Identification, characterization, and expression analysis of calmodulin and calmodulin-like genes in grapevine (Vitis vinifera) reveal likely roles in stress responses.

PubMed

Vandelle, Elodie; Vannozzi, Alessandro; Wong, Darren; Danzi, Davide; Digby, Anne-Marie; Dal Santo, Silvia; Astegno, Alessandra

2018-06-04

Calcium (Ca 2+ ) is an ubiquitous key second messenger in plants, where it modulates many developmental and adaptive processes in response to various stimuli. Several proteins containing Ca 2+ binding domain have been identified in plants, including calmodulin (CaM) and calmodulin-like (CML) proteins, which play critical roles in translating Ca 2+ signals into proper cellular responses. In this work, a genome-wide analysis conducted in Vitis vinifera identified three CaM- and 62 CML-encoding genes. We assigned gene family nomenclature, analyzed gene structure, chromosomal location and gene duplication, as well as protein motif organization. The phylogenetic clustering revealed a total of eight subgroups, including one unique clade of VviCaMs distinct from VviCMLs. VviCaMs were found to contain four EF-hand motifs whereas VviCML proteins have one to five. Most of grapevine CML genes were intronless, while VviCaMs were intron rich. All the genes were well spread among the 19 grapevine chromosomes and displayed a high level of duplication. The expression profiling of VviCaM/VviCML genes revealed a broad expression pattern across all grape organs and tissues at various developmental stages, and a significant modulation in biotic stress-related responses. Our results highlight the complexity of CaM/CML protein family also in grapevine, supporting the versatile role of its different members in modulating cellular responses to various stimuli, in particular to biotic stresses. This work lays the foundation for further functional and structural studies on specific grapevine CaMs/CMLs in order to better understand the role of Ca 2+ -binding proteins in grapevine and to explore their potential for further biotechnological applications. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

DDD versus VVIR versus VVI mode in patients with indication to dual-chamber stimulation: a prospective, randomized, controlled, single-blind study.

PubMed

Moro, Eugenio; Caprioglio, Francesco; Berton, Giuseppe; Marcon, Carlo; Riva, Umberto; Corbucci, Giorgio; Delise, Pietro

2005-09-01

The aim of this study was to compare VVI, VVIR and DDD modes in patients with indication to dual-chamber stimulation, depending on left ventricular function. Two groups of patients were implanted with a DDD pacemaker: Group I with ejection fraction > 40% and Group II with ejection fraction < 40%. Patients with a history of atrial arrhythmia or retrograde conduction were excluded. At follow-up (1 month each) quality of life (QoL), patient preference and echo parameters were collected. At hospital discharge all patients were programmed in DDD for 1 month and then randomized to VVI or VVIR mode. At the end of the period in VVI or VVIR mode each patient underwent a control period in DDD and then was programmed in VVIR or VVI mode. Seventeen patients out of 23 preferred DDD mode and 6 did not perceive any subjective difference among DDD, VVI and VVIR modes (4/9 in Group I and 2/14 in Group II, p = 0.0017). QoL was significantly different between the two groups and at each follow-up showed the best values in DDD. The correlation between QoL and Tei index was 0.62 in Group I (p < 0.001) and 0.35 in Group II (p = 0.001). Neither ejection fraction nor fractional shortening showed any significant difference during the three phases of the study. Most patients preferred the DDD mode. The Tei index showed a good correlation with QoL and both QoL and Tei index significantly improved with DDD mode as compared to VVI and VVIR.

Grapevine and Arabidopsis Cation-Chloride Cotransporters Localize to the Golgi and Trans-Golgi Network and Indirectly Influence Long-Distance Ion Transport and Plant Salt Tolerance1[OPEN

PubMed Central

Henderson, Sam W.; Wege, Stefanie; Qiu, Jiaen; Blackmore, Deidre H.; Walker, Amanda R.; Tyerman, Stephen D.; Walker, Rob R.; Gilliham, Matthew

2015-01-01

Plant cation-chloride cotransporters (CCCs) have been implicated in conferring salt tolerance. They are predicted to improve shoot salt exclusion by directly catalyzing the retrieval of sodium (Na+) and chloride (Cl−) ions from the root xylem. We investigated whether grapevine (Vitis vinifera [Vvi]) CCC has a role in salt tolerance by cloning and functionally characterizing the gene from the cultivar Cabernet Sauvignon. Amino acid sequence analysis revealed that VviCCC shares a high degree of similarity with other plant CCCs. A VviCCC-yellow fluorescent protein translational fusion protein localized to the Golgi and the trans-Golgi network and not the plasma membrane when expressed transiently in tobacco (Nicotiana benthamiana) leaves and Arabidopsis (Arabidopsis thaliana) mesophyll protoplasts. AtCCC-green fluorescent protein from Arabidopsis also localized to the Golgi and the trans-Golgi network. In Xenopus laevis oocytes, VviCCC targeted to the plasma membrane, where it catalyzed bumetanide-sensitive 36Cl–, 22Na+, and 86Rb+ uptake, suggesting that VviCCC (like AtCCC) belongs to the Na+-K+-2Cl– cotransporter class of CCCs. Expression of VviCCC in an Arabidopsis ccc knockout mutant abolished the mutant’s stunted growth phenotypes and reduced shoot Cl– and Na+ content to wild-type levels after growing plants in 50 mm NaCl. In grapevine roots, VviCCC transcript abundance was not regulated by Cl– treatment and was present at similar levels in both the root stele and cortex of three Vitis spp. genotypes that exhibit differential shoot salt exclusion. Our findings indicate that CCC function is conserved between grapevine and Arabidopsis, but neither protein is likely to directly mediate ion transfer with the xylem or have a direct role in salt tolerance. PMID:26378102

Coastwide Reference Monitoring System (CRMS) Vegetation Volume Index: An assessment tool for marsh habitat focused on the three-dimensional structure at CRMS vegetation monitoring stations

USGS Publications Warehouse

Wood, William B.; Visser, Jenneke M.; Piazza, Sarai C.; Sharp, Leigh A.; Hundy, Laura C.; McGinnis, Tommy E.

2015-12-04

The VV and VVI will be used to establish trends, to make comparisons, and to evaluate restoration projects. Assessments that rely on the VVI will be included in appropriate Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) project reports and analyses. Implementation of the VVI will give coastal managers a new tool to design, implement, and monitor coastal restoration projects. A yearly trajectory of site, project, basin, and coastwide VVI will be posted on the CRMS Web site as data are collected. The primary purpose of the tool is to assess CWPPRA restoration project effectiveness, but it will also be useful in identifying areas in need of restoration and in coastwide vegetation assessments.

Implantation of VVI pacemaker in a patient with dextrocardia, persistent left superior vena cava, and sick sinus syndrome

PubMed Central

Guo, Gongliang; Yang, Lili; Wu, Jinyi; Sun, Liqun

2017-01-01

Abstract Background: Dextrocardia, or right-lying heart, is an uncommon congenital heart disease in which the apex of the heart is located on the right side of chest. Persistent left superior vena cava (PLSVA) is a rare venous anomaly that is often associated with the abnormalities of cardiac transduction system. A case with combination of dextrocardia, persistent left superior vena cava, and sick sinus syndrome has not been reported. Methods: We used different techniques including cardiac color Doppler echocardiography, 24-hour Holter monitoring, and abdominal ultrasound to make a diagnosis and treated the patient by implanting a VVI pacemaker. Results: A 50-year-old woman was admitted with a syncope. Angiography of the right atrium and superior vena cava, echocardiography, electrocardiography, and abdominal ultrasound revealed the presence of the combination of mirror image dextrocardia, PLSVA, and sick sinus syndrome. The complex structural anomalies presented great technical challenges for interventional treatments. After thorough examination and understanding of the structural anatomy and anomalies of the superior and inferior vena cava and cardiac chambers, we successfully treated this patient by implanting a VVI pacemaker. Conclusion: Physicians must be aware of the complexity of the morphological and anatomical structures of dextrocardia accompanying PLSVC. Given that the diagnosis of situs inversus was performed at a relatively advanced age, it is therefore important to make such a correct diagnosis followed by appropriate therapeutic intervention. PMID:28151908

The Role of Linear Acceleration in Visual-Vestibular Interactions and Implications in Aircraft Operations

NASA Technical Reports Server (NTRS)

Correia, Manning J.; Luke, Brian L.; McGrath, Braden J.; Clark, John B.; Rupert, Angus H.

1996-01-01

While considerable attention has been given to visual-vestibular interaction (VVI) during angular motion of the head as might occur during an aircraft spin, much less attention has been given to VVI during linear motion of the head. Such interaction might occur, for example, while viewing a stationary or moving display during vertical take-off and landing operations Research into linear VVI, particularly during prolonged periods of linear acceleration, has been hampered by the unavailability of a programmable translator capable of large excursions We collaborated with Otis Elevator Co. and used their research tower and elevator, whose motion could be digitally programmed, to vertically translate human subjects over a distance of 92.3 meters with a peak linear acceleration of 2 meters/sec(exp 2) During pulsatile or sinusoidal translation, the subjects viewed moving stripes (optokinetic stimulus) or a fixed point source (light emitting diode, led, display), respectively and it was generally found that. The direction of linear acceleration relative to the cardinal head axes and the direction of the slow component of optokinetic nystagmus (OKN) determined the extent of VVI during concomitant stripe motion and linear acceleration. Acceleration along the z head axis (A(sub z)) produced the largest VVI, particularly when the slow component of OKN was in the same direction as eye movements produced by the linear acceleration and Eye movements produced by linear acceleration are suppressed by viewing a fixed target at frequencies below 10 Hz But, above this frequency the suppression produced by VVI is removed. Finally, as demonstrated in non-human primates, vergence of the eyes appears to modulate the vertical eye movement response to linear acceleration in humans.

[Atrial fibrillation before and after pacemaker implantation (WI and DDD) in patients with complete atrioventricular block].

PubMed

Matusik, Paweł; Woznica, Natalia; Lelakowsk, Jacek

2010-05-01

Atrial fibrillation (AF) is a frequent problem of patients with pacemakers, and depends not only on disease but also on stimulation method. The aim of the study was to estimate the prevalence of AF before and after pacemaker implantation as well as to assess the influence of VVI and DDD cardiac pacing on onset of AF in patients with complete atrioventricularblock (AVB). We included 155 patients controlled between 2000 and 2008 in Pacemaker Clinic because of AVB III degree, treated with VVI or DDD pacemaker implantation. Information about the health status of the patients was gathered from medical documentation and analysis of clinical ambulatory electrocardiograms. The study group comprised of 68 women and 87 men, mean age 68.7 +/- 13.9 years during implantation. 69% of patients had VVI pacemaker. There were 72.3% of patients with sinus rhythm before pacemaker implantation. During follow-up 4 +/- 2.8 years in 19.6% cases onset of atrial fibrillation de novo was diagnosed (in 31.3% in VVI mode vs. 2.2% in DDD mode; p = 0.00014). Mean time to AF since implantation was approximately 2.5 years. In VVI group (21 persons) amounted 32.1 months, while in 1 patient with DDD pacemaker 18 months. Between group with AF after implantation and with sinus rhythm preserved there was no statistically significant difference in age or gender (p = 0.89512 and p = 0.1253, respectively). Prevalence of atrial fibrillation after pacemaker implantation increased to 40%. Atrial fibrillation is frequent in patients before and after pacemaker implantation, especially in patients stimulated in VVI mode. Major possibility of atrial fibrillation onset after pacemaker implantation should result in more attention during routine ECG examination.

Insights into the Role of the Berry-Specific Ethylene Responsive Factor VviERF045

PubMed Central

Leida, Carmen; Dal Rì, Antonio; Dalla Costa, Lorenza; Gómez, Maria D.; Pompili, Valerio; Sonego, Paolo; Engelen, Kristof; Masuero, Domenico; Ríos, Gabino; Moser, Claudio

2016-01-01

During grape ripening, numerous transcriptional and metabolic changes are required in order to obtain colored, sweet, and flavored berries. There is evidence that ethylene, together with other signals, plays an important role in triggering the onset of ripening. Here, we report the functional characterization of a berry-specific Ethylene Responsive Factor (ERF), VviERF045, which is induced just before véraison and peaks at ripening. Phylogenetic analysis revealed it is close to the SHINE clade of ERFs, factors involved in the regulation of wax biosynthesis and cuticle morphology. Transgenic grapevines lines overexpressing VviERF045 were obtained, in vitro propagated, phenotypically characterized, and analyzed for the content of specific classes of metabolites. The effect of VviERF045 was correlated with the level of transgene expression, with high-expressing lines showing stunted growth, discolored and smaller leaves, and a lower level of chlorophylls and carotenoids. One line with intermediate expression, L15, was characterized at the transcriptomic level and showed 573 differentially expressed genes compared to wild type plants. Microscopy and gene expression analyses point toward a major role of VviERF045 in epidermis patterning by acting on waxes and cuticle. They also indicate that VviERF045 affects phenolic secondary metabolism and induces a reaction resembling a plant immune response with modulation of receptor like-kinases and pathogen related genes. These results suggest also a possible role of this transcription factor in berry ripening, likely related to changes in epidermis and cuticle of the berry, cell expansion, a decrease in photosynthetic capacity, and the activation of several defense related genes as well as from the phenylpropanoid metabolism. All these processes occur in the berry during ripening. PMID:28018369

The stimulation of the vaginal immune system with short-term administration of a vaginal gel containing fraction of Propionibacterium acnes, hyaluronic acid and polycarbophil is efficacious in vaginal infections dependent on disorders in the vaginal ecosystem.

PubMed

Melis, Gian Benedetto; Piras, Bruno; Marotto, Maria Francesca; Neri, Manuela; Corda, Valentina; Vallerino, Valerio; Saba, Alessandra; Lello, Stefano; Pilloni, Monica; Zedda, Pierina; Paoletti, Anna Maria; Mais, Valerio

2018-04-12

The vaginal immune system (VIS) is the first defense against antigens recognized as foreign. Substances capable of locally activating the VIS could be a valid strategy to treat vulvo-vaginal infections (VVI), caused by changes in the vaginal ecosystem, such as bacterial vaginosis (BV), vulvo-vaginal candidiasis (CA), and mixed vaginitis (MV). Bacterial lysates, obtained by crushing bacterial cultures, exert immuno-modulatory activities. The parietal fraction from Propionibacterium acnes is a patent of Depofarma (MoglianoVeneto, Italy). The preparation that associates such fraction to hyaluronic acid and polycarbophil is a registered trademark, commercially available in Italy as vaginal gel, Immunovag ® . The study aimed to evaluate whether a 5-day-treatment with Immunovag ® improves the symptoms and signs of VVI, in 60 women with Gardnerella vaginalis (GV), 154 with CA, 95 with MV, diagnosed with vulvar vaginal swab (VVS), and in 283 with BV, diagnosed with the Amsel criteria. At the end of the treatment (visit 2), the symptoms and signs of VVI disappeared in a significant number of subjects (χ 2 p < .02 vs pre-treatment) in all VVI groups, and their intensity was significantly (p < .0002) reduced in the subjects in which they were still present. Immunovag ® represents a valid treatment of VVI induced by changes in the vaginal ecosystem.

Characterization of a Thermo-Inducible Chlorophyll-Deficient Mutant in Barley.

PubMed

Wang, Rong; Yang, Fei; Zhang, Xiao-Qi; Wu, Dianxin; Tan, Cong; Westcott, Sharon; Broughton, Sue; Li, Chengdao; Zhang, Wenying; Xu, Yanhao

2017-01-01

Leaf color is an important trait for not only controlling crop yield but also monitoring plant status under temperature stress. In this study, a thermo-inducible chlorophyll-deficient mutant, named V-V-Y, was identified from a gamma-radiated population of the barley variety Vlamingh. The leaves of the mutant were green under normal growing temperature but turned yellowish under high temperature in the glasshouse experiment. The ratio of chlorophyll a and chlorophyll b in the mutant declined much faster in the first 7-9 days under heat treatment. The leaves of V-V-Y turned yellowish but took longer to senesce under heat stress in the field experiment. Genetic analysis indicated that a single nuclear gene controlled the mutant trait. The mutant gene ( vvy ) was mapped to the long arm of chromosome 4H between SNP markers 1_0269 and 1_1531 with a genetic distance of 2.2 cM and a physical interval of 9.85 Mb. A QTL for grain yield was mapped to the same interval and explained 10.4% of the yield variation with a LOD score of 4. This QTL is coincident with the vvy gene interval that is responsible for the thermo-inducible chlorophyll-deficient trait. Fine mapping, based on the barley reference genome sequence, further narrowed the vvy gene to a physical interval of 0.428 Mb with 11 annotated genes. This is the first report of fine mapping a thermo-inducible chlorophyll-deficient gene in barley.

Right ventricular mechanics in hypertrophic cardiomyopathy using feature tracking

PubMed Central

Badran, Hala Mahfouz; Soliman, Mahmood; Hassan, Hesham; Abdelfatah, Raed; Saadan, Haythem; Yacoub, Magdi

2013-01-01

Objectives: Right ventricular (RV) mechanics in hypertrophic cardiomyopathy (HCM) are poorly understood. We investigate global and regional deformation of the RV in HCM and its relationship to LV phenotype, using 2D strain vector velocity imaging (VVI). Methods: 100 HCM patients (42% females, 41 ± 19 years) and 30 control patients were studied using VVI. Longitudinal peak systolic strain (ϵsys), strain rate (SR), time to peak (ϵ) (TTP), displacement of RV free wall (RVFW) and septal wall were analyzed. Similar parameters were quantified in LV septal, lateral, anterior and inferior segments. Intra-V-delay was defined as SD of TTP. Inter-V-delay was estimated from TTP difference between the most delayed LV segment & RVFW. Results: ϵsys and SR of both RV & LV, showed loss of base to apex gradient and significant decline in HCM (p < 0.001). Deformation variables estimated from RVFW were strongly correlated with each other (r = 0.93, p < 0.0001). Both were directly related to LV ϵsys, SRsys, SRe, ejection fraction (EF)%, RVFW displacement (P < 0.001) and inversely related to age, positive family history (p < 0.004, 0.005), RV wall thickness, maximum wall thickness (MWT), intra-V-delay, LA volume (P < 0.0001), LVOT gradient (p < 0.02, 0.005) respectively. ROC curves were constructed to explore the cut-off point that discriminates RV dysfunction. Global and RVFW ϵsys: − 19.5% shows 77, 70% sensitivity & 97% specificity, SRsys: − 1.3s− 1 shows 82, 70% sensitivity & 30% specificity. Multivariate analyses revealed that RVFW displacement (β = − 0.9, p < 0.0001) and global LV SRsys (β = 5.9, p < 0.0001) are independent predictors of global RV deformation. Conclusions: Impairment of RV deformation is evident in HCM using feature tracking. It is independently influenced by LV mechanics and correlated to the severity of LV phenotype. RVFW deformation analysis and global RV assessment are comparable. PMID:24689019

The MADS-box gene Agamous-like 11 is essential for seed morphogenesis in grapevine.

PubMed

Malabarba, Jaiana; Buffon, Vanessa; Mariath, Jorge E A; Gaeta, Marcos L; Dornelas, Marcelo C; Margis-Pinheiro, Márcia; Pasquali, Giancarlo; Revers, Luís F

2017-03-01

Despite the wide appreciation of seedless grapes, little is known about the molecular mechanisms that drive the stenospermocarpic seedless-type phenotype in grapevine. In order to address the molecular mechanisms that control seedlessness in grapevine, our study aimed to characterize VviAGL11, a class D MADS-box transcription factor gene that has been proposed as the major candidate gene involved in Vitis vinifera seed morphogenesis. VviAGL11 allelic variations in seeded and seedless grapevine cultivars were determined, and its correlations with allele-specific steady-state mRNA levels were investigated. VviAGL11 relative expression was significantly higher in seeds at 2, 4, and 6 weeks after fruit set, whereas in the seedless grape its transcript levels were extremely low in all stages analyzed. In situ hybridization revealed transcript accumulation specifically in the dual endotesta layer of the seeds, which is responsible for elongation and an increase of cell number, a necessary step to determine the lignification and the final seed size. No hybridization signals were visible in the seedless grapevine tissues, and a morphoanatomical analysis showed an apparent loss of identity of the endotesta layer of the seed traces. Ectopic expression of VviAGL11 in the Arabidopsis SEEDSTICK mutant background restored the wild-type phenotype and confirmed the direct role of VviAGL11 in seed morphogenesis, suggesting that depletion of its expression is responsible for the erroneous development of a highly essential seed layer, therefore culminating in the typical apirenic phenotype. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Coordinator(a) de Servicios Clinicos. Parte I (Unidad I-IV). Parte II (Unidad V-VI). Guia. Documento de Trabajo (Clinical Services Coordinator. Part I. Units I-IV. Part II. Units V-VI. Guide. Working Document).

ERIC Educational Resources Information Center

Puerto Rico State Dept. of Education, Hato Rey. Area for Vocational and Technical Education.

This guide is intended for instructing secondary students in the occupation of clinical services coordinator in a hospital. The first part contains four units on the following subjects: the occupation of clinical services coordinator; interpersonal relationships; ethical/legal aspects; and communications (telephone, intercom, and others). For each…

Facial nerve hemangioma: a rare case involving the vertical segment.

PubMed

Ahmadi, Neda; Newkirk, Kenneth; Kim, H Jeffrey

2013-02-01

This case report and literature review reports on a rare case of facial nerve hemangioma (FNH) involving the vertical facial nerve (FN) segment, and discusses the clinical presentation, imaging, pathogenesis, and management of these rare lesions. A 53-year-old male presented with a 10-year history of right hemifacial twitching and progressive facial paresis (House-Brackmann grading score V/VI). The computed tomography and magnetic resonance imaging studies confirmed an expansile lesion along the vertical FN segment. Excision and histopathologic examination demonstrated FNH. FNHs involving the vertical FN segment are extremely rare. Despite being rare lesions, we believe that familiarity with the presentation and management of FNHs are imperative. Laryngoscope, 2012. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

Cardiac pacing for severe childhood neurally mediated syncope with reflex anoxic seizures

PubMed Central

McLeod, K; Wilson, N; Hewitt, J; Norrie, J; Stephenson, J

1999-01-01

OBJECTIVE—To determine whether permanent cardiac pacing could prevent syncope and seizures in children with frequent severe neurally mediated syncope, and if so whether dual chamber pacing was superior to single chamber ventricular pacing.
METHODS—Dual chamber pacemakers were implanted into 12 children (eight male, four female) aged 2-14 years (median 2.8 years) with frequent episodes of reflex anoxic seizures and a recorded prolonged asystole during an attack. The pacemaker was programmed to sensing only (ODO), single chamber ventricular pacing with hysteresis (VVI), and dual chamber pacing with rate drop response (DDD) for four month periods, with each patient allocated to one of the six possible sequences of these modes, according to chronological order of pacemaker implantation. The parent and patient were blinded to the pacemaker mode and asked to record all episodes of syncope or presyncope ("near miss" events). The doctor analysing the results was blinded to the patient and pacemaker mode.
RESULTS—One patient was withdrawn from the study after the pacemaker was removed because of infection. In the remaining children, both dual chamber and single chamber pacing significantly reduced the number of syncopal episodes compared with sensing only (p = 0.0078 for both). VVI was as effective as DDD for preventing syncope, but DDD was superior to VVI in reducing near miss events (p = 0.016).
CONCLUSIONS—Permanent pacing is an effective treatment for children with severe neurally mediated syncope and reflex anoxic seizures. VVI is as effective as DDD in preventing syncope and seizures, but DDD is superior in preventing overall symptoms.


Keywords: syncope; reflex anoxic seizures; pacing; paediatric cardiology PMID:10573501

Hernia Surgical Mesh Implants

MedlinePlus

... Surgical Clinics of North America; 83(5):1045-51, v-vi. 2 . http://www.facs.org/public_ ... FDA Contact FDA Browse by Product Area Product Areas back Food Drugs Medical Devices Radiation-Emitting Products ...

The nuclear pacemaker: Is renewed interest warranted

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

Parsonnet, V.; Berstein, A.D.; Perry, G.Y.

1990-10-01

From 1973 through 1987, 155 radioisotope-powered nuclear pacemakers were implanted in 132 patients at the Newark Beth Israel Medical Center. The longevity of the first 15 devices, all of which were fixed-rate (VOO) pacemakers, was significantly better than that of 15 lithium-chemistry demand (VVI) pacemakers used as control devices (p = 0.0002). Of the entire cohort of 155 nuclear pacemakers, 136 were VVI devices and 19 were VOO units. The patients with VOO pacemakers needed reoperations more often than did those with VVI pacemakers, chiefly for mode change (p less than 0.001). Power-source failure was observed in only 1 case,more » but 47 nuclear pacemakers were removed for other reasons, including component malfunction (15 units), mode change (12 units), high pacing thresholds (8 units) and lead or connector problems (5 units). The actuarial survival at 15 years was 99% for power sources and 82% for the entire pacing systems (pulse generators plus leads). The frequency of malignancy was similar to that of the population at large and primary tumor sites were randomly distributed. Deaths most commonly were due to cardiac causes (68%). Thus, nuclear pacemakers are safe and reliable and their greater initial cost appears to be offset by their longevity and the resulting decrease in the frequency of reoperations. It is reasonable to suggest that further use be made of long-lasting nuclear power sources for modern pacemakers and other implantable rhythm-management devices.« less

A Subdivision-Based Representation for Vector Image Editing.

PubMed

Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou

2012-11-01

Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.

Devonian of the Northern Rocky Mountains and plains

USGS Publications Warehouse

Sandberg, Charles A.; Mapel, William J.

1967-01-01

5. Undivided uppermost Devonian (Famennian, to V-VI) and lowermost Mississippian (Tournaisian, cuI-lower cuIIα) carbonaceous and clastic rocks deposited in six shallow basins interspersed among areas uplifted during the penecontemporaneous Antler orogeny.

Pressure evolution of electrical transport in the 3D topological insulator (Bi,Sb)2(Te,Se)3

NASA Astrophysics Data System (ADS)

Jeffries, Jason; Butch, N. P.; Vohra, Y. K.; Weir, S. T.

2014-03-01

The group V-VI compounds--like Bi2Se3, Sb2Te3, or Bi2Te3--have been widely studied in recent years for their bulk topological properties. The high-Z members of this series form with the same crystal structure, and are therefore amenable to isostructural substitution studies. It is possible to tune the Bi-Sb and Te-Se ratios such that the material exhibits insulating behavior, thus providing an excellent platform for understanding how a topological insulator evolves with applied pressure. We report our observations of the pressure-dependent electrical transport and compare that behavior with other binary V-VI compounds under pressure. Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under Contract DE-AC52-07NA27344.

Pacing-induced chronic atrial fibrillation impairs sinus node function in dogs. Electrophysiological remodeling.

PubMed

Elvan, A; Wylie, K; Zipes, D P

1996-12-01

We assessed the effects of pacing-induced chronic atrial fibrillation (AF) on sinus node function, intra-atrial conduction, and atrial refractoriness. In 15 mongrel dogs (20 to 30 kg), AV nodal block was produced by radiofrequency catheter ablation, and a ventricular-inhibited (VVI) pacemaker (Minix 8330, Medtronic) was implanted and programmed to pace at 80 pulses per minute. In 11 of these dogs, right atrial endocardial pacing leads were connected to a pulse generator (Itrel 7432, Medtronic) and set at a rate of 20 Hz to induce AF. Corrected sinus node recovery time, P-wave duration, 24-hour Holter ECG to assess AF duration, maximal heart rate in response to isoproterenol (10 micrograms/min), intrinsic heart rate after administration of atropine (0.04 mg/kg) and propranolol (0.1 mg/kg), and atrial effective refractory periods (ERPs) were obtained at baseline (EPS-1) and after 2 to 6 weeks (EPS-2) of VVI pacing alone (n = 4) or VVI pacing and rapid atrial pacing (n = 11). At EPS-2, corrected sinus node recovery time and P-wave duration were prolonged, maximal heart rate and intrinsic heart rate were decreased, atrial ERPs were shortened, and the duration of AF was increased significantly compared with EPS-1. These changes partially reversed toward baseline 1 week after conversion to sinus rhythm. Sinus node function and AF inducibility observed in the control dogs that underwent ventricular pacing alone (n = 4) did not change. Pacing-induced chronic AF induces sinus node dysfunction, prolongs intra-atrial conduction time, shortens atrial refractoriness, and perpetuates AF, changes that reverse gradually after termination of AF.

Method for indexing and retrieving manufacturing-specific digital imagery based on image content

DOEpatents

Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

2004-06-15

A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

The major origin of seedless grapes is associated with a missense mutation in the MADS-box gene VviAGL11.

PubMed

Royo, Carolina; Torres-Pérez, Rafael; Mauri, Nuria; Diestro, Nieves; Cabezas, José Antonio; Marchal, Cécile; Lacombe, Thierry; Ibáñez, Javier; Tornel, Manuel; Carreño, Juan; Martínez-Zapater, José M; Carbonell-Bejerano, Pablo

2018-05-31

Seedlessness is greatly prized by consumers of fresh grapes. While stenospermocarpic seed abortion determined by the SEED DEVELOPMENT INHIBITOR (SDI) locus is the usual source of seedlessness in commercial grapevine (Vitis vinifera) cultivars, the underlying sdi mutation remains unknown. Here, we undertook an integrative approach to identify the causal mutation. Quantitative genetics and fine mapping in two 'Crimson Seedless' (CS)-derived F1 mapping populations confirmed the major effect of the SDI locus and delimited the sdi mutation to a 323-kb region on chromosome 18. RNA-seq comparing seed traces of seedless and seeds of seeded F1 individuals identified processes triggered during sdi-determined seed abortion, including activation of salicylic acid-dependent defenses. The RNA-seq dataset was investigated for candidate genes and, while no evidence for causal cis-acting regulatory mutations was detected, deleterious nucleotide changes in coding sequences of the seedless haplotype were predicted in two genes within the sdi fine mapping interval. Targeted re-sequencing of the two genes in a collection of 124 grapevine cultivars showed that only the point variation causing the Arg197Leu substitution in the seed morphogenesis regulator gene AGAMOUS-LIKE 11 (VviAGL11) was fully linked with stenospermocarpy. The concurrent post-zygotic variation identified for this missense polymorphism and seedlessness phenotype in seeded somatic variants of the original stenospermocarpic cultivar supports a causal effect. We postulate that seed abortion caused by this amino acid substitution in VviAGL11 is the major cause of seedlessness in cultivated grapevine. This information can be exploited to boost seedless grape breeding. {copyright, serif} 2018 American Society of Plant Biologists. All rights reserved.

WGE: a CRISPR database for genome engineering.

PubMed

Hodgkins, Alex; Farne, Anna; Perera, Sajith; Grego, Tiago; Parry-Smith, David J; Skarnes, William C; Iyer, Vivek

2015-09-15

The rapid development of CRISPR-Cas9 mediated genome editing techniques has given rise to a number of online and stand-alone tools to find and score CRISPR sites for whole genomes. Here we describe the Wellcome Trust Sanger Institute Genome Editing database (WGE), which uses novel methods to compute, visualize and select optimal CRISPR sites in a genome browser environment. The WGE database currently stores single and paired CRISPR sites and pre-calculated off-target information for CRISPRs located in the mouse and human exomes. Scoring and display of off-target sites is simple, and intuitive, and filters can be applied to identify high-quality CRISPR sites rapidly. WGE also provides a tool for the design and display of gene targeting vectors in the same genome browser, along with gene models, protein translation and variation tracks. WGE is open, extensible and can be set up to compute and present CRISPR sites for any genome. The WGE database is freely available at www.sanger.ac.uk/htgt/wge : vvi@sanger.ac.uk or skarnes@sanger.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Energy-conserving programming of VVI pacemakers: a telemetry-supported, long-term, follow-up study.

PubMed

Klein, H H; Knake, W

1990-06-01

Thirty patients with VVI pacemakers (Quantum 253-09, 253-19, Intermedics Inc., Freeport, TX) were observed for a mean of 65 months. Within 12 months after implantation, optimized output programming was performed in 29 patients. This included a decrease in pulse amplitude (22 patients), pulse width (4 patients), and/or pacing rate (11 patients). After 65 months postimplantation, telemetered battery voltage and battery impedance were compared with the predicted values expected when the pulse generator constantly stimulates at nominal program conditions (heart rate 72.3 beats/min, pulse amplitude 5.4 V, pulse width 0.61 ms). Instead of an expected cell voltage of 2.6 V and a cell impedance of 10 k omega mean telemetered values amounted to 2.78 V and 1.4 k omega, respectively. These data correspond to a battery age of 12-15 months at nominal program conditions. This long-term follow-up study suggests that adequate programming will extend battery longevity and thus pulse generator survival in many patients.

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

Gilkey, Lindsay

This milestone presents a demonstration of the High-to-Low (Hi2Lo) process in the VVI focus area. Validation and additional calculations with the commercial computational fluid dynamics code, STAR-CCM+, were performed using a 5x5 fuel assembly with non-mixing geometry and spacer grids. This geometry was based on the benchmark experiment provided by Westinghouse. Results from the simulations were compared to existing experimental data and to the subchannel thermal-hydraulics code COBRA-TF (CTF). An uncertainty quantification (UQ) process was developed for the STAR-CCM+ model and results of the STAR UQ were communicated to CTF. Results from STAR-CCM+ simulations were used as experimental design pointsmore » in CTF to calibrate the mixing parameter β and compared to results obtained using experimental data points. This demonstrated that CTF’s β parameter can be calibrated to match existing experimental data more closely. The Hi2Lo process for the STAR-CCM+/CTF code coupling was documented in this milestone and closely linked L3:VVI.H2LP15.01 milestone report.« less

Auto and hetero-associative memory using a 2-D optical logic gate

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor)

1992-01-01

An optical system for auto-associative and hetero-associative recall utilizing Hamming distance as the similarity measure between a binary input image vector V(sup k) and a binary image vector V(sup m) in a first memory array using an optical Exclusive-OR gate for multiplication of each of a plurality of different binary image vectors in memory by the input image vector. After integrating the light of each product V(sup k) x V(sup m), a shortest Hamming distance detection electronics module determines which product has the lowest light intensity and emits a signal that activates a light emitting diode to illuminate a corresponding image vector in a second memory array for display. That corresponding image vector is identical to the memory image vector V(sup m) in the first memory array for auto-associative recall or related to it, such as by name, for hetero-associative recall.

Grape Ripening Is Regulated by Deficit Irrigation/Elevated Temperatures According to Cluster Position in the Canopy

PubMed Central

Zarrouk, Olfa; Brunetti, Cecilia; Egipto, Ricardo; Pinheiro, Carla; Genebra, Tânia; Gori, Antonella; Lopes, Carlos M.; Tattini, Massimiliano; Chaves, M. Manuela

2016-01-01

The impact of water deficit on berry quality has been extensively investigated during the last decades. Nonetheless, there is a scarcity of knowledge on the performance of varieties exposed to a combination of high temperatures/water stress during the growing season and under vineyard conditions. The objective of this research was to investigate the effects of two irrigation regimes, sustained deficit irrigation (SDI, 30% ETc) and regulated deficit irrigation (RDI, 15% ETc) and of two cluster positions within the canopy (east- and west-exposed sides) on berry ripening in red Aragonez (Tempranillo) grapevines. The study was undertaken for two successive years in a commercial vineyard in South Portugal, monitoring the following parameters: pre-dawn leaf water potential, berry temperature, sugars, polyphenols, abscisic acid (ABA) and related metabolites. Additionally, expression patterns for different transcripts encoding for enzymes responsible for anthocyanin and ABA biosynthesis (VviUFGT, VvNCED1, VvβG1, VviHyd1, VviHyd2) were analyzed. In both years anthocyanin concentration was lower in RDI at the west side (RDIW- the hottest one) from véraison onwards, suggesting that the most severe water stress conditions exacerbated the negative impact of high temperature on anthocyanin. The down-regulation of VviUFGT expression revealed a repression of the anthocyanin synthesis in berries of RDIW, at early stages of berry ripening. At full-maturation, anthocyanin degradation products were detected, being highest at RDIW. This suggests that the negative impact of water stress and high temperature on anthocyanins results from the repression of biosynthesis at the onset of ripening and from degradation at later stages. On the other hand, berries grown under SDI displayed a higher content in phenolics than those under RDI, pointing out for the attenuation of the negative temperature effects under SDI. Irrigation regime and berry position had small effect on free-ABA concentration. However, ABA catabolism/conjugation process and ABA biosynthetic pathway were affected by water and heat stresses. This indicates the role of ABA-GE and catabolites in berry ABA homeostasis under abiotic stresses. Principal component analysis (PCA) showed that the strongest influence in berry ripening is the deficit irrigation regime, while temperature is an important variable determining the improvement or impairment of berry quality by the deficit irrigation regime. In summary, this work shows the interaction between irrigation regime and high temperature on the control of berry ripening. PMID:27895648

Grape Ripening Is Regulated by Deficit Irrigation/Elevated Temperatures According to Cluster Position in the Canopy.

PubMed

Zarrouk, Olfa; Brunetti, Cecilia; Egipto, Ricardo; Pinheiro, Carla; Genebra, Tânia; Gori, Antonella; Lopes, Carlos M; Tattini, Massimiliano; Chaves, M Manuela

2016-01-01

The impact of water deficit on berry quality has been extensively investigated during the last decades. Nonetheless, there is a scarcity of knowledge on the performance of varieties exposed to a combination of high temperatures/water stress during the growing season and under vineyard conditions. The objective of this research was to investigate the effects of two irrigation regimes, sustained deficit irrigation (SDI, 30% ET c ) and regulated deficit irrigation (RDI, 15% ET c ) and of two cluster positions within the canopy (east- and west-exposed sides) on berry ripening in red Aragonez (Tempranillo) grapevines. The study was undertaken for two successive years in a commercial vineyard in South Portugal, monitoring the following parameters: pre-dawn leaf water potential, berry temperature, sugars, polyphenols, abscisic acid (ABA) and related metabolites. Additionally, expression patterns for different transcripts encoding for enzymes responsible for anthocyanin and ABA biosynthesis ( VviUFGT, VvNCED1, Vv β G1, VviHyd1, VviHyd2 ) were analyzed. In both years anthocyanin concentration was lower in RDI at the west side (RDIW- the hottest one) from véraison onwards, suggesting that the most severe water stress conditions exacerbated the negative impact of high temperature on anthocyanin. The down-regulation of VviUFGT expression revealed a repression of the anthocyanin synthesis in berries of RDIW, at early stages of berry ripening. At full-maturation, anthocyanin degradation products were detected, being highest at RDIW. This suggests that the negative impact of water stress and high temperature on anthocyanins results from the repression of biosynthesis at the onset of ripening and from degradation at later stages. On the other hand, berries grown under SDI displayed a higher content in phenolics than those under RDI, pointing out for the attenuation of the negative temperature effects under SDI. Irrigation regime and berry position had small effect on free-ABA concentration. However, ABA catabolism/conjugation process and ABA biosynthetic pathway were affected by water and heat stresses. This indicates the role of ABA-GE and catabolites in berry ABA homeostasis under abiotic stresses. Principal component analysis (PCA) showed that the strongest influence in berry ripening is the deficit irrigation regime, while temperature is an important variable determining the improvement or impairment of berry quality by the deficit irrigation regime. In summary, this work shows the interaction between irrigation regime and high temperature on the control of berry ripening.

Content based image retrieval using local binary pattern operator and data mining techniques.

PubMed

Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

2015-01-01

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

Method for the reduction of image content redundancy in large image databases

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

Image Coding Based on Address Vector Quantization.

NASA Astrophysics Data System (ADS)

Feng, Yushu

Image coding is finding increased application in teleconferencing, archiving, and remote sensing. This thesis investigates the potential of Vector Quantization (VQ), a relatively new source coding technique, for compression of monochromatic and color images. Extensions of the Vector Quantization technique to the Address Vector Quantization method have been investigated. In Vector Quantization, the image data to be encoded are first processed to yield a set of vectors. A codeword from the codebook which best matches the input image vector is then selected. Compression is achieved by replacing the image vector with the index of the code-word which produced the best match, the index is sent to the channel. Reconstruction of the image is done by using a table lookup technique, where the label is simply used as an address for a table containing the representative vectors. A code-book of representative vectors (codewords) is generated using an iterative clustering algorithm such as K-means, or the generalized Lloyd algorithm. A review of different Vector Quantization techniques are given in chapter 1. Chapter 2 gives an overview of codebook design methods including the Kohonen neural network to design codebook. During the encoding process, the correlation of the address is considered and Address Vector Quantization is developed for color image and monochrome image coding. Address VQ which includes static and dynamic processes is introduced in chapter 3. In order to overcome the problems in Hierarchical VQ, Multi-layer Address Vector Quantization is proposed in chapter 4. This approach gives the same performance as that of the normal VQ scheme but the bit rate is about 1/2 to 1/3 as that of the normal VQ method. In chapter 5, a Dynamic Finite State VQ based on a probability transition matrix to select the best subcodebook to encode the image is developed. In chapter 6, a new adaptive vector quantization scheme, suitable for color video coding, called "A Self -Organizing Adaptive VQ Technique" is presented. In addition to chapters 2 through 6 which report on new work, this dissertation includes one chapter (chapter 1) and part of chapter 2 which review previous work on VQ and image coding, respectively. Finally, a short discussion of directions for further research is presented in conclusion.

Correlated Topic Vector for Scene Classification.

PubMed

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

A Novel Gradient Vector Flow Snake Model Based on Convex Function for Infrared Image Segmentation

PubMed Central

Zhang, Rui; Zhu, Shiping; Zhou, Qin

2016-01-01

Infrared image segmentation is a challenging topic because infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow, have several advantages in terms of infrared image segmentation. However, the GVF (Gradient Vector Flow) model also has some drawbacks including a dilemma between noise smoothing and weak edge protection, which decrease the effect of infrared image segmentation significantly. In order to solve this problem, we propose a novel generalized gradient vector flow snakes model combining GGVF (Generic Gradient Vector Flow) and NBGVF (Normally Biased Gradient Vector Flow) models. We also adopt a new type of coefficients setting in the form of convex function to improve the ability of protecting weak edges while smoothing noises. Experimental results and comparisons against other methods indicate that our proposed snakes model owns better ability in terms of infrared image segmentation than other snakes models. PMID:27775660

Method and system for non-linear motion estimation

NASA Technical Reports Server (NTRS)

Lu, Ligang (Inventor)

2011-01-01

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

Vector generator scan converter

DOEpatents

Moore, James M.; Leighton, James F.

1990-01-01

High printing speeds for graphics data are achieved with a laser printer by transmitting compressed graphics data from a main processor over an I/O (input/output) channel to a vector generator scan converter which reconstructs a full graphics image for input to the laser printer through a raster data input port. The vector generator scan converter includes a microprocessor with associated microcode memory containing a microcode instruction set, a working memory for storing compressed data, vector generator hardward for drawing a full graphic image from vector parameters calculated by the microprocessor, image buffer memory for storing the reconstructed graphics image and an output scanner for reading the graphics image data and inputting the data to the printer. The vector generator scan converter eliminates the bottleneck created by the I/O channel for transmitting graphics data from the main processor to the laser printer, and increases printer speed up to thirty fold.

Vector generator scan converter

DOEpatents

Moore, J.M.; Leighton, J.F.

1988-02-05

High printing speeds for graphics data are achieved with a laser printer by transmitting compressed graphics data from a main processor over an I/O channel to a vector generator scan converter which reconstructs a full graphics image for input to the laser printer through a raster data input port. The vector generator scan converter includes a microprocessor with associated microcode memory containing a microcode instruction set, a working memory for storing compressed data, vector generator hardware for drawing a full graphic image from vector parameters calculated by the microprocessor, image buffer memory for storing the reconstructed graphics image and an output scanner for reading the graphics image data and inputting the data to the printer. The vector generator scan converter eliminates the bottleneck created by the I/O channel for transmitting graphics data from the main processor to the laser printer, and increases printer speed up to thirty fold. 7 figs.

Combining diffusion magnetic resonance tractography with stereology highlights increased cross-cortical integration in primates.

PubMed

Charvet, Christine J; Hof, Patrick R; Raghanti, Mary Ann; Van Der Kouwe, Andre J; Sherwood, Chet C; Takahashi, Emi

2017-04-01

The isocortex of primates is disproportionately expanded relative to many other mammals, yet little is known about what the expansion of the isocortex entails for differences in cellular composition and connectivity patterns in primates. Across the depth of the isocortex, neurons exhibit stereotypical patterns of projections. Upper-layer neurons (i.e., layers II-IV) project within and across cortical areas, whereas many lower-layer pyramidal neurons (i.e., layers V-VI) favor connections to subcortical regions. To identify evolutionary changes in connectivity patterns, we quantified upper (i.e., layers II-IV)- and lower (i.e., layers V-VI)-layer neuron numbers in primates and other mammals such as rodents and carnivores. We also used MR tractography based on high-angular resolution diffusion imaging and diffusion spectrum imaging to compare anterior-to-posterior corticocortical tracts between primates and other mammals. We found that primates possess disproportionately more upper-layer neurons as well as an expansion of anterior-to-posterior corticocortical tracts compared with other mammals. Taken together, these findings demonstrate that primates deviate from other mammals in exhibiting increased cross-cortical connectivity. J. Comp. Neurol. 525:1075-1093, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines

PubMed Central

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-01-01

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately. PMID:27879843

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines.

PubMed

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-04-15

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately.

Low-rate image coding using vector quantization

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

Makur, A.

1990-01-01

This thesis deals with the development and analysis of a computationally simple vector quantization image compression system for coding monochrome images at low bit rate. Vector quantization has been known to be an effective compression scheme when a low bit rate is desirable, but the intensive computation required in a vector quantization encoder has been a handicap in using it for low rate image coding. The present work shows that, without substantially increasing the coder complexity, it is indeed possible to achieve acceptable picture quality while attaining a high compression ratio. Several modifications to the conventional vector quantization coder aremore » proposed in the thesis. These modifications are shown to offer better subjective quality when compared to the basic coder. Distributed blocks are used instead of spatial blocks to construct the input vectors. A class of input-dependent weighted distortion functions is used to incorporate psychovisual characteristics in the distortion measure. Computationally simple filtering techniques are applied to further improve the decoded image quality. Finally, unique designs of the vector quantization coder using electronic neural networks are described, so that the coding delay is reduced considerably.« less

Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization.

PubMed

Karayiannis, N B; Pai, P I

1999-02-01

This paper evaluates a segmentation technique for magnetic resonance (MR) images of the brain based on fuzzy algorithms for learning vector quantization (FALVQ). These algorithms perform vector quantization by updating all prototypes of a competitive network through an unsupervised learning process. Segmentation of MR images is formulated as an unsupervised vector quantization process, where the local values of different relaxation parameters form the feature vectors which are represented by a relatively small set of prototypes. The experiments evaluate a variety of FALVQ algorithms in terms of their ability to identify different tissues and discriminate between normal tissues and abnormalities.

Signal detection using support vector machines in the presence of ultrasonic speckle

NASA Astrophysics Data System (ADS)

Kotropoulos, Constantine L.; Pitas, Ioannis

2002-04-01

Support Vector Machines are a general algorithm based on guaranteed risk bounds of statistical learning theory. They have found numerous applications, such as in classification of brain PET images, optical character recognition, object detection, face verification, text categorization and so on. In this paper we propose the use of support vector machines to segment lesions in ultrasound images and we assess thoroughly their lesion detection ability. We demonstrate that trained support vector machines with a Radial Basis Function kernel segment satisfactorily (unseen) ultrasound B-mode images as well as clinical ultrasonic images.

Intermittent output failure of a VVI device due to the disintegration of the generator.

PubMed

Böhm, A; Kayser, S; Pintér, A; Préda, I

2001-01-01

The metal case and the header of a Biovallees Coralite 247 pacemaker fell apart in a patient resulting in syncope due to myopotential inhibition. Upon recalling our patients with that type of device, we found a similar technological failure in 11 of 16 of them. This finding warrants a consideration for recalling that Biovallees device.

What Is Language? Unit I: Language Curriculum, Levels V-VI [Grades Five and Six]; Teacher's Guide.

ERIC Educational Resources Information Center

Oregon Univ., Eugene. Oregon Elementary English Project.

Designed (1) to create an interest in the study of language, (2) to help students understand something about the characteristics of language, and (3) to show students that language is a system, Unit I of the Oregon Elementary English Project offers the following six lessons: "Are Animals Like Humans? compares human and animal communication;…

Road Signs to Writing: Language Curriculum, Grades V-VI; Teacher's Guide.

ERIC Educational Resources Information Center

Oregon Univ., Eugene. Oregon Elementary English Project.

This curriculum unit, developed by the Oregon Elementary English Project, is intended for use with fifth and sixth graders as a guide for writing. Included are discussions of the various marks of punctuation and the rules for using them, the use of capitals, writing dialog and paragraphs, and the mechanics of letter writing. The guide can be used…

Rotation invariants of vector fields from orthogonal moments

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

Yang, Bo; Kostková, Jitka; Flusser, Jan

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

Rotation invariants of vector fields from orthogonal moments

DOE PAGES

Yang, Bo; Kostková, Jitka; Flusser, Jan; ...

2017-09-11

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

Color TV: total variation methods for restoration of vector-valued images.

PubMed

Blomgren, P; Chan, T F

1998-01-01

We propose a new definition of the total variation (TV) norm for vector-valued functions that can be applied to restore color and other vector-valued images. The new TV norm has the desirable properties of 1) not penalizing discontinuities (edges) in the image, 2) being rotationally invariant in the image space, and 3) reducing to the usual TV norm in the scalar case. Some numerical experiments on denoising simple color images in red-green-blue (RGB) color space are presented.

Multiscale vector fields for image pattern recognition

NASA Technical Reports Server (NTRS)

Low, Kah-Chan; Coggins, James M.

1990-01-01

A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.

Human pose tracking from monocular video by traversing an image motion mapped body pose manifold

NASA Astrophysics Data System (ADS)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2010-01-01

Tracking human pose from monocular video sequences is a challenging problem due to the large number of independent parameters affecting image appearance and nonlinear relationships between generating parameters and the resultant images. Unlike the current practice of fitting interpolation functions to point correspondences between underlying pose parameters and image appearance, we exploit the relationship between pose parameters and image motion flow vectors in a physically meaningful way. Change in image appearance due to pose change is realized as navigating a low dimensional submanifold of the infinite dimensional Lie group of diffeomorphisms of the two dimensional sphere S2. For small changes in pose, image motion flow vectors lie on the tangent space of the submanifold. Any observed image motion flow vector field is decomposed into the basis motion vector flow fields on the tangent space and combination weights are used to update corresponding pose changes in the different dimensions of the pose parameter space. Image motion flow vectors are largely invariant to style changes in experiments with synthetic and real data where the subjects exhibit variation in appearance and clothing. The experiments demonstrate the robustness of our method (within +/-4° of ground truth) to style variance.

Page segmentation using script identification vectors: A first look

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

Hochberg, J.; Cannon, M.; Kelly, P.

1997-07-01

Document images in which different scripts, such as Chinese and Roman, appear on a single page pose a problem for optical character recognition (OCR) systems. This paper explores the use of script identification vectors in the analysis of multilingual document images. A script identification vector is calculated for each connected component in a document. The vector expresses the closest distance between the component and templates developed for each of thirteen scripts, including Arabic, Chinese, Cyrillic, and Roman. The authors calculate the first three principal components within the resulting thirteen-dimensional space for each image. By mapping these components to red, green,more » and blue, they can visualize the information contained in the script identification vectors. The visualization of several multilingual images suggests that the script identification vectors can be used to segment images into script-specific regions as large as several paragraphs or as small as a few characters. The visualized vectors also reveal distinctions within scripts, such as font in Roman documents, and kanji vs. kana in Japanese. Results are best for documents containing highly dissimilar scripts such as Roman and Japanese. Documents containing similar scripts, such as Roman and Cyrillic will require further investigation.« less

Multiple image encryption scheme based on pixel exchange operation and vector decomposition

NASA Astrophysics Data System (ADS)

Xiong, Y.; Quan, C.; Tay, C. J.

2018-02-01

We propose a new multiple image encryption scheme based on a pixel exchange operation and a basic vector decomposition in Fourier domain. In this algorithm, original images are imported via a pixel exchange operator, from which scrambled images and pixel position matrices are obtained. Scrambled images encrypted into phase information are imported using the proposed algorithm and phase keys are obtained from the difference between scrambled images and synthesized vectors in a charge-coupled device (CCD) plane. The final synthesized vector is used as an input in a random phase encoding (DRPE) scheme. In the proposed encryption scheme, pixel position matrices and phase keys serve as additional private keys to enhance the security of the cryptosystem which is based on a 4-f system. Numerical simulations are presented to demonstrate the feasibility and robustness of the proposed encryption scheme.

Semi-automatic feedback using concurrence between mixture vectors for general databases

NASA Astrophysics Data System (ADS)

Larabi, Mohamed-Chaker; Richard, Noel; Colot, Olivier; Fernandez-Maloigne, Christine

2001-12-01

This paper describes how a query system can exploit the basic knowledge by employing semi-automatic relevance feedback to refine queries and runtimes. For general databases, it is often useless to call complex attributes, because we have not sufficient information about images in the database. Moreover, these images can be topologically very different from one to each other and an attribute that is powerful for a database category may be very powerless for the other categories. The idea is to use very simple features, such as color histogram, correlograms, Color Coherence Vectors (CCV), to fill out the signature vector. Then, a number of mixture vectors is prepared depending on the number of very distinctive categories in the database. Knowing that a mixture vector is a vector containing the weight of each attribute that will be used to compute a similarity distance. We post a query in the database using successively all the mixture vectors defined previously. We retain then the N first images for each vector in order to make a mapping using the following information: Is image I present in several mixture vectors results? What is its rank in the results? These informations allow us to switch the system on an unsupervised relevance feedback or user's feedback (supervised feedback).

Object recognition of real targets using modelled SAR images

NASA Astrophysics Data System (ADS)

Zherdev, D. A.

2017-12-01

In this work the problem of recognition is studied using SAR images. The algorithm of recognition is based on the computation of conjugation indices with vectors of class. The support subspaces for each class are constructed by exception of the most and the less correlated vectors in a class. In the study we examine the ability of a significant feature vector size reduce that leads to recognition time decrease. The images of targets form the feature vectors that are transformed using pre-trained convolutional neural network (CNN).

Long Detection Programming in Single-Chamber Defibrillators Reduces Unnecessary Therapies and Mortality: The ADVANCE III Trial.

