this paper, we present two methods for registering multiple multi-spectral images. The first method performs registration using sensor specifications to match the FOVs and resolutions directly through image resampling. In the second method, registration is obtained through geometric correction based on a spatial transformation defined by user selected control points and regression analysis.

Wavefront correction in two-photon microscopy with a multi-actuator adaptive lens.

PubMed

Bueno, Juan M; Skorsetz, Martin; Bonora, Stefano; Artal, Pablo

2018-05-28

A multi-actuator adaptive lens (AL) was incorporated into a multi-photon (MP) microscope to improve the quality of images of thick samples. Through a hill-climbing procedure the AL corrected for the specimen-induced aberrations enhancing MP images. The final images hardly differed when two different metrics were used, although the sets of Zernike coefficients were not identical. The optimized MP images acquired with the AL were also compared with those obtained with a liquid-crystal-on-silicon spatial light modulator. Results have shown that both devices lead to similar images, which corroborates the usefulness of this AL for MP imaging.

Dynamic performance of MEMS deformable mirrors for use in an active/adaptive two-photon microscope

NASA Astrophysics Data System (ADS)

Zhang, Christian C.; Foster, Warren B.; Downey, Ryan D.; Arrasmith, Christopher L.; Dickensheets, David L.

2016-03-01

Active optics can facilitate two-photon microscopic imaging deep in tissue. We are investigating fast focus control mirrors used in concert with an aberration correction mirror to control the axial position of focus and system aberrations dynamically during scanning. With an adaptive training step, sample-induced aberrations may be compensated as well. If sufficiently fast and precise, active optics may be able to compensate under-corrected imaging optics as well as sample aberrations to maintain diffraction-limited performance throughout the field of view. Toward this end we have measured a Boston Micromachines Corporation Multi-DM 140 element deformable mirror, and a Revibro Optics electrostatic 4-zone focus control mirror to characterize dynamic performance. Tests for the Multi-DM included both step response and sinusoidal frequency sweeps of specific Zernike modes. For the step response we measured 10%-90% rise times for the target Zernike amplitude, and wavefront rms error settling times. Frequency sweeps identified the 3dB bandwidth of the mirror when attempting to follow a sinusoidal amplitude trajectory for a specific Zernike mode. For five tested Zernike modes (defocus, spherical aberration, coma, astigmatism and trefoil) we find error settling times for mode amplitudes up to 400nm to be less than 52 us, and 3 dB frequencies range from 6.5 kHz to 10 kHz. The Revibro Optics mirror was tested for step response only, with error settling time of 80 μs for a large 3 um defocus step, and settling time of only 18 μs for a 400nm spherical aberration step. These response speeds are sufficient for intra-scan correction at scan rates typical of two-photon microscopy.

Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks.

PubMed

Dvornek, Nicha C; Ventola, Pamela; Pelphrey, Kevin A; Duncan, James S

2017-09-01

Functional magnetic resonance imaging (fMRI) has helped characterize the pathophysiology of autism spectrum disorders (ASD) and carries promise for producing objective biomarkers for ASD. Recent work has focused on deriving ASD biomarkers from resting-state functional connectivity measures. However, current efforts that have identified ASD with high accuracy were limited to homogeneous, small datasets, while classification results for heterogeneous, multi-site data have shown much lower accuracy. In this paper, we propose the use of recurrent neural networks with long short-term memory (LSTMs) for classification of individuals with ASD and typical controls directly from the resting-state fMRI time-series. We used the entire large, multi-site Autism Brain Imaging Data Exchange (ABIDE) I dataset for training and testing the LSTM models. Under a cross-validation framework, we achieved classification accuracy of 68.5%, which is 9% higher than previously reported methods that used fMRI data from the whole ABIDE cohort. Finally, we presented interpretation of the trained LSTM weights, which highlight potential functional networks and regions that are known to be implicated in ASD.

Informing Aerosol Transport Models With Satellite Multi-Angle Aerosol Measurements

NASA Technical Reports Server (NTRS)

Limbacher, J.; Patadia, F.; Petrenko, M.; Martin, M. Val; Chin, M.; Gaitley, B.; Garay, M.; Kalashnikova, O.; Nelson, D.; Scollo, S.

2011-01-01

As the aerosol products from the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) mature, we are placing greater focus on ways of using the aerosol amount and type data products, and aerosol plume heights, to constrain aerosol transport models. We have demonstrated the ability to map aerosol air-mass-types regionally, and have identified product upgrades required to apply them globally, including the need for a quality flag indicating the aerosol type information content, that varies depending upon retrieval conditions. We have shown that MISR aerosol type can distinguish smoke from dust, volcanic ash from sulfate and water particles, and can identify qualitative differences in mixtures of smoke, dust, and pollution aerosol components in urban settings. We demonstrated the use of stereo imaging to map smoke, dust, and volcanic effluent plume injection height, and the combination of MISR and MODIS aerosol optical depth maps to constrain wildfire smoke source strength. This talk will briefly highlight where we stand on these application, with emphasis on the steps we are taking toward applying the capabilities toward constraining aerosol transport models, planet-wide.

Micro-beam Laue alignment of multi-reflection Bragg coherent diffraction imaging measurements.

PubMed

Hofmann, Felix; Phillips, Nicholas W; Harder, Ross J; Liu, Wenjun; Clark, Jesse N; Robinson, Ian K; Abbey, Brian

2017-09-01

Multi-reflection Bragg coherent diffraction imaging has the potential to allow three-dimensional (3D) resolved measurements of the full lattice strain tensor in specific micro-crystals. Until now such measurements were hampered by the need for laborious, time-intensive alignment procedures. Here a different approach is demonstrated, using micro-beam Laue X-ray diffraction to first determine the lattice orientation of the micro-crystal. This information is then used to rapidly align coherent diffraction measurements of three or more reflections from the crystal. Based on these, 3D strain and stress fields in the crystal are successfully determined. This approach is demonstrated on a focused ion beam milled micro-crystal from which six reflections could be measured. Since information from more than three independent reflections is available, the reliability of the phases retrieved from the coherent diffraction data can be assessed. Our results show that rapid, reliable 3D coherent diffraction measurements of the full lattice strain tensor in specific micro-crystals are now feasible and can be successfully carried out even in heavily distorted samples.

Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks

PubMed Central

Dvornek, Nicha C.; Ventola, Pamela; Pelphrey, Kevin A.; Duncan, James S.

2017-01-01

Functional magnetic resonance imaging (fMRI) has helped characterize the pathophysiology of autism spectrum disorders (ASD) and carries promise for producing objective biomarkers for ASD. Recent work has focused on deriving ASD biomarkers from resting-state functional connectivity measures. However, current efforts that have identified ASD with high accuracy were limited to homogeneous, small datasets, while classification results for heterogeneous, multi-site data have shown much lower accuracy. In this paper, we propose the use of recurrent neural networks with long short-term memory (LSTMs) for classification of individuals with ASD and typical controls directly from the resting-state fMRI time-series. We used the entire large, multi-site Autism Brain Imaging Data Exchange (ABIDE) I dataset for training and testing the LSTM models. Under a cross-validation framework, we achieved classification accuracy of 68.5%, which is 9% higher than previously reported methods that used fMRI data from the whole ABIDE cohort. Finally, we presented interpretation of the trained LSTM weights, which highlight potential functional networks and regions that are known to be implicated in ASD. PMID:29104967

The iMars web-GIS - spatio-temporal data queries and single image web map services

NASA Astrophysics Data System (ADS)

Walter, S. H. G.; Steikert, R.; Schreiner, B.; Sidiropoulos, P.; Tao, Y.; Muller, J.-P.; Putry, A. R. D.; van Gasselt, S.

2017-09-01

We introduce a new approach for a system dedicated to planetary surface change detection by simultaneous visualisation of single-image time series in a multi-temporal context. In the context of the EU FP-7 iMars project we process and ingest vast amounts of automatically co-registered (ACRO) images. The base of the co-registration are the high precision HRSC multi-orbit quadrangle image mosaics, which are based on bundle-block-adjusted multi-orbit HRSC DTMs.

[Research progress of multi-model medical image fusion and recognition].

PubMed

Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

2013-10-01

Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

MMX-I: data-processing software for multimodal X-ray imaging and tomography

PubMed Central

Bergamaschi, Antoine; Medjoubi, Kadda; Messaoudi, Cédric; Marco, Sergio; Somogyi, Andrea

2016-01-01

A new multi-platform freeware has been developed for the processing and reconstruction of scanning multi-technique X-ray imaging and tomography datasets. The software platform aims to treat different scanning imaging techniques: X-ray fluorescence, phase, absorption and dark field and any of their combinations, thus providing an easy-to-use data processing tool for the X-ray imaging user community. A dedicated data input stream copes with the input and management of large datasets (several hundred GB) collected during a typical multi-technique fast scan at the Nanoscopium beamline and even on a standard PC. To the authors’ knowledge, this is the first software tool that aims at treating all of the modalities of scanning multi-technique imaging and tomography experiments. PMID:27140159

WE-H-209-00: Carson/Zagzebski Distinguished Lectureship: Image Guided Ultrasound Therapy

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

NONE

Focused ultrasound has been shown to be the only method that allows noninvasive thermal coagulation of tissues and recently this potential has been explored for image-guided drug delivery. In this presentation, the advances in ultrasound phased array technology for energy delivery, exposure monitoring and control will be discussed. Experimental results from novel multi-frequency transmit/receive arrays will be presented. In addition, the feasibility of fully electronically focused and steered high power arrays with many thousands of transducer elements will be discussed. Finally, some of the recent clinical and preclinical results for the treatment of brain disease will be reviewed. Learning Objectives:more » Introduce FUS therapy principles and modern techniques Discuss use of FUS for drug delivery Cover the technology required to deliver FUS and monitor therapy Present clinical examples of the uses of these techniques This research was supported by funding from The Canada Research Chair Program, Grants from CIHR and NIH (no. EB003268).; K. Hynynen, Canada Foundation for Innovation; Canadian Institutes of Health Research; Focused Ultrasound Surgery Foundation; Canada Research Chair Program; Natural Sciences and Engineering Research Council of Canada; Ontario Research Fund; National Institutes of Health; Canadian Cancer Society Research Institute; The Weston Brain Institute; Harmonic Medical; Focused Ultrasound Instruments.« less

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

Multi-spectral endogenous fluorescence imaging for bacterial differentiation

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Babayants, Margarita V.; Korotkov, Oleg V.; Kudrin, Konstantin G.; Rimskaya, Elena N.; Shikunova, Irina A.; Kurlov, Vladimir N.; Cherkasova, Olga P.; Komandin, Gennady A.; Reshetov, Igor V.; Zaytsev, Kirill I.

2017-07-01

In this paper, the multi-spectral endogenous fluorescence imaging was implemented for bacterial differentiation. The fluorescence imaging was performed using a digital camera equipped with a set of visual bandpass filters. Narrowband 365 nm ultraviolet radiation passed through a beam homogenizer was used to excite the sample fluorescence. In order to increase a signal-to-noise ratio and suppress a non-fluorescence background in images, the intensity of the UV excitation was modulated using a mechanical chopper. The principal components were introduced for differentiating the samples of bacteria based on the multi-spectral endogenous fluorescence images.

Rapid Multi-Tracer PET Tumor Imaging With F-FDG and Secondary Shorter-Lived Tracers.

PubMed

Black, Noel F; McJames, Scott; Kadrmas, Dan J

2009-10-01

Rapid multi-tracer PET, where two to three PET tracers are rapidly scanned with staggered injections, can recover certain imaging measures for each tracer based on differences in tracer kinetics and decay. We previously showed that single-tracer imaging measures can be recovered to a certain extent from rapid dual-tracer (62)Cu - PTSM (blood flow) + (62)Cu - ATSM (hypoxia) tumor imaging. In this work, the feasibility of rapidly imaging (18)F-FDG plus one or two of these shorter-lived secondary tracers was evaluated in the same tumor model. Dynamic PET imaging was performed in four dogs with pre-existing tumors, and the raw scan data was combined to emulate 60 minute long dual- and triple-tracer scans, using the single-tracer scans as gold standards. The multi-tracer data were processed for static (SUV) and kinetic (K(1), K(net)) endpoints for each tracer, followed by linear regression analysis of multi-tracer versus single-tracer results. Static and quantitative dynamic imaging measures of FDG were both accurately recovered from the multi-tracer scans, closely matching the single-tracer FDG standards (R > 0.99). Quantitative blood flow information, as measured by PTSM K(1) and SUV, was also accurately recovered from the multi-tracer scans (R = 0.97). Recovery of ATSM kinetic parameters proved more difficult, though the ATSM SUV was reasonably well recovered (R = 0.92). We conclude that certain additional information from one to two shorter-lived PET tracers may be measured in a rapid multi-tracer scan alongside FDG without compromising the assessment of glucose metabolism. Such additional and complementary information has the potential to improve tumor characterization in vivo, warranting further investigation of rapid multi-tracer techniques.

Rapid Multi-Tracer PET Tumor Imaging With 18F-FDG and Secondary Shorter-Lived Tracers

PubMed Central

Black, Noel F.; McJames, Scott; Kadrmas, Dan J.

2009-01-01

Rapid multi-tracer PET, where two to three PET tracers are rapidly scanned with staggered injections, can recover certain imaging measures for each tracer based on differences in tracer kinetics and decay. We previously showed that single-tracer imaging measures can be recovered to a certain extent from rapid dual-tracer 62Cu – PTSM (blood flow) + 62Cu — ATSM (hypoxia) tumor imaging. In this work, the feasibility of rapidly imaging 18F-FDG plus one or two of these shorter-lived secondary tracers was evaluated in the same tumor model. Dynamic PET imaging was performed in four dogs with pre-existing tumors, and the raw scan data was combined to emulate 60 minute long dual- and triple-tracer scans, using the single-tracer scans as gold standards. The multi-tracer data were processed for static (SUV) and kinetic (K1, Knet) endpoints for each tracer, followed by linear regression analysis of multi-tracer versus single-tracer results. Static and quantitative dynamic imaging measures of FDG were both accurately recovered from the multi-tracer scans, closely matching the single-tracer FDG standards (R > 0.99). Quantitative blood flow information, as measured by PTSM K1 and SUV, was also accurately recovered from the multi-tracer scans (R = 0.97). Recovery of ATSM kinetic parameters proved more difficult, though the ATSM SUV was reasonably well recovered (R = 0.92). We conclude that certain additional information from one to two shorter-lived PET tracers may be measured in a rapid multi-tracer scan alongside FDG without compromising the assessment of glucose metabolism. Such additional and complementary information has the potential to improve tumor characterization in vivo, warranting further investigation of rapid multi-tracer techniques. PMID:20046800

Segmentation of white rat sperm image

NASA Astrophysics Data System (ADS)

Bai, Weiguo; Liu, Jianguo; Chen, Guoyuan

2011-11-01

The segmentation of sperm image exerts a profound influence in the analysis of sperm morphology, which plays a significant role in the research of animals' infertility and reproduction. To overcome the microscope image's properties of low contrast and highly polluted noise, and to get better segmentation results of sperm image, this paper presents a multi-scale gradient operator combined with a multi-structuring element for the micro-spermatozoa image of white rat, as the multi-scale gradient operator can smooth the noise of an image, while the multi-structuring element can retain more shape details of the sperms. Then, we use the Otsu method to segment the modified gradient image whose gray scale processed is strong in sperms and weak in the background, converting it into a binary sperm image. As the obtained binary image owns impurities that are not similar with sperms in the shape, we choose a form factor to filter those objects whose form factor value is larger than the select critical value, and retain those objects whose not. And then, we can get the final binary image of the segmented sperms. The experiment shows this method's great advantage in the segmentation of the micro-spermatozoa image.

FPGA-based multi-channel fluorescence lifetime analysis of Fourier multiplexed frequency-sweeping lifetime imaging

PubMed Central

Zhao, Ming; Li, Yu; Peng, Leilei

2014-01-01

We report a fast non-iterative lifetime data analysis method for the Fourier multiplexed frequency-sweeping confocal FLIM (Fm-FLIM) system [ Opt. Express22, 10221 ( 2014)24921725]. The new method, named R-method, allows fast multi-channel lifetime image analysis in the system’s FPGA data processing board. Experimental tests proved that the performance of the R-method is equivalent to that of single-exponential iterative fitting, and its sensitivity is well suited for time-lapse FLIM-FRET imaging of live cells, for example cyclic adenosine monophosphate (cAMP) level imaging with GFP-Epac-mCherry sensors. With the R-method and its FPGA implementation, multi-channel lifetime images can now be generated in real time on the multi-channel frequency-sweeping FLIM system, and live readout of FRET sensors can be performed during time-lapse imaging. PMID:25321778

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

NASA Astrophysics Data System (ADS)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

In vivo optimisation study for multi-baseline MR-based thermometry in the context of hyperthermia using MR-guided high intensity focused ultrasound for head and neck applications.

PubMed

Pichardo, Samuel; Köhler, Max; Lee, Justin; Hynnyen, Kullervo

2014-12-01

In this in vivo study, the feasibility to perform hyperthermia treatments in the head and neck using magnetic resonance image-guided high intensity focused ultrasound (MRgHIFU) was established using a porcine acute model. Porcine specimens with a weight between 17 and 18 kg were treated in the omohyoid muscle in the neck. Hyperthermia was applied with a target temperature of 41 °C for 30 min using a Sonalleve MRgHIFU system. MR-based thermometry was calculated using water-proton resonance frequency shift and multi-baseline look-up tables indexed by peak-to-peak displacement (Dpp) measurements using a pencil-beam navigator. Three hyperthermia experiments were conducted at different Dpp values of 0.2, 1.0 and 3.0 mm. An optimisation study was carried out to establish the optimal parameters controlling the multi-baseline method that ensured a minimisation of spatial-average peak-to-peak temperature (TSA-pp) and temperature direct current bias (TSA-DC). The multi-baseline technique reduced considerably the noise on both TSA-pp and TSA-DC. The reduction of noise was more important when Dpp was higher. For Dpp = 3 mm the average (±standard deviation (SD)) of TSA-pp and TSA-DC was reduced from 4.5 (± 2.5) and 2.5 (±0.6) °C, respectively, to 0.8 (± 0.7) and 0.09 (± 0.2) °C. This in vivo study showed the level of noise in PRFS-based thermometry introduced by respiratory motion in the context of MRgHIFU hyperthermia treatment for head and neck and the feasibility of reducing this noise using a multi-baseline technique.

Enhanced Imaging of Specific Cell-Surface Glycosylation Based on Multi-FRET.

