Retinal imaging and image analysis.

PubMed

Abràmoff, Michael D; Garvin, Mona K; Sonka, Milan

2010-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships.

Retinal Imaging and Image Analysis

PubMed Central

Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

2011-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:22275207

Quantitative evaluation of in vivo vital-dye fluorescence endoscopic imaging for the detection of Barrett’s-associated neoplasia

PubMed Central

Thekkek, Nadhi; Lee, Michelle H.; Polydorides, Alexandros D.; Rosen, Daniel G.; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2015-01-01

Abstract. Current imaging tools are associated with inconsistent sensitivity and specificity for detection of Barrett’s-associated neoplasia. Optical imaging has shown promise in improving the classification of neoplasia in vivo. The goal of this pilot study was to evaluate whether in vivo vital dye fluorescence imaging (VFI) has the potential to improve the accuracy of early-detection of Barrett’s-associated neoplasia. In vivo endoscopic VFI images were collected from 65 sites in 14 patients with confirmed Barrett’s esophagus (BE), dysplasia, or esophageal adenocarcinoma using a modular video endoscope and a high-resolution microendoscope (HRME). Qualitative image features were compared to histology; VFI and HRME images show changes in glandular structure associated with neoplastic progression. Quantitative image features in VFI images were identified for objective image classification of metaplasia and neoplasia, and a diagnostic algorithm was developed using leave-one-out cross validation. Three image features extracted from VFI images were used to classify tissue as neoplastic or not with a sensitivity of 87.8% and a specificity of 77.6% (AUC=0.878). A multimodal approach incorporating VFI and HRME imaging can delineate epithelial changes present in Barrett’s-associated neoplasia. Quantitative analysis of VFI images may provide a means for objective interpretation of BE during surveillance. PMID:25950645

Quantitative evaluation of in vivo vital-dye fluorescence endoscopic imaging for the detection of Barrett's-associated neoplasia.

PubMed

Thekkek, Nadhi; Lee, Michelle H; Polydorides, Alexandros D; Rosen, Daniel G; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2015-05-01

Current imaging tools are associated with inconsistent sensitivity and specificity for detection of Barrett's-associated neoplasia. Optical imaging has shown promise in improving the classification of neoplasia in vivo. The goal of this pilot study was to evaluate whether in vivo vital dye fluorescence imaging (VFI) has the potential to improve the accuracy of early-detection of Barrett's-associated neoplasia. In vivo endoscopic VFI images were collected from 65 sites in 14 patients with confirmed Barrett's esophagus (BE), dysplasia, oresophageal adenocarcinoma using a modular video endoscope and a high-resolution microendoscope(HRME). Qualitative image features were compared to histology; VFI and HRME images show changes in glandular structure associated with neoplastic progression. Quantitative image features in VFI images were identified for objective image classification of metaplasia and neoplasia, and a diagnostic algorithm was developed using leave-one-out cross validation. Three image features extracted from VFI images were used to classify tissue as neoplastic or not with a sensitivity of 87.8% and a specificity of 77.6% (AUC = 0.878). A multimodal approach incorporating VFI and HRME imaging can delineate epithelial changes present in Barrett's-associated neoplasia. Quantitative analysis of VFI images may provide a means for objective interpretation of BE during surveillance.

Automated retinal image quality assessment on the UK Biobank dataset for epidemiological studies.

PubMed

Welikala, R A; Fraz, M M; Foster, P J; Whincup, P H; Rudnicka, A R; Owen, C G; Strachan, D P; Barman, S A

2016-04-01

Morphological changes in the retinal vascular network are associated with future risk of many systemic and vascular diseases. However, uncertainty over the presence and nature of some of these associations exists. Analysis of data from large population based studies will help to resolve these uncertainties. The QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) retinal image analysis system allows automated processing of large numbers of retinal images. However, an image quality assessment module is needed to achieve full automation. In this paper, we propose such an algorithm, which uses the segmented vessel map to determine the suitability of retinal images for use in the creation of vessel morphometric data suitable for epidemiological studies. This includes an effective 3-dimensional feature set and support vector machine classification. A random subset of 800 retinal images from UK Biobank (a large prospective study of 500,000 middle aged adults; where 68,151 underwent retinal imaging) was used to examine the performance of the image quality algorithm. The algorithm achieved a sensitivity of 95.33% and a specificity of 91.13% for the detection of inadequate images. The strong performance of this image quality algorithm will make rapid automated analysis of vascular morphometry feasible on the entire UK Biobank dataset (and other large retinal datasets), with minimal operator involvement, and at low cost. Copyright © 2016 Elsevier Ltd. All rights reserved.

Formulas for Image Factor Scores

ERIC Educational Resources Information Center

Hakstian, A. Ralph

1973-01-01

Formulas are presented in this paper for computing scores associated with factors of G, the image covariance matrix, under three conditions. The subject of the paper is restricted to "pure" image analysis. (Author/NE)

Associative memory model for searching an image database by image snippet

NASA Astrophysics Data System (ADS)

Khan, Javed I.; Yun, David Y.

1994-09-01

This paper presents an associative memory called an multidimensional holographic associative computing (MHAC), which can be potentially used to perform feature based image database query using image snippet. MHAC has the unique capability to selectively focus on specific segments of a query frame during associative retrieval. As a result, this model can perform search on the basis of featural significance described by a subset of the snippet pixels. This capability is critical for visual query in image database because quite often the cognitive index features in the snippet are statistically weak. Unlike, the conventional artificial associative memories, MHAC uses a two level representation and incorporates additional meta-knowledge about the reliability status of segments of information it receives and forwards. In this paper we present the analysis of focus characteristics of MHAC.

Presence of muscle dysmorphia symptomology among male weightlifters.

PubMed

Hildebrandt, Tom; Schlundt, David; Langenbucher, James; Chung, Tammy

2006-01-01

Limited research exists on muscle dysmorphia (MD) in men and in nonclinical populations. The current study evaluated types of body image disturbance among 237 male weightlifters. Latent class analysis of 8 measures of body image disturbance revealed 5 independent types of respondents: Dysmorphic, Muscle Concerned, Fat Concerned, Normal Behavioral, and Normal. One-way analysis of variance of independent measures of body image disturbance and associated psychopathology confirmed significant differences between groups. The Dysmorphic group reported a pattern of body image disturbance consistent with MD by displaying a high overall level of body image disturbance, symptoms of associated psychopathology, steroid use, and appearance-controlling behavior. Findings generally supported classifying MD as a subtype of body dysmorphic disorder and an obsessive-compulsive spectrum disorder. Implications for studying body image disturbance in male weightlifters, and further evaluation of the MD diagnostic criteria are discussed.

An image analysis system for near-infrared (NIR) fluorescence lymph imaging

NASA Astrophysics Data System (ADS)

Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Rasmussen, John C.; Sevick-Muraca, Eva M.

2011-03-01

Quantitative analysis of lymphatic function is crucial for understanding the lymphatic system and diagnosing the associated diseases. Recently, a near-infrared (NIR) fluorescence imaging system is developed for real-time imaging lymphatic propulsion by intradermal injection of microdose of a NIR fluorophore distal to the lymphatics of interest. However, the previous analysis software3, 4 is underdeveloped, requiring extensive time and effort to analyze a NIR image sequence. In this paper, we develop a number of image processing techniques to automate the data analysis workflow, including an object tracking algorithm to stabilize the subject and remove the motion artifacts, an image representation named flow map to characterize lymphatic flow more reliably, and an automatic algorithm to compute lymph velocity and frequency of propulsion. By integrating all these techniques to a system, the analysis workflow significantly reduces the amount of required user interaction and improves the reliability of the measurement.

Evolution of ventriculomegaly: comparison between foetal MR imaging and postnatal diagnostic imaging.

PubMed

Mehrabi, Sara; Adami, Alessia; Ventriglia, Anna; Zantedeschi, Lisa; Franchi, Massimo; Manfredi, Riccardo

2013-10-01

We evaluated the evolution of ventriculomegaly (VM) by comparing foetal magnetic resonance imaging (MRI) with postnatal transcranial ultrasonography (US) and/or encephalic MRI. Between January 2006 and April 2011, 70 foetuses with a mean gestational age of 28 weeks and 4 days (range, 18-36) weeks with VM on foetal MRI were assessed in this prospective study. Half-Fourier rapid acquisition with relaxation enhancement (RARE) T2-weighted, T1-weighted and diffusion-weighted (DWI) images along the three orthogonal planes according to the longitudinal axis of the mother, and subsequently of the foetal brain, were acquired. Quantitative image analysis included the transverse diameter of lateral ventricles in axial and coronal planes. Qualitative image analysis included searching for associated structural anomalies. Thirty-four of 70 patients with a diagnosis of VM on foetal MRI underwent postnatal imaging. Twenty-five of those 34 (73%) had mild, four (12%) had moderate and five (15%) had severe VM on MRI. Normalisation of the diameter of lateral ventricles was observed in 16 of the 34 (47%) newborns. Among these 16, 13 (81%) had mild and three (19%) had moderate VM (two isolated and one associated VM). VM stabilisation was observed in 16 of the 34 (47%) babies. Among them, 11 (69%) had mild (eight isolated and three associated), one (6%) had moderate associated and four (25%) had severe associated VM. Progression from mild to severe (associated) VM was observed in two of the 34 (6%) babies. The absence of associated anomalies and a mild VM are favourable prognostic factors in the evolution of VM.

Quantitative analysis of cardiovascular MR images.

PubMed

van der Geest, R J; de Roos, A; van der Wall, E E; Reiber, J H

1997-06-01

The diagnosis of cardiovascular disease requires the precise assessment of both morphology and function. Nearly all aspects of cardiovascular function and flow can be quantified nowadays with fast magnetic resonance (MR) imaging techniques. Conventional and breath-hold cine MR imaging allow the precise and highly reproducible assessment of global and regional left ventricular function. During the same examination, velocity encoded cine (VEC) MR imaging provides measurements of blood flow in the heart and great vessels. Quantitative image analysis often still relies on manual tracing of contours in the images. Reliable automated or semi-automated image analysis software would be very helpful to overcome the limitations associated with the manual and tedious processing of the images. Recent progress in MR imaging of the coronary arteries and myocardial perfusion imaging with contrast media, along with the further development of faster imaging sequences, suggest that MR imaging could evolve into a single technique ('one stop shop') for the evaluation of many aspects of heart disease. As a result, it is very likely that the need for automated image segmentation and analysis software algorithms will further increase. In this paper the developments directed towards the automated image analysis and semi-automated contour detection for cardiovascular MR imaging are presented.

Body image dissatisfaction and anthropometric indicators in male children and adolescents.

PubMed

Ferrari, E P; Minatto, G; Berria, J; Silva, S F Dos S; Fidelix, Y L; Ribeiro, R R; Santos, K D; Petroski, E L

2015-10-01

The aim of this study was to investigate the association between body image dissatisfaction and body mass index (BMI) and body fat percentage (BF%) and to identify which of these anthropometric indicators are more strongly associated, and finally to estimate the prevalence of overweight and high body adiposity in male children and adolescents, according to maturational stages. Overall, 1499 students aged from 7 to 17 years from Cascavel, PR, Brazil, were evaluated. Body image was self-rated through the body silhouette scale. Body weight, height and triceps and subscapular skinfolds were measured and BMI and BF% were calculated. Sexual maturity was self-assessed by the development of pubic hair. Data analysis used the Fisher exact test, the χ(2)-test and multinomial logistic regression. Body image dissatisfaction because of excess weight was associated with BMI and BF%, whereas in prepubertal students, this association did not remain in the adjusted analysis. In pubescent students, both BMI (odds ratio (OR)=5.25, confidence interval (CI) 95%=3.06-9.01) and BF% (OR=2.42, CI 95%=1.60-3.66), and in post-pubescent students for BMI (OR=3.77, CI 95%=1.33-10.70), the association remained. Body image dissatisfaction because of thinness was associated only with BF% in pubescent (OR=0.50, CI 95%= 0.33-0.75) and post-pubescent students (OR=0.38, CI 95%= 0.16-0.94). Body image dissatisfaction was associated with BMI and BF%, especially in pubescent and post-pubescent students.

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

The application of retinal fundus camera imaging in dementia: A systematic review.

PubMed

McGrory, Sarah; Cameron, James R; Pellegrini, Enrico; Warren, Claire; Doubal, Fergus N; Deary, Ian J; Dhillon, Baljean; Wardlaw, Joanna M; Trucco, Emanuele; MacGillivray, Thomas J

2017-01-01

The ease of imaging the retinal vasculature, and the evolving evidence suggesting this microvascular bed might reflect the cerebral microvasculature, presents an opportunity to investigate cerebrovascular disease and the contribution of microvascular disease to dementia with fundus camera imaging. A systematic review and meta-analysis was carried out to assess the measurement of retinal properties in dementia using fundus imaging. Ten studies assessing retinal properties in dementia were included. Quantitative measurement revealed significant yet inconsistent pathologic changes in vessel caliber, tortuosity, and fractal dimension. Retinopathy was more prevalent in dementia. No association of age-related macular degeneration with dementia was reported. Inconsistent findings across studies provide tentative support for the application of fundus camera imaging as a means of identifying changes associated with dementia. The potential of fundus image analysis in differentiating between dementia subtypes should be investigated using larger well-characterized samples. Future work should focus on refining and standardizing methods and measurements.

Brain Imaging and Behavioral Outcome in Traumatic Brain Injury.

ERIC Educational Resources Information Center

Bigler, Erin D.

1996-01-01

This review explores the cellular pathology associated with traumatic brain injury (TBI) and its relation to neurobehavioral outcomes, the relationship of brain imaging findings to underlying pathology, brain imaging techniques, various image analysis procedures and how they relate to neuropsychological testing, and the importance of brain imaging…

STEM_CELL: a software tool for electron microscopy: part 2--analysis of crystalline materials.

PubMed

Grillo, Vincenzo; Rossi, Francesca

2013-02-01

A new graphical software (STEM_CELL) for analysis of HRTEM and STEM-HAADF images is here introduced in detail. The advantage of the software, beyond its graphic interface, is to put together different analysis algorithms and simulation (described in an associated article) to produce novel analysis methodologies. Different implementations and improvements to state of the art approach are reported in the image analysis, filtering, normalization, background subtraction. In particular two important methodological results are here highlighted: (i) the definition of a procedure for atomic scale quantitative analysis of HAADF images, (ii) the extension of geometric phase analysis to large regions up to potentially 1μm through the use of under sampled images with aliasing effects. Copyright © 2012 Elsevier B.V. All rights reserved.

General Staining and Segmentation Procedures for High Content Imaging and Analysis.

PubMed

Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

2018-01-01

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging.

PubMed

Valm, Alex M; Mark Welch, Jessica L; Rieken, Christopher W; Hasegawa, Yuko; Sogin, Mitchell L; Oldenbourg, Rudolf; Dewhirst, Floyd E; Borisy, Gary G

2011-03-08

Microbes in nature frequently function as members of complex multitaxon communities, but the structural organization of these communities at the micrometer level is poorly understood because of limitations in labeling and imaging technology. We report here a combinatorial labeling strategy coupled with spectral image acquisition and analysis that greatly expands the number of fluorescent signatures distinguishable in a single image. As an imaging proof of principle, we first demonstrated visualization of Escherichia coli labeled by fluorescence in situ hybridization (FISH) with 28 different binary combinations of eight fluorophores. As a biological proof of principle, we then applied this Combinatorial Labeling and Spectral Imaging FISH (CLASI-FISH) strategy using genus- and family-specific probes to visualize simultaneously and differentiate 15 different phylotypes in an artificial mixture of laboratory-grown microbes. We then illustrated the utility of our method for the structural analysis of a natural microbial community, namely, human dental plaque, a microbial biofilm. We demonstrate that 15 taxa in the plaque community can be imaged simultaneously and analyzed and that this community was dominated by early colonizers, including species of Streptococcus, Prevotella, Actinomyces, and Veillonella. Proximity analysis was used to determine the frequency of inter- and intrataxon cell-to-cell associations which revealed statistically significant intertaxon pairings. Cells of the genera Prevotella and Actinomyces showed the most interspecies associations, suggesting a central role for these genera in establishing and maintaining biofilm complexity. The results provide an initial systems-level structural analysis of biofilm organization.

Associative Memory Synthesis, Performance, Storage Capacity And Updating: New Heteroassociative Memory Results

NASA Astrophysics Data System (ADS)

Casasent, David; Telfer, Brian

1988-02-01

The storage capacity, noise performance, and synthesis of associative memories for image analysis are considered. Associative memory synthesis is shown to be very similar to that of linear discriminant functions used in pattern recognition. These lead to new associative memories and new associative memory synthesis and recollection vector encodings. Heteroassociative memories are emphasized in this paper, rather than autoassociative memories, since heteroassociative memories provide scene analysis decisions, rather than merely enhanced output images. The analysis of heteroassociative memories has been given little attention. Heteroassociative memory performance and storage capacity are shown to be quite different from those of autoassociative memories, with much more dependence on the recollection vectors used and less dependence on M/N. This allows several different and preferable synthesis techniques to be considered for associative memories. These new associative memory synthesis techniques and new techniques to update associative memories are included. We also introduce a new SNR performance measure that is preferable to conventional noise standard deviation ratios.

Putting tools in the toolbox: Development of a free, open-source toolbox for quantitative image analysis of porous media.

NASA Astrophysics Data System (ADS)

Iltis, G.; Caswell, T. A.; Dill, E.; Wilkins, S.; Lee, W. K.

2014-12-01

X-ray tomographic imaging of porous media has proven to be a valuable tool for investigating and characterizing the physical structure and state of both natural and synthetic porous materials, including glass bead packs, ceramics, soil and rock. Given that most synchrotron facilities have user programs which grant academic researchers access to facilities and x-ray imaging equipment free of charge, a key limitation or hindrance for small research groups interested in conducting x-ray imaging experiments is the financial cost associated with post-experiment data analysis. While the cost of high performance computing hardware continues to decrease, expenses associated with licensing commercial software packages for quantitative image analysis continue to increase, with current prices being as high as $24,000 USD, for a single user license. As construction of the Nation's newest synchrotron accelerator nears completion, a significant effort is being made here at the National Synchrotron Light Source II (NSLS-II), Brookhaven National Laboratory (BNL), to provide an open-source, experiment-to-publication toolbox that reduces the financial and technical 'activation energy' required for performing sophisticated quantitative analysis of multidimensional porous media data sets, collected using cutting-edge x-ray imaging techniques. Implementation focuses on leveraging existing open-source projects and developing additional tools for quantitative analysis. We will present an overview of the software suite that is in development here at BNL including major design decisions, a demonstration of several test cases illustrating currently available quantitative tools for analysis and characterization of multidimensional porous media image data sets and plans for their future development.

Association Between Brain Gene Expression, DNA Methylation, and Alteration of Ex Vivo Magnetic Resonance Imaging Transverse Relaxation in Late-Life Cognitive Decline.

PubMed

Yu, Lei; Dawe, Robert J; Boyle, Patricia A; Gaiteri, Chris; Yang, Jingyun; Buchman, Aron S; Schneider, Julie A; Arfanakis, Konstantinos; De Jager, Philip L; Bennett, David A

2017-12-01

Alteration of ex vivo magnetic resonance imaging transverse relaxation is associated with late-life cognitive decline even after controlling for common neuropathologic conditions. However, the underlying neurobiology of this association is unknown. To investigate the association between brain gene expression, DNA methylation, and alteration of magnetic resonance imaging transverse relaxation in late-life cognitive decline. Data came from 2 community-based longitudinal cohort studies of aging and dementia, the Religious Orders Study, which began in 1993, and the Rush Memory and Aging Project, which began in 1997. All participants agreed to undergo annual clinical evaluations and to donate their brains after death. By October 24, 2016, a total of 1358 individuals had died and had brain autopsies that were approved by board-certified neuropathologists. Of those, 552 had undergone ex vivo imaging. The gene expression analysis was limited to 174 individuals with both imaging and brain RNA sequencing data. The DNA methylation analysis was limited to 225 individuals with both imaging and brain methylation data. Maps of ex vivo magnetic resonance imaging transverse relaxation were generated using fast spin echo imaging. The target was a composite measure of the transverse relaxation rate (R2) that was associated with cognitive decline after controlling for common neuropathologic conditions. Next-generation RNA sequencing and DNA methylation data were generated using frozen tissue from the dorsolateral prefrontal cortex. Genome-wide association analysis was used to investigate gene expression and, separately, DNA methylation for signals associated with the R2 measure. Of the 552 individuals with ex vivo imaging data, 394 were women and 158 were men, and the mean (SD) age at death was 90.4 (6.0) years. Four co-expressed genes (PADI2 [Ensembl ENSG00000117115], ZNF385A [Ensembl ENSG00000161642], PSD2 [Ensembl ENSG00000146005], and A2ML1 [Ensembl ENSG00000166535]) were identified, of which higher expressions were associated with slower R2. The association of R2 with cognitive decline was attenuated when the gene expression signals were added to the model, such that the mean (SE) coefficient of association was reduced from 0.028 (0.008) (P < .001) to 0.019 (0.009) (P = .03). The DNA methylation scan did not detect a genome-wide significant signal, but it revealed an anticorrelation between R2 and DNA methylation in many of the cytosine-guanine dinucleotides. Brain gene expression and DNA methylation dysregulations are implicated in the alteration of brain tissue properties associated with late-life cognitive decline above and beyond the influence of common neuropathologic conditions.

High-Performance Computational Analysis of Glioblastoma Pathology Images with Database Support Identifies Molecular and Survival Correlates.

PubMed

Kong, Jun; Wang, Fusheng; Teodoro, George; Cooper, Lee; Moreno, Carlos S; Kurc, Tahsin; Pan, Tony; Saltz, Joel; Brat, Daniel

2013-12-01

In this paper, we present a novel framework for microscopic image analysis of nuclei, data management, and high performance computation to support translational research involving nuclear morphometry features, molecular data, and clinical outcomes. Our image analysis pipeline consists of nuclei segmentation and feature computation facilitated by high performance computing with coordinated execution in multi-core CPUs and Graphical Processor Units (GPUs). All data derived from image analysis are managed in a spatial relational database supporting highly efficient scientific queries. We applied our image analysis workflow to 159 glioblastomas (GBM) from The Cancer Genome Atlas dataset. With integrative studies, we found statistics of four specific nuclear features were significantly associated with patient survival. Additionally, we correlated nuclear features with molecular data and found interesting results that support pathologic domain knowledge. We found that Proneural subtype GBMs had the smallest mean of nuclear Eccentricity and the largest mean of nuclear Extent, and MinorAxisLength. We also found gene expressions of stem cell marker MYC and cell proliferation maker MKI67 were correlated with nuclear features. To complement and inform pathologists of relevant diagnostic features, we queried the most representative nuclear instances from each patient population based on genetic and transcriptional classes. Our results demonstrate that specific nuclear features carry prognostic significance and associations with transcriptional and genetic classes, highlighting the potential of high throughput pathology image analysis as a complementary approach to human-based review and translational research.