PubMed

Gasparini, Maurizio; Lunati, Maurizio G; Proclemer, Alessandro; Arenal, Angel; Kloppe, Axel; Martínez Ferrer, Josè B; Hersi, Ahmad S; Gulaj, Marcin; Wijffels, Maurits C E; Santi, Elisabetta; Manotta, Laura; Varma, Niraj

2017-11-01

This study sought to evaluate the effects of programming a long detection in single-chamber (VVI) implantable cardioverter-defibrillators (ICDs) in the multicenter prospective ADVANCE III (Avoid DeliVering TherApies for Non-sustained Arrhythmias in ICD PatiEnts III) trial. Programming strategies may reduce unnecessary ICD shocks and their adverse effects but to date have been described only for dual-chamber ICDs. A total of 545 subjects (85% male; atrial fibrillation 25%, left ventricular ejection fraction 31%, ischemic etiology 68%, secondary prevention indications 32%) receiving a VVI ICD were randomized to long detection (30 of 40 intervals) or standard programming (18 of 24 intervals) based on device type, atrial fibrillation history, and indication. In both arms, antitachycardia pacing (ATP) therapy during charging was programmed for episodes with cycle length 320 to 200 ms and shock only for cycle length <200 ms. Wavelet and stability functions enabled. Therapies delivered were compared using a negative binomial regression model. A total of 267 patients were randomized to long detection and 278 to the control group. Median follow-up was 12 months. One hundred twelve therapies (shocks and ATP) occurred in the long detection arm versus 257 in the control arm, for a 48% reduction with 30 of 40 intervals (95% confidence interval [CI]: 0.36 to 0.76; p = 0.002). In the long detection arm, overall shocks were reduced by 40% compared to the control arm (48 vs. 24; 95% CI: 0.38 to 0.94; p = 0.026) and appropriate shocks by 51% (34 vs. 74; 95% CI: 0.26 to 0.94; p = 0.033). Syncopal events did not differ between arms, but survival improved in the long detection arm. Among patients implanted with a VVI ICD, programming with the long detection interval significantly reduced appropriate therapies, shocks, and all-cause mortality. (Avoid DeliVering TherApies for Non-sustained Arrhythmias in ICD PatiEnts III [ADVANCEIII]; NCT00617175). Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

CTF (Subchannel) Calculations and Validation L3:VVI.H2L.P15.01

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

Gordon, Natalie

The goal of the Verification and Validation Implementation (VVI) High to Low (Hi2Lo) process is utilizing a validated model in a high resolution code to generate synthetic data for improvement of the same model in a lower resolution code. This process is useful in circumstances where experimental data does not exist or it is not sufficient in quantity or resolution. Data from the high-fidelity code is treated as calibration data (with appropriate uncertainties and error bounds) which can be used to train parameters that affect solution accuracy in the lower-fidelity code model, thereby reducing uncertainty. This milestone presents a demonstrationmore » of the Hi2Lo process derived in the VVI focus area. The majority of the work performed herein describes the steps of the low-fidelity code used in the process with references to the work detailed in the companion high-fidelity code milestone (Reference 1). The CASL low-fidelity code used to perform this work was Cobra Thermal Fluid (CTF) and the high-fidelity code was STAR-CCM+ (STAR). The master branch version of CTF (pulled May 5, 2017 – Reference 2) was utilized for all CTF analyses performed as part of this milestone. The statistical and VVUQ components of the Hi2Lo framework were performed using Dakota version 6.6 (release date May 15, 2017 – Reference 3). Experimental data from Westinghouse Electric Company (WEC – Reference 4) was used throughout the demonstrated process to compare with the high-fidelity STAR results. A CTF parameter called Beta was chosen as the calibration parameter for this work. By default, Beta is defined as a constant mixing coefficient in CTF and is essentially a tuning parameter for mixing between subchannels. Since CTF does not have turbulence models like STAR, Beta is the parameter that performs the most similar function to the turbulence models in STAR. The purpose of the work performed in this milestone is to tune Beta to an optimal value that brings the CTF results closer to those measured in the WEC experiments.« less

SU-E-J-45: The Correlation Between CBCT Flat Panel Misalignment and 3D Image Guidance Accuracy

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

Kenton, O; Valdes, G; Yin, L

Purpose To simulate the impact of CBCT flat panel misalignment on the image quality, the calculated correction vectors in 3D image guided proton therapy and to determine if these calibration errors can be caught in our QA process. Methods The X-ray source and detector geometrical calibration (flexmap) file of the CBCT system in the AdaPTinsight software (IBA proton therapy) was edited to induce known changes in the rotational and translational calibrations of the imaging panel. Translations of up to ±10 mm in the x, y and z directions (see supplemental) and rotational errors of up to ±3° were induced. Themore » calibration files were then used to reconstruct the CBCT image of a pancreatic patient and CatPhan phantom. Correction vectors were calculated for the patient using the software’s auto match system and compared to baseline values. The CatPhan CBCT images were used for quantitative evaluation of image quality for each type of induced error. Results Translations of 1 to 3 mm in the x and y calibration resulted in corresponding correction vector errors of equal magnitude. Similar 10mm shifts were seen in the y-direction; however, in the x-direction, the image quality was too degraded for a match. These translational errors can be identified through differences in isocenter from orthogonal kV images taken during routine QA. Errors in the z-direction had no effect on the correction vector and image quality.Rotations of the imaging panel calibration resulted in corresponding correction vector rotations of the patient images. These rotations also resulted in degraded image quality which can be identified through quantitative image quality metrics. Conclusion Misalignment of CBCT geometry can lead to incorrect translational and rotational patient correction vectors. These errors can be identified through QA of the imaging isocenter as compared to orthogonal images combined with monitoring of CBCT image quality.« less

Switching non-local vector median filter

NASA Astrophysics Data System (ADS)

Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji

2016-04-01

This paper describes a novel image filtering method that removes random-valued impulse noise superimposed on a natural color image. In impulse noise removal, it is essential to employ a switching-type filtering method, as used in the well-known switching median filter, to preserve the detail of an original image with good quality. In color image filtering, it is generally preferable to deal with the red (R), green (G), and blue (B) components of each pixel of a color image as elements of a vectorized signal, as in the well-known vector median filter, rather than as component-wise signals to prevent a color shift after filtering. By taking these fundamentals into consideration, we propose a switching-type vector median filter with non-local processing that mainly consists of a noise detector and a noise removal filter. Concretely, we propose a noise detector that proactively detects noise-corrupted pixels by focusing attention on the isolation tendencies of pixels of interest not in an input image but in difference images between RGB components. Furthermore, as the noise removal filter, we propose an extended version of the non-local median filter, we proposed previously for grayscale image processing, named the non-local vector median filter, which is designed for color image processing. The proposed method realizes a superior balance between the preservation of detail and impulse noise removal by proactive noise detection and non-local switching vector median filtering, respectively. The effectiveness and validity of the proposed method are verified in a series of experiments using natural color images.

Applications of lentiviral vectors in molecular imaging.

PubMed

Chatterjee, Sushmita; De, Abhijit

2014-06-01

Molecular imaging provides the ability of simultaneous visual and quantitative estimation of long term gene expression directly from living organisms. To reveal the kinetics of gene expression by imaging method, often sustained expression of the transgene is required. Lentiviral vectors have been extensively used over last fifteen years for delivery of a transgene in a wide variety of cell types. Lentiviral vectors have the well known advantages such as sustained transgene delivery through stable integration into the host genome, the capability of infecting non-dividing and dividing cells, broad tissue tropism, a reasonably large carrying capacity for delivering therapeutic and reporter gene combinations. Additionally, they do not express viral proteins during transduction, have a potentially safe integration site profile, and a relatively easy system for vector manipulation and infective viral particle production. As a result, lentiviral vector mediated therapeutic and imaging reporter gene delivery to various target organs holds promise for the future treatment. In this review, we have conducted a brief survey of important lentiviral vector developments in diverse biomedical fields including reproductive biology.

Patch-based image reconstruction for PET using prior-image derived dictionaries

NASA Astrophysics Data System (ADS)

Tahaei, Marzieh S.; Reader, Andrew J.

2016-09-01

In PET image reconstruction, regularization is often needed to reduce the noise in the resulting images. Patch-based image processing techniques have recently been successfully used for regularization in medical image reconstruction through a penalized likelihood framework. Re-parameterization within reconstruction is another powerful regularization technique in which the object in the scanner is re-parameterized using coefficients for spatially-extensive basis vectors. In this work, a method for extracting patch-based basis vectors from the subject’s MR image is proposed. The coefficients for these basis vectors are then estimated using the conventional MLEM algorithm. Furthermore, using the alternating direction method of multipliers, an algorithm for optimizing the Poisson log-likelihood while imposing sparsity on the parameters is also proposed. This novel method is then utilized to find sparse coefficients for the patch-based basis vectors extracted from the MR image. The results indicate the superiority of the proposed methods to patch-based regularization using the penalized likelihood framework.

Adaptive marginal median filter for colour images.

PubMed

Morillas, Samuel; Gregori, Valentín; Sapena, Almanzor

2011-01-01

This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.

Time-varying behavior of motion vectors in vection-induced images in relation to autonomic regulation.

PubMed

Kiryu, Tohru; Yamada, Hiroshi; Jimbo, Masahiro; Bando, Takehiko

2004-01-01

Virtual reality (VR) is a promising technology in biomedical engineering, but at the same time enlarges another problem called cybersickness. Aiming at suppression of cybersicknes, we are investigating the influences of vection-induced images on the autonomic regulation quantitatively. We used the motion vectors to quantify image scenes and measured electrocardiogram, blood pressure, and respiration for evaluating the autonomic regulation. Using the estimated motion vectors, we further synthesized random-dot pattern images to survey which component of the global motion vectors seriously affected the autonomic regulation. The results showed that the zoom component with a specific frequency band (0.1-3.0 Hz) would induce sickness.

SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

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

Jaskowiak, J; Ahmad, S; Ali, I

Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were usedmore » to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased significantly and that limited image quality and poor correlation between the motion amplitude and DVF was obtained.« less

Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

GPU Accelerated Vector Median Filter

NASA Technical Reports Server (NTRS)

Aras, Rifat; Shen, Yuzhong

2011-01-01

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

Stokes vector based interpolation method to improve the efficiency of bio-inspired polarization-difference imaging in turbid media

NASA Astrophysics Data System (ADS)

Guan, Jinge; Ren, Wei; Cheng, Yaoyu

2018-04-01

We demonstrate an efficient polarization-difference imaging system in turbid conditions by using the Stokes vector of light. The interaction of scattered light with the polarizer is analyzed by the Stokes-Mueller formalism. An interpolation method is proposed to replace the mechanical rotation of the polarization axis of the analyzer theoretically, and its performance is verified by the experiment at different turbidity levels. We show that compared with direct imaging, the Stokes vector based imaging method can effectively reduce the effect of light scattering and enhance the image contrast.

Manifolds for pose tracking from monocular video

NASA Astrophysics Data System (ADS)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2015-03-01

We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).

[Lymphoscintigrams with anatomical landmarks obtained with vector graphics].

PubMed

Rubini, Giuseppe; Antonica, Filippo; Renna, Maria Antonia; Ferrari, Cristina; Iuele, Francesca; Stabile Ianora, Antonio Amato; Losco, Matteo; Niccoli Asabella, Artor

2012-11-01

Nuclear medicine images are difficult to interpret because they do not include anatomical details. The aim of this study was to obtain lymphoscintigrams with anatomical landmarks that could be easily interpreted by General Physicians. Traditional lymphoscintigrams were processed with Adobe© Photoshop® CS6 and converted into vector images created by Illustrator®. The combination with a silhouette vector improved image interpretation, without resulting in longer radiation exposure or acquisition times.

A human neurodevelopmental model for Williams syndrome.

PubMed

Chailangkarn, Thanathom; Trujillo, Cleber A; Freitas, Beatriz C; Hrvoj-Mihic, Branka; Herai, Roberto H; Yu, Diana X; Brown, Timothy T; Marchetto, Maria C; Bardy, Cedric; McHenry, Lauren; Stefanacci, Lisa; Järvinen, Anna; Searcy, Yvonne M; DeWitt, Michelle; Wong, Wenny; Lai, Philip; Ard, M Colin; Hanson, Kari L; Romero, Sarah; Jacobs, Bob; Dale, Anders M; Dai, Li; Korenberg, Julie R; Gage, Fred H; Bellugi, Ursula; Halgren, Eric; Semendeferi, Katerina; Muotri, Alysson R

2016-08-18

Williams syndrome is a genetic neurodevelopmental disorder characterized by an uncommon hypersociability and a mosaic of retained and compromised linguistic and cognitive abilities. Nearly all clinically diagnosed individuals with Williams syndrome lack precisely the same set of genes, with breakpoints in chromosome band 7q11.23 (refs 1-5). The contribution of specific genes to the neuroanatomical and functional alterations, leading to behavioural pathologies in humans, remains largely unexplored. Here we investigate neural progenitor cells and cortical neurons derived from Williams syndrome and typically developing induced pluripotent stem cells. Neural progenitor cells in Williams syndrome have an increased doubling time and apoptosis compared with typically developing neural progenitor cells. Using an individual with atypical Williams syndrome, we narrowed this cellular phenotype to a single gene candidate, frizzled 9 (FZD9). At the neuronal stage, layer V/VI cortical neurons derived from Williams syndrome were characterized by longer total dendrites, increased numbers of spines and synapses, aberrant calcium oscillation and altered network connectivity. Morphometric alterations observed in neurons from Williams syndrome were validated after Golgi staining of post-mortem layer V/VI cortical neurons. This model of human induced pluripotent stem cells fills the current knowledge gap in the cellular biology of Williams syndrome and could lead to further insights into the molecular mechanism underlying the disorder and the human social brain.

A human neurodevelopmental model for Williams syndrome

PubMed Central

Chailangkarn, Thanathom; Trujillo, Cleber A.; Freitas, Beatriz C.; Hrvoj-Mihic, Branka; Herai, Roberto H.; Yu, Diana X.; Brown, Timothy T.; Marchetto, Maria C. N.; Bardy, Cedric; McHenry, Lauren; Stefanacci, Lisa; Järvinen, Anna; Searcy, Yvonne M.; DeWitt, Michelle; Wong, Wenny; Lai, Philip; Ard, M. Colin; Hanson, Kari L.; Romero, Sarah; Jacobs, Bob; Dale, Anders M.; Dai, Li; Korenberg, Julie R.; Gage, Fred H.; Bellugi, Ursula; Halgren, Eric; Semendeferi, Katerina; Muotri, Alysson R.

2016-01-01

Summary Williams syndrome (WS) is a genetic neurodevelopmental disorder characterized by an uncommon hypersociability and a mosaic of retained and compromised linguistic and cognitive abilities. Nearly all clinically diagnosed individuals with WS lack precisely the same set of genes, with breakpoints in chromosome band 7q11.231–5. The contribution of specific genes to the neuroanatomical and functional alterations, leading to behavioral pathologies in humans, remains largely unexplored. Here, we investigate neural progenitor cells (NPCs) and cortical neurons derived from WS and typically developing (TD) induced pluripotent stem cells (iPSCs). WS NPCs have an increased doubling time and apoptosis compared to TD NPCs. Using an atypical WS subject6, 7, we narrowed this cellular phenotype to a single gene candidate, FZD9. At the neuronal stage, WS-derived layers V/VI cortical neurons were characterized by longer total dendrites, increased numbers of spines and synapses, aberrant calcium oscillation and altered network connectivity. Morphometric alterations observed in WS neurons were validated after Golgi staining of postmortem layers V/VI cortical neurons. This human iPSC model8 fills in the current knowledge gap in WS cellular biology and could lead to further insights into the molecular mechanism underlying the disorder and the human social brain. PMID:27509850

Efficacy of early physical therapy in severe Bell's palsy: a randomized controlled trial.

PubMed

Nicastri, Maria; Mancini, Patrizia; De Seta, Daniele; Bertoli, Gianantonio; Prosperini, Luca; Toni, Danilo; Inghilleri, Maurizio; Filipo, Roberto

2013-01-01

Bell's palsy (BP) is the most frequent form of peripheral palsy of the facial nerve. Prognosis for recovery is good for most patients; in the remaining cases, different grades of residual impairment persist. Physical therapy, in association with drug administration, aims to improve outcomes. To assess the efficacy of early physical therapy in association with standard drug administration versus pharmacological therapy only, in terms of time to maximum gains and grade of recovery of function, and to examine who will most benefit from rehabilitation. From June 2008 to May 2010, 232 individuals were evaluated. The 87 patients meeting the eligibility criteria were randomly assigned to the experimental group (prednisone and valacyclovir plus physical therapy, n = 39) or the control group (pharmacological therapy, n = 48) within 10 days of onset. Intention-to-treat analyses were done. The physical therapy had a significant effect on grade (P = .038) and time (P = .044) to recovery only in patients presenting with severe facial palsy (House-Brackmann [HB] grade V/VI). No significant differences were found between the study and control groups for outcome of synkinesis. Physical therapy appears to be effective only in the more severe BP (baseline HB grade V/VI), whereas less severe BP (baseline HB grade IV) results in complete spontaneous recovery, regardless of physical therapy.

Configurations of a two-tiered amplified gene expression system in adenoviral vectors designed to improve the specificity of in vivo prostate cancer imaging

PubMed Central

Sato, M; Figueiredo, ML; Burton, JB; Johnson, M; Chen, M; Powell, R; Gambhir, SS; Carey, M; Wu, L

2009-01-01

Effective treatment for recurrent, disseminated prostate cancer is notably limited. We have developed adenoviral vectors with a prostate-specific two-step transcriptional amplification (TSTA) system that would express therapeutic genes at a robust level to target metastatic disease. The TSTA system employs the prostate-specific antigen (PSA) promoter/enhancer to drive a potent synthetic activator, which in turn activates the expression of the therapeutic gene. In this study, we explored different configurations of this bipartite system and discovered that physical separation of the two TSTA components into E1 and E3 regions of adenovirus was able to enhance androgen regulation and cell-discriminatory expression. The TSTA vectors that express imaging reporter genes were assessed by noninvasive imaging technologies in animal models. The improved selectivity of the E1E3 configured vector was reflected in silenced ectopic expression in the lung. Significantly, the enhanced specificity of the E1E3 vector enabled the detection of lung metastasis of prostate cancer. An E1E3 TSTA vector that expresses the herpes simplex virus thymidine kinase gene can effectively direct positron emission tomography (PET) imaging of the tumor. The prostate-targeted gene delivery vectors with robust and cell-specific expression capability will advance the development of safe and effective imaging guided therapy for recurrent metastatic stages of prostate cancer. PMID:18305574

Automated vector selection of SIVQ and parallel computing integration MATLAB™: Innovations supporting large-scale and high-throughput image analysis studies.

PubMed

Cheng, Jerome; Hipp, Jason; Monaco, James; Lucas, David R; Madabhushi, Anant; Balis, Ulysses J

2011-01-01

Spatially invariant vector quantization (SIVQ) is a texture and color-based image matching algorithm that queries the image space through the use of ring vectors. In prior studies, the selection of one or more optimal vectors for a particular feature of interest required a manual process, with the user initially stochastically selecting candidate vectors and subsequently testing them upon other regions of the image to verify the vector's sensitivity and specificity properties (typically by reviewing a resultant heat map). In carrying out the prior efforts, the SIVQ algorithm was noted to exhibit highly scalable computational properties, where each region of analysis can take place independently of others, making a compelling case for the exploration of its deployment on high-throughput computing platforms, with the hypothesis that such an exercise will result in performance gains that scale linearly with increasing processor count. An automated process was developed for the selection of optimal ring vectors to serve as the predicate matching operator in defining histopathological features of interest. Briefly, candidate vectors were generated from every possible coordinate origin within a user-defined vector selection area (VSA) and subsequently compared against user-identified positive and negative "ground truth" regions on the same image. Each vector from the VSA was assessed for its goodness-of-fit to both the positive and negative areas via the use of the receiver operating characteristic (ROC) transfer function, with each assessment resulting in an associated area-under-the-curve (AUC) figure of merit. Use of the above-mentioned automated vector selection process was demonstrated in two cases of use: First, to identify malignant colonic epithelium, and second, to identify soft tissue sarcoma. For both examples, a very satisfactory optimized vector was identified, as defined by the AUC metric. Finally, as an additional effort directed towards attaining high-throughput capability for the SIVQ algorithm, we demonstrated the successful incorporation of it with the MATrix LABoratory (MATLAB™) application interface. The SIVQ algorithm is suitable for automated vector selection settings and high throughput computation.

Use of Forward Scattering Particle Image Velocimetry to Quantify a Flow Field Near a Fully Submerged Tension Leg Platform in the Presence of Waves

DTIC Science & Technology

2012-05-01

8217’�/_’ ________ __ � J "Q. F E -3 ¥-------���-------����------------ c( -6 ------------------------------- Time (s) -9...image). Figure 5: Corrected image (left) and vector diagram (right) - wave amplitude of 5.33cm (2.1in) (Wave Crest) ·( J 20 ·0 IS ·0 10 ·0 ( j ...34 ·-0.20 ··0 " -U J ( J Figure 8: Corrected image and vector diagram - wave amplitude of -4.83cm (-1.9in) Figure 9: Corrected image and vector

Measurements of wind vectors, eddy momentum transports, and energy conversions in Jupiter's atmosphere from Voyager 1 images

NASA Astrophysics Data System (ADS)

Beebe, R. F.; Ingersoll, A. P.; Hunt, G. E.; Mitchell, J. L.; Muller, J.-P.

1980-01-01

Voyager 1 narrow-angle images were used to obtain displacements of features down to 100 to 200 km in size over intervals of 10 hours. A global map of velocity vectors and longitudinally averaged zonal wind vectors as functions of the latitude, is presented and discussed

Method and System for Temporal Filtering in Video Compression Systems

NASA Technical Reports Server (NTRS)

Lu, Ligang; He, Drake; Jagmohan, Ashish; Sheinin, Vadim

2011-01-01

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

Polarization Control with Plasmonic Antenna Tips: A Universal Approach to Optical Nanocrystallography and Vector-Field Imaging

NASA Astrophysics Data System (ADS)

Park, Kyoung-Duck; Raschke, Markus B.

2018-05-01

Controlling the propagation and polarization vectors in linear and nonlinear optical spectroscopy enables to probe the anisotropy of optical responses providing structural symmetry selective contrast in optical imaging. Here we present a novel tilted antenna-tip approach to control the optical vector-field by breaking the axial symmetry of the nano-probe in tip-enhanced near-field microscopy. This gives rise to a localized plasmonic antenna effect with significantly enhanced optical field vectors with control of both \\textit{in-plane} and \\textit{out-of-plane} components. We use the resulting vector-field specificity in the symmetry selective nonlinear optical response of second-harmonic generation (SHG) for a generalized approach to optical nano-crystallography and -imaging. In tip-enhanced SHG imaging of monolayer MoS$_2$ films and single-crystalline ferroelectric YMnO$_3$, we reveal nano-crystallographic details of domain boundaries and domain topology with enhanced sensitivity and nanoscale spatial resolution. The approach is applicable to any anisotropic linear and nonlinear optical response, and provides for optical nano-crystallographic imaging of molecular or quantum materials.

Elastic and acoustic wavefield decompositions and application to reverse time migrations

NASA Astrophysics Data System (ADS)

Wang, Wenlong

P- and S-waves coexist in elastic wavefields, and separation between them is an essential step in elastic reverse-time migrations (RTMs). Unlike the traditional separation methods that use curl and divergence operators, which do not preserve the wavefield vector component information, we propose and compare two vector decomposition methods, which preserve the same vector components that exist in the input elastic wavefield. The amplitude and phase information is automatically preserved, so no amplitude or phase corrections are required. The decoupled propagation method is extended from elastic to viscoelastic wavefields. To use the decomposed P and S vector wavefields and generate PP and PS images, we create a new 2D migration context for isotropic, elastic RTM which includes PS vector decomposition; the propagation directions of both incident and reflected P- and S-waves are calculated directly from the stress and particle velocity definitions of the decomposed P- and S-wave Poynting vectors. Then an excitation-amplitude image condition that scales the receiver wavelet by the source vector magnitude produces angle-dependent images of PP and PS reflection coefficients with the correct polarities, polarization, and amplitudes. It thus simplifies the process of obtaining PP and PS angle-domain common-image gathers (ADCIGs); it is less effort to generate ADCIGs from vector data than from scalar data. Besides P- and S-waves decomposition, separations of up- and down-going waves are also a part of processing of multi-component recorded data and propagating wavefields. A complex trace based up/down separation approach is extended from acoustic to elastic, and combined with P- and S-wave decomposition by decoupled propagation. This eliminates the need for a Fourier transform over time, thereby significantly reducing the storage cost and improving computational efficiency. Wavefield decomposition is applied to both synthetic elastic VSP data and propagating wavefield snapshots. Poynting vectors obtained from the particle-velocity and stress fields after P/S and up/down decompositions are much more accurate than those without. The up/down separation algorithm is also applicable in acoustic RTMs, where both (forward-time extrapolated) source and (reverse-time extrapolated) receiver wavefields are decomposed into up-going and down-going parts. Together with the crosscorrelation imaging condition, four images (down-up, up-down, up-up and down-down) are generated, which facilitate the analysis of artifacts and the imaging ability of the four images. Artifacts may exist in all the decomposed images, but their positions and types are different. The causes of artifacts in different images are explained and illustrated with sketches and numerical tests.

Generation of HIV-1 based bi-cistronic lentiviral vectors for stable gene expression and live cell imaging.

PubMed

Sehgal, Lalit; Budnar, Srikanth; Bhatt, Khyati; Sansare, Sneha; Mukhopadhaya, Amitabha; Kalraiya, Rajiv D; Dalal, Sorab N

2012-10-01

The study of protein-protein interactions, protein localization, protein organization into higher order structures and organelle dynamics in live cells, has greatly enhanced the understanding of various cellular processes. Live cell imaging experiments employ plasmid or viral vectors to express the protein/proteins of interest fused to a fluorescent protein. Unlike plasmid vectors, lentiviral vectors can be introduced into both dividing and non dividing cells, can be pseudotyped to infect a broad or narrow range of cells, and can be used to generate transgenic animals. However, the currently available lentiviral vectors are limited by the choice of fluorescent protein tag, choice of restriction enzyme sites in the Multiple Cloning Sites (MCS) and promoter choice for gene expression. In this report, HIV-1 based bi-cistronic lentiviral vectors have been generated that drive the expression of multiple fluorescent tags (EGFP, mCherry, ECFP, EYFP and dsRed), using two different promoters. The presence of a unique MCS with multiple restriction sites allows the generation of fusion proteins with the fluorescent tag of choice, allowing analysis of multiple fusion proteins in live cell imaging experiments. These novel lentiviral vectors are improved delivery vehicles for gene transfer applications and are important tools for live cell imaging in vivo.

Vectorized image segmentation via trixel agglomeration

DOEpatents

Prasad, Lakshman [Los Alamos, NM; Skourikhine, Alexei N [Los Alamos, NM

2006-10-24

A computer implemented method transforms an image comprised of pixels into a vectorized image specified by a plurality of polygons that can be subsequently used to aid in image processing and understanding. The pixelated image is processed to extract edge pixels that separate different colors and a constrained Delaunay triangulation of the edge pixels forms a plurality of triangles having edges that cover the pixelated image. A color for each one of the plurality of triangles is determined from the color pixels within each triangle. A filter is formed with a set of grouping rules related to features of the pixelated image and applied to the plurality of triangle edges to merge adjacent triangles consistent with the filter into polygons having a plurality of vertices. The pixelated image may be then reformed into an array of the polygons, that can be represented collectively and efficiently by standard vector image.

Evaluation of a Ferroelectric Liquid Crystal Spatial Light Modulator

DTIC Science & Technology

1991-01-09

MAR 83 APR edition may be used until exhausted SECURITY CLASSIFICATION OF THIS PAGE All other edition% are obsolete UbIu.LAb F L l.D i/(ii Blank...7 VII. CONCLUSIONS.................................................. 8 Accesion For- NTIS CRA&I ~ 4Ii U, ai-;-oui iced L DiA: ibutiko: i...thin phase grating. The authors are also thankful for the assistance of Ms. Cindy Gabardi in preparing this manuscript. v/(vi Blank) 1. INTRODUCTION A

Global rotational motion and displacement estimation of digital image stabilization based on the oblique vectors matching algorithm

NASA Astrophysics Data System (ADS)

Yu, Fei; Hui, Mei; Zhao, Yue-jin

2009-08-01

The image block matching algorithm based on motion vectors of correlative pixels in oblique direction is presented for digital image stabilization. The digital image stabilization is a new generation of image stabilization technique which can obtains the information of relative motion among frames of dynamic image sequences by the method of digital image processing. In this method the matching parameters are calculated from the vectors projected in the oblique direction. The matching parameters based on the vectors contain the information of vectors in transverse and vertical direction in the image blocks at the same time. So the better matching information can be obtained after making correlative operation in the oblique direction. And an iterative weighted least square method is used to eliminate the error of block matching. The weights are related with the pixels' rotational angle. The center of rotation and the global emotion estimation of the shaking image can be obtained by the weighted least square from the estimation of each block chosen evenly from the image. Then, the shaking image can be stabilized with the center of rotation and the global emotion estimation. Also, the algorithm can run at real time by the method of simulated annealing in searching method of block matching. An image processing system based on DSP was used to exam this algorithm. The core processor in the DSP system is TMS320C6416 of TI, and the CCD camera with definition of 720×576 pixels was chosen as the input video signal. Experimental results show that the algorithm can be performed at the real time processing system and have an accurate matching precision.

Targeted systemic gene therapy and molecular imaging of cancer contribution of the vascular-targeted AAVP vector.

PubMed

Hajitou, Amin

2010-01-01

Gene therapy and molecular-genetic imaging have faced a major problem: the lack of an efficient systemic gene delivery vector. Unquestionably, eukaryotic viruses have been the vectors of choice for gene delivery to mammalian cells; however, they have had limited success in systemic gene therapy. This is mainly due to undesired uptake by the liver and reticuloendothelial system, broad tropism for mammalian cells causing toxicity, and their immunogenicity. On the other hand, prokaryotic viruses such as bacteriophage (phage) have no tropism for mammalian cells, but can be engineered to deliver genes to these cells. However, phage-based vectors have inherently been considered poor vectors for mammalian cells. We have reported a new generation of vascular-targeted systemic hybrid prokaryotic-eukaryotic vectors as chimeras between an adeno-associated virus (AAV) and targeted bacteriophage (termed AAV/phage; AAVP). In this hybrid vector, the targeted bacteriophage serves as a shuttle to deliver the AAV transgene cassette inserted in an intergenomic region of the phage DNA genome. As a proof of concept, we assessed the in vivo efficacy of vector in animal models of cancer by displaying on the phage capsid the cyclic Arg-Gly-Asp (RGD-4C) ligand that binds to alphav integrin receptors specifically expressed on the angiogenic blood vessels of tumors. The ligand-directed vector was able to specifically deliver imaging and therapeutic transgenes to tumors in mice, rats, and dogs while sparing the normal organs. This chapter reviews some gene transfer strategies and the potential of the vascular-targeted AAVP vector for enhancing the effectiveness of existing systemic gene delivery and genetic-imaging technologies. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Model-based VQ for image data archival, retrieval and distribution

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1995-01-01

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Autofocus and fusion using nonlinear correlation

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

Cabazos-Marín, Alma Rocío; Álvarez-Borrego, Josué, E-mail: josue@cicese.mx; Coronel-Beltrán, Ángel

2014-10-06

In this work a new algorithm is proposed for auto focusing and images fusion captured by microscope's CCD. The proposed algorithm for auto focusing implements the spiral scanning of each image in the stack f(x, y){sub w} to define the V{sub w} vector. The spectrum of the vector FV{sub w} is calculated by fast Fourier transform. The best in-focus image is determined by a focus measure that is obtained by the FV{sub 1} nonlinear correlation vector, of the reference image, with each other FV{sub W} images in the stack. In addition, fusion is performed with a subset of selected imagesmore » f(x, y){sub SBF} like the images with best focus measurement. Fusion creates a new improved image f(x, y){sub F} with the selection of pixels of higher intensity.« less

Method and system for the diagnosis of disease using retinal image content and an archive of diagnosed human patient data

DOEpatents

Tobin, Kenneth W; Karnowski, Thomas P; Chaum, Edward

2013-08-06

A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Medical Image Compression Based on Vector Quantization with Variable Block Sizes in Wavelet Domain

PubMed Central

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality. PMID:23049544

Medical image compression based on vector quantization with variable block sizes in wavelet domain.

PubMed

Jiang, Huiyan; Ma, Zhiyuan; Hu, Yang; Yang, Benqiang; Zhang, Libo

2012-01-01

An optimized medical image compression algorithm based on wavelet transform and improved vector quantization is introduced. The goal of the proposed method is to maintain the diagnostic-related information of the medical image at a high compression ratio. Wavelet transformation was first applied to the image. For the lowest-frequency subband of wavelet coefficients, a lossless compression method was exploited; for each of the high-frequency subbands, an optimized vector quantization with variable block size was implemented. In the novel vector quantization method, local fractal dimension (LFD) was used to analyze the local complexity of each wavelet coefficients, subband. Then an optimal quadtree method was employed to partition each wavelet coefficients, subband into several sizes of subblocks. After that, a modified K-means approach which is based on energy function was used in the codebook training phase. At last, vector quantization coding was implemented in different types of sub-blocks. In order to verify the effectiveness of the proposed algorithm, JPEG, JPEG2000, and fractal coding approach were chosen as contrast algorithms. Experimental results show that the proposed method can improve the compression performance and can achieve a balance between the compression ratio and the image visual quality.

Effective Clipart Image Vectorization through Direct Optimization of Bezigons.

PubMed

Yang, Ming; Chao, Hongyang; Zhang, Chi; Guo, Jun; Yuan, Lu; Sun, Jian

2016-02-01

Bezigons, i.e., closed paths composed of Bézier curves, have been widely employed to describe shapes in image vectorization results. However, most existing vectorization techniques infer the bezigons by simply approximating an intermediate vector representation (such as polygons). Consequently, the resultant bezigons are sometimes imperfect due to accumulated errors, fitting ambiguities, and a lack of curve priors, especially for low-resolution images. In this paper, we describe a novel method for vectorizing clipart images. In contrast to previous methods, we directly optimize the bezigons rather than using other intermediate representations; therefore, the resultant bezigons are not only of higher fidelity compared with the original raster image but also more reasonable because they were traced by a proficient expert. To enable such optimization, we have overcome several challenges and have devised a differentiable data energy as well as several curve-based prior terms. To improve the efficiency of the optimization, we also take advantage of the local control property of bezigons and adopt an overlapped piecewise optimization strategy. The experimental results show that our method outperforms both the current state-of-the-art method and commonly used commercial software in terms of bezigon quality.

Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data

NASA Astrophysics Data System (ADS)

Schäfer, D.; Lin, M.; Rao, P. P.; Loffroy, R.; Liapi, E.; Noordhoek, N.; Eshuis, P.; Radaelli, A.; Grass, M.; Geschwind, J.-F. H.

2012-03-01

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

Coastal modification of a scene employing multispectral images and vector operators.

PubMed

Lira, Jorge

2017-05-01

Changes in sea level, wind patterns, sea current patterns, and tide patterns have produced morphologic transformations in the coastline area of Tamaulipas Sate in North East Mexico. Such changes generated a modification of the coastline and variations of the texture-relief and texture of the continental area of Tamaulipas. Two high-resolution multispectral satellite Satellites Pour l'Observation de la Terre images were employed to quantify the morphologic change of such continental area. The images cover a time span close to 10 years. A variant of the principal component analysis was used to delineate the modification of the land-water line. To quantify changes in texture-relief and texture, principal component analysis was applied to the multispectral images. The first principal components of each image were modeled as a discrete bidimensional vector field. The divergence and Laplacian vector operators were applied to the discrete vector field. The divergence provided the change of texture, while the Laplacian produced the change of texture-relief in the area of study.

Fradkin-Bacry-Ruegg-Souriau perihelion vector for Gorringe-Leach equations

NASA Astrophysics Data System (ADS)

Grandati, Yves; Bérard, Alain; Mohrbach, Hervé

2010-02-01

We show that every generalized Gorringe-Leach equation admits an associated Fradkin-Bacry-Ruegg-Souriau’s vector which, in general, is only a piecewise conserved quantity. In the case of dualizable generalized Gorringe-Leach equations, which include the case of conservative motions in central power law potentials, the image sets of the FBRS vectors for dual classes are dual images of each other.

Aortic Valve Stenosis Increases Helical Flow and Flow Complexity: A Study of Intra-Operative Cardiac Vector Flow Imaging.

PubMed

Hansen, Kristoffer Lindskov; Møller-Sørensen, Hasse; Kjaergaard, Jesper; Jensen, Maiken Brit; Jensen, Jørgen Arendt; Nielsen, Michael Bachmann

2017-08-01

Aortic valve stenosis alters blood flow in the ascending aorta. Using intra-operative vector flow imaging on the ascending aorta, secondary helical flow during peak systole and diastole, as well as flow complexity of primary flow during systole, were investigated in patients with normal, stenotic and replaced aortic valves. Peak systolic helical flow, diastolic helical flow and flow complexity during systole differed between the groups (p < 0.0001), and correlated to peak systolic velocity (R = 0.94, 0.87 and 0.88, respectively). The study indicates that aortic valve stenosis increases helical flow and flow complexity, which are measurable with vector flow imaging. For assessment of aortic stenosis and optimization of valve surgery, vector flow imaging may be useful. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Application of optical correlation techniques to particle imaging velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1988-01-01

Pulsed laser sheet velocimetry yields nonintrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usually MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the partical image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.

Transcriptome analyses of the Dof-like gene family in grapevine reveal its involvement in berry, flower and seed development.

PubMed

da Silva, Danielle Costenaro; da Silveira Falavigna, Vítor; Fasoli, Marianna; Buffon, Vanessa; Porto, Diogo Denardi; Pappas, Georgios Joannis; Pezzotti, Mario; Pasquali, Giancarlo; Revers, Luís Fernando

2016-01-01

The Dof (DNA-binding with one finger) protein family spans a group of plant transcription factors involved in the regulation of several functions, such as plant responses to stress, hormones and light, phytochrome signaling and seed germination. Here we describe the Dof-like gene family in grapevine (Vitis vinifera L.), which consists of 25 genes coding for Dof. An extensive in silico characterization of the VviDofL gene family was performed. Additionally, the expression of the entire gene family was assessed in 54 grapevine tissues and organs using an integrated approach with microarray (cv Corvina) and real-time PCR (cv Pinot Noir) analyses. The phylogenetic analysis comparing grapevine sequences with those of Arabidopsis, tomato, poplar and already described Dof genes in other species allowed us to identify several duplicated genes. The diversification of grapevine DofL genes during evolution likely resulted in a broader range of biological roles. Furthermore, distinct expression patterns were identified between samples analyzed, corroborating such hypothesis. Our expression results indicate that several VviDofL genes perform their functional roles mainly during flower, berry and seed development, highlighting their importance for grapevine growth and production. The identification of similar expression profiles between both approaches strongly suggests that these genes have important regulatory roles that are evolutionally conserved between grapevine cvs Corvina and Pinot Noir.

Transcriptome analyses of the Dof-like gene family in grapevine reveal its involvement in berry, flower and seed development

PubMed Central

da Silva, Danielle Costenaro; da Silveira Falavigna, Vítor; Fasoli, Marianna; Buffon, Vanessa; Porto, Diogo Denardi; Pappas, Georgios Joannis; Pezzotti, Mario; Pasquali, Giancarlo; Revers, Luís Fernando

2016-01-01

The Dof (DNA-binding with one finger) protein family spans a group of plant transcription factors involved in the regulation of several functions, such as plant responses to stress, hormones and light, phytochrome signaling and seed germination. Here we describe the Dof-like gene family in grapevine (Vitis vinifera L.), which consists of 25 genes coding for Dof. An extensive in silico characterization of the VviDofL gene family was performed. Additionally, the expression of the entire gene family was assessed in 54 grapevine tissues and organs using an integrated approach with microarray (cv Corvina) and real-time PCR (cv Pinot Noir) analyses. The phylogenetic analysis comparing grapevine sequences with those of Arabidopsis, tomato, poplar and already described Dof genes in other species allowed us to identify several duplicated genes. The diversification of grapevine DofL genes during evolution likely resulted in a broader range of biological roles. Furthermore, distinct expression patterns were identified between samples analyzed, corroborating such hypothesis. Our expression results indicate that several VviDofL genes perform their functional roles mainly during flower, berry and seed development, highlighting their importance for grapevine growth and production. The identification of similar expression profiles between both approaches strongly suggests that these genes have important regulatory roles that are evolutionally conserved between grapevine cvs Corvina and Pinot Noir. PMID:27610237

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor.

PubMed

Liu, Zhenwang; Xu, Jiangtao; Wang, Xinlei; Nie, Kaiming; Jin, Weimin

2015-09-16

In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.

The determination of high-resolution spatio-temporal glacier motion fields from time-lapse sequences

NASA Astrophysics Data System (ADS)

Schwalbe, Ellen; Maas, Hans-Gerd

2017-12-01

This paper presents a comprehensive method for the determination of glacier surface motion vector fields at high spatial and temporal resolution. These vector fields can be derived from monocular terrestrial camera image sequences and are a valuable data source for glaciological analysis of the motion behaviour of glaciers. The measurement concepts for the acquisition of image sequences are presented, and an automated monoscopic image sequence processing chain is developed. Motion vector fields can be derived with high precision by applying automatic subpixel-accuracy image matching techniques on grey value patterns in the image sequences. Well-established matching techniques have been adapted to the special characteristics of the glacier data in order to achieve high reliability in automatic image sequence processing, including the handling of moving shadows as well as motion effects induced by small instabilities in the camera set-up. Suitable geo-referencing techniques were developed to transform image measurements into a reference coordinate system.The result of monoscopic image sequence analysis is a dense raster of glacier surface point trajectories for each image sequence. Each translation vector component in these trajectories can be determined with an accuracy of a few centimetres for points at a distance of several kilometres from the camera. Extensive practical validation experiments have shown that motion vector and trajectory fields derived from monocular image sequences can be used for the determination of high-resolution velocity fields of glaciers, including the analysis of tidal effects on glacier movement, the investigation of a glacier's motion behaviour during calving events, the determination of the position and migration of the grounding line and the detection of subglacial channels during glacier lake outburst floods.

Image segmentation using fuzzy LVQ clustering networks

NASA Technical Reports Server (NTRS)

Tsao, Eric Chen-Kuo; Bezdek, James C.; Pal, Nikhil R.

1992-01-01

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.

3D temporal subtraction on multislice CT images using nonlinear warping technique

NASA Astrophysics Data System (ADS)

Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio

2007-03-01

The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.

Feature detection in satellite images using neural network technology

NASA Technical Reports Server (NTRS)

Augusteijn, Marijke F.; Dimalanta, Arturo S.

1992-01-01

A feasibility study of automated classification of satellite images is described. Satellite images were characterized by the textures they contain. In particular, the detection of cloud textures was investigated. The method of second-order gray level statistics, using co-occurrence matrices, was applied to extract feature vectors from image segments. Neural network technology was employed to classify these feature vectors. The cascade-correlation architecture was successfully used as a classifier. The use of a Kohonen network was also investigated but this architecture could not reliably classify the feature vectors due to the complicated structure of the classification problem. The best results were obtained when data from different spectral bands were fused.

Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design

PubMed Central

Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco

2016-01-01

The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms. PMID:27886061

Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design.

PubMed

Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco

2016-11-23

The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms.

Road Damage Extraction from Post-Earthquake Uav Images Assisted by Vector Data

NASA Astrophysics Data System (ADS)

Chen, Z.; Dou, A.

2018-04-01

Extraction of road damage information after earthquake has been regarded as urgent mission. To collect information about stricken areas, Unmanned Aerial Vehicle can be used to obtain images rapidly. This paper put forward a novel method to detect road damage and bring forward a coefficient to assess road accessibility. With the assistance of vector road data, image data of the Jiuzhaigou Ms7.0 Earthquake is tested. In the first, the image is clipped according to vector buffer. Then a large-scale segmentation is applied to remove irrelevant objects. Thirdly, statistics of road features are analysed, and damage information is extracted. Combining with the on-filed investigation, the extraction result is effective.

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

NASA Technical Reports Server (NTRS)

Jaggi, S.

1993-01-01

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Word-level recognition of multifont Arabic text using a feature vector matching approach

NASA Astrophysics Data System (ADS)

Erlandson, Erik J.; Trenkle, John M.; Vogt, Robert C., III

1996-03-01

Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. An alternative approach is to recognize text imagery at the word level, without analyzing individual characters. This approach avoids the problem of individual character segmentation, and can overcome local errors in character recognition. A word-level recognition system for machine-printed Arabic text has been implemented. Arabic is a script language, and is therefore difficult to segment at the character level. Character segmentation has been avoided by recognizing text imagery of complete words. The Arabic recognition system computes a vector of image-morphological features on a query word image. This vector is matched against a precomputed database of vectors from a lexicon of Arabic words. Vectors from the database with the highest match score are returned as hypotheses for the unknown image. Several feature vectors may be stored for each word in the database. Database feature vectors generated using multiple fonts and noise models allow the system to be tuned to its input stream. Used in conjunction with database pruning techniques, this Arabic recognition system has obtained promising word recognition rates on low-quality multifont text imagery.

Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

PubMed

Hipp, Jason D; Cheng, Jerome Y; Toner, Mehmet; Tompkins, Ronald G; Balis, Ulysses J

2011-02-26

HISTORICALLY, EFFECTIVE CLINICAL UTILIZATION OF IMAGE ANALYSIS AND PATTERN RECOGNITION ALGORITHMS IN PATHOLOGY HAS BEEN HAMPERED BY TWO CRITICAL LIMITATIONS: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Subband directional vector quantization in radiological image compression

NASA Astrophysics Data System (ADS)

Akrout, Nabil M.; Diab, Chaouki; Prost, Remy; Goutte, Robert; Amiel, Michel

1992-05-01

The aim of this paper is to propose a new scheme for image compression. The method is very efficient for images which have directional edges such as the tree-like structure of the coronary vessels in digital angiograms. This method involves two steps. First, the original image is decomposed at different resolution levels using a pyramidal subband decomposition scheme. For decomposition/reconstruction of the image, free of aliasing and boundary errors, we use an ideal band-pass filter bank implemented in the Discrete Cosine Transform domain (DCT). Second, the high-frequency subbands are vector quantized using a multiresolution codebook with vertical and horizontal codewords which take into account the edge orientation of each subband. The proposed method reduces the blocking effect encountered at low bit rates in conventional vector quantization.

Automatic tool alignment in a backscatter X-ray scanning system

DOEpatents

Garretson, Justin; Hobart, Clinton G.; Gladwell, Thomas S.; Monda, Mark J.

2015-11-17

Technologies pertaining to backscatter x-ray scanning systems are described herein. The backscatter x-ray scanning system includes an x-ray source, which directs collimated x-rays along a plurality of output vectors towards a target. A detector detects diffusely reflected x-rays subsequent to respective collimated x-rays impacting the target, and outputs signals indicative of parameters of the detected x-rays. An image processing system generates an x-ray image based upon parameters of the detected x-rays, wherein each pixel in the image corresponds to a respective output vector. A user selects a particular portion of the image, and a medical device is positioned such that its directional axis is coincident with the output vector corresponding to at least one pixel in the portion of the image.

Automatic tool alignment in a backscatter x-ray scanning system

DOEpatents

Garretson, Justin; Hobart, Clinton G.; Gladwell, Thomas S.; Monda, Mark J.

2015-06-16

Technologies pertaining to backscatter x-ray scanning systems are described herein. The backscatter x-ray scanning system includes an x-ray source, which directs collimated x-rays along a plurality of output vectors towards a target. A detector detects diffusely reflected x-rays subsequent to respective collimated x-rays impacting the target, and outputs signals indicative of parameters of the detected x-rays. An image processing system generates an x-ray image based upon parameters of the detected x-rays, wherein each pixel in the image corresponds to a respective output vector. A user selects a particular portion of the image, and a tool is positioned such that its directional axis is coincident with the output vector corresponding to at least one pixel in the portion of the image.

Optical threshold secret sharing scheme based on basic vector operations and coherence superposition

NASA Astrophysics Data System (ADS)

Deng, Xiaopeng; Wen, Wei; Mi, Xianwu; Long, Xuewen

2015-04-01

We propose, to our knowledge for the first time, a simple optical algorithm for secret image sharing with the (2,n) threshold scheme based on basic vector operations and coherence superposition. The secret image to be shared is firstly divided into n shadow images by use of basic vector operations. In the reconstruction stage, the secret image can be retrieved by recording the intensity of the coherence superposition of any two shadow images. Compared with the published encryption techniques which focus narrowly on information encryption, the proposed method can realize information encryption as well as secret sharing, which further ensures the safety and integrality of the secret information and prevents power from being kept centralized and abused. The feasibility and effectiveness of the proposed method are demonstrated by numerical results.

A method to determine fault vectors in 4H-SiC from stacking sequences observed on high resolution transmission electron microscopy images

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

Wu, Fangzhen; Wang, Huanhuan; Raghothamachar, Balaji

A new method has been developed to determine the fault vectors associated with stacking faults in 4H-SiC from their stacking sequences observed on high resolution TEM images. This method, analogous to the Burgers circuit technique for determination of dislocation Burgers vector, involves determination of the vectors required in the projection of the perfect lattice to correct the deviated path constructed in the faulted material. Results for several different stacking faults were compared with fault vectors determined from X-ray topographic contrast analysis and were found to be consistent. This technique is expected to applicable to all structures comprising corner shared tetrahedra.

Evaluation of the specificity and sensitivity of ferritin as an MRI reporter gene in the mouse brain using lentiviral and adeno-associated viral vectors.

PubMed

Vande Velde, G; Rangarajan, J R; Toelen, J; Dresselaers, T; Ibrahimi, A; Krylychkina, O; Vreys, R; Van der Linden, A; Maes, F; Debyser, Z; Himmelreich, U; Baekelandt, V

2011-06-01

The development of in vivo imaging protocols to reliably track transplanted cells or to report on gene expression is critical for treatment monitoring in (pre)clinical cell and gene therapy protocols. Therefore, we evaluated the potential of lentiviral vectors (LVs) and adeno-associated viral vectors (AAVs) to express the magnetic resonance imaging (MRI) reporter gene ferritin in the rodent brain. First, we compared the induction of background MRI contrast for both vector systems in immune-deficient and immune-competent mice. LV injection resulted in hypointense (that is, dark) changes of T(2)/T(2)(*) (spin-spin relaxation time)-weighted MRI contrast at the injection site, which can be partially explained by an inflammatory response against the vector injection. In contrast to LVs, AAV injection resulted in reduced background contrast. Moreover, AAV-mediated ferritin overexpression resulted in significantly enhanced contrast to background on T(2)(*)-weighted MRI. Although sensitivity associated with the ferritin reporter remains modest, AAVs seem to be the most promising vector system for in vivo MRI reporter gene imaging.

Discrimination of malignant lymphomas and leukemia using Radon transform based-higher order spectra

NASA Astrophysics Data System (ADS)

Luo, Yi; Celenk, Mehmet; Bejai, Prashanth

2006-03-01

A new algorithm that can be used to automatically recognize and classify malignant lymphomas and leukemia is proposed in this paper. The algorithm utilizes the morphological watersheds to obtain boundaries of cells from cell images and isolate them from the surrounding background. The areas of cells are extracted from cell images after background subtraction. The Radon transform and higher-order spectra (HOS) analysis are utilized as an image processing tool to generate class feature vectors of different type cells and to extract testing cells' feature vectors. The testing cells' feature vectors are then compared with the known class feature vectors for a possible match by computing the Euclidean distances. The cell in question is classified as belonging to one of the existing cell classes in the least Euclidean distance sense.

Motion Estimation Using the Firefly Algorithm in Ultrasonic Image Sequence of Soft Tissue

PubMed Central

Chao, Chih-Feng; Horng, Ming-Huwi; Chen, Yu-Chan

2015-01-01

Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method. PMID:25873987

Motion estimation using the firefly algorithm in ultrasonic image sequence of soft tissue.

PubMed

Chao, Chih-Feng; Horng, Ming-Huwi; Chen, Yu-Chan

2015-01-01

Ultrasonic image sequence of the soft tissue is widely used in disease diagnosis; however, the speckle noises usually influenced the image quality. These images usually have a low signal-to-noise ratio presentation. The phenomenon gives rise to traditional motion estimation algorithms that are not suitable to measure the motion vectors. In this paper, a new motion estimation algorithm is developed for assessing the velocity field of soft tissue in a sequence of ultrasonic B-mode images. The proposed iterative firefly algorithm (IFA) searches for few candidate points to obtain the optimal motion vector, and then compares it to the traditional iterative full search algorithm (IFSA) via a series of experiments of in vivo ultrasonic image sequences. The experimental results show that the IFA can assess the vector with better efficiency and almost equal estimation quality compared to the traditional IFSA method.

Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

NASA Technical Reports Server (NTRS)

Shen, Han-Wei; Johnson, Christopher R.; Ma, Kwan-Liu

1996-01-01

We present local and global techniques to visualize three-dimensional vector field data. Using the Line Integral Convolution (LIC) method to image the global vector field, our new algorithm allows the user to introduce colored 'dye' into the vector field to highlight local flow features. A fast algorithm is proposed that quickly recomputes the dyed LIC images. In addition, we introduce volume rendering methods that can map the LIC texture on any contour surface and/or translucent region defined by additional scalar quantities, and can follow the advection of colored dye throughout the volume.

Novel DOTA-based prochelator for divalent peptide vectorization: synthesis of dimeric bombesin analogues for multimodality tumor imaging and therapy.

PubMed

Abiraj, Keelara; Jaccard, Hugues; Kretzschmar, Martin; Helm, Lothar; Maecke, Helmut R

2008-07-28

Dimeric peptidic vectors, obtained by the divalent grafting of bombesin analogues on a newly synthesized DOTA-based prochelator, showed improved qualities as tumor targeted imaging probes in comparison to their monomeric analogues.

Self-Organizing-Map Program for Analyzing Multivariate Data

NASA Technical Reports Server (NTRS)

Li, P. Peggy; Jacob, Joseph C.; Block, Gary L.; Braverman, Amy J.

2005-01-01

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

Continuous-wave THz vector imaging system utilizing two-tone signal generation and self-mixing detection.

PubMed

Song, Hajun; Hwang, Sejin; An, Hongsung; Song, Ho-Jin; Song, Jong-In

2017-08-21

We propose and demonstrate a continuous-wave vector THz imaging system utilizing a photonic generation of two-tone THz signals and self-mixing detection. The proposed system measures amplitude and phase information simultaneously without the local oscillator reference or phase rotation scheme that is required for heterodyne or homodyne detection. In addition, 2π phase ambiguity that occurs when the sample is thicker than the wavelength of THz radiation can be avoided. In this work, THz signal having two frequency components was generated with a uni-traveling-carrier photodiode and electro-optic modulator on the emitter side and detected with a Schottky barrier diode detector used as a self-mixer on the receiver side. The proposed THz vector imaging system exhibited a 50-dB signal to noise ratio and 0.012-rad phase fluctuation with 100-μs integration time at 325-GHz. With the system, we demonstrate two-dimensional THz phase contrast imaging. Considering the recent use of two-dimensional arrays of Schottky barrier diodes as a THz image sensor, the proposed system is greatly advantageous for realizing a real-time THz vector imaging system due to its simple receiver configuration.

Local structure-based image decomposition for feature extraction with applications to face recognition.

PubMed

Qian, Jianjun; Yang, Jian; Xu, Yong

2013-09-01

This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.

OPERATION HARDTACK. Project 3.3. Shock Loading in Ships from Underwater Bursts and Response of Shipboard Equipment

DTIC Science & Technology

1985-09-01

ke l aBit porn of ceeturlifie (atofer md) Sleeelig Gar Room 1iI ¶1 Fitt’ Natfore eck 7 3IMao hlie 01 A VVi Bolkifuad otiffteel2i 1~ Zn ft ov SIS frst...stiffener flange 33 Too of hull Centerline "R SS A Hull stiffener flange 33 Top of hull Centerline 9 R VM Hull stiffener flange 33 45 dog port from top 45 deg

Blast Mitigation by Water Mist, (3) Mitigation of Confined and Unconfined Blasts

DTIC Science & Technology

2006-07-14

2 (vv)I1 1 j7(T - TJ) (18) In addition to drag, heat transfer, and vaporization, droplet breakup must also be accounted for when large droplets...Mitigation of Confined and Unconfined Blasts Table of Contents 1 . Introduction 2 . Numerical Model and Solution Procedure 2.1 Gas-phase Model 2.2...enclosure at 1 , 2 , 5, and 15 ms after detonation of a 2.12 kg explosive without water mist present. Temperature contour range is from 300 to 2500 K

Evaluation of CONAP Concept for Advanced ABM Nosetips

DTIC Science & Technology

1976-11-01

AU~ ~ MMRCOT 63 EVALUATION OF CONAP CONCEPT. FOR MNS AANCED AOA WOS Nciveniber97O6𔃼iJ ’Archie Ossin , Paul KendallI -Martin MariettaAerospace -POstOf...29 May 1974 through 30 June 1976. Mr. Archie Ossin was the task leader and Mr. William A. Bauman was program manager. v/vi CONTENTS Summary...followed by full scale ground tests in a rocket exhaust facility should be performed. 50 REFERENCES 1. Ossin , A., Cawthon, D. M. "Evaluation of the CONAP

Cascaded image analysis for dynamic crack detection in material testing

NASA Astrophysics Data System (ADS)

Hampel, U.; Maas, H.-G.

Concrete probes in civil engineering material testing often show fissures or hairline-cracks. These cracks develop dynamically. Starting at a width of a few microns, they usually cannot be detected visually or in an image of a camera imaging the whole probe. Conventional image analysis techniques will detect fissures only if they show a width in the order of one pixel. To be able to detect and measure fissures with a width of a fraction of a pixel at an early stage of their development, a cascaded image analysis approach has been developed, implemented and tested. The basic idea of the approach is to detect discontinuities in dense surface deformation vector fields. These deformation vector fields between consecutive stereo image pairs, which are generated by cross correlation or least squares matching, show a precision in the order of 1/50 pixel. Hairline-cracks can be detected and measured by applying edge detection techniques such as a Sobel operator to the results of the image matching process. Cracks will show up as linear discontinuities in the deformation vector field and can be vectorized by edge chaining. In practical tests of the method, cracks with a width of 1/20 pixel could be detected, and their width could be determined at a precision of 1/50 pixel.

The vectorization of a ray tracing program for image generation

NASA Technical Reports Server (NTRS)

Plunkett, D. J.; Cychosz, J. M.; Bailey, M. J.