PubMed

Yuan, Baoyin; Chen, Yuanyuan; Sun, Yuqiong; Guo, Qiuping; Huang, Jin; Liu, Jianbo; Meng, Xiangxian; Yang, Xiaohai; Wen, Xiaohong; Li, Zenghui; Li, Lie; Wang, Kemin

2018-05-15

Cell-surface glycosylation contains abundant biological information that reflects cell physiological state, and it is of great value to image cell-surface glycosylation to elucidate its functions. Here we present a hybridization chain reaction (HCR)-based multifluorescence resonance energy transfer (multi-FRET) method for specific imaging of cell-surface glycosylation. By installing donors through metabolic glycan labeling and acceptors through aptamer-tethered nanoassemblies on the same glycoconjugate, intramolecular multi-FRET occurs due to near donor-acceptor distance. Benefiting from amplified effect and spatial flexibility of the HCR nanoassemblies, enhanced multi-FRET imaging of specific cell-surface glycosylation can be obtained. With this HCR-based multi-FRET method, we achieved obvious contrast in imaging of protein-specific GalNAcylation on 7211 cell surfaces. In addition, we demonstrated the general applicability of this method by visualizing the protein-specific sialylation on CEM cell surfaces. Furthermore, the expression changes of CEM cell-surface protein-specific sialylation under drug treatment was accurately monitored. This developed imaging method may provide a powerful tool in researching glycosylation functions, discovering biomarkers, and screening drugs.

Discriminative Multi-View Interactive Image Re-Ranking.

PubMed

Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

2017-07-01

Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

Analysis of Rapid Multi-Focal Zone ARFI Imaging

PubMed Central

Rosenzweig, Stephen; Palmeri, Mark; Nightingale, Kathryn

2015-01-01

Acoustic radiation force impulse (ARFI) imaging has shown promise for visualizing structure and pathology within multiple organs; however, because the contrast depends on the push beam excitation width, image quality suffers outside of the region of excitation. Multi-focal zone ARFI imaging has previously been used to extend the region of excitation (ROE), but the increased acquisition duration and acoustic exposure have limited its utility. Supersonic shear wave imaging has previously demonstrated that through technological improvements in ultrasound scanners and power supplies, it is possible to rapidly push at multiple locations prior to tracking displacements, facilitating extended depth of field shear wave sources. Similarly, ARFI imaging can utilize these same radiation force excitations to achieve tight pushing beams with a large depth of field. Finite element method simulations and experimental data are presented demonstrating that single- and rapid multi-focal zone ARFI have comparable image quality (less than 20% loss in contrast), but the multi-focal zone approach has an extended axial region of excitation. Additionally, as compared to single push sequences, the rapid multi-focal zone acquisitions improve the contrast to noise ratio by up to 40% in an example 4 mm diameter lesion. PMID:25643078

Subdiffractional focusing and guiding of polaritonic rays in a natural hyperbolic material

PubMed Central

Dai, S.; Ma, Q.; Andersen, T.; Mcleod, A. S.; Fei, Z.; Liu, M. K.; Wagner, M.; Watanabe, K.; Taniguchi, T.; Thiemens, M.; Keilmann, F.; Jarillo-Herrero, P.; Fogler, M. M.; Basov, D. N.

2015-01-01

Uniaxial materials whose axial and tangential permittivities have opposite signs are referred to as indefinite or hyperbolic media. In such materials, light propagation is unusual leading to novel and often non-intuitive optical phenomena. Here we report infrared nano-imaging experiments demonstrating that crystals of hexagonal boron nitride, a natural mid-infrared hyperbolic material, can act as a ‘hyper-focusing lens' and as a multi-mode waveguide. The lensing is manifested by subdiffractional focusing of phonon–polaritons launched by metallic disks underneath the hexagonal boron nitride crystal. The waveguiding is revealed through the modal analysis of the periodic patterns observed around such launchers and near the sample edges. Our work opens new opportunities for anisotropic layered insulators in infrared nanophotonics complementing and potentially surpassing concurrent artificial hyperbolic materials with lower losses and higher optical localization. PMID:25902364

Visible camera cryostat design and performance for the SuMIRe Prime Focus Spectrograph (PFS)

NASA Astrophysics Data System (ADS)

Smee, Stephen A.; Gunn, James E.; Golebiowski, Mirek; Hope, Stephen C.; Madec, Fabrice; Gabriel, Jean-Francois; Loomis, Craig; Le fur, Arnaud; Dohlen, Kjetil; Le Mignant, David; Barkhouser, Robert; Carr, Michael; Hart, Murdock; Tamura, Naoyuki; Shimono, Atsushi; Takato, Naruhisa

2016-08-01

We describe the design and performance of the SuMIRe Prime Focus Spectrograph (PFS) visible camera cryostats. SuMIRe PFS is a massively multi-plexed ground-based spectrograph consisting of four identical spectrograph modules, each receiving roughly 600 fibers from a 2394 fiber robotic positioner at the prime focus. Each spectrograph module has three channels covering wavelength ranges 380 nm - 640 nm, 640 nm - 955 nm, and 955 nm - 1.26 um, with the dispersed light being imaged in each channel by a f/1.07 vacuum Schmidt camera. The cameras are very large, having a clear aperture of 300 mm at the entrance window, and a mass of 280 kg. In this paper we describe the design of the visible camera cryostats and discuss various aspects of cryostat performance.

HCP: A Flexible CNN Framework for Multi-label Image Classification.

PubMed

Wei, Yunchao; Xia, Wei; Lin, Min; Huang, Junshi; Ni, Bingbing; Dong, Jian; Zhao, Yao; Yan, Shuicheng

2015-10-26

Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still remains an open problem, mainly due to the complex underlying object layouts and insufficient multi-label training images. In this work, we propose a flexible deep CNN infrastructure, called Hypotheses-CNN-Pooling (HCP), where an arbitrary number of object segment hypotheses are taken as the inputs, then a shared CNN is connected with each hypothesis, and finally the CNN output results from different hypotheses are aggregated with max pooling to produce the ultimate multi-label predictions. Some unique characteristics of this flexible deep CNN infrastructure include: 1) no ground-truth bounding box information is required for training; 2) the whole HCP infrastructure is robust to possibly noisy and/or redundant hypotheses; 3) the shared CNN is flexible and can be well pre-trained with a large-scale single-label image dataset, e.g., ImageNet; and 4) it may naturally output multi-label prediction results. Experimental results on Pascal VOC 2007 and VOC 2012 multi-label image datasets well demonstrate the superiority of the proposed HCP infrastructure over other state-of-the-arts. In particular, the mAP reaches 90.5% by HCP only and 93.2% after the fusion with our complementary result in [44] based on hand-crafted features on the VOC 2012 dataset.

Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens.

PubMed

Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N; Zawadzki, Robert J; Sarunic, Marinko V

2015-08-24

Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images.

Fiber-based three-dimensional multi-mode interference device as efficient power divider and vector curvature sensor

NASA Astrophysics Data System (ADS)

Zhang, Ziyang; Fiebrandt, Julia; Haynes, Dionne; Sun, Kai; Madhav, Kalaga; Stoll, Andreas; Makan, Kirill; Makan, Vadim; Roth, Martin

2018-03-01

Three-dimensional multi-mode interference devices are demonstrated using a single-mode fiber (SMF) center-spliced to a section of polygon-shaped core multimode fiber (MMF). This simple structure can effectively generate well-localized self-focusing spots that match to the layout of a chosen multi-core fiber (MCF) as a launcher device. An optimized hexagon-core MMF can provide efficient coupling from a SMF to a 7-core MCF with an insertion loss of 0.6 dB and a power imbalance of 0.5 dB, while a square-core MMF can form a self-imaging pattern with symmetrically distributed 2 × 2, 3 × 3 or 4 × 4 spots. These spots can be directly received by a two-dimensional detector array. The device can work as a vector curvature sensor by comparing the relative power among the spots with a resolution of ∼0.1° over a 1.8 mm-long MMF.

Multi-signal FIB/SEM tomography

NASA Astrophysics Data System (ADS)

Giannuzzi, Lucille A.

2012-06-01

Focused ion beam (FIB) milling coupled with scanning electron microscopy (SEM) on the same platform enables 3D microstructural analysis of structures using FIB for serial sectioning and SEM for imaging. Since FIB milling is a destructive technique, the acquisition of multiple signals from each slice is desirable. The feasibility of collecting both an inlens backscattered electron (BSE) signal and an inlens secondary electron (SE) simultaneously from a single scan of the electron beam from each FIB slice is demonstrated. The simultaneous acquisition of two different SE signals from two different detectors (inlens vs. Everhart-Thornley (ET) detector) is also possible. Obtaining multiple signals from each FIB slice with one scan increases the acquisition throughput. In addition, optimization of microstructural and morphological information from the target is achieved using multi-signals. Examples of multi-signal FIB/SEM tomography from a dental implant will be provided where both material contrast from the bone/ceramic coating/Ti substrate phases and porosity in the ceramic coating will be characterized.

Multiple speckle illumination for optical-resolution photoacoustic imaging

NASA Astrophysics Data System (ADS)

Poisson, Florian; Stasio, Nicolino; Moser, Christophe; Psaltis, Demetri; Bossy, Emmanuel

2017-03-01

Optical-resolution photoacoustic microscopy offers exquisite and specific contrast to optical absorption. Conventional approaches generally involves raster scanning a focused spot over the sample. Here, we demonstrate that a full-field illumination approach with multiple speckle illumination can also provide diffraction-limited optical-resolution photoacoustic images. Two different proof-of-concepts are demonstrated with micro-structured test samples. The first approach follows the principle of correlation/ghost imaging,1, 2 and is based on cross-correlating photoacoustic signals under multiple speckle illumination with known speckle patterns measured during a calibration step. The second approach is a speckle scanning microscopy technique, which adapts the technique proposed in fluorescence microscopy by Bertolotti and al.:3 in our work, spatially unresolved photoacoustic measurements are performed for various translations of unknown speckle patterns. A phase-retrieval algorithm is used to reconstruct the object from the knowledge of the modulus of its Fourier Transform yielded by the measurements. Because speckle patterns naturally appear in many various situations, including propagation through biological tissue or multi-mode fibers (for which focusing light is either very demanding if not impossible), speckle-illumination-based photoacoustic microscopy provides a powerful framework for the development of novel reconstruction approaches, well-suited to compressed sensing approaches.2

Instrumentation progress at the Giant Magellan Telescope project

NASA Astrophysics Data System (ADS)

Jacoby, George H.; Bernstein, R.; Bouchez, A.; Colless, M.; Crane, Jeff; DePoy, D.; Espeland, B.; Hare, Tyson; Jaffe, D.; Lawrence, J.; Marshall, J.; McGregor, P.; Shectman, Stephen; Sharp, R.; Szentgyorgyi, A.; Uomoto, Alan; Walls, B.

2016-08-01

Instrument development for the 24m Giant Magellan Telescope (GMT) is described: current activities, progress, status, and schedule. One instrument team has completed its preliminary design and is currently beginning its final design (GCLEF, an optical 350-950 nm, high-resolution and precision radial velocity echelle spectrograph). A second instrument team is in its conceptual design phase (GMACS, an optical 350-950 nm, medium resolution, 6-10 arcmin field, multi-object spectrograph). A third instrument team is midway through its preliminary design phase (GMTIFS, a near-IR YJHK diffraction-limited imager/integral-field-spectrograph), focused on risk reduction prototyping and design optimization. A fourth instrument team is currently fabricating the 5 silicon immersion gratings needed to begin its preliminary design phase (GMTNIRS, a simultaneous JHKLM high-resolution, AO-fed, echelle spectrograph). And, another instrument team is focusing on technical development and prototyping (MANIFEST, a facility robotic, multifiber feed, with a 20 arcmin field of view). In addition, a medium-field (6 arcmin, 0.06 arcsec/pix) optical imager will support telescope and AO commissioning activities, and will excel at narrow-band imaging. In the spirit of advancing synergies with other groups, the challenges of running an ELT instrument program and opportunities for cross-ELT collaborations are discussed.

Image charge multi-role and function detectors

NASA Astrophysics Data System (ADS)

Milnes, James; Lapington, Jon S.; Jagutzki, Ottmar; Howorth, Jon

2009-06-01

The image charge technique used with microchannel plate imaging tubes provides several operational and practical benefits by serving to isolate the electronic image readout from the detector. The simple dielectric interface between detector and readout provides vacuum isolation and no vacuum electrical feed-throughs are required. Since the readout is mechanically separate from the detector, an image tube of generic design can be simply optimised for various applications by attaching it to different readout devices and electronics. We present imaging performance results using a single image tube with a variety of readout devices suited to differing applications: (a) A four electrode charge division tetra wedge anode, optimised for best spatial resolution in photon counting mode. (b) A cross delay line anode, enabling higher count rate, and the possibility of discriminating near co-incident events, and an event timing resolution of better than 1 ns. (c) A multi-anode readout connected, either to a multi-channel oscilloscope for analogue measurements of fast optical pulses, or alternately, to a multi-channel time correlated single photon counting (TCSPC) card.

Hurricane Earl Multi-level Winds

NASA Image and Video Library

2010-09-02

NASA Multi-angle Imaging SpectroRadiometer instrument captured this image of Hurricane Earl Aug. 30, 2010. At this time, Hurricane Earl was a Category 3 storm. The hurricane eye is just visible on the right edge of the MISR image swath.

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

Intelligent multi-spectral IR image segmentation

NASA Astrophysics Data System (ADS)

Lu, Thomas; Luong, Andrew; Heim, Stephen; Patel, Maharshi; Chen, Kang; Chao, Tien-Hsin; Chow, Edward; Torres, Gilbert

2017-05-01

This article presents a neural network based multi-spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. This article compares the neural network based segmentation method to the Wavelet-threshold and Grab-Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-spectral IR images.

Two-dimensional multi-frequency imaging of a tumor inclusion in a homogeneous breast phantom using the harmonic motion Doppler imaging method.

PubMed

Tafreshi, Azadeh Kamali; Top, Can Barış; Gençer, Nevzat Güneri

2017-06-21

Harmonic motion microwave Doppler imaging (HMMDI) is a novel imaging modality for imaging the coupled electrical and mechanical properties of body tissues. In this paper, we used two experimental systems with different receiver configurations to obtain HMMDI images from tissue-mimicking phantoms at multiple vibration frequencies between 15 Hz and 35 Hz. In the first system, we used a spectrum analyzer to obtain the Doppler data in the frequency domain, while in the second one, we used a homodyne receiver that was designed to acquire time-domain data. The developed phantoms mimicked the elastic and dielectric properties of breast fat tissue, and included a [Formula: see text] mm cylindrical inclusion representing the tumor. A focused ultrasound probe was mechanically scanned in two lateral dimensions to obtain two-dimensional HMMDI images of the phantoms. The inclusions were resolved inside the fat phantom using both experimental setups. The image resolution increased with increasing vibration frequency. The designed receiver showed higher sensitivity than the spectrum analyzer measurements. The results also showed that time-domain data acquisition should be used to fully exploit the potential of the HMMDI method.

Two-dimensional multi-frequency imaging of a tumor inclusion in a homogeneous breast phantom using the harmonic motion Doppler imaging method

NASA Astrophysics Data System (ADS)

Kamali Tafreshi, Azadeh; Barış Top, Can; Güneri Gençer, Nevzat

2017-06-01

Harmonic motion microwave Doppler imaging (HMMDI) is a novel imaging modality for imaging the coupled electrical and mechanical properties of body tissues. In this paper, we used two experimental systems with different receiver configurations to obtain HMMDI images from tissue-mimicking phantoms at multiple vibration frequencies between 15 Hz and 35 Hz. In the first system, we used a spectrum analyzer to obtain the Doppler data in the frequency domain, while in the second one, we used a homodyne receiver that was designed to acquire time-domain data. The developed phantoms mimicked the elastic and dielectric properties of breast fat tissue, and included a 14~\\text{mm}× 9 mm cylindrical inclusion representing the tumor. A focused ultrasound probe was mechanically scanned in two lateral dimensions to obtain two-dimensional HMMDI images of the phantoms. The inclusions were resolved inside the fat phantom using both experimental setups. The image resolution increased with increasing vibration frequency. The designed receiver showed higher sensitivity than the spectrum analyzer measurements. The results also showed that time-domain data acquisition should be used to fully exploit the potential of the HMMDI method.

Single-event transient imaging with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor.

PubMed

Mochizuki, Futa; Kagawa, Keiichiro; Okihara, Shin-ichiro; Seo, Min-Woong; Zhang, Bo; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

2016-02-22

In the work described in this paper, an image reproduction scheme with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor was demonstrated. The sensor captures an object by compressing a sequence of images with focal-plane temporally random-coded shutters, followed by reconstruction of time-resolved images. Because signals are modulated pixel-by-pixel during capturing, the maximum frame rate is defined only by the charge transfer speed and can thus be higher than those of conventional ultra-high-speed cameras. The frame rate and optical efficiency of the multi-aperture scheme are discussed. To demonstrate the proposed imaging method, a 5×3 multi-aperture image sensor was fabricated. The average rising and falling times of the shutters were 1.53 ns and 1.69 ns, respectively. The maximum skew among the shutters was 3 ns. The sensor observed plasma emission by compressing it to 15 frames, and a series of 32 images at 200 Mfps was reconstructed. In the experiment, by correcting disparities and considering temporal pixel responses, artifacts in the reconstructed images were reduced. An improvement in PSNR from 25.8 dB to 30.8 dB was confirmed in simulations.

Structure Size Enhanced Histogram

NASA Astrophysics Data System (ADS)

Wesarg, Stefan; Kirschner, Matthias

Direct volume visualization requires the definition of transfer functions (TFs) for the assignment of opacity and color. Multi-dimensional TFs are based on at least two image properties, and are specified by means of 2D histograms. In this work we propose a new type of a 2D histogram which combines gray value with information about the size of the structures. This structure size enhanced (SSE) histogram is an intuitive approach for representing anatomical features. Clinicians — the users we are focusing on — are much more familiar with selecting features by their size than by their gradient magnitude value. As a proof of concept, we employ the SSE histogram for the definition of two-dimensional TFs for the visualization of 3D MRI and CT image data.

LUNA: low-flying UAV-based forest monitoring system

NASA Astrophysics Data System (ADS)

Keizer, Jan Jacob; Pereira, Luísa; Pinto, Glória; Alves, Artur; Barros, Antonio; Boogert, Frans-Joost; Cambra, Sílvia; de Jesus, Cláudia; Frankenbach, Silja; Mesquita, Raquel; Serôdio, João; Martins, José; Almendra, Ricardo

2015-04-01

The LUNA project is aiming to develop an information system for precision forestry and, in particular, the monitoring of eucalypt plantations that is first and foremost based on multi-spectral imagery acquired using low-flying uav's. The presentation will focus on the first phase of image acquisition, processing and analysis for a series of pot experiments addressing main threats for early-stage eucalypt plantations in Portugal, i.e. acute , chronic and cyclic hydric stress, nutrient stress, fungal infections and insect plague attacks. The imaging results will be compared with spectroscopic measurements as well as with eco-physiological and plant morphological measurements. Furthermore, the presentation will show initial results of the project's second phase, comprising field tests in existing eucalypt plantations in north-central Portugal.