Cell tracking for cell image analysis

NASA Astrophysics Data System (ADS)

Bise, Ryoma; Sato, Yoichi

2017-04-01

Cell image analysis is important for research and discovery in biology and medicine. In this paper, we present our cell tracking methods, which is capable of obtaining fine-grain cell behavior metrics. In order to address difficulties under dense culture conditions, where cell detection cannot be done reliably since cell often touch with blurry intercellular boundaries, we proposed two methods which are global data association and jointly solving cell detection and association. We also show the effectiveness of the proposed methods by applying the method to the biological researches.

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images.

PubMed

Lingley-Papadopoulos, Colleen A; Loew, Murray H; Zara, Jason M

2009-01-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images

NASA Astrophysics Data System (ADS)

Lingley-Papadopoulos, Colleen A.; Loew, Murray H.; Zara, Jason M.

2009-07-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Some uses of wavelets for imaging dynamic processes in live cochlear structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, J.

2007-09-01

A variety of image and signal processing algorithms based on wavelet filtering tools have been developed during the last few decades, that are well adapted to the experimental variability typically encountered in live biological microscopy. A number of processing tools are reviewed, that use wavelets for adaptive image restoration and for motion or brightness variation analysis by optical flow computation. The usefulness of these tools for biological imaging is illustrated in the context of the restoration of images of the inner ear and the analysis of cochlear motion patterns in two and three dimensions. I also report on recent work that aims at capturing fluorescence intensity changes associated with vesicle dynamics at synaptic zones of sensory hair cells. This latest application requires one to separate the intensity variations associated with the physiological process under study from the variations caused by motion of the observed structures. A wavelet optical flow algorithm for doing this is presented, and its effectiveness is demonstrated on artificial and experimental image sequences.

Imageability and semantic association in the representation and processing of event verbs.

PubMed

Xu, Xu; Kang, Chunyan; Guo, Taomei

2016-05-01

This study examined the relative salience of imageability (the degree to which a word evokes mental imagery) versus semantic association (the density of semantic network in which a word is embedded) in the representation and processing of four types of event verbs: sensory, cognitive, speech, and motor verbs. ERP responses were recorded, while 34 university students performed on a lexical decision task. Analysis focused primarily on amplitude differences across verb conditions within the N400 time window where activities are considered representing meaning activation. Variation in N400 amplitude across four types of verbs was found significantly associated with the level of imageability, but not the level of semantic association. The findings suggest imageability as a more salient factor relative to semantic association in the processing of these verbs. The role of semantic association and the representation of speech verbs are also discussed.

Image Processing Software

NASA Technical Reports Server (NTRS)

1990-01-01

The Ames digital image velocimetry technology has been incorporated in a commercially available image processing software package that allows motion measurement of images on a PC alone. The software, manufactured by Werner Frei Associates, is IMAGELAB FFT. IMAGELAB FFT is a general purpose image processing system with a variety of other applications, among them image enhancement of fingerprints and use by banks and law enforcement agencies for analysis of videos run during robberies.

Hyperspectral Imaging and Spectroscopy of Fluorescently Coupled Acyl-CoA: Cholesterol Acyltransferase in Insect Cells

NASA Technical Reports Server (NTRS)

Malak, H.; Mahtani, H.; Herman, P.; Vecer, J.; Lu, X.; Chang, T. Y.; Richmond, Robert C.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

A high-performance hyperspectral imaging module with high throughput of light suitable for low-intensity fluorescence microscopic imaging and subsequent analysis, including single-pixel-defined emission spectroscopy, was tested on Sf21 insect cells expressing green fluorescence associated with recombinant green fluorescent protein linked or not with the membrane protein acyl-CoA:cholesterol acyltransferase. The imager utilized the phenomenon of optical activity as a new technique providing information over a spectral range of 220-1400 nm, and was inserted between the microscope and an 8-bit CCD video-rate camera. The resulting fluorescence image did not introduce observable image aberrations. The images provided parallel acquisition of well resolved concurrent spatial and spectral information such that fluorescence associated with green fluorescent protein alone was demonstrated to be diffuse within the Sf21 insect cell, and that green fluorescence associated with the membrane protein was shown to be specifically concentrated within regions of the cell cytoplasm. Emission spectra analyzed from different regions of the fluorescence image showed blue shift specific for the regions of concentration associated with the membrane protein.

Assessment of Prospectively Assigned Likert Scores for Targeted Magnetic Resonance Imaging-Transrectal Ultrasound Fusion Biopsies in Patients with Suspected Prostate Cancer.

PubMed

Costa, Daniel N; Lotan, Yair; Rofsky, Neil M; Roehrborn, Claus; Liu, Alexander; Hornberger, Brad; Xi, Yin; Francis, Franto; Pedrosa, Ivan

2016-01-01

We assess the performance of prospectively assigned magnetic resonance imaging based Likert scale scores for the detection of clinically significant prostate cancer, and analyze the pre-biopsy imaging variables associated with increased cancer detection using targeted magnetic resonance imaging-transrectal ultrasound fusion biopsy. In this retrospective review of prospectively generated data including men with abnormal multiparametric prostate magnetic resonance imaging (at least 1 Likert score 3 or greater lesion) who underwent subsequent targeted magnetic resonance imaging-transrectal ultrasound fusion biopsy, we determined the association between different imaging variables (Likert score, lesion size, lesion location, prostate volume, radiologist experience) and targeted biopsy positivity rate. We also compared the detection of clinically significant cancer according to Likert scale scores. Tumors with high volume (50% or more of any core) Gleason score 3+4 or any tumor with greater Gleason score were considered clinically significant. Each lesion served as the elementary unit for analysis. We used logistic regression for univariate and multivariate (stepwise selection) analysis to assess for an association between targeted biopsy positivity rate and each tested variable. The relationship between Likert scale and Gleason score was evaluated using the Spearman correlation coefficient. A total of 161 men with 244 lesions met the study eligibility criteria. Targeted biopsies diagnosed cancer in 41% (66 of 161) of the men and 41% (99 of 244) of the lesions. The Likert score was the strongest predictor of targeted biopsy positivity (OR 3.7, p <0.0001). Other imaging findings associated with a higher targeted biopsy positivity rate included smaller prostate volume (OR 0.7, p <0.01), larger lesion size (OR 2.2, p <0.001) and anterior location (OR 2.0, p=0.01). On multiple logistic regression analysis Likert score, lesion size and prostate volume were significant predictors of targeted biopsy positivity. Higher Likert scores were also associated with increased detection of clinically significant tumors (p <0.0001). The Likert scale score used to convey the degree of suspicion on multiparametric magnetic resonance imaging is the strongest predictor of targeted biopsy positivity and of the presence of clinically significant tumor. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue

PubMed Central

Bjornsson, Christopher S; Lin, Gang; Al-Kofahi, Yousef; Narayanaswamy, Arunachalam; Smith, Karen L; Shain, William; Roysam, Badrinath

2009-01-01

Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic ‘divide and conquer’ methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick (~100 μm) slices of rat brain tissue were labeled using 3 – 5 fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features were used to classify astrocytes, microglia, neurons, and endothelial cells. Associations among cells and between cells and vasculature were computed and represented as graphical networks to enable further analysis. The automated results were validated using a graphical interface that permits investigator inspection and corrective editing of each cell in 3D. Nuclear counting accuracy was >89%, and cell classification accuracy ranged from 81–92% depending on cell type. We present a software system named FARSIGHT implementing our methodology. Its output is a detailed XML file containing measurements that may be used for diverse quantitative hypothesis-driven and exploratory studies of the central nervous system. PMID:18294697

[Perception of odor quality by Free Image-Association Test].

PubMed

Ueno, Y

1992-10-01

A method was devised for evaluating odor quality. Subjects were requested to freely describe the images elicited by smelling odors. This test was named the "Free Image-Association Test (FIT)". The test was applied for 20 flavors of various foods, five odors from the standards of T&T olfactometer (Japanese standard olfactory test), butter of yak milk, and incense from Lamaism temples. The words for expressing imagery were analyzed by multidimensional scaling and cluster analysis. Seven clusters of odors were obtained. The feature of these clusters were quite similar to that of primary odors which have been suggested by previous studies. However, the clustering of odors can not be explained on the basis of the primary-odor theory, but the information processing theory originally proposed by Miller (1956). These results support the usefulness of the Free Image-Association Test for investigating odor perception based on the images associated with odors.

Which patellofemoral joint imaging features are associated with patellofemoral pain? Systematic review and meta-analysis.

PubMed

Drew, B T; Redmond, A C; Smith, T O; Penny, F; Conaghan, P G

2016-02-01

To review the association between patellofemoral joint (PFJ) imaging features and patellofemoral pain (PFP). A systematic review of the literature from AMED, CiNAHL, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, PEDro, EMBASE and SPORTDiscus was undertaken from their inception to September 2014. Studies were eligible if they used magnetic resonance imaging (MRI), computed tomography (CT), ultrasound (US) or X-ray (XR) to compare PFJ features between a PFP group and an asymptomatic control group in people <45 years of age. A pooled meta-analysis was conducted and data was interpreted using a best evidence synthesis. Forty studies (all moderate to high quality) describing 1043 people with PFP and 839 controls were included. Two features were deemed to have a large standardised mean difference (SMD) based on meta-analysis: an increased MRI bisect offset at 0° knee flexion under load (0.99; 95% CI: 0.49, 1.49) and an increased CT congruence angle at 15° knee flexion, both under load (1.40 95% CI: 0.04, 2.76) and without load (1.24; 95% CI: 0.37, 2.12). A medium SMD was identified for MRI patella tilt and patellofemoral contact area. Limited evidence was found to support the association of other imaging features with PFP. A sensitivity analysis showed an increase in the SMD for patella bisect offset at 0° knee flexion (1.91; 95% CI: 1.31, 2.52) and patella tilt at 0° knee flexion (0.99; 95% CI: 0.47, 1.52) under full weight bearing. Certain PFJ imaging features were associated with PFP. Future interventional strategies may be targeted at these features. CRD 42014009503. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Infrared Spectroscopic Imaging of Latent Fingerprints and Associated Forensic Evidence

PubMed Central

Chen, Tsoching; Schultz, Zachary D.; Levin, Ira W.

2011-01-01

Fingerprints reflecting a specific chemical history, such as exposure to explosives, are clearly distinguished from overlapping, and interfering latent fingerprints using infrared spectroscopic imaging techniques and multivariate analysis. PMID:19684917

Next-generation technologies for spatial proteomics: Integrating ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR imaging mass spectrometry for protein analysis.

PubMed

Spraggins, Jeffrey M; Rizzo, David G; Moore, Jessica L; Noto, Michael J; Skaar, Eric P; Caprioli, Richard M

2016-06-01

MALDI imaging mass spectrometry is a powerful analytical tool enabling the visualization of biomolecules in tissue. However, there are unique challenges associated with protein imaging experiments including the need for higher spatial resolution capabilities, improved image acquisition rates, and better molecular specificity. Here we demonstrate the capabilities of ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR IMS platforms as they relate to these challenges. High spatial resolution MALDI-TOF protein images of rat brain tissue and cystic fibrosis lung tissue were acquired at image acquisition rates >25 pixels/s. Structures as small as 50 μm were spatially resolved and proteins associated with host immune response were observed in cystic fibrosis lung tissue. Ultra-high speed MALDI-TOF enables unique applications including megapixel molecular imaging as demonstrated for lipid analysis of cystic fibrosis lung tissue. Additionally, imaging experiments using MALDI FTICR IMS were shown to produce data with high mass accuracy (<5 ppm) and resolving power (∼75 000 at m/z 5000) for proteins up to ∼20 kDa. Analysis of clear cell renal cell carcinoma using MALDI FTICR IMS identified specific proteins localized to healthy tissue regions, within the tumor, and also in areas of increased vascularization around the tumor. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantification of Abdominal Fat in Obese and Healthy Adolescents Using 3 Tesla Magnetic Resonance Imaging and Free Software for Image Analysis.

PubMed

Eloi, Juliana Cristina; Epifanio, Matias; de Gonçalves, Marília Maia; Pellicioli, Augusto; Vieira, Patricia Froelich Giora; Dias, Henrique Bregolin; Bruscato, Neide; Soder, Ricardo Bernardi; Santana, João Carlos Batista; Mouzaki, Marialena; Baldisserotto, Matteo

2017-01-01

Computed tomography, which uses ionizing radiation and expensive software packages for analysis of scans, can be used to quantify abdominal fat. The objective of this study is to measure abdominal fat with 3T MRI using free software for image analysis and to correlate these findings with anthropometric and laboratory parameters in adolescents. This prospective observational study included 24 overweight/obese and 33 healthy adolescents (mean age 16.55 years). All participants underwent abdominal MRI exams. Visceral and subcutaneous fat area and percentage were correlated with anthropometric parameters, lipid profile, glucose metabolism, and insulin resistance. Student's t test and Mann-Whitney's test was applied. Pearson's chi-square test was used to compare proportions. To determine associations Pearson's linear correlation or Spearman's correlation were used. In both groups, waist circumference (WC) was associated with visceral fat area (P = 0.001 and P = 0.01 respectively), and triglycerides were associated with fat percentage (P = 0.046 and P = 0.071 respectively). In obese individuals, total cholesterol/HDL ratio was associated with visceral fat area (P = 0.03) and percentage (P = 0.09), and insulin and HOMA-IR were associated with visceral fat area (P = 0.001) and percentage (P = 0.005). 3T MRI can provide reliable and good quality images for quantification of visceral and subcutaneous fat by using a free software package. The results demonstrate that WC is a good predictor of visceral fat in obese adolescents and visceral fat area is associated with total cholesterol/HDL ratio, insulin and HOMA-IR.

Study of the structure changes caused by volcanic activity in Mexico applying the lineament analysis to the Aster (Terra) satellite data.

NASA Astrophysics Data System (ADS)

Arellano-Baeza, A. A.; Garcia, R. V.; Trejo-Soto, M.; Molina-Sauceda, E.

Mexico is one of the most volcanically active regions in North America Volcanic activity in central Mexico is associated with the subduction of the Cocos and Rivera plates beneath the North American plate Periods of enhanced microseismic activity associated with the volcanic activity of the Colima and Popocapetl volcanoes are compared to some periods of low microseismic activity We detected changes in the number and orientation of lineaments associated with the microseismic activity due to lineament analysis of a temporal sequence of high resolution satellite images of both volcanoes 15 m resolution multispectral images provided by the ASTER VNIR instrument were used The Lineament Extraction and Stripes Statistic Analysis LESSA software package was employed for the lineament extraction

Application of ERTS-1 imagery to the harvest model of the US Menhaden fishery

NASA Technical Reports Server (NTRS)

Maughan, P. M.; Marmelstein, A. D.; Temple, O. R.

1973-01-01

Preliminary results of an experiment to demonstrate the utility of ERTS-1 imagery for providing significant information to the harvest model of the menhaden industry are reported. Fisheries and related environmental data were obtained discontinuously throughout the 1973 menhaden (a surface schooling, coastal species) fishing season in Mississippi Sound. The unexpected complexity of the physical environment in Mississippi Sound precluded simplistic analysis of fish/environment relationships. Preliminary indications are that an association does exist between fish availability and differences in water transparency (turbidity) within the Sound. A clearer relationship is developing between major turbid features, imaged by ERTS-1 and location of successful fishing attempts. On all occasions where relatively cloudfree ERTS-1 overflight days coincided with fishery activity, overlays of catch location of ERTS-1 images show an association of school position with interfaces between imaged turbid features. Analysis is currently underway to determine persistence of such associations in an attempt to define minimum satellite return time necessary to maintain continuity of associations.

Sex-role orientation associations with college students' body-image preferences.

PubMed

Johnson, H Durell; Lamont, Janine; Monacelli, Jennifer; Vojick, Alex

2004-12-01

Sex roles dictate acceptable attitudes and preferences for men and women. Further, perception of ideal body type is one attitude and preference that may be associated with sex-role orientation. Therefore, the current study examined the association between sex-role orientation and men's and women's reports of their preferred body type and their views of others' preferred body type for men and women. Responses from 172 university students indicated sex-role associations with participants' personal body-type preferences and participants' perceptions of the body types others prefer. Analysis indicates that a more masculine sex-role orientation was associated with men's and women's perceptions of larger ideal body images. Results are discussed in terms of the association between sex-role orientation and possible susceptibility to societal standards of ideal body images.

Radiomic analysis in prediction of Human Papilloma Virus status.

PubMed

Yu, Kaixian; Zhang, Youyi; Yu, Yang; Huang, Chao; Liu, Rongjie; Li, Tengfei; Yang, Liuqing; Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Zhu, Hongtu

2017-12-01

Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oropharynx cancer patients. We designed a statistical radiomics approach analyzing CT images to predict HPV status. Various radiomics features were extracted from CT scans, and analyzed using statistical feature selection and prediction methods. Our approach ranked the highest in the 2016 Medical Image Computing and Computer Assisted Intervention (MICCAI) grand challenge: Oropharynx Cancer (OPC) Radiomics Challenge, Human Papilloma Virus (HPV) Status Prediction. Further analysis on the most relevant radiomic features distinguishing HPV positive and negative subjects suggested that HPV positive patients usually have smaller and simpler tumors.

Techniques in helical scanning, dynamic imaging and image segmentation for improved quantitative analysis with X-ray micro-CT

NASA Astrophysics Data System (ADS)

Sheppard, Adrian; Latham, Shane; Middleton, Jill; Kingston, Andrew; Myers, Glenn; Varslot, Trond; Fogden, Andrew; Sawkins, Tim; Cruikshank, Ron; Saadatfar, Mohammad; Francois, Nicolas; Arns, Christoph; Senden, Tim

2014-04-01

This paper reports on recent advances at the micro-computed tomography facility at the Australian National University. Since 2000 this facility has been a significant centre for developments in imaging hardware and associated software for image reconstruction, image analysis and image-based modelling. In 2010 a new instrument was constructed that utilises theoretically-exact image reconstruction based on helical scanning trajectories, allowing higher cone angles and thus better utilisation of the available X-ray flux. We discuss the technical hurdles that needed to be overcome to allow imaging with cone angles in excess of 60°. We also present dynamic tomography algorithms that enable the changes between one moment and the next to be reconstructed from a sparse set of projections, allowing higher speed imaging of time-varying samples. Researchers at the facility have also created a sizeable distributed-memory image analysis toolkit with capabilities ranging from tomographic image reconstruction to 3D shape characterisation. We show results from image registration and present some of the new imaging and experimental techniques that it enables. Finally, we discuss the crucial question of image segmentation and evaluate some recently proposed techniques for automated segmentation.

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

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

Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less

APPLEPIPS /Apple Personal Image Processing System/ - An interactive digital image processing system for the Apple II microcomputer

NASA Technical Reports Server (NTRS)

Masuoka, E.; Rose, J.; Quattromani, M.

1981-01-01

Recent developments related to microprocessor-based personal computers have made low-cost digital image processing systems a reality. Image analysis systems built around these microcomputers provide color image displays for images as large as 256 by 240 pixels in sixteen colors. Descriptive statistics can be computed for portions of an image, and supervised image classification can be obtained. The systems support Basic, Fortran, Pascal, and assembler language. A description is provided of a system which is representative of the new microprocessor-based image processing systems currently on the market. While small systems may never be truly independent of larger mainframes, because they lack 9-track tape drives, the independent processing power of the microcomputers will help alleviate some of the turn-around time problems associated with image analysis and display on the larger multiuser systems.

Imaging mass spectrometry data reduction: automated feature identification and extraction.

PubMed

McDonnell, Liam A; van Remoortere, Alexandra; de Velde, Nico; van Zeijl, René J M; Deelder, André M

2010-12-01

Imaging MS now enables the parallel analysis of hundreds of biomolecules, spanning multiple molecular classes, which allows tissues to be described by their molecular content and distribution. When combined with advanced data analysis routines, tissues can be analyzed and classified based solely on their molecular content. Such molecular histology techniques have been used to distinguish regions with differential molecular signatures that could not be distinguished using established histologic tools. However, its potential to provide an independent, complementary analysis of clinical tissues has been limited by the very large file sizes and large number of discrete variables associated with imaging MS experiments. Here we demonstrate data reduction tools, based on automated feature identification and extraction, for peptide, protein, and lipid imaging MS, using multiple imaging MS technologies, that reduce data loads and the number of variables by >100×, and that highlight highly-localized features that can be missed using standard data analysis strategies. It is then demonstrated how these capabilities enable multivariate analysis on large imaging MS datasets spanning multiple tissues. Copyright © 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

Perceptions of Public Breastfeeding Images and Their Association With Breastfeeding Knowledge and Attitudes Among an Internet Panel of Men Ages 21-44 in the United States.

PubMed

Magnusson, Brianna M; Thackeray, Callie R; Van Wagenen, Sarah A; Davis, Siena F; Richards, Rickelle; Merrill, Ray M

2017-02-01

Men's attitudes toward public breastfeeding may influence a woman's decisions about breastfeeding and her perceived comfort with public breastfeeding. Research aim: This study aimed to evaluate factors associated with men's visual perception of images of public breastfeeding. A 95-item online survey was administered to 502 U.S. men ages 21 to 44. Respondents were presented with four images of women breastfeeding and asked to evaluate agreement with 15 adjectives describing each image. Based on factor analysis, 13 of these adjectives were combined to create the Breastfeeding Images Scale for each image. An 8-item Situational Statements Scale and the 17-item Iowa Infant Feeding Attitude Scale (IIFAS) were used to assess breastfeeding knowledge and attitudes. Multiple regression was used to evaluate the association between breastfeeding attitudes and knowledge and the Breastfeeding Images Scale. The image depicting a woman breastfeeding privately at home had the highest mean score of 71.95, 95% confidence interval (CI) [70.69, 73.22], on the Breastfeeding Images Scale, compared with 61.93, 95% CI [60.51, 63.36], for the image of a woman breastfeeding in a public setting. The overall mean scale score for the IIFAS was 56.99, 95% CI [56.27, 57.70], and for the Situational Statements Scale was 28.80, 95% CI [27.92, 29.69]. For all images, increasing breastfeeding knowledge and attitudes measured by the IIFAS and the Situational Statements Scale were associated with a more positive perception of the image. Images of public breastfeeding are viewed less favorably by men in the sample than are images of private breastfeeding. Knowledge and attitudes toward breastfeeding are positively associated with perception of breastfeeding images.

GiA Roots: software for the high throughput analysis of plant root system architecture.