1984-01-01

Ray tracing is a widely used method for producing realistic computer generated images. Ray tracing involves firing an imaginary ray from a view point, through a point on an image plane, into a three dimensional scene. The intersections of the ray with the objects in the scene determines what is visible at the point on the image plane. This process must be repeated many times, once for each point (commonly called a pixel) in the image plane. A typical image contains more than a million pixels making this process computationally expensive. A traditional ray tracing program processes one ray at a time. In such a serial approach, as much as ninety percent of the execution time is spent computing the intersection of a ray with the surface in the scene. With the CYBER 205, many rays can be intersected with all the bodies im the scene with a single series of vector operations. Vectorization of this intersection process results in large decreases in computation time. The CADLAB's interest in ray tracing stems from the need to produce realistic images of mechanical parts. A high quality image of a part during the design process can increase the productivity of the designer by helping him visualize the results of his work. To be useful in the design process, these images must be produced in a reasonable amount of time. This discussion will explain how the ray tracing process was vectorized and gives examples of the images obtained.

Justification of Fuzzy Declustering Vector Quantization Modeling in Classification of Genotype-Image Phenotypes

NASA Astrophysics Data System (ADS)

Ng, Theam Foo; Pham, Tuan D.; Zhou, Xiaobo

2010-01-01

With the fast development of multi-dimensional data compression and pattern classification techniques, vector quantization (VQ) has become a system that allows large reduction of data storage and computational effort. One of the most recent VQ techniques that handle the poor estimation of vector centroids due to biased data from undersampling is to use fuzzy declustering-based vector quantization (FDVQ) technique. Therefore, in this paper, we are motivated to propose a justification of FDVQ based hidden Markov model (HMM) for investigating its effectiveness and efficiency in classification of genotype-image phenotypes. The performance evaluation and comparison of the recognition accuracy between a proposed FDVQ based HMM (FDVQ-HMM) and a well-known LBG (Linde, Buzo, Gray) vector quantization based HMM (LBG-HMM) will be carried out. The experimental results show that the performances of both FDVQ-HMM and LBG-HMM are almost similar. Finally, we have justified the competitiveness of FDVQ-HMM in classification of cellular phenotype image database by using hypotheses t-test. As a result, we have validated that the FDVQ algorithm is a robust and an efficient classification technique in the application of RNAi genome-wide screening image data.

Cubic-panorama image dataset analysis for storage and transmission

NASA Astrophysics Data System (ADS)

Salehi, Saeed; Dubois, Eric

2013-02-01

In this paper we address the problem of disparity estimation required for free navigation in acquired cubicpanorama image datasets. A client server based scheme is assumed and a remote user is assumed to seek information at each navigation step. The initial compression of such image datasets for storage as well as the transmission of the required data is addressed in this work. Regarding the compression of such data for storage, a fast method that uses properties of the epipolar geometry together with the cubic format of panoramas is used to estimate disparity vectors efficiently. Assuming the use of B pictures, the concept of forward and backward prediction is addressed. Regarding the transmission stage, a new disparity vector transcoding-like scheme is introduced and a frame conversion scenario is addressed. Details on how to pick the best vector among candidate disparity vectors is explained. In all the above mentioned cases, results are compared both visually through error images as well as using the objective measure of Peak Signal to Noise Ratio (PSNR) versus time.

Autofocus algorithm using one-dimensional Fourier transform and Pearson correlation

NASA Astrophysics Data System (ADS)

Bueno Mario, A.; Alvarez-Borrego, Josue; Acho, L.

2004-10-01

A new autofocus algorithm based on one-dimensional Fourier transform and Pearson correlation for Z automatized microscope is proposed. Our goal is to determine in fast response time and accuracy, the best focused plane through an algorithm. We capture in bright and dark field several images set at different Z distances from biological organism sample. The algorithm uses the one-dimensional Fourier transform to obtain the image frequency content of a vectors pattern previously defined comparing the Pearson correlation of these frequency vectors versus the reference image frequency vector, the most out of focus image, we find the best focusing. Experimental results showed the algorithm has fast response time and accuracy in getting the best focus plane from captured images. In conclusions, the algorithm can be implemented in real time systems due fast response time, accuracy and robustness. The algorithm can be used to get focused images in bright and dark field and it can be extended to include fusion techniques to construct multifocus final images beyond of this paper.

Analysis of identification of digital images from a map of cosmic microwaves

NASA Astrophysics Data System (ADS)

Skeivalas, J.; Turla, V.; Jurevicius, M.; Viselga, G.

2018-04-01

This paper discusses identification of digital images from the cosmic microwave background radiation map formed according to the data of the European Space Agency "Planck" telescope by applying covariance functions and wavelet theory. The estimates of covariance functions of two digital images or single images are calculated according to the random functions formed of the digital images in the form of pixel vectors. The estimates of pixel vectors are formed on expansion of the pixel arrays of the digital images by a single vector. When the scale of a digital image is varied, the frequencies of single-pixel color waves remain constant and the procedure for calculation of covariance functions is not affected. For identification of the images, the RGB format spectrum has been applied. The impact of RGB spectrum components and the color tensor on the estimates of covariance functions was analyzed. The identity of digital images is assessed according to the changes in the values of the correlation coefficients in a certain range of values by applying the developed computer program.

Improvement of cardiac CT reconstruction using local motion vector fields.

PubMed

Schirra, Carsten Oliver; Bontus, Claas; van Stevendaal, Udo; Dössel, Olaf; Grass, Michael

2009-03-01

The motion of the heart is a major challenge for cardiac imaging using CT. A novel approach to decrease motion blur and to improve the signal to noise ratio is motion compensated reconstruction which takes motion vector fields into account in order to correct motion. The presented work deals with the determination of local motion vector fields from high contrast objects and their utilization within motion compensated filtered back projection reconstruction. Image registration is applied during the quiescent cardiac phases. Temporal interpolation in parameter space is used in order to estimate motion during strong motion phases. The resulting motion vector fields are during image reconstruction. The method is assessed using a software phantom and several clinical cases for calcium scoring. As a criterion for reconstruction quality, calcium volume scores were derived from both, gated cardiac reconstruction and motion compensated reconstruction throughout the cardiac phases using low pitch helical cone beam CT acquisitions. The presented technique is a robust method to determine and utilize local motion vector fields. Motion compensated reconstruction using the derived motion vector fields leads to superior image quality compared to gated reconstruction. As a result, the gating window can be enlarged significantly, resulting in increased SNR, while reliable Hounsfield units are achieved due to the reduced level of motion artefacts. The enlargement of the gating window can be translated into reduced dose requirements.

A hybrid LBG/lattice vector quantizer for high quality image coding

NASA Technical Reports Server (NTRS)

Ramamoorthy, V.; Sayood, K.; Arikan, E. (Editor)

1991-01-01

It is well known that a vector quantizer is an efficient coder offering a good trade-off between quantization distortion and bit rate. The performance of a vector quantizer asymptotically approaches the optimum bound with increasing dimensionality. A vector quantized image suffers from the following types of degradations: (1) edge regions in the coded image contain staircase effects, (2) quasi-constant or slowly varying regions suffer from contouring effects, and (3) textured regions lose details and suffer from granular noise. All three of these degradations are due to the finite size of the code book, the distortion measures used in the design, and due to the finite training procedure involved in the construction of the code book. In this paper, we present an adaptive technique which attempts to ameliorate the edge distortion and contouring effects.

Vector-Based Data Services for NASA Earth Science

NASA Astrophysics Data System (ADS)

Rodriguez, J.; Roberts, J. T.; Ruvane, K.; Cechini, M. F.; Thompson, C. K.; Boller, R. A.; Baynes, K.

2016-12-01

Vector data sources offer opportunities for mapping and visualizing science data in a way that allows for more customizable rendering and deeper data analysis than traditional raster images, and popular formats like GeoJSON and Mapbox Vector Tiles allow diverse types of geospatial data to be served in a high-performance and easily consumed-package. Vector data is especially suited to highly dynamic mapping applications and visualization of complex datasets, while growing levels of support for vector formats and features in open-source mapping clients has made utilizing them easier and more powerful than ever. NASA's Global Imagery Browse Services (GIBS) is working to make NASA data more easily and conveniently accessible than ever by serving vector datasets via GeoJSON, Mapbox Vector Tiles, and raster images. This presentation will review these output formats, the services, including WFS, WMS, and WMTS, that can be used to access the data, and some ways in which vector sources can be utilized in popular open-source mapping clients like OpenLayers. Lessons learned from GIBS' recent move towards serving vector will be discussed, as well as how to use GIBS open source software to create, configure, and serve vector data sources using Mapserver and the GIBS OnEarth Apache module.

Renewal: New Aspects of Acceleration and Transport of Solar Energetic Particles (SEPs) from the Sun to the Earth

DTIC Science & Technology

2014-10-31

Hole .......................................................4 2. SOHO EIT Image with Coronal Holes and FPA Vector...Diagram of CME Deflection by a Coronal Hole Figure 2: SOHO EIT Image with Coronal Holes and FPA Vector Approved for public release; distribution

A new image representation for compact and secure communication

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

Prasad, Lakshman; Skourikhine, A. N.

In many areas of nuclear materials management there is a need for communication, archival, and retrieval of annotated image data between heterogeneous platforms and devices to effectively implement safety, security, and safeguards of nuclear materials. Current image formats such as JPEG are not ideally suited in such scenarios as they are not scalable to different viewing formats, and do not provide a high-level representation of images that facilitate automatic object/change detection or annotation. The new Scalable Vector Graphics (SVG) open standard for representing graphical information, recommended by the World Wide Web Consortium (W3C) is designed to address issues of imagemore » scalability, portability, and annotation. However, until now there has been no viable technology to efficiently field images of high visual quality under this standard. Recently, LANL has developed a vectorized image representation that is compatible with the SVG standard and preserves visual quality. This is based on a new geometric framework for characterizing complex features in real-world imagery that incorporates perceptual principles of processing visual information known from cognitive psychology and vision science, to obtain a polygonal image representation of high fidelity. This representation can take advantage of all textual compression and encryption routines unavailable to other image formats. Moreover, this vectorized image representation can be exploited to facilitate automated object recognition that can reduce time required for data review. The objects/features of interest in these vectorized images can be annotated via animated graphics to facilitate quick and easy display and comprehension of processed image content.« less

Image search engine with selective filtering and feature-element-based classification

NASA Astrophysics Data System (ADS)

Li, Qing; Zhang, Yujin; Dai, Shengyang

2001-12-01

With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.

Contour-based image warping

NASA Astrophysics Data System (ADS)

Chan, Kwai H.; Lau, Rynson W.

1996-09-01

Image warping concerns about transforming an image from one spatial coordinate to another. It is widely used for the vidual effect of deforming and morphing images in the film industry. A number of warping techniques have been introduced, which are mainly based on the corresponding pair mapping of feature points, feature vectors or feature patches (mostly triangular or quadrilateral). However, very often warping of an image object with an arbitrary shape is required. This requires a warping technique which is based on boundary contour instead of feature points or feature line-vectors. In addition, when feature point or feature vector based techniques are used, approximation of the object boundary by using point or vectors is required. In this case, the matching process of the corresponding pairs will be very time consuming if a fine approximation is required. In this paper, we propose a contour-based warping technique for warping image objects with arbitrary shapes. The novel idea of the new method is the introduction of mathematical morphology to allow a more flexible control of image warping. Two morphological operators are used as contour determinators. The erosion operator is used to warp image contents which are inside a user specified contour while the dilation operation is used to warp image contents which are outside of the contour. This new method is proposed to assist further development of a semi-automatic motion morphing system when accompanied with robust feature extractors such as deformable template or active contour model.

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet.

PubMed

Mariappan, Leo; Hu, Gang; He, Bin

2014-02-01

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼ 1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction.

Accelerating 4D flow MRI by exploiting vector field divergence regularization.

PubMed

Santelli, Claudio; Loecher, Michael; Busch, Julia; Wieben, Oliver; Schaeffter, Tobias; Kozerke, Sebastian

2016-01-01

To improve velocity vector field reconstruction from undersampled four-dimensional (4D) flow MRI by penalizing divergence of the measured flow field. Iterative image reconstruction in which magnitude and phase are regularized separately in alternating iterations was implemented. The approach allows incorporating prior knowledge of the flow field being imaged. In the present work, velocity data were regularized to reduce divergence, using either divergence-free wavelets (DFW) or a finite difference (FD) method using the ℓ1-norm of divergence and curl. The reconstruction methods were tested on a numerical phantom and in vivo data. Results of the DFW and FD approaches were compared with data obtained with standard compressed sensing (CS) reconstruction. Relative to standard CS, directional errors of vector fields and divergence were reduced by 55-60% and 38-48% for three- and six-fold undersampled data with the DFW and FD methods. Velocity vector displays of the numerical phantom and in vivo data were found to be improved upon DFW or FD reconstruction. Regularization of vector field divergence in image reconstruction from undersampled 4D flow data is a valuable approach to improve reconstruction accuracy of velocity vector fields. © 2014 Wiley Periodicals, Inc.

Video-rate terahertz electric-field vector imaging

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

Takai, Mayuko; Takeda, Masatoshi; Sasaki, Manabu

We present an experimental setup to dramatically reduce a measurement time for obtaining spatial distributions of terahertz electric-field (E-field) vectors. The method utilizes the electro-optic sampling, and we use a charge-coupled device to detect a spatial distribution of the probe beam polarization rotation by the E-field-induced Pockels effect in a 〈110〉-oriented ZnTe crystal. A quick rotation of the ZnTe crystal allows analyzing the terahertz E-field direction at each image position, and the terahertz E-field vector mapping at a fixed position of an optical delay line is achieved within 21 ms. Video-rate mapping of terahertz E-field vectors is likely to bemore » useful for achieving real-time sensing of terahertz vector beams, vector vortices, and surface topography. The method is also useful for a fast polarization analysis of terahertz beams.« less

Optical image security using Stokes polarimetry of spatially variant polarized beam

NASA Astrophysics Data System (ADS)

Fatima, Areeba; Nishchal, Naveen K.

2018-06-01

We propose a novel security scheme that uses vector beam characterized by the spatially variant polarization distribution. A vector beam is so generated that its helical components carry tailored phases corresponding to the image/images that is/are to be encrypted. The tailoring of phase has been done by employing the modified Gerchberg-Saxton algorithm for phase retrieval. Stokes parameters for the final vector beam is evaluated and is used to construct the ciphertext and one of the keys. The advantage of the proposed scheme is that it generates real ciphertext and keys which are easier to transmit and store than complex quantities. Moreover, the known plaintext attack is not applicable to this system. As a proof-of-concept, simulation results have been presented for securing single and double gray-scale images.

Vector coding of wavelet-transformed images

NASA Astrophysics Data System (ADS)

Zhou, Jun; Zhi, Cheng; Zhou, Yuanhua

1998-09-01

Wavelet, as a brand new tool in signal processing, has got broad recognition. Using wavelet transform, we can get octave divided frequency band with specific orientation which combines well with the properties of Human Visual System. In this paper, we discuss the classified vector quantization method for multiresolution represented image.

Multiclass Reduced-Set Support Vector Machines

NASA Technical Reports Server (NTRS)

Tang, Benyang; Mazzoni, Dominic

2006-01-01

There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduced-set methods can be applied to multiclass SVMs made up of several binary SVMs, with significantly better results than reducing each binary SVM independently. Our approach is based on Burges' approach that constructs each reduced-set vector as the pre-image of a vector in kernel space, but we extend this by recomputing the SVM weights and bias optimally using the original SVM objective function. This leads to greater accuracy for a binary reduced-set SVM, and also allows vectors to be 'shared' between multiple binary SVMs for greater multiclass accuracy with fewer reduced-set vectors. We also propose computing pre-images using differential evolution, which we have found to be more robust than gradient descent alone. We show experimental results on a variety of problems and find that this new approach is consistently better than previous multiclass reduced-set methods, sometimes with a dramatic difference.

Vectorized Rebinning Algorithm for Fast Data Down-Sampling

NASA Technical Reports Server (NTRS)

Dean, Bruce; Aronstein, David; Smith, Jeffrey

2013-01-01

A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.

Saccadic eye movement performance as an indicator of driving ability in elderly drivers.

PubMed

Schmitt, Kai-Uwe; Seeger, Rolf; Fischer, Hartmut; Lanz, Christian; Muser, Markus; Walz, Felix; Schwarz, Urs

2015-01-01

Regular checking of the fitness to drive of elderly car-license holders is required in some countries, and this will become increasingly important as more countries face aging populations. The present study investigated whether the analysis of saccadic eye movements could be used as a screening method for the assessment of driving ability. Three different paradigms (prosaccades, antisaccades, and visuovisual interactive (VVI) saccades) were used to test saccadic eye movements in 144 participants split into four groups: elderly drivers who came to the attention of road authorities for suspected lack of fitness to drive, a group of elderly drivers who served as a comparison group, a group of neurology patients with established brain lesion diagnoses, and a young comparison group. The group of elderly drivers with suspected deficits in driving skills also underwent a medical examination and a practical on-road driving test. The results of the saccadic eye tests of the different groups were compared. Antisaccade results indicated a strong link to driving behaviour: elderly drivers who were not fit to drive exhibited a poor performance on the antisaccade task and the performance in the VVI task was also clearly poorer in this group. Testing saccadic eye movements appears to be a promising and efficient method for screening large numbers of people such as elderly drivers. This study indicated a link between antisaccade performance and the ability to drive. Hence, measuring saccadic eye movements should be considered as a tool for screening the fitness to drive.

Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

NASA Astrophysics Data System (ADS)

Hung, C. H.; Chang, W. C.; Chen, L. C.

2016-06-01

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

An Approach towards Ultrasound Kidney Cysts Detection using Vector Graphic Image Analysis

NASA Astrophysics Data System (ADS)

Mahmud, Wan Mahani Hafizah Wan; Supriyanto, Eko

2017-08-01

This study develops new approach towards detection of kidney ultrasound image for both with single cyst as well as multiple cysts. 50 single cyst images and 25 multiple cysts images were used to test the developed algorithm. Steps involved in developing this algorithm were vector graphic image formation and analysis, thresholding, binarization, filtering as well as roundness test. Performance evaluation to 50 single cyst images gave accuracy of 92%, while for multiple cysts images, the accuracy was about 86.89% when tested to 25 multiple cysts images. This developed algorithm may be used in developing a computerized system such as computer aided diagnosis system to help medical experts in diagnosis of kidney cysts.

Capabilities of software "Vector-M" for a diagnostics of the ionosphere state from auroral emissions images and plasma characteristics from the different orbits as a part of the system of control of space weather

NASA Astrophysics Data System (ADS)

Avdyushev, V.; Banshchikova, M.; Chuvashov, I.; Kuzmin, A.

2017-09-01

In the paper are presented capabilities of software "Vector-M" for a diagnostics of the ionosphere state from auroral emissions images and plasma characteristics from the different orbits as a part of the system of control of space weather. The software "Vector-M" is developed by the celestial mechanics and astrometry department of Tomsk State University in collaboration with Space Research Institute (Moscow) and Central Aerological Observatory of Russian Federal Service for Hydrometeorology and Environmental Monitoring. The software "Vector-M" is intended for calculation of attendant geophysical and astronomical information for the centre of mass of the spacecraft and the space of observations in the experiment with auroral imager Aurovisor-VIS/MP in the orbit of the perspective Meteor-MP spacecraft.

Surveillance of Arthropod Vector-Borne Infectious Diseases Using Remote Sensing Techniques: A Review

PubMed Central

Kalluri, Satya; Gilruth, Peter; Rogers, David; Szczur, Martha

2007-01-01

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed. PMID:17967056

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

PubMed

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Automated image segmentation using support vector machines

NASA Astrophysics Data System (ADS)

Powell, Stephanie; Magnotta, Vincent A.; Andreasen, Nancy C.

2007-03-01

Neurodegenerative and neurodevelopmental diseases demonstrate problems associated with brain maturation and aging. Automated methods to delineate brain structures of interest are required to analyze large amounts of imaging data like that being collected in several on going multi-center studies. We have previously reported on using artificial neural networks (ANN) to define subcortical brain structures including the thalamus (0.88), caudate (0.85) and the putamen (0.81). In this work, apriori probability information was generated using Thirion's demons registration algorithm. The input vector consisted of apriori probability, spherical coordinates, and an iris of surrounding signal intensity values. We have applied the support vector machine (SVM) machine learning algorithm to automatically segment subcortical and cerebellar regions using the same input vector information. SVM architecture was derived from the ANN framework. Training was completed using a radial-basis function kernel with gamma equal to 5.5. Training was performed using 15,000 vectors collected from 15 training images in approximately 10 minutes. The resulting support vectors were applied to delineate 10 images not part of the training set. Relative overlap calculated for the subcortical structures was 0.87 for the thalamus, 0.84 for the caudate, 0.84 for the putamen, and 0.72 for the hippocampus. Relative overlap for the cerebellar lobes ranged from 0.76 to 0.86. The reliability of the SVM based algorithm was similar to the inter-rater reliability between manual raters and can be achieved without rater intervention.

Quantitative analysis of rib movement based on dynamic chest bone images: preliminary results

NASA Astrophysics Data System (ADS)

Tanaka, R.; Sanada, S.; Oda, M.; Mitsutaka, M.; Suzuki, K.; Sakuta, K.; Kawashima, H.

2014-03-01

Rib movement during respiration is one of the diagnostic criteria in pulmonary impairments. In general, the rib movement is assessed in fluoroscopy. However, the shadows of lung vessels and bronchi overlapping ribs prevent accurate quantitative analysis of rib movement. Recently, an image-processing technique for separating bones from soft tissue in static chest radiographs, called "bone suppression technique", has been developed. Our purpose in this study was to evaluate the usefulness of dynamic bone images created by the bone suppression technique in quantitative analysis of rib movement. Dynamic chest radiographs of 10 patients were obtained using a dynamic flat-panel detector (FPD). Bone suppression technique based on a massive-training artificial neural network (MTANN) was applied to the dynamic chest images to create bone images. Velocity vectors were measured in local areas on the dynamic bone images, which formed a map. The velocity maps obtained with bone and original images for scoliosis and normal cases were compared to assess the advantages of bone images. With dynamic bone images, we were able to quantify and distinguish movements of ribs from those of other lung structures accurately. Limited rib movements of scoliosis patients appeared as reduced rib velocity vectors. Vector maps in all normal cases exhibited left-right symmetric distributions, whereas those in abnormal cases showed nonuniform distributions. In conclusion, dynamic bone images were useful for accurate quantitative analysis of rib movements: Limited rib movements were indicated as a reduction of rib movement and left-right asymmetric distribution on vector maps. Thus, dynamic bone images can be a new diagnostic tool for quantitative analysis of rib movements without additional radiation dose.

A novel retinal vessel extraction algorithm based on matched filtering and gradient vector flow

NASA Astrophysics Data System (ADS)

Yu, Lei; Xia, Mingliang; Xuan, Li

2013-10-01

The microvasculature network of retina plays an important role in the study and diagnosis of retinal diseases (age-related macular degeneration and diabetic retinopathy for example). Although it is possible to noninvasively acquire high-resolution retinal images with modern retinal imaging technologies, non-uniform illumination, the low contrast of thin vessels and the background noises all make it difficult for diagnosis. In this paper, we introduce a novel retinal vessel extraction algorithm based on gradient vector flow and matched filtering to segment retinal vessels with different likelihood. Firstly, we use isotropic Gaussian kernel and adaptive histogram equalization to smooth and enhance the retinal images respectively. Secondly, a multi-scale matched filtering method is adopted to extract the retinal vessels. Then, the gradient vector flow algorithm is introduced to locate the edge of the retinal vessels. Finally, we combine the results of matched filtering method and gradient vector flow algorithm to extract the vessels at different likelihood levels. The experiments demonstrate that our algorithm is efficient and the intensities of vessel images exactly represent the likelihood of the vessels.

Fuzzy inference enhanced information recovery from digital PIV using cross-correlation combined with particle tracking

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

1995-01-01

Particle Image Velocimetry provides a means of measuring the instantaneous 2-component velocity field across a planar region of a seeded flowfield. In this work only two camera, single exposure images are considered where both cameras have the same view of the illumination plane. Two competing techniques which yield unambiguous velocity vector direction information have been widely used for reducing the single exposure, multiple image data: cross-correlation and particle tracking. Correlation techniques yield averaged velocity estimates over subregions of the flow, whereas particle tracking techniques give individual particle velocity estimates. The correlation technique requires identification of the correlation peak on the correlation plane corresponding to the average displacement of particles across the subregion. Noise on the images and particle dropout contribute to spurious peaks on the correlation plane, leading to misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work fuzzy logic techniques are used to determine the true correlation displacement peak even when it is not the maximum peak on the correlation plane, hence maximizing the information recovery from the correlation operation, maintaining the number of independent measurements and minimizing the number of spurious velocity vectors. Correlation peaks are correctly identified in both high and low seed density cases. The correlation velocity vector map can then be used as a guide for the particle tracking operation. Again fuzzy logic techniques are used, this time to identify the correct particle image pairings between exposures to determine particle displacements, and thus velocity. The advantage of this technique is the improved spatial resolution which is available from the particle tracking operation. Particle tracking alone may not be possible in the high seed density images typically required for achieving good results from the correlation technique. This two staged approach offers a velocimetric technique capable of measuring particle velocities with high spatial resolution over a broad range of seeding densities.

High Order Entropy-Constrained Residual VQ for Lossless Compression of Images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Scales, Allen

1995-01-01

High order entropy coding is a powerful technique for exploiting high order statistical dependencies. However, the exponentially high complexity associated with such a method often discourages its use. In this paper, an entropy-constrained residual vector quantization method is proposed for lossless compression of images. The method consists of first quantizing the input image using a high order entropy-constrained residual vector quantizer and then coding the residual image using a first order entropy coder. The distortion measure used in the entropy-constrained optimization is essentially the first order entropy of the residual image. Experimental results show very competitive performance.

Real-Time Symbol Extraction From Grey-Level Images

NASA Astrophysics Data System (ADS)

Massen, R.; Simnacher, M.; Rosch, J.; Herre, E.; Wuhrer, H. W.

1988-04-01

A VME-bus image pipeline processor for extracting vectorized contours from grey-level images in real-time is presented. This 3 Giga operation per second processor uses large kernel convolvers and new non-linear neighbourhood processing algorithms to compute true 1-pixel wide and noise-free contours without thresholding even from grey-level images with quite varying edge sharpness. The local edge orientation is used as an additional cue to compute a list of vectors describing the closed and open contours in real-time and to dump a CAD-like symbolic image description into a symbol memory at pixel clock rate.

Aerial images visual localization on a vector map using color-texture segmentation

NASA Astrophysics Data System (ADS)

Kunina, I. A.; Teplyakov, L. M.; Gladkov, A. P.; Khanipov, T. M.; Nikolaev, D. P.

2018-04-01

In this paper we study the problem of combining UAV obtained optical data and a coastal vector map in absence of satellite navigation data. The method is based on presenting the territory as a set of segments produced by color-texture image segmentation. We then find such geometric transform which gives the best match between these segments and land and water areas of the georeferenced vector map. We calculate transform consisting of an arbitrary shift relatively to the vector map and bound rotation and scaling. These parameters are estimated using the RANSAC algorithm which matches the segments contours and the contours of land and water areas of the vector map. To implement this matching we suggest computing shape descriptors robust to rotation and scaling. We performed numerical experiments demonstrating the practical applicability of the proposed method.

SU-E-T-428: Feasibility Study of 4D Image Reconstruction by Organ Motion Vector Extension Based On Portal Images

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

Yoon, J; Jung, J; Yeo, I

2015-06-15

Purpose: To develop and to test a method to generate a new 4D CT images of the treatment day from the old 4D CT and the portal images of the day when the motion extent exceeded from that represented by plan CTs. Methods: A motion vector of a moving tumor in a patient may be extended to reconstruct the tumor position when the motion extent exceeded from that represented by plan CTs. To test this, 1. a phantom that consists of a polystyrene cylinder (tumor) embedded in cork (lung) was placed on a moving platform with 4 sec/cycle and amplitudesmore » of 1 cm and 2 cm, and was 4D-scanned. 2. A 6MV photon beam was irradiated on the moving phantoms and cineEPID images were obtained. 3. A motion vector of the tumor was acquired from 4D CT images of the phantom with 1 cm amplitude. 4. From cine EPID images of the phantom with the 2 cm amplitude, various motion extents (0.3 cm, 0.5 cm, etc) were acquired and programmed into the motion vector, producing CT images at each position. 5. The reconstructed CT images were then compared with pre-acquired “reference” 4D CT images at each position (i.e. phase). Results: The CT image was reconstructed and compared with the reference image, showing a slight mismatch in the transition direction limited by voxel size (slice thickness) in CT image. Due to the rigid nature of the phantom studied, the modeling the displacement of the center of object was sufficient. When deformable tumors are to be modeled, more complex scheme is necessary, which utilize cine EPID and 4D CT images. Conclusion: The new idea of CT image reconstruction was demonstrated. Deformable tumor movements need to be considered in the future.« less

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

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

Chang, X; Yang, D

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was usedmore » to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.« less

Impact of Short Interval SMS Digital Data on Wind Vector Determination for a Severe Local Storms Area

NASA Technical Reports Server (NTRS)

Peslen, C. A.

1979-01-01

The impact of 5 minute interval SMS-2 visible digital image data in analyzing severe local storms is examined using wind vectors derived from cloud tracking on time lapsed sequence of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on 6 May 1975, hail-producing thunderstorms occurred ahead of a well defined dry line. The results demonstrate that satellite-derived wind vectors and their associated divergence fields complement conventional meteorological analyses in describing the conditions preceding severe local storm development.

Solar monochromatic images in magneto-sensitive spectral lines and maps of vector magnetic fields

NASA Technical Reports Server (NTRS)

Shihui, Y.; Jiehai, J.; Minhan, J.

1985-01-01

A new method which allows by use of the monochromatic images in some magneto-sensitive spectra line to derive both the magnetic field strength as well as the angle between magnetic field lines and line of sight for various places in solar active regions is described. In this way two dimensional maps of vector magnetic fields may be constructed. This method was applied to some observational material and reasonable results were obtained. In addition, a project for constructing the three dimensional maps of vector magnetic fields was worked out.

Quantum dot coating of baculoviral vectors enables visualization of transduced cells and tissues

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

Zhao, Ying; Lo, Seong Loong; Zheng, Yuangang

2013-04-26

Highlights: •The use of quantum dot (QD)-labeled viral vectors for in vivo imaging is not well investigated. •A new method to label enveloped baculovirus with glutathione-capped CdTe QDs is developed. •The labeling enables the identification of transduced, cultured cells based on fluorescence. •The labeling also allows evaluation of viral transduction in a real-time manner in living mice. •The method has the potential to assess viral vector-based gene therapy protocols in future. -- Abstract: Imaging of transduced cells and tissues is valuable in developing gene transfer vectors and evaluating gene therapy efficacy. We report here a simple method to use brightmore » and photostable quantum dots to label baculovirus, an emerging gene therapy vector. The labeling was achieved through the non-covalent interaction of glutathione-capped CdTe quantum dots with the virus envelope, without the use of chemical conjugation. The quantum dot labeling was nondestructive to viral transduction function and enabled the identification of baculoviral vector-transduced, living cells based on red fluorescence. When the labeled baculoviral vectors were injected intravenously or intraventricularly for in vivo delivery of a transgene into mice, quantum dot fluorescence signals allow us monitor whether or not the injected tissues were transduced. More importantly, using a dual-color whole-body imaging technology, we demonstrated that in vivo viral transduction could be evaluated in a real-time manner in living mice. Thus, our method of labeling a read-to-use gene delivery vector with quantum dots could be useful towards the improvement of vector design and will have the potential to assess baculovirus-based gene therapy protocols in future.« less

Reflectance Prediction Modelling for Residual-Based Hyperspectral Image Coding

PubMed Central

Xiao, Rui; Gao, Junbin; Bossomaier, Terry

2016-01-01

A Hyperspectral (HS) image provides observational powers beyond human vision capability but represents more than 100 times the data compared to a traditional image. To transmit and store the huge volume of an HS image, we argue that a fundamental shift is required from the existing “original pixel intensity”-based coding approaches using traditional image coders (e.g., JPEG2000) to the “residual”-based approaches using a video coder for better compression performance. A modified video coder is required to exploit spatial-spectral redundancy using pixel-level reflectance modelling due to the different characteristics of HS images in their spectral and shape domain of panchromatic imagery compared to traditional videos. In this paper a novel coding framework using Reflectance Prediction Modelling (RPM) in the latest video coding standard High Efficiency Video Coding (HEVC) for HS images is proposed. An HS image presents a wealth of data where every pixel is considered a vector for different spectral bands. By quantitative comparison and analysis of pixel vector distribution along spectral bands, we conclude that modelling can predict the distribution and correlation of the pixel vectors for different bands. To exploit distribution of the known pixel vector, we estimate a predicted current spectral band from the previous bands using Gaussian mixture-based modelling. The predicted band is used as the additional reference band together with the immediate previous band when we apply the HEVC. Every spectral band of an HS image is treated like it is an individual frame of a video. In this paper, we compare the proposed method with mainstream encoders. The experimental results are fully justified by three types of HS dataset with different wavelength ranges. The proposed method outperforms the existing mainstream HS encoders in terms of rate-distortion performance of HS image compression. PMID:27695102

Patterns of CMR measured longitudinal strain and its association with late gadolinium enhancement in patients with cardiac amyloidosis and its mimics.

PubMed

Williams, Lynne K; Forero, Julian F; Popovic, Zoran B; Phelan, Dermot; Delgado, Diego; Rakowski, Harry; Wintersperger, Bernd J; Thavendiranathan, Paaladinesh

2017-08-07

Regional variability of longitudinal strain (LS) has been previously described with echocardiography in patients with cardiac amyloidosis (CA), however, the reason for this variability is not completely evident. We sought to describe regional patterns in LS using feature-tracking software applied to cardiovascular magnetic resonance (CMR) cine images in patients with CA, hypertrophic cardiomyopathy (HCM), and Anderson-Fabry's disease (AFD) and to relate these patterns to the distribution of late gadolinium enhancement (LGE). Patients with CA (n = 45) were compared to LV mass indexed matched patients with HCM (n = 19) and AFD (n = 19). Peak systolic LS measurements were obtained using Velocity Vector Imaging (VVI) software on CMR cine images. A relative regional LS ratio (RRSR) was calculated as the ratio of the average of the apical segmental LS divided by the sum of the average basal and mid-ventricular segmental LS. LGE was quantified for the basal, mid, and apical segments using a threshold of 5SD above remote myocardium. A regional LGE ratio was calculated similar to RRSR. Patients with CA had significantly had worse global LS (-15.7 ± 4.6%) than those with HCM (-18.0 ± 4.6%, p = 0.046) and AFD (-21.9 ± 5.1%, p < 0.001). The RRSR was higher in patients with CA (1.00 ± 0.31) than in AFD (0.79 ± 0.24; p = 0.018) but not HCM (0.84 ± 0.32; p = 0.114). In CA, a regional difference in LGE burden was noted, with lower LGE in the apex (31.5 ± 19.1%) compared to the mid (38.2 ± 19.0%) and basal (53.7 ± 22.7%; p < 0.001 for both) segments. The regional LGE ratio was not significantly different between patients with CA (0.33 ± 0.15) and AFD (0.47 ± 0.58; p = 0.14) but lower compared to those with HCM (0.72 ± 0.43; p < 0.0001). LGE percentage showed a significant impact on LS (p < 0.0001), with a 0.9% decrease in absolute LS for every 10% increase in LGE percentage. The presence of marked "relative apical sparing" of LS along with a significant reduction in global LS seen in patients with CA on CMR cine analysis may provide an additional tool to differentiate CA from other cause of LVH. The concomitant presence of a base to apex gradient in quantitative LGE burden suggests that the regional strain gradient may be at least partially explained by the burden of amyloid deposition and fibrosis.

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor

PubMed Central

Hast, Anders; Wählby, Carolina; Sintorn, Ida-Maria

2017-01-01

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images. PMID:29190737

Object recognition of ladar with support vector machine

NASA Astrophysics Data System (ADS)

Sun, Jian-Feng; Li, Qi; Wang, Qi

2005-01-01

Intensity, range and Doppler images can be obtained by using laser radar. Laser radar can detect much more object information than other detecting sensor, such as passive infrared imaging and synthetic aperture radar (SAR), so it is well suited as the sensor of object recognition. Traditional method of laser radar object recognition is extracting target features, which can be influenced by noise. In this paper, a laser radar recognition method-Support Vector Machine is introduced. Support Vector Machine (SVM) is a new hotspot of recognition research after neural network. It has well performance on digital written and face recognition. Two series experiments about SVM designed for preprocessing and non-preprocessing samples are performed by real laser radar images, and the experiments results are compared.

A recursive technique for adaptive vector quantization

NASA Technical Reports Server (NTRS)

Lindsay, Robert A.

1989-01-01

Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression. The VQ performs well when compressing all types of imagery including Video, Electro-Optical (EO), Infrared (IR), Synthetic Aperture Radar (SAR), Multi-Spectral (MS), and digital map data. The only requirement is to change the codebook to switch the compressor from one image sensor to another. There are several approaches for designing codebooks for a vector quantizer. Adaptive Vector Quantization is a procedure that simultaneously designs codebooks as the data is being encoded or quantized. This is done by computing the centroid as a recursive moving average where the centroids move after every vector is encoded. When computing the centroid of a fixed set of vectors the resultant centroid is identical to the previous centroid calculation. This method of centroid calculation can be easily combined with VQ encoding techniques. The defined quantizer changes after every encoded vector by recursively updating the centroid of minimum distance which is the selected by the encoder. Since the quantizer is changing definition or states after every encoded vector, the decoder must now receive updates to the codebook. This is done as side information by multiplexing bits into the compressed source data.

Boost OCR accuracy using iVector based system combination approach

NASA Astrophysics Data System (ADS)

Peng, Xujun; Cao, Huaigu; Natarajan, Prem

2015-01-01

Optical character recognition (OCR) is a challenging task because most existing preprocessing approaches are sensitive to writing style, writing material, noises and image resolution. Thus, a single recognition system cannot address all factors of real document images. In this paper, we describe an approach to combine diverse recognition systems by using iVector based features, which is a newly developed method in the field of speaker verification. Prior to system combination, document images are preprocessed and text line images are extracted with different approaches for each system, where iVector is transformed from a high-dimensional supervector of each text line and is used to predict the accuracy of OCR. We merge hypotheses from multiple recognition systems according to the overlap ratio and the predicted OCR score of text line images. We present evaluation results on an Arabic document database where the proposed method is compared against the single best OCR system using word error rate (WER) metric.

a Robust Descriptor Based on Spatial and Frequency Structural Information for Visible and Thermal Infrared Image Matching

NASA Astrophysics Data System (ADS)

Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.

2017-09-01

Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.

Magnetoacoustic Tomography with Magnetic Induction: Bioimepedance reconstruction through vector source imaging

PubMed Central

Mariappan, Leo; He, Bin

2013-01-01

Magneto acoustic tomography with magnetic induction (MAT-MI) is a technique proposed to reconstruct the conductivity distribution in biological tissue at ultrasound imaging resolution. A magnetic pulse is used to generate eddy currents in the object, which in the presence of a static magnetic field induces Lorentz force based acoustic waves in the medium. This time resolved acoustic waves are collected with ultrasound transducers and, in the present work, these are used to reconstruct the current source which gives rise to the MAT-MI acoustic signal using vector imaging point spread functions. The reconstructed source is then used to estimate the conductivity distribution of the object. Computer simulations and phantom experiments are performed to demonstrate conductivity reconstruction through vector source imaging in a circular scanning geometry with a limited bandwidth finite size piston transducer. The results demonstrate that the MAT-MI approach is capable of conductivity reconstruction in a physical setting. PMID:23322761

a Method for the Seamlines Network Automatic Selection Based on Building Vector

NASA Astrophysics Data System (ADS)

Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

2018-04-01

In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

Iris recognition using image moments and k-means algorithm.

PubMed

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%.

Iris Recognition Using Image Moments and k-Means Algorithm

PubMed Central

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%. PMID:24977221

Magnetoacoustic tomography with magnetic induction for high-resolution bioimepedance imaging through vector source reconstruction under the static field of MRI magnet

PubMed Central

Mariappan, Leo; Hu, Gang; He, Bin

2014-01-01

Purpose: Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging modality to reconstruct the electrical conductivity of biological tissue based on the acoustic measurements of Lorentz force induced tissue vibration. This study presents the feasibility of the authors' new MAT-MI system and vector source imaging algorithm to perform a complete reconstruction of the conductivity distribution of real biological tissues with ultrasound spatial resolution. Methods: In the present study, using ultrasound beamformation, imaging point spread functions are designed to reconstruct the induced vector source in the object which is used to estimate the object conductivity distribution. Both numerical studies and phantom experiments are performed to demonstrate the merits of the proposed method. Also, through the numerical simulations, the full width half maximum of the imaging point spread function is calculated to estimate of the spatial resolution. The tissue phantom experiments are performed with a MAT-MI imaging system in the static field of a 9.4 T magnetic resonance imaging magnet. Results: The image reconstruction through vector beamformation in the numerical and experimental studies gives a reliable estimate of the conductivity distribution in the object with a ∼1.5 mm spatial resolution corresponding to the imaging system frequency of 500 kHz ultrasound. In addition, the experiment results suggest that MAT-MI under high static magnetic field environment is able to reconstruct images of tissue-mimicking gel phantoms and real tissue samples with reliable conductivity contrast. Conclusions: The results demonstrate that MAT-MI is able to image the electrical conductivity properties of biological tissues with better than 2 mm spatial resolution at 500 kHz, and the imaging with MAT-MI under a high static magnetic field environment is able to provide improved imaging contrast for biological tissue conductivity reconstruction. PMID:24506649

Image coding using entropy-constrained residual vector quantization

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Barnes, Christopher F.

1993-01-01

The residual vector quantization (RVQ) structure is exploited to produce a variable length codeword RVQ. Necessary conditions for the optimality of this RVQ are presented, and a new entropy-constrained RVQ (ECRVQ) design algorithm is shown to be very effective in designing RVQ codebooks over a wide range of bit rates and vector sizes. The new EC-RVQ has several important advantages. It can outperform entropy-constrained VQ (ECVQ) in terms of peak signal-to-noise ratio (PSNR), memory, and computation requirements. It can also be used to design high rate codebooks and codebooks with relatively large vector sizes. Experimental results indicate that when the new EC-RVQ is applied to image coding, very high quality is achieved at relatively low bit rates.

Efficient storage and management of radiographic images using a novel wavelet-based multiscale vector quantizer

NASA Astrophysics Data System (ADS)

Yang, Shuyu; Mitra, Sunanda

2002-05-01

Due to the huge volumes of radiographic images to be managed in hospitals, efficient compression techniques yielding no perceptual loss in the reconstructed images are becoming a requirement in the storage and management of such datasets. A wavelet-based multi-scale vector quantization scheme that generates a global codebook for efficient storage and transmission of medical images is presented in this paper. The results obtained show that even at low bit rates one is able to obtain reconstructed images with perceptual quality higher than that of the state-of-the-art scalar quantization method, the set partitioning in hierarchical trees.

Optoelectronic Inner-Product Neural Associative Memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1993-01-01

Optoelectronic apparatus acts as artificial neural network performing associative recall of binary images. Recall process is iterative one involving optical computation of inner products between binary input vector and one or more reference binary vectors in memory. Inner-product method requires far less memory space than matrix-vector method.

Support Vector Machines Model of Computed Tomography for Assessing Lymph Node Metastasis in Esophageal Cancer with Neoadjuvant Chemotherapy.

PubMed

Wang, Zhi-Long; Zhou, Zhi-Guo; Chen, Ying; Li, Xiao-Ting; Sun, Ying-Shi

The aim of this study was to diagnose lymph node metastasis of esophageal cancer by support vector machines model based on computed tomography. A total of 131 esophageal cancer patients with preoperative chemotherapy and radical surgery were included. Various indicators (tumor thickness, tumor length, tumor CT value, total number of lymph nodes, and long axis and short axis sizes of largest lymph node) on CT images before and after neoadjuvant chemotherapy were recorded. A support vector machines model based on these CT indicators was built to predict lymph node metastasis. Support vector machines model diagnosed lymph node metastasis better than preoperative short axis size of largest lymph node on CT. The area under the receiver operating characteristic curves were 0.887 and 0.705, respectively. The support vector machine model of CT images can help diagnose lymph node metastasis in esophageal cancer with preoperative chemotherapy.

The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Kepner, J. V.; Janka, R. S.; Lebak, J.; Richards, M. A.

1999-12-01

The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.

Covariance estimation in Terms of Stokes Parameters with Application to Vector Sensor Imaging

DTIC Science & Technology

2016-12-15

S. Klein, “HF Vector Sensor for Radio Astronomy : Ground Testing Results,” in AIAA SPACE 2016, ser. AIAA SPACE Forum, American Institute of... astronomy ,” in 2016 IEEE Aerospace Conference, Mar. 2016, pp. 1–17. doi: 10.1109/ AERO.2016.7500688. [4] K.-C. Ho, K.-C. Tan, and B. T. G. Tan, “Estimation of...Statistical Imaging in Radio Astronomy via an Expectation-Maximization Algorithm for Structured Covariance Estimation,” in Statistical Methods in Imaging: IN

Vector quantizer based on brightness maps for image compression with the polynomial transform

NASA Astrophysics Data System (ADS)

Escalante-Ramirez, Boris; Moreno-Gutierrez, Mauricio; Silvan-Cardenas, Jose L.

2002-11-01

We present a vector quantization scheme acting on brightness fields based on distance/distortion criteria correspondent with psycho-visual aspects. These criteria quantify sensorial distortion between vectors that represent either portions of a digital image or alternatively, coefficients of a transform-based coding system. In the latter case, we use an image representation model, namely the Hermite transform, that is based on some of the main perceptual characteristics of the human vision system (HVS) and in their response to light stimulus. Energy coding in the brightness domain, determination of local structure, code-book training and local orientation analysis are all obtained by means of the Hermite transform. This paper, for thematic reasons, is divided in four sections. The first one will shortly highlight the importance of having newer and better compression algorithms. This section will also serve to explain briefly the most relevant characteristics of the HVS, advantages and disadvantages related with the behavior of our vision in front of ocular stimulus. The second section shall go through a quick review of vector quantization techniques, focusing their performance on image treatment, as a preview for the image vector quantizer compressor actually constructed in section 5. Third chapter was chosen to concentrate the most important data gathered on brightness models. The building of this so-called brightness maps (quantification of the human perception on the visible objects reflectance), in a bi-dimensional model, will be addressed here. The Hermite transform, a special case of polynomial transforms, and its usefulness, will be treated, in an applicable discrete form, in the fourth chapter. As we have learned from previous works 1, Hermite transform has showed to be a useful and practical solution to efficiently code the energy within an image block, deciding which kind of quantization is to be used upon them (whether scalar or vector). It will also be a unique tool to structurally classify the image block within a given lattice. This particular operation intends to be one of the main contributions of this work. The fifth section will fuse the proposals derived from the study of the three main topics- addressed in the last sections- in order to propose an image compression model that takes advantage of vector quantizers inside the brightness transformed domain to determine the most important structures, finding the energy distribution inside the Hermite domain. Sixth and last section will show some results obtained while testing the coding-decoding model. The guidelines to evaluate the image compressing performance were the compression ratio, SNR and psycho-visual quality. Some conclusions derived from the research and possible unexplored paths will be shown on this section as well.

Modeling respiratory motion for reducing motion artifacts in 4D CT images.

PubMed

Zhang, Yongbin; Yang, Jinzhong; Zhang, Lifei; Court, Laurence E; Balter, Peter A; Dong, Lei

2013-04-01

Four-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. However, significant image distortions (artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts. The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a lung cancer patient by comparing the synthesized images and the original images at different phases. The synthesized images matched well with the original images. The motion model was used to reduce irregular motion artifacts in the 4D CT images of three lung cancer patients. Visual assessment indicated that the proposed approach could reduce severe image artifacts. The shape distortions around the diaphragm and tumor regions were mitigated in the synthesized 4D CT images. The authors have derived a mathematical model to represent the regular respiratory motion from a patient-specific 4D CT set and have demonstrated its application in reducing irregular motion artifacts in 4D CT images. The authors' approach can mitigate shape distortions of anatomy caused by irregular breathing motion during 4D CT acquisition.

Safety of the Wearable Cardioverter Defibrillator (WCD) in Patients with Implanted Pacemakers.

PubMed

Schmitt, Joern; Abaci, Guezine; Johnson, Victoria; Erkapic, Damir; Gemein, Christopher; Chasan, Ritvan; Weipert, Kay; Hamm, Christian W; Klein, Helmut U

2017-03-01

The wearable cardioverter defibrillator (WCD) is an important approach for better risk stratification, applied to patients considered to be at high risk of sudden arrhythmic death. Patients with implanted pacemakers may also become candidates for use of the WCD. However, there is a potential risk that pacemaker signals may mislead the WCD detection algorithm and cause inappropriate WCD shock delivery. The aim of the study was to test the impact of different types of pacing, various right ventricular (RV) lead positions, and pacing modes for potential misleading of the WCD detection algorithm. Sixty patients with implanted pacemakers received the WCD for a short time and each pacing mode (AAI, VVI, and DDD) was tested for at least 30 seconds in unipolar and bipolar pacing configuration. In case of triggering the WCD detection algorithm and starting the sequence of arrhythmia alarms, shock delivery was prevented by pushing of the response buttons. In six of 60 patients (10%), continuous unipolar pacing in DDD mode triggered the WCD detection algorithm. In no patient, triggering occurred with bipolar DDD pacing, unipolar and bipolar AAI, and VVI pacing. Triggering was independent of pacing amplitude, RV pacing lead position, and pulse generator implantation site. Unipolar DDD pacing bears a high risk of false triggering of the WCD detection algorithm. Other types of unipolar pacing and all bipolar pacing modes do not seem to mislead the WCD detection algorithm. Therefore, patients with no reprogrammable unipolar DDD pacing should not become candidates for the WCD. © 2016 Wiley Periodicals, Inc.

DDD versus VVIR pacing in patients, ages 70 and over, with complete heart block.

PubMed

Ouali, Sana; Neffeti, Elyes; Ghoul, Karima; Hammas, Sami; Kacem, Slim; Gribaa, Rim; Remedi, Fahmi; Boughzela, Essia

2010-05-01

Dual-chamber pacing is believed to have an advantage over single-chamber ventricular pacing. The aim of the study was to determine whether elderly patients with implanted pacemaker for complete atrioventricular block gain significant benefit from dual-chamber (DDD) compared with single-chamber ventricular demand (VVIR). The study was designed as a double-blind randomized two-period crossover study-each pacing mode was maintained for 3 months. Thirty patients (eight men, mean age 76.5 +/- 4.3 years) with implanted PM were submitted to a standard protocol, which included an interview, functional class assessment, quality of life (QoL) questionnaires, 6-minute walk test, and transthoracic echocardiographic examinations. QoL was measured by the SF-36. All these parameters were obtained on DDD mode pacing and VVIR mode pacing. Paired data were compared. QoL was significantly different between the two groups and showed the best values in DDD. Overall, no patient preferred VVIR mode, 18 preferred DDD mode, and 12 expressed no preference. No differences in mean walking distances were observed between patients with single-chamber and dual-chamber pacing. VVI pacing elicited marked decrease in left ventricle ejection fraction and significant enlargement of the left atrium. DDD pacing resulted in significant increase of the peak systolic velocities in lateral mitral annulus and septal mitral annulus. Early diastolic velocities on both sides of mitral annulus did not change. In active elderly patients with complete heart block, DDD pacing is associated with improved quality of life and systolic ventricular function compared with VVI pacing.

Recognizing human activities using appearance metric feature and kinematics feature

NASA Astrophysics Data System (ADS)

Qian, Huimin; Zhou, Jun; Lu, Xinbiao; Wu, Xinye

2017-05-01

The problem of automatically recognizing human activities from videos through the fusion of the two most important cues, appearance metric feature and kinematics feature, is considered. And a system of two-dimensional (2-D) Poisson equations is introduced to extract the more discriminative appearance metric feature. Specifically, the moving human blobs are first detected out from the video by background subtraction technique to form a binary image sequence, from which the appearance feature designated as the motion accumulation image and the kinematics feature termed as centroid instantaneous velocity are extracted. Second, 2-D discrete Poisson equations are employed to reinterpret the motion accumulation image to produce a more differentiated Poisson silhouette image, from which the appearance feature vector is created through the dimension reduction technique called bidirectional 2-D principal component analysis, considering the balance between classification accuracy and time consumption. Finally, a cascaded classifier based on the nearest neighbor classifier and two directed acyclic graph support vector machine classifiers, integrated with the fusion of the appearance feature vector and centroid instantaneous velocity vector, is applied to recognize the human activities. Experimental results on the open databases and a homemade one confirm the recognition performance of the proposed algorithm.

An imaging vector magnetograph for the next solar maximum

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; Mickey, Donald L.

1988-01-01

Measurements of the vector magnetic field in the solar atmosphere with high spatial and temporal resolution over a large field of view are critical to understanding the nature and evolution of currents in active regions. Such measurements, when combined with the thermal and nonthermal X-ray images from the upcoming Solar-A mission, will reveal the large-scale relationship between these currents and sites of heating and particle acceleration in flaring coronal magnetic flux tubes. The conceptual design of an imaging vector magnetograph that combines a modest solar telescope with a rotating quarter-wave plate, an acousto-optical tunable prefilter as a blocker for a servo-controlled Fabry-Perot etalon, CCD cameras, and a rapid digital tape recorder are described. Its high spatial resolution (1/2 arcsec pixel size) over a large field of view (4 x 5 arcmin) will be sufficient to significantly measure, for the first time, the magnetic energy dissipated in major solar flares. Its millisecond tunability and wide spectra range (5000 to 8000 A) enable nearly simultaneous vector magnetic field measurements in the gas-pressure-dominated photosphere and magnetically dominated chromosphere, as well as effective co-alignment with Solar-A's X-ray images.

Rapid surface defect detection based on singular value decomposition using steel strips as an example

NASA Astrophysics Data System (ADS)

Sun, Qianlai; Wang, Yin; Sun, Zhiyi

2018-05-01

For most surface defect detection methods based on image processing, image segmentation is a prerequisite for determining and locating the defect. In our previous work, a method based on singular value decomposition (SVD) was used to determine and approximately locate surface defects on steel strips without image segmentation. For the SVD-based method, the image to be inspected was projected onto its first left and right singular vectors respectively. If there were defects in the image, there would be sharp changes in the projections. Then the defects may be determined and located according sharp changes in the projections of each image to be inspected. This method was simple and practical but the SVD should be performed for each image to be inspected. Owing to the high time complexity of SVD itself, it did not have a significant advantage in terms of time consumption over image segmentation-based methods. Here, we present an improved SVD-based method. In the improved method, a defect-free image is considered as the reference image which is acquired under the same environment as the image to be inspected. The singular vectors of each image to be inspected are replaced by the singular vectors of the reference image, and SVD is performed only once for the reference image off-line before detecting of the defects, thus greatly reducing the time required. The improved method is more conducive to real-time defect detection. Experimental results confirm its validity.

GaAs Supercomputing: Architecture, Language, And Algorithms For Image Processing

NASA Astrophysics Data System (ADS)

Johl, John T.; Baker, Nick C.

1988-10-01

The application of high-speed GaAs processors in a parallel system matches the demanding computational requirements of image processing. The architecture of the McDonnell Douglas Astronautics Company (MDAC) vector processor is described along with the algorithms and language translator. Most image and signal processing algorithms can utilize parallel processing and show a significant performance improvement over sequential versions. The parallelization performed by this system is within each vector instruction. Since each vector has many elements, each requiring some computation, useful concurrent arithmetic operations can easily be performed. Balancing the memory bandwidth with the computation rate of the processors is an important design consideration for high efficiency and utilization. The architecture features a bus-based execution unit consisting of four to eight 32-bit GaAs RISC microprocessors running at a 200 MHz clock rate for a peak performance of 1.6 BOPS. The execution unit is connected to a vector memory with three buses capable of transferring two input words and one output word every 10 nsec. The address generators inside the vector memory perform different vector addressing modes and feed the data to the execution unit. The functions discussed in this paper include basic MATRIX OPERATIONS, 2-D SPATIAL CONVOLUTION, HISTOGRAM, and FFT. For each of these algorithms, assembly language programs were run on a behavioral model of the system to obtain performance figures.

Flow velocity vector fields by ultrasound particle imaging velocimetry: in vitro comparison with optical flow velocimetry.

PubMed

Westerdale, John; Belohlavek, Marek; McMahon, Eileen M; Jiamsripong, Panupong; Heys, Jeffrey J; Milano, Michele

2011-02-01

We performed an in vitro study to assess the precision and accuracy of particle imaging velocimetry (PIV) data acquired using a clinically available portable ultrasound system via comparison with stereo optical PIV. The performance of ultrasound PIV was compared with optical PIV on a benchmark problem involving vortical flow with a substantial out-of-plane velocity component. Optical PIV is capable of stereo image acquisition, thus measuring out-of-plane velocity components. This allowed us to quantify the accuracy of ultrasound PIV, which is limited to in-plane acquisition. The system performance was assessed by considering the instantaneous velocity fields without extracting velocity profiles by spatial averaging. Within the 2-dimensional correlation window, using 7 time-averaged frames, the vector fields were found to have correlations of 0.867 in the direction along the ultrasound beam and 0.738 in the perpendicular direction. Out-of-plane motion of greater than 20% of the in-plane vector magnitude was found to increase the SD by 11% for the vectors parallel to the ultrasound beam direction and 8.6% for the vectors perpendicular to the beam. The results show a close correlation and agreement of individual velocity vectors generated by ultrasound PIV compared with optical PIV. Most of the measurement distortions were caused by out-of-plane velocity components.