An imaging informatics-based system to support animal studies for treating pain in spinal cord injury utilizing proton-beam radiotherapy

NASA Astrophysics Data System (ADS)

Verma, Sneha K.; Liu, Brent J.; Gridley, Daila S.; Mao, Xiao W.; Kotha, Nikhil

2015-03-01

In previous years we demonstrated an imaging informatics system designed to support multi-institutional research focused on the utilization of proton radiation for treating spinal cord injury (SCI)-related pain. This year we will demonstrate an update on the system with new modules added to perform image processing on evaluation data using immunhistochemistry methods to observe effects of proton therapy. The overarching goal of the research is to determine the effectiveness of using the proton beam for treating SCI-related neuropathic pain as an alternative to invasive surgical lesioning. The research is a joint collaboration between three major institutes, University of Southern California (data collection/integration and image analysis), Spinal Cord Institute VA Healthcare System, Long Beach (patient subject recruitment), and Loma Linda University and Medical Center (human and preclinical animal studies). The system that we are presenting is one of its kind which is capable of integrating a large range of data types, including text data, imaging data, DICOM objects from proton therapy treatment and pathological data. For multi-institutional studies, keeping data secure and integrated is very crucial. Different kinds of data within the study workflow are generated at different stages and different groups of people who process and analyze them in order to see hidden patterns within healthcare data from a broader perspective. The uniqueness of our system relies on the fact that it is platform independent and web-based which makes it very useful in such a large-scale study.

Sentinel 2B: the image quality performances at the beginning of the mission

NASA Astrophysics Data System (ADS)

Trémas, T.; Lonjou, V.; Dick, A.; Languille, F.; Gaudel-Vacaresse, A.; Vidal, B.; Revel, C.

2017-09-01

Launched on March 6th, 2017 from Kourou, Sentinel 2B has passed the phase of commissioning. Sentinel 2B will work together with Sentinel 2A launched in June 2015. The building and implementation of the satellite has been made under the responsibility of ESA, for the European Commission. The subset of Image Quality commissioning was delegated by ESA to CNES, referring to the experience of the French Space Agency on previous imagers. This phase lasted 4 months after the launch, a little longer than the formal In Orbit Calibration period conducted by ESA, some Image Quality parameters requiring several months before converging to a stable state. This paper presents the status of the satellite, from an IQ prospective, just before it entered its operational phase. The radiometric and geometric performances are listed, including: the absolute radiometric calibration, the equalization, the SNR, the absolute and the multi-temporal location accuracy. The performances of both satellites Sentinel and Sentinel 2B working together, will be addressed. A particular focus will be done on multi-temporal location performances, homogeneity of radiometric inter calibrations. The accomplishment of the Global Reference Image over Europe is evoked as well. The IQ commissioning phase ended on June 2017. From this date, the monitoring of IQ parameters is under the responsibility of ESA/ESRIN. Nevertheless, CNES continues to support ESA to survey the accuracy of S2A and S2B performances. The article ends by dealing with the prospective offered by the couple Sentinel 2A + Sentinel 2B.

Abdominal Organ Location, Morphology, and Rib Coverage for the 5(th), 50(th), and 95(th) Percentile Males and Females in the Supine and Seated Posture using Multi-Modality Imaging.

PubMed

Hayes, Ashley R; Gayzik, F Scott; Moreno, Daniel P; Martin, R Shayn; Stitzel, Joel D

The purpose of this study was to use data from a multi-modality image set of males and females representing the 5(th), 50(th), and 95(th) percentile (n=6) to examine abdominal organ location, morphology, and rib coverage variations between supine and seated postures. Medical images were acquired from volunteers in three image modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and upright MRI (uMRI). A manual and semi-automated segmentation method was used to acquire data and a registration technique was employed to conduct a comparative analysis between abdominal organs (liver, spleen, and kidneys) in both postures. Location of abdominal organs, defined by center of gravity movement, varied between postures and was found to be significant (p=0.002 to p=0.04) in multiple directions for each organ. In addition, morphology changes, including compression and expansion, were seen in each organ as a result of postural changes. Rib coverage, defined as the projected area of the ribs onto the abdominal organs, was measured in frontal, lateral, and posterior projections, and also varied between postures. A significant change in rib coverage between postures was measured for the spleen and right kidney (p=0.03 and p=0.02). The results indicate that posture affects the location, morphology and rib coverage area of abdominal organs and these implications should be noted in computational modeling efforts focused on a seated posture.

Automatic classification and detection of clinically relevant images for diabetic retinopathy

NASA Astrophysics Data System (ADS)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing

PubMed Central

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery. PMID:27711246

Robust and Accurate Image-Based Georeferencing Exploiting Relative Orientation Constraints

NASA Astrophysics Data System (ADS)

Cavegn, S.; Blaser, S.; Nebiker, S.; Haala, N.

2018-05-01

Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2 cm in an indoor area, and 3 cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2-3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

PubMed

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery.

Influence of sample preparation and reliability of automated numerical refocusing in stain-free analysis of dissected tissues with quantitative phase digital holographic microscopy

NASA Astrophysics Data System (ADS)

Kemper, Björn; Lenz, Philipp; Bettenworth, Dominik; Krausewitz, Philipp; Domagk, Dirk; Ketelhut, Steffi

2015-05-01

Digital holographic microscopy (DHM) has been demonstrated to be a versatile tool for high resolution non-destructive quantitative phase imaging of surfaces and multi-modal minimally-invasive monitoring of living cell cultures in-vitro. DHM provides quantitative monitoring of physiological processes through functional imaging and structural analysis which, for example, gives new insight into signalling of cellular water permeability and cell morphology changes due to toxins and infections. Also the analysis of dissected tissues quantitative DHM phase contrast prospects application fields by stain-free imaging and the quantification of tissue density changes. We show that DHM allows imaging of different tissue layers with high contrast in unstained tissue sections. As the investigation of fixed samples represents a very important application field in pathology, we also analyzed the influence of the sample preparation. The retrieved data demonstrate that the quality of quantitative DHM phase images of dissected tissues depends strongly on the fixing method and common staining agents. As in DHM the reconstruction is performed numerically, multi-focus imaging is achieved from a single digital hologram. Thus, we evaluated the automated refocussing feature of DHM for application on different types of dissected tissues and revealed that on moderately stained samples highly reproducible holographic autofocussing can be achieved. Finally, it is demonstrated that alterations of the spatial refractive index distribution in murine and human tissue samples represent a reliable absolute parameter that is related of different degrees of inflammation in experimental colitis and Crohn's disease. This paves the way towards the usage of DHM in digital pathology for automated histological examinations and further studies to elucidate the translational potential of quantitative phase microscopy for the clinical management of patients, e.g., with inflammatory bowel disease.

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

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.

Modeling of Focused Acoustic Field of a Concave Multi-annular Phased Array Using Spheroidal Beam Equation

NASA Astrophysics Data System (ADS)

Yu, Li-Li; Shou, Wen-De; Hui, Chun

2012-02-01

A theoretical model of focused acoustic field for a multi-annular phased array on concave spherical surface is proposed. In this model, the source boundary conditions of the spheroidal beam equation (SBE) for multi-annular phased elements are studied. Acoustic field calculated by the dynamic focusing model of SBE is compared with numerical results of the O'Neil and Khokhlov—Zabolotskaya—Kuznetsov (KZK) model, respectively. Axial dynamic focusing and the harmonic effects are presented. The results demonstrate that the dynamic focusing model of SBE is good valid for a concave multi-annular phased array with a large aperture angle in the linear or nonlinear field.

Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging.

PubMed

Shen, Kai; Lu, Hui; Baig, Sarfaraz; Wang, Michael R

2017-11-01

The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues.

[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.

Techniques and Tools for Estimating Ionospheric Effects in Interferometric and Polarimetric SAR Data

NASA Technical Reports Server (NTRS)

Rosen, P.; Lavalle, M.; Pi, X.; Buckley, S.; Szeliga, W.; Zebker, H.; Gurrola, E.

2011-01-01

The InSAR Scientific Computing Environment (ISCE) is a flexible, extensible software tool designed for the end-to-end processing and analysis of synthetic aperture radar data. ISCE inherits the core of the ROI_PAC interferometric tool, but contains improvements at all levels of the radar processing chain, including a modular and extensible architecture, new focusing approach, better geocoding of the data, handling of multi-polarization data, radiometric calibration, and estimation and correction of ionospheric effects. In this paper we describe the characteristics of ISCE with emphasis on the ionospheric modules. To detect ionospheric anomalies, ISCE implements the Faraday rotation method using quadpolarimetric images, and the split-spectrum technique using interferometric single-, dual- and quad-polarimetric images. The ability to generate co-registered time series of quad-polarimetric images makes ISCE also an ideal tool to be used for polarimetric-interferometric radar applications.

Yogurt's flexible image during its rise in popularity in post-war Belgium.

PubMed

Verriet, Jon; Leroy, Frédéric

2017-01-01

The consumption of yogurt in Western countries has risen for over a century, first slowly, then more rapidly. The purpose of the present study was to investigate this prolonged phase of growth, by examining the popularity and the projected image of yogurt. A particular focus was on the way these aspects were reflected in consumption patterns and media representations. The data showed how during its period of rapid popularization, yogurt's visibility in the media greatly increased. It was concluded that the product's image was highly flexible in post-war decades, evidenced by the multi-pronged approach taken by marketers. Yogurt was not only advertised as both tasty and healthy, but also as natural and convenient, a strategy that appears to have been informed by consumers' preferences and existing cultural values. This demonstrates how a high degree of product differentiation and diversification during a product's growth stage can result in a heterogeneous image, allowing for a broad range of marketing strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository

PubMed Central

Jernigan, Terry L.; Brown, Timothy T.; Hagler, Donald J.; Akshoomoff, Natacha; Bartsch, Hauke; Newman, Erik; Thompson, Wesley K.; Bloss, Cinnamon S.; Murray, Sarah S.; Schork, Nicholas; Kennedy, David N.; Kuperman, Joshua M.; McCabe, Connor; Chung, Yoonho; Libiger, Ondrej; Maddox, Melanie; Casey, B. J.; Chang, Linda; Ernst, Thomas M.; Frazier, Jean A.; Gruen, Jeffrey R.; Sowell, Elizabeth R.; Kenet, Tal; Kaufmann, Walter E.; Mostofsky, Stewart; Amaral, David G.; Dale, Anders M.

2015-01-01

The main objective of the multi-site Pediatric Imaging, Neurocognition, and Genetics (PING) study was to create a large repository of standardized measurements of behavioral and imaging phenotypes accompanied by whole genome genotyping acquired from typically-developing children varying widely in age (3 to 20 years). This cross-sectional study produced sharable data from 1493 children, and these data have been described in several publications focusing on brain and cognitive development. Researchers may gain access to these data by applying for an account on the PING Portal and filing a Data Use Agreement. Here we describe the recruiting and screening of the children and give a brief overview of the assessments performed, the imaging methods applied, the genetic data produced, and the numbers of cases for whom different data types are available. We also cite sources of more detailed information about the methods and data. Finally we describe the procedures for accessing the data and for using the PING data exploration portal. PMID:25937488

The Pediatric Imaging, Neurocognition, and Genetics (PING) Data Repository.

PubMed

Jernigan, Terry L; Brown, Timothy T; Hagler, Donald J; Akshoomoff, Natacha; Bartsch, Hauke; Newman, Erik; Thompson, Wesley K; Bloss, Cinnamon S; Murray, Sarah S; Schork, Nicholas; Kennedy, David N; Kuperman, Joshua M; McCabe, Connor; Chung, Yoonho; Libiger, Ondrej; Maddox, Melanie; Casey, B J; Chang, Linda; Ernst, Thomas M; Frazier, Jean A; Gruen, Jeffrey R; Sowell, Elizabeth R; Kenet, Tal; Kaufmann, Walter E; Mostofsky, Stewart; Amaral, David G; Dale, Anders M

2016-01-01

The main objective of the multi-site Pediatric Imaging, Neurocognition, and Genetics (PING) study was to create a large repository of standardized measurements of behavioral and imaging phenotypes accompanied by whole genome genotyping acquired from typically-developing children varying widely in age (3 to 20 years). This cross-sectional study produced sharable data from 1493 children, and these data have been described in several publications focusing on brain and cognitive development. Researchers may gain access to these data by applying for an account on the PING portal and filing a data use agreement. Here we describe the recruiting and screening of the children and give a brief overview of the assessments performed, the imaging methods applied, the genetic data produced, and the numbers of cases for whom different data types are available. We also cite sources of more detailed information about the methods and data. Finally we describe the procedures for accessing the data and for using the PING data exploration portal. Copyright © 2015 Elsevier Inc. All rights reserved.

Imaging of Stellar Surfacess Using Radio Facilities Including ALMA

NASA Astrophysics Data System (ADS)

O'Gorman, Eamon

2018-04-01

Until very recently, studies focusing on imaging stars at continuum radio wavelengths (here defined as submillimeter, millimeter, and centimeter wavelengths) has been scarce. These studies have mainly been carried out with the Very Large Array on a handful of evolved stars (i.e., Asymptotic Giant Branch and Red Supergiant stars) whereby their stellar disks have just about been spatially resolved. Some of these results however, have challenged our historical views on the nature of evolved star atmospheres. Now, the very long baselines of the Atacama Large Millimeter/submillimeter Array and the newly upgraded Karl G. Jansky Very Large Array provide a new opportunity to image these atmospheres at unprecedented spatial resolution and sensitivity across a much wider portion of the radio spectrum. In this talk I will first provide a history of stellar radio imaging and then discuss some recent exciting ALMA results. Finally I will present some brand new multi-wavelength ALMA and VLA results for the famous red supergiant Antares.

Laser scanning saturated structured illumination microscopy based on phase modulation

NASA Astrophysics Data System (ADS)

Huang, Yujia; Zhu, Dazhao; Jin, Luhong; Kuang, Cuifang; Xu, Yingke; Liu, Xu

2017-08-01

Wide-field saturated structured illumination microscopy has not been widely used due to the requirement of high laser power. We propose a novel method called laser scanning saturated structured illumination microscopy (LS-SSIM), which introduces high order of harmonics frequency and greatly reduces the required laser power for SSIM imaging. To accomplish that, an excitation PSF with two peaks is generated and scanned along different directions on the sample. Raw images are recorded cumulatively by a CCD detector and then reconstructed to form a high-resolution image with extended optical transfer function (OTF). Our theoretical analysis and simulation results show that LS-SSIM method reaches a resolution of 0.16 λ, equivalent to 2.7-fold resolution than conventional wide-field microscopy. In addition, LS-SSIM greatly improves the optical sectioning capability of conventional wide-field illumination system by diminishing our-of-focus light. Furthermore, this modality has the advantage of implementation in multi-photon microscopy with point scanning excitation to image samples in greater depths.

Use of focus groups in multi-site, multi-ethnic research projects for women's health: a Study of Women Across the Nation (swan) example.

PubMed

Kagawa-Singer, Marjorie; Adler, Shelley R; Mouton, Charles E; Ory, Marcia; Underwood, Lynne G

2009-01-01

To outline the lessons learned about the use of focus groups for the multisite, multi-ethnic longitudinal Study of Women Across the Nation (SWAN). Focus groups were designed to identify potential cultural differences in the incidence of symptoms and the meaning of transmenopause among women of diverse cultures, and to identify effective recruitment and retention strategies. Inductive and deductive focus groups for a multi-ethnic study. Seven community research sites across the United States conducted focus groups with six ethnic populations: African American, Chinese American, Japanese American, Mexican American, non-Hispanic white, and Puerto Rican. Community women from each ethnic group of color. A set of four/five focus groups in each ethnic group as the formative stage of the deductive, quantitative SWAN survey. Identification of methodological advantages and challenges to the successful implementation of formative focus groups in a multi-ethnic, multi-site population-based epidemiologic study. We provide recommendations from our lessons learned to improve the use of focus groups in future studies with multi-ethnic populations. Mixed methods using inductive and deductive approaches require the scientific integrity of both research paradigms. Adequate resources and time must be budgeted as essential parts of the overall strategy from the outset of study. Inductive cross-cultural researchers should be key team members, beginning with inception through each subsequent design phase to increase the scientific validity, generalizability, and comparability of the results across diverse ethnic groups, to assure the relevance, validity and applicability of the findings to the multicultural population of focus.

MISR Where on Earth…? Mystery Image Quiz #29

Atmospheric Science Data Center

2017-09-07

... ready for a challenge? Become a geographical detective and solve the latest mystery quiz from NASA’s MISR (Multi-angle Imaging ... ready for a challenge? Become a geographical detective and solve the latest mystery quiz from NASA’s MISR (Multi-angle Imaging ...

Optimization of Focused Ultrasound and Image Based Modeling in Image Guided Interventions

NASA Astrophysics Data System (ADS)

Almekkawy, Mohamed Khaled Ibrahim

Image-guided high intensity focused ultrasound (HIFU) is becoming increasingly accepted as a form of noninvasive ablative therapy for the treatment of prostate cancer, uterine fibroids and other tissue abnormalities. In principle, HIFU beams can be focused within small volumes which results in forming precise lesions within the target volume (e.g. tumor, atherosclerotic plaque) while sparing the intervening tissue. With this precision, HIFU offers the promise of noninvasive tumor therapy. The goal of this thesis is to develop an image-guidance mode with an interactive image-based computational modeling of tissue response to HIFU. This model could be used in treatment planning and post-treatment retrospective evaluation of treatment outcome(s). Within the context of treatment planning, the challenge of using HIFU to target tumors in organs partially obscured by the rib cage are addressed. Ribs distort HIFU beams in a manner that reduces the focusing gain at the target (tumor) and could cause a treatment-limiting collateral damage. We present a refocusing algorithms to efficiently steer higher power towards the target while limiting power deposition on the ribs, improving the safety and efficacy of tumor ablation. Our approach is based on an approximation of a non-convex to a convex optimization known as the semidefinite relaxation (SDR) technique. An important advantage of the SDR method over previously proposed optimization methods is the explicit control of the sidelobes in the focal plane. A finite-difference time domain (FDTD) heterogeneous propagation model of a 1-MHz concave phased array was used to model the acoustic propagation and temperature simulations in different tissues including ribs. The numerical methods developed for the refocusing problem are also used for retrospective analysis of targeting of atherosclerotic plaques using HIFU. Cases were simulated where seven adjacent HIFU shots (5000 W/cm2, 2 sec exposure time) were focused at the plaque tissue within the posterior wall of external femoral artery. After segmentation of the ultrasound image obtained for the treatment region in-vivo, we integrated this anatomical information into our simulation to account for different parameters that may be caused by these multi-region anatomical complexities. An FDTD heterogeneous model was used for both acoustic field and temperature computations. The acoustic field simulation considered a concave (40-mm radius of curvature) 32-element array operating at 3.5 MHz. To account for the blood flow in the vicinity of the target (plaque), we have used a modified transient bioheat transfer equation (tBHTE) with a convective term. The results from the numerical simulation were in good agreement with the thermal lesions identified by histological examination of the treated tissues. Within the context of accounting for the blood flow in tBHTE, the estimation of the displacement of tissue and blood motion are addressed. A new multi-dimensional speckle tracking method (MDST) utilizing the Riesz transform with subsample accuracy in all dimensions is described. Field II simulation of flow data in a channel is generated to provide a validation of the accuracy of the method. In addition, the new MDST method is applied to imaging data from the carotid artery of a healthy human volunteers. The results obtained show that using Riesz transform produces more robust estimation of the true displacement compared to previously published results.