PubMed

Galkovskyi, Taras; Mileyko, Yuriy; Bucksch, Alexander; Moore, Brad; Symonova, Olga; Price, Charles A; Topp, Christopher N; Iyer-Pascuzzi, Anjali S; Zurek, Paul R; Fang, Suqin; Harer, John; Benfey, Philip N; Weitz, Joshua S

2012-07-26

Characterizing root system architecture (RSA) is essential to understanding the development and function of vascular plants. Identifying RSA-associated genes also represents an underexplored opportunity for crop improvement. Software tools are needed to accelerate the pace at which quantitative traits of RSA are estimated from images of root networks. We have developed GiA Roots (General Image Analysis of Roots), a semi-automated software tool designed specifically for the high-throughput analysis of root system images. GiA Roots includes user-assisted algorithms to distinguish root from background and a fully automated pipeline that extracts dozens of root system phenotypes. Quantitative information on each phenotype, along with intermediate steps for full reproducibility, is returned to the end-user for downstream analysis. GiA Roots has a GUI front end and a command-line interface for interweaving the software into large-scale workflows. GiA Roots can also be extended to estimate novel phenotypes specified by the end-user. We demonstrate the use of GiA Roots on a set of 2393 images of rice roots representing 12 genotypes from the species Oryza sativa. We validate trait measurements against prior analyses of this image set that demonstrated that RSA traits are likely heritable and associated with genotypic differences. Moreover, we demonstrate that GiA Roots is extensible and an end-user can add functionality so that GiA Roots can estimate novel RSA traits. In summary, we show that the software can function as an efficient tool as part of a workflow to move from large numbers of root images to downstream analysis.

Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.

PubMed

Wu, Jia; Gong, Guanghua; Cui, Yi; Li, Ruijiang

2016-11-01

To predict pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). In this Institutional Review Board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using 3T DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with high temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast washout were statistically significant (P < 0.05) after correcting for multiple testing, with area under the receiver operating characteristic (ROC) curve (AUC) or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (P = 0.002) in leave-one-out cross-validation. This improved upon conventional imaging predictors such as tumor volume (AUC = 0.53) and texture features based on whole-tumor analysis (AUC = 0.65). The heterogeneity of the tumor subregion associated with fast washout on DCE-MRI predicted pathological response to NAC in breast cancer. J. Magn. Reson. Imaging 2016;44:1107-1115. © 2016 International Society for Magnetic Resonance in Medicine.

Microvessel prediction in H&E Stained Pathology Images using fully convolutional neural networks.

PubMed

Yi, Faliu; Yang, Lin; Wang, Shidan; Guo, Lei; Huang, Chenglong; Xie, Yang; Xiao, Guanghua

2018-02-27

Pathological angiogenesis has been identified in many malignancies as a potential prognostic factor and target for therapy. In most cases, angiogenic analysis is based on the measurement of microvessel density (MVD) detected by immunostaining of CD31 or CD34. However, most retrievable public data is generally composed of Hematoxylin and Eosin (H&E)-stained pathology images, for which is difficult to get the corresponding immunohistochemistry images. The role of microvessels in H&E stained images has not been widely studied due to their complexity and heterogeneity. Furthermore, identifying microvessels manually for study is a labor-intensive task for pathologists, with high inter- and intra-observer variation. Therefore, it is important to develop automated microvessel-detection algorithms in H&E stained pathology images for clinical association analysis. In this paper, we propose a microvessel prediction method using fully convolutional neural networks. The feasibility of our proposed algorithm is demonstrated through experimental results on H&E stained images. Furthermore, the identified microvessel features were significantly associated with the patient clinical outcomes. This is the first study to develop an algorithm for automated microvessel detection in H&E stained pathology images.

Effect of Quantitative Nuclear Image Features on Recurrence of Ductal Carcinoma In Situ (DCIS) of the Breast

PubMed Central

Axelrod, David E.; Miller, Naomi A.; Lickley, H. Lavina; Qian, Jin; Christens-Barry, William A.; Yuan, Yan; Fu, Yuejiao; Chapman, Judith-Anne W.

2008-01-01

Background Nuclear grade has been associated with breast DCIS recurrence and progression to invasive carcinoma; however, our previous study of a cohort of patients with breast DCIS did not find such an association with outcome. Fifty percent of patients had heterogeneous DCIS with more than one nuclear grade. The aim of the current study was to investigate the effect of quantitative nuclear features assessed with digital image analysis on ipsilateral DCIS recurrence. Methods Hematoxylin and eosin stained slides for a cohort of 80 patients with primary breast DCIS were reviewed and two fields with representative grade (or grades) were identified by a Pathologist and simultaneously used for acquisition of digital images for each field. Van Nuys worst nuclear grade was assigned, as was predominant grade, and heterogeneous grading when present. Patients were grouped by heterogeneity of their nuclear grade: Group A: nuclear grade 1 only, nuclear grades 1 and 2, or nuclear grade 2 only (32 patients), Group B: nuclear grades 1, 2 and 3, or nuclear grades 2 and 3 (31 patients), Group 3: nuclear grade 3 only (17 patients). Nuclear fine structure was assessed by software which captured thirty-nine nuclear feature values describing nuclear morphometry, densitometry, and texture. Step-wise forward Cox regressions were performed with previous clinical and pathologic factors, and the new image analysis features. Results Duplicate measurements were similar for 89.7% to 97.4% of assessed image features. The rate of correct classification of nuclear grading with digital image analysis features was similar in the two fields, and pooled assessment across both fields. In the pooled assessment, a discriminant function with one nuclear morphometric and one texture feature was significantly (p = 0.001) associated with nuclear grading, and provided correct jackknifed classification of a patient’s nuclear grade for Group A (78.1%), Group B (48.4%), and Group C (70.6%). The factors significantly associated with DCIS recurrence were those previously found, type of initial presentation (p = 0.03) and amount of parenchymal involvement (p = 0.05), along with the morphometry image feature of ellipticity (p = 0.04). Conclusion Analysis of nuclear features measured by image cytometry may contribute to the classification and prognosis of breast DCIS patients with more than one nuclear grade. PMID:18779878

Continuing Medical Education Speakers with High Evaluation Scores Use more Image-based Slides.

PubMed

Ferguson, Ian; Phillips, Andrew W; Lin, Michelle

2017-01-01

Although continuing medical education (CME) presentations are common across health professions, it is unknown whether slide design is independently associated with audience evaluations of the speaker. Based on the conceptual framework of Mayer's theory of multimedia learning, this study aimed to determine whether image use and text density in presentation slides are associated with overall speaker evaluations. This retrospective analysis of six sequential CME conferences (two annual emergency medicine conferences over a three-year period) used a mixed linear regression model to assess whether post-conference speaker evaluations were associated with image fraction (percentage of image-based slides per presentation) and text density (number of words per slide). A total of 105 unique lectures were given by 49 faculty members, and 1,222 evaluations (70.1% response rate) were available for analysis. On average, 47.4% (SD=25.36) of slides had at least one educationally-relevant image (image fraction). Image fraction significantly predicted overall higher evaluation scores [F(1, 100.676)=6.158, p=0.015] in the mixed linear regression model. The mean (SD) text density was 25.61 (8.14) words/slide but was not a significant predictor [F(1, 86.293)=0.55, p=0.815]. Of note, the individual speaker [χ 2 (1)=2.952, p=0.003] and speaker seniority [F(3, 59.713)=4.083, p=0.011] significantly predicted higher scores. This is the first published study to date assessing the linkage between slide design and CME speaker evaluations by an audience of practicing clinicians. The incorporation of images was associated with higher evaluation scores, in alignment with Mayer's theory of multimedia learning. Contrary to this theory, however, text density showed no significant association, suggesting that these scores may be multifactorial. Professional development efforts should focus on teaching best practices in both slide design and presentation skills.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA–DTI working group

PubMed Central

Jahanshad, Neda; Kochunov, Peter; Sprooten, Emma; Mandl, René C.; Nichols, Thomas E.; Almassy, Laura; Blangero, John; Brouwer, Rachel M.; Curran, Joanne E.; de Zubicaray, Greig I.; Duggirala, Ravi; Fox, Peter T.; Hong, L. Elliot; Landman, Bennett A.; Martin, Nicholas G.; McMahon, Katie L.; Medland, Sarah E.; Mitchell, Braxton D.; Olvera, Rene L.; Peterson, Charles P.; Starr, John M.; Sussmann, Jessika E.; Toga, Arthur W.; Wardlaw, Joanna M.; Wright, Margaret J.; Hulshoff Pol, Hilleke E.; Bastin, Mark E.; McIntosh, Andrew M.; Deary, Ian J.; Thompson, Paul M.; Glahn, David C.

2013-01-01

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA–DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18–85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/). PMID:23629049

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Associative architecture for image processing

NASA Astrophysics Data System (ADS)

Adar, Rutie; Akerib, Avidan

1997-09-01

This article presents a new generation in parallel processing architecture for real-time image processing. The approach is implemented in a real time image processor chip, called the XiumTM-2, based on combining a fully associative array which provides the parallel engine with a serial RISC core on the same die. The architecture is fully programmable and can be programmed to implement a wide range of color image processing, computer vision and media processing functions in real time. The associative part of the chip is based on patented pending methodology of Associative Computing Ltd. (ACL), which condenses 2048 associative processors, each of 128 'intelligent' bits. Each bit can be a processing bit or a memory bit. At only 33 MHz and 0.6 micron manufacturing technology process, the chip has a computational power of 3 billion ALU operations per second and 66 billion string search operations per second. The fully programmable nature of the XiumTM-2 chip enables developers to use ACL tools to write their own proprietary algorithms combined with existing image processing and analysis functions from ACL's extended set of libraries.

Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data—a preliminary study

NASA Astrophysics Data System (ADS)

Xia, Wei; Chen, Ying; Zhang, Rui; Yan, Zhuangzhi; Zhou, Xiaobo; Zhang, Bo; Gao, Xin

2018-02-01

Our objective was to identify prognostic imaging biomarkers for hepatocellular carcinoma in contrast-enhanced computed tomography (CECT) with biological interpretations by associating imaging features and gene modules. We retrospectively analyzed 371 patients who had gene expression profiles. For the 38 patients with CECT imaging data, automatic intra-tumor partitioning was performed, resulting in three spatially distinct subregions. We extracted a total of 37 quantitative imaging features describing intensity, geometry, and texture from each subregion. Imaging features were selected after robustness and redundancy analysis. Gene modules acquired from clustering were chosen for their prognostic significance. By constructing an association map between imaging features and gene modules with Spearman rank correlations, the imaging features that significantly correlated with gene modules were obtained. These features were evaluated with Cox’s proportional hazard models and Kaplan-Meier estimates to determine their prognostic capabilities for overall survival (OS). Eight imaging features were significantly correlated with prognostic gene modules, and two of them were associated with OS. Among these, the geometry feature volume fraction of the subregion, which was significantly correlated with all prognostic gene modules representing cancer-related interpretation, was predictive of OS (Cox p  =  0.022, hazard ratio  =  0.24). The texture feature cluster prominence in the subregion, which was correlated with the prognostic gene module representing lipid metabolism and complement activation, also had the ability to predict OS (Cox p  =  0.021, hazard ratio  =  0.17). Imaging features depicting the volume fraction and textural heterogeneity in subregions have the potential to be predictors of OS with interpretable biological meaning.

The impact of early shame memories in Binge Eating Disorder: The mediator effect of current body image shame and cognitive fusion.

PubMed

Duarte, Cristiana; Pinto-Gouveia, José

2017-12-01

This study examined the phenomenology of shame experiences from childhood and adolescence in a sample of women with Binge Eating Disorder. Moreover, a path analysis was investigated testing whether the association between shame-related memories which are traumatic and central to identity, and binge eating symptoms' severity, is mediated by current external shame, body image shame and body image cognitive fusion. Participants in this study were 114 patients, who were assessed through the Eating Disorder Examination and the Shame Experiences Interview, and through self-report measures of external shame, body image shame, body image cognitive fusion and binge eating symptoms. Shame experiences where physical appearance was negatively commented or criticized by others were the most frequently recalled. A path analysis showed a good fit between the hypothesised mediational model and the data. The traumatic and centrality qualities of shame-related memories predicted current external shame, especially body image shame. Current shame feelings were associated with body image cognitive fusion, which, in turn, predicted levels of binge eating symptomatology. Findings support the relevance of addressing early shame-related memories and negative affective and self-evaluative experiences, namely related to body image, in the understanding and management of binge eating. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative Immunofluorescence Analysis of Nucleolus-Associated Chromatin.

PubMed

Dillinger, Stefan; Németh, Attila

2016-01-01

The nuclear distribution of eu- and heterochromatin is nonrandom, heterogeneous, and dynamic, which is mirrored by specific spatiotemporal arrangements of histone posttranslational modifications (PTMs). Here we describe a semiautomated method for the analysis of histone PTM localization patterns within the mammalian nucleus using confocal laser scanning microscope images of fixed, immunofluorescence stained cells as data source. The ImageJ-based process includes the segmentation of the nucleus, furthermore measurements of total fluorescence intensities, the heterogeneity of the staining, and the frequency of the brightest pixels in the region of interest (ROI). In the presented image analysis pipeline, the perinucleolar chromatin is selected as primary ROI, and the nuclear periphery as secondary ROI.

Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging

PubMed Central

Lauzon, Carolyn B.; Asman, Andrew J.; Esparza, Michael L.; Burns, Scott S.; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W.; Davis, Nicole; Cutting, Laurie E.; Landman, Bennett A.

2013-01-01

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible. PMID:23637895

Simultaneous analysis and quality assurance for diffusion tensor imaging.

PubMed

Lauzon, Carolyn B; Asman, Andrew J; Esparza, Michael L; Burns, Scott S; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W; Davis, Nicole; Cutting, Laurie E; Landman, Bennett A

2013-01-01

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible.

Prostate cancer localization with endorectal MR imaging and MR spectroscopic imaging: effect of clinical data on reader accuracy.

PubMed

Dhingsa, Rajpal; Qayyum, Aliya; Coakley, Fergus V; Lu, Ying; Jones, Kirk D; Swanson, Mark G; Carroll, Peter R; Hricak, Hedvig; Kurhanewicz, John

2004-01-01

To determine the effect of digital rectal examination findings, sextant biopsy results, and prostate-specific antigen (PSA) levels on reader accuracy in the localization of prostate cancer with endorectal magnetic resonance (MR) imaging and MR spectroscopic imaging. This was a retrospective study of 37 patients (mean age, 57 years) with biopsy-proved prostate cancer. Transverse T1-weighted, transverse high-spatial-resolution, and coronal T2-weighted MR images and MR spectroscopic images were obtained. Two independent readers, unaware of clinical data, recorded the size and location of suspicious peripheral zone tumor nodules on a standardized diagram of the prostate. Readers also recorded their degree of diagnostic confidence for each nodule on a five-point scale. Both readers repeated this interpretation with knowledge of rectal examination findings, sextant biopsy results, and PSA level. Step-section histopathologic findings were the reference standard. Logistic regression analysis with generalized estimating equations was used to correlate tumor detection with clinical data, and alternative free-response receiver operating characteristic (AFROC) curve analysis was used to examine the overall effect of clinical data on all positive results. Fifty-one peripheral zone tumor nodules were identified at histopathologic evaluation. Logistic regression analysis showed awareness of clinical data significantly improved tumor detection rate (P <.02) from 15 to 19 nodules for reader 1 and from 13 to 19 nodules for reader 2 (27%-37% overall) by using both size and location criteria. AFROC analysis showed no significant change in overall reader performance because there was an associated increase in the number of false-positive findings with awareness of clinical data, from 11 to 21 for reader 1 and from 16 to 25 for reader 2. Awareness of clinical data significantly improves reader detection of prostate cancer nodules with endorectal MR imaging and MR spectroscopic imaging, but there is no overall change in reader accuracy, because of an associated increase in false-positive findings. A stricter definition of a true-positive result is associated with reduced sensitivity for prostate cancer nodule detection. Copyright RSNA, 2004

Digital image processing of bone - Problems and potentials

NASA Technical Reports Server (NTRS)

Morey, E. R.; Wronski, T. J.

1980-01-01

The development of a digital image processing system for bone histomorphometry and fluorescent marker monitoring is discussed. The system in question is capable of making measurements of UV or light microscope features on a video screen with either video or computer-generated images, and comprises a microscope, low-light-level video camera, video digitizer and display terminal, color monitor, and PDP 11/34 computer. Capabilities demonstrated in the analysis of an undecalcified rat tibia include the measurement of perimeter and total bone area, and the generation of microscope images, false color images, digitized images and contoured images for further analysis. Software development will be based on an existing software library, specifically the mini-VICAR system developed at JPL. It is noted that the potentials of the system in terms of speed and reliability far exceed any problems associated with hardware and software development.

Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images.

PubMed

Pang, Jincheng; Özkucur, Nurdan; Ren, Michael; Kaplan, David L; Levin, Michael; Miller, Eric L

2015-11-01

Phase Contrast Microscopy (PCM) is an important tool for the long term study of living cells. Unlike fluorescence methods which suffer from photobleaching of fluorophore or dye molecules, PCM image contrast is generated by the natural variations in optical index of refraction. Unfortunately, the same physical principles which allow for these studies give rise to complex artifacts in the raw PCM imagery. Of particular interest in this paper are neuron images where these image imperfections manifest in very different ways for the two structures of specific interest: cell bodies (somas) and dendrites. To address these challenges, we introduce a novel parametric image model using the level set framework and an associated variational approach which simultaneously restores and segments this class of images. Using this technique as the basis for an automated image analysis pipeline, results for both the synthetic and real images validate and demonstrate the advantages of our approach.

Merging dietary assessment with the adolescent lifestyle.

PubMed

Schap, T E; Zhu, F; Delp, E J; Boushey, C J

2014-01-01

The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera [e.g. Apple iPhone, Apple iPod Touch (Apple Inc., Cupertino, CA, USA); Nexus One (Google, Mountain View, CA, USA)]. Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis (i.e. segmentation, feature extraction and classification), which allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies to provide a detailed diet analysis for use in epidemiological or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarises the system design and the evidence-based development of image-based methods for dietary assessment among children. © 2013 The Authors Journal of Human Nutrition and Dietetics © 2013 The British Dietetic Association Ltd.

Drusen regression is associated with local changes in fundus autofluorescence in intermediate age-related macular degeneration.

PubMed

Toy, Brian C; Krishnadev, Nupura; Indaram, Maanasa; Cunningham, Denise; Cukras, Catherine A; Chew, Emily Y; Wong, Wai T

2013-09-01

To investigate the association of spontaneous drusen regression in intermediate age-related macular degeneration (AMD) with changes on fundus photography and fundus autofluorescence (FAF) imaging. Prospective observational case series. Fundus images from 58 eyes (in 58 patients) with intermediate AMD and large drusen were assessed over 2 years for areas of drusen regression that exceeded the area of circle C1 (diameter 125 μm; Age-Related Eye Disease Study grading protocol). Manual segmentation and computer-based image analysis were used to detect and delineate areas of drusen regression. Delineated regions were graded as to their appearance on fundus photographs and FAF images, and changes in FAF signal were graded manually and quantitated using automated image analysis. Drusen regression was detected in approximately half of study eyes using manual (48%) and computer-assisted (50%) techniques. At year-2, the clinical appearance of areas of drusen regression on fundus photography was mostly unremarkable, with a majority of eyes (71%) demonstrating no detectable clinical abnormalities, and the remainder (29%) showing minor pigmentary changes. However, drusen regression areas were associated with local changes in FAF that were significantly more prominent than changes on fundus photography. A majority of eyes (64%-66%) demonstrated a predominant decrease in overall FAF signal, while 14%-21% of eyes demonstrated a predominant increase in overall FAF signal. FAF imaging demonstrated that drusen regression in intermediate AMD was often accompanied by changes in local autofluorescence signal. Drusen regression may be associated with concurrent structural and physiologic changes in the outer retina. Published by Elsevier Inc.

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions.

PubMed

Saha, Tanumoy; Rathmann, Isabel; Galic, Milos

2017-07-11

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

Proceedings of the NASA Workshop on Registration and Rectification

NASA Technical Reports Server (NTRS)

Bryant, N. A. (Editor)

1982-01-01

Issues associated with the registration and rectification of remotely sensed data. Near and long range applications research tasks and some medium range technology augmentation research areas are recommended. Image sharpness, feature extraction, inter-image mapping, error analysis, and verification methods are addressed.

Retinal status analysis method based on feature extraction and quantitative grading in OCT images.

PubMed

Fu, Dongmei; Tong, Hejun; Zheng, Shuang; Luo, Ling; Gao, Fulin; Minar, Jiri

2016-07-22

Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosis.

Automated analysis of high-content microscopy data with deep learning.

PubMed

Kraus, Oren Z; Grys, Ben T; Ba, Jimmy; Chong, Yolanda; Frey, Brendan J; Boone, Charles; Andrews, Brenda J

2017-04-18

Existing computational pipelines for quantitative analysis of high-content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the application of deep learning to biological image data can overcome the pitfalls associated with conventional machine learning classifiers. Using a deep convolutional neural network (DeepLoc) to analyze yeast cell images, we show improved performance over traditional approaches in the automated classification of protein subcellular localization. We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone-arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. We offer an open-source implementation that enables updating DeepLoc on new microscopy datasets. This study highlights deep learning as an important tool for the expedited analysis of high-content microscopy data. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Relationship between perceived body image and recorded body mass index among Kuwaiti female university students.

PubMed

Kabir, Yearul; Zafar, Tasleem A; Waslien, Carol

2013-01-01

The associations between body image and attitudes toward obesity and thinness and their associations with measured body mass index (BMI) among female students of Kuwait University (n = 137) was examined in 2008. The body image perceptions were assessed using nine female silhouettes figures. The difference between current perceived body image (PBI) and ideal body image (IBI) was used as a measure of body image dissatisfaction (BID). Students tended to have a bigger PBI and smaller IBI than would be expected from their BMI category, leading to high levels of BID in each BMI category. PBI, IBI, BID, RBI were highly correlated with each other, and BMI was significantly correlated with each of them. The coefficients of these associations were not significantly altered in multiple regression analysis by the addition of potential confounding variables, such as age, marital status, physical activity, dieting behavior, parental education, and family size. These results suggest that PBI and a desire to be thinner were strongly related to BID and that thinness is becoming more desired in Kuwaiti society than the plump body image of the past.

Visual Exploration of Genetic Association with Voxel-based Imaging Phenotypes in an MCI/AD Study

PubMed Central

Kim, Sungeun; Shen, Li; Saykin, Andrew J.; West, John D.