Evaluation of global and regional right ventricular systolic function in patients with pulmonary hypertension using a novel speckle tracking method.

PubMed

Pirat, Bahar; McCulloch, Marti L; Zoghbi, William A

2006-09-01

This study sought to demonstrate that a novel speckle-tracking method can be used to assess right ventricular (RV) global and regional systolic function. Fifty-eight patients with pulmonary arterial hypertension (11 men; mean age 53 +/- 14 years) and 19 age-matched controls were studied. Echocardiographic images in apical planes were analyzed by conventional manual tracing for volumes and ejection fractions and by novel software (Axius Velocity Vector Imaging). Myocardial velocity, strain rate, and strain were determined at the basal, mid, and apical segments of the RV free wall and ventricular septum by Velocity Vector Imaging. RV volumes and ejection fractions obtained with manual tracing correlated strongly with the same indexes obtained by the Velocity Vector Imaging method in all subjects (r = 0.95 to 0.98, p < 0.001 for all). Peak systolic myocardial velocities, strain rate, and strain were significantly impaired in patients with pulmonary arterial hypertension compared with controls and were most altered in patients with the most severe pulmonary arterial hypertension (p < 0.05 for all). Pulmonary artery systolic pressure and a Doppler index of pulmonary vascular resistance were independent predictors of RV strain (r = -0.61 and r = -0.65, respectively, p < 0.05 for both). In conclusion, the new automated Velocity Vector Imaging method provides simultaneous quantitation of global and regional RV function that is angle independent and can be applied retrospectively to already stored digital images.

Long-term development of the Czech landscape studied on the basis of old topographic maps

NASA Astrophysics Data System (ADS)

Skokanová, H.; Havlíček, M.

2009-04-01

The paper deals with long-term land use changes in the Czech Republic with the help of old topographic maps. Departments of Landscape Ecology and GIS Applications from the Silva Tarouca Research Institute for Landscape and Ornamental Gardening, v.v.i. study these changes mainly in the research project MSM 6293359101 Research into sources and indicators of biodiversity in cultural landscape in the context of its fragmentation dynamics, the subpart Quantitative analysis of the dynamics of the Czech landscape development. In this paper, the authors concentrate mainly on map sources, which were acquired for the purpose of the project and also introduce partial results. Maps, which are the sources for the analyses, are following: maps from 2nd Austrian military survey in the scale 1:28 800 (created for the territory of the Czech Republic in the period 1836-1852), maps from 3rd Austrian military survey in the scale 1:25 000 (created for the Czech Republic in the period 1876-1880), Czechoslovak military topographic maps in the scale 1:25 000 from 1950s and 1990s, and Czech topographic base maps in the scale 1:10 000 from 2002-2006. It is necessary to complete maps of the 2nd and 3rd Austrian military survey thanks to their incompleteness, mainly along state borders. Also maps from 1nd Austrian military survey in the scale 1:28 800 (created for the Czech Republic in the period 1764-1783) are available; however, their usage for the accurate analyses in the GIS environment is restricted by their poor cartographic accuracy. Apart of the above mentioned maps, there has been progress in collecting maps from the interwar and war period (revised maps of the 3rd Austrian military survey maps, maps of the provisional military survey from 1923-1933, maps of definitive military survey from 1934-1938 and maps from survey of Moravian part of the Protectorate of Bohemia and Moravia, so called Messtischblätter from 1939-1945). Maps from five periods are manually vectorised in the GIS environment. When vectorizing maps, nine land use categories are distinguished according to the methodology created at the author's workplace. Only areas larger than 0.8 ha are vectorized with regard to the output scale of the project (1:200 000), which includes the whole territory of the republic. The so far vectorized areas are shown in the overview maps. The main analyses lay in overlaying vectorized maps and in calculation of the number of land use changes for the whole researched period. These then show stable areas, i.e. areas where no change in land use occurred, and dynamic areas with one or more changes. Also types of the land use changes both among individual maps and for the whole period can be detected.

Robust resolution enhancement optimization methods to process variations based on vector imaging model

NASA Astrophysics Data System (ADS)

Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong

2012-03-01

Optical proximity correction (OPC) and phase shifting mask (PSM) are the most widely used resolution enhancement techniques (RET) in the semiconductor industry. Recently, a set of OPC and PSM optimization algorithms have been developed to solve for the inverse lithography problem, which are only designed for the nominal imaging parameters without giving sufficient attention to the process variations due to the aberrations, defocus and dose variation. However, the effects of process variations existing in the practical optical lithography systems become more pronounced as the critical dimension (CD) continuously shrinks. On the other hand, the lithography systems with larger NA (NA>0.6) are now extensively used, rendering the scalar imaging models inadequate to describe the vector nature of the electromagnetic field in the current optical lithography systems. In order to tackle the above problems, this paper focuses on developing robust gradient-based OPC and PSM optimization algorithms to the process variations under a vector imaging model. To achieve this goal, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. The steepest descent algorithm is used to optimize the mask iteratively. In order to improve the efficiency of the proposed algorithms, a set of algorithm acceleration techniques (AAT) are exploited during the optimization procedure.

Vector Acoustics, Vector Sensors, and 3D Underwater Imaging

NASA Astrophysics Data System (ADS)

Lindwall, D.

2007-12-01

Vector acoustic data has two more dimensions of information than pressure data and may allow for 3D underwater imaging with much less data than with hydrophone data. The vector acoustic sensors measures the particle motions due to passing sound waves and, in conjunction with a collocated hydrophone, the direction of travel of the sound waves. When using a controlled source with known source and sensor locations, the reflection points of the sound field can be determined with a simple trigonometric calculation. I demonstrate this concept with an experiment that used an accelerometer based vector acoustic sensor in a water tank with a short-pulse source and passive scattering targets. The sensor consists of a three-axis accelerometer and a matched hydrophone. The sound source was a standard transducer driven by a short 7 kHz pulse. The sensor was suspended in a fixed location and the hydrophone was moved about the tank by a robotic arm to insonify the tank from many locations. Several floats were placed in the tank as acoustic targets at diagonal ranges of approximately one meter. The accelerometer data show the direct source wave as well as the target scattered waves and reflections from the nearby water surface, tank bottom and sides. Without resorting to the usual methods of seismic imaging, which in this case is only two dimensional and relied entirely on the use of a synthetic source aperture, the two targets, the tank walls, the tank bottom, and the water surface were imaged. A directional ambiguity inherent to vector sensors is removed by using collocated hydrophone data. Although this experiment was in a very simple environment, it suggests that 3-D seismic surveys may be achieved with vector sensors using the same logistics as a 2-D survey that uses conventional hydrophones. This work was supported by the Office of Naval Research, program element 61153N.

A method to rapidly and accurately compare relative efficacies of non-invasive imaging reporter genes in a mouse model, and its application to luciferase reporters

PubMed Central

Gil, Jose S.; Machado, Hidevaldo B.; Herschman, Harvey R.

2013-01-01

Purpose Our goal is to develop a simple, quantitative, robust method to compare the efficacy of imaging reporter genes in culture and in vivo. We describe an adenoviral vector-liver transduction procedure, and compare the luciferase reporter efficacies. Procedures Alternative reporter genes are expressed in a common adenoviral vector. Vector amounts used in vivo are based on cell culture titrations, ensuring the same transduction efficacy is used for each vector. After imaging, in vivo and in vitro values are normalized to hepatic vector transduction using quantitative real-time PCR. Results We assayed standard firefly luciferase (FLuc), enhanced firefly luciferase (EFLuc), luciferase 2 (Luc2), humanized Renilla luciferase (hRLuc), Renilla luciferase 8.6-535 (RLuc8.6), and a membrane-bound Gaussia luciferase variant (extGLuc) in cell culture and in vivo. We observed a greater that 100-fold increase in bioluminescent signal for both EFLuc and Luc2 when compared to FLuc, and a greater than 106-fold increase for RLuc8.6 when compared to hRLuc. ExtGLuc was not detectable in liver. Conclusions Our findings contrast, in some cases, with conclusions drawn in prior comparisons of these reporter genes, and demonstrate the need for a standardized method to evaluate alternative reporter genes in vivo. Our procedure can be adapted for reporter genes that utilize alternative imaging modalities (fluorescence, bioluminescence, MRI, SPECT, PET). PMID:21850545

Fuzzy Logic Particle Tracking

NASA Technical Reports Server (NTRS)

2005-01-01

A new all-electronic Particle Image Velocimetry technique that can efficiently map high speed gas flows has been developed in-house at the NASA Lewis Research Center. Particle Image Velocimetry is an optical technique for measuring the instantaneous two component velocity field across a planar region of a seeded flow field. A pulsed laser light sheet is used to illuminate the seed particles entrained in the flow field at two instances in time. One or more charged coupled device (CCD) cameras can be used to record the instantaneous positions of particles. Using the time between light sheet pulses and determining either the individual particle displacements or the average displacement of particles over a small subregion of the recorded image enables the calculation of the fluid velocity. Fuzzy logic minimizes the required operator intervention in identifying particles and computing velocity. Using two cameras that have the same view of the illumination plane yields two single exposure image frames. Two competing techniques that yield unambiguous velocity vector direction information have been widely used for reducing the single-exposure, multiple image frame data: (1) cross-correlation and (2) particle tracking. Correlation techniques yield averaged velocity estimates over subregions of the flow, whereas particle tracking techniques give individual particle velocity estimates. For the correlation technique, the correlation peak corresponding to the average displacement of particles across the subregion must be identified. Noise on the images and particle dropout result in misidentification of the true correlation peak. The subsequent velocity vector maps contain spurious vectors where the displacement peaks have been improperly identified. Typically these spurious vectors are replaced by a weighted average of the neighboring vectors, thereby decreasing the independence of the measurements. In this work, fuzzy logic techniques are used to determine the true correlation displacement peak even when it is not the maximum peak, hence maximizing the information recovery from the correlation operation, maintaining the number of independent measurements, and minimizing the number of spurious velocity vectors. Correlation peaks are correctly identified in both high and low seed density cases. The correlation velocity vector map can then be used as a guide for the particle-tracking operation. Again fuzzy logic techniques are used, this time to identify the correct particle image pairings between exposures to determine particle displacements, and thus the velocity. Combining these two techniques makes use of the higher spatial resolution available from the particle tracking. Particle tracking alone may not be possible in the high seed density images typically required for achieving good results from the correlation technique. This two-staged velocimetric technique can measure particle velocities with high spatial resolution over a broad range of seeding densities.

Asynchronous arterial systolic expansion as a marker of vascular aging: assessment of the carotid artery with velocity vector imaging.

PubMed

Yang, Woo-In; Shim, Chi Y; Bang, Woo D; Oh, Chang M; Chang, Hyuk J; Chung, Namsik; Ha, Jong-Won

2011-12-01

Arterial elastic properties change with aging. Measurements of pulse wave velocity and augmentation index are useful for the evaluation of arterial stiffness. However, they likely represent only global characteristics of the arterial tree rather than local vascular alterations. The aim of this study was to evaluate whether local vascular properties assessed by velocity vector imaging differed with aging. Vascular properties of carotid arteries with ages were assessed in 100 healthy volunteers (52 men) ranging from 20 to 68 years using velocity vector imaging. The peak circumferential strain and strain rate of the six segments in left common carotid arteries were analyzed and the standard deviation of the time to peak circumferential strain and strain rate of the six segments, representing the synchronicity of the arterial expansion, were calculated. Central blood pressure, augmentation index and pulse wave velocity were assessed by commercially available radial artery tonometry, the SphygmoCor system (AtCor Medical, West Ryde, Australia). A validated generalized transfer function was used to acquire the central aortic pressures and pressure waveforms. Pulse wave velocity, augmentation index and velocity vector imaging parameters showed significant changes with age. However, the age-related changes in pulse wave velocity, augmentation index and velocity vector imaging parameters were different. The increase in pulse wave velocity was more prominent in older individuals, whereas the changes in augmentation index and carotid strain and strain rate were evident earlier, at the age of 30 years. Unlike augmentation index, which showed little change in older individuals, the standard deviation of time to peak strain and strain rate showed a steady increase from younger to older individuals. Asynchronous arterial expansion could be a useful discriminative marker of vascular aging independent of individual's age.

Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion.

PubMed

Li, Gang; Liu, Tianming; Nie, Jingxin; Guo, Lei; Malicki, Jarema; Mara, Andrew; Holley, Scott A; Xia, Weiming; Wong, Stephen T C

2007-10-01

The zebrafish has become an important vertebrate animal model for the study of developmental biology, functional genomics, and disease mechanisms. It is also being used for drug discovery. Computerized detection of blob objects has been one of the important tasks in quantitative phenotyping of zebrafish. We present a new automated method that is able to detect blob objects, such as nuclei or cells in microscopic zebrafish images. This method is composed of three key steps. The first step is to produce a diffused gradient vector field by a physical elastic deformable model. In the second step, the flux image is computed on the diffused gradient vector field. The third step performs thresholding and nonmaximum suppression based on the flux image. We report the validation and experimental results of this method using zebrafish image datasets from three independent research labs. Both sensitivity and specificity of this method are over 90%. This method is able to differentiate closely juxtaposed or connected blob objects, with high sensitivity and specificity in different situations. It is characterized by a good, consistent performance in blob object detection.

Dynamic right ventricular outflow tract (infundibular) stenosis and pectus excavatum in a dog

PubMed Central

Fournier, Tanya E.

2008-01-01

This is the first published report of a dog with dynamic right ventricular outflow tract (infundibular) stenosis, right ventricular hypertrophy, and pectus excavatum. A juvenile dog presented with a grade V/VI left base systolic heart murmur, tachycardia, and pectus excavatum. Diagnosis of the aforementioned conditions was based on radiography, electrocardiography, and echocardiography. At 9 1/2 wk of age the heart murmur was no longer audible and the right ventricular stenosis and hypertrophy had dissipated and regressed, respectively. Resolution may be associated with growth of the dog. A good prognosis is foreseen. PMID:18512460

Progressive Vector Quantization on a massively parallel SIMD machine with application to multispectral image data

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1994-01-01

A progressive vector quantization (VQ) compression approach is discussed which decomposes image data into a number of levels using full search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the Advanced Very High Resolution Radiometer instrument and other Earth observation image data, and investigate the trade-offs in selecting the number of decomposition levels and codebook training method.

A low-cost vector processor boosting compute-intensive image processing operations

NASA Technical Reports Server (NTRS)

Adorf, Hans-Martin

1992-01-01

Low-cost vector processing (VP) is within reach of everyone seriously engaged in scientific computing. The advent of affordable add-on VP-boards for standard workstations complemented by mathematical/statistical libraries is beginning to impact compute-intensive tasks such as image processing. A case in point in the restoration of distorted images from the Hubble Space Telescope. A low-cost implementation is presented of the standard Tarasko-Richardson-Lucy restoration algorithm on an Intel i860-based VP-board which is seamlessly interfaced to a commercial, interactive image processing system. First experience is reported (including some benchmarks for standalone FFT's) and some conclusions are drawn.

Vision based nutrient deficiency classification in maize plants using multi class support vector machines

NASA Astrophysics Data System (ADS)

Leena, N.; Saju, K. K.

2018-04-01

Nutritional deficiencies in plants are a major concern for farmers as it affects productivity and thus profit. The work aims to classify nutritional deficiencies in maize plant in a non-destructive mannerusing image processing and machine learning techniques. The colored images of the leaves are analyzed and classified with multi-class support vector machine (SVM) method. Several images of maize leaves with known deficiencies like nitrogen, phosphorous and potassium (NPK) are used to train the SVM classifier prior to the classification of test images. The results show that the method was able to classify and identify nutritional deficiencies.

Polarimetric signature imaging of anisotropic bio-medical tissues

NASA Astrophysics Data System (ADS)

Wu, Stewart H.; Yang, De-Ming; Chiou, Arthur; Nee, Soe-Mie F.; Nee, Tsu-Wei

2010-02-01

Polarimetric imaging of Stokes vector (I, Q, U, V) can provide 4 independent signatures showing the linear and circular polarizations of biological tissues and cells. Using a recently developed Stokes digital imaging system, we measured the Stokes vector images of tissue samples from sections of rat livers containing normal portions and hematomas. The derived Mueller matrix elements can quantitatively provide multi-signature data of the bio-sample. This polarimetric optical technology is a new option of biosensing technology to inspect the structures of tissue samples, particularly for discriminating tumor and non-tumor biopsy. This technology is useful for critical disease discrimination and medical diagnostics applications.

Obstacle detection by recognizing binary expansion patterns

NASA Technical Reports Server (NTRS)

Baram, Yoram; Barniv, Yair

1993-01-01

This paper describes a technique for obstacle detection, based on the expansion of the image-plane projection of a textured object, as its distance from the sensor decreases. Information is conveyed by vectors whose components represent first-order temporal and spatial derivatives of the image intensity, which are related to the time to collision through the local divergence. Such vectors may be characterized as patterns corresponding to 'safe' or 'dangerous' situations. We show that essential information is conveyed by single-bit vector components, representing the signs of the relevant derivatives. We use two recently developed, high capacity classifiers, employing neural learning techniques, to recognize the imminence of collision from such patterns.

A new method of edge detection for object recognition

USGS Publications Warehouse

Maddox, Brian G.; Rhew, Benjamin

2004-01-01

Traditional edge detection systems function by returning every edge in an input image. This can result in a large amount of clutter and make certain vectorization algorithms less accurate. Accuracy problems can then have a large impact on automated object recognition systems that depend on edge information. A new method of directed edge detection can be used to limit the number of edges returned based on a particular feature. This results in a cleaner image that is easier for vectorization. Vectorized edges from this process could then feed an object recognition system where the edge data would also contain information as to what type of feature it bordered.

A study on locating the sonic source of sinusoidal magneto-acoustic signals using a vector method.

PubMed

Zhang, Shunqi; Zhou, Xiaoqing; Ma, Ren; Yin, Tao; Liu, Zhipeng

2015-01-01

Methods based on the magnetic-acoustic effect are of great significance in studying the electrical imaging properties of biological tissues and currents. The continuous wave method, which is commonly used, can only detect the current amplitude without the sound source position. Although the pulse mode adopted in magneto-acoustic imaging can locate the sonic source, the low measuring accuracy and low SNR has limited its application. In this study, a vector method was used to solve and analyze the magnetic-acoustic signal based on the continuous sine wave mode. This study includes theory modeling of the vector method, simulations to the line model, and experiments with wire samples to analyze magneto-acoustic (MA) signal characteristics. The results showed that the amplitude and phase of the MA signal contained the location information of the sonic source. The amplitude and phase obeyed the vector theory in the complex plane. This study sets a foundation for a new technique to locate sonic sources for biomedical imaging of tissue conductivity. It also aids in studying biological current detecting and reconstruction based on the magneto-acoustic effect.

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

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

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

Local alignment vectors reveal cancer cell-induced ECM fiber remodeling dynamics

PubMed Central

Lee, Byoungkoo; Konen, Jessica; Wilkinson, Scott; Marcus, Adam I.; Jiang, Yi

2017-01-01

Invasive cancer cells interact with the surrounding extracellular matrix (ECM), remodeling ECM fiber network structure by condensing, degrading, and aligning these fibers. We developed a novel local alignment vector analysis method to quantitatively measure collagen fiber alignment as a vector field using Circular Statistics. This method was applied to human non-small cell lung carcinoma (NSCLC) cell lines, embedded as spheroids in a collagen gel. Collagen remodeling was monitored using second harmonic generation imaging under normal conditions and when the LKB1-MARK1 pathway was disrupted through RNAi-based approaches. The results showed that inhibiting LKB1 or MARK1 in NSCLC increases the collagen fiber alignment and captures outward alignment vectors from the tumor spheroid, corresponding to high invasiveness of LKB1 mutant cancer cells. With time-lapse imaging of ECM micro-fiber morphology, the local alignment vector can measure the dynamic signature of invasive cancer cell activity and cell-migration-induced ECM and collagen remodeling and realigning dynamics. PMID:28045069

3D reconstruction of the magnetic vector potential using model based iterative reconstruction.

PubMed

Prabhat, K C; Aditya Mohan, K; Phatak, Charudatta; Bouman, Charles; De Graef, Marc

2017-11-01

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. A comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach. Copyright © 2017 Elsevier B.V. All rights reserved.

Earth Observation and Indicators Pertaining to Determinants of Health- An Approach to Support Local Scale Characterization of Environmental Determinants of Vector-Borne Diseases

NASA Astrophysics Data System (ADS)

Kotchi, Serge Olivier; Brazeau, Stephanie; Ludwig, Antoinette; Aube, Guy; Berthiaume, Pilippe

2016-08-01

Environmental determinants (EVDs) were identified as key determinant of health (DoH) for the emergence and re-emergence of several vector-borne diseases. Maintaining ongoing acquisition of data related to EVDs at local scale and for large regions constitutes a significant challenge. Earth observation (EO) satellites offer a framework to overcome this challenge. However, EO image analysis methods commonly used to estimate EVDs are time and resource consuming. Moreover, variations of microclimatic conditions combined with high landscape heterogeneity limit the effectiveness of climatic variables derived from EO. In this study, we present what are DoH and EVDs, the impacts of EVDs on vector-borne diseases in the context of global environmental change, the need to characterize EVDs of vector-borne diseases at local scale and its challenges, and finally we propose an approach based on EO images to estimate at local scale indicators pertaining to EVDs of vector-borne diseases.

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

DOE PAGES

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta; ...

2017-07-03

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

Fast higher-order MR image reconstruction using singular-vector separation.

PubMed

Wilm, Bertram J; Barmet, Christoph; Pruessmann, Klaas P

2012-07-01

Medical resonance imaging (MRI) conventionally relies on spatially linear gradient fields for image encoding. However, in practice various sources of nonlinear fields can perturb the encoding process and give rise to artifacts unless they are suitably addressed at the reconstruction level. Accounting for field perturbations that are neither linear in space nor constant over time, i.e., dynamic higher-order fields, is particularly challenging. It was previously shown to be feasible with conjugate-gradient iteration. However, so far this approach has been relatively slow due to the need to carry out explicit matrix-vector multiplications in each cycle. In this work, it is proposed to accelerate higher-order reconstruction by expanding the encoding matrix such that fast Fourier transform can be employed for more efficient matrix-vector computation. The underlying principle is to represent the perturbing terms as sums of separable functions of space and time. Compact representations with this property are found by singular-vector analysis of the perturbing matrix. Guidelines for balancing the accuracy and speed of the resulting algorithm are derived by error propagation analysis. The proposed technique is demonstrated for the case of higher-order field perturbations due to eddy currents caused by diffusion weighting. In this example, image reconstruction was accelerated by two orders of magnitude.

Magnetic Resonance Imaging in Nondependent Pacemaker Patients with Pacemakers and Defibrillators with a Nearly Depleted Battery.

PubMed

Okamura, Hideo; Padmanabhan, Deepak; Watson, Robert E; Dalzell, Connie; Acker, Nancy; Jondal, Mary; Romme, Abby L; Cha, Yong-Mei; Asirvatham, Samuel J; Felmlee, Joel P; Friedman, Paul A

2017-05-01

Magnetic resonance imaging (MRI) in patients with non-MRI-conditional cardiac implantable electronic devices (CIEDs) has been shown to be safe when performed under closely monitored protocols. However, the safety of MRI in patients with devices with a nearly depleted battery has not been reported. Prospective data were collected between January 2008 and May 2015 in patients with non-MRI-conditional CIEDs undergoing clinically indicated MRI under institutional protocol. Patients who were pacemaker dependent were excluded. Patients whose devices were at elective replacement indicator (ERI) at the time of MRI or close to ERI (ERI or replacement for battery depletion within 3 months of scan) were identified through database review and analyzed for clinical events. MRI scans (n = 569) were performed in 442 patients. Of these, we identified 13 scans performed with a nearly depleted battery in nine patients. All scans with implantable cardioverter defibrillators (ICDs, n = 9) were uneventful. However, two scans with pacemakers close to ERI resulted in a power-on-reset (PoR) event. One scan with a pacemaker close to ERI that was programmed to DOO mode reached ERI during MRI and automatically changed to VVI mode. Additionally, one scan with a pacemaker at ERI did not allow programming. All pacemakers with events were implanted before 2005. Patients with pacemakers and ICDs with a nearly depleted battery can safely undergo MRI when patients are not pacemaker dependent. Attention should be paid because old devices can result in PoR or ERI during MRI, which may lead to oversensing and inhibition of pacing. © 2017 Wiley Periodicals, Inc.

Integrated Dual Imaging Detector

NASA Technical Reports Server (NTRS)

Rust, David M.

1999-01-01

A new type of image detector was designed to simultaneously analyze the polarization of light at all picture elements in a scene. The integrated Dual Imaging detector (IDID) consists of a lenslet array and a polarizing beamsplitter bonded to a commercial charge coupled device (CCD). The IDID simplifies the design and operation of solar vector magnetographs and the imaging polarimeters and spectroscopic imagers used, for example, in atmosphere and solar research. When used in a solar telescope, the vector magnetic fields on the solar surface. Other applications include environmental monitoring, robot vision, and medical diagnoses (through the eye). Innovations in the IDID include (1) two interleaved imaging arrays (one for each polarization plane); (2) large dynamic range (well depth of 10(exp 5) electrons per pixel); (3) simultaneous readout and display of both images; and (4) laptop computer signal processing to produce polarization maps in field situations.

Two-dimensional PCA-based human gait identification

NASA Astrophysics Data System (ADS)

Chen, Jinyan; Wu, Rongteng

2012-11-01

It is very necessary to recognize person through visual surveillance automatically for public security reason. Human gait based identification focus on recognizing human by his walking video automatically using computer vision and image processing approaches. As a potential biometric measure, human gait identification has attracted more and more researchers. Current human gait identification methods can be divided into two categories: model-based methods and motion-based methods. In this paper a two-Dimensional Principal Component Analysis and temporal-space analysis based human gait identification method is proposed. Using background estimation and image subtraction we can get a binary images sequence from the surveillance video. By comparing the difference of two adjacent images in the gait images sequence, we can get a difference binary images sequence. Every binary difference image indicates the body moving mode during a person walking. We use the following steps to extract the temporal-space features from the difference binary images sequence: Projecting one difference image to Y axis or X axis we can get two vectors. Project every difference image in the difference binary images sequence to Y axis or X axis difference binary images sequence we can get two matrixes. These two matrixes indicate the styles of one walking. Then Two-Dimensional Principal Component Analysis(2DPCA) is used to transform these two matrixes to two vectors while at the same time keep the maximum separability. Finally the similarity of two human gait images is calculated by the Euclidean distance of the two vectors. The performance of our methods is illustrated using the CASIA Gait Database.

A new integrated dual time-point amyloid PET/MRI data analysis method.

PubMed

Cecchin, Diego; Barthel, Henryk; Poggiali, Davide; Cagnin, Annachiara; Tiepolt, Solveig; Zucchetta, Pietro; Turco, Paolo; Gallo, Paolo; Frigo, Anna Chiara; Sabri, Osama; Bui, Franco

2017-11-01

In the initial evaluation of patients with suspected dementia and Alzheimer's disease, there is no consensus on how to perform semiquantification of amyloid in such a way that it: (1) facilitates visual qualitative interpretation, (2) takes the kinetic behaviour of the tracer into consideration particularly with regard to at least partially correcting for blood flow dependence, (3) analyses the amyloid load based on accurate parcellation of cortical and subcortical areas, (4) includes partial volume effect correction (PVEC), (5) includes MRI-derived topographical indexes, (6) enables application to PET/MRI images and PET/CT images with separately acquired MR images, and (7) allows automation. A method with all of these characteristics was retrospectively tested in 86 subjects who underwent amyloid ( 18 F-florbetaben) PET/MRI in a clinical setting (using images acquired 90-110 min after injection, 53 were classified visually as amyloid-negative and 33 as amyloid-positive). Early images after tracer administration were acquired between 0 and 10 min after injection, and later images were acquired between 90 and 110 min after injection. PVEC of the PET data was carried out using the geometric transfer matrix method. Parametric images and some regional output parameters, including two innovative "dual time-point" indexes, were obtained. Subjects classified visually as amyloid-positive showed a sparse tracer uptake in the primary sensory, motor and visual areas in accordance with the isocortical stage of the topographic distribution of the amyloid plaque (Braak stages V/VI). In patients classified visually as amyloid-negative, the method revealed detectable levels of tracer uptake in the basal portions of the frontal and temporal lobes, areas that are known to be sites of early deposition of amyloid plaques that probably represented early accumulation (Braak stage A) that is typical of normal ageing. There was a strong correlation between age and the indexes of the new dual time-point amyloid imaging method in amyloid-negative patients. The method can be considered a valuable tool in both routine clinical practice and in the research setting as it will standardize data regarding amyloid deposition. It could potentially also be used to identify early amyloid plaque deposition in younger subjects in whom treatment could theoretically be more effective.

Streaking images that appear only in the plane of diffraction in undoped GaAs single crystals: Diffraction imaging (topography) by monochromatic synchrotron radiation

NASA Technical Reports Server (NTRS)

Kuriyama, Masao; Steiner, Bruce; Dobbyn, Ronald C.; Laor, Uri; Larson, David; Brown, Margaret

1988-01-01

Streaking images restricted to the direction of the diffraction (scattering) vector have been observed on transmission through undoped GaAs. These disruption images (caused by the reduction of diffraction in the direction of observation) appear both in the forward and in Bragg diffracted directions in monochromatic synchrontron radiation diffraction imaging. This previously unobserved phenomenon can be explained in terms of planar defects (interfaces) or platelets which affects the absorption coefficient in anomalous transmission. Such regions of the crystal look perfect despite the presence of imperfections when the scattering vector is not perpendicular to the normal of the platelets. The observed crystallographic orientation of these interfaces strongly indicates that they are antiphase boundaries.

A Query Expansion Framework in Image Retrieval Domain Based on Local and Global Analysis

PubMed Central

Rahman, M. M.; Antani, S. K.; Thoma, G. R.

2011-01-01

We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval. In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval. To generate the concept vocabularies, a statistical model is built by utilizing Support Vector Machine (SVM)-based classification techniques. The images are represented as “bag of concepts” that comprise perceptually and/or semantically distinguishable color and texture patches from local image regions in a multi-dimensional feature space. To explore the correlation between the concepts and overcome the assumption of feature independence in this model, we propose query expansion techniques in the image domain from a new perspective based on both local and global analysis. For the local analysis, the correlations between the concepts based on the co-occurrence pattern, and the metrical constraints based on the neighborhood proximity between the concepts in encoded images, are analyzed by considering local feedback information. We also analyze the concept similarities in the collection as a whole in the form of a similarity thesaurus and propose an efficient query expansion based on the global analysis. The experimental results on a photographic collection of natural scenes and a biomedical database of different imaging modalities demonstrate the effectiveness of the proposed framework in terms of precision and recall. PMID:21822350

Gross feature recognition of Anatomical Images based on Atlas grid (GAIA): Incorporating the local discrepancy between an atlas and a target image to capture the features of anatomic brain MRI.

PubMed

Qin, Yuan-Yuan; Hsu, Johnny T; Yoshida, Shoko; Faria, Andreia V; Oishi, Kumiko; Unschuld, Paul G; Redgrave, Graham W; Ying, Sarah H; Ross, Christopher A; van Zijl, Peter C M; Hillis, Argye E; Albert, Marilyn S; Lyketsos, Constantine G; Miller, Michael I; Mori, Susumu; Oishi, Kenichi

2013-01-01

We aimed to develop a new method to convert T1-weighted brain MRIs to feature vectors, which could be used for content-based image retrieval (CBIR). To overcome the wide range of anatomical variability in clinical cases and the inconsistency of imaging protocols, we introduced the Gross feature recognition of Anatomical Images based on Atlas grid (GAIA), in which the local intensity alteration, caused by pathological (e.g., ischemia) or physiological (development and aging) intensity changes, as well as by atlas-image misregistration, is used to capture the anatomical features of target images. As a proof-of-concept, the GAIA was applied for pattern recognition of the neuroanatomical features of multiple stages of Alzheimer's disease, Huntington's disease, spinocerebellar ataxia type 6, and four subtypes of primary progressive aphasia. For each of these diseases, feature vectors based on a training dataset were applied to a test dataset to evaluate the accuracy of pattern recognition. The feature vectors extracted from the training dataset agreed well with the known pathological hallmarks of the selected neurodegenerative diseases. Overall, discriminant scores of the test images accurately categorized these test images to the correct disease categories. Images without typical disease-related anatomical features were misclassified. The proposed method is a promising method for image feature extraction based on disease-related anatomical features, which should enable users to submit a patient image and search past clinical cases with similar anatomical phenotypes.

Median filtering detection using variation of neighboring line pairs for image forensics

NASA Astrophysics Data System (ADS)

Rhee, Kang Hyeon

2016-09-01

Attention to tampering by median filtering (MF) has recently increased in digital image forensics. For the MF detection (MFD), this paper presents a feature vector that is extracted from two kinds of variations between the neighboring line pairs: the row and column directions. Of these variations in the proposed method, one is defined by a gradient difference of the intensity values between the neighboring line pairs, and the other is defined by a coefficient difference of the Fourier transform (FT) between the neighboring line pairs. Subsequently, the constructed 19-dimensional feature vector is composed of these two parts. One is the extracted 9-dimensional from the space domain of an image and the other is the 10-dimensional from the frequency domain of an image. The feature vector is trained in a support vector machine classifier for MFD in the altered images. As a result, in the measured performances of the experimental items, the area under the receiver operating characteristic curve (AUC, ROC) by the sensitivity (PTP: the true positive rate) and 1-specificity (PFP: the false-positive rate) are above 0.985 and the classification ratios are also above 0.979. Pe (a minimal average decision error) ranges from 0 to 0.024, and PTP at PFP=0.01 ranges from 0.965 to 0.996. It is confirmed that the grade evaluation of the proposed variation-based MF detection method is rated as "Excellent (A)" by AUC is above 0.9.

Design and implementation of a cartographic client application for mobile devices using SVG Tiny and J2ME

NASA Astrophysics Data System (ADS)

Hui, L.; Behr, F.-J.; Schröder, D.

2006-10-01

The dissemination of digital geospatial data is available now on mobile devices such as PDAs (personal digital assistants) and smart-phones etc. The mobile devices which support J2ME (Java 2 Micro Edition) offer users and developers one open interface, which they can use to develop or download the software according their own demands. Currently WMS (Web Map Service) can afford not only traditional raster image, but also the vector image. SVGT (Scalable Vector Graphics Tiny) is one subset of SVG (Scalable Vector Graphics) and because of its precise vector information, original styling and small file size, SVGT format is fitting well for the geographic mapping purpose, especially for the mobile devices which has bandwidth net connection limitation. This paper describes the development of a cartographic client for the mobile devices, using SVGT and J2ME technology. Mobile device will be simulated on the desktop computer for a series of testing with WMS, for example, send request and get the responding data from WMS and then display both vector and raster format image. Analyzing and designing of System structure such as user interface and code structure are discussed, the limitation of mobile device should be taken into consideration for this applications. The parsing of XML document which is received from WMS after the GetCapabilities request and the visual realization of SVGT and PNG (Portable Network Graphics) image are important issues in codes' writing. At last the client was tested on Nokia S40/60 mobile phone successfully.

Neuron density is decreased in the prefrontal cortex in Williams syndrome.

PubMed

Lew, Caroline Horton; Brown, Chelsea; Bellugi, Ursula; Semendeferi, Katerina

2017-01-01

Williams Syndrome (WS) is a rare neurodevelopmental disorder associated with a hemideletion in chromosome 7, which manifests a distinct behavioral phenotype characterized by a hyperaffiliative social drive, in striking contrast to the social avoidance behaviors that are common in Autism Spectrum Disorder (ASD). MRI studies have observed structural and functional abnormalities in WS cortex, including the prefrontal cortex (PFC), a region implicated in social cognition. This study utilizes the Bellugi Williams Syndrome Brain Collection, a unique resource that comprises the largest WS postmortem brain collection in existence, and is the first to quantitatively examine WS PFC cytoarchitecture. We measured neuron density in layers II/III and V/VI of five cortical areas: PFC areas BA 10 and BA 11, primary motor BA 4, primary somatosensory BA 3, and visual area BA 18 in six matched pairs of WS and typically developing (TD) controls. Neuron density in PFC was lower in WS relative to TD, with layers V/VI demonstrating the largest decrease in density, reaching statistical significance in BA 10. In contrast, BA 3 and BA 18 demonstrated a higher density in WS compared to TD, although this difference was not statistically significant. Neuron density in BA 4 was similar in WS and TD. While other cortical areas were altered in WS, prefrontal areas appeared to be most affected. Neuron density is also altered in the PFC of individuals with ASD. Together these findings suggest that the PFC is targeted in neurodevelopmental disorders associated with sociobehavioral alterations. Autism Res 2017, 10: 99-112. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Neuropathological diagnostic criteria for Alzheimer's disease.

PubMed

Murayama, Shigeo; Saito, Yuko

2004-09-01

Neuropathological diagnostic criteria for Alzheimer's disease (AD) are based on tau-related pathology: NFT or neuritic plaques (NP). The Consortium to Establish a Registry for Alzheimer's disease (CERAD) criterion evaluates the highest density of neocortical NP from 0 (none) to C (abundant). Clinical documentation of dementia and NP stage A in younger cases, B in young old cases and C in older cases fulfils the criterion of AD. The CERAD criterion is most frequently used in clinical outcome studies because of its inclusion of clinical information. Braak and Braak's criterion evaluates the density and distribution of NFT and classifies them into: I/II, entorhinal; III/IV, limbic; and V/VI, neocortical stage. These three stages correspond to normal cognition, cognitive impairment and dementia, respectively. As Braak's criterion is based on morphological evaluation of the brain alone, this criterion is usually adopted in the research setting. The National Institute for Aging and Ronald and Nancy Reagan Institute of the Alzheimer's Association criterion combines these two criteria and categorizes cases into NFT V/VI and NP C, NFT III/IV and NP B, and NFT I/II and NP A, corresponding to high, middle and low probability of AD, respectively. As most AD cases in the aged population are categorized into Braak tangle stage IV and CERAD stage C, the usefulness of this criterion has not yet been determined. The combination of Braak's NFT stage equal to or above IV and Braak's senile plaque Stage C provides, arguably, the highest sensitivity and specificity. In future, the criteria should include in vivo dynamic neuropathological data, including 3D MRI, PET scan and CSF biomarkers, as well as more sensitive and specific immunohistochemical and immunochemical grading of AD.

Real time display Fourier-domain OCT using multi-thread parallel computing with data vectorization

NASA Astrophysics Data System (ADS)

Eom, Tae Joong; Kim, Hoon Seop; Kim, Chul Min; Lee, Yeung Lak; Choi, Eun-Seo

2011-03-01

We demonstrate a real-time display of processed OCT images using multi-thread parallel computing with a quad-core CPU of a personal computer. The data of each A-line are treated as one vector to maximize the data translation rate between the cores of the CPU and RAM stored image data. A display rate of 29.9 frames/sec for processed OCT data (4096 FFT-size x 500 A-scans) is achieved in our system using a wavelength swept source with 52-kHz swept frequency. The data processing times of the OCT image and a Doppler OCT image with a 4-time average are 23.8 msec and 91.4 msec.

Vector quantization

NASA Technical Reports Server (NTRS)

Gray, Robert M.

1989-01-01

During the past ten years Vector Quantization (VQ) has developed from a theoretical possibility promised by Shannon's source coding theorems into a powerful and competitive technique for speech and image coding and compression at medium to low bit rates. In this survey, the basic ideas behind the design of vector quantizers are sketched and some comments made on the state-of-the-art and current research efforts.

CW-THz vector spectroscopy and imaging system based on 1.55-µm fiber-optics.

PubMed

Kim, Jae-Young; Song, Ho-Jin; Yaita, Makoto; Hirata, Akihiko; Ajito, Katsuhiro

2014-01-27

We present a continuous-wave terahertz (THz) vector spectroscopy and imaging system based on a 1.5-µm fiber optic uni-traveling-carrier photodiode and InGaAs photo-conductive receiver. Using electro-optic (EO) phase modulators for THz phase control with shortened optical paths, the system achieves fast vector measurement with effective phase stabilization. Dynamic ranges of 100 dB · Hz and 75 dB · Hz at 300 GHz and 1 THz, and phase stability of 1.5° per minute are obtained. With the simultaneous measurement of absorbance and relative permittivity, we demonstrate non-destructive analyses of pharmaceutical cocrystals inside tablets within a few minutes.

Optical implementation of inner product neural associative memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor)

1995-01-01

An optical implementation of an inner-product neural associative memory is realized with a first spatial light modulator for entering an initial two-dimensional N-tuple vector and for entering a thresholded output vector image after each iteration until convergence is reached, and a second spatial light modulator for entering M weighted vectors of inner-product scalars multiplied with each of the M stored vectors, where the inner-product scalars are produced by multiplication of the initial input vector in the first iterative cycle (and thresholded vectors in subsequent iterative cycles) with each of the M stored vectors, and the weighted vectors are produced by multiplication of the scalars with corresponding ones of the stored vectors. A Hughes liquid crystal light valve is used for the dual function of summing the weighted vectors and thresholding the sum vector. The thresholded vector is then entered through the first spatial light modulator for reiteration of the process cycle until convergence is reached.

Lipid nanoparticle vectorization of indocyanine green improves fluorescence imaging for tumor diagnosis and lymph node resection.

PubMed

Navarro, Fabrice P; Berger, Michel; Guillermet, Stéphanie; Josserand, Véronique; Guyon, Laurent; Neumann, Emmanuelle; Vinet, Françoise; Texier, Isabelle

2012-10-01

Fluorescence imaging is opening a new era in image-guided surgery and other medical applications. The only FDA approved contrast agent in the near infrared is IndoCyanine Green (ICG), which despites its low toxicity, displays poor chemical and optical properties for long-term and sensitive imaging applications in human. Lipid nanoparticles are investigated for improving ICG optical properties and in vivo fluorescence imaging sensitivity. 30 nm diameter lipid nanoparticles (LNP) are loaded with ICG. Their characterization and use for tumor and lymph node imaging are described. Nano-formulation benefits dye optical properties (6 times improved brightness) and chemical stability (>6 months at 4 degrees C in aqueous buffer). More importantly, LNP vectorization allows never reported sensitive and prolonged (>1 day) labeling of tumors and lymph nodes. Composed of human-use approved ingredients, this novel ICG nanometric formulation is foreseen to expand rapidly the field of clinical fluorescence imaging applications.

Vector Quantization Algorithm Based on Associative Memories

NASA Astrophysics Data System (ADS)

Guzmán, Enrique; Pogrebnyak, Oleksiy; Yáñez, Cornelio; Manrique, Pablo

This paper presents a vector quantization algorithm for image compression based on extended associative memories. The proposed algorithm is divided in two stages. First, an associative network is generated applying the learning phase of the extended associative memories between a codebook generated by the LBG algorithm and a training set. This associative network is named EAM-codebook and represents a new codebook which is used in the next stage. The EAM-codebook establishes a relation between training set and the LBG codebook. Second, the vector quantization process is performed by means of the recalling stage of EAM using as associative memory the EAM-codebook. This process generates a set of the class indices to which each input vector belongs. With respect to the LBG algorithm, the main advantages offered by the proposed algorithm is high processing speed and low demand of resources (system memory); results of image compression and quality are presented.

Theory of high-resolution tunneling spin transport on a magnetic skyrmion

NASA Astrophysics Data System (ADS)

Palotás, Krisztián; Rózsa, Levente; Szunyogh, László

2018-05-01

Tunneling spin transport characteristics of a magnetic skyrmion are described theoretically in magnetic scanning tunneling microscopy (STM). The spin-polarized charge current in STM (SP-STM) and tunneling spin transport vector quantities, the longitudinal spin current and the spin transfer torque, are calculated in high spatial resolution within the same theoretical framework. A connection between the conventional charge current SP-STM image contrasts and the magnitudes of the spin transport vectors is demonstrated that enables the estimation of tunneling spin transport properties based on experimentally measured SP-STM images. A considerable tunability of the spin transport vectors by the involved spin polarizations is also highlighted. These possibilities and the combined theory of tunneling charge and vector spin transport pave the way for gaining deep insight into electric-current-induced tunneling spin transport properties in SP-STM and to the related dynamics of complex magnetic textures at surfaces.

Wind Field Extractions from SAR Sentinel-1 Images Using Electromagnetic Models

NASA Astrophysics Data System (ADS)

La, Tran Vu; Khenchaf, Ali; Comblet, Fabrice; Nahum, Carole

2016-08-01

Among available wind sources, i.e. measured data, numeric weather models, the retrieval of wind vectors from Synthetic Aperture Radar (SAR) data / images is particularly preferred due to a lot of SAR systems (available data in most meteorological conditions, revisit mode, high resolution, etc.). For this purpose, the retrieval of wind vectors is principally based on the empirical (EP) models, e.g. CMOD series in C-band. Little studies have been reported about the use of the electromagnetic (EM) models for wind vector retrieval, since it is quite complicated to invert. However, the EM models can be applied for most cases of polarization, frequency and wind regime. In order to evaluate the advantages and limits of the EM models for wind vector retrieval, we compare in this study estimated results by the EM and EP models for both cases of polarization (vertical-vertical, or VV-pol and horizontal- horizontal, or HH-pol).

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1996-01-01

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.

A VLSI chip set for real time vector quantization of image sequences

NASA Technical Reports Server (NTRS)

Baker, Richard L.

1989-01-01

The architecture and implementation of a VLSI chip set that vector quantizes (VQ) image sequences in real time is described. The chip set forms a programmable Single-Instruction, Multiple-Data (SIMD) machine which can implement various vector quantization encoding structures. Its VQ codebook may contain unlimited number of codevectors, N, having dimension up to K = 64. Under a weighted least squared error criterion, the engine locates at video rates the best code vector in full-searched or large tree searched VQ codebooks. The ability to manipulate tree structured codebooks, coupled with parallelism and pipelining, permits searches in as short as O (log N) cycles. A full codebook search results in O(N) performance, compared to O(KN) for a Single-Instruction, Single-Data (SISD) machine. With this VLSI chip set, an entire video code can be built on a single board that permits realtime experimentation with very large codebooks.

Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging.

PubMed

Deylami, Ali Mohades; Asl, Babak Mohammadzadeh

2018-06-04

Minimum variance beamformer (MVB) improves the resolution and contrast of medical ultrasound images compared with delay and sum (DAS) beamformer. The weight vector of this beamformer should be calculated for each imaging point independently, with a cost of increasing computational complexity. The large number of necessary calculations limits this beamformer to application in real-time systems. A beamformer is proposed based on the MVB with lower computational complexity while preserving its advantages. This beamformer avoids matrix inversion, which is the most complex part of the MVB, by solving the optimization problem iteratively. The received signals from two imaging points close together do not vary much in medical ultrasound imaging. Therefore, using the previously optimized weight vector for one point as initial weight vector for the new neighboring point can improve the convergence speed and decrease the computational complexity. The proposed method was applied on several data sets, and it has been shown that the method can regenerate the results obtained by the MVB while the order of complexity is decreased from O(L 3 ) to O(L 2 ). Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

An imaging vector magnetograph for the next solar maximum

NASA Technical Reports Server (NTRS)

Mickey, D. L.; Labonte, B. J.; Canfield, R. C.

1989-01-01

Researchers describe the conceptual design of a new imaging vector magnetograph currently being constructed at the University of Hawaii. The instrument combines a modest solar telescope with a rotating quarter-wave plate, an acousto-optical tunable prefilter as a blocker for a servo-controlled Fabry-Perot etalon, CCD cameras, and on-line digital image processing. Its high spatial resolution (1/2 arcsec pixel size) over a large field of view (5 by 5 arcmin) will be sufficient to significantly measure, for the first time, the magnetic energy dissipated in major solar flares. Its millisecond tunability and wide spectral range (5000 to 7000 A) enable nearly simultaneous vector magnetic field measurements in the gas-pressure-dominated photosphere and magnetically-dominated chromosphere, as well as effective co-alignment with Solar-A's X ray images. Researchers expect to have the instrument in operation at Mees Solar Observatory (Haleakala) in early 1991. They have chosen to use tunable filters as wavelength-selection elements in order to emphasize the spatial relationships between magnetic field elements, and to permit construction of a compact, efficient instrument. This means that spectral information must be obtained from sequences of images, which can cause line profile distortions due to effects of atmospheric seeing.

Detection of potential mosquito breeding sites based on community sourced geotagged images

NASA Astrophysics Data System (ADS)

Agarwal, Ankit; Chaudhuri, Usashi; Chaudhuri, Subhasis; Seetharaman, Guna

2014-06-01

Various initiatives have been taken all over the world to involve the citizens in the collection and reporting of data to make better and informed data-driven decisions. Our work shows how the geotagged images collected through the general population can be used to combat Malaria and Dengue by identifying and visualizing localities that contain potential mosquito breeding sites. Our method first employs image quality assessment on the client side to reject the images with distortions like blur and artifacts. Each geotagged image received on the server is converted into a feature vector using the bag of visual words model. We train an SVM classifier on a histogram-based feature vector obtained after the vector quantization of SIFT features to discriminate images containing either a small stagnant water body like puddle, or open containers and tires, bushes etc. from those that contain flowing water, manicured lawns, tires attached to a vehicle etc. A geographical heat map is generated by assigning a specific location a probability value of it being a potential mosquito breeding ground of mosquito using feature level fusion or the max approach presented in the paper. The heat map thus generated can be used by concerned health authorities to take appropriate action and to promote civic awareness.

Detection of Hard Exudates in Colour Fundus Images Using Fuzzy Support Vector Machine-Based Expert System.

PubMed

Jaya, T; Dheeba, J; Singh, N Albert

2015-12-01

Diabetic retinopathy is a major cause of vision loss in diabetic patients. Currently, there is a need for making decisions using intelligent computer algorithms when screening a large volume of data. This paper presents an expert decision-making system designed using a fuzzy support vector machine (FSVM) classifier to detect hard exudates in fundus images. The optic discs in the colour fundus images are segmented to avoid false alarms using morphological operations and based on circular Hough transform. To discriminate between the exudates and the non-exudates pixels, colour and texture features are extracted from the images. These features are given as input to the FSVM classifier. The classifier analysed 200 retinal images collected from diabetic retinopathy screening programmes. The tests made on the retinal images show that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and features sets, the area under the receiver operating characteristic curve reached 0.9606, which corresponds to a sensitivity of 94.1% with a specificity of 90.0%. The results suggest that detecting hard exudates using FSVM contribute to computer-assisted detection of diabetic retinopathy and as a decision support system for ophthalmologists.

Effective Moment Feature Vectors for Protein Domain Structures

PubMed Central

Shi, Jian-Yu; Yiu, Siu-Ming; Zhang, Yan-Ning; Chin, Francis Yuk-Lun

2013-01-01

Imaging processing techniques have been shown to be useful in studying protein domain structures. The idea is to represent the pairwise distances of any two residues of the structure in a 2D distance matrix (DM). Features and/or submatrices are extracted from this DM to represent a domain. Existing approaches, however, may involve a large number of features (100–400) or complicated mathematical operations. Finding fewer but more effective features is always desirable. In this paper, based on some key observations on DMs, we are able to decompose a DM image into four basic binary images, each representing the structural characteristics of a fundamental secondary structure element (SSE) or a motif in the domain. Using the concept of moments in image processing, we further derive 45 structural features based on the four binary images. Together with 4 features extracted from the basic images, we represent the structure of a domain using 49 features. We show that our feature vectors can represent domain structures effectively in terms of the following. (1) We show a higher accuracy for domain classification. (2) We show a clear and consistent distribution of domains using our proposed structural vector space. (3) We are able to cluster the domains according to our moment features and demonstrate a relationship between structural variation and functional diversity. PMID:24391828

Integrating image quality in 2nu-SVM biometric match score fusion.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2007-10-01

This paper proposes an intelligent 2nu-support vector machine based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images. The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each subband of the image. The match score and the corresponding quality score of an image are fused using 2nu-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms.

Deformation Invariant Attribute Vector for Deformable Registration of Longitudinal Brain MR Images

PubMed Central

Li, Gang; Guo, Lei; Liu, Tianming

2009-01-01

This paper presents a novel approach to define deformation invariant attribute vector (DIAV) for each voxel in 3D brain image for the purpose of anatomic correspondence detection. The DIAV method is validated by using synthesized deformation in 3D brain MRI images. Both theoretic analysis and experimental studies demonstrate that the proposed DIAV is invariant to general nonlinear deformation. Moreover, our experimental results show that the DIAV is able to capture rich anatomic information around the voxels and exhibit strong discriminative ability. The DIAV has been integrated into a deformable registration algorithm for longitudinal brain MR images, and the results on both simulated and real brain images are provided to demonstrate the good performance of the proposed registration algorithm based on matching of DIAVs. PMID:19369031

Segmentation of mosaicism in cervicographic images using support vector machines

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; Long, L. Rodney; Antani, Sameer; Jeronimo, Jose; Thoma, George R.

2009-02-01

The National Library of Medicine (NLM), in collaboration with the National Cancer Institute (NCI), is creating a large digital repository of cervicographic images for the study of uterine cervix cancer prevention. One of the research goals is to automatically detect diagnostic bio-markers in these images. Reliable bio-marker segmentation in large biomedical image collections is a challenging task due to the large variation in image appearance. Methods described in this paper focus on segmenting mosaicism, which is an important vascular feature used to visually assess the degree of cervical intraepithelial neoplasia. The proposed approach uses support vector machines (SVM) trained on a ground truth dataset annotated by medical experts (which circumvents the need for vascular structure extraction). We have evaluated the performance of the proposed algorithm and experimentally demonstrated its feasibility.

Optimizing modelling in iterative image reconstruction for preclinical pinhole PET

NASA Astrophysics Data System (ADS)

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

2016-05-01

The recently developed versatile emission computed tomography (VECTor) technology enables high-energy SPECT and simultaneous SPECT and PET of small animals at sub-mm resolutions. VECTor uses dedicated clustered pinhole collimators mounted in a scanner with three stationary large-area NaI(Tl) gamma detectors. Here, we develop and validate dedicated image reconstruction methods that compensate for image degradation by incorporating accurate models for the transport of high-energy annihilation gamma photons. Ray tracing software was used to calculate photon transport through the collimator structures and into the gamma detector. Input to this code are several geometric parameters estimated from system calibration with a scanning 99mTc point source. Effects on reconstructed images of (i) modelling variable depth-of-interaction (DOI) in the detector, (ii) incorporating photon paths that go through multiple pinholes (‘multiple-pinhole paths’ (MPP)), and (iii) including various amounts of point spread function (PSF) tail were evaluated. Imaging 18F in resolution and uniformity phantoms showed that including large parts of PSFs is essential to obtain good contrast-noise characteristics and that DOI modelling is highly effective in removing deformations of small structures, together leading to 0.75 mm resolution PET images of a hot-rod Derenzo phantom. Moreover, MPP modelling reduced the level of background noise. These improvements were also clearly visible in mouse images. Performance of VECTor can thus be significantly improved by accurately modelling annihilation gamma photon transport.

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy.

PubMed

Welikala, R A; Fraz, M M; Dehmeshki, J; Hoppe, A; Tah, V; Mann, S; Williamson, T H; Barman, S A

2015-07-01

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Skeletonization and Partitioning of Digital Images Using Discrete Morse Theory.

PubMed

Delgado-Friedrichs, Olaf; Robins, Vanessa; Sheppard, Adrian

2015-03-01

We show how discrete Morse theory provides a rigorous and unifying foundation for defining skeletons and partitions of grayscale digital images. We model a grayscale image as a cubical complex with a real-valued function defined on its vertices (the voxel values). This function is extended to a discrete gradient vector field using the algorithm presented in Robins, Wood, Sheppard TPAMI 33:1646 (2011). In the current paper we define basins (the building blocks of a partition) and segments of the skeleton using the stable and unstable sets associated with critical cells. The natural connection between Morse theory and homology allows us to prove the topological validity of these constructions; for example, that the skeleton is homotopic to the initial object. We simplify the basins and skeletons via Morse-theoretic cancellation of critical cells in the discrete gradient vector field using a strategy informed by persistent homology. Simple working Python code for our algorithms for efficient vector field traversal is included. Example data are taken from micro-CT images of porous materials, an application area where accurate topological models of pore connectivity are vital for fluid-flow modelling.