MR-based keyhole SPECT for small animal imaging

PubMed Central

Lee, Keum Sil; Roeck, Werner W; Gullberg, Grant T; Nalcioglu, Orhan

2011-01-01

The rationale for multi-modality imaging is to integrate the strengths of different imaging technologies while reducing the shortcomings of an individual modality. The work presented here proposes a limited-field-of-view (LFOV) SPECT reconstruction technique that can be implemented on a multi-modality MR/SPECT system that can be used to obtain simultaneous MRI and SPECT images for small animal imaging. The reason for using a combined MR/SPECT system in this work is to eliminate any possible misregistration between the two sets of images when MR images are used as a priori information for SPECT. In nuclear imaging the target area is usually smaller than the entire object; thus, focusing the detector on the LFOV results in various advantages including the use of a smaller nuclear detector (less cost), smaller reconstruction region (faster reconstruction) and higher spatial resolution when used in conjunction with pinhole collimators with magnification. The MR/SPECT system can be used to choose a region of interest (ROI) for SPECT. A priori information obtained by the full field-of-view (FOV) MRI combined with the preliminary SPECT image can be used to reduce the dimensions of the SPECT reconstruction by limiting the computation to the smaller FOV while reducing artifacts resulting from the truncated data. Since the technique is based on SPECT imaging within the LFOV it will be called the keyhole SPECT (K-SPECT) method. At first MRI images of the entire object using a larger FOV are obtained to determine the location of the ROI covering the target organ. Once the ROI is determined, the animal is moved inside the radiofrequency (rf) coil to bring the target area inside the LFOV and then simultaneous MRI and SPECT are performed. The spatial resolution of the SPECT image is improved by employing a pinhole collimator with magnification >1 by having carefully calculated acceptance angles for each pinhole to avoid multiplexing. In our design all the pinholes are focused to the center of the LFOV. K-SPECT reconstruction is accomplished by generating an adaptive weighting matrix using a priori information obtained by simultaneously acquired MR images and the radioactivity distribution obtained from the ROI region of the SPECT image that is reconstructed without any a priori input. Preliminary results using simulations with numerical phantoms show that the image resolution of the SPECT image within the LFOV is improved while minimizing artifacts arising from parts of the object outside the LFOV due to the chosen magnification and the new reconstruction technique. The root-mean-square-error (RMSE) in the out-of-field artifacts was reduced by 60% for spherical phantoms using the K-SPECT reconstruction technique and by 48.5–52.6% for the heart in the case with the MOBY phantom. The KSPECT reconstruction technique significantly improved the spatial resolution and quantification while reducing artifacts from the contributions outside the LFOV as well as reducing the dimension of the reconstruction matrix. PMID:21220840

Dangerous gas detection based on infrared video

NASA Astrophysics Data System (ADS)

Ding, Kang; Hong, Hanyu; Huang, Likun

2018-03-01

As the gas leak infrared imaging detection technology has significant advantages of high efficiency and remote imaging detection, in order to enhance the detail perception of observers and equivalently improve the detection limit, we propose a new type of gas leak infrared image detection method, which combines background difference methods and multi-frame interval difference method. Compared to the traditional frame methods, the multi-frame interval difference method we proposed can extract a more complete target image. By fusing the background difference image and the multi-frame interval difference image, we can accumulate the information of infrared target image of the gas leak in many aspect. The experiment demonstrate that the completeness of the gas leakage trace information is enhanced significantly, and the real-time detection effect can be achieved.

Automated Geo/Co-Registration of Multi-Temporal Very-High-Resolution Imagery.

PubMed

Han, Youkyung; Oh, Jaehong

2018-05-17

For time-series analysis using very-high-resolution (VHR) multi-temporal satellite images, both accurate georegistration to the map coordinates and subpixel-level co-registration among the images should be conducted. However, applying well-known matching methods, such as scale-invariant feature transform and speeded up robust features for VHR multi-temporal images, has limitations. First, they cannot be used for matching an optical image to heterogeneous non-optical data for georegistration. Second, they produce a local misalignment induced by differences in acquisition conditions, such as acquisition platform stability, the sensor's off-nadir angle, and relief displacement of the considered scene. Therefore, this study addresses the problem by proposing an automated geo/co-registration framework for full-scene multi-temporal images acquired from a VHR optical satellite sensor. The proposed method comprises two primary steps: (1) a global georegistration process, followed by (2) a fine co-registration process. During the first step, two-dimensional multi-temporal satellite images are matched to three-dimensional topographic maps to assign the map coordinates. During the second step, a local analysis of registration noise pixels extracted between the multi-temporal images that have been mapped to the map coordinates is conducted to extract a large number of well-distributed corresponding points (CPs). The CPs are finally used to construct a non-rigid transformation function that enables minimization of the local misalignment existing among the images. Experiments conducted on five Kompsat-3 full scenes confirmed the effectiveness of the proposed framework, showing that the georegistration performance resulted in an approximately pixel-level accuracy for most of the scenes, and the co-registration performance further improved the results among all combinations of the georegistered Kompsat-3 image pairs by increasing the calculated cross-correlation values.

Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens

PubMed Central

Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N.; Zawadzki, Robert J.; Sarunic, Marinko V.

2015-01-01

Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images. PMID:26368169

The Effect of Sub-Aperture in DRIA Framework Applied on Multi-Aspect PolSAR Data

NASA Astrophysics Data System (ADS)

Xue, Feiteng; Yin, Qiang; Lin, Yun; Hong, Wen

2016-08-01

Multi-aspect SAR is a new remote sensing technology, achieves consecutive data in large look angle as platform moves. Multi- aspect observation brings higher resolution and SNR to SAR picture. Multi-aspect PolSAR data can increase the accuracy of target identify and classification because it contains the 3-D polarimetric scattering properties.DRIA(detecting-removing-incoherent-adding)framework is a multi-aspect PolSAR data processing method. In this method, the anisotropic and isotropic scattering is separated by maximum- likelihood ratio test. The anisotropic scattering is removed to gain a removal series. The isotropic scattering is incoherent added to gain a high resolution picture. The removal series describes the anisotropic scattering property and is used in features extraction and classification.This article focuses on the effect brought by difference of sub-aperture numbers in anisotropic scattering detection and removal. The more sub-apertures are, the less look angle is. Artificial target has anisotropic scattering because of Bragg resonances. The increase of sub-aperture number brings more accurate observation in azimuth though the quality of each single image may loss. The accuracy of classification in agricultural fields is affected by the anisotropic scattering brought by Bragg resonances. The size of the sub-aperture has a significant effect in the removal result of Bragg resonances.

Vehicle Re-Identification by Deep Hidden Multi-View Inference.

PubMed

Zhou, Yi; Liu, Li; Shao, Ling

2018-07-01

Vehicle re-identification (re-ID) is an area that has received far less attention in the computer vision community than the prevalent person re-ID. Possible reasons for this slow progress are the lack of appropriate research data and the special 3D structure of a vehicle. Previous works have generally focused on some specific views (e.g., front); but, these methods are less effective in realistic scenarios, where vehicles usually appear in arbitrary views to cameras. In this paper, we focus on the uncertainty of vehicle viewpoint in re-ID, proposing two end-to-end deep architectures: the Spatially Concatenated ConvNet and convolutional neural network (CNN)-LSTM bi-directional loop. Our models exploit the great advantages of the CNN and long short-term memory (LSTM) to learn transformations across different viewpoints of vehicles. Thus, a multi-view vehicle representation containing all viewpoints' information can be inferred from the only one input view, and then used for learning to measure distance. To verify our models, we also introduce a Toy Car RE-ID data set with images from multiple viewpoints of 200 vehicles. We evaluate our proposed methods on the Toy Car RE-ID data set and the public Multi-View Car, VehicleID, and VeRi data sets. Experimental results illustrate that our models achieve consistent improvements over the state-of-the-art vehicle re-ID approaches.

Strategic planning for radiology: opening an outpatient diagnostic imaging center.

PubMed

Leepson, Evan

2003-01-01

Launching a new diagnostic imaging center involves very specific requirements and roadmaps, including five major areas of change that have a direct impact on planning: Imaging and communication technology Finances and reimbursement Ownership structure of imaging entities Critical workforce shortages Imaging is moving outside radiology First, planning must focus on the strategic level of any organization, whether it is a multi-national corporation or a six-person radiology group. Think of all organizations as a triangle with three horizontal levels: strategic, managerial and operational. The strategic level of decision-making is at the top of the triangle, and here is where planning must take place. For strategic planning to work, there must be focused time and energy spent on this activity, usually away from the reading room and imaging center. There are five planning strategies, which must have the explicit goal of developing and growing the imaging center. The five strategies are: Clinical and quality issues, Governance and administration, Technology, Relationships, Marketing and business development. The best way to plan and implement these strategies is to create work groups of radiologists, technologists, and administrative and support staff. Once the group agrees on the strategy and tactic, it takes responsibility for implementation. Embarking on the launch of a new outpatient diagnostic imaging center is no small undertaking, and anyone who has struggled with such an endeavor can readily attest to the associated challenges and benefits. Success depends on many things, and one of the most important factors relates to the amount of time and the quality of effort spent on strategic planning at the outset. Neglecting or skimping on this phase may lead to unforeseen obstacles that could potentially derail the project.

Multi-Wave and Hybrid Imaging Techniques: A New Direction for Nondestructive Testing and Structural Health Monitoring

PubMed Central

Cheng, Yuhua; Deng, Yiming; Cao, Jing; Xiong, Xin; Bai, Libing; Li, Zhaojun

2013-01-01

In this article, the state-of-the-art multi-wave and hybrid imaging techniques in the field of nondestructive evaluation and structural health monitoring were comprehensively reviewed. A new direction for assessment and health monitoring of various structures by capitalizing the advantages of those imaging methods was discussed. Although sharing similar system configurations, the imaging physics and principles of multi-wave phenomena and hybrid imaging methods are inherently different. After a brief introduction of nondestructive evaluation (NDE), structure health monitoring (SHM) and their related challenges, several recent advances that have significantly extended imaging methods from laboratory development into practical applications were summarized, followed by conclusions and discussion on future directions. PMID:24287536

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

Imaging properties and its improvements of scanning/imaging x-ray microscope

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

Takeuchi, Akihisa, E-mail: take@spring8.or.jp; Uesugi, Kentaro; Suzuki, Yoshio

A scanning / imaging X-ray microscope (SIXM) system has been developed at SPring-8. The SIXM consists of a scanning X-ray microscope with a one-dimensional (1D) X-ray focusing device and an imaging (full-field) X-ray microscope with a 1D X-ray objective. The motivation of the SIXM system is to realize a quantitative and highly-sensitive multimodal 3D X-ray tomography by taking advantages of both the scanning X-ray microscope using multi-pixel detector and the imaging X-ray microscope. Data acquisition process of a 2D image is completely different between in the horizontal direction and in the vertical direction; a 1D signal is obtained with themore » linear-scanning while the other dimensional signal is obtained with the imaging optics. Such condition have caused a serious problem on the imaging properties that the imaging quality in the vertical direction has been much worse than that in the horizontal direction. In this paper, two approaches to solve this problem will be presented. One is introducing a Fourier transform method for phase retrieval from one phase derivative image, and the other to develop and employ a 1D diffuser to produce an asymmetrical coherent illumination.« less

Post-processing of adaptive optics images based on frame selection and multi-frame blind deconvolution

NASA Astrophysics Data System (ADS)

Tian, Yu; Rao, Changhui; Wei, Kai

2008-07-01

The adaptive optics can only partially compensate the image blurred by atmospheric turbulence due to the observing condition and hardware restriction. A post-processing method based on frame selection and multi-frames blind deconvolution to improve images partially corrected by adaptive optics is proposed. The appropriate frames which are suitable for blind deconvolution from the recorded AO close-loop frames series are selected by the frame selection technique and then do the multi-frame blind deconvolution. There is no priori knowledge except for the positive constraint in blind deconvolution. It is benefit for the use of multi-frame images to improve the stability and convergence of the blind deconvolution algorithm. The method had been applied in the image restoration of celestial bodies which were observed by 1.2m telescope equipped with 61-element adaptive optical system at Yunnan Observatory. The results show that the method can effectively improve the images partially corrected by adaptive optics.

3D reconstruction from multi-view VHR-satellite images in MicMac

NASA Astrophysics Data System (ADS)

Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur

2018-05-01

This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

Design of a multi-spectral imager built using the compressive sensing single-pixel camera architecture

NASA Astrophysics Data System (ADS)

McMackin, Lenore; Herman, Matthew A.; Weston, Tyler

2016-02-01

We present the design of a multi-spectral imager built using the architecture of the single-pixel camera. The architecture is enabled by the novel sampling theory of compressive sensing implemented optically using the Texas Instruments DLP™ micro-mirror array. The array not only implements spatial modulation necessary for compressive imaging but also provides unique diffractive spectral features that result in a multi-spectral, high-spatial resolution imager design. The new camera design provides multi-spectral imagery in a wavelength range that extends from the visible to the shortwave infrared without reduction in spatial resolution. In addition to the compressive imaging spectrometer design, we present a diffractive model of the architecture that allows us to predict a variety of detailed functional spatial and spectral design features. We present modeling results, architectural design and experimental results that prove the concept.

Low cost light-sheet microscopy for whole brain imaging

NASA Astrophysics Data System (ADS)

Kumar, Manish; Nasenbeny, Jordan; Kozorovitskiy, Yevgenia

2018-02-01

Light-sheet microscopy has evolved as an indispensable tool in imaging biological samples. It can image 3D samples at fast speed, with high-resolution optical sectioning, and with reduced photobleaching effects. These properties make light-sheet microscopy ideal for imaging fluorophores in a variety of biological samples and organisms, e.g. zebrafish, drosophila, cleared mouse brains, etc. While most commercial turnkey light-sheet systems are expensive, the existing lower cost implementations, e.g. OpenSPIM, are focused on achieving high-resolution imaging of small samples or organisms like zebrafish. In this work, we substantially reduce the cost of light-sheet microscope system while targeting to image much larger samples, i.e. cleared mouse brains, at single-cell resolution. The expensive components of a lightsheet system - excitation laser, water-immersion objectives, and translation stage - are replaced with an incoherent laser diode, dry objectives, and a custom-built Arduino-controlled translation stage. A low-cost CUBIC protocol is used to clear fixed mouse brain samples. The open-source platforms of μManager and Fiji support image acquisition, processing, and visualization. Our system can easily be extended to multi-color light-sheet microscopy.

On-site Rapid Diagnosis of Intracranial Hematoma using Portable Multi-slice Microwave Imaging System.

PubMed

Mobashsher, Ahmed Toaha; Abbosh, A M

2016-11-29

Rapid, on-the-spot diagnostic and monitoring systems are vital for the survival of patients with intracranial hematoma, as their conditions drastically deteriorate with time. To address the limited accessibility, high costs and static structure of currently used MRI and CT scanners, a portable non-invasive multi-slice microwave imaging system is presented for accurate 3D localization of hematoma inside human head. This diagnostic system provides fast data acquisition and imaging compared to the existing systems by means of a compact array of low-profile, unidirectional antennas with wideband operation. The 3D printed low-cost and portable system can be installed in an ambulance for rapid on-site diagnosis by paramedics. In this paper, the multi-slice head imaging system's operating principle is numerically analysed and experimentally validated on realistic head phantoms. Quantitative analyses demonstrate that the multi-slice head imaging system is able to generate better quality reconstructed images providing 70% higher average signal to clutter ratio, 25% enhanced maximum signal to clutter ratio and with around 60% hematoma target localization compared to the previous head imaging systems. Nevertheless, numerical and experimental results demonstrate that previous reported 2D imaging systems are vulnerable to localization error, which is overcome in the presented multi-slice 3D imaging system. The non-ionizing system, which uses safe levels of very low microwave power, is also tested on human subjects. Results of realistic phantom and subjects demonstrate the feasibility of the system in future preclinical trials.

Converting Multi-Shell and Diffusion Spectrum Imaging to High Angular Resolution Diffusion Imaging

PubMed Central

Yeh, Fang-Cheng; Verstynen, Timothy D.

2016-01-01

Multi-shell and diffusion spectrum imaging (DSI) are becoming increasingly popular methods of acquiring diffusion MRI data in a research context. However, single-shell acquisitions, such as diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), still remain the most common acquisition schemes in practice. Here we tested whether multi-shell and DSI data have conversion flexibility to be interpolated into corresponding HARDI data. We acquired multi-shell and DSI data on both a phantom and in vivo human tissue and converted them to HARDI. The correlation and difference between their diffusion signals, anisotropy values, diffusivity measurements, fiber orientations, connectivity matrices, and network measures were examined. Our analysis result showed that the diffusion signals, anisotropy, diffusivity, and connectivity matrix of the HARDI converted from multi-shell and DSI were highly correlated with those of the HARDI acquired on the MR scanner, with correlation coefficients around 0.8~0.9. The average angular error between converted and original HARDI was 20.7° at voxels with signal-to-noise ratios greater than 5. The network topology measures had less than 2% difference, whereas the average nodal measures had a percentage difference around 4~7%. In general, multi-shell and DSI acquisitions can be converted to their corresponding single-shell HARDI with high fidelity. This supports multi-shell and DSI acquisitions over HARDI acquisition as the scheme of choice for diffusion acquisitions. PMID:27683539

The Performance Analysis Based on SAR Sample Covariance Matrix

PubMed Central

Erten, Esra

2012-01-01

Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given. PMID:22736976

Generalization of the Lyot filter and its application to snapshot spectral imaging.