2010-01-01

Neuroimaging genomics is a new transdisciplinary research field, which aims to examine genetic effects on brain via integrated analyses of high throughput neuroimaging and genomic data. We report our recent work on (1) developing an imaging genomic browsing system that allows for whole genome and entire brain analyses based on visual exploration and (2) applying the system to the imaging genomic analysis of an existing MCI/AD cohort. Voxel-based morphometry is used to define imaging phenotypes. ANCOVA is employed to evaluate the effect of the interaction of genotypes and diagnosis in relation to imaging phenotypes while controlling for relevant covariates. Encouraging experimental results suggest that the proposed system has substantial potential for enabling discovery of imaging genomic associations through visual evaluation and for localizing candidate imaging regions and genomic regions for refined statistical modeling. PMID:19963597

Vulnerability Analysis of HD Photo Image Viewer Applications

DTIC Science & Technology

2007-09-01

the successor to the ubiquitous JPEG image format, as well as the eventual de facto standard in the digital photography market. With massive efforts...renamed to HD Photo in November of 2006, is being touted as the successor to the ubiquitous JPEG image format, as well as the eventual de facto standard...associated state-of-the-art compression algorithm “specifically designed [for] all types of continuous tone photographic” images [HDPhotoFeatureSpec

Comparison of longitudinal excursion of a nerve-phantom model using quantitative ultrasound imaging and motion analysis system methods: A convergent validity study.

PubMed

Paquette, Philippe; El Khamlichi, Youssef; Lamontagne, Martin; Higgins, Johanne; Gagnon, Dany H

2017-08-01

Quantitative ultrasound imaging is gaining popularity in research and clinical settings to measure the neuromechanical properties of the peripheral nerves such as their capability to glide in response to body segment movement. Increasing evidence suggests that impaired median nerve longitudinal excursion is associated with carpal tunnel syndrome. To date, psychometric properties of longitudinal nerve excursion measurements using quantitative ultrasound imaging have not been extensively investigated. This study investigates the convergent validity of the longitudinal nerve excursion by comparing measures obtained using quantitative ultrasound imaging with those determined with a motion analysis system. A 38-cm long rigid nerve-phantom model was used to assess the longitudinal excursion in a laboratory environment. The nerve-phantom model, immersed in a 20-cm deep container filled with a gelatin-based solution, was moved 20 times using a linear forward and backward motion. Three light-emitting diodes were used to record nerve-phantom excursion with a motion analysis system, while a 5-cm linear transducer allowed simultaneous recording via ultrasound imaging. Both measurement techniques yielded excellent association ( r  = 0.99) and agreement (mean absolute difference between methods = 0.85 mm; mean relative difference between methods = 7.48 %). Small discrepancies were largely found when larger excursions (i.e. > 10 mm) were performed, revealing slight underestimation of the excursion by the ultrasound imaging analysis software. Quantitative ultrasound imaging is an accurate method to assess the longitudinal excursion of an in vitro nerve-phantom model and appears relevant for future research protocols investigating the neuromechanical properties of the peripheral nerves.

Image Analysis Algorithms for Immunohistochemical Assessment of Cell Death Events and Fibrosis in Tissue Sections

PubMed Central

Krajewska, Maryla; Smith, Layton H.; Rong, Juan; Huang, Xianshu; Hyer, Marc L.; Zeps, Nikolajs; Iacopetta, Barry; Linke, Steven P.; Olson, Allen H.; Reed, John C.; Krajewski, Stan

2009-01-01

Cell death is of broad physiological and pathological importance, making quantification of biochemical events associated with cell demise a high priority for experimental pathology. Fibrosis is a common consequence of tissue injury involving necrotic cell death. Using tissue specimens from experimental mouse models of traumatic brain injury, cardiac fibrosis, and cancer, as well as human tumor specimens assembled in tissue microarray (TMA) format, we undertook computer-assisted quantification of specific immunohistochemical and histological parameters that characterize processes associated with cell death. In this study, we demonstrated the utility of image analysis algorithms for color deconvolution, colocalization, and nuclear morphometry to characterize cell death events in tissue specimens: (a) subjected to immunostaining for detecting cleaved caspase-3, cleaved poly(ADP-ribose)-polymerase, cleaved lamin-A, phosphorylated histone H2AX, and Bcl-2; (b) analyzed by terminal deoxyribonucleotidyl transferase–mediated dUTP nick end labeling assay to detect DNA fragmentation; and (c) evaluated with Masson's trichrome staining. We developed novel algorithm-based scoring methods and validated them using TMAs as a high-throughput format. The proposed computer-assisted scoring methods for digital images by brightfield microscopy permit linear quantification of immunohistochemical and histochemical stainings. Examples are provided of digital image analysis performed in automated or semiautomated fashion for successful quantification of molecular events associated with cell death in tissue sections. (J Histochem Cytochem 57:649–663, 2009) PMID:19289554

Theory and applications of structured light single pixel imaging

NASA Astrophysics Data System (ADS)

Stokoe, Robert J.; Stockton, Patrick A.; Pezeshki, Ali; Bartels, Randy A.

2018-02-01

Many single-pixel imaging techniques have been developed in recent years. Though the methods of image acquisition vary considerably, the methods share unifying features that make general analysis possible. Furthermore, the methods developed thus far are based on intuitive processes that enable simple and physically-motivated reconstruction algorithms, however, this approach may not leverage the full potential of single-pixel imaging. We present a general theoretical framework of single-pixel imaging based on frame theory, which enables general, mathematically rigorous analysis. We apply our theoretical framework to existing single-pixel imaging techniques, as well as provide a foundation for developing more-advanced methods of image acquisition and reconstruction. The proposed frame theoretic framework for single-pixel imaging results in improved noise robustness, decrease in acquisition time, and can take advantage of special properties of the specimen under study. By building on this framework, new methods of imaging with a single element detector can be developed to realize the full potential associated with single-pixel imaging.

Wavelet Analysis for RADARSAT Exploitation: Demonstration of Algorithms for Maritime Surveillance

DTIC Science & Technology

2007-02-01

this study , we demonstrate wavelet analysis for exploitation of RADARSAT ocean imagery, including wind direction estimation, oceanic and atmospheric ...of image striations that can arise as a texture pattern caused by turbulent coherent structures in the marine atmospheric boundary layer. The image...associated change in the pattern texture (i.e., the nature of the turbulent atmospheric structures) across the front. Due to the large spatial scale of

Microspectroscopy of spectral biomarkers associated with human corneal stem cells

PubMed Central

Nakamura, Takahiro; Kelly, Jemma G.; Trevisan, Júlio; Cooper, Leanne J.; Bentley, Adam J.; Carmichael, Paul L.; Scott, Andrew D.; Cotte, Marine; Susini, Jean; Martin-Hirsch, Pierre L.; Kinoshita, Shigeru; Martin, Francis L.

2010-01-01

Purpose Synchrotron-based radiation (SRS) Fourier-transform infrared (FTIR) microspectroscopy potentially provides novel biomarkers of the cell differentiation process. Because such imaging gives a “biochemical-cell fingerprint” through a cell-sized aperture, we set out to determine whether distinguishing chemical entities associated with putative stem cells (SCs), transit-amplifying (TA) cells, or terminally-differentiated (TD) cells could be identified in human corneal epithelium. Methods Desiccated cryosections (10 μm thick) of cornea on barium fluoride infrared transparent windows were interrogated using SRS FTIR microspectroscopy. Infrared analysis was performed through the acquisition of point spectra or image maps. Results Point spectra were subjected to principal component analysis (PCA) to identify distinguishing chemical entities. Spectral image maps to highlight SCs, TA cells, and TD cells of the cornea were then generated. Point spectrum analysis using PCA highlighted remarkable segregation between the three cell classes. Discriminating chemical entities were associated with several spectral differences over the DNA/RNA (1,425–900 cm−1) and protein/lipid (1,800–1480 cm−1) regions. Prominent biomarkers of SCs compared to TA cells and/or TD cells were 1,040 cm−1, 1,080 cm−1, 1,107 cm−1, 1,225 cm−1, 1,400 cm−1, 1,525 cm−1, 1,558 cm−1, and 1,728 cm−1. Chemical entities associated with DNA/RNA conformation (1,080 cm−1 and 1,225 cm−1) were associated with SCs, whereas protein/lipid biochemicals (1,558 cm−1 and 1,728 cm−1) most distinguished TA cells and TD cells. Conclusions SRS FTIR microspectroscopy can be employed to identify differential spectral biomarkers of SCs, TA cells, and/or TD cells in human cornea. This nondestructive imaging technology is a novel approach to characterizing SCs in situ. PMID:20520745

In vivo imaging of advanced glycation end products (AGEs) of albumin: first observations of significantly reduced clearance and liver deposition properties in mice.

PubMed

Tsutsui, Ayumi; Ogura, Akihiro; Tahara, Tsuyoshi; Nozaki, Satoshi; Urano, Sayaka; Hara, Mitsuko; Kojima, Soichi; Kurbangalieva, Almira; Onoe, Hirotaka; Watanabe, Yasuyoshi; Taniguchi, Naoyuki; Tanaka, Katsunori

2016-06-15

Advanced glycation end products (AGEs) are associated with various diseases, especially during aging and the development of diabetes and uremia. To better understand these biological processes, investigation of the in vivo kinetics of AGEs, i.e., analysis of trafficking and clearance properties, was carried out by molecular imaging. Following the preparation of Cy7.5-labeled AGE-albumin and intravenous injection in BALB/cA-nu/nu mice, noninvasive fluorescence kinetics analysis was performed. In vivo imaging and fluorescence microscopy analysis revealed that non-enzymatic AGEs were smoothly captured by scavenger cells in the liver, i.e., Kupffer and other sinusoidal cells, but were unable to be properly cleared from the body. Overall, these results highlight an important link between AGEs and various disorders associated with them, which may serve as a platform for future research to better understand the processes and mechanisms of these disorders.

A novel structure-aware sparse learning algorithm for brain imaging genetics.

PubMed

Du, Lei; Jingwen, Yan; Kim, Sungeun; Risacher, Shannon L; Huang, Heng; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

2014-01-01

Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most existing SCCA algorithms are designed using the soft threshold strategy, which assumes that the features in the data are independent from each other. This independence assumption usually does not hold in imaging genetic data, and thus inevitably limits the capability of yielding optimal solutions. We propose a novel structure-aware SCCA (denoted as S2CCA) algorithm to not only eliminate the independence assumption for the input data, but also incorporate group-like structure in the model. Empirical comparison with a widely used SCCA implementation, on both simulated and real imaging genetic data, demonstrated that S2CCA could yield improved prediction performance and biologically meaningful findings.

TU-CD-BRB-08: Radiomic Analysis of FDG-PET Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated with SBRT

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

Cui, Y; Shirato, H; Song, J

2015-06-15

Purpose: This study aims to identify novel prognostic imaging biomarkers in locally advanced pancreatic cancer (LAPC) using quantitative, high-throughput image analysis. Methods: 86 patients with LAPC receiving chemotherapy followed by SBRT were retrospectively studied. All patients had a baseline FDG-PET scan prior to SBRT. For each patient, we extracted 435 PET imaging features of five types: statistical, morphological, textural, histogram, and wavelet. These features went through redundancy checks, robustness analysis, as well as a prescreening process based on their concordance indices with respect to the relevant outcomes. We then performed principle component analysis on the remaining features (number ranged frommore » 10 to 16), and fitted a Cox proportional hazard regression model using the first 3 principle components. Kaplan-Meier analysis was used to assess the ability to distinguish high versus low-risk patients separated by median predicted survival. To avoid overfitting, all evaluations were based on leave-one-out cross validation (LOOCV), in which each holdout patient was assigned to a risk group according to the model obtained from a separate training set. Results: For predicting overall survival (OS), the most dominant imaging features were wavelet coefficients. There was a statistically significant difference in OS between patients with predicted high and low-risk based on LOOCV (hazard ratio: 2.26, p<0.001). Similar imaging features were also strongly associated with local progression-free survival (LPFS) (hazard ratio: 1.53, p=0.026) on LOOCV. In comparison, neither SUVmax nor TLG was associated with LPFS (p=0.103, p=0.433) (Table 1). Results for progression-free survival and distant progression-free survival showed similar trends. Conclusion: Radiomic analysis identified novel imaging features that showed improved prognostic value over conventional methods. These features characterize the degree of intra-tumor heterogeneity reflected on FDG-PET images, and their biological underpinnings warrant further investigation. If validated in large, prospective cohorts, this method could be used to stratify patients based on individualized risk.« less

Comparison of three‐dimensional analysis and stereological techniques for quantifying lithium‐ion battery electrode microstructures

PubMed Central

TAIWO, OLUWADAMILOLA O.; FINEGAN, DONAL P.; EASTWOOD, DAVID S.; FIFE, JULIE L.; BROWN, LEON D.; DARR, JAWWAD A.; LEE, PETER D.; BRETT, DANIEL J.L.

2016-01-01

Summary Lithium‐ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium‐ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3‐D imaging techniques, quantitative assessment of 3‐D microstructures from 2‐D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two‐dimensional (2‐D) data sets. In this study, stereological prediction and three‐dimensional (3‐D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium‐ion battery electrodes were imaged using synchrotron‐based X‐ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2‐D image sections generated from tomographic imaging, whereas direct 3‐D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2‐D image sections is bound to be associated with ambiguity and that volume‐based 3‐D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially‐dependent parameters, such as tortuosity and pore‐phase connectivity. PMID:26999804

Comparison of three-dimensional analysis and stereological techniques for quantifying lithium-ion battery electrode microstructures.

PubMed

Taiwo, Oluwadamilola O; Finegan, Donal P; Eastwood, David S; Fife, Julie L; Brown, Leon D; Darr, Jawwad A; Lee, Peter D; Brett, Daniel J L; Shearing, Paul R

2016-09-01

Lithium-ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium-ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3-D imaging techniques, quantitative assessment of 3-D microstructures from 2-D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two-dimensional (2-D) data sets. In this study, stereological prediction and three-dimensional (3-D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium-ion battery electrodes were imaged using synchrotron-based X-ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2-D image sections generated from tomographic imaging, whereas direct 3-D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2-D image sections is bound to be associated with ambiguity and that volume-based 3-D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially-dependent parameters, such as tortuosity and pore-phase connectivity. © 2016 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

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

Wu, J; Gong, G; Cui, Y

Purpose: To predict early pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multi-region analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). Methods: In this institution review board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with a high-temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitativemore » Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Results: Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast wash-out were statistically significant (p< 0.05) after correcting for multiple testing, with area under the ROC curve or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (p = 0.002) in leave-one-out cross validation. This improved upon conventional imaging predictors such as tumor volume (AUC=0.53) and texture features based on whole-tumor analysis (AUC=0.65). Conclusion: The heterogeneity of the tumor subregion associated with fast wash-out on DCE-MRI predicted early pathological response to neoadjuvant chemotherapy in breast cancer.« less

Ultrasound estimates of muscle quality in older adults: reliability and comparison of Photoshop and ImageJ for the grayscale analysis of muscle echogenicity

PubMed Central

Seamon, Bryant A.; Teixeira, Carla; Ismail, Catheeja

2016-01-01

Background. Quantitative diagnostic ultrasound imaging has been proposed as a method of estimating muscle quality using measures of echogenicity. The Rectangular Marquee Tool (RMT) and the Free Hand Tool (FHT) are two types of editing features used in Photoshop and ImageJ for determining a region of interest (ROI) within an ultrasound image. The primary objective of this study is to determine the intrarater and interrater reliability of Photoshop and ImageJ for the estimate of muscle tissue echogenicity in older adults via grayscale histogram analysis. The secondary objective is to compare the mean grayscale values obtained using both the RMT and FHT methods across both image analysis platforms. Methods. This cross-sectional observational study features 18 community-dwelling men (age = 61.5 ± 2.32 years). Longitudinal views of the rectus femoris were captured using B-mode ultrasound. The ROI for each scan was selected by 2 examiners using the RMT and FHT methods from each software program. Their reliability is assessed using intraclass correlation coefficients (ICCs) and the standard error of the measurement (SEM). Measurement agreement for these values is depicted using Bland-Altman plots. A paired t-test is used to determine mean differences in echogenicity expressed as grayscale values using the RMT and FHT methods to select the post-image acquisition ROI. The degree of association among ROI selection methods and image analysis platforms is analyzed using the coefficient of determination (R2). Results. The raters demonstrated excellent intrarater and interrater reliability using the RMT and FHT methods across both platforms (lower bound 95% CI ICC = .97–.99, p < .001). Mean differences between the echogenicity estimates obtained with the RMT and FHT methods was .87 grayscale levels (95% CI [.54–1.21], p < .0001) using data obtained with both programs. The SEM for Photoshop was .97 and 1.05 grayscale levels when using the RMT and FHT ROI selection methods, respectively. Comparatively, the SEM values were .72 and .81 grayscale levels, respectively, when using the RMT and FHT ROI selection methods in ImageJ. Uniform coefficients of determination (R2 = .96–.99, p < .001) indicate strong positive associations among the grayscale histogram analysis measurement conditions independent of the ROI selection methods and imaging platform. Conclusion. Our method for evaluating muscle echogenicity demonstrated a high degree of intrarater and interrater reliability using both the RMT and FHT methods across 2 common image analysis platforms. The minimal measurement error exhibited by the examiners demonstrates that the ROI selection methods used with Photoshop and ImageJ are suitable for the post-acquisition image analysis of tissue echogenicity in older adults. PMID:26925339

Diagnostic imaging for chronic plantar heel pain: a systematic review and meta-analysis

PubMed Central

2009-01-01

Background Chronic plantar heel pain (CPHP) is a generalised term used to describe a range of undifferentiated conditions affecting the plantar heel. Plantar fasciitis is reported as the most common cause and the terms are frequently used interchangeably in the literature. Diagnostic imaging has been used by many researchers and practitioners to investigate the involvement of specific anatomical structures in CPHP. These observations help to explain the underlying pathology of the disorder, and are of benefit in forming an accurate diagnosis and targeted treatment plan. The purpose of this systematic review was to investigate the diagnostic imaging features associated with CPHP, and evaluate study findings by meta-analysis where appropriate. Methods Bibliographic databases including Medline, Embase, CINAHL, SportDiscus and The Cochrane Library were searched electronically on March 25, 2009. Eligible articles were required to report imaging findings in participants with CPHP unrelated to inflammatory arthritis, and to compare these findings with a control group. Methodological quality was evaluated by use of the Quality Index as described by Downs and Black. Meta-analysis of study data was conducted where appropriate. Results Plantar fascia thickness as measured by ultrasonography was the most widely reported imaging feature. Meta-analysis revealed that the plantar fascia of CPHP participants was 2.16 mm thicker than control participants (95% CI = 1.60 to 2.71 mm, P < 0.001) and that CPHP participants were more likely to have plantar fascia thickness values greater than 4.0 mm (OR = 105.11, 95% CI = 3.09 to 3577.28, P = 0.01). CPHP participants were also more likely to show radiographic evidence of subcalcaneal spur than control participants (OR = 8.52, 95% CI = 4.08 to 17.77, P < 0.001). Conclusion This systematic review has identified 23 studies investigating the diagnostic imaging appearance of the plantar fascia and inferior calcaneum in people with CPHP. Analysis of these studies found that people with CPHP are likely to have a thickened plantar fascia with associated fluid collection, and that thickness values >4.0 mm are diagnostic of plantar fasciitis. Additionally, subcalcaneal spur formation is strongly associated with pain beneath the heel. PMID:19912628

Dedicated tool to assess the impact of a rhetorical task on human body temperature.

PubMed

Koprowski, Robert; Wilczyński, Sławomir; Martowska, Katarzyna; Gołuch, Dominik; Wrocławska-Warchala, Emilia

2017-10-01

Functional infrared thermal imaging is a method widely used in medicine, including analysis of the mechanisms related to the effect of emotions on physiological processes. The article shows how the body temperature may change during stress associated with performing a rhetorical task and proposes new parameters useful for dynamic thermal imaging measurements MATERIALS AND METHODS: 29 healthy male subjects were examined. They were given a rhetorical task that induced stress. Analysis and processing of collected body temperature data in a spatial resolution of 256×512pixels and a temperature resolution of 0.1°C enabled to show the dynamics of temperature changes. This analysis was preceded by dedicated image analysis and processing methods RESULTS: The presented dedicated algorithm for image analysis and processing allows for fully automated, reproducible and quantitative assessment of temperature changes and time constants in a sequence of thermal images of the patient. When performing the rhetorical task, the temperature rose by 0.47±0.19°C in 72.41% of the subjects, including 20.69% in whom the temperature decreased by 0.49±0.14°C after 237±141s. For 20.69% of the subjects only a drop in temperature was registered. For the remaining 6.89% of the cases, no temperature changes were registered CONCLUSIONS: The performance of the rhetorical task by the subjects causes body temperature changes. The ambiguous temperature response to the given stress factor indicates the complex mechanisms responsible for regulating stressful situations. Stress associated with the examination itself induces body temperature changes. These changes should always be taken into account in the analysis of infrared data. Copyright © 2017 Elsevier B.V. All rights reserved.

Representations of Codeine Misuse on Instagram: Content Analysis

PubMed Central

Cherian, Roy; Westbrook, Marisa; Ramo, Danielle

2018-01-01

Background Prescription opioid misuse has doubled over the past 10 years and is now a public health epidemic. Analysis of social media data may provide additional insights into opioid misuse to supplement the traditional approaches of data collection (eg, self-report on surveys). Objective The aim of this study was to characterize representations of codeine misuse through analysis of public posts on Instagram to understand text phrases related to misuse. Methods We identified hashtags and searchable text phrases associated with codeine misuse by analyzing 1156 sequential Instagram posts over the course of 2 weeks from May 2016 to July 2016. Content analysis of posts associated with these hashtags identified the most common themes arising in images, as well as culture around misuse, including how misuse is happening and being perpetuated through social media. Results A majority of images (50/100; 50.0%) depicted codeine in its commonly misused form, combined with soda (lean). Codeine misuse was commonly represented with the ingestion of alcohol, cannabis, and benzodiazepines. Some images highlighted the previously noted affinity between codeine misuse and hip-hop culture or mainstream popular culture images. Conclusions The prevalence of codeine misuse images, glamorizing of ingestion with soda and alcohol, and their integration with mainstream, popular culture imagery holds the potential to normalize and increase codeine misuse and overdose. To reduce harm and prevent misuse, immediate public health efforts are needed to better understand the relationship between the potential normalization, ritualization, and commercialization of codeine misuse. PMID:29559422

Nondestructive Analysis of Tumor-Associated Membrane Protein Integrating Imaging and Amplified Detection in situ Based on Dual-Labeled DNAzyme.