Visualization and manipulating the image of a formal data structure (FDS)-based database

NASA Astrophysics Data System (ADS)

Verdiesen, Franc; de Hoop, Sylvia; Molenaar, Martien

1994-08-01

A vector map is a terrain representation with a vector-structured geometry. Molenaar formulated an object-oriented formal data structure for 3D single valued vector maps. This FDS is implemented in a database (Oracle). In this study we describe a methodology for visualizing a FDS-based database and manipulating the image. A data set retrieved by querying the database is converted into an import file for a drawing application. An objective of this study is that an end-user can alter and add terrain objects in the image. The drawing application creates an export file, that is compared with the import file. Differences between these files result in updating the database which involves checks on consistency. In this study Autocad is used for visualizing and manipulating the image of the data set. A computer program has been written for the data exchange and conversion between Oracle and Autocad. The data structure of the FDS is compared to the data structure of Autocad and the data of the FDS is converted into the structure of Autocad equal to the FDS.

Color and Vector Flow Imaging in Parallel Ultrasound With Sub-Nyquist Sampling.

PubMed

Madiena, Craig; Faurie, Julia; Poree, Jonathan; Garcia, Damien; Garcia, Damien; Madiena, Craig; Faurie, Julia; Poree, Jonathan

2018-05-01

RF acquisition with a high-performance multichannel ultrasound system generates massive data sets in short periods of time, especially in "ultrafast" ultrasound when digital receive beamforming is required. Sampling at a rate four times the carrier frequency is the standard procedure since this rule complies with the Nyquist-Shannon sampling theorem and simplifies quadrature sampling. Bandpass sampling (or undersampling) outputs a bandpass signal at a rate lower than the maximal frequency without harmful aliasing. Advantages over Nyquist sampling are reduced storage volumes and data workflow, and simplified digital signal processing tasks. We used RF undersampling in color flow imaging (CFI) and vector flow imaging (VFI) to decrease data volume significantly (factor of 3 to 13 in our configurations). CFI and VFI with Nyquist and sub-Nyquist samplings were compared in vitro and in vivo. The estimate errors due to undersampling were small or marginal, which illustrates that Doppler and vector Doppler images can be correctly computed with a drastically reduced amount of RF samples. Undersampling can be a method of choice in CFI and VFI to avoid information overload and reduce data transfer and storage.

[Orthogonal Vector Projection Algorithm for Spectral Unmixing].

PubMed

Song, Mei-ping; Xu, Xing-wei; Chang, Chein-I; An, Ju-bai; Yao, Li

2015-12-01

Spectrum unmixing is an important part of hyperspectral technologies, which is essential for material quantity analysis in hyperspectral imagery. Most linear unmixing algorithms require computations of matrix multiplication and matrix inversion or matrix determination. These are difficult for programming, especially hard for realization on hardware. At the same time, the computation costs of the algorithms increase significantly as the number of endmembers grows. Here, based on the traditional algorithm Orthogonal Subspace Projection, a new method called. Orthogonal Vector Projection is prompted using orthogonal principle. It simplifies this process by avoiding matrix multiplication and inversion. It firstly computes the final orthogonal vector via Gram-Schmidt process for each endmember spectrum. And then, these orthogonal vectors are used as projection vector for the pixel signature. The unconstrained abundance can be obtained directly by projecting the signature to the projection vectors, and computing the ratio of projected vector length and orthogonal vector length. Compared to the Orthogonal Subspace Projection and Least Squares Error algorithms, this method does not need matrix inversion, which is much computation costing and hard to implement on hardware. It just completes the orthogonalization process by repeated vector operations, easy for application on both parallel computation and hardware. The reasonability of the algorithm is proved by its relationship with Orthogonal Sub-space Projection and Least Squares Error algorithms. And its computational complexity is also compared with the other two algorithms', which is the lowest one. At last, the experimental results on synthetic image and real image are also provided, giving another evidence for effectiveness of the method.

IBMISPS (International Brain Mapping & Intraoperative Surgical Planning Symposium)

DTIC Science & Technology

2005-12-01

they received the 2005 Excellence in R, D & E award for their contribution in the feild of prosthetics and brain imaging. Excellence in Educational...specific bipolar magnetic gradient pulses which measure the velocity vector components of motion. Presented here are the development of dynamic MR...movies of quantitative velocity vector components, 30 frames per second. The 3 velocity vector maps with tensor analysis produced maps of the

A Preliminary Study to Forecast Japanese Encephalitis Vector Abundance in Paddy Growing Area, with the Aid of Radar Satellite Images.

PubMed

Raju, K Hari Kishan; Sabesan, Shanmugavelu; Rajavel, Aladu Ramakrishnan; Subramanian, Swaminathan; Natarajan, Ramalingam; Thenmozhi, Velayutham; Tyagi, Brij Kishore; Jambulingam, Purushothaman

2016-02-01

Vector mosquitoes of Japanese encephalitis (JE) breed mostly in rice fields, and human cases occur scattered over extended rural rice-growing areas. From this, one may surmise an ecological connection with the irrigation facilities and paddy cultivation. Furthermore, it has been hypothesized that a particular stage of paddy growth is a premonitory sign that can lead to a markedly increased population of the vector mosquitoes. The present study aimed to forecast the vector abundance by monitoring the paddy growth using remote sensing and geographical information systems. The abundance of the JE vector Culex tritaeniorhynchus peaked when the paddy crop was at its heading stage and dipped when the crop reached the maturing stage. A significant positive correlation was observed between paddy growth and adult density (r = 0.73, p < 0.008). The sigma naught values (σ0) derived from satellite images of paddy fields ranged from -18.3 (during transplantation stage) to approximately -10 (during the noncultivation period). A significant positive correlation was observed between σ0 and paddy growth stages (r = 0.87, p < 0.05) and adult vector density (r = 0.74, p = 0.04). The σ0 value observed during the vegetative and flowering stages of paddy growth ranged from -17.6 to -17.16, at which period the vector density started building up. This could be the spectral signature that denotes the "risk," following which a high vector abundance is expected during heading stage of the paddy.

Cross-modal face recognition using multi-matcher face scores

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2015-05-01

The performance of face recognition can be improved using information fusion of multimodal images and/or multiple algorithms. When multimodal face images are available, cross-modal recognition is meaningful for security and surveillance applications. For example, a probe face is a thermal image (especially at nighttime), while only visible face images are available in the gallery database. Matching a thermal probe face onto the visible gallery faces requires crossmodal matching approaches. A few such studies were implemented in facial feature space with medium recognition performance. In this paper, we propose a cross-modal recognition approach, where multimodal faces are cross-matched in feature space and the recognition performance is enhanced with stereo fusion at image, feature and/or score level. In the proposed scenario, there are two cameras for stereo imaging, two face imagers (visible and thermal images) in each camera, and three recognition algorithms (circular Gaussian filter, face pattern byte, linear discriminant analysis). A score vector is formed with three cross-matched face scores from the aforementioned three algorithms. A classifier (e.g., k-nearest neighbor, support vector machine, binomial logical regression [BLR]) is trained then tested with the score vectors by using 10-fold cross validations. The proposed approach was validated with a multispectral stereo face dataset from 105 subjects. Our experiments show very promising results: ACR (accuracy rate) = 97.84%, FAR (false accept rate) = 0.84% when cross-matching the fused thermal faces onto the fused visible faces by using three face scores and the BLR classifier.

Progressive low-bitrate digital color/monochrome image coding by neuro-fuzzy clustering

NASA Astrophysics Data System (ADS)

Mitra, Sunanda; Meadows, Steven

1997-10-01

Color image coding at low bit rates is an area of research that is just being addressed in recent literature since the problems of storage and transmission of color images are becoming more prominent in many applications. Current trends in image coding exploit the advantage of subband/wavelet decompositions in reducing the complexity in optimal scalar/vector quantizer (SQ/VQ) design. Compression ratios (CRs) of the order of 10:1 to 20:1 with high visual quality have been achieved by using vector quantization of subband decomposed color images in perceptually weighted color spaces. We report the performance of a recently developed adaptive vector quantizer, namely, AFLC-VQ for effective reduction in bit rates while maintaining high visual quality of reconstructed color as well as monochrome images. For 24 bit color images, excellent visual quality is maintained upto a bit rate reduction to approximately 0.48 bpp (for each color plane or monochrome 0.16 bpp, CR 50:1) by using the RGB color space. Further tuning of the AFLC-VQ, and addition of an entropy coder module after the VQ stage results in extremely low bit rates (CR 80:1) for good quality, reconstructed images. Our recent study also reveals that for similar visual quality, RGB color space requires less bits/pixel than either the YIQ, or HIS color space for storing the same information when entropy coding is applied. AFLC-VQ outperforms other standard VQ and adaptive SQ techniques in retaining visual fidelity at similar bit rate reduction.

Presence of a predator image in potential breeding sites and oviposition responses of a dengue vector.

PubMed

Dieng, Hamady; Satho, Tomomitsu; Suradi, Nur Farrahana Binti; Hakim, Hafijah; Abang, Fatimah; Aliasan, Nur Ezzati; Miake, Fumio; Zuharah, Wan Fatma; Kassim, Nur Faeza A; Majid, Abdul Hafiz A; Fadzly, Nik; Vargas, Ronald E Morales; Morales, Noppawan P; Noweg, Gabriel Tonga

2017-12-01

In dengue vector control, attempts to minimize or replace the use of pesticides have mostly involved use of predators, but success has been severely impeded by difficulties associated with financial and environmental costs, predator mass production, and persistence in target habitats. Visual deterrents have been used successfully to control animal pests, in some cases in an effort to replace pesticide use. Despite evidence that visual signals are crucial in site choice for egg deposition by dengue vectors, and that female mosquitoes respond to artificial predation, the role of predator intimidation as it affects the oviposition behavior of dengue vectors remains largely unexplored. Here, we examined the oviposition responses of Aedes aegypti exposed to various mosquito predator pictures. Gravid females were presented with equal opportunities to oviposit in two cups with predator images [Toxorhynchites splendens-TXI, Goldfish (Carassius auratus)-small (SFI) and large (LFI) and Tx. splendens+Goldfish-TXFI] and two others without pictures. Differences in egg deposition were examined between sites with and without these images. When given a chance to oviposit in cups with and without TXI, Ae. aegypti females were similarly attracted to both sites. When provided an opportunity to oviposit in cups displaying pictures of fish (SFI or LFI) and blank cups, egg deposition rates were much lower in the fish picture sites. Females showed a preference for blank cups over TXFI for egg deposition. They also equally avoided cups with pictures of fish, regardless of the size of the picture. Our results indicate that the presence of images of goldfish and their association with Tx. larvae significantly reduced egg deposition by Ae. aegypti, and this was not the case with the predatory larvae alone. The observations that the images of natural predators can repel gravid females of a dengue vector provide novel possibilities to develop effective and inexpensive alternative tools to harmful insecticides. Copyright © 2017 Elsevier B.V. All rights reserved.

Text analysis devices, articles of manufacture, and text analysis methods

DOEpatents

Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

2015-03-31

Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes a display configured to depict visible images, and processing circuitry coupled with the display and wherein the processing circuitry is configured to access a first vector of a text item and which comprises a plurality of components, to access a second vector of the text item and which comprises a plurality of components, to weight the components of the first vector providing a plurality of weighted values, to weight the components of the second vector providing a plurality of weighted values, and to combine the weighted values of the first vector with the weighted values of the second vector to provide a third vector.

SSM/I and ECMWF Wind Vector Comparison

NASA Technical Reports Server (NTRS)

Wentz, Frank J.; Ashcroft, Peter D.

1996-01-01

Wentz was the first to convincingly show that satellite microwave radiometers have the potential to measure the oceanic wind vector. The most compelling evidence for this conclusion was the monthly wind vector maps derived solely from a statistical analysis of Special Sensor Microwave Imager (SSM/I) observations. In a qualitative sense, these maps clearly showed the general circulation over the world's oceans. In this report we take a closer look at the SSM/I monthly wind vector maps and compare them to European Center for Medium-Range Weather Forecasts (ECMWF) wind fields. This investigation leads both to an empirical comparison of SSM/I calculated wind vectors with ECMWF wind vectors, and to an examination of possible reasons that the SSM/I calculated wind vector direction would be inherently more reliable at some locations than others.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

PubMed Central

Tang, Xiaoying; Yoshida, Shoko; Hsu, John; Huisman, Thierry A. G. M.; Faria, Andreia V.; Oishi, Kenichi; Kutten, Kwame; Poretti, Andrea; Li, Yue; Miller, Michael I.; Mori, Susumu

2014-01-01

In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs). This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases. DTI images are modeled as high dimensional fields, with each voxel exhibiting a vector valued feature comprising of mean diffusivity (MD), fractional anisotropy (FA), and fiber angle. For each structure, the probability distribution of each element in the feature vector is modeled as a mixture of Gaussians, the parameters of which are estimated from the labeled atlases. The structure-specific feature vector is then used to parcellate the test image. For each atlas, a likelihood is iteratively computed based on the structure-specific vector feature. The likelihoods from multiple atlases are then fused. The updating and fusing of the likelihoods is achieved based on the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation problems. We first demonstrate the performance of the algorithm by examining the parcellation accuracy of 18 structures from 25 subjects with a varying degree of structural abnormality. Dice values ranging 0.8–0.9 were obtained. In addition, strong correlation was found between the volume size of the automated and the manual parcellation. Then, we present scan-rescan reproducibility based on another dataset of 16 DTI images – an average of 3.73%, 1.91%, and 1.79% for volume, mean FA, and mean MD respectively. Finally, the range of anatomical variability in the normal population was quantified for each structure. PMID:24809486

Adaptive mesh optimization and nonrigid motion recovery based image registration for wide-field-of-view ultrasound imaging.

PubMed

Tan, Chaowei; Wang, Bo; Liu, Paul; Liu, Dong

2008-01-01

Wide field of view (WFOV) imaging mode obtains an ultrasound image over an area much larger than the real time window normally available. As the probe is moved over the region of interest, new image frames are combined with prior frames to form a panorama image. Image registration techniques are used to recover the probe motion, eliminating the need for a position sensor. Speckle patterns, which are inherent in ultrasound imaging, change, or become decorrelated, as the scan plane moves, so we pre-smooth the image to reduce the effects of speckle in registration, as well as reducing effects from thermal noise. Because we wish to track the movement of features such as structural boundaries, we use an adaptive mesh over the entire smoothed image to home in on areas with feature. Motion estimation using blocks centered at the individual mesh nodes generates a field of motion vectors. After angular correction of motion vectors, we model the overall movement between frames as a nonrigid deformation. The polygon filling algorithm for precise, persistence-based spatial compounding constructs the final speckle reduced WFOV image.

Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems

PubMed Central

2013-01-01

This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1) separate the root system into a small number of large pieces to reduce root overlap, (2) scan these pieces one by one, (3) analyze separate images with a root tracing software and (4) combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns. PMID:23286457

Novel scanning procedure enabling the vectorization of entire rhizotron-grown root systems.

PubMed

Lobet, Guillaume; Draye, Xavier

2013-01-04

: This paper presents an original spit-and-combine imaging procedure that enables the complete vectorization of complex root systems grown in rhizotrons. The general principle of the method is to (1) separate the root system into a small number of large pieces to reduce root overlap, (2) scan these pieces one by one, (3) analyze separate images with a root tracing software and (4) combine all tracings into a single vectorized root system. This method generates a rich dataset containing morphological, topological and geometrical information of entire root systems grown in rhizotrons. The utility of the method is illustrated with a detailed architectural analysis of a 20-day old maize root system, coupled with a spatial analysis of water uptake patterns.

Automatic deformable diffusion tensor registration for fiber population analysis.

PubMed

Irfanoglu, M O; Machiraju, R; Sammet, S; Pierpaoli, C; Knopp, M V

2008-01-01

In this work, we propose a novel method for deformable tensor-to-tensor registration of Diffusion Tensor Images. Our registration method models the distances in between the tensors with Geode-sic-Loxodromes and employs a version of Multi-Dimensional Scaling (MDS) algorithm to unfold the manifold described with this metric. Defining the same shape properties as tensors, the vector images obtained through MDS are fed into a multi-step vector-image registration scheme and the resulting deformation fields are used to reorient the tensor fields. Results on brain DTI indicate that the proposed method is very suitable for deformable fiber-to-fiber correspondence and DTI-atlas construction.

Local Subspace Classifier with Transform-Invariance for Image Classification

NASA Astrophysics Data System (ADS)

Hotta, Seiji

A family of linear subspace classifiers called local subspace classifier (LSC) outperforms the k-nearest neighbor rule (kNN) and conventional subspace classifiers in handwritten digit classification. However, LSC suffers very high sensitivity to image transformations because it uses projection and the Euclidean distances for classification. In this paper, I present a combination of a local subspace classifier (LSC) and a tangent distance (TD) for improving accuracy of handwritten digit recognition. In this classification rule, we can deal with transform-invariance easily because we are able to use tangent vectors for approximation of transformations. However, we cannot use tangent vectors in other type of images such as color images. Hence, kernel LSC (KLSC) is proposed for incorporating transform-invariance into LSC via kernel mapping. The performance of the proposed methods is verified with the experiments on handwritten digit and color image classification.

Advanced Techniques for Scene Analysis

DTIC Science & Technology

2010-06-01

robustness prefers a bigger intergration window to handle larger motions. The advantage of pyramidal implementation is that, while each motion vector dL...labeled SAR images. Now the previous algorithm leads to a more dedicated classifier for the particular target; however, our algorithm trades generality for...accuracy is traded for generality. 7.3.2 I-RELIEF Feature weighting transforms the original feature vector x into a new feature vector x′ by assigning each

Cross-Service Investigation of Geographical Information Systems

DTIC Science & Technology

2004-03-01

Figure 8 illustrates the combined layers. Information for the layers is stored in a database format. The two types of storage are vector and...raster models. In a vector model, the image and information are stored as geometric objects such as points, lines, or polygons. In a raster model...DNCs are a vector -based digital database with selected maritime significant physical features from hydrographic charts. Layers within the DNC are data

An image segmentation method for apple sorting and grading using support vector machine and Otsu's method

USDA-ARS?s Scientific Manuscript database

Segmentation is the first step in image analysis to subdivide an image into meaningful regions. The segmentation result directly affects the subsequent image analysis. The objective of the research was to develop an automatic adjustable algorithm for segmentation of color images, using linear suppor...

Comparison of scoliosis measurements based on three-dimensional vertebra vectors and conventional two-dimensional measurements: advantages in evaluation of prognosis and surgical results.

PubMed

Illés, Tamás; Somoskeöy, Szabolcs

2013-06-01

A new concept of vertebra vectors based on spinal three-dimensional (3D) reconstructions of images from the EOS system, a new low-dose X-ray imaging device, was recently proposed to facilitate interpretation of EOS 3D data, especially with regard to horizontal plane images. This retrospective study was aimed at the evaluation of the spinal layout visualized by EOS 3D and vertebra vectors before and after surgical correction, the comparison of scoliotic spine measurement values based on 3D vertebra vectors with measurements using conventional two-dimensional (2D) methods, and an evaluation of horizontal plane vector parameters for their relationship with the magnitude of scoliotic deformity. 95 patients with adolescent idiopathic scoliosis operated according to the Cotrel-Dubousset principle were subjected to EOS X-ray examinations pre- and postoperatively, followed by 3D reconstructions and generation of vertebra vectors in a calibrated coordinate system to calculate vector coordinates and parameters, as published earlier. Differences in values of conventional 2D Cobb methods and methods based on vertebra vectors were evaluated by means comparison T test and relationship of corresponding parameters was analysed by bivariate correlation. Relationship of horizontal plane vector parameters with the magnitude of scoliotic deformities and results of surgical correction were analysed by Pearson correlation and linear regression. In comparison to manual 2D methods, a very close relationship was detectable in vertebra vector-based curvature data for coronal curves (preop r 0.950, postop r 0.935) and thoracic kyphosis (preop r 0.893, postop r 0.896), while the found small difference in L1-L5 lordosis values (preop r 0.763, postop r 0.809) was shown to be strongly related to the magnitude of corresponding L5 wedge. The correlation analysis results revealed strong correlation between the magnitude of scoliosis and the lateral translation of apical vertebra in horizontal plane. The horizontal plane coordinates of the terminal and initial points of apical vertebra vectors represent this (r 0.701; r 0.667). Less strong correlation was detected in the axial rotation of apical vertebras and the magnitudes of the frontal curves (r 0.459). Vertebra vectors provide a key opportunity to visualize spinal deformities in all three planes simultaneously. Measurement methods based on vertebral vectors proved to be just as accurate and reliable as conventional measurement methods for coronal and sagittal plane parameters. In addition, the horizontal plane display of the curves can be studied using the same vertebra vectors. Based on the vertebra vectors data, during the surgical treatment of spinal deformities, the diminution of the lateral translation of the vertebras seems to be more important in the results of the surgical correction than the correction of the axial rotation.

Design of polarization imaging system based on CIS and FPGA

NASA Astrophysics Data System (ADS)

Zeng, Yan-an; Liu, Li-gang; Yang, Kun-tao; Chang, Da-ding

2008-02-01

As polarization is an important characteristic of light, polarization image detecting is a new image detecting technology of combining polarimetric and image processing technology. Contrasting traditional image detecting in ray radiation, polarization image detecting could acquire a lot of very important information which traditional image detecting couldn't. Polarization image detecting will be widely used in civilian field and military field. As polarization image detecting could resolve some problem which couldn't be resolved by traditional image detecting, it has been researched widely around the world. The paper introduces polarization image detecting in physical theory at first, then especially introduces image collecting and polarization image process based on CIS (CMOS image sensor) and FPGA. There are two parts including hardware and software for polarization imaging system. The part of hardware include drive module of CMOS image sensor, VGA display module, SRAM access module and the real-time image data collecting system based on FPGA. The circuit diagram and PCB was designed. Stokes vector and polarization angle computing method are analyzed in the part of software. The float multiply of Stokes vector is optimized into just shift and addition operation. The result of the experiment shows that real time image collecting system could collect and display image data from CMOS image sensor in real-time.

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

Vector disparity sensor with vergence control for active vision systems.

PubMed

Barranco, Francisco; Diaz, Javier; Gibaldi, Agostino; Sabatini, Silvio P; Ros, Eduardo

2012-01-01

This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system.

DIRECT OBSERVATION OF SOLAR CORONAL MAGNETIC FIELDS BY VECTOR TOMOGRAPHY OF THE CORONAL EMISSION LINE POLARIZATIONS

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

Kramar, M.; Lin, H.; Tomczyk, S., E-mail: kramar@cua.edu, E-mail: lin@ifa.hawaii.edu, E-mail: tomczyk@ucar.edu

We present the first direct “observation” of the global-scale, 3D coronal magnetic fields of Carrington Rotation (CR) Cycle 2112 using vector tomographic inversion techniques. The vector tomographic inversion uses measurements of the Fe xiii 10747 Å Hanle effect polarization signals by the Coronal Multichannel Polarimeter (CoMP) and 3D coronal density and temperature derived from scalar tomographic inversion of Solar Terrestrial Relations Observatory (STEREO)/Extreme Ultraviolet Imager (EUVI) coronal emission lines (CELs) intensity images as inputs to derive a coronal magnetic field model that best reproduces the observed polarization signals. While independent verifications of the vector tomography results cannot be performed, wemore » compared the tomography inverted coronal magnetic fields with those constructed by magnetohydrodynamic (MHD) simulations based on observed photospheric magnetic fields of CR 2112 and 2113. We found that the MHD model for CR 2112 is qualitatively consistent with the tomography inverted result for most of the reconstruction domain except for several regions. Particularly, for one of the most noticeable regions, we found that the MHD simulation for CR 2113 predicted a model that more closely resembles the vector tomography inverted magnetic fields. In another case, our tomographic reconstruction predicted an open magnetic field at a region where a coronal hole can be seen directly from a STEREO-B/EUVI image. We discuss the utilities and limitations of the tomographic inversion technique, and present ideas for future developments.« less

Vector Disparity Sensor with Vergence Control for Active Vision Systems

PubMed Central

Barranco, Francisco; Diaz, Javier; Gibaldi, Agostino; Sabatini, Silvio P.; Ros, Eduardo

2012-01-01

This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The control of the vergence angle of a binocular system allows us to efficiently explore dynamic environments, but requires a generalization of the disparity computation with respect to a static camera setup, where the disparity is strictly 1-D after the image rectification. The interaction between vision and motor control allows us to develop an active sensor that achieves high accuracy of the disparity computation around the fixation point, and fast reaction time for the vergence control. In this contribution, we address the development of a real-time architecture for vector disparity computation using an FPGA device. We implement the disparity unit and the control module for vergence, version, and tilt to determine the fixation point. In addition, two on-chip different alternatives for the vector disparity engines are discussed based on the luminance (gradient-based) and phase information of the binocular images. The multiscale versions of these engines are able to estimate the vector disparity up to 32 fps on VGA resolution images with very good accuracy as shown using benchmark sequences with known ground-truth. The performances in terms of frame-rate, resource utilization, and accuracy of the presented approaches are discussed. On the basis of these results, our study indicates that the gradient-based approach leads to the best trade-off choice for the integration with the active vision system. PMID:22438737

Spiral Flow Phantom for Ultrasound Flow Imaging Experimentation.

PubMed

Yiu, Billy Y S; Yu, Alfred C H

2017-12-01

As new ultrasound flow imaging methods are being developed, there is a growing need to devise appropriate flow phantoms that can holistically assess the accuracy of the derived flow estimates. In this paper, we present a novel spiral flow phantom design whose Archimedean spiral lumen naturally gives rise to multi-directional flow over all possible angles (i.e., from 0° to 360°). Developed using lost-core casting principles, the phantom geometry comprised a three-loop spiral (4-mm diameter and 5-mm pitch), and it was set to operate in steady flow mode (3 mL/s flow rate). After characterizing the flow pattern within the spiral vessel using computational fluid dynamics (CFD) simulations, the phantom was applied to evaluate the performance of color flow imaging (CFI) and high-frame-rate vector flow imaging. Significant spurious coloring artifacts were found when using CFI to visualize flow in the spiral phantom. In contrast, using vector flow imaging (least-squares multi-angle Doppler based on a three-transmit and three-receive configuration), we observed consistent depiction of flow velocity magnitude and direction within the spiral vessel lumen. The spiral flow phantom was also found to be a useful tool in facilitating demonstration of dynamic flow visualization based on vector projectile imaging. Overall, these results demonstrate the spiral flow phantom's practical value in analyzing the efficacy of ultrasound flow estimation methods.

Passive acoustic mapping of cavitation using eigenspace-based robust Capon beamformer in ultrasound therapy.

PubMed

Lu, Shukuan; Hu, Hong; Yu, Xianbo; Long, Jiangying; Jing, Bowen; Zong, Yujin; Wan, Mingxi

2018-03-01

Pulse-echo imaging technique can only play a role when high intensity focused ultrasound (HIFU) is turned off due to the interference between the primary HIFU signal and the transmission pulse. Passive acoustic mapping (PAM) has been proposed as a tool for true real-time monitoring of HIFU therapy. However, the most-used PAM algorithm based on time exposure acoustic (TEA) limits the quality of cavitation image. Recently, robust Capon beamformer (RCB) has been used in PAM to provide improved resolution and reduced artifacts over TEA-based PAM, but the presented results have not been satisfactory. In the present study, we applied an eigenspace-based RCB (EISRCB) method to further improve the PAM image quality. The optimal weighting vector of the proposed method was found by projecting the RCB weighting vector onto the desired vector subspace constructed from the eigenstructure of the covariance matrix. The performance of the proposed PAM was validated by both simulations and in vitro histotripsy experiments. The results suggested that the proposed PAM significantly outperformed the conventionally used TEA and RCB-based PAM. The comparison results between pulse-echo images of the residual bubbles and cavitation images showed the potential of our proposed PAM in accurate localization of cavitation activity during HIFU therapy. Copyright © 2017 Elsevier B.V. All rights reserved.

a Hyperspectral Image Classification Method Using Isomap and Rvm

NASA Astrophysics Data System (ADS)

Chang, H.; Wang, T.; Fang, H.; Su, Y.

2018-04-01

Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this application, there are still drawbacks in traditional classification methods. Thus further investigations on some aspects, such as dimension reduction, data mining, and rational use of spatial information, should be developed. In this paper, we used a widely utilized global manifold learning approach, isometric feature mapping (ISOMAP), to address the intrinsic nonlinearities of hyperspectral image for dimension reduction. Considering the impropriety of Euclidean distance in spectral measurement, we applied spectral angle (SA) for substitute when constructed the neighbourhood graph. Then, relevance vector machines (RVM) was introduced to implement classification instead of support vector machines (SVM) for simplicity, generalization and sparsity. Therefore, a probability result could be obtained rather than a less convincing binary result. Moreover, taking into account the spatial information of the hyperspectral image, we employ a spatial vector formed by different classes' ratios around the pixel. At last, we combined the probability results and spatial factors with a criterion to decide the final classification result. To verify the proposed method, we have implemented multiple experiments with standard hyperspectral images compared with some other methods. The results and different evaluation indexes illustrated the effectiveness of our method.

Automated thematic mapping and change detection of ERTS-A images. [farmlands, cities, and mountain identification in Utah, Washington, Arizona, and California

NASA Technical Reports Server (NTRS)

Gramenopoulos, N. (Principal Investigator)

1974-01-01

The author has identified the following significant results. A diffraction pattern analysis of MSS images led to the development of spatial signatures for farm land, urban areas and mountains. Four spatial features are employed to describe the spatial characteristics of image cells in the digital data. Three spectral features are combined with the spatial features to form a seven dimensional vector describing each cell. Then, the classification of the feature vectors is accomplished by using the maximum likelihood criterion. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month, but vary substantially between seasons. Three ERTS-1 images from the Phoenix, Arizona area were processed, and recognition rates between 85% and 100% were obtained for the terrain classes of desert, farms, mountains, and urban areas. To eliminate the need for training data, a new clustering algorithm has been developed. Seven ERTS-1 images from four test sites have been processed through the clustering algorithm, and high recognition rates have been achieved for all terrain classes.

Towards Ultra-High Resolution Fibre Tract Mapping of the Human Brain – Registration of Polarised Light Images and Reorientation of Fibre Vectors

PubMed Central

Palm, Christoph; Axer, Markus; Gräßel, David; Dammers, Jürgen; Lindemeyer, Johannes; Zilles, Karl; Pietrzyk, Uwe; Amunts, Katrin

2009-01-01

Polarised light imaging (PLI) utilises the birefringence of the myelin sheaths in order to visualise the orientation of nerve fibres in microtome sections of adult human post-mortem brains at ultra-high spatial resolution. The preparation of post-mortem brains for PLI involves fixation, freezing and cutting into 100-μm-thick sections. Hence, geometrical distortions of histological sections are inevitable and have to be removed for 3D reconstruction and subsequent fibre tracking. We here present a processing pipeline for 3D reconstruction of these sections using PLI derived multimodal images of post-mortem brains. Blockface images of the brains were obtained during cutting; they serve as reference data for alignment and elimination of distortion artefacts. In addition to the spatial image transformation, fibre orientation vectors were reoriented using the transformation fields, which consider both affine and subsequent non-linear registration. The application of this registration and reorientation approach results in a smooth fibre vector field, which reflects brain morphology. PLI combined with 3D reconstruction and fibre tracking is a powerful tool for human brain mapping. It can also serve as an independent method for evaluating in vivo fibre tractography. PMID:20461231

FIVQ algorithm for interference hyper-spectral image compression

NASA Astrophysics Data System (ADS)

Wen, Jia; Ma, Caiwen; Zhao, Junsuo

2014-07-01

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASIS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences.

Predicting pork loin intramuscular fat using computer vision system.

PubMed

Liu, J-H; Sun, X; Young, J M; Bachmeier, L A; Newman, D J

2018-09-01

The objective of this study was to investigate the ability of computer vision system to predict pork intramuscular fat percentage (IMF%). Center-cut loin samples (n = 85) were trimmed of subcutaneous fat and connective tissue. Images were acquired and pixels were segregated to estimate image IMF% and 18 image color features for each image. Subjective IMF% was determined by a trained grader. Ether extract IMF% was calculated using ether extract method. Image color features and image IMF% were used as predictors for stepwise regression and support vector machine models. Results showed that subjective IMF% had a correlation of 0.81 with ether extract IMF% while the image IMF% had a 0.66 correlation with ether extract IMF%. Accuracy rates for regression models were 0.63 for stepwise and 0.75 for support vector machine. Although subjective IMF% has shown to have better prediction, results from computer vision system demonstrates the potential of being used as a tool in predicting pork IMF% in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

Statistical Inference for Porous Materials using Persistent Homology.

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

Moon, Chul; Heath, Jason E.; Mitchell, Scott A.

2017-12-01

We propose a porous materials analysis pipeline using persistent homology. We rst compute persistent homology of binarized 3D images of sampled material subvolumes. For each image we compute sets of homology intervals, which are represented as summary graphics called persistence diagrams. We convert persistence diagrams into image vectors in order to analyze the similarity of the homology of the material images using the mature tools for image analysis. Each image is treated as a vector and we compute its principal components to extract features. We t a statistical model using the loadings of principal components to estimate material porosity, permeability,more » anisotropy, and tortuosity. We also propose an adaptive version of the structural similarity index (SSIM), a similarity metric for images, as a measure to determine the statistical representative elementary volumes (sREV) for persistence homology. Thus we provide a capability for making a statistical inference of the uid ow and transport properties of porous materials based on their geometry and connectivity.« less

Combining Vector Quantization and Histogram Equalization.

ERIC Educational Resources Information Center

Cosman, Pamela C.; And Others

1992-01-01

Discussion of contrast enhancement techniques focuses on the use of histogram equalization with a data compression technique, i.e., tree-structured vector quantization. The enhancement technique of intensity windowing is described, and the use of enhancement techniques for medical images is explained, including adaptive histogram equalization.…

Recent weather extremes and impact agricultural production and vector-borne disease patterns

USDA-ARS?s Scientific Manuscript database

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA’s satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to ...

Image velocimetry for clouds with relaxation labeling based on deformation consistency

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

Non-overlapped P- and S-wave Poynting vectors and their solution by the grid method

NASA Astrophysics Data System (ADS)

Lu, Yongming; Liu, Qiancheng

2018-06-01

The Poynting vector represents the local directional energy flux density of seismic waves in geophysics. It is widely used in elastic reverse time migration to analyze source illumination, suppress low-wavenumber noise, correct for image polarity and extract angle-domain common-image gathers. However, the P- and S-waves are mixed together during wavefield propagation so that the P and S energy fluxes are not clean everywhere, especially at the overlapped points. In this paper, we use a modified elastic-wave equation in which the P and S vector wavefields are naturally separated. Then, we develop an efficient method to evaluate the separable P and S Poynting vectors, respectively, based on the view that the group velocity and phase velocity have the same direction in isotropic elastic media. We furthermore formulate our method using an unstructured mesh-based modeling method named the grid method. Finally, we verify our method using two numerical examples.

Image/text automatic indexing and retrieval system using context vector approach

NASA Astrophysics Data System (ADS)

Qing, Kent P.; Caid, William R.; Ren, Clara Z.; McCabe, Patrick

1995-11-01

Thousands of documents and images are generated daily both on and off line on the information superhighway and other media. Storage technology has improved rapidly to handle these data but indexing this information is becoming very costly. HNC Software Inc. has developed a technology for automatic indexing and retrieval of free text and images. This technique is demonstrated and is based on the concept of `context vectors' which encode a succinct representation of the associated text and features of sub-image. In this paper, we will describe the Automated Librarian System which was designed for free text indexing and the Image Content Addressable Retrieval System (ICARS) which extends the technique from the text domain into the image domain. Both systems have the ability to automatically assign indices for a new document and/or image based on the content similarities in the database. ICARS also has the capability to retrieve images based on similarity of content using index terms, text description, and user-generated images as a query without performing segmentation or object recognition.

Fourier spatial frequency analysis for image classification: training the training set

NASA Astrophysics Data System (ADS)

Johnson, Timothy H.; Lhamo, Yigah; Shi, Lingyan; Alfano, Robert R.; Russell, Stewart

2016-04-01

The Directional Fourier Spatial Frequencies (DFSF) of a 2D image can identify similarity in spatial patterns within groups of related images. A Support Vector Machine (SVM) can then be used to classify images if the inter-image variance of the FSF in the training set is bounded. However, if variation in FSF increases with training set size, accuracy may decrease as the size of the training set increases. This calls for a method to identify a set of training images from among the originals that can form a vector basis for the entire class. Applying the Cauchy product method we extract the DFSF spectrum from radiographs of osteoporotic bone, and use it as a matched filter set to eliminate noise and image specific frequencies, and demonstrate that selection of a subset of superclassifiers from within a set of training images improves SVM accuracy. Central to this challenge is that the size of the search space can become computationally prohibitive for all but the smallest training sets. We are investigating methods to reduce the search space to identify an optimal subset of basis training images.

Optical computing and image processing using photorefractive gallium arsenide

NASA Technical Reports Server (NTRS)

Cheng, Li-Jen; Liu, Duncan T. H.

1990-01-01

Recent experimental results on matrix-vector multiplication and multiple four-wave mixing using GaAs are presented. Attention is given to a simple concept of using two overlapping holograms in GaAs to do two matrix-vector multiplication processes operating in parallel with a common input vector. This concept can be used to construct high-speed, high-capacity, reconfigurable interconnection and multiplexing modules, important for optical computing and neural-network applications.

Black light - How sensors filter spectral variation of the illuminant

NASA Technical Reports Server (NTRS)

Brainard, David H.; Wandell, Brian A.; Cowan, William B.

1989-01-01

Visual sensor responses may be used to classify objects on the basis of their surface reflectance functions. In a color image, the image data are represented as a vector of sensor responses at each point in the image. This vector depends both on the surface reflectance functions and on the spectral power distribution of the ambient illumination. Algorithms designed to classify objects on the basis of their surface reflectance functions typically attempt to overcome the dependence of the sensor responses on the illuminant by integrating sensor data collected from multiple surfaces. In machine vision applications, it is shown that it is often possible to design the sensor spectral responsivities so that the vector direction of the sensor responses does not depend upon the illuminant. The conditions under which this is possible are given and an illustrative calculation is performed. In biological systems, where the sensor responsivities are fixed, it is shown that some changes in the illumination cause no change in the sensor responses. Such changes in illuminant are called black illuminants. It is possible to express any illuminant as the sum of two unique components. One component is a black illuminant. The second component is called the visible component. The visible component of an illuminant completely characterizes the effect of the illuminant on the vector of sensor responses.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

High-order distance-based multiview stochastic learning in image classification.

PubMed

Yu, Jun; Rui, Yong; Tang, Yuan Yan; Tao, Dacheng

2014-12-01

How do we find all images in a larger set of images which have a specific content? Or estimate the position of a specific object relative to the camera? Image classification methods, like support vector machine (supervised) and transductive support vector machine (semi-supervised), are invaluable tools for the applications of content-based image retrieval, pose estimation, and optical character recognition. However, these methods only can handle the images represented by single feature. In many cases, different features (or multiview data) can be obtained, and how to efficiently utilize them is a challenge. It is inappropriate for the traditionally concatenating schema to link features of different views into a long vector. The reason is each view has its specific statistical property and physical interpretation. In this paper, we propose a high-order distance-based multiview stochastic learning (HD-MSL) method for image classification. HD-MSL effectively combines varied features into a unified representation and integrates the labeling information based on a probabilistic framework. In comparison with the existing strategies, our approach adopts the high-order distance obtained from the hypergraph to replace pairwise distance in estimating the probability matrix of data distribution. In addition, the proposed approach can automatically learn a combination coefficient for each view, which plays an important role in utilizing the complementary information of multiview data. An alternative optimization is designed to solve the objective functions of HD-MSL and obtain different views on coefficients and classification scores simultaneously. Experiments on two real world datasets demonstrate the effectiveness of HD-MSL in image classification.

Color deconvolution. Optimizing handling of 3D unitary optical density vectors with polar coordinates.

PubMed

Bigras, Gilbert

2012-06-01

Color deconvolution relies on determination of unitary optical density vectors (OD(3D)) derived from pure constituent stains initially defined as intensity vectors in RGB space. OD(3D) can be defined in polar coordinates (phi, theta, radius); always being equal to one, radius can be ignored. Easier handling of unitary optical density 2D vectors (OD(2D)) is shown. OD(2D) pure stains used in anatomical pathology were assessed as centroid values (phi, theta) with a measure of variance: inertia based on arc lengths between centroid value and sampled points. These variables were plotted on a stereographic projection plane. In order to assess pure stains OD(2D), different methods of sampling RGB pixels were tested and compared: (2) direct sampling of nuclei from preparations using (a) composite H&E and (b) hematoxylin only and (2) for any pure stain RGB image, different associated 8-bit masks (saturation, brightness and RGB average) were used for sampling and compared. Behaviors of phi, theta and inertia were obtained by moving threshold in 8-bit mask histograms. Phi and theta stability were tested against variable light intensity during image acquisition and by using 2 different image acquisition systems. The more saturated RGB pixels are, the more stable phi, theta and inertia values are obtained. Different commercial hematoxylins have distinct OD(2D) characteristics. UltraView DAB stain shows high inertia and is angularly closer to usual counterstains than ultraView Red stain, which also has a lower inertia. Superior accuracy is expected from the latter stain. Phi and theta OD(2D) values are sensitive to light intensity variation, to the used imaging system and to the used objectives. An ImageJ plugin was designed to plot and interactively modify OD(2D) values with instant update of color deconvolution allowing heuristic segmentation. Utilization of polar OD(2D) eases statistical characterization of OD(3D) vectors: conditions of optimal sampling were demonstrated and various factors influencing OD(2D) stability were explored. Stereographic projection plane allows intuitive visualization of OD(3D) vectors as well as heuristic vectorial modification. All findings are not restricted to anatomical pathology but can be applied to bright field microscopy and subtractive color applications in general.

Volume illustration of muscle from diffusion tensor images.

PubMed

Chen, Wei; Yan, Zhicheng; Zhang, Song; Crow, John Allen; Ebert, David S; McLaughlin, Ronald M; Mullins, Katie B; Cooper, Robert; Ding, Zi'ang; Liao, Jun

2009-01-01

Medical illustration has demonstrated its effectiveness to depict salient anatomical features while hiding the irrelevant details. Current solutions are ineffective for visualizing fibrous structures such as muscle, because typical datasets (CT or MRI) do not contain directional details. In this paper, we introduce a new muscle illustration approach that leverages diffusion tensor imaging (DTI) data and example-based texture synthesis techniques. Beginning with a volumetric diffusion tensor image, we reformulate it into a scalar field and an auxiliary guidance vector field to represent the structure and orientation of a muscle bundle. A muscle mask derived from the input diffusion tensor image is used to classify the muscle structure. The guidance vector field is further refined to remove noise and clarify structure. To simulate the internal appearance of the muscle, we propose a new two-dimensional example based solid texture synthesis algorithm that builds a solid texture constrained by the guidance vector field. Illustrating the constructed scalar field and solid texture efficiently highlights the global appearance of the muscle as well as the local shape and structure of the muscle fibers in an illustrative fashion. We have applied the proposed approach to five example datasets (four pig hearts and a pig leg), demonstrating plausible illustration and expressiveness.

Multipurpose image watermarking algorithm based on multistage vector quantization.

PubMed

Lu, Zhe-Ming; Xu, Dian-Guo; Sun, Sheng-He

2005-06-01

The rapid growth of digital multimedia and Internet technologies has made copyright protection, copy protection, and integrity verification three important issues in the digital world. To solve these problems, the digital watermarking technique has been presented and widely researched. Traditional watermarking algorithms are mostly based on discrete transform domains, such as the discrete cosine transform, discrete Fourier transform (DFT), and discrete wavelet transform (DWT). Most of these algorithms are good for only one purpose. Recently, some multipurpose digital watermarking methods have been presented, which can achieve the goal of content authentication and copyright protection simultaneously. However, they are based on DWT or DFT. Lately, several robust watermarking schemes based on vector quantization (VQ) have been presented, but they can only be used for copyright protection. In this paper, we present a novel multipurpose digital image watermarking method based on the multistage vector quantizer structure, which can be applied to image authentication and copyright protection. In the proposed method, the semi-fragile watermark and the robust watermark are embedded in different VQ stages using different techniques, and both of them can be extracted without the original image. Simulation results demonstrate the effectiveness of our algorithm in terms of robustness and fragility.

Detection of endoscopic looping during colonoscopy procedure by using embedded bending sensors

PubMed Central

Bruce, Michael; Choi, JungHun

2018-01-01

Background Looping of the colonoscope shaft during procedure is one of the most common obstacles encountered by colonoscopists. It occurs in 91% of cases with the N-sigmoid loop being the most common, occurring in 79% of cases. Purpose Herein, a novel system is developed that will give a complete three-dimensional (3D) vector image of the shaft as it passes through the colon, to aid the colonoscopist in detecting loops before they form. Patients and methods A series of connected links spans the middle 50% of the shaft, where loops are likely to form. Two potentiometers are attached at each joint to measure angular deflection in two directions to allow for 3D positioning. This 3D positioning is converted into a 3D vector image using computer software. MATLAB software has been used to display the image on a computer monitor. For the different configuration of the colon model, the system determined the looping status. Results Different configurations (N loop, reverse gamma loop, and reverse splenic flexure) of the loops were well defined using 3D vector image. Conclusion The novel sensory system can accurately define the various configuration of the colon during the colonoscopy procedure. PMID:29849469

Wavelet Transforms in Parallel Image Processing

DTIC Science & Technology

1994-01-27

NUMBER OF PAGES Object Segmentation, Texture Segmentation, Image Compression, Image 137 Halftoning , Neural Network, Parallel Algorithms, 2D and 3D...Vector Quantization of Wavelet Transform Coefficients ........ ............................. 57 B.1.f Adaptive Image Halftoning based on Wavelet...application has been directed to the adaptive image halftoning . The gray information at a pixel, including its gray value and gradient, is represented by

PIV-DCNN: cascaded deep convolutional neural networks for particle image velocimetry

NASA Astrophysics Data System (ADS)

Lee, Yong; Yang, Hua; Yin, Zhouping

2017-12-01

Velocity estimation (extracting the displacement vector information) from the particle image pairs is of critical importance for particle image velocimetry. This problem is mostly transformed into finding the sub-pixel peak in a correlation map. To address the original displacement extraction problem, we propose a different evaluation scheme (PIV-DCNN) with four-level regression deep convolutional neural networks. At each level, the networks are trained to predict a vector from two input image patches. The low-level network is skilled at large displacement estimation and the high- level networks are devoted to improving the accuracy. Outlier replacement and symmetric window offset operation glue the well- functioning networks in a cascaded manner. Through comparison with the standard PIV methods (one-pass cross-correlation method, three-pass window deformation), the practicability of the proposed PIV-DCNN is verified by the application to a diversity of synthetic and experimental PIV images.

Information-Efficient Spectral Imaging Sensor With Tdi

DOEpatents

Rienstra, Jeffrey L.; Gentry, Stephen M.; Sweatt, William C.

2004-01-13

A programmable optical filter for use in multispectral and hyperspectral imaging employing variable gain time delay and integrate arrays. A telescope focuses an image of a scene onto at least one TDI array that is covered by a multispectral filter that passes separate bandwidths of light onto the rows in the TDI array. The variable gain feature of the TDI array allows individual rows of pixels to be attenuated individually. The attenuations are functions of the magnitudes of the positive and negative components of a spectral basis vector. The spectral basis vector is constructed so that its positive elements emphasize the presence of a target and its negative elements emphasize the presence of the constituents of the background of the imaged scene. This system provides for a very efficient determination of the presence of the target, as opposed to the very data intensive data manipulations that are required in conventional hyperspectral imaging systems.

Fast image interpolation for motion estimation using graphics hardware

NASA Astrophysics Data System (ADS)

Kelly, Francis; Kokaram, Anil

2004-05-01

Motion estimation and compensation is the key to high quality video coding. Block matching motion estimation is used in most video codecs, including MPEG-2, MPEG-4, H.263 and H.26L. Motion estimation is also a key component in the digital restoration of archived video and for post-production and special effects in the movie industry. Sub-pixel accurate motion vectors can improve the quality of the vector field and lead to more efficient video coding. However sub-pixel accuracy requires interpolation of the image data. Image interpolation is a key requirement of many image processing algorithms. Often interpolation can be a bottleneck in these applications, especially in motion estimation due to the large number pixels involved. In this paper we propose using commodity computer graphics hardware for fast image interpolation. We use the full search block matching algorithm to illustrate the problems and limitations of using graphics hardware in this way.

A Demons algorithm for image registration with locally adaptive regularization.

PubMed

Cahill, Nathan D; Noble, J Alison; Hawkes, David J

2009-01-01

Thirion's Demons is a popular algorithm for nonrigid image registration because of its linear computational complexity and ease of implementation. It approximately solves the diffusion registration problem by successively estimating force vectors that drive the deformation toward alignment and smoothing the force vectors by Gaussian convolution. In this article, we show how the Demons algorithm can be generalized to allow image-driven locally adaptive regularization in a manner that preserves both the linear complexity and ease of implementation of the original Demons algorithm. We show that the proposed algorithm exhibits lower target registration error and requires less computational effort than the original Demons algorithm on the registration of serial chest CT scans of patients with lung nodules.

Low bit rate coding of Earth science images

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1993-01-01

In this paper, the authors discuss compression based on some new ideas in vector quantization and their incorporation in a sub-band coding framework. Several variations are considered, which collectively address many of the individual compression needs within the earth science community. The approach taken in this work is based on some recent advances in the area of variable rate residual vector quantization (RVQ). This new RVQ method is considered separately and in conjunction with sub-band image decomposition. Very good results are achieved in coding a variety of earth science images. The last section of the paper provides some comparisons that illustrate the improvement in performance attributable to this approach relative the the JPEG coding standard.

Vectoring of parallel synthetic jets: A parametric study

NASA Astrophysics Data System (ADS)

Berk, Tim; Gomit, Guillaume; Ganapathisubramani, Bharathram

2016-11-01

The vectoring of a pair of parallel synthetic jets can be described using five dimensionless parameters: the aspect ratio of the slots, the Strouhal number, the Reynolds number, the phase difference between the jets and the spacing between the slots. In the present study, the influence of the latter four on the vectoring behaviour of the jets is examined experimentally using particle image velocimetry. Time-averaged velocity maps are used to study the variations in vectoring behaviour for a parametric sweep of each of the four parameters independently. A topological map is constructed for the full four-dimensional parameter space. The vectoring behaviour is described both qualitatively and quantitatively. A vectoring mechanism is proposed, based on measured vortex positions. We acknowledge the financial support from the European Research Council (ERC Grant Agreement No. 277472).

Discovering and understanding the vector field using simulation in android app

NASA Astrophysics Data System (ADS)

Budi, A.; Muliyati, D.

2018-05-01

An understanding of vector field’s concepts are fundamental parts of the electrodynamics course. In this paper, we use a simple simulation that can be used to show qualitative imaging results as a variation of the vector field. Android application packages the simulation with consideration of the efficiency of use during the lecture. In addition, this simulation also trying to cover the divergences and curl concepts from the same conditions that students have a complete understanding and can distinguish concepts that have been described only mathematically. This simulation is designed to show the relationship between the field magnitude and its potential. This application can show vector field simulations in various conditions that help to improve students’ understanding of vector field concepts and their relation to particle existence around the field vector.

Robust and accurate vectorization of line drawings.

PubMed

Hilaire, Xavier; Tombre, Karl

2006-06-01

This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.

An optimized color transformation for the analysis of digital images of hematoxylin & eosin stained slides.

PubMed

Zarella, Mark D; Breen, David E; Plagov, Andrei; Garcia, Fernando U

2015-01-01

Hematoxylin and eosin (H&E) staining is ubiquitous in pathology practice and research. As digital pathology has evolved, the reliance of quantitative methods that make use of H&E images has similarly expanded. For example, cell counting and nuclear morphometry rely on the accurate demarcation of nuclei from other structures and each other. One of the major obstacles to quantitative analysis of H&E images is the high degree of variability observed between different samples and different laboratories. In an effort to characterize this variability, as well as to provide a substrate that can potentially mitigate this factor in quantitative image analysis, we developed a technique to project H&E images into an optimized space more appropriate for many image analysis procedures. We used a decision tree-based support vector machine learning algorithm to classify 44 H&E stained whole slide images of resected breast tumors according to the histological structures that are present. This procedure takes an H&E image as an input and produces a classification map of the image that predicts the likelihood of a pixel belonging to any one of a set of user-defined structures (e.g., cytoplasm, stroma). By reducing these maps into their constituent pixels in color space, an optimal reference vector is obtained for each structure, which identifies the color attributes that maximally distinguish one structure from other elements in the image. We show that tissue structures can be identified using this semi-automated technique. By comparing structure centroids across different images, we obtained a quantitative depiction of H&E variability for each structure. This measurement can potentially be utilized in the laboratory to help calibrate daily staining or identify troublesome slides. Moreover, by aligning reference vectors derived from this technique, images can be transformed in a way that standardizes their color properties and makes them more amenable to image processing.

Fruit fly optimization based least square support vector regression for blind image restoration

NASA Astrophysics Data System (ADS)

Zhang, Jiao; Wang, Rui; Li, Junshan; Yang, Yawei

2014-11-01

The goal of image restoration is to reconstruct the original scene from a degraded observation. It is a critical and challenging task in image processing. Classical restorations require explicit knowledge of the point spread function and a description of the noise as priors. However, it is not practical for many real image processing. The recovery processing needs to be a blind image restoration scenario. Since blind deconvolution is an ill-posed problem, many blind restoration methods need to make additional assumptions to construct restrictions. Due to the differences of PSF and noise energy, blurring images can be quite different. It is difficult to achieve a good balance between proper assumption and high restoration quality in blind deconvolution. Recently, machine learning techniques have been applied to blind image restoration. The least square support vector regression (LSSVR) has been proven to offer strong potential in estimating and forecasting issues. Therefore, this paper proposes a LSSVR-based image restoration method. However, selecting the optimal parameters for support vector machine is essential to the training result. As a novel meta-heuristic algorithm, the fruit fly optimization algorithm (FOA) can be used to handle optimization problems, and has the advantages of fast convergence to the global optimal solution. In the proposed method, the training samples are created from a neighborhood in the degraded image to the central pixel in the original image. The mapping between the degraded image and the original image is learned by training LSSVR. The two parameters of LSSVR are optimized though FOA. The fitness function of FOA is calculated by the restoration error function. With the acquired mapping, the degraded image can be recovered. Experimental results show the proposed method can obtain satisfactory restoration effect. Compared with BP neural network regression, SVR method and Lucy-Richardson algorithm, it speeds up the restoration rate and performs better. Both objective and subjective restoration performances are studied in the comparison experiments.

Clinical validation of coronal and sagittal spinal curve measurements based on three-dimensional vertebra vector parameters.

PubMed

Somoskeöy, Szabolcs; Tunyogi-Csapó, Miklós; Bogyó, Csaba; Illés, Tamás

2012-10-01

For many decades, visualization and evaluation of three-dimensional (3D) spinal deformities have only been possible by two-dimensional (2D) radiodiagnostic methods, and as a result, characterization and classification were based on 2D terminologies. Recent developments in medical digital imaging and 3D visualization techniques including surface 3D reconstructions opened a chance for a long-sought change in this field. Supported by a 3D Terminology on Spinal Deformities of the Scoliosis Research Society, an approach for 3D measurements and a new 3D classification of scoliosis yielded several compelling concepts on 3D visualization and new proposals for 3D classification in recent years. More recently, a new proposal for visualization and complete 3D evaluation of the spine by 3D vertebra vectors has been introduced by our workgroup, a concept, based on EOS 2D/3D, a groundbreaking new ultralow radiation dose integrated orthopedic imaging device with sterEOS 3D spine reconstruction software. Comparison of accuracy, correlation of measurement values, intraobserver and interrater reliability of methods by conventional manual 2D and vertebra vector-based 3D measurements in a routine clinical setting. Retrospective, nonrandomized study of diagnostic X-ray images created as part of a routine clinical protocol of eligible patients examined at our clinic during a 30-month period between July 2007 and December 2009. In total, 201 individuals (170 females, 31 males; mean age, 19.88 years) including 10 healthy athletes with normal spine and patients with adolescent idiopathic scoliosis (175 cases), adult degenerative scoliosis (11 cases), and Scheuermann hyperkyphosis (5 cases). Overall range of coronal curves was between 2.4 and 117.5°. Analysis of accuracy and reliability of measurements was carried out on a group of all patients and in subgroups based on coronal plane deviation: 0 to 10° (Group 1; n=36), 10 to 25° (Group 2; n=25), 25 to 50° (Group 3; n=69), 50 to 75° (Group 4; n=49), and above 75° (Group 5; n=22). All study subjects were examined by EOS 2D imaging, resulting in anteroposterior (AP) and lateral (LAT) full spine, orthogonal digital X-ray images, in standing position. Conventional coronal and sagittal curvature measurements including sagittal L5 vertebra wedges were determined by 3 experienced examiners, using traditional Cobb methods on EOS 2D AP and LAT images. Vertebra vector-based measurements were performed as published earlier, based on computer-assisted calculations of corresponding spinal curvature. Vertebra vectors were generated by dedicated software from sterEOS 3D spine models reconstructed from EOS 2D images by the same three examiners. Manual measurements were performed by each examiner, thrice for sterEOS 3D reconstructions and twice for vertebra vector-based measurements. Means comparison t test, Pearson bivariate correlation analysis, reliability analysis by intraclass correlation coefficients for intraobserver reproducibility and interrater reliability were performed using SPSS v16.0 software. In comparison with manual 2D methods, only small and nonsignificant differences were detectable in vertebra vector-based curvature data for coronal curves and thoracic kyphosis, whereas the found difference in L1-L5 lordosis values was shown to be strongly related to the magnitude of corresponding L5 wedge. Intraobserver reliability was excellent for both methods, and interrater reproducibility was consistently higher for vertebra vector-based methods that was also found to be unaffected by the magnitude of coronal curves or sagittal plane deviations. Vertebra vector-based angulation measurements could fully substitute conventional manual 2D measurements, with similar accuracy and higher intraobserver reliability and interrater reproducibility. Vertebra vectors represent a truly 3D solution for clear and comprehensible 3D visualization of spinal deformities while preserving crucial parametric information for vertebral size, 3D position, orientation, and rotation. The concept of vertebra vectors may serve as a starting point to a valid and clinically useful alternative for a new 3D classification of scoliosis. Copyright © 2012 Elsevier Inc. All rights reserved.