PubMed

Gorman, Alistair; Fletcher-Holmes, David William; Harvey, Andrew Robert

2010-03-15

A snapshot multi-spectral imaging technique is described which employs multiple cascaded birefringent interferometers to simultaneously spectrally filter and demultiplex multiple spectral images onto a single detector array. Spectral images are recorded directly without the need for inversion and without rejection of light and so the technique offers the potential for high signal-to-noise ratio. An example of an eight-band multi-spectral movie sequence is presented; we believe this is the first such demonstration of a technique able to record multi-spectral movie sequences without the need for computer reconstruction.

High flux solar energy transformation

DOEpatents

Winston, R.; Gleckman, P.L.; O'Gallagher, J.J.

1991-04-09

Disclosed are multi-stage systems for high flux transformation of solar energy allowing for uniform solar intensification by a factor of 60,000 suns or more. Preferred systems employ a focusing mirror as a primary concentrative device and a non-imaging concentrator as a secondary concentrative device with concentrative capacities of primary and secondary stages selected to provide for net solar flux intensification of greater than 2000 over 95 percent of the concentration area. Systems of the invention are readily applied as energy sources for laser pumping and in other photothermal energy utilization processes. 7 figures.

High flux solar energy transformation

DOEpatents

Winston, Roland; Gleckman, Philip L.; O'Gallagher, Joseph J.

1991-04-09

Disclosed are multi-stage systems for high flux transformation of solar energy allowing for uniform solar intensification by a factor of 60,000 suns or more. Preferred systems employ a focusing mirror as a primary concentrative device and a non-imaging concentrator as a secondary concentrative device with concentrative capacities of primary and secondary stages selected to provide for net solar flux intensification of greater than 2000 over 95 percent of the concentration area. Systems of the invention are readily applied as energy sources for laser pumping and in other photothermal energy utilization processes.

Earth Science

NASA Image and Video Library

1996-01-31

The Near Earth Asteroid Rendezvous (NEAR) spacecraft embarks on a journey that will culminate in a close encounter with an asteroid. The launch of NEAR inaugurates NASA's irnovative Discovery program of small-scale planetary missions with rapid, lower-cost development cycles and focused science objectives. NEAR will rendezvous in 1999 with the asteroid 433 Eros to begin the first long-term, close-up look at an asteroid's surface composition and physical properties. NEAR's science payload includes an x-ray/gamma ray spectrometer, an near-infrared spectrograph, a laser rangefinder, a magnetometer, a radio science experiment and a multi-spectral imager.

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

PubMed

Wang, Shuo; Zhou, Mu; Liu, Zaiyi; Liu, Zhenyu; Gu, Dongsheng; Zang, Yali; Dong, Di; Gevaert, Olivier; Tian, Jie

2017-08-01

Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and their surroundings make it difficult for robust nodule segmentation. In this study, we propose a data-driven model, termed the Central Focused Convolutional Neural Networks (CF-CNN), to segment lung nodules from heterogeneous CT images. Our approach combines two key insights: 1) the proposed model captures a diverse set of nodule-sensitive features from both 3-D and 2-D CT images simultaneously; 2) when classifying an image voxel, the effects of its neighbor voxels can vary according to their spatial locations. We describe this phenomenon by proposing a novel central pooling layer retaining much information on voxel patch center, followed by a multi-scale patch learning strategy. Moreover, we design a weighted sampling to facilitate the model training, where training samples are selected according to their degree of segmentation difficulty. The proposed method has been extensively evaluated on the public LIDC dataset including 893 nodules and an independent dataset with 74 nodules from Guangdong General Hospital (GDGH). We showed that CF-CNN achieved superior segmentation performance with average dice scores of 82.15% and 80.02% for the two datasets respectively. Moreover, we compared our results with the inter-radiologists consistency on LIDC dataset, showing a difference in average dice score of only 1.98%. Copyright © 2017. Published by Elsevier B.V.

BreedVision--a multi-sensor platform for non-destructive field-based phenotyping in plant breeding.

PubMed

Busemeyer, Lucas; Mentrup, Daniel; Möller, Kim; Wunder, Erik; Alheit, Katharina; Hahn, Volker; Maurer, Hans Peter; Reif, Jochen C; Würschum, Tobias; Müller, Joachim; Rahe, Florian; Ruckelshausen, Arno

2013-02-27

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies.

BreedVision — A Multi-Sensor Platform for Non-Destructive Field-Based Phenotyping in Plant Breeding

PubMed Central

Busemeyer, Lucas; Mentrup, Daniel; Möller, Kim; Wunder, Erik; Alheit, Katharina; Hahn, Volker; Maurer, Hans Peter; Reif, Jochen C.; Würschum, Tobias; Müller, Joachim; Rahe, Florian; Ruckelshausen, Arno

2013-01-01

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies. PMID:23447014

Digital liver biopsy: Bio-imaging of fatty liver for translational and clinical research.

PubMed

Mancini, Marcello; Summers, Paul; Faita, Francesco; Brunetto, Maurizia R; Callea, Francesco; De Nicola, Andrea; Di Lascio, Nicole; Farinati, Fabio; Gastaldelli, Amalia; Gridelli, Bruno; Mirabelli, Peppino; Neri, Emanuele; Salvadori, Piero A; Rebelos, Eleni; Tiribelli, Claudio; Valenti, Luca; Salvatore, Marco; Bonino, Ferruccio

2018-02-27

The rapidly growing field of functional, molecular and structural bio-imaging is providing an extraordinary new opportunity to overcome the limits of invasive liver biopsy and introduce a "digital biopsy" for in vivo study of liver pathophysiology. To foster the application of bio-imaging in clinical and translational research, there is a need to standardize the methods of both acquisition and the storage of the bio-images of the liver. It can be hoped that the combination of digital, liquid and histologic liver biopsies will provide an innovative synergistic tri-dimensional approach to identifying new aetiologies, diagnostic and prognostic biomarkers and therapeutic targets for the optimization of personalized therapy of liver diseases and liver cancer. A group of experts of different disciplines (Special Interest Group for Personalized Hepatology of the Italian Association for the Study of the Liver, Institute for Biostructures and Bio-imaging of the National Research Council and Bio-banking and Biomolecular Resources Research Infrastructure) discussed criteria, methods and guidelines for facilitating the requisite application of data collection. This manuscript provides a multi-Author review of the issue with special focus on fatty liver.

Cardiac Sarcoidosis: Clinical Manifestations, Imaging Characteristics, and Therapeutic Approach

PubMed Central

Houston, Brian A; Mukherjee, Monica

2014-01-01

Sarcoidosis is a multi-system disease pathologically characterized by the accumulation of T-lymphocytes and mononuclear phagocytes into the sine qua non pathologic structure of the noncaseating granuloma. Cardiac involvement remains a key source of morbidity and mortality in sarcoidosis. Definitive diagnosis of cardiac sarcoidosis, particularly early enough in the disease course to provide maximal therapeutic impact, has proven a particularly difficult challenge. However, major advancements in imaging techniques have been made in the last decade. Advancements in imaging modalities including echocardiography, nuclear spectroscopy, positron emission tomography, and magnetic resonance imaging all have improved our ability to diagnose cardiac sarcoidosis, and in many cases to provide a more accurate prognosis and thus targeted therapy. Likewise, therapy for cardiac sarcoidosis is beginning to advance past a “steroids-only” approach, as novel immunosuppressant agents provide effective steroid-sparing options. The following focused review will provide a brief discussion of the epidemiology and clinical presentation of cardiac sarcoidosis followed by a discussion of up-to-date imaging modalities employed in its assessment and therapeutic approaches. PMID:25452702

Multi exposure image fusion algorithm based on YCbCr space

NASA Astrophysics Data System (ADS)

Yang, T. T.; Fang, P. Y.

2018-05-01

To solve the problem that scene details and visual effects are difficult to be optimized in high dynamic image synthesis, we proposes a multi exposure image fusion algorithm for processing low dynamic range images in YCbCr space, and weighted blending of luminance and chromatic aberration components respectively. The experimental results show that the method can retain color effect of the fused image while balancing details of the bright and dark regions of the high dynamic image.

Engineering of multi-segmented light tunnel and flattop focus with designed axial lengths and gaps

NASA Astrophysics Data System (ADS)

Yu, Yanzhong; Huang, Han; Zhou, Mianmian; Zhan, Qiwen

2018-01-01

Based on the radiation pattern from a sectional-uniform line source antenna, a three-dimensional (3D) focus engineering technique for the creation of multi-segmented light tunnel and flattop focus with designed axial lengths and gaps is proposed. Under a 4Pi focusing system, the fields radiated from sectional-uniform magnetic and electromagnetic current line source antennas are employed to generate multi-segmented optical tube and flattop focus, respectively. Numerical results demonstrate that the produced light tube and flattop focus remain homogeneous along the optical axis; and their lengths of the nth segment and the nth gap between consecutive segments can be easily adjusted and only depend on the sizes of the nth section and the nth blanking between adjacent sectional antennas. The optical tube is a pure azimuthally polarized field but for the flattop focus the longitudinal polarization is dominant on the optical axis. To obtain the required pupil plane illumination for constructing the above focal field with prescribed characteristics, the inverse problem of the antenna radiation field is solved. These peculiar focusing fields might find potential applications in multi-particle acceleration, multi-particle trapping and manipulation.

Image recognition on raw and processed potato detection: a review

NASA Astrophysics Data System (ADS)

Qi, Yan-nan; Lü, Cheng-xu; Zhang, Jun-ning; Li, Ya-shuo; Zeng, Zhen; Mao, Wen-hua; Jiang, Han-lu; Yang, Bing-nan

2018-02-01

Objective: Chinese potato staple food strategy clearly pointed out the need to improve potato processing, while the bottleneck of this strategy is technology and equipment of selection of appropriate raw and processed potato. The purpose of this paper is to summarize the advanced raw and processed potato detection methods. Method: According to consult research literatures in the field of image recognition based potato quality detection, including the shape, weight, mechanical damage, germination, greening, black heart, scab potato etc., the development and direction of this field were summarized in this paper. Result: In order to obtain whole potato surface information, the hardware was built by the synchronous of image sensor and conveyor belt to achieve multi-angle images of a single potato. Researches on image recognition of potato shape are popular and mature, including qualitative discrimination on abnormal and sound potato, and even round and oval potato, with the recognition accuracy of more than 83%. Weight is an important indicator for potato grading, and the image classification accuracy presents more than 93%. The image recognition of potato mechanical damage focuses on qualitative identification, with the main affecting factors of damage shape and damage time. The image recognition of potato germination usually uses potato surface image and edge germination point. Both of the qualitative and quantitative detection of green potato have been researched, currently scab and blackheart image recognition need to be operated using the stable detection environment or specific device. The image recognition of processed potato mainly focuses on potato chips, slices and fries, etc. Conclusion: image recognition as a food rapid detection tool have been widely researched on the area of raw and processed potato quality analyses, its technique and equipment have the potential for commercialization in short term, to meet to the strategy demand of development potato as staple food in China.

Using consumer-grade devices for multi-imager non-contact imaging photoplethysmography

NASA Astrophysics Data System (ADS)

Blackford, Ethan B.; Estepp, Justin R.

2017-02-01

Imaging photoplethysmography is a technique through which the morphology of the blood volume pulse can be obtained through non-contact video recordings of exposed skin with superficial vasculature. The acceptance of such a convenient modality for use in everyday applications may well depend upon the availability of consumer-grade imagers that facilitate ease-of-adoption. Multiple imagers have been used previously in concept demonstrations, showing improvements in quality of the extracted blood volume pulse signal. However, the use of multi-imager sensors requires synchronization of the frame exposures between the individual imagers, a capability that has only recently been available without creating custom solutions. In this work, we consider the use of multiple, commercially-available, synchronous imagers for use in imaging photoplethysmography. A commercially-available solution for adopting multi-imager synchronization was analyzed for 21 stationary, seated participants while ground-truth physiological signals were simultaneously measured. A total of three imagers were used, facilitating a comparison between fused data from all three imagers versus data from the single, central imager in the array. The within-subjects design included analyses of pulse rate and pulse signal-to-noise ratio. Using the fused data from the triple-imager array, mean absolute error in pulse rate measurement was reduced to 3.8 as compared to 7.4 beats per minute with the single imager. While this represents an overall improvement in the multi-imager case, it is also noted that these errors are substantially higher than those obtained in comparable studies. We further discuss these results and their implications for using readily-available commercial imaging solutions for imaging photoplethysmography applications.

A 3D Freehand Ultrasound System for Multi-view Reconstructions from Sparse 2D Scanning Planes

PubMed Central

2011-01-01

Background A significant limitation of existing 3D ultrasound systems comes from the fact that the majority of them work with fixed acquisition geometries. As a result, the users have very limited control over the geometry of the 2D scanning planes. Methods We present a low-cost and flexible ultrasound imaging system that integrates several image processing components to allow for 3D reconstructions from limited numbers of 2D image planes and multiple acoustic views. Our approach is based on a 3D freehand ultrasound system that allows users to control the 2D acquisition imaging using conventional 2D probes. For reliable performance, we develop new methods for image segmentation and robust multi-view registration. We first present a new hybrid geometric level-set approach that provides reliable segmentation performance with relatively simple initializations and minimum edge leakage. Optimization of the segmentation model parameters and its effect on performance is carefully discussed. Second, using the segmented images, a new coarse to fine automatic multi-view registration method is introduced. The approach uses a 3D Hotelling transform to initialize an optimization search. Then, the fine scale feature-based registration is performed using a robust, non-linear least squares algorithm. The robustness of the multi-view registration system allows for accurate 3D reconstructions from sparse 2D image planes. Results Volume measurements from multi-view 3D reconstructions are found to be consistently and significantly more accurate than measurements from single view reconstructions. The volume error of multi-view reconstruction is measured to be less than 5% of the true volume. We show that volume reconstruction accuracy is a function of the total number of 2D image planes and the number of views for calibrated phantom. In clinical in-vivo cardiac experiments, we show that volume estimates of the left ventricle from multi-view reconstructions are found to be in better agreement with clinical measures than measures from single view reconstructions. Conclusions Multi-view 3D reconstruction from sparse 2D freehand B-mode images leads to more accurate volume quantification compared to single view systems. The flexibility and low-cost of the proposed system allow for fine control of the image acquisition planes for optimal 3D reconstructions from multiple views. PMID:21251284

A 3D freehand ultrasound system for multi-view reconstructions from sparse 2D scanning planes.

PubMed

Yu, Honggang; Pattichis, Marios S; Agurto, Carla; Beth Goens, M

2011-01-20

A significant limitation of existing 3D ultrasound systems comes from the fact that the majority of them work with fixed acquisition geometries. As a result, the users have very limited control over the geometry of the 2D scanning planes. We present a low-cost and flexible ultrasound imaging system that integrates several image processing components to allow for 3D reconstructions from limited numbers of 2D image planes and multiple acoustic views. Our approach is based on a 3D freehand ultrasound system that allows users to control the 2D acquisition imaging using conventional 2D probes.For reliable performance, we develop new methods for image segmentation and robust multi-view registration. We first present a new hybrid geometric level-set approach that provides reliable segmentation performance with relatively simple initializations and minimum edge leakage. Optimization of the segmentation model parameters and its effect on performance is carefully discussed. Second, using the segmented images, a new coarse to fine automatic multi-view registration method is introduced. The approach uses a 3D Hotelling transform to initialize an optimization search. Then, the fine scale feature-based registration is performed using a robust, non-linear least squares algorithm. The robustness of the multi-view registration system allows for accurate 3D reconstructions from sparse 2D image planes. Volume measurements from multi-view 3D reconstructions are found to be consistently and significantly more accurate than measurements from single view reconstructions. The volume error of multi-view reconstruction is measured to be less than 5% of the true volume. We show that volume reconstruction accuracy is a function of the total number of 2D image planes and the number of views for calibrated phantom. In clinical in-vivo cardiac experiments, we show that volume estimates of the left ventricle from multi-view reconstructions are found to be in better agreement with clinical measures than measures from single view reconstructions. Multi-view 3D reconstruction from sparse 2D freehand B-mode images leads to more accurate volume quantification compared to single view systems. The flexibility and low-cost of the proposed system allow for fine control of the image acquisition planes for optimal 3D reconstructions from multiple views.

System design of the CRISM (compact reconnaissance imaging spectrometer for Mars) hyperspectral imager

NASA Astrophysics Data System (ADS)

Silverglate, Peter R.; Fort, Dennis E.

2004-01-01

CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) is a hyperspectral imager that will be launched on the MRO (Mars Reconnaissance Orbiter) in August 2005. The MRO will circle Mars in a polar orbit at a nominal altitude of 325 km. The CRISM spectral range spans the ultraviolet (UV) to the mid-wave infrared (MWIR), 400 nm to 4050 nm. The instrument utilizes a Ritchey-Chretien telescope with a 2.06º field of view (FOV) to focus light on the entrance slit of a dual spectrometer. Within the spectrometer light is split by a dichroic into VNIR (visible-near infrared) (λ <= 1.05 μm) and IR (infrared) (λ >= 1.05 μm) beams. Each beam is directed into a separate modified Offner spectrometer that focuses a spectrally dispersed image of the slit onto a two dimensional focal plane (FP). The IR FP is a 640 x 480 HgCdTe area array; the VNIR FP is a 640 x 480 silicon photodiode area array. The spectral image is contiguously sampled with a 6.55 nm spectral spacing and an instantaneous field of view of 60 μradians. The orbital motion of the MRO pushbroom scans the spectrometer slit across the Martian surface, allowing the planet to be mapped in 558 spectral bands. There are four major mapping modes: A quick initial multi-spectral mapping of a major portion of the Martian surface in 59 selected spectral bands at a spatial resolution of 600 μradians (10:1 binning); an extended multi-spectral mapping of the entire Martian surface in 59 selected spectral bands at a spatial resolution of 300 μradians (5:1 binning); a high resolution Target Mode, performing hyperspectral mapping of selected targets of interest at full spatial and spectral resolution; and an atmospheric Emission Phase Function (EPF) mode for atmospheric study and correction at full spectral resolution at a spatial resolution of 300 μradians (5:1 binning). The instrument is gimbaled to allow scanning over +/-60° for the EPF and Target modes. The scanning also permits orbital motion compensation, enabling longer integration times and consequently higher signal-to-noise ratios for selected areas on the Martian surface in Target Mode.

System design of the CRISM (compact reconnaissance imaging spectrometer for Mars) hyperspectral imager

NASA Astrophysics Data System (ADS)

Silverglate, Peter R.; Fort, Dennis E.