PubMed

Chen, Xiaoxia; Zhao, Jing; Chen, Tianshu; Gao, Tao; Zhu, Xiaoli; Li, Genxi

2018-01-01

Comprehensive analysis of the expression level and location of tumor-associated membrane proteins (TMPs) is of vital importance for the profiling of tumor cells. Currently, two kinds of independent techniques, i.e. ex situ detection and in situ imaging, are usually required for the quantification and localization of TMPs respectively, resulting in some inevitable problems. Methods: Herein, based on a well-designed and fluorophore-labeled DNAzyme, we develop an integrated and facile method, in which imaging and quantification of TMPs in situ are achieved simultaneously in a single system. The labeled DNAzyme not only produces localized fluorescence for the visualization of TMPs but also catalyzes the cleavage of a substrate to produce quantitative fluorescent signals that can be collected from solution for the sensitive detection of TMPs. Results: Results from the DNAzyme-based in situ imaging and quantification of TMPs match well with traditional immunofluorescence and western blotting. In addition to the advantage of two-in-one, the DNAzyme-based method is highly sensitivity, allowing the detection of TMPs in only 100 cells. Moreover, the method is nondestructive. Cells after analysis could retain their physiological activity and could be cultured for other applications. Conclusion: The integrated system provides solid results for both imaging and quantification of TMPs, making it a competitive method over some traditional techniques for the analysis of TMPs, which offers potential application as a toolbox in the future.

Emergency department imaging: are weather and calendar factors associated with imaging volume?

PubMed

Burns, K; Chernyak, V; Scheinfeld, M H

2016-12-01

To identify weather and calendar factors that would enable prediction of daily emergency department (ED) imaging volume to aid appropriate scheduling of imaging resources for efficient ED function. Daily ED triage and imaging volumes for radiography, computed tomography (CT), and ultrasound were obtained from hospital databases for the period between January 2011 and December 2013 at a large tertiary urban hospital with a Level II trauma centre. These data were tabulated alongside daily weather conditions (temperature, wind and precipitation), day of week, season, and holidays. Multivariate analysis was performed. Pearson correlations were used to measure the association between number of imaging studies performed and ED triage volume. For every additional 50 triaged patients, the odds of having high (imaging volume ≥90th percentile) radiography, CT, and ultrasound volume increased by 4.3 times (p<0.001), 1.5 times (p=0.02), and 1.4 times (p=0.02), respectively. Tuesday was an independent predictor of high radiography volume (odds ratio=2.8) and Monday was an independent predictor of high CT volume (odds ratio=3.0). Weekday status was an independent factor increasing the odds of a high US volume compared to Saturday (odds ratios ranging from 5.6-9.8). Weather factors and other calendar variables were not independent predictors of high imaging volume. Using Pearson correlations, ED triage volume correlated with number of radiographs, CT, and ultrasound examinations with r=0.73, 0.37, and 0.41, respectively (p<0.0001). As ED triage volume was found to be the only factor associated with imaging volume for all techniques, analysis of predictors of ED triage volumes at a particular healthcare facility would be useful to determine imaging needs. Although calendar and weather factors were found to be minor or non-significant independent predictors of ED imaging utilisation, these may be important in influencing the actual number of ED triages. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

A simulator for evaluating methods for the detection of lesion-deficit associations

NASA Technical Reports Server (NTRS)

Megalooikonomou, V.; Davatzikos, C.; Herskovits, E. H.

2000-01-01

Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

Quantitative image analysis of immunohistochemical stains using a CMYK color model

PubMed Central

Pham, Nhu-An; Morrison, Andrew; Schwock, Joerg; Aviel-Ronen, Sarit; Iakovlev, Vladimir; Tsao, Ming-Sound; Ho, James; Hedley, David W

2007-01-01

Background Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases. Methods We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections. Results The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies. Conclusion The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both basic as well as clinical research in an unbiased, reproducible and high throughput evaluation of IHC intensity. PMID:17326824

Predictors of underestimation of malignancy after image-guided core needle biopsy diagnosis of flat epithelial atypia or atypical ductal hyperplasia.

PubMed

Yu, Chi-Chang; Ueng, Shir-Hwa; Cheung, Yun-Chung; Shen, Shih-Che; Kuo, Wen-Lin; Tsai, Hsiu-Pei; Lo, Yung-Feng; Chen, Shin-Cheh

2015-01-01

Flat epithelial atypia (FEA) and atypical ductal hyperplasia (ADH) are precursors of breast malignancy. Management of FEA or ADH after image-guided core needle biopsy (CNB) remains controversial. The aim of this study was to evaluate malignancy underestimation rates after FEA or ADH diagnosis using image-guided CNB and to identify clinical characteristics and imaging features associated with malignancy as well as identify cases with low underestimation rates that may be treatable by observation only. We retrospectively reviewed 2,875 consecutive image-guided CNBs recorded in an electronic data base from January 2010 to December 2011 and identified 128 (4.5%) FEA and 83 (2.9%) ADH diagnoses (211 total cases). Of these, 64 (30.3%) were echo-guided CNB procedures and 147 (69.7%) mammography-guided CNBs. Twenty patients (9.5%) were upgraded to malignancy. Multivariate analysis indicated that age (OR = 1.123, p = 0.002, increase of 1 year), mass-type lesion with calcifications (OR = 8.213, p = 0.006), and ADH in CNB specimens (OR = 8.071, p = 0.003) were independent predictors of underestimation. In univariate analysis of echo-guided CNB (n = 64), mass with calcifications had the highest underestimation rate (p < 0.001). Multivariate analysis of 147 mammography-guided CNBs revealed that age (OR = 1.122, p = 0.040, increase of 1 year) and calcification distribution were significant independent predictors of underestimation. No FEA case in which, complete calcification retrieval was recorded after CNB was upgraded to malignancy. Older age at diagnosis on image-guided CNB was a predictor of malignancy underestimation. Mass with calcifications was more likely to be associated with malignancy, and in cases presenting as calcifications only, segmental distribution or linear shapes were significantly associated with upgrading. Excision after FEA or ADH diagnosis by image-guided CNB is warranted except for FEA diagnosed using mammography-guided CNB with complete calcification retrieval. © 2015 Wiley Periodicals, Inc.

Instagram Unfiltered: Exploring Associations of Body Image Satisfaction, Instagram #Selfie Posting, and Negative Romantic Relationship Outcomes.

PubMed

Ridgway, Jessica L; Clayton, Russell B

2016-01-01

The purpose of this study was to examine the predictors and consequences associated with Instagram selfie posting. Thus, this study explored whether body image satisfaction predicts Instagram selfie posting and whether Instagram selfie posting is then associated with Instagram-related conflict and negative romantic relationship outcomes. A total of 420 Instagram users aged 18 to 62 years (M = 29.3, SD = 8.12) completed an online survey questionnaire. Analysis of a serial multiple mediator model using bootstrapping methods indicated that body image satisfaction was sequentially associated with increased Instagram selfie posting and Instagram-related conflict, which related to increased negative romantic relationship outcomes. These findings suggest that when Instagram users promote their body image satisfaction in the form of Instagram selfie posts, risk of Instagram-related conflict and negative romantic relationship outcomes might ensue. Findings from the current study provide a baseline understanding to potential and timely trends regarding Instagram selfie posting.

Understanding the Organo-Carbonate Associations in Carbonaceous Chondrites with the Use of Micro-Raman Analysis

NASA Technical Reports Server (NTRS)

Chan, Q. H. S.; Zolensky, M. E.

2015-01-01

Carbonates can potentially provide sites for organic materials to accrue and develop into complex macromolecules. This study examines the organics associated with carbonates in carbonaceous chondrites using micron-Raman imaging.

Understanding the Organo-Carbonate Associations in Carbonaceous Chondrites with the Use of Micro-Raman Analysis

NASA Technical Reports Server (NTRS)

Chan, Q. H. S.; Zolensky, M. E.

2015-01-01

Carbonates can potentially provide sites for organic materials to accrue and develop into complex macromolecules. This study examines the organics associated with carbonates in carbonaceous chondrites using µ-Raman imaging.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Optical Associative Processors For Visual Perception"

NASA Astrophysics Data System (ADS)

Casasent, David; Telfer, Brian

1988-05-01

We consider various associative processor modifications required to allow these systems to be used for visual perception, scene analysis, and object recognition. For these applications, decisions on the class of the objects present in the input image are required and thus heteroassociative memories are necessary (rather than the autoassociative memories that have been given most attention). We analyze the performance of both associative processors and note that there is considerable difference between heteroassociative and autoassociative memories. We describe associative processors suitable for realizing functions such as: distortion invariance (using linear discriminant function memory synthesis techniques), noise and image processing performance (using autoassociative memories in cascade with with a heteroassociative processor and with a finite number of autoassociative memory iterations employed), shift invariance (achieved through the use of associative processors operating on feature space data), and the analysis of multiple objects in high noise (which is achieved using associative processing of the output from symbolic correlators). We detail and provide initial demonstrations of the use of associative processors operating on iconic, feature space and symbolic data, as well as adaptive associative processors.

How to Perform a Systematic Review and Meta-analysis of Diagnostic Imaging Studies.

PubMed

Cronin, Paul; Kelly, Aine Marie; Altaee, Duaa; Foerster, Bradley; Petrou, Myria; Dwamena, Ben A

2018-05-01

A systematic review is a comprehensive search, critical evaluation, and synthesis of all the relevant studies on a specific (clinical) topic that can be applied to the evaluation of diagnostic and screening imaging studies. It can be a qualitative or a quantitative (meta-analysis) review of available literature. A meta-analysis uses statistical methods to combine and summarize the results of several studies. In this review, a 12-step approach to performing a systematic review (and meta-analysis) is outlined under the four domains: (1) Problem Formulation and Data Acquisition, (2) Quality Appraisal of Eligible Studies, (3) Statistical Analysis of Quantitative Data, and (4) Clinical Interpretation of the Evidence. This review is specifically geared toward the performance of a systematic review and meta-analysis of diagnostic test accuracy (imaging) studies. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Moving image analysis to the cloud: A case study with a genome-scale tomographic study

NASA Astrophysics Data System (ADS)

Mader, Kevin; Stampanoni, Marco

2016-01-01

Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

Imaging of Melanin Disruption in Age-Related Macular Degeneration Using Multispectral Imaging.

PubMed

Dugel, Pravin U; Zimmer, Cheryl N

2016-02-01

To investigate whether multispectral imaging (MSI) is able to obtain a noninvasive view of melanin disruption associated with age-related macular degeneration (AMD), which could support early diagnosis and potential treatment strategies. A single retinal center, retrospective, observational, image analysis study of MSI images of 43 patients was done to determine the extent of melanin pigment exhibited in association with AMD, based on the Age-Related Eye Disease Study classification and grading scale. Corresponding fundus photos were also graded for 12 of the eyes. Fifty-one of 61 eyes (84%) of 43 patients with AMD were determined to have melanin disruption in their MSI images in at least the central and/or one of four inner ETDRS areas. There was a relationship between severity of disease and the degree of melanin disruption. The sensitivity of fundus photography for melanin pigment as compared to MSI was only 62.5%, with three false-negatives. A direct, noninvasive, unobstructed view of melanin disruption associated with AMD can be observed using MSI. Copyright 2016, SLACK Incorporated.

Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture.

PubMed

Russell, Richard A; Adams, Niall M; Stephens, David A; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S

2009-04-22

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

PubMed Central

Russell, Richard A.; Adams, Niall M.; Stephens, David A.; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S.

2009-01-01

Abstract Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments. PMID:19383481

Image Harvest: an open-source platform for high-throughput plant image processing and analysis

PubMed Central

Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

2016-01-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

Photovoltaic panel extraction from very high-resolution aerial imagery using region-line primitive association analysis and template matching

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Sun, Yujie; Wang, Qiao

2018-07-01

In object-based image analysis (OBIA), object classification performance is jointly determined by image segmentation, sample or rule setting, and classifiers. Typically, as a crucial step to obtain object primitives, image segmentation quality significantly influences subsequent feature extraction and analyses. By contrast, template matching extracts specific objects from images and prevents shape defects caused by image segmentation. However, creating or editing templates is tedious and sometimes results in incomplete or inaccurate templates. In this study, we combine OBIA and template matching techniques to address these problems and aim for accurate photovoltaic panel (PVP) extraction from very high-resolution (VHR) aerial imagery. The proposed method is based on the previously proposed region-line primitive association framework, in which complementary information between region (segment) and line (straight line) primitives is utilized to achieve a more powerful performance than routine OBIA. Several novel concepts, including the mutual fitting ratio and best-fitting template based on region-line primitive association analyses, are proposed. Automatic template generation and matching method for PVP extraction from VHR imagery are designed for concept and model validation. Results show that the proposed method can successfully extract PVPs without any user-specified matching template or training sample. High user independency and accuracy are the main characteristics of the proposed method in comparison with routine OBIA and template matching techniques.

Cesarean section scar diverticulum evaluation by saline contrast-enhanced magnetic resonance imaging: The relationship between variable parameters and longer menstrual bleeding.

PubMed

Yao, Min; Wang, Wenjing; Zhou, Jieru; Sun, Minghua; Zhu, Jialiang; Chen, Pin; Wang, Xipeng

2017-04-01

This study was conducted to determine a more accurate imaging method for the diagnosis of cesarean scar diverticulum (CSD) and to identify the parameters of CSD strongly associated with prolonged menstrual bleeding. We enrolled 282 women with a history of cesarean section (CS) who presented with prolonged menstrual bleeding between January 2012 and May 2015. Transvaginal ultrasound, general magnetic resonance imaging (MRI) and contrast-enhanced MRI were used to diagnose CSD. Five parameters were compared among the imaging modalities: length, width, depth and thickness of the remaining muscular layer (TRM) of CSD and the depth/TRM ratio. Correlation between the five parameters and days of menstrual bleeding was performed. Finally, multivariate analysis was used to determine the parameters associated with menstrual bleeding longer than 14 days. Contrast-enhanced MRI yielded greater length or width or thinner TRM of CSD compared with MRI and transvaginal ultrasound. CSD size did not significantly differ between women who had undergone one and two CSs. Correlation analysis revealed that CSD (P = 0.038) and TRM (P = 0.003) lengths were significantly associated with days of menstrual bleeding. Longer than 14 days of bleeding was defined by cut-off values of 2.15 mm for TRM and 13.85 mm for length. TRM and number of CSs were strongly associated with menstrual bleeding longer than 14 days. CE-MRI is a relatively accurate and efficient imaging method for the diagnosis of CSD. A cut-off value of TRM of 2.15 mm is the most important parameter associated with menstrual bleeding longer than 14 days. © 2017 Japan Society of Obstetrics and Gynecology.

Regional and socioeconomic disparities in emergency department use of radiographic imaging for acute pediatric sinusitis.

PubMed

Sedaghat, Ahmad R; Cunningham, Michael J; Ishman, Stacey L

2014-01-01

Acute pediatric sinusitis (APS) is a common complication of pediatric upper respiratory tract infections. Children with all degrees of APS severity may present to emergency departments (EDs) for evaluation and management. This study was designed to analyze the use of imaging in APS presenting to U.S. EDs. A cross-sectional analysis of the 2008 National Emergency Department Sample database was performed. One hundred one thousand six hundred sixty children, aged ≤18 years, assigned at least one ICD9 code for APS were identified. Current procedural terminology codes for sinus plain film radiographs, computed tomography (CT), and magnetic resonance imaging identified children who underwent sinus imaging. Association of performance of sinus imaging was sought with multiple predictor variables including clinicodemographic and hospital characteristics. The use of any imaging was associated with older age (odds ratio [OR] = 1.07; p < 0.001), male gender (OR = 1.57; p < 0.001), and diagnosis of chronic rhinosinusitis (OR = 2.46; p < 0.001). Imaging was more common in metropolitan teaching (OR = 1.40;0 p < 0.001) and nonteaching (OR = 5.64; p < 0.001) hospitals. Markers of higher socioeconomic status--private health insurance (OR = 1.37; p < 0.001) and higher income level (OR = 1.96; p < 0.001)--were associated with greater use of imaging, especially CT scans. The use of ED imaging in APS is appropriately associated with factors known to be associated with APS complications. However, additional disparities with respect to regional and socioeconomic factors exist. Interventions to eliminate these health care disparities in use of imaging resources may lead to quality improvement in care and outcomes for APS.

A concept for holistic whole body MRI data analysis, Imiomics

PubMed Central

Malmberg, Filip; Johansson, Lars; Lind, Lars; Sundbom, Magnus; Ahlström, Håkan; Kullberg, Joel

2017-01-01

Purpose To present and evaluate a whole-body image analysis concept, Imiomics (imaging–omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a person over time and integrated with non-imaging data. Methods The presented image registration method utilizes relative elasticity constraints of different tissue obtained from whole-body water-fat MRI. The registration method is evaluated by inverse consistency and Dice coefficients and the Imiomics concept is evaluated by example analyses of importance for metabolic research using non-imaging parameters where we know what to expect. The example analyses include whole body imaging atlas creation, anomaly detection, and cross-sectional and longitudinal analysis. Results The image registration method evaluation on 128 subjects shows low inverse consistency errors and high Dice coefficients. Also, the statistical atlas with fat content intensity values shows low standard deviation values, indicating successful deformations to the common coordinate system. The example analyses show expected associations and correlations which agree with explicit measurements, and thereby illustrate the usefulness of the proposed Imiomics concept. Conclusions The registration method is well-suited for Imiomics analyses, which enable analyses of relationships to non-imaging data, e.g. clinical data, in new types of holistic targeted and untargeted big-data analysis. PMID:28241015

Identifying image preferences based on demographic attributes

NASA Astrophysics Data System (ADS)

Fedorovskaya, Elena A.; Lawrence, Daniel R.

2014-02-01

The intent of this study is to determine what sorts of images are considered more interesting by which demographic groups. Specifically, we attempt to identify images whose interestingness ratings are influenced by the demographic attribute of the viewer's gender. To that end, we use the data from an experiment where 18 participants (9 women and 9 men) rated several hundred images based on "visual interest" or preferences in viewing images. The images were selected to represent the consumer "photo-space" - typical categories of subject matter found in consumer photo collections. They were annotated using perceptual and semantic descriptors. In analyzing the image interestingness ratings, we apply a multivariate procedure known as forced classification, a feature of dual scaling, a discrete analogue of principal components analysis (similar to correspondence analysis). This particular analysis of ratings (i.e., ordered-choice or Likert) data enables the investigator to emphasize the effect of a specific item or collection of items. We focus on the influence of the demographic item of gender on the analysis, so that the solutions are essentially confined to subspaces spanned by the emphasized item. Using this technique, we can know definitively which images' ratings have been influenced by the demographic item of choice. Subsequently, images can be evaluated and linked, on one hand, to their perceptual and semantic descriptors, and, on the other hand, to the preferences associated with viewers' demographic attributes.

Intraoral radiographs texture analysis for dental implant planning.

PubMed

Mundim, Mayara B V; Dias, Danilo R; Costa, Ronaldo M; Leles, Cláudio R; Azevedo-Marques, Paulo M; Ribeiro-Rotta, Rejane F

2016-11-01

Computer vision extracts features or attributes from images improving diagnosis accuracy and aiding in clinical decisions. This study aims to investigate the feasibility of using texture analysis of periapical radiograph images as a tool for dental implant treatment planning. Periapical radiograph images of 127 jawbone sites were obtained before and after implant placement. From the superimposition of the pre- and post-implant images, four regions of interest (ROI) were delineated on the pre-implant images for each implant site: mesial, distal and apical peri-implant areas and a central area. Each ROI was analysed using Matlab® software and seven image attributes were extracted: mean grey level (MGL), standard deviation of grey levels (SDGL), coefficient of variation (CV), entropy (En), contrast, correlation (Cor) and angular second moment (ASM). Images were grouped by bone types-Lekholm and Zarb classification (1,2,3,4). Peak insertion torque (PIT) and resonance frequency analysis (RFA) were recorded during implant placement. Differences among groups were tested for each image attribute. Agreement between measurements of the peri-implant ROIs and overall ROI (peri-implant + central area) was tested, as well as the association between primary stability measures (PIT and RFA) and texture attributes. Differences among bone type groups were found for MGL (p = 0.035), SDGL (p = 0.024), CV (p < 0.001) and En (p < 0.001). The apical ROI showed a significant difference from the other regions for all attributes, except Cor. Concordance correlation coefficients were all almost perfect (ρ > 0.93), except for ASM (ρ = 0.62). Texture attributes were significantly associated with the implant stability measures. Texture analysis of periapical radiographs may be a reliable non-invasive quantitative method for the assessment of jawbone and prediction of implant stability, with potential clinical applications. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A preliminary computer pattern analysis of satellite images of mature extratropical cyclones

NASA Technical Reports Server (NTRS)

Burfeind, Craig R.; Weinman, James A.; Barkstrom, Bruce R.

1987-01-01

This study has applied computerized pattern analysis techniques to the location and classification of features of several mature extratropical cyclones that were depicted in GOES satellite images. These features include the location of the center of the cyclone vortex core and the location of the associated occluded front. The cyclone type was classified in accord with the scheme of Troup and Streten. The present analysis was implemented on a personal computer; results were obtained within approximately one or two minutes without the intervention of an analyst.

Non-invasive, Contrast-enhanced Spectral Imaging of Breast Cancer Signatures in Preclinical Animal Models In vivo

PubMed Central

Ramanujan, V Krishnan; Ren, Songyang; Park, Sangyong; Farkas, Daniel L

2011-01-01

We report here a non-invasive multispectral imaging platform for monitoring spectral reflectance and fluorescence images from primary breast carcinoma and metastatic lymph nodes in preclinical rat model in vivo. The system is built around a monochromator light source and an acousto-optic tunable filter (AOTF) for spectral selection. Quantitative analysis of the measured reflectance profiles in the presence of a widely-used lymphazurin dye clearly demonstrates the capability of the proposed imaging platform to detect tumor-associated spectral signatures in the primary tumors as well as metastatic lymphatics. Tumor-associated changes in vascular oxygenation and interstitial fluid pressure are reasoned to be the physiological sources of the measured reflectance profiles. We also discuss the translational potential of our imaging platform in intra-operative clinical setting. PMID:21572915

Combined image and genomic analysis of high-grade serous ovarian cancer reveals PTEN loss as a common driver event and prognostic classifier.