The possibilities of improvement in the sensitivity of cancer fluorescence diagnostics by computer image processing

NASA Astrophysics Data System (ADS)

Ledwon, Aleksandra; Bieda, Robert; Kawczyk-Krupka, Aleksandra; Polanski, Andrzej; Wojciechowski, Konrad; Latos, Wojciech; Sieron-Stoltny, Karolina; Sieron, Aleksander

2008-02-01

Background: Fluorescence diagnostics uses the ability of tissues to fluoresce after exposition to a specific wavelength of light. The change in fluorescence between normal and progression to cancer allows to see early cancer and precancerous lesions often missed by white light. Aim: To improve by computer image processing the sensitivity of fluorescence images obtained during examination of skin, oral cavity, vulva and cervix lesions, during endoscopy, cystoscopy and bronchoscopy using Xillix ONCOLIFE. Methods: Function of image f(x,y):R2 --> R 3 was transformed from original color space RGB to space in which vector of 46 values refers to every point labeled by defined xy-coordinates- f(x,y):R2 --> R 46. By means of Fisher discriminator vector of attributes of concrete point analalyzed in the image was reduced according to two defined classes defined as pathologic areas (foreground) and healthy areas (background). As a result the highest four fisher's coefficients allowing the greatest separation between points of pathologic (foreground) and healthy (background) areas were chosen. In this way new function f(x,y):R2 --> R 4 was created in which point x,y corresponds with vector Y, H, a*, c II. In the second step using Gaussian Mixtures and Expectation-Maximisation appropriate classificator was constructed. This classificator enables determination of probability that the selected pixel of analyzed image is a pathologically changed point (foreground) or healthy one (background). Obtained map of probability distribution was presented by means of pseudocolors. Results: Image processing techniques improve the sensitivity, quality and sharpness of original fluorescence images. Conclusion: Computer image processing enables better visualization of suspected areas examined by means of fluorescence diagnostics.

Vector assembly of colloids on monolayer substrates

NASA Astrophysics Data System (ADS)

Jiang, Lingxiang; Yang, Shenyu; Tsang, Boyce; Tu, Mei; Granick, Steve

2017-06-01

The key to spontaneous and directed assembly is to encode the desired assembly information to building blocks in a programmable and efficient way. In computer graphics, raster graphics encodes images on a single-pixel level, conferring fine details at the expense of large file sizes, whereas vector graphics encrypts shape information into vectors that allow small file sizes and operational transformations. Here, we adapt this raster/vector concept to a 2D colloidal system and realize `vector assembly' by manipulating particles on a colloidal monolayer substrate with optical tweezers. In contrast to raster assembly that assigns optical tweezers to each particle, vector assembly requires a minimal number of optical tweezers that allow operations like chain elongation and shortening. This vector approach enables simple uniform particles to form a vast collection of colloidal arenes and colloidenes, the spontaneous dissociation of which is achieved with precision and stage-by-stage complexity by simply removing the optical tweezers.

Vectoring of parallel synthetic jets

NASA Astrophysics Data System (ADS)

Berk, Tim; Ganapathisubramani, Bharathram; Gomit, Guillaume

2015-11-01

A pair of parallel synthetic jets can be vectored by applying a phase difference between the two driving signals. The resulting jet can be merged or bifurcated and either vectored towards the actuator leading in phase or the actuator lagging in phase. In the present study, the influence of phase difference and Strouhal number on the vectoring behaviour is examined experimentally. Phase-locked vorticity fields, measured using Particle Image Velocimetry (PIV), are used to track vortex pairs. The physical mechanisms that explain the diversity in vectoring behaviour are observed based on the vortex trajectories. For a fixed phase difference, the vectoring behaviour is shown to be primarily influenced by pinch-off time of vortex rings generated by the synthetic jets. Beyond a certain formation number, the pinch-off timescale becomes invariant. In this region, the vectoring behaviour is determined by the distance between subsequent vortex rings. We acknowledge the financial support from the European Research Council (ERC grant agreement no. 277472).

Fabric wrinkle characterization and classification using modified wavelet coefficients and optimized support-vector-machine classifier

USDA-ARS?s Scientific Manuscript database

This paper presents a novel wrinkle evaluation method that uses modified wavelet coefficients and an optimized support-vector-machine (SVM) classification scheme to characterize and classify wrinkle appearance of fabric. Fabric images were decomposed with the wavelet transform (WT), and five parame...

Corrosion-Control (CC) Program SIMA (Shore Intermediate Maintenance Activity) Pilot CC (Corrosion-Control) Shop Service Test and Technical Support. Volume 1. Final Report. Sections 1 to 8.

DTIC Science & Technology

1985-11-30

fri 11 41 CC -j L ii La u 6: Kl9 L : 1 V)VI Go L...COPELAND) were conducted and 211 items were inspected. Of those degraded items, 64 required rework . Lessons learned from the inspections are proving...8217,," " "-" " ".’...’ " "-’,’-’** .* ". " -.- ".’’-"-*"-.-- " "- -" "- .. ’ ."’. . . ". ".".".. .. . . ." "’ "" .""""-"","" * r DISTRIBUTION (Cont’d) NO. OF COPES Commanding Officer, USS

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

Computation of fluid and particle motion from a time-sequenced image pair: a global outlier identification approach.

PubMed

Ray, Nilanjan

2011-10-01

Fluid motion estimation from time-sequenced images is a significant image analysis task. Its application is widespread in experimental fluidics research and many related areas like biomedical engineering and atmospheric sciences. In this paper, we present a novel flow computation framework to estimate the flow velocity vectors from two consecutive image frames. In an energy minimization-based flow computation, we propose a novel data fidelity term, which: 1) can accommodate various measures, such as cross-correlation or sum of absolute or squared differences of pixel intensities between image patches; 2) has a global mechanism to control the adverse effect of outliers arising out of motion discontinuities, proximity of image borders; and 3) can go hand-in-hand with various spatial smoothness terms. Further, the proposed data term and related regularization schemes are both applicable to dense and sparse flow vector estimations. We validate these claims by numerical experiments on benchmark flow data sets. © 2011 IEEE

Magnetic resonance image compression using scalar-vector quantization

NASA Astrophysics Data System (ADS)

Mohsenian, Nader; Shahri, Homayoun

1995-12-01

A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. SVQ is a fixed-rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity issues of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation which is typical of coding schemes which use variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes our SVQ based coder an attractive compression scheme for picture archiving and communication systems (PACS), currently under consideration for an all digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired.

Full-reference quality assessment of stereoscopic images by learning binocular receptive field properties.

PubMed

Shao, Feng; Li, Kemeng; Lin, Weisi; Jiang, Gangyi; Yu, Mei; Dai, Qionghai

2015-10-01

Quality assessment of 3D images encounters more challenges than its 2D counterparts. Directly applying 2D image quality metrics is not the solution. In this paper, we propose a new full-reference quality assessment for stereoscopic images by learning binocular receptive field properties to be more in line with human visual perception. To be more specific, in the training phase, we learn a multiscale dictionary from the training database, so that the latent structure of images can be represented as a set of basis vectors. In the quality estimation phase, we compute sparse feature similarity index based on the estimated sparse coefficient vectors by considering their phase difference and amplitude difference, and compute global luminance similarity index by considering luminance changes. The final quality score is obtained by incorporating binocular combination based on sparse energy and sparse complexity. Experimental results on five public 3D image quality assessment databases demonstrate that in comparison with the most related existing methods, the devised algorithm achieves high consistency with subjective assessment.

GIS based Cadastral level Forest Information System using World View-II data in Bir Hisar (Haryana)

NASA Astrophysics Data System (ADS)

Mothi Kumar, K. E.; Singh, S.; Attri, P.; Kumar, R.; Kumar, A.; Sarika; Hooda, R. S.; Sapra, R. K.; Garg, V.; Kumar, V.; Nivedita

2014-11-01

Identification and demarcation of Forest lands on the ground remains a major challenge in Forest administration and management. Cadastral forest mapping deals with forestlands boundary delineation and their associated characterization (forest/non forest). The present study is an application of high resolution World View-II data for digitization of Protected Forest boundary at cadastral level with integration of Records of Right (ROR) data. Cadastral vector data was generated by digitization of spatial data using scanned mussavies in ArcGIS environment. Ortho-images were created from World View-II digital stereo data with Universal Transverse Mercator coordinate system with WGS 84 datum. Cadastral vector data of Bir Hisar (Hisar district, Haryana) and adjacent villages was spatially adjusted over ortho-image using ArcGIS software. Edge matching of village boundaries was done with respect to khasra boundaries of individual village. The notified forest grids were identified on ortho-image and grid vector data was extracted from georeferenced cadastral data. Cadastral forest boundary vectors were digitized from ortho-images. Accuracy of cadastral data was checked by comparison of randomly selected geo-coordinates points, tie lines and boundary measurements of randomly selected parcels generated from image data set with that of actual field measurements. Area comparison was done between cadastral map area, the image map area and RoR area. The area covered under Protected Forest was compared with ROR data and within an accuracy of less than 1 % from ROR area was accepted. The methodology presented in this paper is useful to update the cadastral forest maps. The produced GIS databases and large-scale Forest Maps may serve as a data foundation towards a land register of forests. The study introduces the use of very high resolution satellite data to develop a method for cadastral surveying through on - screen digitization in a less time as compared to the old fashioned cadastral parcel boundaries surveying method.

Preparation of a Versatile Bifunctional Zeolite for Targeted Imaging Applications

PubMed Central

Ndiege, Nicholas; Raidoo, Renugan; Schultz, Michael K.; Larsen, Sarah

2011-01-01

Bifunctional zeolite Y was prepared for use in targeted in vivo molecular imaging applications. The strategy involved functionalization of the external surface of zeolite Y with chloropropyltriethoxysilane followed by reaction with sodium azide to form azide-functionalized NaY, which is amenable to copper(1) catalyzed click chemistry. In this study, a model alkyne (4-pentyn-1-ol) was attached to the azide-terminated surface via click chemistry to demonstrate feasibility for attachment of molecular targeting vectors (e.g., peptides, aptamers) to the zeolite surface. The modified particle efficiently incorporates the imaging radioisotope gallium-68 (68Ga) into the pores of the azide-functionalized NaY zeolite to form a stable bifunctional molecular targeting vector. The result is a versatile “clickable” zeolite platform that can be tailored for future in vivo molecular targeting and imaging modalities. PMID:21306141

Exploring the impact of wavelet-based denoising in the classification of remote sensing hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco

2016-10-01

The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.

Fine-scale mapping of vector habitats using very high resolution satellite imagery: a liver fluke case-study.

PubMed

De Roeck, Els; Van Coillie, Frieke; De Wulf, Robert; Soenen, Karen; Charlier, Johannes; Vercruysse, Jozef; Hantson, Wouter; Ducheyne, Els; Hendrickx, Guy

2014-12-01

The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke, as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of <5m resolution was acquired in the spring of 2013 for the area around Bruges, Belgium, a region where dairy farms suffer from liver fluke infections transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

Remote sensing and GIS integration: Towards intelligent imagery within a spatial data infrastructure

NASA Astrophysics Data System (ADS)

Abdelrahim, Mohamed Mahmoud Hosny

2001-11-01

In this research, an "Intelligent Imagery System Prototype" (IISP) was developed. IISP is an integration tool that facilitates the environment for active, direct, and on-the-fly usage of high resolution imagery, internally linked to hidden GIS vector layers, to query the real world phenomena and, consequently, to perform exploratory types of spatial analysis based on a clear/undisturbed image scene. The IISP was designed and implemented using the software components approach to verify the hypothesis that a fully rectified, partially rectified, or even unrectified digital image can be internally linked to a variety of different hidden vector databases/layers covering the end user area of interest, and consequently may be reliably used directly as a base for "on-the-fly" querying of real-world phenomena and for performing exploratory types of spatial analysis. Within IISP, differentially rectified, partially rectified (namely, IKONOS GEOCARTERRA(TM)), and unrectified imagery (namely, scanned aerial photographs and captured video frames) were investigated. The system was designed to handle four types of spatial functions, namely, pointing query, polygon/line-based image query, database query, and buffering. The system was developed using ESRI MapObjects 2.0a as the core spatial component within Visual Basic 6.0. When used to perform the pre-defined spatial queries using different combinations of image and vector data, the IISP provided the same results as those obtained by querying pre-processed vector layers even when the image used was not orthorectified and the vector layers had different parameters. In addition, the real-time pixel location orthorectification technique developed and presented within the IKONOS GEOCARTERRA(TM) case provided a horizontal accuracy (RMSE) of +/- 2.75 metres. This accuracy is very close to the accuracy level obtained when purchasing the orthorectified IKONOS PRECISION products (RMSE of +/- 1.9 metre). The latter cost approximately four times as much as the IKONOS GEOCARTERRA(TM) products. The developed IISP is a step closer towards the direct and active involvement of high-resolution remote sensing imagery in querying the real world and performing exploratory types of spatial analysis. (Abstract shortened by UMI.)

Computerized tongue image segmentation via the double geo-vector flow

PubMed Central

2014-01-01

Background Visual inspection for tongue analysis is a diagnostic method in traditional Chinese medicine (TCM). Owing to the variations in tongue features, such as color, texture, coating, and shape, it is difficult to precisely extract the tongue region in images. This study aims to quantitatively evaluate tongue diagnosis via automatic tongue segmentation. Methods Experiments were conducted using a clinical image dataset provided by the Laboratory of Traditional Medical Syndromes, Shanghai University of TCM. First, a clinical tongue image was refined by a saliency window. Second, we initialized the tongue area as the upper binary part and lower level set matrix. Third, a double geo-vector flow (DGF) was proposed to detect the tongue edge and segment the tongue region in the image, such that the geodesic flow was evaluated in the lower part, and the geo-gradient vector flow was evaluated in the upper part. Results The performance of the DGF was evaluated using 100 images. The DGF exhibited better results compared with other representative studies, with its true-positive volume fraction reaching 98.5%, its false-positive volume fraction being 1.51%, and its false-negative volume fraction being 1.42%. The errors between the proposed automatic segmentation results and manual contours were 0.29 and 1.43% in terms of the standard boundary error metrics of Hausdorff distance and mean distance, respectively. Conclusions By analyzing the time complexity of the DGF and evaluating its performance via standard boundary and area error metrics, we have shown both efficiency and effectiveness of the DGF for automatic tongue image segmentation. PMID:24507094

Computerized tongue image segmentation via the double geo-vector flow.

PubMed

Shi, Miao-Jing; Li, Guo-Zheng; Li, Fu-Feng; Xu, Chao

2014-02-08

Visual inspection for tongue analysis is a diagnostic method in traditional Chinese medicine (TCM). Owing to the variations in tongue features, such as color, texture, coating, and shape, it is difficult to precisely extract the tongue region in images. This study aims to quantitatively evaluate tongue diagnosis via automatic tongue segmentation. Experiments were conducted using a clinical image dataset provided by the Laboratory of Traditional Medical Syndromes, Shanghai University of TCM. First, a clinical tongue image was refined by a saliency window. Second, we initialized the tongue area as the upper binary part and lower level set matrix. Third, a double geo-vector flow (DGF) was proposed to detect the tongue edge and segment the tongue region in the image, such that the geodesic flow was evaluated in the lower part, and the geo-gradient vector flow was evaluated in the upper part. The performance of the DGF was evaluated using 100 images. The DGF exhibited better results compared with other representative studies, with its true-positive volume fraction reaching 98.5%, its false-positive volume fraction being 1.51%, and its false-negative volume fraction being 1.42%. The errors between the proposed automatic segmentation results and manual contours were 0.29 and 1.43% in terms of the standard boundary error metrics of Hausdorff distance and mean distance, respectively. By analyzing the time complexity of the DGF and evaluating its performance via standard boundary and area error metrics, we have shown both efficiency and effectiveness of the DGF for automatic tongue image segmentation.

A bioluminescent imaging mouse model for Marburg virus based on a pseudovirus system.

PubMed

Zhang, Li; Li, Qianqian; Liu, Qiang; Huang, Weijin; Nie, Jianhui; Wang, Youchun

2017-08-03

Marburg virus (MARV) can cause lethal hemorrhagic fever in humans. Handling of MARV is restricted to high-containment biosafety level 4 (BSL-4) facilities, which greatly impedes research into this virus. In this study, a high titer of MARV pseudovirus was generated through optimization of the HIV backbone vectors, the ratio of backbone vector to MARV glycoprotein expression vector, and the transfection reagents. An in vitro neutralization assay and an in vivo bioluminescent imaging mouse model for MARV were developed based on the pseudovirus. Protective serum against MARV was successfully induced in guinea pigs, which showed high neutralization activity in vitro and could also protect Balb/c mice from MARV pseudovirus infection in vivo. This system could be a convenient tool to enable the evaluation of vaccines and therapeutic drugs against MARV in non-BSL-4 laboratories.

Cryogenic STM in 3D vector magnetic fields realized through a rotatable insert.

PubMed

Trainer, C; Yim, C M; McLaren, M; Wahl, P

2017-09-01

Spin-polarized scanning tunneling microscopy (SP-STM) performed in vector magnetic fields promises atomic scale imaging of magnetic structure, providing complete information on the local spin texture of a sample in three dimensions. Here, we have designed and constructed a turntable system for a low temperature STM which in combination with a 2D vector magnet provides magnetic fields of up to 5 T in any direction relative to the tip-sample geometry. This enables STM imaging and spectroscopy to be performed at the same atomic-scale location and field-of-view on the sample, and most importantly, without experiencing any change on the tip apex before and after field switching. Combined with a ferromagnetic tip, this enables us to study the magnetization of complex magnetic orders in all three spatial directions.

Combined empirical mode decomposition and texture features for skin lesion classification using quadratic support vector machine.

PubMed

Wahba, Maram A; Ashour, Amira S; Napoleon, Sameh A; Abd Elnaby, Mustafa M; Guo, Yanhui

2017-12-01

Basal cell carcinoma is one of the most common malignant skin lesions. Automated lesion identification and classification using image processing techniques is highly required to reduce the diagnosis errors. In this study, a novel technique is applied to classify skin lesion images into two classes, namely the malignant Basal cell carcinoma and the benign nevus. A hybrid combination of bi-dimensional empirical mode decomposition and gray-level difference method features is proposed after hair removal. The combined features are further classified using quadratic support vector machine (Q-SVM). The proposed system has achieved outstanding performance of 100% accuracy, sensitivity and specificity compared to other support vector machine procedures as well as with different extracted features. Basal Cell Carcinoma is effectively classified using Q-SVM with the proposed combined features.

Human action classification using procrustes shape theory

NASA Astrophysics Data System (ADS)

Cho, Wanhyun; Kim, Sangkyoon; Park, Soonyoung; Lee, Myungeun

2015-02-01

In this paper, we propose new method that can classify a human action using Procrustes shape theory. First, we extract a pre-shape configuration vector of landmarks from each frame of an image sequence representing an arbitrary human action, and then we have derived the Procrustes fit vector for pre-shape configuration vector. Second, we extract a set of pre-shape vectors from tanning sample stored at database, and we compute a Procrustes mean shape vector for these preshape vectors. Third, we extract a sequence of the pre-shape vectors from input video, and we project this sequence of pre-shape vectors on the tangent space with respect to the pole taking as a sequence of mean shape vectors corresponding with a target video. And we calculate the Procrustes distance between two sequences of the projection pre-shape vectors on the tangent space and the mean shape vectors. Finally, we classify the input video into the human action class with minimum Procrustes distance. We assess a performance of the proposed method using one public dataset, namely Weizmann human action dataset. Experimental results reveal that the proposed method performs very good on this dataset.

An integrated use of topography with RSI in gully mapping, Shandong Peninsula, China.

PubMed

He, Fuhong; Wang, Tao; Gu, Lijuan; Li, Tao; Jiang, Weiguo; Shao, Hongbo

2014-01-01

Taking the Quickbird optical satellite imagery of the small watershed of Beiyanzigou valley of Qixia city, Shandong province, as the study data, we proposed a new method by using a fused image of topography with remote sensing imagery (RSI) to achieve a high precision interpretation of gully edge lines. The technique first transformed remote sensing imagery into HSV color space from RGB color space. Then the slope threshold values of gully edge line and gully thalweg were gained through field survey and the slope data were segmented using thresholding, respectively. Based on the fused image in combination with gully thalweg thresholding vectors, the gully thalweg thresholding vectors were amended. Lastly, the gully edge line might be interpreted based on the amended gully thalweg vectors, fused image, gully edge line thresholding vectors, and slope data. A testing region was selected in the study area to assess the accuracy. Then accuracy assessment of the gully information interpreted by both interpreting remote sensing imagery only and the fused image was performed using the deviation, kappa coefficient, and overall accuracy of error matrix. Compared with interpreting remote sensing imagery only, the overall accuracy and kappa coefficient are increased by 24.080% and 264.364%, respectively. The average deviations of gully head and gully edge line are reduced by 60.448% and 67.406%, respectively. The test results show the thematic and the positional accuracy of gully interpreted by new method are significantly higher. Finally, the error sources for interpretation accuracy by the two methods were analyzed.

An Integrated Use of Topography with RSI in Gully Mapping, Shandong Peninsula, China

PubMed Central

He, Fuhong; Wang, Tao; Gu, Lijuan; Li, Tao; Jiang, Weiguo; Shao, Hongbo

2014-01-01

Taking the Quickbird optical satellite imagery of the small watershed of Beiyanzigou valley of Qixia city, Shandong province, as the study data, we proposed a new method by using a fused image of topography with remote sensing imagery (RSI) to achieve a high precision interpretation of gully edge lines. The technique first transformed remote sensing imagery into HSV color space from RGB color space. Then the slope threshold values of gully edge line and gully thalweg were gained through field survey and the slope data were segmented using thresholding, respectively. Based on the fused image in combination with gully thalweg thresholding vectors, the gully thalweg thresholding vectors were amended. Lastly, the gully edge line might be interpreted based on the amended gully thalweg vectors, fused image, gully edge line thresholding vectors, and slope data. A testing region was selected in the study area to assess the accuracy. Then accuracy assessment of the gully information interpreted by both interpreting remote sensing imagery only and the fused image was performed using the deviation, kappa coefficient, and overall accuracy of error matrix. Compared with interpreting remote sensing imagery only, the overall accuracy and kappa coefficient are increased by 24.080% and 264.364%, respectively. The average deviations of gully head and gully edge line are reduced by 60.448% and 67.406%, respectively. The test results show the thematic and the positional accuracy of gully interpreted by new method are significantly higher. Finally, the error sources for interpretation accuracy by the two methods were analyzed. PMID:25302333

Fluorescent protein vectors for pancreatic islet cell identification in live-cell imaging.

PubMed

Shuai, Hongyan; Xu, Yunjian; Yu, Qian; Gylfe, Erik; Tengholm, Anders

2016-10-01

The islets of Langerhans contain different types of endocrine cells, which are crucial for glucose homeostasis. β- and α-cells that release insulin and glucagon, respectively, are most abundant, whereas somatostatin-producing δ-cells and particularly pancreatic polypeptide-releasing PP-cells are more scarce. Studies of islet cell function are hampered by difficulties to identify the different cell types, especially in live-cell imaging experiments when immunostaining is unsuitable. The aim of the present study was to create a set of vectors for fluorescent protein expression with cell-type-specific promoters and evaluate their applicability in functional islet imaging. We constructed six adenoviral vectors for expression of red and green fluorescent proteins controlled by the insulin, preproglucagon, somatostatin, or pancreatic polypeptide promoters. After transduction of mouse and human islets or dispersed islet cells, a majority of the fluorescent cells also immunostained for the appropriate hormone. Recordings of the sub-plasma membrane Ca(2+) and cAMP concentrations with a fluorescent indicator and a protein biosensor, respectively, showed that labeled cells respond to glucose and other modulators of secretion and revealed a striking variability in Ca(2+) signaling among α-cells. The measurements allowed comparison of the phase relationship of Ca(2+) oscillations between different types of cells within intact islets. We conclude that the fluorescent protein vectors allow easy identification of specific islet cell types and can be used in live-cell imaging together with organic dyes and genetically encoded biosensors. This approach will facilitate studies of normal islet physiology and help to clarify molecular defects and disturbed cell interactions in diabetic islets.

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Huang, Y. F.; Stevenson, Robert L.

1994-01-01

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.

Nanoscale magnetic imaging using picosecond thermal gradients

NASA Astrophysics Data System (ADS)

Fuchs, Gregory

Research and development in spintronics is challenged by the lack of table-top magnetic imaging technologies that posses the simultaneous temporal resolution and spatial resolution to characterize magnetization dynamics in emerging spintronic devices. In addition, many of the most exciting magnetic material systems for spintronics are difficult to image with any method. To address this challenge, we developed a spatiotemporal magnetic microscope based on picosecond heat pulses that stroboscopically transduces an in-plane magnetization into a voltage signal. When the magnetic device contains a magnetic metal like FeCoB or NiFe, we use the time-resolved anomalous Nernst effect. When it contains a magnetic insulator/normal metal bilayer like yttrium iron garnet/platinum, we use the combination of the time-resolved longitudinal spin Seebeck effect and the inverse spin Hall effect. We demonstrate that these imaging modalities have time resolutions in the range of 10-100 ps and sensitivities in the range of 0.1 - 0.3° /√{Hz} , which enables not only static magnetic imaging, but also phase-sensitive ferromagnetic resonance imaging. One application of this technology is for magnetic torque vector imaging, which we apply to a spin Hall device. We find an unexpected variation in the spin torque vector that suggests conventional, all-electrical FMR measurements of spin torque vectors can produce a systematic error as large as 30% when quantifying the spin Hall efficiency. Finally, I will describe how time-resolved magnetic imaging can greatly exceed the spatial resolution of optical diffraction. We demonstrate scanning a sharp gold tip to create near-field thermal transfer from a picosecond laser pulse to a magnetic sample as the basis of a nanoscale spatiotemporal microscope. We gratefully acknowledge support from the AFOSR (FA9550-14-1-0243) and the NSF through the Cornell Center for Materials Research (DMR-1120296).

ISBDD Model for Classification of Hyperspectral Remote Sensing Imagery

PubMed Central

Li, Na; Xu, Zhaopeng; Zhao, Huijie; Huang, Xinchen; Drummond, Jane; Wang, Daming

2018-01-01

The diverse density (DD) algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels). However, the feature vector learned by the DD algorithm cannot always effectively represent one type of ground cover. To handle this problem, an instance space-based diverse density (ISBDD) model that employs a novel training strategy is proposed in this paper. In the ISBDD model, DD values of each pixel are computed instead of learning a feature vector, and as a result, the pixel can be classified according to its DD values. Airborne hyperspectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor and the Push-broom Hyperspectral Imager (PHI) are applied to evaluate the performance of the proposed model. Results show that the overall classification accuracy of ISBDD model on the AVIRIS and PHI images is up to 97.65% and 89.02%, respectively, while the kappa coefficient is up to 0.97 and 0.88, respectively. PMID:29510547

Incremental classification learning for anomaly detection in medical images

NASA Astrophysics Data System (ADS)

Giritharan, Balathasan; Yuan, Xiaohui; Liu, Jianguo

2009-02-01

Computer-aided diagnosis usually screens thousands of instances to find only a few positive cases that indicate probable presence of disease.The amount of patient data increases consistently all the time. In diagnosis of new instances, disagreement occurs between a CAD system and physicians, which suggests inaccurate classifiers. Intuitively, misclassified instances and the previously acquired data should be used to retrain the classifier. This, however, is very time consuming and, in some cases where dataset is too large, becomes infeasible. In addition, among the patient data, only a small percentile shows positive sign, which is known as imbalanced data.We present an incremental Support Vector Machines(SVM) as a solution for the class imbalance problem in classification of anomaly in medical images. The support vectors provide a concise representation of the distribution of the training data. Here we use bootstrapping to identify potential candidate support vectors for future iterations. Experiments were conducted using images from endoscopy videos, and the sensitivity and specificity were close to that of SVM trained using all samples available at a given incremental step with significantly improved efficiency in training the classifier.

Agricultural mapping using Support Vector Machine-Based Endmember Extraction (SVM-BEE)

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

Archibald, Richard K; Filippi, Anthony M; Bhaduri, Budhendra L

Extracting endmembers from remotely sensed images of vegetated areas can present difficulties. In this research, we applied a recently developed endmember-extraction algorithm based on Support Vector Machines (SVMs) to the problem of semi-autonomous estimation of vegetation endmembers from a hyperspectral image. This algorithm, referred to as Support Vector Machine-Based Endmember Extraction (SVM-BEE), accurately and rapidly yields a computed representation of hyperspectral data that can accommodate multiple distributions. The number of distributions is identified without prior knowledge, based upon this representation. Prior work established that SVM-BEE is robustly noise-tolerant and can semi-automatically and effectively estimate endmembers; synthetic data and a geologicmore » scene were previously analyzed. Here we compared the efficacies of the SVM-BEE and N-FINDR algorithms in extracting endmembers from a predominantly agricultural scene. SVM-BEE was able to estimate vegetation and other endmembers for all classes in the image, which N-FINDR failed to do. Classifications based on SVM-BEE endmembers were markedly more accurate compared with those based on N-FINDR endmembers.« less

Simplified method for the screening of technological maturity of red grape and total phenolic compounds of red grape skin: application of the characteristic vector method to near-infrared spectra.

PubMed

Nogales-Bueno, Julio; Ayala, Fernando; Hernández-Hierro, José Miguel; Rodríguez-Pulido, Francisco José; Echávarri, José Federico; Heredia, Francisco José

2015-05-06

Characteristic vector analysis has been applied to near-infrared spectra to extract the main spectral information from hyperspectral images. For this purpose, 3, 6, 9, and 12 characteristic vectors have been used to reconstruct the spectra, and root-mean-square errors (RMSEs) have been calculated to measure the differences between characteristic vector reconstructed spectra (CVRS) and hyperspectral imaging spectra (HIS). RMSE values obtained were 0.0049, 0.0018, 0.0012, and 0.0012 [log(1/R) units] for spectra allocated into the validation set, for 3, 6, 9, and 12 characteristic vectors, respectively. After that, calibration models have been developed and validated using the different groups of CVRS to predict skin total phenolic concentration, sugar concentration, titratable acidity, and pH by modified partial least-squares (MPLS) regression. The obtained results have been compared to those previously obtained from HIS. The models developed from the CVRS reconstructed from 12 characteristic vectors present similar values of coefficients of determination (RSQ) and standard errors of prediction (SEP) than the models developed from HIS. RSQ and SEP were 0.84 and 1.13 mg g(-1) of skin grape (expressed as gallic acid equivalents), 0.93 and 2.26 °Brix, 0.97 and 3.87 g L(-1) (expressed as tartaric acid equivalents), and 0.91 and 0.14 for skin total phenolic concentration, sugar concentration, titratable acidity, and pH, respectively, for the models developed from the CVRS reconstructed from 12 characteristic vectors.

Imer-product array processor for retrieval of stored images represented by bipolar binary (+1,-1) pixels using partial input trinary pixels represented by (+1,-1)

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Awwal, Abdul A. S. (Inventor); Karim, Mohammad A. (Inventor)

1993-01-01

An inner-product array processor is provided with thresholding of the inner product during each iteration to make more significant the inner product employed in estimating a vector to be used as the input vector for the next iteration. While stored vectors and estimated vectors are represented in bipolar binary (1,-1), only those elements of an initial partial input vector that are believed to be common with those of a stored vector are represented in bipolar binary; the remaining elements of a partial input vector are set to 0. This mode of representation, in which the known elements of a partial input vector are in bipolar binary form and the remaining elements are set equal to 0, is referred to as trinary representation. The initial inner products corresponding to the partial input vector will then be equal to the number of known elements. Inner-product thresholding is applied to accelerate convergence and to avoid convergence to a negative input product.

Computer aided detection of tumor and edema in brain FLAIR magnetic resonance image using ANN

NASA Astrophysics Data System (ADS)

Pradhan, Nandita; Sinha, A. K.

2008-03-01

This paper presents an efficient region based segmentation technique for detecting pathological tissues (Tumor & Edema) of brain using fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. This work segments FLAIR brain images for normal and pathological tissues based on statistical features and wavelet transform coefficients using k-means algorithm. The image is divided into small blocks of 4×4 pixels. The k-means algorithm is used to cluster the image based on the feature vectors of blocks forming different classes representing different regions in the whole image. With the knowledge of the feature vectors of different segmented regions, supervised technique is used to train Artificial Neural Network using fuzzy back propagation algorithm (FBPA). Segmentation for detecting healthy tissues and tumors has been reported by several researchers by using conventional MRI sequences like T1, T2 and PD weighted sequences. This work successfully presents segmentation of healthy and pathological tissues (both Tumors and Edema) using FLAIR images. At the end pseudo coloring of segmented and classified regions are done for better human visualization.

An H-band Vector Vortex Coronagraph for the Subaru Coronagraphic Extreme-adaptive Optics System

NASA Astrophysics Data System (ADS)

Kühn, J.; Serabyn, E.; Lozi, J.; Jovanovic, N.; Currie, T.; Guyon, O.; Kudo, T.; Martinache, F.; Liewer, K.; Singh, G.; Tamura, M.; Mawet, D.; Hagelberg, J.; Defrere, D.

2018-03-01

The vector vortex is a coronagraphic imaging mode of the recently commissioned Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) platform on the 8 m Subaru Telescope. This multi-purpose high-contrast visible and near-infrared (R- to K-band) instrument is not only intended to serve as a VLT-class “planet-imager” instrument in the northern hemisphere, but also to operate as a technology demonstration testbed ahead of the ELTs-era, with a particular emphasis on small inner-working angle (IWA) coronagraphic capabilities. The given priority to small-IWA imaging led to the early design choice to incorporate focal-plane phase-mask coronagraphs. In this context, a test H-band vector vortex liquid crystal polymer waveplate was provided to SCExAO, to allow a one-to-one comparison of different small-IWA techniques on the same telescope instrument, before considering further steps. Here we present a detailed overview of the vector vortex coronagraph, from its installation and performances on the SCExAO optical bench, to the on-sky results in the extreme AO regime, as of late 2016/early 2017. To this purpose, we also provide a few recent on-sky imaging examples, notably high-contrast ADI detection of the planetary-mass companion κ Andromedae b, with a signal-to-noise ratio above 100 reached in less than 10 mn exposure time.

Molecular phylogeny of the Anopheles gambiae complex suggests genetic introgression between principal malaria vectors.

PubMed Central

Besansky, N J; Powell, J R; Caccone, A; Hamm, D M; Scott, J A; Collins, F H

1994-01-01

The six Afrotropical species of mosquitoes comprising the Anopheles gambiae complex include the most efficient vectors of malaria in the world as well as a nonvector species. The accepted interpretation of evolutionary relationships among these species is based on chromosomal inversions and suggests that the two principal vectors, A. gambiae and Anopheles arabiensis, are on distant branches of the phylogenetic tree. However, DNA sequence data indicate that these two species are sister taxa and suggest gene flow between them. These results have important implications for malaria control strategies involving the replacement of vector with nonvector populations. Images PMID:8041714

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

The use of digital spaceborne SAR data for the delineation of surface features indicative of malaria vector breeding habitats

NASA Technical Reports Server (NTRS)

Imhoff, M. L.; Vermillion, C. H.; Khan, F. A.

1984-01-01

An investigation to examine the utility of spaceborne radar image data to malaria vector control programs is described. Specific tasks involve an analysis of radar illumination geometry vs information content, the synergy of radar and multispectral data mergers, and automated information extraction techniques.

Person Authentication Using Learned Parameters of Lifting Wavelet Filters

NASA Astrophysics Data System (ADS)

Niijima, Koichi

2006-10-01

This paper proposes a method for identifying persons by the use of the lifting wavelet parameters learned by kurtosis-minimization. Our learning method uses desirable properties of kurtosis and wavelet coefficients of a facial image. Exploiting these properties, the lifting parameters are trained so as to minimize the kurtosis of lifting wavelet coefficients computed for the facial image. Since this minimization problem is an ill-posed problem, it is solved by the aid of Tikhonov's regularization method. Our learning algorithm is applied to each of the faces to be identified to generate its feature vector whose components consist of the learned parameters. The constructed feature vectors are memorized together with the corresponding faces in a feature vectors database. Person authentication is performed by comparing the feature vector of a query face with those stored in the database. In numerical experiments, the lifting parameters are trained for each of the neutral faces of 132 persons (74 males and 58 females) in the AR face database. Person authentication is executed by using the smile and anger faces of the same persons in the database.

Multimodality imaging of reporter gene expression using a novel fusion vector in living cells and animals

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

Gambhir, Sanjiv; Pritha, Ray

Novel double and triple fusion reporter gene constructs harboring distinct imagable reporter genes are provided, as well as applications for the use of such double and triple fusion constructs in living cells and in living animals using distinct imaging technologies.

Multimodality imaging of reporter gene expression using a novel fusion vector in living cells and animals

DOEpatents

Gambhir, Sanjiv; Pritha, Ray

2015-07-14

Novel double and triple fusion reporter gene constructs harboring distinct imagable reporter genes are provided, as well as applications for the use of such double and triple fusion constructs in living cells and in living animals using distinct imaging technologies.

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

Shoaf, S.; APS Engineering Support Division

A real-time image analysis system was developed for beam imaging diagnostics. An Apple Power Mac G5 with an Active Silicon LFG frame grabber was used to capture video images that were processed and analyzed. Software routines were created to utilize vector-processing hardware to reduce the time to process images as compared to conventional methods. These improvements allow for more advanced image processing diagnostics to be performed in real time.

Short-interval SMS wind vector determinations for a severe local storms area

NASA Technical Reports Server (NTRS)

Peslen, C. A.

1980-01-01

Short-interval SMS-2 visible digital image data are used to derive wind vectors from cloud tracking on time-lapsed sequences of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on May 6, 1975 hail-producing thunderstorms occurred ahead of a well defined dry line. Cloud tracking is performed on the Goddard Space Flight Center Atmospheric and Oceanographic Information Processing System. Lower tropospheric cumulus tracers are selected with the assistance of a cloud-top height algorithm. Divergence is derived from the cloud motions using a modified Cressman (1959) objective analysis technique which is designed to organize irregularly spaced wind vectors into uniformly gridded wind fields. The results demonstrate the feasibility of using satellite-derived wind vectors and their associated divergence fields in describing the conditions preceding severe local storm development. For this case, an area of convergence appeared ahead of the dry line and coincided with the developing area of severe weather. The magnitude of the maximum convergence varied between -10 to the -5th and -10 to the -14th per sec. The number of satellite-derived wind vectors which were required to describe conditions of the low-level atmosphere was adequate before numerous cumulonimbus cells formed. This technique is limited in areas of advanced convection.

The effects of inhaled L-methamphetamine on athletic performance while riding a stationary bike: a randomised placebo-controlled trial.

PubMed

Dufka, F; Galloway, G; Baggott, M; Mendelson, J

2009-10-01

L-methamphetamine (the non-abused isomer of methamphetamine) is banned in athletic competition because it may improve athletic performance, but there are no studies assessing its effects on performance. In the United States L-methamphetamine is formulated in the non-prescription Vick's Vapor Inhaler (VVI) nasal decongestant. VVIs sold elsewhere (we used ones from the UK) contain similar inactive ingredients (menthol, camphor and Siberian pine oil) but no L-methamphetamine. This study tested the effects of inhaled L-methamphetamine delivered from a widely available non-prescription product on athletic performance. In a 2-session double-blind placebo-controlled study 12 participants (ages 14-17) were dosed with 4 (session 1) and 12 (session 2) inhalations from VVIs with (USA) or without (UK) L-methamphetamine and then performed two 20 minute rides on a stationary bike with rides separated by a 30 minute rest. The main outcome measure was miles travelled during each 20 minute ride. Secondary outcome measures included postride urine toxicology; heart rate and blood pressure before, 1, 5 and 10 minutes postride; energy, performance, endurance, and ability to breathe; and VVI preference. Data were analysed using Excel statistical macros. After approximately 16 microg L-methamphetamine distance travelled was 5.26 (SD 0.53) miles vs 5.30 (0.55) with placebo; p = 0.81. After approximately 48 microg L-methamphetamine distance travelled was 5.30 (0.51) vs 5.35 (0.43) with placebo; p = 0.85. The approximately 16 microg dose increased systolic blood pressure from 72.6 (4.3) to 79.6 (6.6) mm Hg (p = 0.03) at 5 minutes postride but there were no other differences in outcomes. Modest doses of inhaled L-methamphetamine probably do not improve athletic performance but do minimally raise diastolic blood pressure.

Importance of rate control or rate regulation for improving exercise capacity and quality of life in patients with permanent atrial fibrillation and normal left ventricular function: a randomised controlled study

PubMed Central

Levy, T; Walker, S; Mason, M; Spurrell, P; Rex, S; Brant, S; Paul, V

2001-01-01

OBJECTIVE—To determine the importance of rhythm regulation or rate control in patients with permanent atrial fibrillation (AF) and normal left ventricular function.
PATIENTS AND INTERVENTIONS—Thirty six patients with a mixed fast and slow ventricular response rate to their AF were randomised to either His bundle ablation (HBA) and VVIR pacemaker (HBA group) or VVI pacemaker and atrioventricular modifying drugs (Med group). Outcomes assessed at one, three, six, and 12 months included exercise duration and quality of life.
RESULTS—Exercise duration significantly improved from baseline in both groups. There was no difference in outcome between the groups (Med +40% v HBA +20%, p = NS). The heart rate profile on exercise was similarly slowed in both groups compared to baseline. Quality of life significantly improved in both treatment arms for the modified Karolinska questionnaire (KQ) (Med +50% v HBA +50%, p = NS) and the Nottingham health profile (NHP) (Med +40% v HBA +20%, p = NS). However, for the individual symptom scores of each questionnaire more were improved in the Med group (KQ-Med 6 improved v HBA 4, NHP-Med 3 v HBA 1). Left ventricular function was equally preserved by both treatments during follow up.
CONCLUSION—In these patients control of ventricular response rate with either HBA + VVIR pacemaker or atrioventricular modifying drugs + VVI pacemaker will lead to a significant improvement in exercise duration and quality of life. Rhythm regulation by HBA did not confer additional benefit, suggesting rate control alone is necessary for the successful symptomatic treatment of these patients in permanent AF.


Keywords: ablation; atrial fibrillation; pacemaker; atrioventricular modifying drugs PMID:11156667

Effects of cryogen spray cooling and high radiant exposures on selective vascular injury during laser irradiation of human skin.

PubMed

Tunnell, James W; Chang, David W; Johnston, Carol; Torres, Jorge H; Patrick, Charles W; Miller, Michael J; Thomsen, Sharon L; Anvari, Bahman

2003-06-01

Increasing radiant exposure offers a means to increase treatment efficacy during laser-mediated treatment of vascular lesions, such as port-wine stains; however, excessive radiant exposure decreases selective vascular injury due to increased heat generation within the epidermis and collateral damage to perivascular collagen. To determine if cryogen spray cooling could be used to maintain selective vascular injury (ie, prevent epidermal and perivascular collagen damage) when using high radiant exposures (16-30 J/cm2). Observational study. Academic hospital and research laboratory. Twenty women with normal abdominal skin (skin phototypes I-VI). Skin was irradiated with a pulsed dye laser (wavelength = 585 nm; pulse duration = 1.5 milliseconds; 5-mm-diameter spot) using various radiant exposures (8-30 J/cm2) without and with cryogen spray cooling (50- to 300-millisecond cryogen spurts). Hematoxylin-eosin-stained histologic sections from each irradiated site were examined for the degree of epidermal damage, maximum depth of red blood cell coagulation, and percentage of vessels containing perivascular collagen coagulation. Long cryogen spurt durations (>200 milliseconds) protected the epidermis in light-skinned individuals (skin phototypes I-IV) at the highest radiant exposure (30 J/cm2); however, epidermal protection could not be achieved in dark-skinned individuals (skin phototypes V-VI) even at the lowest radiant exposure (8 J/cm2). The red blood cell coagulation depth increased with increasing radiant exposure (to >2.5 mm for skin phototypes I-IV and to approximately 1.2 mm for skin phototypes V-VI). In addition, long cryogen spurt durations (>200 milliseconds) prevented perivascular collagen coagulation in all skin types. Cryogen spurt durations much longer than those currently used in therapy (>200 milliseconds) may be clinically useful for protecting the epidermis and perivascular tissues when using high radiant exposures during cutaneous laser therapies. Additional studies are necessary to prove clinical safety of these protocols.

Intermittent pacemaker dysfunction caused by digital mobile telephones.

PubMed

Naegeli, B; Osswald, S; Deola, M; Burkart, F

1996-05-01

This study was designed to evaluate possible interactions between digital mobile telephones and implanted pacemakers. Electromagnetic fields may interfere with normal pacemaker function. Development of bipolar sensing leads and modern noise filtering techniques have lessened this problem. However, it remains unclear whether these features also protect from high frequency noise arising from digital cellular phones. In 39 patients with an implanted pacemaker (14 dual-chamber [DDD], 8 atrial-synchronized ventricular-inhibited [VDD(R)] and 17 ventricular-inhibited [VVI(R)] pacemakers), four mobile phones with different levels of power output (2 and 8 W) were tested in the standby, dialing and operating mode. During continuous electrocardiographic monitoring, 672 tests were performed in each mode with the phones positioned over the pulse generator, the atrial and the ventricular electrode tip. The tests were carried out at different sensitivity settings and, where possible, in the unipolar and bipolar pacing modes as well. In 7 (18%) of 39 patients, a reproducible interference was induced during 26 (3.9%) of 672 tests with the operating phones in close proximity (<10 cm) to the pacemaker. In 22 dual-chamber (14 DDD, 8 VDD) pacemakers, atrial triggering occurred in 7 (2.8%) of 248 and ventricular inhibition in 5 (2.8%) of 176 tests. In 17 VVI(R) systems, pacemaker inhibition was induced in 14 (5.6%) of 248 tests. Interference was more likely to occur at higher power output of the phone and at maximal sensitivity of the pacemakers (maximal vs. nominal sensitivity, 6% vs. 1.8% positive test results, p = 0.009). When the bipolar and unipolar pacing modes were compared in the same patients, ventricular inhibition was induced only in the unipolar mode (12.5% positive test results, p = 0.0003). Digital mobile phones in close proximity to implanted pacemakers may cause intermittent pacemaker dysfunction with inappropriate ventricular tracking and potentially dangerous pacemaker inhibition.

Length of Acupuncture Training and Structural Plastic Brain Changes in Professional Acupuncturists

PubMed Central

Dong, Minghao; Zhao, Ling; Yuan, Kai; Zeng, Fang; Sun, Jinbo; Liu, Jixin; Yu, Dahua; von Deneen, Karen M.; Liang, Fanrong; Qin, Wei; Tian, Jie

2013-01-01

Background The research on brain plasticity has fascinated researchers for decades. Use/training serves as an instrumental factor to influence brain neuroplasticity. Parallel to acquisition of behavioral expertise, extensive use/training is concomitant with substantial changes of cortical structure. Acupuncturists, serving as a model par excellence to study tactile-motor and emotional regulation plasticity, receive intensive training in national medical schools following standardized training protocol. Moreover, their behavioral expertise is corroborated during long-term clinical practice. Although our previous study reported functional plastic brain changes in the acupuncturists, whether or not structural plastic changes occurred in acupuncturists is yet elusive. Methodology/Principal Findings Cohorts of acupuncturists (N = 22) and non-acupuncturists (N = 22) were recruited. Behavioral tests were delivered to assess the acupuncturists’ behavioral expertise. The results confirmed acupuncturists’ tactile-motor skills and emotion regulation proficiency compared to non-acupuncturists. Using the voxel-based morphometry technique, we revealed larger grey matter volumes in acupuncturists in the hand representation of the contralateral primary somatosensory cortex (SI), the right lobule V/VI and the bilateral ventral anterior cingulate cortex/ventral medial prefrontal cortex. Grey matter volumes of the SI and Lobule V/VI positively correlated with the duration of acupuncture practice. Conclusions To our best knowledge, this study provides first evidence for the anatomical alterations in acupuncturists, which would possibly be the neural correlates underlying acupuncturists’ exceptional skills. On one hand, we suggest our findings may have ramifications for tactile-motor rehabilitation. On the other hand, our results in emotion regulation domain may serve as a target for our future studies, from which we can understand how modulations of aversive emotions elicited by empathic pain develop in the context of expertise. Future longitudinal study is necessary to establish the presence and direction of a causal link between practice/use and brain anatomy. PMID:23840505

A Fast SVM-Based Tongue's Colour Classification Aided by k-Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis.

PubMed

Kamarudin, Nur Diyana; Ooi, Chia Yee; Kawanabe, Tadaaki; Odaguchi, Hiroshi; Kobayashi, Fuminori

2017-01-01

In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k -means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k -means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds.

Speech Signal and Facial Image Processing for Obstructive Sleep Apnea Assessment

PubMed Central

Espinoza-Cuadros, Fernando; Fernández-Pozo, Rubén; Toledano, Doroteo T.; Alcázar-Ramírez, José D.; López-Gonzalo, Eduardo; Hernández-Gómez, Luis A.

2015-01-01

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). OSA is generally diagnosed through a costly procedure requiring an overnight stay of the patient at the hospital. This has led to proposing less costly procedures based on the analysis of patients' facial images and voice recordings to help in OSA detection and severity assessment. In this paper we investigate the use of both image and speech processing to estimate the apnea-hypopnea index, AHI (which describes the severity of the condition), over a population of 285 male Spanish subjects suspected to suffer from OSA and referred to a Sleep Disorders Unit. Photographs and voice recordings were collected in a supervised but not highly controlled way trying to test a scenario close to an OSA assessment application running on a mobile device (i.e., smartphones or tablets). Spectral information in speech utterances is modeled by a state-of-the-art low-dimensional acoustic representation, called i-vector. A set of local craniofacial features related to OSA are extracted from images after detecting facial landmarks using Active Appearance Models (AAMs). Support vector regression (SVR) is applied on facial features and i-vectors to estimate the AHI. PMID:26664493

Speech Signal and Facial Image Processing for Obstructive Sleep Apnea Assessment.

PubMed

Espinoza-Cuadros, Fernando; Fernández-Pozo, Rubén; Toledano, Doroteo T; Alcázar-Ramírez, José D; López-Gonzalo, Eduardo; Hernández-Gómez, Luis A

2015-01-01

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). OSA is generally diagnosed through a costly procedure requiring an overnight stay of the patient at the hospital. This has led to proposing less costly procedures based on the analysis of patients' facial images and voice recordings to help in OSA detection and severity assessment. In this paper we investigate the use of both image and speech processing to estimate the apnea-hypopnea index, AHI (which describes the severity of the condition), over a population of 285 male Spanish subjects suspected to suffer from OSA and referred to a Sleep Disorders Unit. Photographs and voice recordings were collected in a supervised but not highly controlled way trying to test a scenario close to an OSA assessment application running on a mobile device (i.e., smartphones or tablets). Spectral information in speech utterances is modeled by a state-of-the-art low-dimensional acoustic representation, called i-vector. A set of local craniofacial features related to OSA are extracted from images after detecting facial landmarks using Active Appearance Models (AAMs). Support vector regression (SVR) is applied on facial features and i-vectors to estimate the AHI.

A Fast SVM-Based Tongue's Colour Classification Aided by k-Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis

PubMed Central

Ooi, Chia Yee; Kawanabe, Tadaaki; Odaguchi, Hiroshi; Kobayashi, Fuminori

2017-01-01

In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k-means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k-means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds. PMID:29065640

Time-Dependent Stochastic Inversion in Acoustic Tomography of the Atmosphere with Reciprocal Sound Transmission

DTIC Science & Technology

2008-10-17

R E 1960 A new approach to linear filtering and prediction problems Trans. ASME D 82 35–45 [23] Brown R G and Hwang Y C 1992 Introduction to Random...vector Wiener filter [21]. TDSI is also somewhat similar to the Kalman filter [22, 23] which is applied in many areas including tomography [24–27]. The...453–76 [21] Links J M, Prince J L and Gupta S N 1996 A vector Wiener filter for dual-radionuclide imaging IEEE Trans. Med. Imaging 15 700–9 [22] Kalman

Vector and Raster Data Storage Based on Morton Code

NASA Astrophysics Data System (ADS)

Zhou, G.; Pan, Q.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Liu, X.

2018-05-01

Even though geomatique is so developed nowadays, the integration of spatial data in vector and raster formats is still a very tricky problem in geographic information system environment. And there is still not a proper way to solve the problem. This article proposes a method to interpret vector data and raster data. In this paper, we saved the image data and building vector data of Guilin University of Technology to Oracle database. Then we use ADO interface to connect database to Visual C++ and convert row and column numbers of raster data and X Y of vector data to Morton code in Visual C++ environment. This method stores vector and raster data to Oracle Database and uses Morton code instead of row and column and X Y to mark the position information of vector and raster data. Using Morton code to mark geographic information enables storage of data make full use of storage space, simultaneous analysis of vector and raster data more efficient and visualization of vector and raster more intuitive. This method is very helpful for some situations that need to analyse or display vector data and raster data at the same time.

A system for verifying models and classification maps by extraction of information from a variety of data sources

NASA Technical Reports Server (NTRS)

Norikane, L.; Freeman, A.; Way, J.; Okonek, S.; Casey, R.

1992-01-01

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

Image size invariant visual cryptography for general access structures subject to display quality constraints.

PubMed

Lee, Kai-Hui; Chiu, Pei-Ling

2013-10-01

Conventional visual cryptography (VC) suffers from a pixel-expansion problem, or an uncontrollable display quality problem for recovered images, and lacks a general approach to construct visual secret sharing schemes for general access structures. We propose a general and systematic approach to address these issues without sophisticated codebook design. This approach can be used for binary secret images in non-computer-aided decryption environments. To avoid pixel expansion, we design a set of column vectors to encrypt secret pixels rather than using the conventional VC-based approach. We begin by formulating a mathematic model for the VC construction problem to find the column vectors for the optimal VC construction, after which we develop a simulated-annealing-based algorithm to solve the problem. The experimental results show that the display quality of the recovered image is superior to that of previous papers.

Automated metastatic brain lesion detection: a computer aided diagnostic and clinical research tool

NASA Astrophysics Data System (ADS)

Devine, Jeremy; Sahgal, Arjun; Karam, Irene; Martel, Anne L.

2016-03-01

The accurate localization of brain metastases in magnetic resonance (MR) images is crucial for patients undergoing stereotactic radiosurgery (SRS) to ensure that all neoplastic foci are targeted. Computer automated tumor localization and analysis can improve both of these tasks by eliminating inter and intra-observer variations during the MR image reading process. Lesion localization is accomplished using adaptive thresholding to extract enhancing objects. Each enhancing object is represented as a vector of features which includes information on object size, symmetry, position, shape, and context. These vectors are then used to train a random forest classifier. We trained and tested the image analysis pipeline on 3D axial contrast-enhanced MR images with the intention of localizing the brain metastases. In our cross validation study and at the most effective algorithm operating point, we were able to identify 90% of the lesions at a precision rate of 60%.

Unsupervised color image segmentation using a lattice algebra clustering technique

NASA Astrophysics Data System (ADS)

Urcid, Gonzalo; Ritter, Gerhard X.