2003-12-01

CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) is a hyperspectral imager that will be launched on the MRO (Mars Reconnaissance Orbiter) in August 2005. The MRO will circle Mars in a polar orbit at a nominal altitude of 325 km. The CRISM spectral range spans the ultraviolet (UV) to the mid-wave infrared (MWIR), 400 nm to 4050 nm. The instrument utilizes a Ritchey-Chretien telescope with a 2.06º field of view (FOV) to focus light on the entrance slit of a dual spectrometer. Within the spectrometer light is split by a dichroic into VNIR (visible-near infrared) (λ <= 1.05 μm) and IR (infrared) (λ >= 1.05 μm) beams. Each beam is directed into a separate modified Offner spectrometer that focuses a spectrally dispersed image of the slit onto a two dimensional focal plane (FP). The IR FP is a 640 x 480 HgCdTe area array; the VNIR FP is a 640 x 480 silicon photodiode area array. The spectral image is contiguously sampled with a 6.55 nm spectral spacing and an instantaneous field of view of 60 μradians. The orbital motion of the MRO pushbroom scans the spectrometer slit across the Martian surface, allowing the planet to be mapped in 558 spectral bands. There are four major mapping modes: A quick initial multi-spectral mapping of a major portion of the Martian surface in 59 selected spectral bands at a spatial resolution of 600 μradians (10:1 binning); an extended multi-spectral mapping of the entire Martian surface in 59 selected spectral bands at a spatial resolution of 300 μradians (5:1 binning); a high resolution Target Mode, performing hyperspectral mapping of selected targets of interest at full spatial and spectral resolution; and an atmospheric Emission Phase Function (EPF) mode for atmospheric study and correction at full spectral resolution at a spatial resolution of 300 μradians (5:1 binning). The instrument is gimbaled to allow scanning over +/-60° for the EPF and Target modes. The scanning also permits orbital motion compensation, enabling longer integration times and consequently higher signal-to-noise ratios for selected areas on the Martian surface in Target Mode.

Critical Zone Co-dynamics: Quantifying Interactions between Subsurface, Land Surface, and Vegetation Properties Using UAV and Geophysical Approaches

NASA Astrophysics Data System (ADS)

Dafflon, B.; Leger, E.; Peterson, J.; Falco, N.; Wainwright, H. M.; Wu, Y.; Tran, A. P.; Brodie, E.; Williams, K. H.; Versteeg, R.; Hubbard, S. S.

2017-12-01

Improving understanding and modelling of terrestrial systems requires advances in measuring and quantifying interactions among subsurface, land surface and vegetation processes over relevant spatiotemporal scales. Such advances are important to quantify natural and managed ecosystem behaviors, as well as to predict how watershed systems respond to increasingly frequent hydrological perturbations, such as droughts, floods and early snowmelt. Our study focuses on the joint use of UAV-based multi-spectral aerial imaging, ground-based geophysical tomographic monitoring (incl., electrical and electromagnetic imaging) and point-scale sensing (soil moisture sensors and soil sampling) to quantify interactions between above and below ground compartments of the East River Watershed in the Upper Colorado River Basin. We evaluate linkages between physical properties (incl. soil composition, soil electrical conductivity, soil water content), metrics extracted from digital surface and terrain elevation models (incl., slope, wetness index) and vegetation properties (incl., greenness, plant type) in a 500 x 500 m hillslope-floodplain subsystem of the watershed. Data integration and analysis is supported by numerical approaches that simulate the control of soil and geomorphic characteristic on hydrological processes. Results provide an unprecedented window into critical zone interactions, revealing significant below- and above-ground co-dynamics. Baseline geophysical datasets provide lithological structure along the hillslope, which includes a surface soil horizon, underlain by a saprolite layer and the fractured Mancos shale. Time-lapse geophysical data show very different moisture dynamics in various compartments and locations during the winter and growing season. Integration with aerial imaging reveals a significant linkage between plant growth and the subsurface wetness, soil characteristics and the topographic gradient. The obtained information about the organization and connectivity of the landscape is being transferred to larger regions using aerial imaging and will be used to constrain multi-scale, multi-physics hydro-biogeochemical simulations of the East River watershed response to hydrological perturbations.

Novel approach to multispectral image compression on the Internet

NASA Astrophysics Data System (ADS)

Zhu, Yanqiu; Jin, Jesse S.

2000-10-01

Still image coding techniques such as JPEG have been always applied onto intra-plane images. Coding fidelity is always utilized in measuring the performance of intra-plane coding methods. In many imaging applications, it is more and more necessary to deal with multi-spectral images, such as the color images. In this paper, a novel approach to multi-spectral image compression is proposed by using transformations among planes for further compression of spectral planes. Moreover, a mechanism of introducing human visual system to the transformation is provided for exploiting the psycho visual redundancy. The new technique for multi-spectral image compression, which is designed to be compatible with the JPEG standard, is demonstrated on extracting correlation among planes based on human visual system. A high measure of compactness in the data representation and compression can be seen with the power of the scheme taken into account.

Multi-spectral imaging with infrared sensitive organic light emitting diode

PubMed Central

Kim, Do Young; Lai, Tzung-Han; Lee, Jae Woong; Manders, Jesse R.; So, Franky

2014-01-01

Commercially available near-infrared (IR) imagers are fabricated by integrating expensive epitaxial grown III-V compound semiconductor sensors with Si-based readout integrated circuits (ROIC) by indium bump bonding which significantly increases the fabrication costs of these image sensors. Furthermore, these typical III-V compound semiconductors are not sensitive to the visible region and thus cannot be used for multi-spectral (visible to near-IR) sensing. Here, a low cost infrared (IR) imaging camera is demonstrated with a commercially available digital single-lens reflex (DSLR) camera and an IR sensitive organic light emitting diode (IR-OLED). With an IR-OLED, IR images at a wavelength of 1.2 µm are directly converted to visible images which are then recorded in a Si-CMOS DSLR camera. This multi-spectral imaging system is capable of capturing images at wavelengths in the near-infrared as well as visible regions. PMID:25091589

Color sensitivity of the multi-exposure HDR imaging process

NASA Astrophysics Data System (ADS)

Lenseigne, Boris; Jacobs, Valéry Ann; Withouck, Martijn; Hanselaer, Peter; Jonker, Pieter P.

2013-04-01

Multi-exposure high dynamic range(HDR) imaging builds HDR radiance maps by stitching together different views of a same scene with varying exposures. Practically, this process involves converting raw sensor data into low dynamic range (LDR) images, estimate the camera response curves, and use them in order to recover the irradiance for every pixel. During the export, applying white balance settings and image stitching, which both have an influence on the color balance in the final image. In this paper, we use a calibrated quasi-monochromatic light source, an integrating sphere, and a spectrograph in order to evaluate and compare the average spectral response of the image sensor. We finally draw some conclusion about the color consistency of HDR imaging and the additional steps necessary to use multi-exposure HDR imaging as a tool to measure the physical quantities such as radiance and luminance.

Multi-spectral imaging with infrared sensitive organic light emitting diode

NASA Astrophysics Data System (ADS)

Kim, Do Young; Lai, Tzung-Han; Lee, Jae Woong; Manders, Jesse R.; So, Franky

2014-08-01

Commercially available near-infrared (IR) imagers are fabricated by integrating expensive epitaxial grown III-V compound semiconductor sensors with Si-based readout integrated circuits (ROIC) by indium bump bonding which significantly increases the fabrication costs of these image sensors. Furthermore, these typical III-V compound semiconductors are not sensitive to the visible region and thus cannot be used for multi-spectral (visible to near-IR) sensing. Here, a low cost infrared (IR) imaging camera is demonstrated with a commercially available digital single-lens reflex (DSLR) camera and an IR sensitive organic light emitting diode (IR-OLED). With an IR-OLED, IR images at a wavelength of 1.2 µm are directly converted to visible images which are then recorded in a Si-CMOS DSLR camera. This multi-spectral imaging system is capable of capturing images at wavelengths in the near-infrared as well as visible regions.

Segmentation of neuroanatomy in magnetic resonance images

NASA Astrophysics Data System (ADS)

Simmons, Andrew; Arridge, Simon R.; Barker, G. J.; Tofts, Paul S.

1992-06-01

Segmentation in neurological magnetic resonance imaging (MRI) is necessary for feature extraction, volume measurement and for the three-dimensional display of neuroanatomy. Automated and semi-automated methods offer considerable advantages over manual methods because of their lack of subjectivity, their data reduction capabilities, and the time savings they give. We have used dual echo multi-slice spin-echo data sets which take advantage of the intrinsically multispectral nature of MRI. As a pre-processing step, a rf non-uniformity correction is applied and if the data is noisy the images are smoothed using a non-isotropic blurring method. Edge-based processing is used to identify the skin (the major outer contour) and the eyes. Edge-focusing has been used to significantly simplify edge images and thus allow simple postprocessing to pick out the brain contour in each slice of the data set. Edge- focusing is a technique which locates significant edges using a high degree of smoothing at a coarse level and tracks these edges to a fine level where the edges can be determined with high positional accuracy. Both 2-D and 3-D edge-detection methods have been compared. Once isolated, the brain is further processed to identify CSF, and, depending upon the MR pulse sequence used, the brain itself may be sub-divided into gray matter and white matter using semi-automatic contrast enhancement and clustering methods.

Object-oriented recognition of high-resolution remote sensing image

NASA Astrophysics Data System (ADS)

Wang, Yongyan; Li, Haitao; Chen, Hong; Xu, Yuannan

2016-01-01

With the development of remote sensing imaging technology and the improvement of multi-source image's resolution in satellite visible light, multi-spectral and hyper spectral , the high resolution remote sensing image has been widely used in various fields, for example military field, surveying and mapping, geophysical prospecting, environment and so forth. In remote sensing image, the segmentation of ground targets, feature extraction and the technology of automatic recognition are the hotspot and difficulty in the research of modern information technology. This paper also presents an object-oriented remote sensing image scene classification method. The method is consist of vehicles typical objects classification generation, nonparametric density estimation theory, mean shift segmentation theory, multi-scale corner detection algorithm, local shape matching algorithm based on template. Remote sensing vehicles image classification software system is designed and implemented to meet the requirements .

Software Toolbox for Low-Frequency Conductivity and Current Density Imaging Using MRI.

PubMed

Sajib, Saurav Z K; Katoch, Nitish; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

2017-11-01

Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes. Low-frequency conductivity and current density imaging using MRI includes magnetic resonance electrical impedance tomography (MREIT), diffusion tensor MREIT (DT-MREIT), conductivity tensor imaging (CTI), and magnetic resonance current density imaging (MRCDI). MRCDI and MREIT provide current density and isotropic conductivity images, respectively, using current-injection phase MRI techniques. DT-MREIT produces anisotropic conductivity tensor images by incorporating diffusion weighted MRI into MREIT. These current-injection techniques are finding clinical applications in diagnostic imaging and also in transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), and electroporation where treatment currents can function as imaging currents. To avoid adverse effects of nerve and muscle stimulations due to injected currents, conductivity tensor imaging (CTI) utilizes B1 mapping and multi-b diffusion weighted MRI to produce low-frequency anisotropic conductivity tensor images without injecting current. This paper describes numerical implementations of several key mathematical functions for conductivity and current density image reconstructions in MRCDI, MREIT, DT-MREIT, and CTI. To facilitate experimental studies of clinical applications, we developed a software toolbox for these low-frequency conductivity and current density imaging methods. This MR-based conductivity imaging (MRCI) toolbox includes 11 toolbox functions which can be used in the MATLAB environment. The MRCI toolbox is available at http://iirc.khu.ac.kr/software.html . Its functions were tested by using several experimental datasets, which are provided together with the toolbox. Users of the toolbox can focus on experimental designs and interpretations of reconstructed images instead of developing their own image reconstruction softwares. We expect more toolbox functions to be added from future research outcomes.

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

NASA Technical Reports Server (NTRS)

Knasel, T. Michael

1996-01-01

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Imaging of Combat-Related Thoracic Trauma - Review of Penetrating Trauma.

PubMed

Lichtenberger, John P; Kim, Andrew M; Fisher, Dane; Tatum, Peter S; Neubauer, Brian; Peterson, P Gabriel; Carter, Brett W

2018-03-01

Combat-related thoracic trauma is a significant contributor to morbidity and mortality of the casualties from Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF). Penetrating, blunt, and blast injuries were the most common mechanisms of trauma. Imaging plays a key role in the management of combat-related thoracic trauma casualties. This review discusses the imaging manifestations of thoracic injuries from penetrating trauma, emphasizing epidemiology and diagnostic clues seen during OEF and OIF. The assessment of radiologic findings in patients who suffer from combat-related thoracic trauma is the basis of this review article. The imaging modalities for this study include multi-detector computed tomography and chest radiography. High-velocity penetrating projectile injuries appear as hemorrhage and re-expansion pulmonary edema from the temporary cavity and a linear, blood-filled track from the permanent cavity. In cases where the projectile passes totally through the body, entrance wounds at the skin surface and tracks through the subcutaneous tissues may be the only indications of penetrating trauma. When assessing vascular injury, special attention should be paid to the right hilum in contrast-enhanced multi-detector computed tomography, as contrast is concentrated in the superior vena cava and superior cavoatrial junction may obscure small fragments. Additionally, CT angiography may show vessel disruption or extravasation of contrast distal to normal vessel location in addition to intraluminal filling defects and pseudo-aneurysms. Tension pneumopericardium may rarely complicate penetrating or blunt chest trauma. On imaging, distension of the pericardial sack by pneumopericardium and compression of the heart support the diagnosis of tension. On multi-detector computed tomography in the acute trauma setting, fluid in the pleural space should be considered hemothorax, particularly when Hounsfield units are above 35. Acutely, extravasated blood will have similar attenuation to the thoracic vasculature, whereas clotted blood will have higher values of 50-90 Hounsfield units. Combat-related thoracic trauma continues to be a significant contributor to the morbidity and mortality of those injured during OEF and OIF. This review of the imaging manifestations of penetrating thoracic injury during OEF and OIF focuses on key diagnostic findings for clinicians caring for combat casualties. The distinct injury pattern and atypical imaging manifestations of penetrating trauma are important to recognize early due to the acuity of this patient population and the influence of accurate diagnosis on clinical management.

Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging

PubMed Central

Shen, Kai; Lu, Hui; Baig, Sarfaraz; Wang, Michael R.

2017-01-01

The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues. PMID:29188089

Thermal Physical Property-Based Fusion of Geostationary Meteorological Satellite Visible and Infrared Channel Images

PubMed Central

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-01-01

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties. PMID:24919017

Thermal physical property-based fusion of geostationary meteorological satellite visible and infrared channel images.

PubMed

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-06-10

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties.

Microseismic reverse time migration with a multi-cross-correlation staining algorithm for fracture imaging

NASA Astrophysics Data System (ADS)

Yuan, Congcong; Jia, Xiaofeng; Liu, Shishuo; Zhang, Jie

2018-02-01

Accurate characterization of hydraulic fracturing zones is currently becoming increasingly important in production optimization, since hydraulic fracturing may increase the porosity and permeability of the reservoir significantly. Recently, the feasibility of the reverse time migration (RTM) method has been studied for the application in imaging fractures during borehole microseismic monitoring. However, strong low-frequency migration noise, poorly illuminated areas, and the low signal to noise ratio (SNR) data can degrade the imaging results. To improve the quality of the images, we propose a multi-cross-correlation staining algorithm to incorporate into the microseismic reverse time migration for imaging fractures using scattered data. Under the modified RTM method, our results are revealed in two images: one is the improved RTM image using the multi-cross-correlation condition, and the other is an image of the target region using the generalized staining algorithm. The numerical examples show that, compared with the conventional RTM, our method can significantly improve the spatial resolution of images, especially for the image of target region.

Interleaved diffusion-weighted EPI improved by adaptive partial-Fourier and multi-band multiplexed sensitivity-encoding reconstruction

PubMed Central

Chang, Hing-Chiu; Guhaniyogi, Shayan; Chen, Nan-kuei

2014-01-01

Purpose We report a series of techniques to reliably eliminate artifacts in interleaved echo-planar imaging (EPI) based diffusion weighted imaging (DWI). Methods First, we integrate the previously reported multiplexed sensitivity encoding (MUSE) algorithm with a new adaptive Homodyne partial-Fourier reconstruction algorithm, so that images reconstructed from interleaved partial-Fourier DWI data are free from artifacts even in the presence of either a) motion-induced k-space energy peak displacement, or b) susceptibility field gradient induced fast phase changes. Second, we generalize the previously reported single-band MUSE framework to multi-band MUSE, so that both through-plane and in-plane aliasing artifacts in multi-band multi-shot interleaved DWI data can be effectively eliminated. Results The new adaptive Homodyne-MUSE reconstruction algorithm reliably produces high-quality and high-resolution DWI, eliminating residual artifacts in images reconstructed with previously reported methods. Furthermore, the generalized MUSE algorithm is compatible with multi-band and high-throughput DWI. Conclusion The integration of the multi-band and adaptive Homodyne-MUSE algorithms significantly improves the spatial-resolution, image quality, and scan throughput of interleaved DWI. We expect that the reported reconstruction framework will play an important role in enabling high-resolution DWI for both neuroscience research and clinical uses. PMID:24925000

CRF-PEPICO: Double velocity map imaging photoelectron photoion coincidence spectroscopy for reaction kinetics studies

NASA Astrophysics Data System (ADS)

Sztáray, Bálint; Voronova, Krisztina; Torma, Krisztián G.; Covert, Kyle J.; Bodi, Andras; Hemberger, Patrick; Gerber, Thomas; Osborn, David L.

2017-07-01

Photoelectron photoion coincidence (PEPICO) spectroscopy could become a powerful tool for the time-resolved study of multi-channel gas phase chemical reactions. Toward this goal, we have designed and tested electron and ion optics that form the core of a new PEPICO spectrometer, utilizing simultaneous velocity map imaging for both cations and electrons, while also achieving good cation mass resolution through space focusing. These optics are combined with a side-sampled, slow-flow chemical reactor for photolytic initiation of gas-phase chemical reactions. Together with a recent advance that dramatically increases the dynamic range in PEPICO spectroscopy [D. L. Osborn et al., J. Chem. Phys. 145, 164202 (2016)], the design described here demonstrates a complete prototype spectrometer and reactor interface to carry out time-resolved experiments. Combining dual velocity map imaging with cation space focusing yields tightly focused photoion images for translationally cold neutrals, while offering good mass resolution for thermal samples as well. The flexible optics design incorporates linear electric fields in the ionization region, surrounded by dual curved electric fields for velocity map imaging of ions and electrons. Furthermore, the design allows for a long extraction stage, which makes this the first PEPICO experiment to combine ion imaging with the unimolecular dissociation rate constant measurements of cations to detect and account for kinetic shifts. Four examples are shown to illustrate some capabilities of this new design. We recorded the threshold photoelectron spectrum of the propargyl and the iodomethyl radicals. While the former agrees well with a literature threshold photoelectron spectrum, we have succeeded in resolving the previously unobserved vibrational structure in the latter. We have also measured the bimolecular rate constant of the CH2I + O2 reaction and observed its product, the smallest Criegee intermediate, CH2OO. Finally, the second dissociative photoionization step of iodocyclohexane ions, the loss of ethylene from the cyclohexyl cation, is slow at threshold, as illustrated by the asymmetric threshold photoionization time-of-flight distributions.