PubMed

Martins, Filipe C; Santiago, Ines de; Trinh, Anne; Xian, Jian; Guo, Anne; Sayal, Karen; Jimenez-Linan, Mercedes; Deen, Suha; Driver, Kristy; Mack, Marie; Aslop, Jennifer; Pharoah, Paul D; Markowetz, Florian; Brenton, James D

2014-12-17

TP53 and BRCA1/2 mutations are the main drivers in high-grade serous ovarian carcinoma (HGSOC). We hypothesise that combining tissue phenotypes from image analysis of tumour sections with genomic profiles could reveal other significant driver events. Automatic estimates of stromal content combined with genomic analysis of TCGA HGSOC tumours show that stroma strongly biases estimates of PTEN expression. Tumour-specific PTEN expression was tested in two independent cohorts using tissue microarrays containing 521 cases of HGSOC. PTEN loss or downregulation occurred in 77% of the first cohort by immunofluorescence and 52% of the validation group by immunohistochemistry, and is associated with worse survival in a multivariate Cox-regression model adjusted for study site, age, stage and grade. Reanalysis of TCGA data shows that hemizygous loss of PTEN is common (36%) and expression of PTEN and expression of androgen receptor are positively associated. Low androgen receptor expression was associated with reduced survival in data from TCGA and immunohistochemical analysis of the first cohort. PTEN loss is a common event in HGSOC and defines a subgroup with significantly worse prognosis, suggesting the rational use of drugs to target PI3K and androgen receptor pathways for HGSOC. This work shows that integrative approaches combining tissue phenotypes from images with genomic analysis can resolve confounding effects of tissue heterogeneity and should be used to identify new drivers in other cancers.

Fractal and Gray Level Cooccurrence Matrix Computational Analysis of Primary Osteosarcoma Magnetic Resonance Images Predicts the Chemotherapy Response.

PubMed

Djuričić, Goran J; Radulovic, Marko; Sopta, Jelena P; Nikitović, Marina; Milošević, Nebojša T

2017-01-01

The prediction of induction chemotherapy response at the time of diagnosis may improve outcomes in osteosarcoma by allowing for personalized tailoring of therapy. The aim of this study was thus to investigate the predictive potential of the so far unexploited computational analysis of osteosarcoma magnetic resonance (MR) images. Fractal and gray level cooccurrence matrix (GLCM) algorithms were employed in retrospective analysis of MR images of primary osteosarcoma localized in distal femur prior to the OsteoSa induction chemotherapy. The predicted and actual chemotherapy response outcomes were then compared by means of receiver operating characteristic (ROC) analysis and accuracy calculation. Dbin, Λ, and SCN were the standard fractal and GLCM features which significantly associated with the chemotherapy outcome, but only in one of the analyzed planes. Our newly developed normalized fractal dimension, called the space-filling ratio (SFR) exerted an independent and much better predictive value with the prediction significance accomplished in two of the three imaging planes, with accuracy of 82% and area under the ROC curve of 0.20 (95% confidence interval 0-0.41). In conclusion, SFR as the newly designed fractal coefficient provided superior predictive performance in comparison to standard image analysis features, presumably by compensating for the tumor size variation in MR images.

A 2D/3D image analysis system to track fluorescently labeled structures in rod-shaped cells: application to measure spindle pole asymmetry during mitosis.

PubMed

Schmitter, Daniel; Wachowicz, Paulina; Sage, Daniel; Chasapi, Anastasia; Xenarios, Ioannis; Simanis; Unser, Michael

2013-01-01

The yeast Schizosaccharomyces pombe is frequently used as a model for studying the cell cycle. The cells are rod-shaped and divide by medial fission. The process of cell division, or cytokinesis, is controlled by a network of signaling proteins called the Septation Initiation Network (SIN); SIN proteins associate with the SPBs during nuclear division (mitosis). Some SIN proteins associate with both SPBs early in mitosis, and then display strongly asymmetric signal intensity at the SPBs in late mitosis, just before cytokinesis. This asymmetry is thought to be important for correct regulation of SIN signaling, and coordination of cytokinesis and mitosis. In order to study the dynamics of organelles or large protein complexes such as the spindle pole body (SPB), which have been labeled with a fluorescent protein tag in living cells, a number of the image analysis problems must be solved; the cell outline must be detected automatically, and the position and signal intensity associated with the structures of interest within the cell must be determined. We present a new 2D and 3D image analysis system that permits versatile and robust analysis of motile, fluorescently labeled structures in rod-shaped cells. We have designed an image analysis system that we have implemented as a user-friendly software package allowing the fast and robust image-analysis of large numbers of rod-shaped cells. We have developed new robust algorithms, which we combined with existing methodologies to facilitate fast and accurate analysis. Our software permits the detection and segmentation of rod-shaped cells in either static or dynamic (i.e. time lapse) multi-channel images. It enables tracking of two structures (for example SPBs) in two different image channels. For 2D or 3D static images, the locations of the structures are identified, and then intensity values are extracted together with several quantitative parameters, such as length, width, cell orientation, background fluorescence and the distance between the structures of interest. Furthermore, two kinds of kymographs of the tracked structures can be established, one representing the migration with respect to their relative position, the other representing their individual trajectories inside the cell. This software package, called "RodCellJ", allowed us to analyze a large number of S. pombe cells to understand the rules that govern SIN protein asymmetry. (Continued on next page) (Continued from previous page). "RodCellJ" is freely available to the community as a package of several ImageJ plugins to simultaneously analyze the behavior of a large number of rod-shaped cells in an extensive manner. The integration of different image-processing techniques in a single package, as well as the development of novel algorithms does not only allow to speed up the analysis with respect to the usage of existing tools, but also accounts for higher accuracy. Its utility was demonstrated on both 2D and 3D static and dynamic images to study the septation initiation network of the yeast Schizosaccharomyces pombe. More generally, it can be used in any kind of biological context where fluorescent-protein labeled structures need to be analyzed in rod-shaped cells. RodCellJ is freely available under http://bigwww.epfl.ch/algorithms.html.

Hyperspectral fluorescence imaging coupled with multivariate image analysis techniques for contaminant screening of leafy greens

NASA Astrophysics Data System (ADS)

Everard, Colm D.; Kim, Moon S.; Lee, Hoyoung

2014-05-01

The production of contaminant free fresh fruit and vegetables is needed to reduce foodborne illnesses and related costs. Leafy greens grown in the field can be susceptible to fecal matter contamination from uncontrolled livestock and wild animals entering the field. Pathogenic bacteria can be transferred via fecal matter and several outbreaks of E.coli O157:H7 have been associated with the consumption of leafy greens. This study examines the use of hyperspectral fluorescence imaging coupled with multivariate image analysis to detect fecal contamination on Spinach leaves (Spinacia oleracea). Hyperspectral fluorescence images from 464 to 800 nm were captured; ultraviolet excitation was supplied by two LED-based line light sources at 370 nm. Key wavelengths and algorithms useful for a contaminant screening optical imaging device were identified and developed, respectively. A non-invasive screening device has the potential to reduce the harmful consequences of foodborne illnesses.

Hierarchical classification strategy for Phenotype extraction from epidermal growth factor receptor endocytosis screening.

PubMed

Cao, Lu; Graauw, Marjo de; Yan, Kuan; Winkel, Leah; Verbeek, Fons J

2016-05-03

Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system. In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated. The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

NASA Astrophysics Data System (ADS)

Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

Brake Fluid Compatibility with Hardware

DTIC Science & Technology

2014-05-19

association or emblem usage considerations. All other legal considerations are the responsibility of the author and his/her/their employer(s...10 Figure 8. Backscatter SEM Image showing Elemental Analysis Scan Locations ....................... 11 Figure 9. Surface Scan jfs9176...Elemental Analysis .................................................................... 12 Figure 10. Particle Scan jfs9177 Elemental Analysis

Body image dissatisfaction: clinical features, and psychosocial disability in inflammatory bowel disease.

PubMed

McDermott, Edel; Mullen, Georgina; Moloney, Jenny; Keegan, Denise; Byrne, Kathryn; Doherty, Glen A; Cullen, Garret; Malone, Kevin; Mulcahy, Hugh E

2015-02-01

Body image refers to a person's sense of their physical appearance and body function. A negative body image self-evaluation may result in psychosocial dysfunction. Crohn's disease and ulcerative colitis are associated with disabling features, and body image dissatisfaction is a concern for many patients with inflammatory bowel disease (IBD). However, no study has assessed body image and its comorbidities in patients with IBD using validated instruments. Our aim was to explore body image dissatisfaction in patients with IBD and assess its relationship with biological and psychosocial variables. We studied 330 patients (median age, 36 yr; range, 18-83; 169 men) using quantitative and qualitative methods. Patients completed a self-administered questionnaire that included a modified Hopwood Body Image Scale, the Cash Body Image Disturbance Questionnaire, and other validated instruments. Clinical and disease activity data were also collected. Body image dissatisfaction was associated with disease activity (P < 0.001) and steroid treatment (P = 0.03) but not with immunotherapy (P = 0.57) or biological (P = 0.55) therapy. Body image dissatisfaction was also associated with low levels of general (P < 0.001) and IBD-specific (P < 0.001) quality of life, self-esteem (P < 0.001), and sexual satisfaction (P < 0.001), and with high levels of anxiety (P < 0.001) and depression (P < 0.001). Qualitative analysis indicated that patients were concerned about both physical and psychosocial consequences of body image dissatisfaction, including steroid side effects and impaired work and social activities. Body image dissatisfaction is common in patients with IBD, relates to specific clinical variables and is associated with significant psychological dysfunction. Its measurement is warranted as part of a comprehensive patient-centered IBD assessment.

Measurements and analysis in imaging for biomedical applications

NASA Astrophysics Data System (ADS)

Hoeller, Timothy L.

2009-02-01

A Total Quality Management (TQM) approach can be used to analyze data from biomedical optical and imaging platforms of tissues. A shift from individuals to teams, partnerships, and total participation are necessary from health care groups for improved prognostics using measurement analysis. Proprietary measurement analysis software is available for calibrated, pixel-to-pixel measurements of angles and distances in digital images. Feature size, count, and color are determinable on an absolute and comparative basis. Although changes in images of histomics are based on complex and numerous factors, the variation of changes in imaging analysis to correlations of time, extent, and progression of illness can be derived. Statistical methods are preferred. Applications of the proprietary measurement software are available for any imaging platform. Quantification of results provides improved categorization of illness towards better health. As health care practitioners try to use quantified measurement data for patient diagnosis, the techniques reported can be used to track and isolate causes better. Comparisons, norms, and trends are available from processing of measurement data which is obtained easily and quickly from Scientific Software and methods. Example results for the class actions of Preventative and Corrective Care in Ophthalmology and Dermatology, respectively, are provided. Improved and quantified diagnosis can lead to better health and lower costs associated with health care. Systems support improvements towards Lean and Six Sigma affecting all branches of biology and medicine. As an example for use of statistics, the major types of variation involving a study of Bone Mineral Density (BMD) are examined. Typically, special causes in medicine relate to illness and activities; whereas, common causes are known to be associated with gender, race, size, and genetic make-up. Such a strategy of Continuous Process Improvement (CPI) involves comparison of patient results to baseline data using F-statistics. Self-parings over time are also useful. Special and common causes are identified apart from aging in applying the statistical methods. In the future, implementation of imaging measurement methods by research staff, doctors, and concerned patient partners result in improved health diagnosis, reporting, and cause determination. The long-term prospects for quantified measurements are better quality in imaging analysis with applications of higher utility for heath care providers.

Integration of bioinformatics and imaging informatics for identifying rare PSEN1 variants in Alzheimer's disease.

PubMed

Nho, Kwangsik; Horgusluoglu, Emrin; Kim, Sungeun; Risacher, Shannon L; Kim, Dokyoon; Foroud, Tatiana; Aisen, Paul S; Petersen, Ronald C; Jack, Clifford R; Shaw, Leslie M; Trojanowski, John Q; Weiner, Michael W; Green, Robert C; Toga, Arthur W; Saykin, Andrew J

2016-08-12

Pathogenic mutations in PSEN1 are known to cause familial early-onset Alzheimer's disease (EOAD) but common variants in PSEN1 have not been found to strongly influence late-onset AD (LOAD). The association of rare variants in PSEN1 with LOAD-related endophenotypes has received little attention. In this study, we performed a rare variant association analysis of PSEN1 with quantitative biomarkers of LOAD using whole genome sequencing (WGS) by integrating bioinformatics and imaging informatics. A WGS data set (N = 815) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort was used in this analysis. 757 non-Hispanic Caucasian participants underwent WGS from a blood sample and high resolution T1-weighted structural MRI at baseline. An automated MRI analysis technique (FreeSurfer) was used to measure cortical thickness and volume of neuroanatomical structures. We assessed imaging and cerebrospinal fluid (CSF) biomarkers as LOAD-related quantitative endophenotypes. Single variant analyses were performed using PLINK and gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). A total of 839 rare variants (MAF < 1/√(2 N) = 0.0257) were found within a region of ±10 kb from PSEN1. Among them, six exonic (three non-synonymous) variants were observed. A single variant association analysis showed that the PSEN1 p. E318G variant increases the risk of LOAD only in participants carrying APOE ε4 allele where individuals carrying the minor allele of this PSEN1 risk variant have lower CSF Aβ1-42 and higher CSF tau. A gene-based analysis resulted in a significant association of rare but not common (MAF ≥ 0.0257) PSEN1 variants with bilateral entorhinal cortical thickness. This is the first study to show that PSEN1 rare variants collectively show a significant association with the brain atrophy in regions preferentially affected by LOAD, providing further support for a role of PSEN1 in LOAD. The PSEN1 p. E318G variant increases the risk of LOAD only in APOE ε4 carriers. Integrating bioinformatics with imaging informatics for identification of rare variants could help explain the missing heritability in LOAD.

Relationship between diverse patient body size- and image acquisition-related factors, and quantitative and qualitative image quality in coronary computed tomography angiography: a multicenter observational study.

PubMed

Utsunomiya, Daisuke; Tanaka, Ryoichi; Yoshioka, Kunihiro; Awai, Kazuo; Mochizuki, Teruhito; Matsunaga, Naofumi; Ichikawa, Tomoaki; Kanematsu, Masayuki; Kim, Tonsok; Yamashita, Yasuyuki

2016-08-01

We investigated the effects of patient- and image acquisition-related factors on the image quality in coronary CT angiography (CCTA). We enrolled 1197 patients (728 men; 65 ± 12 years). All underwent CCTA under the routine scan protocol in 23 participating hospitals. The subjective image quality (3-point Likert scale: excellent, good, and poor) and the attenuation of the left and right coronary artery (LCA, RCA) were recorded; the effects of patient and image acquisition-related factors on vascular attenuation were then compared. The mean LCA attenuation was 515.2 ± 65.8 (excellent), 401.4 ± 63.4 (good), and 319.5 ± 47.6 HU (poor). The corresponding RCA attenuation was 496.6 ± 67.6, 390.5 ± 58.5, and 308.5 ± 50.7 HU, respectively. Univariate analysis revealed significant associations between sufficient coronary attenuation (> 400 HU) and the age, gender, body surface area (BSA), number of detectors, contrast synchronization, scan mode, and the fractional contrast dose. Multivariate analysis revealed that the bolus tracking method, prospective electrocardiogram gating, and fractional contrast dose were significantly associated with sufficient coronary enhancement. BSA and fractional contrast dose are the most important patient- and image acquisition-related factors for sufficient coronary attenuation in CCTA.

Manchester visual query language

NASA Astrophysics Data System (ADS)

Oakley, John P.; Davis, Darryl N.; Shann, Richard T.

1993-04-01

We report a database language for visual retrieval which allows queries on image feature information which has been computed and stored along with images. The language is novel in that it provides facilities for dealing with feature data which has actually been obtained from image analysis. Each line in the Manchester Visual Query Language (MVQL) takes a set of objects as input and produces another, usually smaller, set as output. The MVQL constructs are mainly based on proven operators from the field of digital image analysis. An example is the Hough-group operator which takes as input a specification for the objects to be grouped, a specification for the relevant Hough space, and a definition of the voting rule. The output is a ranked list of high scoring bins. The query could be directed towards one particular image or an entire image database, in the latter case the bins in the output list would in general be associated with different images. We have implemented MVQL in two layers. The command interpreter is a Lisp program which maps each MVQL line to a sequence of commands which are used to control a specialized database engine. The latter is a hybrid graph/relational system which provides low-level support for inheritance and schema evolution. In the paper we outline the language and provide examples of useful queries. We also describe our solution to the engineering problems associated with the implementation of MVQL.

[Body image disorder in 100 Tunisian female breast cancer patients].

PubMed

Faten, Ellouze; Nader, Marrakchi; Raies, Hend; Sana, Masmoudi; Amel, Mezlini; Fadhel, M'rad Mohamed

2018-04-01

This study aimed at tracking the prevalence of body image disorder in a population of Tunisian women followed for breast cancer and the factors associated with it. The cross-sectional study was conducted at Salah-Azaiez Institute in Tunis, over a period of four months. One hundred outpatients followed for confirmed breast cancer were recruited. The questionnaire targeted the women's sexuality and their couple relationships, along with their socio-demographic, clinical, and therapeutic characteristics. The scales used were BIS, HADS, and FSFI. The prevalence of body image disorder according to BIS was 45% with an average of 11.5±11.2 among the interrogated patients, 24.7% of which reported an alteration in their couple relationships and 47% in their sexual relations. In univariate analysis, body image disorder was associated with family support, change in couple relationship, depression and anxiety. Body image disorder and sexual dysfunction were interrelated: each of them fostered the prevalence of the other. Multivariate analysis showed that occupational activity was an independent predictor and the absence of anxiety an independent protective factor. Body image disorder was an independent predictive factor of depression and anxiety. The quality of couple relation and sexuality, along with the impact of the patient's surrounding are decisive for the protection or alteration of her body image. Copyright © 2018 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.

PubMed

Gurcan, Metin N; Tomaszewski, John; Overton, James A; Doyle, Scott; Ruttenberg, Alan; Smith, Barry

2017-02-01

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology - QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts. Copyright © 2016 Elsevier Inc. All rights reserved.

Blood pulsation measurement using cameras operating in visible light: limitations.

PubMed

Koprowski, Robert

2016-10-03

The paper presents an automatic method for analysis and processing of images from a camera operating in visible light. This analysis applies to images containing the human facial area (body) and enables to measure the blood pulse rate. Special attention was paid to the limitations of this measurement method taking into account the possibility of using consumer cameras in real conditions (different types of lighting, different camera resolution, camera movement). The proposed new method of image analysis and processing was associated with three stages: (1) image pre-processing-allowing for the image filtration and stabilization (object location tracking); (2) main image processing-allowing for segmentation of human skin areas, acquisition of brightness changes; (3) signal analysis-filtration, FFT (Fast Fourier Transformation) analysis, pulse calculation. The presented algorithm and method for measuring the pulse rate has the following advantages: (1) it allows for non-contact and non-invasive measurement; (2) it can be carried out using almost any camera, including webcams; (3) it enables to track the object on the stage, which allows for the measurement of the heart rate when the patient is moving; (4) for a minimum of 40,000 pixels, it provides a measurement error of less than ±2 beats per minute for p < 0.01 and sunlight, or a slightly larger error (±3 beats per minute) for artificial lighting; (5) analysis of a single image takes about 40 ms in Matlab Version 7.11.0.584 (R2010b) with Image Processing Toolbox Version 7.1 (R2010b).

Bone marrow fat content is correlated with hepatic fat content in paediatric non-alcoholic fatty liver disease.

PubMed

Yu, N Y; Wolfson, T; Middleton, M S; Hamilton, G; Gamst, A; Angeles, J E; Schwimmer, J B; Sirlin, C B

2017-05-01

To investigate the relationship between bone marrow fat content and hepatic fat content in children with known or suspected non-alcoholic fatty liver disease (NAFLD). This was an institutional review board-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant, cross-sectional, prospective analysis of data collected between October 2010 to March 2013 in 125 children with known or suspected NAFLD. Written informed consent was obtained for same-day research magnetic resonance imaging (MRI) of the lumbar spine, liver, and abdominal adiposity. Lumbar spine bone marrow proton density fat fraction (PDFF) and hepatic PDFF were estimated using complex-based MRI (C-MRI) techniques and magnitude-based MRI (M-MRI), respectively. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SCAT) were quantified using high-resolution MRI. All images were acquired by two MRI technologists. Hepatic M-MRI images were analysed by an image analyst; all other images were analysed by a single investigator. The relationship between lumbar spine bone marrow PDFF and hepatic PDFF was assessed with and without adjusting for the presence of covariates using correlation and regression analysis. Lumbar spine bone marrow PDFF was positively associated with hepatic PDFF in children with known or suspected NAFLD prior to adjusting for covariates (r=0.33, p=0.0002). Lumbar spine bone marrow PDFF was positively associated with hepatic PDFF in children with known or suspected NAFLD (r=0.24, p=0.0079) after adjusting for age, sex, body mass index z-score, VAT, and SCAT in a multivariable regression analysis. Bone marrow fat content is positively associated with hepatic fat content in children with known or suspected NAFLD. Further research is needed to confirm these results and understand their clinical and biological implications. Copyright © 2016 The Royal College of Radiologists. All rights reserved.

Wavelet-based image analysis system for soil texture analysis

NASA Astrophysics Data System (ADS)

Sun, Yun; Long, Zhiling; Jang, Ping-Rey; Plodinec, M. John

2003-05-01

Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

Derivative spectra matching for wetland vegetation identification and classification by hyperspectral image

NASA Astrophysics Data System (ADS)

Wang, Jinnian; Zheng, Lanfen; Tong, Qingxi

1998-08-01

In this paper, we reported some research result in applying hyperspectral remote sensing data in identification and classification of wetland plant species and associations. Hyperspectral data were acquired by Modular Airborne Imaging Spectrometer (MAIS) over Poyang Lake wetland, China. A derivative spectral matching algorithm was used in hyperspectral vegetation analysis. The field measurement spectra were as reference for derivative spectral matching. In the study area, seven wetland plant associations were identified and classified with overall average accuracy is 84.03%.

Grade 3 ischemia on the admission electrocardiogram is associated with severe microvascular injury on cardiac magnetic resonance imaging after ST elevation myocardial infarction.

PubMed

Weaver, James C; Rees, David; Prasan, Ananth M; Ramsay, David D; Binnekamp, Maurits F; McCrohon, Jane A

2011-01-01

Grade 3 ischemia during ST elevation myocardial infarction (STEMI) is defined as ST elevation with distortion of the terminal portion of the QRS on electrocardiogram (ECG). The aim of this study was to evaluate the effect of ischemic grade on cardiac magnetic resonance (CMR) imaging infarct characteristics such as infarct size, microvascular obstruction (MVO), intramyocardial hemorrhage (IMH), and myocardial salvage. Patients with STEMI treated with primary percutaneous coronary intervention had a 12-lead ECG on presentation for analysis of ischemic grade. Gadolinium-enhanced CMR imaging was performed within 7 days to assess infarct size, MVO, IMH, and myocardial salvage. Of the 37 patients enrolled in the study, grade 3 ischemia was present in 32%. Those with grade 3 ischemia had higher peak troponin I levels (P = .013), more MVO (P < .001), more IMH (P < .001), larger infarct size (P = .025), and less myocardial salvage (P = .012). Regression analysis found that grade 3 ischemia, infarct size, and peak troponin I level were significantly associated with MVO and IMH. Grade 3 ischemia on the admission ECG during STEMI is closely associated with the development of severe microvascular damage on CMR imaging. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

Intracranial haemorrhage associated with ingestion of 'ecstasy'.