2011-08-01

In this paper we introduce a lattice algebra clustering technique for segmenting digital images in the Red-Green- Blue (RGB) color space. The proposed technique is a two step procedure. Given an input color image, the first step determines the finite set of its extreme pixel vectors within the color cube by means of the scaled min-W and max-M lattice auto-associative memory matrices, including the minimum and maximum vector bounds. In the second step, maximal rectangular boxes enclosing each extreme color pixel are found using the Chebychev distance between color pixels; afterwards, clustering is performed by assigning each image pixel to its corresponding maximal box. The two steps in our proposed method are completely unsupervised or autonomous. Illustrative examples are provided to demonstrate the color segmentation results including a brief numerical comparison with two other non-maximal variations of the same clustering technique.

Effective 2D-3D medical image registration using Support Vector Machine.

PubMed

Qi, Wenyuan; Gu, Lixu; Zhao, Qiang

2008-01-01

Registration of pre-operative 3D volume dataset and intra-operative 2D images gradually becomes an important technique to assist radiologists in diagnosing complicated diseases easily and quickly. In this paper, we proposed a novel 2D/3D registration framework based on Support Vector Machine (SVM) to compensate the disadvantages of generating large number of DRR images in the stage of intra-operation. Estimated similarity metric distribution could be built up from the relationship between parameters of transform and prior sparse target metric values by means of SVR method. Based on which, global optimal parameters of transform are finally searched out by an optimizer in order to guide 3D volume dataset to match intra-operative 2D image. Experiments reveal that our proposed registration method improved performance compared to conventional registration method and also provided a precise registration result efficiently.

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

NASA Astrophysics Data System (ADS)

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

2008-02-01

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

Elimination of projection effects from vector magnetograms - The pre-flare configuration of active region AR 4474

NASA Technical Reports Server (NTRS)

Venkatakrishnan, P.; Hagyard, M. J.; Hathaway, D. H.

1988-01-01

A simple method of transforming vector magnetograms to heliographic coordinates is demonstrated. The merits of this transformation are illustrated using a vector magnetogram obtained with the MSFC vector magnetograph 80 minutes prior to a white light flare in active region AR 4474 on April 25, 1984. The original magnetogram shows strong magnetic shear along the neutral line at both the flare site and a nonflaring site. The transformation of the magnetogram to heliographic coordinates shows that the elimination of projection effects results in a much shorter length of the sheared region at the nonflaring site than what is inferred from the image plane vector magnetogram. The length of the sheared region at the flare site is relatively less affected by the transformation.

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Invariant correlation to position and rotation using a binary mask applied to binary and gray images

NASA Astrophysics Data System (ADS)

Álvarez-Borrego, Josué; Solorza, Selene; Bueno-Ibarra, Mario A.

2013-05-01

In this paper more alternative ways to generate the binary ring masks are studied and a new methodology is presented when in the analysis the image come with some distortion due to rotation. This new algorithm requires low computational cost. Signature vectors of the target so like signature vectors of the object to be recognized in the problem image are obtained using a binary ring mask constructed in accordance with the real or the imaginary part of their Fourier transform analyzing two different conditions in each one. In this manner, each image target or problem image, will have four unique binary ring masks. The four ways are analyzed and the best is chosen. In addition, due to any image with rotation include some distortion, the best transect is chosen in the Fourier plane in order to obtain the best signature through the different ways to obtain the binary mask. This methodology is applied to two cases: to identify different types of alphabetic letters in Arial font and to identify different fossil diatoms images. Considering the great similarity between diatom images the results obtained are excellent.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Object-Based Change Detection Using High-Resolution Remotely Sensed Data and GIS

NASA Astrophysics Data System (ADS)

Sofina, N.; Ehlers, M.

2012-08-01

High resolution remotely sensed images provide current, detailed, and accurate information for large areas of the earth surface which can be used for change detection analyses. Conventional methods of image processing permit detection of changes by comparing remotely sensed multitemporal images. However, for performing a successful analysis it is desirable to take images from the same sensor which should be acquired at the same time of season, at the same time of a day, and - for electro-optical sensors - in cloudless conditions. Thus, a change detection analysis could be problematic especially for sudden catastrophic events. A promising alternative is the use of vector-based maps containing information about the original urban layout which can be related to a single image obtained after the catastrophe. The paper describes a methodology for an object-based search of destroyed buildings as a consequence of a natural or man-made catastrophe (e.g., earthquakes, flooding, civil war). The analysis is based on remotely sensed and vector GIS data. It includes three main steps: (i) generation of features describing the state of buildings; (ii) classification of building conditions; and (iii) data import into a GIS. One of the proposed features is a newly developed 'Detected Part of Contour' (DPC). Additionally, several features based on the analysis of textural information corresponding to the investigated vector objects are calculated. The method is applied to remotely sensed images of areas that have been subjected to an earthquake. The results show the high reliability of the DPC feature as an indicator for change.

Volumetric image classification using homogeneous decomposition and dictionary learning: A study using retinal optical coherence tomography for detecting age-related macular degeneration.

PubMed

Albarrak, Abdulrahman; Coenen, Frans; Zheng, Yalin

2017-01-01

Three-dimensional (3D) (volumetric) diagnostic imaging techniques are indispensable with respect to the diagnosis and management of many medical conditions. However there is a lack of automated diagnosis techniques to facilitate such 3D image analysis (although some support tools do exist). This paper proposes a novel framework for volumetric medical image classification founded on homogeneous decomposition and dictionary learning. In the proposed framework each image (volume) is recursively decomposed until homogeneous regions are arrived at. Each region is represented using a Histogram of Oriented Gradients (HOG) which is transformed into a set of feature vectors. The Gaussian Mixture Model (GMM) is then used to generate a "dictionary" and the Improved Fisher Kernel (IFK) approach is used to encode feature vectors so as to generate a single feature vector for each volume, which can then be fed into a classifier generator. The principal advantage offered by the framework is that it does not require the detection (segmentation) of specific objects within the input data. The nature of the framework is fully described. A wide range of experiments was conducted with which to analyse the operation of the proposed framework and these are also reported fully in the paper. Although the proposed approach is generally applicable to 3D volumetric images, the focus for the work is 3D retinal Optical Coherence Tomography (OCT) images in the context of the diagnosis of Age-related Macular Degeneration (AMD). The results indicate that excellent diagnostic predictions can be produced using the proposed framework. Copyright © 2016 Elsevier Ltd. All rights reserved.

Accurate shade image matching by using a smartphone camera.

PubMed

Tam, Weng-Kong; Lee, Hsi-Jian

2017-04-01

Dental shade matching by using digital images may be feasible when suitable color features are properly manipulated. Separating the color features into feature spaces facilitates favorable matching. We propose using support vector machines (SVM), which are outstanding classifiers, in shade classification. A total of 1300 shade tab images were captured using a smartphone camera with auto-mode settings and no flash. The images were shot at angled distances of 14-20cm from a shade guide at a clinic equipped with light tubes that produced a 4000K color temperature. The Group 1 samples comprised 1040 tab images, for which the shade guide was randomly positioned in the clinic, and the Group 2 samples comprised 260 tab images, for which the shade guide had a fixed position in the clinic. Rectangular content was cropped manually on each shade tab image and further divided into 10×2 blocks. The color features extracted from the blocks were described using a feature vector. The feature vectors in each group underwent SVM training and classification by using the "leave-one-out" strategy. The top one and three accuracies of Group 1 were 0.86 and 0.98, respectively, and those of Group 2 were 0.97 and 1.00, respectively. This study provides a feasible technique for dental shade classification that uses the camera of a mobile device. The findings reveal that the proposed SVM classification might outperform the shade-matching results of previous studies that have performed similarity measurements of ΔE levels or used an S, a*, b* feature set. Copyright © 2016 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Studies on image compression and image reconstruction

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Nori, Sekhar; Araj, A.

1994-01-01

During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

Parallel algorithm for determining motion vectors in ice floe images by matching edge features

NASA Technical Reports Server (NTRS)

Manohar, M.; Ramapriyan, H. K.; Strong, J. P.

1988-01-01

A parallel algorithm is described to determine motion vectors of ice floes using time sequences of images of the Arctic ocean obtained from the Synthetic Aperture Radar (SAR) instrument flown on-board the SEASAT spacecraft. Researchers describe a parallel algorithm which is implemented on the MPP for locating corresponding objects based on their translationally and rotationally invariant features. The algorithm first approximates the edges in the images by polygons or sets of connected straight-line segments. Each such edge structure is then reduced to a seed point. Associated with each seed point are the descriptions (lengths, orientations and sequence numbers) of the lines constituting the corresponding edge structure. A parallel matching algorithm is used to match packed arrays of such descriptions to identify corresponding seed points in the two images. The matching algorithm is designed such that fragmentation and merging of ice floes are taken into account by accepting partial matches. The technique has been demonstrated to work on synthetic test patterns and real image pairs from SEASAT in times ranging from .5 to 0.7 seconds for 128 x 128 images.

Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

NASA Astrophysics Data System (ADS)

Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

2017-12-01

In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

Ischemic stroke lesion segmentation in multi-spectral MR images with support vector machine classifiers

NASA Astrophysics Data System (ADS)

Maier, Oskar; Wilms, Matthias; von der Gablentz, Janina; Krämer, Ulrike; Handels, Heinz

2014-03-01

Automatic segmentation of ischemic stroke lesions in magnetic resonance (MR) images is important in clinical practice and for neuroscientific trials. The key problem is to detect largely inhomogeneous regions of varying sizes, shapes and locations. We present a stroke lesion segmentation method based on local features extracted from multi-spectral MR data that are selected to model a human observer's discrimination criteria. A support vector machine classifier is trained on expert-segmented examples and then used to classify formerly unseen images. Leave-one-out cross validation on eight datasets with lesions of varying appearances is performed, showing our method to compare favourably with other published approaches in terms of accuracy and robustness. Furthermore, we compare a number of feature selectors and closely examine each feature's and MR sequence's contribution.

LCD motion blur reduction: a signal processing approach.

PubMed

Har-Noy, Shay; Nguyen, Truong Q

2008-02-01

Liquid crystal displays (LCDs) have shown great promise in the consumer market for their use as both computer and television displays. Despite their many advantages, the inherent sample-and-hold nature of LCD image formation results in a phenomenon known as motion blur. In this work, we develop a method for motion blur reduction using the Richardson-Lucy deconvolution algorithm in concert with motion vector information from the scene. We further refine our approach by introducing a perceptual significance metric that allows us to weight the amount of processing performed on different regions in the image. In addition, we analyze the role of motion vector errors in the quality of our resulting image. Perceptual tests indicate that our algorithm reduces the amount of perceivable motion blur in LCDs.

Defining the Hook Region Anatomy of the Guinea Pig Cochlea for Modeling of Inner Ear Surgery.

PubMed

Lo, Jonathon; Sale, Phillip; Wijewickrema, Sudanthi; Campbell, Luke; Eastwood, Hayden; O'leary, Stephen John

2017-07-01

The aim of this study was to describe the hook region anatomy of the guinea pig cochlea to identify the optimal surgical approach for cochlear implantation and to determine what anatomical structures are at risk. Animal studies investigating hearing loss after cochlear implantation surgery are currently constrained by the lack of a reproducible implantation model. Guinea pig cochleae were imaged using thin-sheet laser imaging microscopy. Images were stitched, reconstructed, and segmented for analysis. Insertion vectors were determined by tracing their paths to the outer wall and converting to Cartesian coordinates. Spherical surface and multiplane views were generated to analyze outer wall and radial forces of the insertion vector. Thin-sheet laser imaging microscopy enabled quantitative, whole specimen analysis of the soft and bony tissue relationships of the complex cochlear hook region in any desired plane without loss of image quality. Round window or cochleostomy approaches in the anteroinferior plane avoided direct damage to cochlear structures. Cochleostomy approach had large interindividual variability of angular depth and outer wall forces but predictable radial force. The guinea pig hook region and lower basal turn have similar structural relationships to humans. Careful cochleostomy placement is essentially for minimizing cochlear trauma and for ensuring a straight insertion vector that successfully advances around the outer wall. Experiments with guinea pigs that control for the surgical approach are likely to provide useful insights into the aetiology and the development of therapies directed at postimplantation hearing loss.

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

The Support Vector Machine is a powerful algorithm, useful in classifying data in to species. The Support Vector Machines implemented in this research were used as classifiers for the final stage in a Multistage Autonomous Target Recognition system. A single kernel SVM known as SVMlight, and a modified version known as a Support Vector Machine with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SMV as a method for classification. From trial to trial, SVM produces consistent results

Rate-dependent Loss of Capture during Ventricular Pacing.

PubMed

Wang, Jingfeng; Chen, Haiyan; Su, Yangang; Ge, Junbo

2015-01-01

A 63-year-old patient who had undergone atrial septal defect surgical repair received implantation of a single chamber VVI pacemaker for long RR intervals during atrial fibrillation. One week later, an intermittent loss of capture and sensing failure was detected at a pacing rate of 70 beats/min. However, a successful capture was observed during rapid pacing. Consequently, the pacing rate was temporarily adjusted to 90 beats/min. At the 3-month follow-up, the pacemaker was shown to be functioning properly independent of the pacing rate. An echocardiogram showed that the increased pacing rates were accompanied by a reduction in the right ventricular outflow tract dimension. The pacemaker was then permanently programmed at a lower rate of 60 beats/min.

Crystal structure of p44, a constitutively active splice variant of visual arrestin.

PubMed

Granzin, Joachim; Cousin, Anneliese; Weirauch, Moritz; Schlesinger, Ramona; Büldt, Georg; Batra-Safferling, Renu

2012-03-09

Visual arrestin specifically binds to photoactivated and phosphorylated rhodopsin and inactivates phototransduction. In contrast, the p44 splice variant can terminate phototransduction by binding to nonphosphorylated light-activated rhodopsin. Here we report the crystal structure of bovine p44 at a resolution of 1.85 Å. Compared to native arrestin, the p44 structure reveals significant differences in regions crucial for receptor binding, namely flexible loop V-VI and polar core regions. Additionally, electrostatic potential is remarkably positive on the N-domain and the C-domain. The p44 structure represents an active conformation that serves as a model to explain the 'constitutive activity' found in arrestin variants. Copyright © 2012 Elsevier Ltd. All rights reserved.

Peculiar liquid-feeding and pathogen transmission behavior of Aedes togoi and comparison with Anopheles sinensis.

PubMed

Lee, Sang Joon; Kang, Dooho; Lee, Seung Chul; Ha, Young-Ran

2016-02-03

Female mosquitoes transmit various diseases as vectors during liquid-feeding. Identifying the determinants of vector efficiency is a major scientific challenge in establishing strategies against these diseases. Infection rate and transmission efficiency are interconnected with the mosquito-induced liquid-feeding flow as main indexes of vector efficiency. However, the relationship between liquid-feeding characteristics and pathogen remains poorly understood. The liquid-feeding behavior of Aedes togoi and Anopheles sinensis was comparatively investigated in conjunction with vector efficiency via micro-particle image velocimetry. The flow rates and ratio of the ejection volume of Aedes togoi were markedly higher than those of Anophels sinensis. These differences would influence pathogen re-ingestion. Wall shear stresses of these mosquito species were also clearly discriminatory affecting the infective rates of vector-borne diseases. The variations in volume of two pump chambers and diameter of proboscis of these mosquito species were compared to determine the differences in the liquid-feeding process. Liquid-feeding characteristics influence vector efficiency; hence, this study can elucidate the vector efficiency of mosquitoes and the vector-pathogen interactions and contribute to the development of strategies against vector-borne diseases.

Peculiar liquid-feeding and pathogen transmission behavior of Aedes togoi and comparison with Anopheles sinensis

NASA Astrophysics Data System (ADS)

Lee, Sang Joon; Kang, Dooho; Lee, Seung Chul; Ha, Young-Ran

2016-02-01

Female mosquitoes transmit various diseases as vectors during liquid-feeding. Identifying the determinants of vector efficiency is a major scientific challenge in establishing strategies against these diseases. Infection rate and transmission efficiency are interconnected with the mosquito-induced liquid-feeding flow as main indexes of vector efficiency. However, the relationship between liquid-feeding characteristics and pathogen remains poorly understood. The liquid-feeding behavior of Aedes togoi and Anopheles sinensis was comparatively investigated in conjunction with vector efficiency via micro-particle image velocimetry. The flow rates and ratio of the ejection volume of Aedes togoi were markedly higher than those of Anophels sinensis. These differences would influence pathogen re-ingestion. Wall shear stresses of these mosquito species were also clearly discriminatory affecting the infective rates of vector-borne diseases. The variations in volume of two pump chambers and diameter of proboscis of these mosquito species were compared to determine the differences in the liquid-feeding process. Liquid-feeding characteristics influence vector efficiency; hence, this study can elucidate the vector efficiency of mosquitoes and the vector-pathogen interactions and contribute to the development of strategies against vector-borne diseases.

[Image processing applying in analysis of motion features of cultured cardiac myocyte in rat].

PubMed

Teng, Qizhi; He, Xiaohai; Luo, Daisheng; Wang, Zhengrong; Zhou, Beiyi; Yuan, Zhirun; Tao, Dachang

2007-02-01

Study of mechanism of medicine actions, by quantitative analysis of cultured cardiac myocyte, is one of the cutting edge researches in myocyte dynamics and molecular biology. The characteristics of cardiac myocyte auto-beating without external stimulation make the research sense. Research of the morphology and cardiac myocyte motion using image analysis can reveal the fundamental mechanism of medical actions, increase the accuracy of medicine filtering, and design the optimal formula of medicine for best medical treatments. A system of hardware and software has been built with complete sets of functions including living cardiac myocyte image acquisition, image processing, motion image analysis, and image recognition. In this paper, theories and approaches are introduced for analysis of living cardiac myocyte motion images and implementing quantitative analysis of cardiac myocyte features. A motion estimation algorithm is used for motion vector detection of particular points and amplitude and frequency detection of a cardiac myocyte. Beatings of cardiac myocytes are sometimes very small. In such case, it is difficult to detect the motion vectors from the particular points in a time sequence of images. For this reason, an image correlation theory is employed to detect the beating frequencies. Active contour algorithm in terms of energy function is proposed to approximate the boundary and detect the changes of edge of myocyte.

Volume Segmentation and Ghost Particles

NASA Astrophysics Data System (ADS)

Ziskin, Isaac; Adrian, Ronald

2011-11-01

Volume Segmentation Tomographic PIV (VS-TPIV) is a type of tomographic PIV in which images of particles in a relatively thick volume are segmented into images on a set of much thinner volumes that may be approximated as planes, as in 2D planar PIV. The planes of images can be analysed by standard mono-PIV, and the volume of flow vectors can be recreated by assembling the planes of vectors. The interrogation process is similar to a Holographic PIV analysis, except that the planes of image data are extracted from two-dimensional camera images of the volume of particles instead of three-dimensional holographic images. Like the tomographic PIV method using the MART algorithm, Volume Segmentation requires at least two cameras and works best with three or four. Unlike the MART method, Volume Segmentation does not require reconstruction of individual particle images one pixel at a time and it does not require an iterative process, so it operates much faster. As in all tomographic reconstruction strategies, ambiguities known as ghost particles are produced in the segmentation process. The effect of these ghost particles on the PIV measurement is discussed. This research was supported by Contract 79419-001-09, Los Alamos National Laboratory.

Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

PubMed

Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

2017-09-01

In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

Development of an ultralow-light-level luminescence image analysis system for dynamic measurements of transcriptional activity in living and migrating cells.

PubMed

Maire, E; Lelièvre, E; Brau, D; Lyons, A; Woodward, M; Fafeur, V; Vandenbunder, B

2000-04-10

We have developed an approach to study in single living epithelial cells both cell migration and transcriptional activation, which was evidenced by the detection of luminescence emission from cells transfected with luciferase reporter vectors. The image acquisition chain consists of an epifluorescence inverted microscope, connected to an ultralow-light-level photon-counting camera and an image-acquisition card associated to specialized image analysis software running on a PC computer. Using a simple method based on a thin calibrated light source, the image acquisition chain has been optimized following comparisons of the performance of microscopy objectives and photon-counting cameras designed to observe luminescence. This setup allows us to measure by image analysis the luminescent light emitted by individual cells stably expressing a luciferase reporter vector. The sensitivity of the camera was adjusted to a high value, which required the use of a segmentation algorithm to eliminate the background noise. Following mathematical morphology treatments, kinetic changes of luminescent sources were analyzed and then correlated with the distance and speed of migration. Our results highlight the usefulness of our image acquisition chain and mathematical morphology software to quantify the kinetics of luminescence changes in migrating cells.

Discriminative Dictionary Learning With Two-Level Low Rank and Group Sparse Decomposition for Image Classification.

PubMed

Wen, Zaidao; Hou, Zaidao; Jiao, Licheng

2017-11-01

Discriminative dictionary learning (DDL) framework has been widely used in image classification which aims to learn some class-specific feature vectors as well as a representative dictionary according to a set of labeled training samples. However, interclass similarities and intraclass variances among input samples and learned features will generally weaken the representability of dictionary and the discrimination of feature vectors so as to degrade the classification performance. Therefore, how to explicitly represent them becomes an important issue. In this paper, we present a novel DDL framework with two-level low rank and group sparse decomposition model. In the first level, we learn a class-shared and several class-specific dictionaries, where a low rank and a group sparse regularization are, respectively, imposed on the corresponding feature matrices. In the second level, the class-specific feature matrix will be further decomposed into a low rank and a sparse matrix so that intraclass variances can be separated to concentrate the corresponding feature vectors. Extensive experimental results demonstrate the effectiveness of our model. Compared with the other state-of-the-arts on several popular image databases, our model can achieve a competitive or better performance in terms of the classification accuracy.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Overview and Performance

NASA Astrophysics Data System (ADS)

Hoeksema, J. Todd; Liu, Yang; Hayashi, Keiji; Sun, Xudong; Schou, Jesper; Couvidat, Sebastien; Norton, Aimee; Bobra, Monica; Centeno, Rebecca; Leka, K. D.; Barnes, Graham; Turmon, Michael

2014-09-01

The Helioseismic and Magnetic Imager (HMI) began near-continuous full-disk solar measurements on 1 May 2010 from the Solar Dynamics Observatory (SDO). An automated processing pipeline keeps pace with observations to produce observable quantities, including the photospheric vector magnetic field, from sequences of filtergrams. The basic vector-field frame list cadence is 135 seconds, but to reduce noise the filtergrams are combined to derive data products every 720 seconds. The primary 720 s observables were released in mid-2010, including Stokes polarization parameters measured at six wavelengths, as well as intensity, Doppler velocity, and the line-of-sight magnetic field. More advanced products, including the full vector magnetic field, are now available. Automatically identified HMI Active Region Patches (HARPs) track the location and shape of magnetic regions throughout their lifetime. The vector field is computed using the Very Fast Inversion of the Stokes Vector (VFISV) code optimized for the HMI pipeline; the remaining 180∘ azimuth ambiguity is resolved with the Minimum Energy (ME0) code. The Milne-Eddington inversion is performed on all full-disk HMI observations. The disambiguation, until recently run only on HARP regions, is now implemented for the full disk. Vector and scalar quantities in the patches are used to derive active region indices potentially useful for forecasting; the data maps and indices are collected in the SHARP data series, hmi.sharp_720s. Definitive SHARP processing is completed only after the region rotates off the visible disk; quick-look products are produced in near real time. Patches are provided in both CCD and heliographic coordinates. HMI provides continuous coverage of the vector field, but has modest spatial, spectral, and temporal resolution. Coupled with limitations of the analysis and interpretation techniques, effects of the orbital velocity, and instrument performance, the resulting measurements have a certain dynamic range and sensitivity and are subject to systematic errors and uncertainties that are characterized in this report.

Few-layer nanoplates of Bi 2 Se 3 and Bi 2 Te 3 with highly tunable chemical potential.

PubMed

Kong, Desheng; Dang, Wenhui; Cha, Judy J; Li, Hui; Meister, Stefan; Peng, Hailin; Liu, Zhongfan; Cui, Yi

2010-06-09

A topological insulator (TI) represents an unconventional quantum phase of matter with insulating bulk band gap and metallic surface states. Recent theoretical calculations and photoemission spectroscopy measurements show that group V-VI materials Bi(2)Se(3), Bi(2)Te(3), and Sb(2)Te(3) are TIs with a single Dirac cone on the surface. These materials have anisotropic, layered structures, in which five atomic layers are covalently bonded to form a quintuple layer, and quintuple layers interact weakly through van der Waals interaction to form the crystal. A few quintuple layers of these materials are predicted to exhibit interesting surface properties. Different from our previous nanoribbon study, here we report the synthesis and characterizations of ultrathin Bi(2)Te(3) and Bi(2)Se(3) nanoplates with thickness down to 3 nm (3 quintuple layers), via catalyst-free vapor-solid (VS) growth mechanism. Optical images reveal thickness-dependent color and contrast for nanoplates grown on oxidized silicon (300 nm SiO(2)/Si). As a new member of TI nanomaterials, ultrathin TI nanoplates have an extremely large surface-to-volume ratio and can be electrically gated more effectively than the bulk form, potentially enhancing surface state effects in transport measurements. Low-temperature transport measurements of a single nanoplate device, with a high-k dielectric top gate, show decrease in carrier concentration by several times and large tuning of chemical potential.

Spanish Pacemaker Registry. Twelfth Official Report of the Spanish Society of Cardiology Working Group on Cardiac Pacing (2014).

PubMed

Cano Pérez, Óscar; Pombo Jiménez, Marta; Coma Samartín, Raúl

2015-12-01

This report describes the results of the analysis of pacemaker implant and replacement data submitted to the Spanish Pacemaker Registry in 2014, with special reference to pacing mode selection. The report is based on the processing of information provided by the European Pacemaker Patient Identification Card. Information was received from 117 hospitals, with a total of 12 358 cards, representing 34% of estimated activity. Use of conventional generators and resynchronization devices was 784 and 64.4 units per million population, respectively. The mean age of patients receiving an implant was 77.3 years. Men received 59% of implants and 56.4% of replacements. Most patients receiving generator implants and replacements were in the age range 80 to 89 years. Most endocardial leads used were bipolar, and 84.2% had an active fixation system. Pacing was in VVI/R mode despite being in sinus rhythm in 24.7% of patients with sick sinus syndrome and 24% of those with atrioventricular block. The use of pacemaker generators and resynchronization devices per million population continued to increase. Most implanted leads had active fixation and approximately 20% had magnetic resonance imaging protection. Age and sex directly influenced pacing mode selection, which could have been improved in more than 20% of cases. Copyright © 2015 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Optical responses evoked by white matter stimulation in rat visual cortical slices and their relation to neural activities.

PubMed

Tanifuji, M; Yamanaka, A; Sunaba, R; Terakawa, S; Toyama, K

1996-10-28

To characterize optical responses (ORs) evoked by white matter (WM) stimulation in slices of rat visual cortex (VC) stained with voltage sensitive dyes, time course of ORs in each layer was investigated by recording ORs with a linearly aligned photodiode array, and the spatial patterns of the ORs at specified time after stimulation were investigated by a CCD camera in combination with stroboscopic illumination. The ORs recorded by the photodiode array were an increase in absorption at 700 nm and a decrease in the wavelength below 650 nm, suggesting that the ORs were dye related. The ORs were compared with field potentials (FPs) to clarify that neural events were represented by the ORs, and in support of this view, we found that the first order spatial differentials of ORs and that of FPs were in good agreement. We further compared ORs with intracellular responses, and found that the ORs mainly represent postsynaptic potentials (PSPs) of VC neurons except for the deeper part of layer VI, where a component representing action potentials in fibers stimulated directly was observed. The time-lapse imaging of ORs showed that excitation first propagated vertically up to layer I and subsequently in the horizontal direction along layers II-III and V-VI as in previous investigations. Spatio-temporal patterns of ORs under blockade of synaptic transmission were also investigated to reveal activity of fibers evoked by WM stimulation which produced such patterns of propagation.

Vectorial mask optimization methods for robust optical lithography

NASA Astrophysics Data System (ADS)

Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong; Arce, Gonzalo R.

2012-10-01

Continuous shrinkage of critical dimension in an integrated circuit impels the development of resolution enhancement techniques for low k1 lithography. Recently, several pixelated optical proximity correction (OPC) and phase-shifting mask (PSM) approaches were developed under scalar imaging models to account for the process variations. However, the lithography systems with larger-NA (NA>0.6) are predominant for current technology nodes, rendering the scalar models inadequate to describe the vector nature of the electromagnetic field that propagates through the optical lithography system. In addition, OPC and PSM algorithms based on scalar models can compensate for wavefront aberrations, but are incapable of mitigating polarization aberrations in practical lithography systems, which can only be dealt with under the vector model. To this end, we focus on developing robust pixelated gradient-based OPC and PSM optimization algorithms aimed at canceling defocus, dose variation, wavefront and polarization aberrations under a vector model. First, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. A steepest descent algorithm is then used to iteratively optimize the mask patterns. Simulations show that the proposed algorithms can effectively improve the process windows of the optical lithography systems.

Radio-guided sentinel lymph node identification by lymphoscintigraphy fused with an anatomical vector profile: clinical applications.

PubMed

Niccoli Asabella, A; Antonica, F; Renna, M A; Rubini, D; Notaristefano, A; Nicoletti, A; Rubini, G

2013-12-01

To develop a method to fuse lymphoscintigraphic images with an adaptable anatomical vector profile and to evaluate its role in the clinical practice. We used Adobe Illustrator CS6 to create different vector profiles, we fused those profiles, using Adobe Photoshop CS6, with lymphoscintigraphic images of the patient. We processed 197 lymphoscintigraphies performed in patients with cutaneous melanomas, breast cancer or delayed lymph drainage. Our models can be adapted to every patient attitude or position and contain different levels of anatomical details ranging from external body profiles to the internal anatomical structures like bones, muscles, vessels, and lymph nodes. If needed, more new anatomical details can be added and embedded in the profile without redrawing them, saving a lot of time. Details can also be easily hidden, allowing the physician to view only relevant information and structures. Fusion times are about 85 s. The diagnostic confidence of the observers increased significantly. The validation process showed a slight shift (mean 4.9 mm). We have created a new, practical, inexpensive digital technique based on commercial software for fusing lymphoscintigraphic images with built-in anatomical reference profiles. It is easily reproducible and does not alter the original scintigraphic image. Our method allows a more meaningful interpretation of lymphoscintigraphies, an easier recognition of the anatomical site and better lymph node dissection planning.

Vector Doppler: spatial sampling analysis and presentation techniques for real-time systems

NASA Astrophysics Data System (ADS)

Capineri, Lorenzo; Scabia, Marco; Masotti, Leonardo F.

2001-05-01

The aim of the vector Doppler (VD) technique is the quantitative reconstruction of a velocity field independently of the ultrasonic probe axis to flow angle. In particular vector Doppler is interesting for studying vascular pathologies related to complex blood flow conditions. Clinical applications require a real-time operating mode and the capability to perform Doppler measurements over a defined volume. The combination of these two characteristics produces a real-time vector velocity map. In previous works the authors investigated the theory of pulsed wave (PW) vector Doppler and developed an experimental system capable of producing off-line 3D vector velocity maps. Afterwards, for producing dynamic velocity vector maps, we realized a new 2D vector Doppler system based on a modified commercial echograph. The measurement and presentation of a vector velocity field requires a correct spatial sampling that must satisfy the Shannon criterion. In this work we tackled this problem, establishing a relationship between sampling steps and scanning system characteristics. Another problem posed by the vector Doppler technique is the data representation in real-time that should be easy to interpret for the physician. With this in mine we attempted a multimedia solution that uses both interpolated images and sound to represent the information of the measured vector velocity map. These presentation techniques were experimented for real-time scanning on flow phantoms and preliminary measurements in vivo on a human carotid artery.

Multispectral Image Road Extraction Based Upon Automated Map Conflation

NASA Astrophysics Data System (ADS)

Chen, Bin

Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD), differs from conventional measures and is created to account for both changes of spectral direction and spectral magnitude in a unified fashion. The ATD measure is particularly suitable for differentiating urban targets such as roads and building rooftops. The curvilinear image provides estimates of the width and orientation of potential road segments. Road vectors derived from OpenStreetMap are then conflated to image road features by applying junction matching and intermediate point matching, followed by refinement with mean-shift clustering and morphological processing to produce a road mask with piecewise width estimates. The proposed approach is tested on a set of challenging, large, and diverse image data sets and the performance accuracy is assessed. The method is effective for road detection and width estimation of roads, even in challenging scenarios when extensive occlusion occurs.

Automatic techniques for 3D reconstruction of critical workplace body postures from range imaging data

NASA Astrophysics Data System (ADS)

Westfeld, Patrick; Maas, Hans-Gerd; Bringmann, Oliver; Gröllich, Daniel; Schmauder, Martin

2013-11-01

The paper shows techniques for the determination of structured motion parameters from range camera image sequences. The core contribution of the work presented here is the development of an integrated least squares 3D tracking approach based on amplitude and range image sequences to calculate dense 3D motion vector fields. Geometric primitives of a human body model are fitted to time series of range camera point clouds using these vector fields as additional information. Body poses and motion information for individual body parts are derived from the model fit. On the basis of these pose and motion parameters, critical body postures are detected. The primary aim of the study is to automate ergonomic studies for risk assessments regulated by law, identifying harmful movements and awkward body postures in a workplace.

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

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.

Dynamic three-dimensional phase-contrast technique in MRI: application to complex flow analysis around the artificial heart valve

NASA Astrophysics Data System (ADS)

Kim, Soo Jeong; Lee, Dong Hyuk; Song, Inchang; Kim, Nam Gook; Park, Jae-Hyeung; Kim, JongHyo; Han, Man Chung; Min, Byong Goo

1998-07-01

Phase-contrast (PC) method of magnetic resonance imaging (MRI) has bee used for quantitative measurements of flow velocity and volume flow rate. It is a noninvasive technique which provides an accurate two-dimensional velocity image. Moreover, Phase Contrast Cine magnetic resonance imaging combines the flow dependent contrast of PC-MRI with the ability of cardiac cine imaging to produce images throughout the cardiac cycle. However, the accuracy of the data acquired from the single through-plane velocity encoding can be reduced by the effect of flow direction, because in many practical cases flow directions are not uniform throughout the whole region of interest. In this study, we present dynamic three-dimensional velocity vector mapping method using PC-MRI which can visualize the complex flow pattern through 3D volume rendered images displayed dynamically. The direction of velocity mapping can be selected along any three orthogonal axes. By vector summation, the three maps can be combined to form a velocity vector map that determines the velocity regardless of the flow direction. At the same time, Cine method is used to observe the dynamic change of flow. We performed a phantom study to evaluate the accuracy of the suggested PC-MRI in continuous and pulsatile flow measurement. Pulsatile flow wave form is generated by the ventricular assistant device (VAD), HEMO-PULSA (Biomedlab, Seoul, Korea). We varied flow velocity, pulsatile flow wave form, and pulsing rate. The PC-MRI-derived velocities were compared with Doppler-derived results. The velocities of the two measurements showed a significant linear correlation. Dynamic three-dimensional velocity vector mapping was carried out for two cases. First, we applied to the flow analysis around the artificial heart valve in a flat phantom. We could observe the flow pattern around the valve through the 3-dimensional cine image. Next, it is applied to the complex flow inside the polymer sac that is used as ventricle in totally implantable artificial heart (TAH). As a result we could observe the flow pattern around the valves of the sac, though complex flow can not be detected correctly in the conventional phase contrast method. In addition, we could calculate the cardiac output from TAH sac by quantitative measurement of the volume of flow across the outlet valve.

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

Feature Vector Construction Method for IRIS Recognition

NASA Astrophysics Data System (ADS)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Optical cage generated by azimuthal- and radial-variant vector beams.

PubMed

Man, Zhongsheng; Bai, Zhidong; Li, Jinjian; Zhang, Shuoshuo; Li, Xiaoyu; Zhang, Yuquan; Ge, Xiaolu; Fu, Shenggui

2018-05-01

We propose a method to generate an optical cage using azimuthal- and radial-variant vector beams in a high numerical aperture optical system. A new kind of vector beam that has azimuthal- and radial-variant polarization states is proposed and demonstrated theoretically. Then, an integrated analytical model to calculate the electromagnetic field and Poynting vector distributions of the input azimuthal- and radial-variant vector beams is derived and built based on the vector diffraction theory of Richards and Wolf. From calculations, a full polarization-controlled optical cage is obtained by simply tailoring the radial index of the polarization, the uniformity U of which is up to 0.7748, and the cleanness C is zero. Additionally, a perfect optical cage can be achieved with U=1, and C=0 by introducing an amplitude modulation; its magnetic field and energy flow are also demonstrated in detail. Such optical cages may be helpful in applications such as optical trapping and high-resolution imaging.

Development and evaluation of an airplane electronic display format aligned with the inertial velocity vector

NASA Technical Reports Server (NTRS)

Steinmetz, G. G.

1986-01-01

The development of an electronic primary flight display format aligned with the aircraft velocity vector, a simulation evaluation comparing this format with an electronic attitude-aligned primary flight display format, and a flight evaluation of the velocity-vector-aligned display format are described. Earlier tests in turbulent conditions with the electronic attitude-aligned display format had exhibited unsteadiness. A primary objective of aligning the display format with the velocity vector was to take advantage of a velocity-vector control-wheel steering system to provide steadiness of display during turbulent conditions. Better situational awareness under crosswind conditions was also achieved. The evaluation task was a curved, descending approach with turbulent and crosswind conditions. Primary flight display formats contained computer-drawn perspective runway images and flight-path angle information. The flight tests were conducted aboard the NASA Transport Systems Research Vehicle (TSRV). Comparative results of the simulation and flight tests were principally obtained from subjective commentary. Overall, the pilots preferred the display format aligned with the velocity vector.

Semantic classification of business images

NASA Astrophysics Data System (ADS)

Erol, Berna; Hull, Jonathan J.

2006-01-01

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator.

PubMed

Khazendar, S; Sayasneh, A; Al-Assam, H; Du, H; Kaijser, J; Ferrara, L; Timmerman, D; Jassim, S; Bourne, T

2015-01-01

Preoperative characterisation of ovarian masses into benign or malignant is of paramount importance to optimise patient management. In this study, we developed and validated a computerised model to characterise ovarian masses as benign or malignant. Transvaginal 2D B mode static ultrasound images of 187 ovarian masses with known histological diagnosis were included. Images were first pre-processed and enhanced, and Local Binary Pattern Histograms were then extracted from 2 × 2 blocks of each image. A Support Vector Machine (SVM) was trained using stratified cross validation with randomised sampling. The process was repeated 15 times and in each round 100 images were randomly selected. The SVM classified the original non-treated static images as benign or malignant masses with an average accuracy of 0.62 (95% CI: 0.59-0.65). This performance significantly improved to an average accuracy of 0.77 (95% CI: 0.75-0.79) when images were pre-processed, enhanced and treated with a Local Binary Pattern operator (mean difference 0.15: 95% 0.11-0.19, p < 0.0001, two-tailed t test). We have shown that an SVM can classify static 2D B mode ultrasound images of ovarian masses into benign and malignant categories. The accuracy improves if texture related LBP features extracted from the images are considered.

Viral vector-based tools advance knowledge of basal ganglia anatomy and physiology.

PubMed

Sizemore, Rachel J; Seeger-Armbruster, Sonja; Hughes, Stephanie M; Parr-Brownlie, Louise C

2016-04-01

Viral vectors were originally developed to deliver genes into host cells for therapeutic potential. However, viral vector use in neuroscience research has increased because they enhance interpretation of the anatomy and physiology of brain circuits compared with conventional tract tracing or electrical stimulation techniques. Viral vectors enable neuronal or glial subpopulations to be labeled or stimulated, which can be spatially restricted to a single target nucleus or pathway. Here we review the use of viral vectors to examine the structure and function of motor and limbic basal ganglia (BG) networks in normal and pathological states. We outline the use of viral vectors, particularly lentivirus and adeno-associated virus, in circuit tracing, optogenetic stimulation, and designer drug stimulation experiments. Key studies that have used viral vectors to trace and image pathways and connectivity at gross or ultrastructural levels are reviewed. We explain how optogenetic stimulation and designer drugs used to modulate a distinct pathway and neuronal subpopulation have enhanced our mechanistic understanding of BG function in health and pathophysiology in disease. Finally, we outline how viral vector technology may be applied to neurological and psychiatric conditions to offer new treatments with enhanced outcomes for patients. Copyright © 2016 the American Physiological Society.

Viral vector-based tools advance knowledge of basal ganglia anatomy and physiology

PubMed Central

Sizemore, Rachel J.; Seeger-Armbruster, Sonja; Hughes, Stephanie M.

2016-01-01

Viral vectors were originally developed to deliver genes into host cells for therapeutic potential. However, viral vector use in neuroscience research has increased because they enhance interpretation of the anatomy and physiology of brain circuits compared with conventional tract tracing or electrical stimulation techniques. Viral vectors enable neuronal or glial subpopulations to be labeled or stimulated, which can be spatially restricted to a single target nucleus or pathway. Here we review the use of viral vectors to examine the structure and function of motor and limbic basal ganglia (BG) networks in normal and pathological states. We outline the use of viral vectors, particularly lentivirus and adeno-associated virus, in circuit tracing, optogenetic stimulation, and designer drug stimulation experiments. Key studies that have used viral vectors to trace and image pathways and connectivity at gross or ultrastructural levels are reviewed. We explain how optogenetic stimulation and designer drugs used to modulate a distinct pathway and neuronal subpopulation have enhanced our mechanistic understanding of BG function in health and pathophysiology in disease. Finally, we outline how viral vector technology may be applied to neurological and psychiatric conditions to offer new treatments with enhanced outcomes for patients. PMID:26888111

Using a Smartphone Camera for Nanosatellite Attitude Determination

NASA Astrophysics Data System (ADS)

Shimmin, R.

2014-09-01

The PhoneSat project at NASA Ames Research Center has repeatedly flown a commercial cellphone in space. As this project continues, additional utility is being extracted from the cell phone hardware to enable more complex missions. The camera in particular shows great potential as an instrument for position and attitude determination, but this requires complex image processing. This paper outlines progress towards that image processing capability. Initial tests on a small collection of sample images have demonstrated the determination of a Moon vector from an image by automatic thresholding and centroiding, allowing the calibration of existing attitude control systems. Work has been undertaken on a further set of sample images towards horizon detection using a variety of techniques including thresholding, edge detection, applying a Hough transform, and circle fitting. Ultimately it is hoped this will allow calculation of an Earth vector for attitude determination and an approximate altitude. A quick discussion of work towards using the camera as a star tracker is then presented, followed by an introduction to further applications of the camera on space missions.

Markov random field model-based edge-directed image interpolation.

PubMed

Li, Min; Nguyen, Truong Q

2008-07-01

This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. In opposite to explicit edge directions, the local edge directions are indicated by length-16 weighting vectors. Implicitly, the weighting vectors are used to formulate geometric regularity (GR) constraint (smoothness along edges and sharpness across edges) and the GR constraint is imposed on the interpolated image through the Markov random field (MRF) model. Furthermore, under the maximum a posteriori-MRF framework, the desired interpolated image corresponds to the minimal energy state of a 2-D random field given the low-resolution image. Simulated annealing methods are used to search for the minimal energy state from the state space. To lower the computational complexity of MRF, a single-pass implementation is designed, which performs nearly as well as the iterative optimization. Simulation results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity. Compared to traditional methods and other edge-directed interpolation methods, the proposed method improves the subjective quality of the interpolated edges while maintaining a high PSNR level.

Diamond-Based Magnetic Imaging with Fourier Optical Processing

NASA Astrophysics Data System (ADS)

Backlund, Mikael P.; Kehayias, Pauli; Walsworth, Ronald L.

2017-11-01

Diamond-based magnetic field sensors have attracted great interest in recent years. In particular, wide-field magnetic imaging using nitrogen-vacancy (NV) centers in diamond has been previously demonstrated in condensed matter, biological, and paleomagnetic applications. Vector magnetic imaging with NV ensembles typically requires a significant applied field (>10 G ) to resolve the contributions from four crystallographic orientations, hindering studies of magnetic samples that require measurement in low or independently specified bias fields. Here we model and measure the complex amplitude distribution of NV emission at the microscope's Fourier plane and show that by modulating this collected light at the Fourier plane, one can decompose the NV ensemble magnetic resonance spectrum into its constituent orientations by purely optical means. This decomposition effectively extends the dynamic range at a given bias field and enables wide-field vector magnetic imaging at arbitrarily low bias fields, thus broadening potential applications of NV imaging and sensing. Our results demonstrate that NV-based microscopy stands to benefit greatly from Fourier optical approaches, which have already found widespread utility in other branches of microscopy.

Extended depth measurement for a Stokes sample imaging polarimeter

NASA Astrophysics Data System (ADS)

Dixon, Alexander W.; Taberner, Andrew J.; Nash, Martyn P.; Nielsen, Poul M. F.

2018-02-01

A non-destructive imaging technique is required for quantifying the anisotropic and heterogeneous structural arrangement of collagen in soft tissue membranes, such as bovine pericardium, which are used in the construction of bioprosthetic heart valves. Previously, our group developed a Stokes imaging polarimeter that measures the linear birefringence of samples in a transmission arrangement. With this device, linear retardance and optic axis orientation; can be estimated over a sample using simple vector algebra on Stokes vectors in the Poincaré sphere. However, this method is limited to a single path retardation of a half-wave, limiting the thickness of samples that can be imaged. The polarimeter has been extended to allow illumination of narrow bandwidth light of controllable wavelength through achromatic lenses and polarization optics. We can now take advantage of the wavelength dependence of relative retardation to remove ambiguities that arise when samples have a single path retardation of a half-wave to full-wave. This effectively doubles the imaging depth of this method. The method has been validated using films of cellulose of varied thickness, and applied to samples of bovine pericardium.

Superresolution radar imaging based on fast inverse-free sparse Bayesian learning for multiple measurement vectors

NASA Astrophysics Data System (ADS)

He, Xingyu; Tong, Ningning; Hu, Xiaowei

2018-01-01

Compressive sensing has been successfully applied to inverse synthetic aperture radar (ISAR) imaging of moving targets. By exploiting the block sparse structure of the target image, sparse solution for multiple measurement vectors (MMV) can be applied in ISAR imaging and a substantial performance improvement can be achieved. As an effective sparse recovery method, sparse Bayesian learning (SBL) for MMV involves a matrix inverse at each iteration. Its associated computational complexity grows significantly with the problem size. To address this problem, we develop a fast inverse-free (IF) SBL method for MMV. A relaxed evidence lower bound (ELBO), which is computationally more amiable than the traditional ELBO used by SBL, is obtained by invoking fundamental property for smooth functions. A variational expectation-maximization scheme is then employed to maximize the relaxed ELBO, and a computationally efficient IF-MSBL algorithm is proposed. Numerical results based on simulated and real data show that the proposed method can reconstruct row sparse signal accurately and obtain clear superresolution ISAR images. Moreover, the running time and computational complexity are reduced to a great extent compared with traditional SBL methods.

Face recognition via sparse representation of SIFT feature on hexagonal-sampling image

NASA Astrophysics Data System (ADS)

Zhang, Daming; Zhang, Xueyong; Li, Lu; Liu, Huayong

2018-04-01

This paper investigates a face recognition approach based on Scale Invariant Feature Transform (SIFT) feature and sparse representation. The approach takes advantage of SIFT which is local feature other than holistic feature in classical Sparse Representation based Classification (SRC) algorithm and possesses strong robustness to expression, pose and illumination variations. Since hexagonal image has more inherit merits than square image to make recognition process more efficient, we extract SIFT keypoint in hexagonal-sampling image. Instead of matching SIFT feature, firstly the sparse representation of each SIFT keypoint is given according the constructed dictionary; secondly these sparse vectors are quantized according dictionary; finally each face image is represented by a histogram and these so-called Bag-of-Words vectors are classified by SVM. Due to use of local feature, the proposed method achieves better result even when the number of training sample is small. In the experiments, the proposed method gave higher face recognition rather than other methods in ORL and Yale B face databases; also, the effectiveness of the hexagonal-sampling in the proposed method is verified.

Digital staining for histopathology multispectral images by the combined application of spectral enhancement and spectral transformation.

PubMed

Bautista, Pinky A; Yagi, Yukako

2011-01-01

In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.

Feature Selection in Order to Extract Multiple Sclerosis Lesions Automatically in 3D Brain Magnetic Resonance Images Using Combination of Support Vector Machine and Genetic Algorithm.

PubMed

Khotanlou, Hassan; Afrasiabi, Mahlagha

2012-10-01

This paper presents a new feature selection approach for automatically extracting multiple sclerosis (MS) lesions in three-dimensional (3D) magnetic resonance (MR) images. Presented method is applicable to different types of MS lesions. In this method, T1, T2, and fluid attenuated inversion recovery (FLAIR) images are firstly preprocessed. In the next phase, effective features to extract MS lesions are selected by using a genetic algorithm (GA). The fitness function of the GA is the Similarity Index (SI) of a support vector machine (SVM) classifier. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. This algorithm is evaluated on 15 real 3D MR images using several measures. As a result, the SI between MS regions determined by the proposed method and radiologists was 87% on average. Experiments and comparisons with other methods show the effectiveness and the efficiency of the proposed approach.

Fast large-scale object retrieval with binary quantization

NASA Astrophysics Data System (ADS)

Zhou, Shifu; Zeng, Dan; Shen, Wei; Zhang, Zhijiang; Tian, Qi

2015-11-01

The objective of large-scale object retrieval systems is to search for images that contain the target object in an image database. Where state-of-the-art approaches rely on global image representations to conduct searches, we consider many boxes per image as candidates to search locally in a picture. In this paper, a feature quantization algorithm called binary quantization is proposed. In binary quantization, a scale-invariant feature transform (SIFT) feature is quantized into a descriptive and discriminative bit-vector, which allows itself to adapt to the classic inverted file structure for box indexing. The inverted file, which stores the bit-vector and box ID where the SIFT feature is located inside, is compact and can be loaded into the main memory for efficient box indexing. We evaluate our approach on available object retrieval datasets. Experimental results demonstrate that the proposed approach is fast and achieves excellent search quality. Therefore, the proposed approach is an improvement over state-of-the-art approaches for object retrieval.

Tensor Sparse Coding for Positive Definite Matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikos

2013-08-02

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for e.g., image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Tensor sparse coding for positive definite matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2014-03-01

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for example, image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Application of Hyperspectal Techniques to Monitoring & Management of Invasive Plant Species Infestation

DTIC Science & Technology

2008-01-09

The image data as acquired from the sensor is a data cloud in multi- dimensional space with each band generating an axis of dimension. When the data... The color of a material is defined by the direction of its unit vector in n- dimensional spectral space . The length of the vector relates only to how...to n- dimensional space . SAM determines the similarity

The house fly, Musca domestica: once again a vector of pathogens of public health significance

USDA-ARS?s Scientific Manuscript database

During the time of Walter Reed in Cuba and in subsequent years of the early 20th century, the house fly lost its image of a being a good fly to have around, and became a dreaded vector of disease-causing organisms. In the U.S., it was dubbed the typhoid fly and many research projects were launched t...

A median filter approach for correcting errors in a vector field

NASA Technical Reports Server (NTRS)

Schultz, H.

1985-01-01

Techniques are presented for detecting and correcting errors in a vector field. These methods employ median filters which are frequently used in image processing to enhance edges and remove noise. A detailed example is given for wind field maps produced by a spaceborne scatterometer. The error detection and replacement algorithm was tested with simulation data from the NASA Scatterometer (NSCAT) project.

Digital photogrammetry at the U.S. Geological Survey

USGS Publications Warehouse

Greve, Clifford W.

1995-01-01

The U.S. Geological Survey is converting its primary map production and revision operations to use digital photogrammetric techniques. The primary source of data for these operations is the digital orthophoto quadrangle derived from National Aerial Photography Program images. These digital orthophotos are used on workstations that permit comparison of existing vector and raster data with the orthophoto and interactive collection and revision of the vector data.

The house fly, Musca domestica: An overlooked vector of pathogens of public health significance

USDA-ARS?s Scientific Manuscript database

During the time of Walter Reed in Cuba and in subsequent years of the early 20th century, the house fly lost its image of a being a good fly to have around, and became a dreaded vector of disease-causing organisms. In the US, it was dubbed the typhoid fly and many research projects were launched to ...

Support vector machine firefly algorithm based optimization of lens system.

PubMed

Shamshirband, Shahaboddin; Petković, Dalibor; Pavlović, Nenad T; Ch, Sudheer; Altameem, Torki A; Gani, Abdullah

2015-01-01

Lens system design is an important factor in image quality. The main aspect of the lens system design methodology is the optimization procedure. Since optimization is a complex, nonlinear task, soft computing optimization algorithms can be used. There are many tools that can be employed to measure optical performance, but the spot diagram is the most useful. The spot diagram gives an indication of the image of a point object. In this paper, the spot size radius is considered an optimization criterion. Intelligent soft computing scheme support vector machines (SVMs) coupled with the firefly algorithm (FFA) are implemented. The performance of the proposed estimators is confirmed with the simulation results. The result of the proposed SVM-FFA model has been compared with support vector regression (SVR), artificial neural networks, and generic programming methods. The results show that the SVM-FFA model performs more accurately than the other methodologies. Therefore, SVM-FFA can be used as an efficient soft computing technique in the optimization of lens system designs.

Proposal of Path Following and Arrival Judgement Methods Using Target Vector for Teleoperation of a Mobile Robot on Uneven Ground by Image Pointing

NASA Astrophysics Data System (ADS)

Tamura, Sho; Maeyama, Shoichi

Rescue robots have been actively developed since Hanshin-Awaji (Kobe) Earthquake. Recently, the rescue robot to reduce the risk of the secondary disaster on NBC terror and critical accident is also developed. For such a background, the development project of mobile RT system in the collapsed is started. This research also participates in this project. It is useful to use the image pointing for the control interface of the rescue robot because it can control the robot by the simple operation. However, the conventional method cannot work on a rough terrain. In this research, we propose the system which controls the robot to arrive the target position on the rough terrain. It is constructed the methods which put the destination into the vector, and control the 3D localizated robot to follow the vector. Finally, the proposed system is evaluated through experiments by remote control of a mobile robot in slope and cofirmed the feasibility.

Circular Data Images for Directional Data

NASA Technical Reports Server (NTRS)

Morpet, William J.

2004-01-01

Directional data includes vectors, points on a unit sphere, axis orientation, angular direction, and circular or periodic data. The theoretical statistics for circular data (random points on a unit circle) or spherical data (random points on a unit sphere) are a recent development. An overview of existing graphical methods for the display of directional data is given. Cross-over occurs when periodic data are measured on a scale for the measurement of linear variables. For example, if angle is represented by a linear color gradient changing uniformly from dark blue at -180 degrees to bright red at +180 degrees, the color image will be discontinuous at +180 degrees and -180 degrees, which are the same location. The resultant color would depend on the direction of approach to the cross-over point. A new graphical method for imaging directional data is described, which affords high resolution without color discontinuity from "cross-over". It is called the circular data image. The circular data image uses a circular color scale in which colors repeat periodically. Some examples of the circular data image include direction of earth winds on a global scale, rocket motor internal flow, earth global magnetic field direction, and rocket motor nozzle vector direction vs. time.

Information-efficient spectral imaging sensor

DOEpatents

Sweatt, William C.; Gentry, Stephen M.; Boye, Clinton A.; Grotbeck, Carter L.; Stallard, Brian R.; Descour, Michael R.

2003-01-01

A programmable optical filter for use in multispectral and hyperspectral imaging. The filter splits the light collected by an optical telescope into two channels for each of the pixels in a row in a scanned image, one channel to handle the positive elements of a spectral basis filter and one for the negative elements of the spectral basis filter. Each channel for each pixel disperses its light into n spectral bins, with the light in each bin being attenuated in accordance with the value of the associated positive or negative element of the spectral basis vector. The spectral basis vector is constructed so that its positive elements emphasize the presence of a target and its negative elements emphasize the presence of the constituents of the background of the imaged scene. The attenuated light in the channels is re-imaged onto separate detectors for each pixel and then the signals from the detectors are combined to give an indication of the presence or not of the target in each pixel of the scanned scene. This system provides for a very efficient optical determination of the presence of the target, as opposed to the very data intensive data manipulations that are required in conventional hyperspectral imaging systems.

The infinitesimal operator for the semigroup of the Frobenius-Perron operator from image sequence data: vector fields and transport barriers from movies.

PubMed

Santitissadeekorn, N; Bollt, E M

2007-06-01

In this paper, we present an approach to approximate the Frobenius-Perron transfer operator from a sequence of time-ordered images, that is, a movie dataset. Unlike time-series data, successive images do not provide a direct access to a trajectory of a point in a phase space; more precisely, a pixel in an image plane. Therefore, we reconstruct the velocity field from image sequences based on the infinitesimal generator of the Frobenius-Perron operator. Moreover, we relate this problem to the well-known optical flow problem from the computer vision community and we validate the continuity equation derived from the infinitesimal operator as a constraint equation for the optical flow problem. Once the vector field and then a discrete transfer operator are found, then, in addition, we present a graph modularity method as a tool to discover basin structure in the phase space. Together with a tool to reconstruct a velocity field, this graph-based partition method provides us with a way to study transport behavior and other ergodic properties of measurable dynamical systems captured only through image sequences.