A Semi-Automatic Image-Based Close Range 3D Modeling Pipeline Using a Multi-Camera Configuration

PubMed Central

Rau, Jiann-Yeou; Yeh, Po-Chia

2012-01-01

The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum. PMID:23112656

A semi-automatic image-based close range 3D modeling pipeline using a multi-camera configuration.

PubMed

Rau, Jiann-Yeou; Yeh, Po-Chia

2012-01-01

The generation of photo-realistic 3D models is an important task for digital recording of cultural heritage objects. This study proposes an image-based 3D modeling pipeline which takes advantage of a multi-camera configuration and multi-image matching technique that does not require any markers on or around the object. Multiple digital single lens reflex (DSLR) cameras are adopted and fixed with invariant relative orientations. Instead of photo-triangulation after image acquisition, calibration is performed to estimate the exterior orientation parameters of the multi-camera configuration which can be processed fully automatically using coded targets. The calibrated orientation parameters of all cameras are applied to images taken using the same camera configuration. This means that when performing multi-image matching for surface point cloud generation, the orientation parameters will remain the same as the calibrated results, even when the target has changed. Base on this invariant character, the whole 3D modeling pipeline can be performed completely automatically, once the whole system has been calibrated and the software was seamlessly integrated. Several experiments were conducted to prove the feasibility of the proposed system. Images observed include that of a human being, eight Buddhist statues, and a stone sculpture. The results for the stone sculpture, obtained with several multi-camera configurations were compared with a reference model acquired by an ATOS-I 2M active scanner. The best result has an absolute accuracy of 0.26 mm and a relative accuracy of 1:17,333. It demonstrates the feasibility of the proposed low-cost image-based 3D modeling pipeline and its applicability to a large quantity of antiques stored in a museum.

Multi-slice ultrasound image calibration of an intelligent skin-marker for soft tissue artefact compensation.

PubMed

Masum, M A; Pickering, M R; Lambert, A J; Scarvell, J M; Smith, P N

2017-09-06

In this paper, a novel multi-slice ultrasound (US) image calibration of an intelligent skin-marker used for soft tissue artefact compensation is proposed to align and orient image slices in an exact H-shaped pattern. Multi-slice calibration is complex, however, in the proposed method, a phantom based visual alignment followed by transform parameters estimation greatly reduces the complexity and provides sufficient accuracy. In this approach, the Hough Transform (HT) is used to further enhance the image features which originate from the image feature enhancing elements integrated into the physical phantom model, thus reducing feature detection uncertainty. In this framework, slice by slice image alignment and calibration are carried out and this provides manual ease and convenience. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dim target detection method based on salient graph fusion

NASA Astrophysics Data System (ADS)

Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

2018-02-01

Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

Geometric registration of remotely sensed data with SAMIR

NASA Astrophysics Data System (ADS)

Gianinetto, Marco; Barazzetti, Luigi; Dini, Luigi; Fusiello, Andrea; Toldo, Roberto

2015-06-01

The commercial market offers several software packages for the registration of remotely sensed data through standard one-to-one image matching. Although very rapid and simple, this strategy does not take into consideration all the interconnections among the images of a multi-temporal data set. This paper presents a new scientific software, called Satellite Automatic Multi-Image Registration (SAMIR), able to extend the traditional registration approach towards multi-image global processing. Tests carried out with high-resolution optical (IKONOS) and high-resolution radar (COSMO-SkyMed) data showed that SAMIR can improve the registration phase with a more rigorous and robust workflow without initial approximations, user's interaction or limitation in spatial/spectral data size. The validation highlighted a sub-pixel accuracy in image co-registration for the considered imaging technologies, including optical and radar imagery.

Cell Motility Dynamics: A Novel Segmentation Algorithm to Quantify Multi-Cellular Bright Field Microscopy Images

PubMed Central

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications. PMID:22096600

Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

PubMed

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.

Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

PubMed

Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

2009-09-01

A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter.

PubMed

Bonny, Jean Marie; Boespflug-Tanguly, Odile; Zanca, Michel; Renou, Jean Pierre

2003-03-01

A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.

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.

Capillary Optics Based X-Ray Micro-Imaging Elemental Analysis

NASA Astrophysics Data System (ADS)

Hampai, D.; Dabagov, S. B.; Cappuccio, G.; Longoni, A.; Frizzi, T.; Cibin, G.

2010-04-01

A rapidly developed during the last few years micro-X-ray fluorescence spectrometry (μXRF) is a promising multi-elemental technique for non-destructive analysis. Typically it is rather hard to perform laboratory μXRF analysis because of the difficulty of producing an original small-size X-ray beam as well as its focusing. Recently developed for X-ray beam focusing polycapillary optics offers laboratory X-ray micro probes. The combination of polycapillary lens and fine-focused micro X-ray tube can provide high intensity radiation flux on a sample that is necessary in order to perform the elemental analysis. In comparison to a pinhole, an optimized "X-ray source-op tics" system can result in radiation density gain of more than 3 orders by the value. The most advanced way to get that result is to use the confocal configuration based on two X-ray lenses, one for the fluorescence excitation and the other for the detection of secondary emission from a sample studied. In case of X-ray capillary microfocusing a μXRF instrument designed in the confocal scheme allows us to obtain a 3D elemental mapping. In this work we will show preliminary results obtained with our prototype, a portable X-ray microscope for X-ray both imaging and fluorescence analysis; it enables μXRF elemental mapping simultaneously with X-ray imaging. A prototype of compact XRF spectrometer with a spatial resolution less than 100 μm has been designed.

Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

NASA Astrophysics Data System (ADS)

Engel, Dave W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David L.; Thompson, Sandra E.

2016-05-01

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

A framework for analysis of large database of old art paintings

NASA Astrophysics Data System (ADS)

Da Rugna, Jérome; Chareyron, Ga"l.; Pillay, Ruven; Joly, Morwena

2011-03-01

For many years, a lot of museums and countries organize the high definition digitalization of their own collections. In consequence, they generate massive data for each object. In this paper, we only focus on art painting collections. Nevertheless, we faced a very large database with heterogeneous data. Indeed, image collection includes very old and recent scans of negative photos, digital photos, multi and hyper spectral acquisitions, X-ray acquisition, and also front, back and lateral photos. Moreover, we have noted that art paintings suffer from much degradation: crack, softening, artifact, human damages and, overtime corruption. Considering that, it appears necessary to develop specific approaches and methods dedicated to digital art painting analysis. Consequently, this paper presents a complete framework to evaluate, compare and benchmark devoted to image processing algorithms.

Recent faulting in western Nevada revealed by multi-scale seismic reflection

USGS Publications Warehouse

Frary, Roxanna N.; Louie, John N.; Stephenson, William J.; Odum, Jackson K.; Kell, Annie; Eisses, Amy; Kent, Graham M.; Driscoll, Neal W.; Karlin, Robert; Baskin, Robert L.; Pullammanappallil, Satish; Liberty, Lee M.

2011-01-01

The main goal of this study is to compare different reflection methods used to image subsurface structure within different physical environments in western Nevada. With all the methods employed, the primary goal is fault imaging for structural information toward geothermal exploration and seismic hazard estimation. We use seismic CHIRP (a swept-frequency marine acquisition system), weight drop (an accelerated hammer source), and two different vibroseis systems to characterize fault structure. We focused our efforts in the Reno metropolitan area and the area within and surrounding Pyramid Lake in northern Nevada. These different methods have provided valuable constraints on the fault geometry and activity, as well as associated fluid movement. These are critical in evaluating the potential for large earthquakes in these areas, and geothermal exploration possibilities near these structures.

Hyperspectral stimulated emission depletion microscopy and methods of use thereof

DOEpatents

Timlin, Jerilyn A; Aaron, Jesse S

2014-04-01

A hyperspectral stimulated emission depletion ("STED") microscope system for high-resolution imaging of samples labeled with multiple fluorophores (e.g., two to ten fluorophores). The hyperspectral STED microscope includes a light source, optical systems configured for generating an excitation light beam and a depletion light beam, optical systems configured for focusing the excitation and depletion light beams on a sample, and systems for collecting and processing data generated by interaction of the excitation and depletion light beams with the sample. Hyperspectral STED data may be analyzed using multivariate curve resolution analysis techniques to deconvolute emission from the multiple fluorophores. The hyperspectral STED microscope described herein can be used for multi-color, subdiffraction imaging of samples (e.g., materials and biological materials) and for analyzing a tissue by Forster Resonance Energy Transfer ("FRET").

Image degradation characteristics and restoration based on regularization for diffractive imaging

NASA Astrophysics Data System (ADS)

Zhi, Xiyang; Jiang, Shikai; Zhang, Wei; Wang, Dawei; Li, Yun

2017-11-01

The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

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

USDA-ARS?s Scientific Manuscript database

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

Ultrasound-aided Multi-parametric Photoacoustic Microscopy of the Mouse Brain.

PubMed

Ning, Bo; Sun, Naidi; Cao, Rui; Chen, Ruimin; Kirk Shung, K; Hossack, John A; Lee, Jin-Moo; Zhou, Qifa; Hu, Song

2015-12-21

High-resolution quantitative imaging of cerebral oxygen metabolism in mice is crucial for understanding brain functions and formulating new strategies to treat neurological disorders, but remains a challenge. Here, we report on our newly developed ultrasound-aided multi-parametric photoacoustic microscopy (PAM), which enables simultaneous quantification of the total concentration of hemoglobin (CHb), the oxygen saturation of hemoglobin (sO2), and cerebral blood flow (CBF) at the microscopic level and through the intact mouse skull. The three-dimensional skull and vascular anatomies delineated by the dual-contrast (i.e., ultrasonic and photoacoustic) system provide important guidance for dynamically focused contour scan and vessel orientation-dependent correction of CBF, respectively. Moreover, bi-directional raster scan allows determining the direction of blood flow in individual vessels. Capable of imaging all three hemodynamic parameters at the same spatiotemporal scale, our ultrasound-aided PAM fills a critical gap in preclinical neuroimaging and lays the foundation for high-resolution mapping of the cerebral metabolic rate of oxygen (CMRO2)-a quantitative index of cerebral oxygen metabolism. This technical innovation is expected to shed new light on the mechanism and treatment of a broad spectrum of neurological disorders, including Alzheimer's disease and ischemic stroke.

ARGOS laser system mechanical design

NASA Astrophysics Data System (ADS)

Deysenroth, M.; Honsberg, M.; Gemperlein, H.; Ziegleder, J.; Raab, W.; Rabien, S.; Barl, L.; Gässler, W.; Borelli, J. L.

2014-07-01

ARGOS, a multi-star adaptive optics system is designed for the wide-field imager and multi-object spectrograph LUCI on the LBT (Large Binocular Telescope). Based on Rayleigh scattering the laser constellation images 3 artificial stars (at 532 nm) per each of the 2 eyes of the LBT, focused at a height of 12 km (Ground Layer Adaptive Optics). The stars are nominally positioned on a circle 2' in radius, but each star can be moved by up to 0.5' in any direction. For all of these needs are following main subsystems necessary: 1. A laser system with its 3 Lasers (Nd:YAG ~18W each) for delivering strong collimated light as for LGS indispensable. 2. The Launch system to project 3 beams per main mirror as a 40 cm telescope to the sky. 3. The Wave Front Sensor with a dichroic mirror. 4. The dichroic mirror unit to grab and interpret the data. 5. A Calibration Unit to adjust the system independently also during day time. 6. Racks + platforms for the WFS units. 7. Platforms and ladders for a secure access. This paper should mainly demonstrate how the ARGOS Laser System is configured and designed to support all other systems.

Time-Resolved and Spectroscopic Three-Dimensional Optical Breast Tomography

DTIC Science & Technology

2009-03-01

polarization sensitive imaging 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON R. R...project; • Development of a near-infrared center of intensity time gated imaging approach; and • Polarization sensitive imaging. We provide an...spectroscopic imaging arrangement, and a multi-source illumination and multi- detector signal acquisition arrangement. 5 5.1.1. Time-resolved transillumination

Multi-wavelength Observations of Neptune’s Atmosphere

NASA Astrophysics Data System (ADS)

de Pater, Imke; Fletcher, L.; Luszcz-Cook, S.; deBoer, D.; Butler, B.; Orton, G.; Sitko, M.; Hammel, H.

2013-10-01

We conducted a multi-wavelength observing campaign on Neptune between June and October, 2003. We used the 10-m Keck telescope at near- and mid-infrared wavelengths and the VLA at radio wavelengths. Near infrared images were taken in October 2003 in broad- and narrow-band filters between 1 and 2.5 micron, using the infrared camera NIRC2 coupled to the Keck Adaptive Optics system. At these wavelengths we detect sunlight reflected off clouds in the upper troposphere and lower stratosphere. As shown by various authors before, bright bands of discrete cloud features are visible between 20°S and 50°S and near 30°N, as well as several distinct bright cloud features near 70°S, and the south polar “dot”. Mid-infrared images were taken on September 5 and 6 (2003) using the Keck LWS system in atmospheric windows at 8, 8.9, 10.7, 11.7, 12.5, 17.65, 18.75 and 22 micron. At these wavelengths we detect thermal emission from Neptune’s stratosphere due to the presence of hydrocarbons, and from near the tropopause due to collision induced opacity by hydrogen. At all wavelengths the South polar region stands out as a bright spot. At 17 - 22 micron also the equatorial region is slightly enhanced in intensity. These characteristics are consistent with later imaging at similar wavelengths (Hammel et al. 2007; Orton et al. 2007). Microwave images were constructed from NRAO VLA data between 0.7 and 6.0 cm. At these wavelengths depths of several up to >50 bar are probed. An increase in brightness indicates decreased opacity of absorbers (e.g., NH3, H2S), since under such circumstances deep, and hence warm levels (adiabatic temperature-pressure profile), will be probed. The multi-wavelength observing campaign in 2003 was focused on obtaining images that probe different altitudes in Neptune’s atmosphere. Indeed, this set of data probes altitudes from about 0.1 mbar down to ~50 bar, and hence can be used to constrain the global atmospheric circulation in Neptune’s atmosphere. At the meeting we will show our results and interpretation of the findings.

Determination of Destructed and Infracted Forest Areas with Multi-temporal High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Seker, D. Z.; Unal, A.; Kaya, S.; Alganci, U.

2015-12-01

Migration from rural areas to city centers and their surroundings is an important problem of not only our country but also the countries that under development stage. This uncontrolled and huge amount of migration brings out urbanization and socio - economic problems. The demand on settling the industrial areas and commercial activities nearby the city centers results with a negative change in natural land cover on cities. Negative impacts of human induced activities on natural resources and land cover has been continuously increasing for decades. The main human activities that resulted with destruction and infraction of forest areas can be defined as mining activities, agricultural activities, industrial / commercial activities and urbanization. Temporal monitoring of the changes in spatial distribution of forest areas is significantly important for effective management and planning progress. Changes can occur as spatially large destructions or small infractions. Therefore there is a need for reliable, fast and accurate data sources. At this point, satellite images proved to be a good data source for determination of the land use /cover changes with their capability of monitoring large areas with reasonable temporal resolutions. Spectral information derived from images provides discrimination of land use/cover types from each other. Developments in remote sensing technology in the last decade improved the spatial resolution of satellites and high resolution images were started to be used to detect even small changes in the land surface. As being the megacity of Turkey, Istanbul has been facing a huge migration for the last 20 years and effects of urbanization and other human based activities over forest areas are significant. Main focus of this study is to determine the destructions and infractions in forest areas of Istanbul, Turkey with 2.5m resolution SPOT 5 multi-temporal satellite imagery. Analysis was mainly constructed on threshold based classification of multi-temporal vegetation index data derived from satellite images. Determined changes were exported to GIS environment and spatial overlay and intersection analyses were performed with use of forest type maps and authorized area maps in order to demonstrate the actual situation of destructions and infractions.

A detail-preserved and luminance-consistent multi-exposure image fusion algorithm

NASA Astrophysics Data System (ADS)

Wang, Guanquan; Zhou, Yue

2018-04-01

When irradiance across a scene varies greatly, we can hardly get an image of the scene without over- or underexposure area, because of the constraints of cameras. Multi-exposure image fusion (MEF) is an effective method to deal with this problem by fusing multi-exposure images of a static scene. A novel MEF method is described in this paper. In the proposed algorithm, coarser-scale luminance consistency is preserved by contribution adjustment using the luminance information between blocks; detail-preserved smoothing filter can stitch blocks smoothly without losing details. Experiment results show that the proposed method performs well in preserving luminance consistency and details.