PubMed Central

Hughes, J C; McCabe, M; Evans, R J

1993-01-01

A case of a patient with intracranial haemorrhage thought to have been associated with ingestion of 'Ecstasy' [3-4 methylenedioxymethamphetamine (MDMA)] is presented. The case illustrates the importance of drug analysis in cases involving illicit drug use. Images Fig. 1 PMID:7906517

Shuttle Entry Imaging Using Infrared Thermography

NASA Technical Reports Server (NTRS)

Horvath, Thomas; Berry, Scott; Alter, Stephen; Blanchard, Robert; Schwartz, Richard; Ross, Martin; Tack, Steve

2007-01-01

During the Columbia Accident Investigation, imaging teams supporting debris shedding analysis were hampered by poor entry image quality and the general lack of information on optical signatures associated with a nominal Shuttle entry. After the accident, recommendations were made to NASA management to develop and maintain a state-of-the-art imagery database for Shuttle engineering performance assessments and to improve entry imaging capability to support anomaly and contingency analysis during a mission. As a result, the Space Shuttle Program sponsored an observation campaign to qualitatively characterize a nominal Shuttle entry over the widest possible Mach number range. The initial objectives focused on an assessment of capability to identify/resolve debris liberated from the Shuttle during entry, characterization of potential anomalous events associated with RCS jet firings and unusual phenomenon associated with the plasma trail. The aeroheating technical community viewed the Space Shuttle Program sponsored activity as an opportunity to influence the observation objectives and incrementally demonstrate key elements of a quantitative spatially resolved temperature measurement capability over a series of flights. One long-term desire of the Shuttle engineering community is to calibrate boundary layer transition prediction methodologies that are presently part of the Shuttle damage assessment process using flight data provided by a controlled Shuttle flight experiment. Quantitative global imaging may offer a complementary method of data collection to more traditional methods such as surface thermocouples. This paper reviews the process used by the engineering community to influence data collection methods and analysis of global infrared images of the Shuttle obtained during hypersonic entry. Emphasis is placed upon airborne imaging assets sponsored by the Shuttle program during Return to Flight. Visual and IR entry imagery were obtained with available airborne imaging platforms used within DoD along with agency assets developed and optimized for use during Shuttle ascent to demonstrate capability (i.e., tracking, acquisition of multispectral data, spatial resolution) and identify system limitations (i.e., radiance modeling, saturation) using state-of-the-art imaging instrumentation and communication systems. Global infrared intensity data have been transformed to temperature by comparison to Shuttle flight thermocouple data. Reasonable agreement is found between the flight thermography images and numerical prediction. A discussion of lessons learned and potential application to a potential Shuttle boundary layer transition flight test is presented.

Longitudinal brain white matter alterations in minimal hepatic encephalopathy before and after liver transplantation.

PubMed

Lin, Wei-Che; Chou, Kun-Hsien; Chen, Chao-Long; Chen, Hsiu-Ling; Lu, Cheng-Hsien; Li, Shau-Hsuan; Huang, Chu-Chung; Lin, Ching-Po; Cheng, Yu-Fan

2014-01-01

Cerebral edema is the common pathogenic mechanism for cognitive impairment in minimal hepatic encephalopathy. Whether complete reversibility of brain edema, cognitive deficits, and their associated imaging can be achieved after liver transplantation remains an open question. To characterize white matter integrity before and after liver transplantation in patients with minimal hepatic encephalopathy, multiple diffusivity indices acquired via diffusion tensor imaging was applied. Twenty-eight patients and thirty age- and sex-matched healthy volunteers were included. Multiple diffusivity indices were obtained from diffusion tensor images, including mean diffusivity, fractional anisotropy, axial diffusivity and radial diffusivity. The assessment was repeated 6-12 month after transplantation. Differences in white matter integrity between groups, as well as longitudinal changes, were evaluated using tract-based spatial statistical analysis. Correlation analyses were performed to identify first scan before transplantation and interval changes among the neuropsychiatric tests, clinical laboratory tests, and diffusion tensor imaging indices. After transplantation, decreased water diffusivity without fractional anisotropy change indicating reversible cerebral edema was found in the left anterior cingulate, claustrum, postcentral gyrus, and right corpus callosum. However, a progressive decrease in fractional anisotropy and an increase in radial diffusivity suggesting demyelination were noted in temporal lobe. Improved pre-transplantation albumin levels and interval changes were associated with better recoveries of diffusion tensor imaging indices. Improvements in interval diffusion tensor imaging indices in the right postcentral gyrus were correlated with visuospatial function score correction. In conclusion, longitudinal voxel-wise analysis of multiple diffusion tensor imaging indices demonstrated different white matter changes in minimal hepatic encephalopathy patients. Transplantation improved extracellular cerebral edema and the results of associated cognition tests. However, white matter demyelination may advance in temporal lobe.

The rise of global warming skepticism: exploring affective image associations in the United States over time.

PubMed

Smith, Nicholas; Leiserowitz, Anthony

2012-06-01

This article explores how affective image associations to global warming have changed over time. Four nationally representative surveys of the American public were conducted between 2002 and 2010 to assess public global warming risk perceptions, policy preferences, and behavior. Affective images (positive or negative feelings and cognitive representations) were collected and content analyzed. The results demonstrate a large increase in "naysayer" associations, indicating extreme skepticism about the issue of climate change. Multiple regression analyses found that holistic affect and "naysayer" associations were more significant predictors of global warming risk perceptions than cultural worldviews or sociodemographic variables, including political party and ideology. The results demonstrate the important role affective imagery plays in judgment and decision-making processes, how these variables change over time, and how global warming is currently perceived by the American public. © 2012 Society for Risk Analysis.

Relationships between Digestive, Circulatory, and Urinary Systems in Portuguese Primary Textbooks

ERIC Educational Resources Information Center

Carvalho, Graça S.; Clèment, Pierre

2007-01-01

In this study, 63 Portuguese primary schoolbooks (1920-2005) were analyzed. The analysis focused on text information (reference to blood absorption and association of the digestive system to other human systems) and on information from images (presence or absence of image "confusion" (when the sequence of the digestive tract is not…

Complications of Whipple surgery: imaging analysis.

PubMed

Bhosale, Priya; Fleming, Jason; Balachandran, Aparna; Charnsangavej, Chuslip; Tamm, Eric P

2013-04-01

The purpose of this article is to describe and illustrate anatomic findings after the Whipple procedure, and the appearance of its complications, on imaging. Knowledge of the cross-sectional anatomy following the Whipple procedure, and clinical findings for associated complications, are essential to rapidly and accurately diagnose such complications on postoperative studies in order to optimize treatment.

Representations of Codeine Misuse on Instagram: Content Analysis.

PubMed

Cherian, Roy; Westbrook, Marisa; Ramo, Danielle; Sarkar, Urmimala

2018-03-20

Prescription opioid misuse has doubled over the past 10 years and is now a public health epidemic. Analysis of social media data may provide additional insights into opioid misuse to supplement the traditional approaches of data collection (eg, self-report on surveys). The aim of this study was to characterize representations of codeine misuse through analysis of public posts on Instagram to understand text phrases related to misuse. We identified hashtags and searchable text phrases associated with codeine misuse by analyzing 1156 sequential Instagram posts over the course of 2 weeks from May 2016 to July 2016. Content analysis of posts associated with these hashtags identified the most common themes arising in images, as well as culture around misuse, including how misuse is happening and being perpetuated through social media. A majority of images (50/100; 50.0%) depicted codeine in its commonly misused form, combined with soda (lean). Codeine misuse was commonly represented with the ingestion of alcohol, cannabis, and benzodiazepines. Some images highlighted the previously noted affinity between codeine misuse and hip-hop culture or mainstream popular culture images. The prevalence of codeine misuse images, glamorizing of ingestion with soda and alcohol, and their integration with mainstream, popular culture imagery holds the potential to normalize and increase codeine misuse and overdose. To reduce harm and prevent misuse, immediate public health efforts are needed to better understand the relationship between the potential normalization, ritualization, and commercialization of codeine misuse. ©Roy Cherian, Marisa Westbrook, Danielle Ramo, Urmimala Sarkar. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 20.03.2018.

Body Image of Women Submitted to Breast Cancer Treatment

PubMed

Guedes, Thais Sousa Rodrigues; Dantas de Oliveira, Nayara Priscila; Holanda, Ayrton Martins; Reis, Mariane Albuquerque; Silva, Clécia Patrocínio da; Rocha e Silva, Bárbara Layse; Cancela, Marianna de Camargo; de Souza, Dyego Leandro Bezerra

2018-06-25

Background: The study of body image includes the perception of women regarding the physical appearance of their own body. The objective of the present study was to verify the prevalence of body image dissatisfaction and its associated factors in women submitted to breast cancer treatment. Methods: A cross-sectional study carried out with 103 female residents of the municipality of Natal (Northeast Brazil), diagnosed with breast cancer who had undergone cancer treatment for at least 12 months prior to the study, and remained under clinical monitoring. The variable body image was measured through the validated Body Image Scale (BIS). Socioeconomic variables and clinical history were also collected through an individual interview with each participant. The Pearson’s chi-squared test (Fisher’s Exact) was utilized for bivariate analysis, calculating the prevalence ratio with 95% confidence interval. Poisson regression with robust variance was utilized for multivariate analysis. The statistical significance considered was 0.05. Results: The prevalence of body image dissatisfaction was 74.8% CI (65%-82%). Statistically significant associations were observed between body image and multi-professional follow-up (p=0.009) and return to employment after treatment (p=0.022). Conclusion: It was concluded that women who reported employment after cancer treatment presented more alterations in self-perception concerning their appearance. Patients who did not receive multi-professional follow-up reported negative body image, evidencing the need for strategies that increase and improve healthcare, aiming to meet the demands of this population. Creative Commons Attribution License

Visualization and Quantitative Analysis of Crack-Tip Plastic Zone in Pure Nickel

NASA Astrophysics Data System (ADS)

Kelton, Randall; Sola, Jalal Fathi; Meletis, Efstathios I.; Huang, Haiying

2018-05-01

Changes in surface morphology have long been thought to be associated with crack propagation in metallic materials. We have studied areal surface texture changes around crack tips in an attempt to understand the correlations between surface texture changes and crack growth behavior. Detailed profiling of the fatigue sample surface was carried out at short fatigue intervals. An image processing algorithm was developed to calculate the surface texture changes. Quantitative analysis of the crack-tip plastic zone, crack-arrested sites near triple points, and large surface texture changes associated with crack release from arrested locations was carried out. The results indicate that surface texture imaging enables visualization of the development of plastic deformation around a crack tip. Quantitative analysis of the surface texture changes reveals the effects of local microstructures on the crack growth behavior.

Diagnostic imaging rates for head injury in the ED and states' medical malpractice tort reforms.

PubMed

Smith-Bindman, Rebecca; McCulloch, Charles E; Ding, Alexander; Ding, Alex; Quale, Christopher; Chu, Philip W

2011-07-01

Physicians' fears of being sued may lead to defensive medical practices, such as ordering nonindicated medical imaging. We investigated the association between states' medical malpractice tort reforms and neurologic imaging rates for patients seen in the emergency department with mild head trauma. We assessed neurologic imaging among a national sample of 8588 women residing in 10 US states evaluated in an emergency setting for head injury between January 1, 1992, and December 31, 2001. We assessed the odds of imaging as it varied by the enactment of medical liability reform laws. The medical liability reform laws were significantly associated with the likelihood of imaging. States with laws that limited monetary damages (odds ratio [OR], 0.63; 95% confidence interval [CI], 0.40-0.99), mandated periodic award payments (OR, 0.64; 95% CI, 0.43-0.97), or specified collateral source offset rules (OR, 0.62; 95% CI, 0.40-0.96) had an approximately 40% lower odds of imaging, whereas states that had laws that limited attorney's contingency fees had significantly higher odds of imaging (OR, 1.5; 95% CI, 0.99-2.4), compared to states without these laws. When we used a summation of the number of laws in place, the greater the number of laws, the lower the odds of imaging. In the multivariate analysis, after adjusting for individual and community factors, the total number of laws remained significantly associated with the odds of imaging, and the effect of the individual laws was attenuated, but not eliminated. The tort reforms we examined were associated with the propensity to obtain neurologic imaging. If these results are confirmed in larger studies, tort reform might mitigate defensive medical practices. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

PubMed

Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

2016-05-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Quantitative analysis of image quality for acceptance and commissioning of an MRI simulator with a semiautomatic method.

PubMed

Chen, Xinyuan; Dai, Jianrong

2018-05-01

Magnetic Resonance Imaging (MRI) simulation differs from diagnostic MRI in purpose, technical requirements, and implementation. We propose a semiautomatic method for image acceptance and commissioning for the scanner, the radiofrequency (RF) coils, and pulse sequences for an MRI simulator. The ACR MRI accreditation large phantom was used for image quality analysis with seven parameters. Standard ACR sequences with a split head coil were adopted to examine the scanner's basic performance. The performance of simulation RF coils were measured and compared using the standard sequence with different clinical diagnostic coils. We used simulation sequences with simulation coils to test the quality of image and advanced performance of the scanner. Codes and procedures were developed for semiautomatic image quality analysis. When using standard ACR sequences with a split head coil, image quality passed all ACR recommended criteria. The image intensity uniformity with a simulation RF coil decreased about 34% compared with the eight-channel diagnostic head coil, while the other six image quality parameters were acceptable. Those two image quality parameters could be improved to more than 85% by built-in intensity calibration methods. In the simulation sequences test, the contrast resolution was sensitive to the FOV and matrix settings. The geometric distortion of simulation sequences such as T1-weighted and T2-weighted images was well-controlled in the isocenter and 10 cm off-center within a range of ±1% (2 mm). We developed a semiautomatic image quality analysis method for quantitative evaluation of images and commissioning of an MRI simulator. The baseline performances of simulation RF coils and pulse sequences have been established for routine QA. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

AOIPS - An interactive image processing system. [Atmospheric and Oceanic Information Processing System

NASA Technical Reports Server (NTRS)

Bracken, P. A.; Dalton, J. T.; Quann, J. J.; Billingsley, J. B.

1978-01-01

The Atmospheric and Oceanographic Information Processing System (AOIPS) was developed to help applications investigators perform required interactive image data analysis rapidly and to eliminate the inefficiencies and problems associated with batch operation. This paper describes the configuration and processing capabilities of AOIPS and presents unique subsystems for displaying, analyzing, storing, and manipulating digital image data. Applications of AOIPS to research investigations in meteorology and earth resources are featured.

Internal PR for Education Associations. PR Bookshelf No. 4.

ERIC Educational Resources Information Center

National Education Association, Washington, DC.

This booklet contains discussion of internal public relations for a local education association with suggestions for enhancing the association's image with its members and potential members. The five sections are (1) "Start with Analysis and Evaluation"--a listing of steps in planning an internal public relations program; (2) "Orientation: A Key…

Molecular Imaging of Vasa Vasorum Neovascularization via DEspR-targeted Contrast-enhanced Ultrasound Micro-imaging in Transgenic Atherosclerosis Rat Model

PubMed Central

Decano, Julius L.; Moran, Anne Marie; Ruiz-Opazo, Nelson; Herrera, Victoria L. M.

2011-01-01

Purpose Given that carotid vasa vasorum neovascularization is associated with increased risk for stroke and cardiac events, the present in vivo study was designed to investigate molecular imaging of carotid artery vasa vasorum neovascularization via target-specific contrast-enhanced ultrasound (CEU) micro-imaging. Procedures Molecular imaging was performed in male transgenic rats with carotid artery disease and non-transgenic controls using dual endothelin1/VEGFsp receptor (DEspR)-targeted microbubbles (MBD) and the Vevo770 micro-imaging system and CEU imaging software. Results DEspR-targeted CEU-positive imaging exhibited significantly higher contrast intensity signal (CIS)-levels and pre-/post-destruction CIS-differences in seven of 13 transgenic rats, in contrast to significantly lower CIS-levels and differences in control isotype-targeted microbubble (MBC)-CEU imaging (n =8) and in MBD CEU-imaging of five non-transgenic control rats (P<0.0001). Ex vivo immunofluorescence analysis demonstrated binding of MBD to DEspR-positive endothelial cells; and association of DEspR-targeted increased contrast intensity signals with DEspR expression in vasa vasorum neovessel and intimal lesions. In vitro analysis demonstrated dose-dependent binding of MBD to DEspR-positive human endothelial cells with increasing %cells bound and number of MBD per cell, in contrast to MBC or non-labeled microbubbles (P<0.0001). Conclusion In vivo DEspR-targeted molecular imaging detected increased DEspR-expression in carotid artery lesions and in expanded vasa vasorum neovessels in transgenic rats with carotid artery disease. Future studies are needed to determine predictive value for stroke or heart disease in this transgenic atherosclerosis rat model and translational applications. PMID:20972637

A system for the real-time display of radar and video images of targets

NASA Technical Reports Server (NTRS)

Allen, W. W.; Burnside, W. D.

1990-01-01

Described here is a software and hardware system for the real-time display of radar and video images for use in a measurement range. The main purpose is to give the reader a clear idea of the software and hardware design and its functions. This system is designed around a Tektronix XD88-30 graphics workstation, used to display radar images superimposed on video images of the actual target. The system's purpose is to provide a platform for tha analysis and documentation of radar images and their associated targets in a menu-driven, user oriented environment.

Finding glenoid surface on scapula in 3D medical images for shoulder joint implant operation planning: 3D OCR

NASA Astrophysics Data System (ADS)

Mohammad Sadeghi, Majid; Kececi, Emin Faruk; Bilsel, Kerem; Aralasmak, Ayse

2017-03-01

Medical imaging has great importance in earlier detection, better treatment and follow-up of diseases. 3D Medical image analysis with CT Scan and MRI images has also been used to aid surgeries by enabling patient specific implant fabrication, where having a precise three dimensional model of associated body parts is essential. In this paper, a 3D image processing methodology for finding the plane on which the glenoid surface has a maximum surface area is proposed. Finding this surface is the first step in designing patient specific shoulder joint implant.

Improving Image Drizzling in the HST Archive: Advanced Camera for Surveys

NASA Astrophysics Data System (ADS)

Hoffmann, Samantha L.; Avila, Roberto J.

2017-06-01

The Mikulski Archive for Space Telescopes (MAST) pipeline performs geometric distortion corrections, associated image combinations, and cosmic ray rejections with AstroDrizzle on Hubble Space Telescope (HST) data. The MDRIZTAB reference table contains a list of relevant parameters that controls this program. This document details our photometric analysis of Advanced Camera for Surveys Wide Field Channel (ACS/WFC) data processed by AstroDrizzle. Based on this analysis, we update the MDRIZTAB table to improve the quality of the drizzled products delivered by MAST.

A whole brain morphometric analysis of changes associated with pre-term birth

NASA Astrophysics Data System (ADS)

Thomaz, C. E.; Boardman, J. P.; Counsell, S.; Hill, D. L. G.; Hajnal, J. V.; Edwards, A. D.; Rutherford, M. A.; Gillies, D. F.; Rueckert, D.

2006-03-01

Pre-term birth is strongly associated with subsequent neuropsychiatric impairment. To identify structural differences in preterm infants we have examined a dataset of magnetic resonance (MR) images containing 88 preterm infants and 19 term born controls. We have analyzed these images by combining image registration, deformation based morphometry (DBM), multivariate statistics, and effect size maps (ESM). The methodology described has been performed directly on the MR intensity images rather than on segmented versions of the images. The results indicate that the approach described makes clear the statistical differences between the control and preterm samples, showing a leave-one-out classification accuracy of 94.74% and 95.45% respectively. In addition, finding the most discriminant direction between the groups and using DBM features and ESM we are able to identify not only what are the changes between preterm and term groups but also how relatively relevant they are in terms of volume expansion and contraction.

THE ASSOCIATION BETWEEN MENSTRUAL CYCLE CHARACTERISTICS AND PERCEIVED BODY IMAGE: A CROSS-SECTIONAL SURVEY OF POLISH FEMALE ADOLESCENTS.

PubMed

Kaczmarek, Maria; Trambacz-Oleszak, Sylwia

2016-05-01

The increasing prevalence of negative body perceptions among adolescent girls and the tendency towards wishing to be thinner have become a cultural norm in Western culture. Adolescent girls are particularly vulnerable to developing a negative body image due to physical and sexual changes occurring during puberty. This study aimed to evaluate the association between different measures of body image perceptions and different phases of the menstrual cycle after controlling for weight status and other potential confounders in Polish adolescent girls aged 12-18 years. Three-hundred and thirty participants of a cross-sectional survey conducted in 2009, normally cycling and with no eating disorders, completed a background questionnaire and the Stunkard Figure Rating Scale, and their anthropometric measurements were collected. The dependent outcome variables were measures of body image (actual body image, ideal body image and ideal-self discrepancy) and dichotomous body image perception (satisfied versus dissatisfied) adjusted for other predictor factors: socio-demographic variables, menstrual history and cycle phases, and weight status. One-way ANOVA indicated that weight status, age at menarche and menstrual cycle phase were associated with actual body image and rate of ideal-self discrepancy. Ideal body image was associated with weight status and menstrual cycle phase. General logistic regression models were constructed to evaluate associations of body dissatisfaction and all potential predictor variables. The final selected model of the multiple logistic regression analysis using the backward elimination procedure revealed that adjusted for other factors, negative body image was significantly associated with different phases of the menstrual cycle (p trend=0.033) and increasing body weight status (p trend=0.0007). The likelihood of body dissatisfaction was greatest during the premenstrual phase of the menstrual cycle (OR=2.38; 95% CI 1.06, 5.32) and among girls in obesity class I (OR=8.04; 95% CI 2.37, 27.26). The study confirmed the association between body image dissatisfaction in adolescent girls and different phases of the menstrual cycle after controlling for weight status. The issue of negative body self-image is not only of cognitive, but also of practical value as understanding better the factors contributing to the formation of a negative body image may be instrumental in developing preventive health programmes targeted at young people.

Quantitative assessment of the impact of biomedical image acquisition on the results obtained from image analysis and processing.