A Support Vector Machine Approach for Truncated Fingerprint Image Detection from Sweeping Fingerprint Sensors

PubMed Central

Chen, Chi-Jim; Pai, Tun-Wen; Cheng, Mox

2015-01-01

A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image might appear to be truncated and distorted when the finger was swept across a fingerprint sensor at a non-linear speed. If the truncated fingerprint images were enrolled as reference targets and collected by any automated fingerprint identification system (AFIS), successful prediction rates for fingerprint matching applications would be decreased significantly. In this paper, a novel and effective methodology with low time computational complexity was developed for detecting truncated fingerprints in a real time manner. Several filtering rules were implemented to validate existences of truncated fingerprints. In addition, a machine learning method of supported vector machine (SVM), based on the principle of structural risk minimization, was applied to reject pseudo truncated fingerprints containing similar characteristics of truncated ones. The experimental result has shown that an accuracy rate of 90.7% was achieved by successfully identifying truncated fingerprint images from testing images before AFIS enrollment procedures. The proposed effective and efficient methodology can be extensively applied to all existing fingerprint matching systems as a preliminary quality control prior to construction of fingerprint templates. PMID:25835186

Ranging through Gabor logons-a consistent, hierarchical approach.

PubMed

Chang, C; Chatterjee, S

1993-01-01

In this work, the correspondence problem in stereo vision is handled by matching two sets of dense feature vectors. Inspired by biological evidence, these feature vectors are generated by a correlation between a bank of Gabor sensors and the intensity image. The sensors consist of two-dimensional Gabor filters at various scales (spatial frequencies) and orientations, which bear close resemblance to the receptive field profiles of simple V1 cells in visual cortex. A hierarchical, stochastic relaxation method is then used to obtain the dense stereo disparities. Unlike traditional hierarchical methods for stereo, feature based hierarchical processing yields consistent disparities. To avoid false matchings due to static occlusion, a dual matching, based on the imaging geometry, is used.

Segmentation of touching mycobacterium tuberculosis from Ziehl-Neelsen stained sputum smear images

NASA Astrophysics Data System (ADS)

Xu, Chao; Zhou, Dongxiang; Liu, Yunhui

2015-12-01

Touching Mycobacterium tuberculosis objects in the Ziehl-Neelsen stained sputum smear images present different shapes and invisible boundaries in the adhesion areas, which increases the difficulty in objects recognition and counting. In this paper, we present a segmentation method of combining the hierarchy tree analysis with gradient vector flow snake to address this problem. The skeletons of the objects are used for structure analysis based on the hierarchy tree. The gradient vector flow snake is used to estimate the object edge. Experimental results show that the single objects composing the touching objects are successfully segmented by the proposed method. This work will improve the accuracy and practicability of the computer-aided diagnosis of tuberculosis.

In vivo image analysis of BoHV-4-based vector in mice.

PubMed

Franceschi, Valentina; Stellari, Fabio Franco; Mangia, Carlo; Jacca, Sarah; Lavrentiadou, Sophia; Cavirani, Sandro; Heikenwalder, Mathias; Donofrio, Gaetano

2014-01-01

Due to its biological characteristics bovine herpesvirus 4 (BoHV-4) has been considered as an appropriate gene delivery vector. Its genomic clone, modified as a bacterial artificial chromosome (BAC), is better genetically manipulable and can be used as an efficient gene delivery and vaccine vector. Although a large amount of data have been accumulated in vitro on this specific aspect, the same cannot be asserted for the in vivo condition. Therefore, here we investigated the fate of a recombinant BoHV-4 strain expressing luciferase (BoHV-4-A-CMVlucΔTK) after intraperitoneal or intravenous inoculation in mice, by generating a novel recombinant BoHV-4 expressing luciferase (BoHV-4-A-CMVlucΔTK) and by following the virus replication through in vivo imaging analysis. BoHV-4-A-CMVlucΔTK was first characterized in vitro where it was shown, on one hand that its replication properties are identical to those of the parental virus, and on the other that the transduced/infected cells strongly express luciferase. When BoHV-4-A-CMVlucΔTK was inoculated in mice, either intraperitoneally or intravenously, BoHV-4-A-CMVlucΔTK infection/transduction was exclusively localized to the liver, as detected by in vivo image analysis, and in particular almost exclusively in the hepatocytes, as determined by immuno-histochemistry. These data, that add a new insight on the biology of BoHV-4 in vivo, provide the first indication for the potential use of a BoHV-4-based vector in gene-transfer in the liver.

A spectral-structural bag-of-features scene classifier for very high spatial resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei

2016-06-01

Land-use classification of very high spatial resolution remote sensing (VHSR) imagery is one of the most challenging tasks in the field of remote sensing image processing. However, the land-use classification is hard to be addressed by the land-cover classification techniques, due to the complexity of the land-use scenes. Scene classification is considered to be one of the expected ways to address the land-use classification issue. The commonly used scene classification methods of VHSR imagery are all derived from the computer vision community that mainly deal with terrestrial image recognition. Differing from terrestrial images, VHSR images are taken by looking down with airborne and spaceborne sensors, which leads to the distinct light conditions and spatial configuration of land cover in VHSR imagery. Considering the distinct characteristics, two questions should be answered: (1) Which type or combination of information is suitable for the VHSR imagery scene classification? (2) Which scene classification algorithm is best for VHSR imagery? In this paper, an efficient spectral-structural bag-of-features scene classifier (SSBFC) is proposed to combine the spectral and structural information of VHSR imagery. SSBFC utilizes the first- and second-order statistics (the mean and standard deviation values, MeanStd) as the statistical spectral descriptor for the spectral information of the VHSR imagery, and uses dense scale-invariant feature transform (SIFT) as the structural feature descriptor. From the experimental results, the spectral information works better than the structural information, while the combination of the spectral and structural information is better than any single type of information. Taking the characteristic of the spatial configuration into consideration, SSBFC uses the whole image scene as the scope of the pooling operator, instead of the scope generated by a spatial pyramid (SP) commonly used in terrestrial image classification. The experimental results show that the whole image as the scope of the pooling operator performs better than the scope generated by SP. In addition, SSBFC codes and pools the spectral and structural features separately to avoid mutual interruption between the spectral and structural features. The coding vectors of spectral and structural features are then concatenated into a final coding vector. Finally, SSBFC classifies the final coding vector by support vector machine (SVM) with a histogram intersection kernel (HIK). Compared with the latest scene classification methods, the experimental results with three VHSR datasets demonstrate that the proposed SSBFC performs better than the other classification methods for VHSR image scenes.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

NASA Astrophysics Data System (ADS)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

Biventricular non-compaction hypertrophic cardiomyopathy in association with congenital complete heart block and type I mitochondrial complex deficiency.

PubMed

Dhar, Ranjana; Reardon, William; McMahon, Colin J

2015-06-01

We report a baby girl with an antenatal diagnosis of biventricular non-compaction and complete heart block detected at 22 weeks' gestation. Postnatal echocardiography confirmed severe biventricular non-compaction hypertrophic cardiomyopathy, multiple muscular ventricular septal defects, and mild-moderate pulmonary valve stenosis. Skeletal muscle biopsy confirmed complex 1 mitochondrial respiratory chain deficiency. An epicardial VVI pacemaker was implanted on day 3 of life and revised at 7 years of age. She remains stable at 8 years of age following pacing and medical treatment with carvedilol, aspirin, co-enzyme Q10, and carnitine. This represents the first report of biventricular non-compaction hypertrophic phenotype in association with congenital complete heart block and complex 1 mitochondrial respiratory chain deficiency in a child.

Analyzing angular distributions for two-step dissociation mechanisms in velocity map imaging.

PubMed

Straus, Daniel B; Butler, Lynne M; Alligood, Bridget W; Butler, Laurie J

2013-08-15

Increasingly, velocity map imaging is becoming the method of choice to study photoinduced molecular dissociation processes. This paper introduces an algorithm to analyze the measured net speed, P(vnet), and angular, β(vnet), distributions of the products from a two-step dissociation mechanism, where the first step but not the second is induced by absorption of linearly polarized laser light. Typically, this might be the photodissociation of a C-X bond (X = halogen or other atom) to produce an atom and a momentum-matched radical that has enough internal energy to subsequently dissociate (without the absorption of an additional photon). It is this second step, the dissociation of the unstable radicals, that one wishes to study, but the measured net velocity of the final products is the vector sum of the velocity imparted to the radical in the primary photodissociation (which is determined by taking data on the momentum-matched atomic cophotofragment) and the additional velocity vector imparted in the subsequent dissociation of the unstable radical. The algorithm allows one to determine, from the forward-convolution fitting of the net velocity distribution, the distribution of velocity vectors imparted in the second step of the mechanism. One can thus deduce the secondary velocity distribution, characterized by a speed distribution P(v1,2°) and an angular distribution I(θ2°), where θ2° is the angle between the dissociating radical's velocity vector and the additional velocity vector imparted to the product detected from the subsequent dissociation of the radical.

Beam-hardening correction by a surface fitting and phase classification by a least square support vector machine approach for tomography images of geological samples

NASA Astrophysics Data System (ADS)

Khan, F.; Enzmann, F.; Kersten, M.

2015-12-01

In X-ray computed microtomography (μXCT) image processing is the most important operation prior to image analysis. Such processing mainly involves artefact reduction and image segmentation. We propose a new two-stage post-reconstruction procedure of an image of a geological rock core obtained by polychromatic cone-beam μXCT technology. In the first stage, the beam-hardening (BH) is removed applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. The final BH-corrected image is extracted from the residual data, or the difference between the surface elevation values and the original grey-scale values. For the second stage, we propose using a least square support vector machine (a non-linear classifier algorithm) to segment the BH-corrected data as a pixel-based multi-classification task. A combination of the two approaches was used to classify a complex multi-mineral rock sample. The Matlab code for this approach is provided in the Appendix. A minor drawback is that the proposed segmentation algorithm may become computationally demanding in the case of a high dimensional training data set.

BSIFT: toward data-independent codebook for large scale image search.

PubMed

Zhou, Wengang; Li, Houqiang; Hong, Richang; Lu, Yijuan; Tian, Qi

2015-03-01

Bag-of-Words (BoWs) model based on Scale Invariant Feature Transform (SIFT) has been widely used in large-scale image retrieval applications. Feature quantization by vector quantization plays a crucial role in BoW model, which generates visual words from the high- dimensional SIFT features, so as to adapt to the inverted file structure for the scalable retrieval. Traditional feature quantization approaches suffer several issues, such as necessity of visual codebook training, limited reliability, and update inefficiency. To avoid the above problems, in this paper, a novel feature quantization scheme is proposed to efficiently quantize each SIFT descriptor to a descriptive and discriminative bit-vector, which is called binary SIFT (BSIFT). Our quantizer is independent of image collections. In addition, by taking the first 32 bits out from BSIFT as code word, the generated BSIFT naturally lends itself to adapt to the classic inverted file structure for image indexing. Moreover, the quantization error is reduced by feature filtering, code word expansion, and query sensitive mask shielding. Without any explicit codebook for quantization, our approach can be readily applied in image search in some resource-limited scenarios. We evaluate the proposed algorithm for large scale image search on two public image data sets. Experimental results demonstrate the index efficiency and retrieval accuracy of our approach.

Predicting High Imaging Utilization Based on Initial Radiology Reports: A Feasibility Study of Machine Learning.

PubMed

Hassanpour, Saeed; Langlotz, Curtis P

2016-01-01

Imaging utilization has significantly increased over the last two decades, and is only recently showing signs of moderating. To help healthcare providers identify patients at risk for high imaging utilization, we developed a prediction model to recognize high imaging utilizers based on their initial imaging reports. The prediction model uses a machine learning text classification framework. In this study, we used radiology reports from 18,384 patients with at least one abdomen computed tomography study in their imaging record at Stanford Health Care as the training set. We modeled the radiology reports in a vector space and trained a support vector machine classifier for this prediction task. We evaluated our model on a separate test set of 4791 patients. In addition to high prediction accuracy, in our method, we aimed at achieving high specificity to identify patients at high risk for high imaging utilization. Our results (accuracy: 94.0%, sensitivity: 74.4%, specificity: 97.9%, positive predictive value: 87.3%, negative predictive value: 95.1%) show that a prediction model can enable healthcare providers to identify in advance patients who are likely to be high utilizers of imaging services. Machine learning classifiers developed from narrative radiology reports are feasible methods to predict imaging utilization. Such systems can be used to identify high utilizers, inform future image ordering behavior, and encourage judicious use of imaging. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

Locally adaptive vector quantization: Data compression with feature preservation

NASA Technical Reports Server (NTRS)

Cheung, K. M.; Sayano, M.

1992-01-01

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

On dealing with multiple correlation peaks in PIV

NASA Astrophysics Data System (ADS)

Masullo, A.; Theunissen, R.

2018-05-01

A novel algorithm to analyse PIV images in the presence of strong in-plane displacement gradients and reduce sub-grid filtering is proposed in this paper. Interrogation windows subjected to strong in-plane displacement gradients often produce correlation maps presenting multiple peaks. Standard multi-grid procedures discard such ambiguous correlation windows using a signal to noise (SNR) filter. The proposed algorithm improves the standard multi-grid algorithm allowing the detection of splintered peaks in a correlation map through an automatic threshold, producing multiple displacement vectors for each correlation area. Vector locations are chosen by translating images according to the peak displacements and by selecting the areas with the strongest match. The method is assessed on synthetic images of a boundary layer of varying intensity and a sinusoidal displacement field of changing wavelength. An experimental case of a flow exhibiting strong velocity gradients is also provided to show the improvements brought by this technique.

Low-resolution expression recognition based on central oblique average CS-LBP with adaptive threshold

NASA Astrophysics Data System (ADS)

Han, Sheng; Xi, Shi-qiong; Geng, Wei-dong

2017-11-01

In order to solve the problem of low recognition rate of traditional feature extraction operators under low-resolution images, a novel algorithm of expression recognition is proposed, named central oblique average center-symmetric local binary pattern (CS-LBP) with adaptive threshold (ATCS-LBP). Firstly, the features of face images can be extracted by the proposed operator after pretreatment. Secondly, the obtained feature image is divided into blocks. Thirdly, the histogram of each block is computed independently and all histograms can be connected serially to create a final feature vector. Finally, expression classification is achieved by using support vector machine (SVM) classifier. Experimental results on Japanese female facial expression (JAFFE) database show that the proposed algorithm can achieve a recognition rate of 81.9% when the resolution is as low as 16×16, which is much better than that of the traditional feature extraction operators.

Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

NASA Astrophysics Data System (ADS)

Baek, Andrew; Farhat, Nabil H.

1998-10-01

Invariant features in two dimensional binary images are extracted in a single layer network of locally coupled spiking (pulsating) model neurons with prescribed synapto-dendritic response. The feature vector for an image is represented as invariant structure in the aggregate histogram of interspike intervals obtained by computing time intervals between successive spikes produced from each neuron over a given period of time and combining such intervals from all neurons in the network into a histogram. Simulation results show that the feature vectors are more pattern-specific and invariant under translation, rotation, and change in scale or intensity than achieved in earlier work. We also describe an application of such networks to segmentation of line (edge-enhanced or silhouette) images. The biomorphic spiking network's capabilities in segmentation and invariant feature extraction may prove to be, when they are combined, valuable in Automated Target Recognition (ATR) and other automated object recognition systems.

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

PubMed

del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J; Raboso, Mariano

2015-06-17

Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation-based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking-to reduce the dimensions of images-and binarization-to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

Vector tomography for reconstructing electric fields with non-zero divergence in bounded domains

NASA Astrophysics Data System (ADS)

Koulouri, Alexandra; Brookes, Mike; Rimpiläinen, Ville

2017-01-01

In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along the integration lines and are called the longitudinal and transverse measurements, respectively. In most cases, however, the transverse measurements cannot be physically acquired. Therefore, the VT methods are typically used to reconstruct divergence-free (or source-free) velocity and flow fields that can be reconstructed solely from the longitudinal measurements. In this paper, we show how vector fields with non-zero divergence in a bounded domain can also be reconstructed from the longitudinal measurements without the need of explicitly evaluating the transverse measurements. To the best of our knowledge, VT has not previously been used for this purpose. In particular, we study low-frequency, time-harmonic electric fields generated by dipole sources in convex bounded domains which arise, for example, in electroencephalography (EEG) source imaging. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modeling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field.

The development of vector based 2.5D print methods for a painting machine

NASA Astrophysics Data System (ADS)

Parraman, Carinna

2013-02-01

Through recent trends in the application of digitally printed decorative finishes to products, CAD, 3D additive layer manufacturing and research in material perception, [1, 2] there is a growing interest in the accurate rendering of materials and tangible displays. Although current advances in colour management and inkjet printing has meant that users can take for granted high-quality colour and resolution in their printed images, digital methods for transferring a photographic coloured image from screen to paper is constrained by pixel count, file size, colorimetric conversion between colour spaces and the gamut limits of input and output devices. This paper considers new approaches to applying alternative colour palettes by using a vector-based approach through the application of paint mixtures, towards what could be described as a 2.5D printing method. The objective is to not apply an image to a textured surface, but where texture and colour are integral to the mark, that like a brush, delineates the contours in the image. The paper describes the difference between the way inks and paints are mixed and applied. When transcribing the fluid appearance of a brush stroke, there is a difference between a halftone printed mark and a painted mark. The issue of surface quality is significant to subjective qualities when studying the appearance of ink or paint on paper. The paper provides examples of a range of vector marks that are then transcribed into brush stokes by the painting machine.

Spherical Harmonic Inductive Detection Coils and their use In Dynamic Pre-emphasis for Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Edler, Karl T.

The issue of eddy currents induced by the rapid switching of magnetic field gradients is a long-standing problem in magnetic resonance imaging. A new method for dealing with this problem is presented whereby spatial harmonic components of the magnetic field are continuously sensed, through their temporal rates of change, and corrected. In this way, the effects of the eddy currents on multiple spatial harmonic components of the magnetic field can be detected and corrections applied during the rise time of the gradients. Sensing the temporal changes in each spatial harmonic is made possible with specially designed detection coils. However to make the design of these coils possible, general relationships between the spatial harmonics of the field, scalar potential, and vector potential are found within the quasi-static approximation. These relationships allow the vector potential to be found from the field -- an inverse curl operation -- and may be of use beyond the specific problem of detection coil design. Using the detection coils as sensors, methods are developed for designing a negative feedback system to control the eddy current effects and optimizing that system with respect to image noise and distortion. The design methods are successfully tested in a series of proof-of-principle experiments which lead to a discussion of how to incorporate similar designs into an operational MRI. Keywords: magnetic resonance imaging, eddy currents, dynamic shimming, negative feedback, quasi-static fields, vector potential, inverse curl

Real-time 3D reconstruction of road curvature in far look-ahead distance from analysis of image sequences

NASA Astrophysics Data System (ADS)

Behringer, Reinhold

1995-12-01

A system for visual road recognition in far look-ahead distance, implemented in the autonomous road vehicle VaMP (a passenger car), is described. Visual cues of a road in a video image are the bright lane markings and the edges formed at the road borders. In a distance of more than 100 m, the most relevant road cue is the homogeneous road area, limited by the two border edges. These cues can be detected by the image processing module KRONOS applying edge detection techniques and areal 2D segmentation based on resolution triangles (analogous to a resolution pyramid). An estimation process performs an update of a state vector, which describes spatial road shape and vehicle orientation relative to the road. This state vector is estimated every 40 ms by exploiting knowledge about the vehicle movement (spatio-temporal model of vehicle dynamics) and the road design rules (clothoidal segments). Kalman filter techniques are applied to obtain an optimal estimate of the state vector by evaluating the measurements of the road border positions in the image sequence taken by a set of CCD cameras. The road consists of segments with piecewise constant curvature parameters. The borders between these segments can be detected by applying methods which have been developed for detection of discontinuities during time-discrete measurements. The road recognition system has been tested in autonomous rides with VaMP on public Autobahnen in real traffic at speeds up to 130 km/h.

Channelized relevance vector machine as a numerical observer for cardiac perfusion defect detection task

NASA Astrophysics Data System (ADS)

Kalayeh, Mahdi M.; Marin, Thibault; Pretorius, P. Hendrik; Wernick, Miles N.; Yang, Yongyi; Brankov, Jovan G.

2011-03-01

In this paper, we present a numerical observer for image quality assessment, aiming to predict human observer accuracy in a cardiac perfusion defect detection task for single-photon emission computed tomography (SPECT). In medical imaging, image quality should be assessed by evaluating the human observer accuracy for a specific diagnostic task. This approach is known as task-based assessment. Such evaluations are important for optimizing and testing imaging devices and algorithms. Unfortunately, human observer studies with expert readers are costly and time-demanding. To address this problem, numerical observers have been developed as a surrogate for human readers to predict human diagnostic performance. The channelized Hotelling observer (CHO) with internal noise model has been found to predict human performance well in some situations, but does not always generalize well to unseen data. We have argued in the past that finding a model to predict human observers could be viewed as a machine learning problem. Following this approach, in this paper we propose a channelized relevance vector machine (CRVM) to predict human diagnostic scores in a detection task. We have previously used channelized support vector machines (CSVM) to predict human scores and have shown that this approach offers better and more robust predictions than the classical CHO method. The comparison of the proposed CRVM with our previously introduced CSVM method suggests that CRVM can achieve similar generalization accuracy, while dramatically reducing model complexity and computation time.

Plane-wave transverse oscillation for high-frame-rate 2-D vector flow imaging.

PubMed

Lenge, Matteo; Ramalli, Alessandro; Tortoli, Piero; Cachard, Christian; Liebgott, Hervé

2015-12-01

Transverse oscillation (TO) methods introduce oscillations in the pulse-echo field (PEF) along the direction transverse to the ultrasound propagation direction. This may be exploited to extend flow investigations toward multidimensional estimates. In this paper, the TOs are coupled with the transmission of plane waves (PWs) to reconstruct high-framerate RF images with bidirectional oscillations in the pulse-echo field. Such RF images are then processed by a 2-D phase-based displacement estimator to produce 2-D vector flow maps at thousands of frames per second. First, the capability of generating TOs after PW transmissions was thoroughly investigated by varying the lateral wavelength, the burst length, and the transmission frequency. Over the entire region of interest, the generated lateral wavelengths, compared with the designed ones, presented bias and standard deviation of -3.3 ± 5.7% and 10.6 ± 7.4% in simulations and experiments, respectively. The performance of the ultrafast vector flow mapping method was also assessed by evaluating the differences between the estimated velocities and the expected ones. Both simulations and experiments show overall biases lower than 20% when varying the beam-to-flow angle, the peak velocity, and the depth of interest. In vivo applications of the method on the common carotid and the brachial arteries are also presented.

General n-dimensional quadrature transform and its application to interferogram demodulation.

PubMed

Servin, Manuel; Quiroga, Juan Antonio; Marroquin, Jose Luis

2003-05-01

Quadrature operators are useful for obtaining the modulating phase phi in interferometry and temporal signals in electrical communications. In carrier-frequency interferometry and electrical communications, one uses the Hilbert transform to obtain the quadrature of the signal. In these cases the Hilbert transform gives the desired quadrature because the modulating phase is monotonically increasing. We propose an n-dimensional quadrature operator that transforms cos(phi) into -sin(phi) regardless of the frequency spectrum of the signal. With the quadrature of the phase-modulated signal, one can easily calculate the value of phi over all the domain of interest. Our quadrature operator is composed of two n-dimensional vector fields: One is related to the gradient of the image normalized with respect to local frequency magnitude, and the other is related to the sign of the local frequency of the signal. The inner product of these two vector fields gives us the desired quadrature signal. This quadrature operator is derived in the image space by use of differential vector calculus and in the frequency domain by use of a n-dimensional generalization of the Hilbert transform. A robust numerical algorithm is given to find the modulating phase of two-dimensional single-image closed-fringe interferograms by use of the ideas put forward.

Radiolabeled Adenoviral Sub-unit Proteins for Molecular Imaging and Therapeutic Applications in Oncology

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

Srivastava, S.; Meinken, G.; Springer, K. Awasthi, V.

2004-10-06

The objective of this project was to develop and optimize new ligand systems, based on adenoviral vectors (intact adenovirus, adeno-viral fiber protein, and the knob protein), for delivering suitable radionuclides into tumor cells for molecular imaging and combined gene/radionuclide therapy of cancer.

In vitro and in vivo documentation of quantum dots labeled Trypanosoma cruzi--Rhodnius prolixus interaction using confocal microscopy.

PubMed

Feder, Denise; Gomes, Suzete A O; de Thomaz, André A; Almeida, Diogo B; Faustino, Wagner M; Fontes, Adriana; Stahl, Cecília V; Santos-Mallet, Jacenir R; Cesar, Carlos L

2009-12-01

Semiconductor quantum dots (QDs) are highly fluorescent nanocrystals markers that allow long photobleaching and do not destroy the parasites. In this paper, we used fluorescent core shell quantum dots to perform studies of live parasite-vector interaction processes without any observable effect on the vitality of parasites. These nanocrystals were synthesized in aqueous medium and physiological pH, which is very important for monitoring live cells activities, and conjugated with molecules such as lectins to label specific carbohydrates involved on the parasite-vector interaction. These QDs were successfully used for the study of in vitro and in vivo interaction of Trypanosoma cruzi and the triatomine Rhodnius prolixus. These QDs allowed us to acquire real time confocal images sequences of live T. cruzi-R. prolixus interactions for an extended period, causing no damage to the cells. By zooming to the region of interest, we have been able to acquire confocal images at the three to four frames per second rate. Our results show that QDs are physiological fluorescent markers capable to label living parasites and insect vector cells. QDs can be functionalized with lectins to specifically mark surface carbohydrates on perimicrovillar membrane of R. prolixus to follow, visualize, and understand interaction between vectors and its parasites in real-time.

Spacebased Estimation of Moisture Transport in Marine Atmosphere Using Support Vector Regression

NASA Technical Reports Server (NTRS)

Xie, Xiaosu; Liu, W. Timothy; Tang, Benyang

2007-01-01

An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere ((Theta)) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data ((Theta) calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of (Theta) derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation comparedwith rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

PubMed

Bisenius, Sandrine; Mueller, Karsten; Diehl-Schmid, Janine; Fassbender, Klaus; Grimmer, Timo; Jessen, Frank; Kassubek, Jan; Kornhuber, Johannes; Landwehrmeyer, Bernhard; Ludolph, Albert; Schneider, Anja; Anderl-Straub, Sarah; Stuke, Katharina; Danek, Adrian; Otto, Markus; Schroeter, Matthias L

2017-01-01

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with a very high accuracy paving the road for its application in clinical settings.

Quantitative image processing in fluid mechanics

NASA Technical Reports Server (NTRS)

Hesselink, Lambertus; Helman, James; Ning, Paul

1992-01-01

The current status of digital image processing in fluid flow research is reviewed. In particular, attention is given to a comprehensive approach to the extraction of quantitative data from multivariate databases and examples of recent developments. The discussion covers numerical simulations and experiments, data processing, generation and dissemination of knowledge, traditional image processing, hybrid processing, fluid flow vector field topology, and isosurface analysis using Marching Cubes.

A pseudoinverse deformation vector field generator and its applications

PubMed Central

Yan, C.; Zhong, H.; Murphy, M.; Weiss, E.; Siebers, J. V.

2010-01-01

Purpose: To present, implement, and test a self-consistent pseudoinverse displacement vector field (PIDVF) generator, which preserves the location of information mapped back-and-forth between image sets. Methods: The algorithm is an iterative scheme based on nearest neighbor interpolation and a subsequent iterative search. Performance of the algorithm is benchmarked using a lung 4DCT data set with six CT images from different breathing phases and eight CT images for a single prostrate patient acquired on different days. A diffeomorphic deformable image registration is used to validate our PIDVFs. Additionally, the PIDVF is used to measure the self-consistency of two nondiffeomorphic algorithms which do not use a self-consistency constraint: The ITK Demons algorithm for the lung patient images and an in-house B-Spline algorithm for the prostate patient images. Both Demons and B-Spline have been QAed through contour comparison. Self-consistency is determined by using a DIR to generate a displacement vector field (DVF) between reference image R and study image S (DVFR–S). The same DIR is used to generate DVFS–R. Additionally, our PIDVF generator is used to create PIDVFS–R. Back-and-forth mapping of a set of points (used as surrogates of contours) using DVFR–S and DVFS–R is compared to back-and-forth mapping performed with DVFR–S and PIDVFS–R. The Euclidean distances between the original unmapped points and the mapped points are used as a self-consistency measure. Results: Test results demonstrate that the consistency error observed in back-and-forth mappings can be reduced two to nine times in point mapping and 1.5 to three times in dose mapping when the PIDVF is used in place of the B-Spline algorithm. These self-consistency improvements are not affected by the exchanging of R and S. It is also demonstrated that differences between DVFS–R and PIDVFS–R can be used as a criteria to check the quality of the DVF. Conclusions: Use of DVF and its PIDVF will improve the self-consistency of points, contour, and dose mappings in image guided adaptive therapy. PMID:20384247

Improving Large-Scale Image Retrieval Through Robust Aggregation of Local Descriptors.

PubMed

Husain, Syed Sameed; Bober, Miroslaw

2017-09-01

Visual search and image retrieval underpin numerous applications, however the task is still challenging predominantly due to the variability of object appearance and ever increasing size of the databases, often exceeding billions of images. Prior art methods rely on aggregation of local scale-invariant descriptors, such as SIFT, via mechanisms including Bag of Visual Words (BoW), Vector of Locally Aggregated Descriptors (VLAD) and Fisher Vectors (FV). However, their performance is still short of what is required. This paper presents a novel method for deriving a compact and distinctive representation of image content called Robust Visual Descriptor with Whitening (RVD-W). It significantly advances the state of the art and delivers world-class performance. In our approach local descriptors are rank-assigned to multiple clusters. Residual vectors are then computed in each cluster, normalized using a direction-preserving normalization function and aggregated based on the neighborhood rank. Importantly, the residual vectors are de-correlated and whitened in each cluster before aggregation, leading to a balanced energy distribution in each dimension and significantly improved performance. We also propose a new post-PCA normalization approach which improves separability between the matching and non-matching global descriptors. This new normalization benefits not only our RVD-W descriptor but also improves existing approaches based on FV and VLAD aggregation. Furthermore, we show that the aggregation framework developed using hand-crafted SIFT features also performs exceptionally well with Convolutional Neural Network (CNN) based features. The RVD-W pipeline outperforms state-of-the-art global descriptors on both the Holidays and Oxford datasets. On the large scale datasets, Holidays1M and Oxford1M, SIFT-based RVD-W representation obtains a mAP of 45.1 and 35.1 percent, while CNN-based RVD-W achieve a mAP of 63.5 and 44.8 percent, all yielding superior performance to the state-of-the-art.

Velocity Measurement in Carotid Artery: Quantitative Comparison of Time-Resolved 3D Phase-Contrast MRI and Image-based Computational Fluid Dynamics

PubMed Central

Sarrami-Foroushani, Ali; Nasr Esfahany, Mohsen; Nasiraei Moghaddam, Abbas; Saligheh Rad, Hamidreza; Firouznia, Kavous; Shakiba, Madjid; Ghanaati, Hossein; Wilkinson, Iain David; Frangi, Alejandro Federico

2015-01-01

Background: Understanding hemodynamic environment in vessels is important for realizing the mechanisms leading to vascular pathologies. Objectives: Three-dimensional velocity vector field in carotid bifurcation is visualized using TR 3D phase-contrast magnetic resonance imaging (TR 3D PC MRI) and computational fluid dynamics (CFD). This study aimed to present a qualitative and quantitative comparison of the velocity vector field obtained by each technique. Subjects and Methods: MR imaging was performed on a 30-year old male normal subject. TR 3D PC MRI was performed on a 3 T scanner to measure velocity in carotid bifurcation. 3D anatomical model for CFD was created using images obtained from time-of-flight MR angiography. Velocity vector field in carotid bifurcation was predicted using CFD and PC MRI techniques. A statistical analysis was performed to assess the agreement between the two methods. Results: Although the main flow patterns were the same for the both techniques, CFD showed a greater resolution in mapping the secondary and circulating flows. Overall root mean square (RMS) errors for all the corresponding data points in PC MRI and CFD were 14.27% in peak systole and 12.91% in end diastole relative to maximum velocity measured at each cardiac phase. Bland-Altman plots showed a very good agreement between the two techniques. However, this study was not aimed to validate any of methods, instead, the consistency was assessed to accentuate the similarities and differences between Time-resolved PC MRI and CFD. Conclusion: Both techniques provided quantitatively consistent results of in vivo velocity vector fields in right internal carotid artery (RCA). PC MRI represented a good estimation of main flow patterns inside the vasculature, which seems to be acceptable for clinical use. However, limitations of each technique should be considered while interpreting results. PMID:26793288

Automatic detection and recognition of traffic signs in stereo images based on features and probabilistic neural networks

NASA Astrophysics Data System (ADS)

Sheng, Yehua; Zhang, Ka; Ye, Chun; Liang, Cheng; Li, Jian

2008-04-01

Considering the problem of automatic traffic sign detection and recognition in stereo images captured under motion conditions, a new algorithm for traffic sign detection and recognition based on features and probabilistic neural networks (PNN) is proposed in this paper. Firstly, global statistical color features of left image are computed based on statistics theory. Then for red, yellow and blue traffic signs, left image is segmented to three binary images by self-adaptive color segmentation method. Secondly, gray-value projection and shape analysis are used to confirm traffic sign regions in left image. Then stereo image matching is used to locate the homonymy traffic signs in right image. Thirdly, self-adaptive image segmentation is used to extract binary inner core shapes of detected traffic signs. One-dimensional feature vectors of inner core shapes are computed by central projection transformation. Fourthly, these vectors are input to the trained probabilistic neural networks for traffic sign recognition. Lastly, recognition results in left image are compared with recognition results in right image. If results in stereo images are identical, these results are confirmed as final recognition results. The new algorithm is applied to 220 real images of natural scenes taken by the vehicle-borne mobile photogrammetry system in Nanjing at different time. Experimental results show a detection and recognition rate of over 92%. So the algorithm is not only simple, but also reliable and high-speed on real traffic sign detection and recognition. Furthermore, it can obtain geometrical information of traffic signs at the same time of recognizing their types.

Image Augmentation for Object Image Classification Based On Combination of Pre-Trained CNN and SVM

NASA Astrophysics Data System (ADS)

Shima, Yoshihiro

2018-04-01

Neural networks are a powerful means of classifying object images. The proposed image category classification method for object images combines convolutional neural networks (CNNs) and support vector machines (SVMs). A pre-trained CNN, called Alex-Net, is used as a pattern-feature extractor. Alex-Net is pre-trained for the large-scale object-image dataset ImageNet. Instead of training, Alex-Net, pre-trained for ImageNet is used. An SVM is used as trainable classifier. The feature vectors are passed to the SVM from Alex-Net. The STL-10 dataset are used as object images. The number of classes is ten. Training and test samples are clearly split. STL-10 object images are trained by the SVM with data augmentation. We use the pattern transformation method with the cosine function. We also apply some augmentation method such as rotation, skewing and elastic distortion. By using the cosine function, the original patterns were left-justified, right-justified, top-justified, or bottom-justified. Patterns were also center-justified and enlarged. Test error rate is decreased by 0.435 percentage points from 16.055% by augmentation with cosine transformation. Error rates are increased by other augmentation method such as rotation, skewing and elastic distortion, compared without augmentation. Number of augmented data is 30 times that of the original STL-10 5K training samples. Experimental test error rate for the test 8k STL-10 object images was 15.620%, which shows that image augmentation is effective for image category classification.

Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator

PubMed Central

Khazendar, S.; Sayasneh, A.; Al-Assam, H.; Du, H.; Kaijser, J.; Ferrara, L.; Timmerman, D.; Jassim, S.; Bourne, T.

2015-01-01

Introduction: Preoperative characterisation of ovarian masses into benign or malignant is of paramount importance to optimise patient management. Objectives: In this study, we developed and validated a computerised model to characterise ovarian masses as benign or malignant. Materials and methods: Transvaginal 2D B mode static ultrasound images of 187 ovarian masses with known histological diagnosis were included. Images were first pre-processed and enhanced, and Local Binary Pattern Histograms were then extracted from 2 × 2 blocks of each image. A Support Vector Machine (SVM) was trained using stratified cross validation with randomised sampling. The process was repeated 15 times and in each round 100 images were randomly selected. Results: The SVM classified the original non-treated static images as benign or malignant masses with an average accuracy of 0.62 (95% CI: 0.59-0.65). This performance significantly improved to an average accuracy of 0.77 (95% CI: 0.75-0.79) when images were pre-processed, enhanced and treated with a Local Binary Pattern operator (mean difference 0.15: 95% 0.11-0.19, p < 0.0001, two-tailed t test). Conclusion: We have shown that an SVM can classify static 2D B mode ultrasound images of ovarian masses into benign and malignant categories. The accuracy improves if texture related LBP features extracted from the images are considered. PMID:25897367

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

Guo, Yiting; Dong, Bin; Wang, Bing

Purpose: Effective and accurate segmentation of the aortic valve (AV) from sequenced ultrasound (US) images remains a technical challenge because of intrinsic factors of ultrasound images that impact the quality and the continuous changes of shape and position of segmented objects. In this paper, a novel shape-constraint gradient Chan-Vese (GCV) model is proposed for segmenting the AV from time serial echocardiography. Methods: The GCV model is derived by incorporating the energy of the gradient vector flow into a CV model framework, where the gradient vector energy term is introduced by calculating the deviation angle between the inward normal force ofmore » the evolution contour and the gradient vector force. The flow force enlarges the capture range and enhances the blurred boundaries of objects. This is achieved by adding a circle-like contour (constructed using the AV structure region as a constraint shape) as an energy item to the GCV model through the shape comparison function. This shape-constrained energy can enhance the image constraint force by effectively connecting separate gaps of the object edge as well as driving the evolution contour to quickly approach the ideal object. Because of the slight movement of the AV in adjacent frames, the initial constraint shape is defined by users, with the other constraint shapes being derived from the segmentation results of adjacent sequence frames after morphological filtering. The AV is segmented from the US images by minimizing the proposed energy function. Results: To evaluate the performance of the proposed method, five assessment parameters were used to compare it with manual delineations performed by radiologists (gold standards). Three hundred and fifteen images acquired from nine groups were analyzed in the experiment. The area-metric overlap error rate was 6.89% ± 2.88%, the relative area difference rate 3.94% ± 2.63%, the average symmetric contour distance 1.08 ± 0.43 mm, the root mean square symmetric contour distance 1.37 ± 0.52 mm, and the maximum symmetric contour distance was 3.57 ± 1.72 mm. Conclusions: Compared with the CV model, as a result of the combination of the gradient vector and neighborhood shape information, this semiautomatic segmentation method significantly improves the accuracy and robustness of AV segmentation, making it feasible for improved segmentation of aortic valves from US images that have fuzzy boundaries.« less

Technique to quantitatively measure magnetic properties of thin structures at <10 NM spatial resolution

DOEpatents

Bajt, Sasa

2003-07-08

A highly sensitive and high resolution magnetic microscope images magnetic properties quantitatively. Imaging is done with a modified transmission electron microscope that allows imaging of the sample in a zero magnetic field. Two images from closely spaced planes, one in focus and one slightly out of focus, are sufficient to calculate the absolute values of the phase change imparted to the electrons, and hence obtain the magnetization vector field distribution.

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".

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors

PubMed Central

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-01-01

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms. PMID:26198233

An Autonomous Star Identification Algorithm Based on One-Dimensional Vector Pattern for Star Sensors.

PubMed

Luo, Liyan; Xu, Luping; Zhang, Hua

2015-07-07

In order to enhance the robustness and accelerate the recognition speed of star identification, an autonomous star identification algorithm for star sensors is proposed based on the one-dimensional vector pattern (one_DVP). In the proposed algorithm, the space geometry information of the observed stars is used to form the one-dimensional vector pattern of the observed star. The one-dimensional vector pattern of the same observed star remains unchanged when the stellar image rotates, so the problem of star identification is simplified as the comparison of the two feature vectors. The one-dimensional vector pattern is adopted to build the feature vector of the star pattern, which makes it possible to identify the observed stars robustly. The characteristics of the feature vector and the proposed search strategy for the matching pattern make it possible to achieve the recognition result as quickly as possible. The simulation results demonstrate that the proposed algorithm can effectively accelerate the star identification. Moreover, the recognition accuracy and robustness by the proposed algorithm are better than those by the pyramid algorithm, the modified grid algorithm, and the LPT algorithm. The theoretical analysis and experimental results show that the proposed algorithm outperforms the other three star identification algorithms.

Which Way Is the Flow?

NASA Technical Reports Server (NTRS)

Kao, David

1999-01-01

The line integral convolution (LIC) technique has been known to be an effective tool for depicting flow patterns in a given vector field. There have been many extensions to make it run faster and reveal useful flow information such as velocity magnitude, motion, and direction. There are also extensions to unsteady flows and 3D vector fields. Surprisingly, none of these extensions automatically highlight flow features, which often represent the most important and interesting physical flow phenomena. In this sketch, a method for highlighting flow direction in LIC images is presented. The method gives an intuitive impression of flow direction in the given vector field and automatically reveals saddle points in the flow.

Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy

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

Stützer, Kristin; Haase, Robert; Exner, Florian

2016-09-15

Purpose: Rating both a lung segmentation algorithm and a deformable image registration (DIR) algorithm for subsequent lung computed tomography (CT) images by different evaluation techniques. Furthermore, investigating the relative performance and the correlation of the different evaluation techniques to address their potential value in a clinical setting. Methods: Two to seven subsequent CT images (69 in total) of 15 lung cancer patients were acquired prior, during, and after radiochemotherapy. Automated lung segmentations were compared to manually adapted contours. DIR between the first and all following CT images was performed with a fast algorithm specialized for lung tissue registration, requiring themore » lung segmentation as input. DIR results were evaluated based on landmark distances, lung contour metrics, and vector field inconsistencies in different subvolumes defined by eroding the lung contour. Correlations between the results from the three methods were evaluated. Results: Automated lung contour segmentation was satisfactory in 18 cases (26%), failed in 6 cases (9%), and required manual correction in 45 cases (66%). Initial and corrected contours had large overlap but showed strong local deviations. Landmark-based DIR evaluation revealed high accuracy compared to CT resolution with an average error of 2.9 mm. Contour metrics of deformed contours were largely satisfactory. The median vector length of inconsistency vector fields was 0.9 mm in the lung volume and slightly smaller for the eroded volumes. There was no clear correlation between the three evaluation approaches. Conclusions: Automatic lung segmentation remains challenging but can assist the manual delineation process. Proven by three techniques, the inspected DIR algorithm delivers reliable results for the lung CT data sets acquired at different time points. Clinical application of DIR demands a fast DIR evaluation to identify unacceptable results, for instance, by combining different automated DIR evaluation methods.« less

Preclinical Potency and Biodistribution Studies of an AAV 5 Vector Expressing Human Interferon-β (ART-I02) for Local Treatment of Patients with Rheumatoid Arthritis

PubMed Central

Aalbers, Caroline J.; Bevaart, Lisette; Loiler, Scott; de Cortie, Karin; Wright, J. Fraser; Mingozzi, Federico; Tak, Paul P.; Vervoordeldonk, Margriet J.

2015-01-01

Introduction Proof of concept for local gene therapy for the treatment of arthritis with immunomodulatory cytokine interferon beta (IFN-β) has shown promising results in animal models of rheumatoid arthritis (RA). For the treatment of RA patients, we engineered a recombinant adeno-associated serotype 5 vector (rAAV5) encoding human (h)IFN-β under control of a nuclear factor κB promoter (ART-I02). Methods The potency of ART-I02 in vitro as well as biodistribution in vivo in arthritic animals was evaluated to characterize the vector prior to clinical application. ART-I02 expression and bioactivity after transduction was evaluated in fibroblast-like synoviocytes (FLS) from different species. Biodistribution of the vector after local injection was assessed in a rat adjuvant arthritis model through qPCR analysis of vector DNA. In vivo imaging was used to investigate transgene expression and kinetics in a mouse collagen induced arthritis model. Results Transduction of RA FLS in vitro with ART-I02 resulted in high expression levels of bioactive hIFN-β. Transduction of FLS from rhesus monkeys, rodents and rabbits with ART-I02 showed high transgene expression, and hIFN-β proved bioactive in FLS from rhesus monkeys. Transgene expression and bioactivity in RA FLS were unaltered in the presence of methotrexate. In vivo, vector biodistribution analysis in rats after intra-articular injection of ART-I02 demonstrated that the majority of vector DNA remained in the joint (>93%). In vivo imaging in mice confirmed local expression of rAAV5 in the knee joint region and demonstrated rapid detectable and sustained expression up until 7 weeks. Conclusions These data show that hIFN-β produced by RA FLS transduced with ART-I02 is bioactive and that intra-articular delivery of rAAV5 drives expression of a therapeutic transgene in the joint, with only limited biodistribution of vector DNA to other tissues, supporting progress towards a phase 1 clinical trial for the local treatment of arthritis in patients with RA. PMID:26107769

Preclinical Potency and Biodistribution Studies of an AAV 5 Vector Expressing Human Interferon-β (ART-I02) for Local Treatment of Patients with Rheumatoid Arthritis.

PubMed

Aalbers, Caroline J; Bevaart, Lisette; Loiler, Scott; de Cortie, Karin; Wright, J Fraser; Mingozzi, Federico; Tak, Paul P; Vervoordeldonk, Margriet J

2015-01-01

Proof of concept for local gene therapy for the treatment of arthritis with immunomodulatory cytokine interferon beta (IFN-β) has shown promising results in animal models of rheumatoid arthritis (RA). For the treatment of RA patients, we engineered a recombinant adeno-associated serotype 5 vector (rAAV5) encoding human (h)IFN-β under control of a nuclear factor κB promoter (ART-I02). The potency of ART-I02 in vitro as well as biodistribution in vivo in arthritic animals was evaluated to characterize the vector prior to clinical application. ART-I02 expression and bioactivity after transduction was evaluated in fibroblast-like synoviocytes (FLS) from different species. Biodistribution of the vector after local injection was assessed in a rat adjuvant arthritis model through qPCR analysis of vector DNA. In vivo imaging was used to investigate transgene expression and kinetics in a mouse collagen induced arthritis model. Transduction of RA FLS in vitro with ART-I02 resulted in high expression levels of bioactive hIFN-β. Transduction of FLS from rhesus monkeys, rodents and rabbits with ART-I02 showed high transgene expression, and hIFN-β proved bioactive in FLS from rhesus monkeys. Transgene expression and bioactivity in RA FLS were unaltered in the presence of methotrexate. In vivo, vector biodistribution analysis in rats after intra-articular injection of ART-I02 demonstrated that the majority of vector DNA remained in the joint (>93%). In vivo imaging in mice confirmed local expression of rAAV5 in the knee joint region and demonstrated rapid detectable and sustained expression up until 7 weeks. These data show that hIFN-β produced by RA FLS transduced with ART-I02 is bioactive and that intra-articular delivery of rAAV5 drives expression of a therapeutic transgene in the joint, with only limited biodistribution of vector DNA to other tissues, supporting progress towards a phase 1 clinical trial for the local treatment of arthritis in patients with RA.

4 × 20 Gbit/s mode division multiplexing over free space using vector modes and a q-plate mode (de)multiplexer

NASA Astrophysics Data System (ADS)

Milione, Giovanni; Lavery, Martin P. J.; Huang, Hao; Ren, Yongxiong; Xie, Guodong; Nguyen, Thien An; Karimi, Ebrahim; Marrucci, Lorenzo; Nolan, Daniel A.; Alfano, Robert R.; Willner, Alan E.

2015-05-01

Vector modes are spatial modes that have spatially inhomogeneous states of polarization, such as, radial and azimuthal polarization. They can produce smaller spot sizes and stronger longitudinal polarization components upon focusing. As a result, they are used for many applications, including optical trapping and nanoscale imaging. In this work, vector modes are used to increase the information capacity of free space optical communication via the method of optical communication referred to as mode division multiplexing. A mode (de)multiplexer for vector modes based on a liquid crystal technology referred to as a q-plate is introduced. As a proof of principle, using the mode (de)multiplexer four vector modes each carrying a 20 Gbit/s quadrature phase shift keying signal on a single wavelength channel (~1550nm), comprising an aggregate 80 Gbit/s, were transmitted ~1m over the lab table with <-16.4 dB (<2%) mode crosstalk. Bit error rates for all vector modes were measured at the forward error correction threshold with power penalties < 3.41dB.

High gamma power in ECoG reflects cortical electrical stimulation effects on unit activity in layers V/VI

NASA Astrophysics Data System (ADS)

Yazdan-Shahmorad, Azadeh; Kipke, Daryl R.; Lehmkuhle, Mark J.

2013-12-01

Objective. Cortical electrical stimulation (CES) has been used extensively in experimental neuroscience to modulate neuronal or behavioral activity, which has led this technique to be considered in neurorehabilitation. Because the cortex and the surrounding anatomy have irregular geometries as well as inhomogeneous and anisotropic electrical properties, the mechanism by which CES has therapeutic effects is poorly understood. Therapeutic effects of CES can be improved by optimizing the stimulation parameters based on the effects of various stimulation parameters on target brain regions. Approach. In this study we have compared the effects of CES pulse polarity, frequency, and amplitude on unit activity recorded from rat primary motor cortex with the effects on the corresponding local field potentials (LFP), and electrocorticograms (ECoG). CES was applied at the surface of the cortex and the unit activity and LFPs were recorded using a penetrating electrode array, which was implanted below the stimulation site. ECoGs were recorded from the vicinity of the stimulation site. Main results. Time-frequency analysis of LFPs following CES showed correlation of gamma frequencies with unit activity response in all layers. More importantly, high gamma power of ECoG signals only correlated with the unit activity in lower layers (V-VI) following CES. Time-frequency correlations, which were found between LFPs, ECoGs and unit activity, were frequency- and amplitude-dependent. Significance. The signature of the neural activity observed in LFP and ECoG signals provides a better understanding of the effects of stimulation on network activity, representative of large numbers of neurons responding to stimulation. These results demonstrate that the neurorehabilitation and neuroprosthetic applications of CES targeting layered cortex can be further improved by using field potential recordings as surrogates to unit activity aimed at optimizing stimulation efficacy. Likewise, the signatures of unit activity observed as changes in high gamma power in ECoGs suggest that future cortical stimulation studies could rely on less invasive feedback schemes that incorporate surface stimulation with ECoG reporting of stimulation efficacy.

A computer vision approach for solar radiation nowcasting using MSG images

NASA Astrophysics Data System (ADS)

Álvarez, L.; Castaño Moraga, C. A.; Martín, J.

2010-09-01

Cloud structures and haze are the two main atmospheric phenomena that reduce the performance of solar power plants, since they absorb solar energy reaching terrestrial surface. Thus, accurate forecasting of solar radiation is a challenging research area that involves both a precise localization of cloud structures and haze, as well as the attenuation introduced by these artifacts. Our work presents a novel approach for nowcasting services based on image processing techniques applied to MSG satellite images provided by the EUMETSAT Rapid Scan Service (RSS) service. These data are an interesting source of information for our purposes since every 5 minutes we obtain actual information of the atmospheric state in nearly real time. However, a workaround must be given in order to forecast solar radiation. To that end, we synthetically forecast MSG images forecasts from past images applying computer vision techniques adapted to fluid flows in order to evolve atmospheric state. First, we classify cloud structures on two different layers, corresponding to top and bottom clouds, which includes haze. This two-level classification responds to the dominant climate conditions found in our region of interest, the Canary Islands archipelago, regulated by the Gulf Stream and Trade Winds. Vertical structure of Trade Winds consists of two layers, the bottom one, which is fresh and humid, and the top one, which is warm and dry. Between these two layers a thermal inversion appears that does not allow bottom clouds to go up and naturally divides clouds in these two layers. Top clouds can be directly obtained from satellite images by means of a segmentation algorithm on histogram heights. However, bottom clouds are usually overlapped by the former, so an inpainting algorithm is used to recover overlapped areas of bottom clouds. For each layer, cloud motion is estimated through a correlation based optic flow algorithm that provides a vector field that describes the displacement field in each layer between two consecutive images in a sequence. Since RSS service from EUMETSAT provides images every 5 minutes (Δt), the cloud motion vector field between images at time t0 and (t0 - Δt) is quite similar to that between (t0 - Δt) and (t0 - 2Δt). Under this assumption, we infer the motion vector field for the next image in order to build a synthetic version of the image at time (t0 + Δt). The computation of this future motion vector field takes into account terrain orography in order to produce more realistic forecasts. In this sense, we are currently working on the integration of information from NWP outputs in order to introduce other atmospheric phenomena. Applying this algorithm several times we are able to produce short-term forecasts up to 6 hours with encouraging performance. To validate our results, we use both, comparison of synthetically generated images with the corresponding images at a given time, and direct solar radiation measurement with the set of meteorological stations located at several points of the canarian archipelago.

Development of 4D mathematical observer models for the task-based evaluation of gated myocardial perfusion SPECT

NASA Astrophysics Data System (ADS)

Lee, Taek-Soo; Frey, Eric C.; Tsui, Benjamin M. W.

2015-04-01

This paper presents two 4D mathematical observer models for the detection of motion defects in 4D gated medical images. Their performance was compared with results from human observers in detecting a regional motion abnormality in simulated 4D gated myocardial perfusion (MP) SPECT images. The first 4D mathematical observer model extends the conventional channelized Hotelling observer (CHO) based on a set of 2D spatial channels and the second is a proposed model that uses a set of 4D space-time channels. Simulated projection data were generated using the 4D NURBS-based cardiac-torso (NCAT) phantom with 16 gates/cardiac cycle. The activity distribution modelled uptake of 99mTc MIBI with normal perfusion and a regional wall motion defect. An analytical projector was used in the simulation and the filtered backprojection (FBP) algorithm was used in image reconstruction followed by spatial and temporal low-pass filtering with various cut-off frequencies. Then, we extracted 2D image slices from each time frame and reorganized them into a set of cine images. For the first model, we applied 2D spatial channels to the cine images and generated a set of feature vectors that were stacked for the images from different slices of the heart. The process was repeated for each of the 1,024 noise realizations, and CHO and receiver operating characteristics (ROC) analysis methodologies were applied to the ensemble of the feature vectors to compute areas under the ROC curves (AUCs). For the second model, a set of 4D space-time channels was developed and applied to the sets of cine images to produce space-time feature vectors to which the CHO methodology was applied. The AUC values of the second model showed better agreement (Spearman’s rank correlation (SRC) coefficient = 0.8) to human observer results than those from the first model (SRC coefficient = 0.4). The agreement with human observers indicates the proposed 4D mathematical observer model provides a good predictor of the performance of human observers in detecting regional motion defects in 4D gated MP SPECT images. The result supports the use of the observer model in the optimization and evaluation of 4D image reconstruction and compensation methods for improving the detection of motion abnormalities in 4D gated MP SPECT images.

Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images

PubMed Central

Srinivasan, Pratul P.; Kim, Leo A.; Mettu, Priyatham S.; Cousins, Scott W.; Comer, Grant M.; Izatt, Joseph A.; Farsiu, Sina

2014-01-01

We present a novel fully automated algorithm for the detection of retinal diseases via optical coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of oriented gradient descriptors as feature vectors of a support vector machine based classifier. The spectral domain OCT data sets used for cross-validation consisted of volumetric scans acquired from 45 subjects: 15 normal subjects, 15 patients with dry age-related macular degeneration (AMD), and 15 patients with diabetic macular edema (DME). Our classifier correctly identified 100% of cases with AMD, 100% cases with DME, and 86.67% cases of normal subjects. This algorithm is a potentially impactful tool for the remote diagnosis of ophthalmic diseases. PMID:25360373

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

Facial Expression Recognition using Multiclass Ensemble Least-Square Support Vector Machine

NASA Astrophysics Data System (ADS)

Lawi, Armin; Sya'Rani Machrizzandi, M.

2018-03-01

Facial expression is one of behavior characteristics of human-being. The use of biometrics technology system with facial expression characteristics makes it possible to recognize a person’s mood or emotion. The basic components of facial expression analysis system are face detection, face image extraction, facial classification and facial expressions recognition. This paper uses Principal Component Analysis (PCA) algorithm to extract facial features with expression parameters, i.e., happy, sad, neutral, angry, fear, and disgusted. Then Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM) is used for the classification process of facial expression. The result of MELS-SVM model obtained from our 185 different expression images of 10 persons showed high accuracy level of 99.998% using RBF kernel.