An improved feature extraction algorithm based on KAZE for multi-spectral image

NASA Astrophysics Data System (ADS)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

A Unified Approach to Diffusion Direction Sensitive Slice Registration and 3-D DTI Reconstruction From Moving Fetal Brain Anatomy

PubMed Central

Fogtmann, Mads; Seshamani, Sharmishtaa; Kroenke, Christopher; Cheng, Xi; Chapman, Teresa; Wilm, Jakob; Rousseau, François

2014-01-01

This paper presents an approach to 3-D diffusion tensor image (DTI) reconstruction from multi-slice diffusion weighted (DW) magnetic resonance imaging acquisitions of the moving fetal brain. Motion scatters the slice measurements in the spatial and spherical diffusion domain with respect to the underlying anatomy. Previous image registration techniques have been described to estimate the between slice fetal head motion, allowing the reconstruction of 3-D a diffusion estimate on a regular grid using interpolation. We propose Approach to Unified Diffusion Sensitive Slice Alignment and Reconstruction (AUDiSSAR) that explicitly formulates a process for diffusion direction sensitive DW-slice-to-DTI-volume alignment. This also incorporates image resolution modeling to iteratively deconvolve the effects of the imaging point spread function using the multiple views provided by thick slices acquired in different anatomical planes. The algorithm is implemented using a multi-resolution iterative scheme and multiple real and synthetic data are used to evaluate the performance of the technique. An accuracy experiment using synthetically created motion data of an adult head and a experiment using synthetic motion added to sedated fetal monkey dataset show a significant improvement in motion-trajectory estimation compared to a state-of-the-art approaches. The performance of the method is then evaluated on challenging but clinically typical in utero fetal scans of four different human cases, showing improved rendition of cortical anatomy and extraction of white matter tracts. While the experimental work focuses on DTI reconstruction (second-order tensor model), the proposed reconstruction framework can employ any 5-D diffusion volume model that can be represented by the spatial parameterizations of an orientation distribution function. PMID:24108711

Multi range spectral feature fitting for hyperspectral imagery in extracting oilseed rape planting area

NASA Astrophysics Data System (ADS)

Pan, Zhuokun; Huang, Jingfeng; Wang, Fumin

2013-12-01

Spectral feature fitting (SFF) is a commonly used strategy for hyperspectral imagery analysis to discriminate ground targets. Compared to other image analysis techniques, SFF does not secure higher accuracy in extracting image information in all circumstances. Multi range spectral feature fitting (MRSFF) from ENVI software allows user to focus on those interesting spectral features to yield better performance. Thus spectral wavelength ranges and their corresponding weights must be determined. The purpose of this article is to demonstrate the performance of MRSFF in oilseed rape planting area extraction. A practical method for defining the weighted values, the variance coefficient weight method, was proposed to set up criterion. Oilseed rape field canopy spectra from the whole growth stage were collected prior to investigating its phenological varieties; oilseed rape endmember spectra were extracted from the Hyperion image as identifying samples to be used in analyzing the oilseed rape field. Wavelength range divisions were determined by the difference between field-measured spectra and image spectra, and image spectral variance coefficient weights for each wavelength range were calculated corresponding to field-measured spectra from the closest date. By using MRSFF, wavelength ranges were classified to characterize the target's spectral features without compromising spectral profile's entirety. The analysis was substantially successful in extracting oilseed rape planting areas (RMSE ≤ 0.06), and the RMSE histogram indicated a superior result compared to a conventional SFF. Accuracy assessment was based on the mapping result compared with spectral angle mapping (SAM) and the normalized difference vegetation index (NDVI). The MRSFF yielded a robust, convincible result and, therefore, may further the use of hyperspectral imagery in precision agriculture.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

Automatic Brain Tumor Detection in T2-weighted Magnetic Resonance Images

NASA Astrophysics Data System (ADS)

Dvořák, P.; Kropatsch, W. G.; Bartušek, K.

2013-10-01

This work focuses on fully automatic detection of brain tumors. The first aim is to determine, whether the image contains a brain with a tumor, and if it does, localize it. The goal of this work is not the exact segmentation of tumors, but the localization of their approximate position. The test database contains 203 T2-weighted images of which 131 are images of healthy brain and the remaining 72 images contain brain with pathological area. The estimation, whether the image shows an afflicted brain and where a pathological area is, is done by multi resolution symmetry analysis. The first goal was tested by five-fold cross-validation technique with 100 repetitions to avoid the result dependency on sample order. This part of the proposed method reaches the true positive rate of 87.52% and the true negative rate of 93.14% for an afflicted brain detection. The evaluation of the second part of the algorithm was carried out by comparing the estimated location to the true tumor location. The detection of the tumor location reaches the rate of 95.83% of correct anomaly detection and the rate 87.5% of correct tumor location.

Megahertz rate, volumetric imaging of bubble clouds in sonothrombolysis using a sparse hemispherical receiver array

NASA Astrophysics Data System (ADS)

Acconcia, Christopher N.; Jones, Ryan M.; Goertz, David E.; O'Reilly, Meaghan A.; Hynynen, Kullervo

2017-09-01

It is well established that high intensity focused ultrasound can be used to disintegrate clots. This approach has the potential to rapidly and noninvasively resolve clot causing occlusions in cardiovascular diseases such as deep vein thrombosis (DVT). However, lack of an appropriate treatment monitoring tool is currently a limiting factor in its widespread adoption. Here we conduct cavitation imaging with a large aperture, sparse hemispherical receiver array during sonothrombolysis with multi-cycle burst exposures (0.1 or 1 ms burst lengths) at 1.51 MHz. It was found that bubble cloud generation on imaging correlated with the locations of clot degradation, as identified with high frequency (30 MHz) ultrasound following exposures. 3D images could be formed at integration times as short as 1 µs, revealing the initiation and rapid development of cavitation clouds. Equating to megahertz frame rates, this is an order of magnitude faster than any other imaging technique available for in vivo application. Collectively, these results suggest that the development of a device to perform DVT therapy procedures would benefit greatly from the integration of receivers tailored to bubble activity imaging.

Megahertz rate, volumetric imaging of bubble clouds in sonothrombolysis using a sparse hemispherical receiver array.

PubMed

Acconcia, Christopher N; Jones, Ryan M; Goertz, David E; O'Reilly, Meaghan A; Hynynen, Kullervo

2017-09-05

It is well established that high intensity focused ultrasound can be used to disintegrate clots. This approach has the potential to rapidly and noninvasively resolve clot causing occlusions in cardiovascular diseases such as deep vein thrombosis (DVT). However, lack of an appropriate treatment monitoring tool is currently a limiting factor in its widespread adoption. Here we conduct cavitation imaging with a large aperture, sparse hemispherical receiver array during sonothrombolysis with multi-cycle burst exposures (0.1 or 1 ms burst lengths) at 1.51 MHz. It was found that bubble cloud generation on imaging correlated with the locations of clot degradation, as identified with high frequency (30 MHz) ultrasound following exposures. 3D images could be formed at integration times as short as 1 µs, revealing the initiation and rapid development of cavitation clouds. Equating to megahertz frame rates, this is an order of magnitude faster than any other imaging technique available for in vivo application. Collectively, these results suggest that the development of a device to perform DVT therapy procedures would benefit greatly from the integration of receivers tailored to bubble activity imaging.

Multi-Image or Lap-Dissolve Slide Techniques and Visual Images in the Large Lecture Section.

ERIC Educational Resources Information Center

Bodner, George M.; And Others

1984-01-01

Advantages and disadvantages of using multi-image or lap-dissolve (LD) slide techniques in large lecture sections are discussed. Production, use, and evaluation of LD programs are also discussed. Indicates that these programs are an effective way of improving instruction on visually oriented topics. (JN)

Simultaneous multi-headed imager geometry calibration method

DOEpatents

Tran, Vi-Hoa [Newport News, VA; Meikle, Steven Richard [Penshurst, AU; Smith, Mark Frederick [Yorktown, VA

2008-02-19

A method for calibrating multi-headed high sensitivity and high spatial resolution dynamic imaging systems, especially those useful in the acquisition of tomographic images of small animals. The method of the present invention comprises: simultaneously calibrating two or more detectors to the same coordinate system; and functionally correcting for unwanted detector movement due to gantry flexing.

Automatic Co-Registration of Multi-Temporal Landsat-8/OLI and Sentinel-2A/MSI Images

NASA Technical Reports Server (NTRS)

Skakun, S.; Roger, J.-C.; Vermote, E.; Justice, C.; Masek, J.

2017-01-01

Many applications in climate change and environmental and agricultural monitoring rely heavily on the exploitation of multi-temporal satellite imagery. Combined use of freely available Landsat-8 and Sentinel-2 images can offer high temporal frequency of about 1 image every 3-5 days globally.

Viewing zone duplication of multi-projection 3D display system using uniaxial crystal.

PubMed

Lee, Chang-Kun; Park, Soon-Gi; Moon, Seokil; Lee, Byoungho

2016-04-18

We propose a novel multiplexing technique for increasing the viewing zone of a multi-view based multi-projection 3D display system by employing double refraction in uniaxial crystal. When linearly polarized images from projector pass through the uniaxial crystal, two possible optical paths exist according to the polarization states of image. Therefore, the optical paths of the image could be changed, and the viewing zone is shifted in a lateral direction. The polarization modulation of the image from a single projection unit enables us to generate two viewing zones at different positions. For realizing full-color images at each viewing zone, a polarization-based temporal multiplexing technique is adopted with a conventional polarization switching device of liquid crystal (LC) display. Through experiments, a prototype of a ten-view multi-projection 3D display system presenting full-colored view images is implemented by combining five laser scanning projectors, an optically clear calcite (CaCO₃) crystal, and an LC polarization rotator. For each time sequence of temporal multiplexing, the luminance distribution of the proposed system is measured and analyzed.

Design and Application of Multi-functional Electrogenerated Chemiluminescence Imaging Analyzer.

PubMed

Jiang, Guangfu; Liu, Xia; Wang, Yaqin; Ruan, Sanpeng; Qi, Honglan; Yang, Yong; Zhou, Qishe; Zhang, Chengxiao

2016-01-01

A multi-functional eletrogenerated chemiluminescence (ECL) imaging analyzer including both a photomultiplier tube and charged coupled device as detectors has been developed. The ECL imaging analyzer can effectively work for electrochemical study, ECL intensity detection at electrode array, and ECL imaging at bipolar electrodes or electrode array. As an ECL imaging example, an ECL biosensor for visual detection of matrix metalloproteinase 7 in the range from 0.05 to 1 ng/mL is demonstrated.

Multi-kernel deconvolution for contrast improvement in a full field imaging system with engineered PSFs using conical diffraction

NASA Astrophysics Data System (ADS)

Enguita, Jose M.; Álvarez, Ignacio; González, Rafael C.; Cancelas, Jose A.

2018-01-01

The problem of restoration of a high-resolution image from several degraded versions of the same scene (deconvolution) has been receiving attention in the last years in fields such as optics and computer vision. Deconvolution methods are usually based on sets of images taken with small (sub-pixel) displacements or slightly different focus. Techniques based on sets of images obtained with different point-spread-functions (PSFs) engineered by an optical system are less popular and mostly restricted to microscopic systems, where a spot of light is projected onto the sample under investigation, which is then scanned point-by-point. In this paper, we use the effect of conical diffraction to shape the PSFs in a full-field macroscopic imaging system. We describe a series of simulations and real experiments that help to evaluate the possibilities of the system, showing the enhancement in image contrast even at frequencies that are strongly filtered by the lens transfer function or when sampling near the Nyquist frequency. Although results are preliminary and there is room to optimize the prototype, the idea shows promise to overcome the limitations of the image sensor technology in many fields, such as forensics, medical, satellite, or scientific imaging.

Quicksilver: Fast predictive image registration - A deep learning approach.

PubMed

Yang, Xiao; Kwitt, Roland; Styner, Martin; Niethammer, Marc

2017-09-01

This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver registration for image-pairs works by patch-wise prediction of a deformation model based directly on image appearance. A deep encoder-decoder network is used as the prediction model. While the prediction strategy is general, we focus on predictions for the Large Deformation Diffeomorphic Metric Mapping (LDDMM) model. Specifically, we predict the momentum-parameterization of LDDMM, which facilitates a patch-wise prediction strategy while maintaining the theoretical properties of LDDMM, such as guaranteed diffeomorphic mappings for sufficiently strong regularization. We also provide a probabilistic version of our prediction network which can be sampled during the testing time to calculate uncertainties in the predicted deformations. Finally, we introduce a new correction network which greatly increases the prediction accuracy of an already existing prediction network. We show experimental results for uni-modal atlas-to-image as well as uni-/multi-modal image-to-image registrations. These experiments demonstrate that our method accurately predicts registrations obtained by numerical optimization, is very fast, achieves state-of-the-art registration results on four standard validation datasets, and can jointly learn an image similarity measure. Quicksilver is freely available as an open-source software. Copyright © 2017 Elsevier Inc. All rights reserved.

Deep multi-scale convolutional neural network for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

Improved microseismic event locations through large-N arrays and wave-equation imaging and inversion

NASA Astrophysics Data System (ADS)

Witten, B.; Shragge, J. C.

2016-12-01

The recent increased focus on small-scale seismicity, Mw < 4 has come about primarily for two reasons. First, there is an increase in induced seismicity related to injection operations primarily for wastewater disposal and hydraulic fracturing for oil and gas recovery and for geothermal energy production. While the seismicity associated with injection is sometimes felt, it is more often weak. Some weak events are detected on current sparse arrays; however, accurate location of the events often requires a larger number of (multi-component) sensors. This leads to the second reason for an increased focus on small magnitude seismicity: a greater number of seismometers are being deployed in large N-arrays. The greater number of sensors decreases the detection threshold and therefore significantly increases the number of weak events found. Overall, these two factors bring new challenges and opportunities. Many standard seismological location and inversion techniques are geared toward large, easily identifiable events recorded on a sparse number of stations. However, with large-N arrays we can detect small events by utilizing multi-trace processing techniques, and increased processing power equips us with tools that employ more complete physics for simultaneously locating events and inverting for P- and S-wave velocity structure. We present a method that uses large-N arrays and wave-equation-based imaging and inversion to jointly locate earthquakes and estimate the elastic velocities of the earth. The technique requires no picking and is thus suitable for weak events. We validate the methodology through synthetic and field data examples.

A novel intravital multi-harmonic generation microscope for early diagnosis of oral cancer

NASA Astrophysics Data System (ADS)

Cheng, Yu-Hsiang; Lin, Chih-Feng; Shih, Ting-Fang; Sun, Chi-Kuang

2013-03-01

Oral cancer is one of the most frequently diagnosed human cancers and leading causes of cancer death all over the world, but the prognosis and overall survival rate are still poor because of delay in diagnosis and lack of early intervention. The failure of early diagnosis is due to insufficiency of proper diagnostic and screening tools and most patients are reluctant to undergo biopsy. Optical virtual biopsy techniques, for imaging cells and tissues at microscopic details capable of differentiating benign from malignant lesions non-invasively, are thus highly desirable. A novel multi-harmonic generation microscope, excited by a 1260 nm Cr:forsterite laser, with second and third harmonic signals demonstrating collagen fiber distribution and cell morphology in a sub-micron resolution, was developed for clinical use. To achieve invivo observation inside the human oral cavity, a small objective probe with a suction capability was carefully designed for patients' comfort and stability. By remotely changing its focus point, the same objective can image the mucosa surface with a low magnification, illuminated by side light-emitting diodes, with a charge-coupled device (CCD) for site location selection before the harmonic generation biopsy was applied. Furthermore, the slow galvanometer mirror and the fast resonant mirror provide a 30 fps frame rate for high-speed real-time observation and the z-motor of this system is triggered at the same rate to provide fast 3D scanning, again ensuring patients' comfort. Focusing on the special cytological and morphological changes of the oral epithelial cells, our preliminary result disclosed excellent consistency with traditional histopathology studies.

A brain MRI bias field correction method created in the Gaussian multi-scale space

NASA Astrophysics Data System (ADS)

Chen, Mingsheng; Qin, Mingxin

2017-07-01

A pre-processing step is needed to correct for the bias field signal before submitting corrupted MR images to such image-processing algorithms. This study presents a new bias field correction method. The method creates a Gaussian multi-scale space by the convolution of the inhomogeneous MR image with a two-dimensional Gaussian function. In the multi-Gaussian space, the method retrieves the image details from the differentiation of the original image and convolution image. Then, it obtains an image whose inhomogeneity is eliminated by the weighted sum of image details in each layer in the space. Next, the bias field-corrected MR image is retrieved after the Υ correction, which enhances the contrast and brightness of the inhomogeneity-eliminated MR image. We have tested the approach on T1 MRI and T2 MRI with varying bias field levels and have achieved satisfactory results. Comparison experiments with popular software have demonstrated superior performance of the proposed method in terms of quantitative indices, especially an improvement in subsequent image segmentation.

in vivo quantification of white matter microstructure for use in aging: A focus on two emerging techniques

PubMed Central

Lamar, Melissa; Zhou, Xiaohong Joe; Charlton, Rebecca A.; Dean, Douglas; Little, Deborah; Deoni, Sean C

2013-01-01

Human brain imaging has seen many advances in the quantification of white matter in vivo. For example, these advances have revealed the association between white matter damage and vascular disease as well as their impact on risk for and development of dementia and depression in an aging population. Current neuroimaging methods to quantify white matter damage provide a foundation for understanding such age-related neuropathology; however, these methods are not as adept at determining the underlying microstructural abnormalities signaling at risk tissue or driving white matter damage in the aging brain. This review will begin with a brief overview of the use of diffusion tensor imaging (DTI) in understanding white matter alterations in aging before focusing in more detail on select advances in both diffusion-based methods and multi-component relaxometry techniques for imaging white matter microstructural integrity within myelin sheaths and the axons they encase. While DTI greatly extended the field of white matter interrogation, these more recent technological advances will add clarity to the underlying microstructural mechanisms that contribute to white matter damage. More specifically, the methods highlighted in this review may prove more sensitive (and specific) for determining the contribution of myelin versus axonal integrity to the aging of white matter in brain. PMID:24080382

Advances in combined endoscopic fluorescence confocal microscopy and optical coherence tomography

NASA Astrophysics Data System (ADS)

Risi, Matthew D.

Confocal microendoscopy provides real-time high resolution cellular level images via a minimally invasive procedure. Results from an ongoing clinical study to detect ovarian cancer with a novel confocal fluorescent microendoscope are presented. As an imaging modality, confocal fluorescence microendoscopy typically requires exogenous fluorophores, has a relatively limited penetration depth (100 μm), and often employs specialized aperture configurations to achieve real-time imaging in vivo. Two primary research directions designed to overcome these limitations and improve diagnostic capability are presented. Ideal confocal imaging performance is obtained with a scanning point illumination and confocal aperture, but this approach is often unsuitable for real-time, in vivo biomedical imaging. By scanning a slit aperture in one direction, image acquisition speeds are greatly increased, but at the cost of a reduction in image quality. The design, implementation, and experimental verification of a custom multi-point-scanning modification to a slit-scanning multi-spectral confocal microendoscope is presented. This new design improves the axial resolution while maintaining real-time imaging rates. In addition, the multi-point aperture geometry greatly reduces the effects of tissue scatter on imaging performance. Optical coherence tomography (OCT) has seen wide acceptance and FDA approval as a technique for ophthalmic retinal imaging, and has been adapted for endoscopic use. As a minimally invasive imaging technique, it provides morphological characteristics of tissues at a cellular level without requiring the use of exogenous fluorophores. OCT is capable of imaging deeper into biological tissue (˜1-2 mm) than confocal fluorescence microscopy. A theoretical analysis of the use of a fiber-bundle in spectral-domain OCT systems is presented. The fiber-bundle enables a flexible endoscopic design and provides fast, parallelized acquisition of the optical coherence tomography data. However, the multi-mode characteristic of the fibers in the fiber-bundle affects the depth sensitivity of the imaging system. A description of light interference in a multi-mode fiber is presented along with numerical simulations and experimental studies to illustrate the theoretical analysis.