PubMed

Koprowski, Robert

2014-07-04

Dedicated, automatic algorithms for image analysis and processing are becoming more and more common in medical diagnosis. When creating dedicated algorithms, many factors must be taken into consideration. They are associated with selecting the appropriate algorithm parameters and taking into account the impact of data acquisition on the results obtained. An important feature of algorithms is the possibility of their use in other medical units by other operators. This problem, namely operator's (acquisition) impact on the results obtained from image analysis and processing, has been shown on a few examples. The analysed images were obtained from a variety of medical devices such as thermal imaging, tomography devices and those working in visible light. The objects of imaging were cellular elements, the anterior segment and fundus of the eye, postural defects and others. In total, almost 200'000 images coming from 8 different medical units were analysed. All image analysis algorithms were implemented in C and Matlab. For various algorithms and methods of medical imaging, the impact of image acquisition on the results obtained is different. There are different levels of algorithm sensitivity to changes in the parameters, for example: (1) for microscope settings and the brightness assessment of cellular elements there is a difference of 8%; (2) for the thyroid ultrasound images there is a difference in marking the thyroid lobe area which results in a brightness assessment difference of 2%. The method of image acquisition in image analysis and processing also affects: (3) the accuracy of determining the temperature in the characteristic areas on the patient's back for the thermal method - error of 31%; (4) the accuracy of finding characteristic points in photogrammetric images when evaluating postural defects - error of 11%; (5) the accuracy of performing ablative and non-ablative treatments in cosmetology - error of 18% for the nose, 10% for the cheeks, and 7% for the forehead. Similarly, when: (7) measuring the anterior eye chamber - there is an error of 20%; (8) measuring the tooth enamel thickness - error of 15%; (9) evaluating the mechanical properties of the cornea during pressure measurement - error of 47%. The paper presents vital, selected issues occurring when assessing the accuracy of designed automatic algorithms for image analysis and processing in bioengineering. The impact of acquisition of images on the problems arising in their analysis has been shown on selected examples. It has also been indicated to which elements of image analysis and processing special attention should be paid in their design.

Tumor image signatures and habitats: a processing pipeline of multimodality metabolic and physiological images.

PubMed

You, Daekeun; Kim, Michelle M; Aryal, Madhava P; Parmar, Hemant; Piert, Morand; Lawrence, Theodore S; Cao, Yue

2018-01-01

To create tumor "habitats" from the "signatures" discovered from multimodality metabolic and physiological images, we developed a framework of a processing pipeline. The processing pipeline consists of six major steps: (1) creating superpixels as a spatial unit in a tumor volume; (2) forming a data matrix [Formula: see text] containing all multimodality image parameters at superpixels; (3) forming and clustering a covariance or correlation matrix [Formula: see text] of the image parameters to discover major image "signatures;" (4) clustering the superpixels and organizing the parameter order of the [Formula: see text] matrix according to the one found in step 3; (5) creating "habitats" in the image space from the superpixels associated with the "signatures;" and (6) pooling and clustering a matrix consisting of correlation coefficients of each pair of image parameters from all patients to discover subgroup patterns of the tumors. The pipeline was applied to a dataset of multimodality images in glioblastoma (GBM) first, which consisted of 10 image parameters. Three major image "signatures" were identified. The three major "habitats" plus their overlaps were created. To test generalizability of the processing pipeline, a second image dataset from GBM, acquired on the scanners different from the first one, was processed. Also, to demonstrate the clinical association of image-defined "signatures" and "habitats," the patterns of recurrence of the patients were analyzed together with image parameters acquired prechemoradiation therapy. An association of the recurrence patterns with image-defined "signatures" and "habitats" was revealed. These image-defined "signatures" and "habitats" can be used to guide stereotactic tissue biopsy for genetic and mutation status analysis and to analyze for prediction of treatment outcomes, e.g., patterns of failure.

Automated discovery of structural features of the optic nerve head on the basis of image and genetic data

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2014-03-01

Evaluation of optic nerve head (ONH) structure is a commonly used clinical technique for both diagnosis and monitoring of glaucoma. Glaucoma is associated with characteristic changes in the structure of the ONH. We present a method for computationally identifying ONH structural features using both imaging and genetic data from a large cohort of participants at risk for primary open angle glaucoma (POAG). Using 1054 participants from the Ocular Hypertension Treatment Study, ONH structure was measured by application of a stereo correspondence algorithm to stereo fundus images. In addition, the genotypes of several known POAG genetic risk factors were considered for each participant. ONH structural features were discovered using both a principal component analysis approach to identify the major modes of variance within structural measurements and a linear discriminant analysis approach to capture the relationship between genetic risk factors and ONH structure. The identified ONH structural features were evaluated based on the strength of their associations with genotype and development of POAG by the end of the OHTS study. ONH structural features with strong associations with genotype were identified for each of the genetic loci considered. Several identified ONH structural features were significantly associated (p < 0.05) with the development of POAG after Bonferroni correction. Further, incorporation of genetic risk status was found to substantially increase performance of early POAG prediction. These results suggest incorporating both imaging and genetic data into ONH structural modeling significantly improves the ability to explain POAG-related changes to ONH structure.

Changes in quantitative 3D shape features of the optic nerve head associated with age

NASA Astrophysics Data System (ADS)

Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

2013-02-01

Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

Wavelet analysis for wind fields estimation.

PubMed

Leite, Gladeston C; Ushizima, Daniela M; Medeiros, Fátima N S; de Lima, Gilson G

2010-01-01

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(-1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms.

Prevalence of body image dissatisfaction and associated factors among physical education students.

PubMed

Ferrari, Elisa Pinheiro; Petroski, Edio Luiz; Silva, Diego Augusto Santos

2013-01-01

To determine the prevalence of and factors associated with body image dissatisfaction among physical education students enrolled in a public university. This study evaluated 236 students and assessed body image perception (silhouette scale), sociodemographic variables (sex, age, parental education, marital status, university course, work, living arrangement, study shift, and income), physical activity level (International Physical Activity Questionnaire - Short Version), dietary habits, tobacco use, excessive intake of alcohol (questions from the tobacco, alcohol and drugs, and nutrition domains of the FANTASTIC instrument), and nutritional status (body mass index [BMI]). Descriptive analysis, the chi-square test, Fisher's exact test, and crude and adjusted multinomial regression were used. The prevalence of body image dissatisfaction was 69.5%; 44.1% were dissatisfied with excess weight. BMI ≥ 25.0 kg/m² was associated with dissatisfaction with excess weight; factors associated with dissatisfaction with slimness were being male, eating an unhealthy diet, and smoking tobacco. Our findings suggest that female college students with a BMI ≥ 25.0 kg/m² are more likely to present dissatisfaction with excess weight. Being male, eating an unhealthy diet, engaging in physical activity for < 739.61 min/week and smoking tobacco were the variables associated with dissatisfaction with thinness.

Seeing shapes in seemingly random spatial patterns: Fractal analysis of Rorschach inkblots

PubMed Central

Taylor, R. P.; Martin, T. P.; Montgomery, R. D.; Smith, J. H.; Micolich, A. P.; Boydston, C.; Scannell, B. C.; Fairbanks, M. S.; Spehar, B.

2017-01-01

Rorschach inkblots have had a striking impact on the worlds of art and science because of the remarkable variety of associations with recognizable and namable objects they induce. Originally adopted as a projective psychological tool to probe mental health, psychologists and artists have more recently interpreted the variety of induced images simply as a signature of the observers’ creativity. Here we analyze the relationship between the spatial scaling parameters of the inkblot patterns and the number of induced associations, and suggest that the perceived images are induced by the fractal characteristics of the blot edges. We discuss how this relationship explains the frequent observation of images in natural scenery. PMID:28196082

What good is SWIR? Passive day comparison of VIS, NIR, and SWIR

NASA Astrophysics Data System (ADS)

Driggers, Ronald G.; Hodgkin, Van; Vollmerhausen, Richard

2013-06-01

This paper is the first of three papers associated with the military benefits of SWIR imaging. This paper describes the benefits associated with passive daytime operations with comparisons of SWIR, NIR, and VIS bands and sensors. This paper includes quantitative findings from previously published papers, analysis of open source data, summaries of various expert analyses, and calculations of notional system performance. We did not accept anecdotal findings as acceptable benefits. Topics include haze and fog penetration, atmospheric transmission, cloud and smoke penetration, target and background contrasts, spectral discrimination, turbulence degradation, and long range target identification. The second and third papers will address passive night imaging and active night imaging.

Information extraction from multivariate images

NASA Technical Reports Server (NTRS)

Park, S. K.; Kegley, K. A.; Schiess, J. R.

1986-01-01

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

Pathophysiology of Degenerative Mitral Regurgitation: New 3-Dimensional Imaging Insights.

PubMed

Antoine, Clemence; Mantovani, Francesca; Benfari, Giovanni; Mankad, Sunil V; Maalouf, Joseph F; Michelena, Hector I; Enriquez-Sarano, Maurice

2018-01-01

Despite its high prevalence, little is known about mechanisms of mitral regurgitation in degenerative mitral valve disease apart from the leaflet prolapse itself. Mitral valve is a complex structure, including mitral annulus, mitral leaflets, papillary muscles, chords, and left ventricular walls. All these structures are involved in physiological and pathological functioning of this valvuloventricular complex but up to now were difficult to analyze because of inherent limitations of 2-dimensional imaging. The advent of 3-dimensional echocardiography, computed tomography, and cardiac magnetic resonance imaging overcoming these limitations provides new insights into mechanistic analysis of degenerative mitral regurgitation. This review will detail the contribution of quantitative and qualitative dynamic analysis of mitral annulus and mitral leaflets by new imaging methods in the understanding of degenerative mitral regurgitation pathophysiology. © 2018 American Heart Association, Inc.

High-Throughput Particle Uptake Analysis by Imaging Flow Cytometry

PubMed Central

Smirnov, Asya; Solga, Michael D.; Lannigan, Joanne; Criss, Alison K.

2017-01-01

Quantifying the efficiency of particle uptake by host cells is important in fields including infectious diseases, autoimmunity, cancer, developmental biology, and drug delivery. Here we present a protocol for high-throughput analysis of particle uptake using imaging flow cytometry, using the bacterium Neisseria gonorrhoeae attached and internalized to neutrophils as an example. Cells are exposed to fluorescently labeled bacteria, fixed, and stained with a bacteria-specific antibody of a different fluorophore. Thus in the absence of a permeabilizing agent, extracellular bacteria are double-labeled with two fluorophores while intracellular bacteria remain single-labeled. A spot count algorithm is used to determine the number of single- and double-labeled bacteria in individual cells, to calculate the percent of cells associated with bacteria, percent of cells with internalized bacteria, and percent of cell-associated bacteria that are internalized. These analyses quantify bacterial association and internalization across thousands of cells and can be applied to diverse experimental systems. PMID:28369762

Computer-based analysis of microvascular alterations in a mouse model for Alzheimer's disease

NASA Astrophysics Data System (ADS)

Heinzer, Stefan; Müller, Ralph; Stampanoni, Marco; Abela, Rafael; Meyer, Eric P.; Ulmann-Schuler, Alexandra; Krucker, Thomas

2007-03-01

Vascular factors associated with Alzheimer's disease (AD) have recently gained increased attention. To investigate changes in vascular, particularly microvascular architecture, we developed a hierarchical imaging framework to obtain large-volume, high-resolution 3D images from brains of transgenic mice modeling AD. In this paper, we present imaging and data analysis methods which allow compiling unique characteristics from several hundred gigabytes of image data. Image acquisition is based on desktop micro-computed tomography (µCT) and local synchrotron-radiation µCT (SRµCT) scanning with a nominal voxel size of 16 µm and 1.4 µm, respectively. Two visualization approaches were implemented: stacks of Z-buffer projections for fast data browsing, and progressive-mesh based surface rendering for detailed 3D visualization of the large datasets. In a first step, image data was assessed visually via a Java client connected to a central database. Identified characteristics of interest were subsequently quantified using global morphometry software. To obtain even deeper insight into microvascular alterations, tree analysis software was developed providing local morphometric parameters such as number of vessel segments or vessel tortuosity. In the context of ever increasing image resolution and large datasets, computer-aided analysis has proven both powerful and indispensable. The hierarchical approach maintains the context of local phenomena, while proper visualization and morphometry provide the basis for detailed analysis of the pathology related to structure. Beyond analysis of microvascular changes in AD this framework will have significant impact considering that vascular changes are involved in other neurodegenerative diseases as well as in cancer, cardiovascular disease, asthma, and arthritis.

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

Repressive coping among British college women: A potential protective factor against body image concerns, drive for thinness, and bulimia symptoms.

PubMed

Mohiyeddini, Changiz

2017-09-01

Repressive coping, as a means of preserving a positive self-image, has been widely explored in the context of dealing with self-evaluative cues. The current study extends this research by exploring whether repressive coping is associated with lower levels of body image concerns, drive for thinness, bulimic symptoms, and higher positive rational acceptance. A sample of 229 female college students was recruited in South London. Repressive coping was measured via the interaction between trait anxiety and defensiveness. The results of moderated regression analysis with simple slope analysis show that compared to non-repressors, repressors reported lower levels of body image concerns, drive for thinness, and bulimic symptoms while exhibiting a higher use of positive rational acceptance. These findings, in line with previous evidence, suggest that repressive coping may be adaptive particularly in the context of body image. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating number and size of forest patches from FIA plot data

Treesearch

Mark D. Nelson; Andrew J. Lister; Mark H. Hansen

2009-01-01

Forest inventory and analysis (FIA) annual plot data provide for estimates of forest area, type, volume, growth, and other attributes. Estimates of forest landscape metrics, such as those describing abundance, size, and shape of forest patches, however, typically are not derived from FIA plot data but from satellite image-based land cover maps. Associating image-based...

The Assessment of Neurological Systems with Functional Imaging

ERIC Educational Resources Information Center

Eidelberg, David

2007-01-01

In recent years a number of multivariate approaches have been introduced to map neural systems in health and disease. In this review, we focus on spatial covariance methods applied to functional imaging data to identify patterns of regional activity associated with behavior. In the rest state, this form of network analysis can be used to detect…

Effective and efficient analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen very soon. This dissertation is composed of three parts: an introduction, some basic knowledges and relative works, and my own three contributions to the development of approaches for spatio-temporal data mining: DYSTAL algorithm, STARSI algorithm, and COSTCOP+ algorithm.

Machine learning to analyze images of shocked materials for precise and accurate measurements

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

Dresselhaus-Cooper, Leora; Howard, Marylesa; Hock, Margaret C.

A supervised machine learning algorithm, called locally adaptive discriminant analysis (LADA), has been developed to locate boundaries between identifiable image features that have varying intensities. LADA is an adaptation of image segmentation, which includes techniques that find the positions of image features (classes) using statistical intensity distributions for each class in the image. In order to place a pixel in the proper class, LADA considers the intensity at that pixel and the distribution of intensities in local (nearby) pixels. This paper presents the use of LADA to provide, with statistical uncertainties, the positions and shapes of features within ultrafast imagesmore » of shock waves. We demonstrate the ability to locate image features including crystals, density changes associated with shock waves, and material jetting caused by shock waves. This algorithm can analyze images that exhibit a wide range of physical phenomena because it does not rely on comparison to a model. LADA enables analysis of images from shock physics with statistical rigor independent of underlying models or simulations.« less

Body image and eating attitudes among adolescent Chinese girls in Hong Kong.

PubMed

Fung, Maria S C; Yuen, Mantak

2003-02-01

The study investigated the relation between body image and eating attitudes among adolescent girls in Hong Kong. A sample of 358 senior secondary school girls completed the measures assessing body-part satisfaction and behaviors associated with eating. Analysis indicated that even though only 4.8% of the girls were overweight, 85.16% desired to weigh less. These Chinese teenage girls were concerned about their weight, and the desire for slimness was widespread. Correlations indicated that higher Body Mass Index was associated with lower satisfaction with weight. Lower scores on weight satisfaction were associated with higher scores on attitudes of dieting and food preoccupation.

Gleason Score Determination with Transrectal Ultrasound-Magnetic Resonance Imaging Fusion Guided Prostate Biopsies--Are We Gaining in Accuracy?

PubMed

Lanz, Camille; Cornud, François; Beuvon, Frédéric; Lefèvre, Arnaud; Legmann, Paul; Zerbib, Marc; Delongchamps, Nicolas Barry

2016-01-01

We evaluated the accuracy of prostate magnetic resonance imaging- transrectal ultrasound targeted biopsy for Gleason score determination. We selected 125 consecutive patients treated with radical prostatectomy for a clinically localized prostate cancer diagnosed on magnetic resonance imaging-transrectal ultrasound targeted biopsy and/or systematic biopsy. On multiparametric magnetic resonance imaging each suspicious area was graded according to PI-RADS™ score. A correlation analysis between multiparametric magnetic resonance imaging and pathological findings was performed. Factors associated with determining the accuracy of Gleason score on targeted biopsy were statistically assessed. Pathological analysis of radical prostatectomy specimens detected 230 tumor foci. Multiparametric magnetic resonance imaging detected 151 suspicious areas. Of these areas targeted biopsy showed 126 cancer foci in 115 patients, and detected the index lesion in all of them. The primary Gleason grade, secondary Gleason grade and Gleason score of the 126 individual tumors were determined accurately in 114 (90%), 75 (59%) and 85 (67%) cases, respectively. Maximal Gleason score was determined accurately in 80 (70%) patients. Gleason score determination accuracy on targeted biopsy was significantly higher for low Gleason and high PI-RADS score tumors. Magnetic resonance imaging-transrectal ultrasound targeted biopsy allowed for an accurate estimation of Gleason score in more than two-thirds of patients. Gleason score misclassification was mostly due to a lack of accuracy in the determination of the secondary Gleason grade. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

What Does a Shoulder MRI Cost the Consumer?

PubMed

Westermann, Robert W; Schick, Cameron; Graves, Christopher M; Duchman, Kyle R; Weinstein, Stuart L

2017-03-01

More than 100 MRIs per 1000 inhabitants are performed in the United States annually, more than almost every other country. Little is known regarding the cost of obtaining an MRI and factors associated with differences in cost. By surveying all hospital-owned and independent imaging centers in Iowa, we wished to determine (1) the cost to the consumer of obtaining a noncontrast shoulder MRI, (2) the frequency and magnitude of discounts provided, and (3) factors associated with differences in cost including location (hospital-owned or independent) and Centers for Medicare & Medicaid Services designation (rural, urban, and critical access). There were 71 hospitals and 26 independent imaging centers that offered MRI services in Iowa. Each site was contacted via telephone and posed a scripted request for the cost of the technical component of a noncontrast shoulder MRI. Radiologists' reading fees were not considered. Statistical analysis was performed using standard methods and significance was defined as a probability less than 0.05. The mean technical component cost to consumers for an MRI was USD 1874 ± USD 694 (range, USD 500-USD 4000). Discounts were offered by 49% of imaging centers, with a mean savings of 21%. Factors associated with increased cost include hospital-owned imaging centers (USD 2062 ± USD 664 versus USD 1400 ± USD 441 at independent imaging centers; p < 0.001; mean difference, USD 662; 95% CI, USD 351-USD 893) and rural imaging centers, unless designated as a critical access hospital (USD 2213 ± USD 668 versus USD 1794 ± USD 680; p = 0.0202; mean difference, USD 419; 95% CI, USD 66-USD 772). In Iowa, the cost to the consumer of a shoulder MRI is significantly less at independent imaging centers compared with hospital-owned centers. Referring physicians and healthcare consumers should be aware that there may be substantial price discrepancies between centers that provide advanced imaging services. Level IV, Economic and decision analysis.

Heterogeneity of Glucose Metabolism in Esophageal Cancer Measured by Fractal Analysis of Fluorodeoxyglucose Positron Emission Tomography Image: Correlation between Metabolic Heterogeneity and Survival.

PubMed

Tochigi, Toru; Shuto, Kiyohiko; Kono, Tsuguaki; Ohira, Gaku; Tohma, Takayuki; Gunji, Hisashi; Hayano, Koichi; Narushima, Kazuo; Fujishiro, Takeshi; Hanaoka, Toshiharu; Akutsu, Yasunori; Okazumi, Shinichi; Matsubara, Hisahiro

2017-01-01

Intratumoral heterogeneity is a well-recognized characteristic feature of cancer. The purpose of this study is to assess the heterogeneity of the intratumoral glucose metabolism using fractal analysis, and evaluate its prognostic value in patients with esophageal squamous cell carcinoma (ESCC). 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) studies of 79 patients who received curative surgery were evaluated. FDG-PET images were analyzed using fractal analysis software, where differential box-counting method was employed to calculate the fractal dimension (FD) of the tumor lesion. Maximum standardized uptake value (SUVmax) and FD were compared with overall survival (OS). The median SUVmax and FD of ESCCs in this cohort were 13.8 and 1.95, respectively. In univariate analysis performed using Cox's proportional hazard model, T stage and FD showed significant associations with OS (p = 0.04, p < 0.0001, respectively), while SUVmax did not (p = 0.1). In Kaplan-Meier analysis, the low FD tumor (<1.95) showed a significant association with favorable OS (p < 0.0001). In wthe multivariate analysis among TNM staging, serum tumor markers, FD, and SUVmax, the FD was identified as the only independent prognostic factor for OS (p = 0.0006; hazards ratio 0.251, 95% CI 0.104-0.562). Metabolic heterogeneity measured by fractal analysis can be a novel imaging biomarker for survival in patients with ESCC. © 2016 S. Karger AG, Basel.

Beyond the limits of present active matrix flat-panel imagers (AMFPIs) for diagnostic radiology

NASA Astrophysics Data System (ADS)

Antonuk, Larry E.; El-Mohri, Youcef; Jee, Kyung-Wook; Maolinbay, Manat; Nassif, Samer C.; Rong, Xiujiang; Siewerdsen, Jeffrey H.; Zhao, Qihua; Street, Robert A.

1999-05-01

A theoretical cascaded systems analysis of the performance limits of x-ray imagers based on thin-film, active matrix flat-panel technology is presented. This analysis specifically focuses upon an examination of the functional dependence of the detective quantum efficiency on exposure. While the DQE of AMFPI systems is relatively high at the large exposure levels associated with radiographic x-ray imaging, there is a significant decline in DQE with decreasing exposure over the medium and lower end of the exposure range associated with fluoroscopic imaging. This fall-off in DQE originates from the relatively large size of the additive noise of AMFPI systems compared to their overall system gain. Therefore, strategies to diminish additive noise and increase system gain should significantly improve performance. Potential strategies for noise reduction include the use of charge compensation lines while strategies for gain enhancement include continuous photodiodes, pixel amplification structures, or higher gain converters. The effect of the implementation of such strategies is examined for a variety for hypothetical imager configurations. Through the modeling of these configurations, such enhancements are shown to hold the potential of making low frequency DQE response large and essentially independent of exposure while greatly reducing the fall-off in DQE at higher spatial frequencies.

Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the "i-ROP" System and Image Features Associated With Expert Diagnosis.

PubMed

Ataer-Cansizoglu, Esra; Bolon-Canedo, Veronica; Campbell, J Peter; Bozkurt, Alican; Erdogmus, Deniz; Kalpathy-Cramer, Jayashree; Patel, Samir; Jonas, Karyn; Chan, R V Paul; Ostmo, Susan; Chiang, Michael F

2015-11-01

We developed and evaluated the performance of a novel computer-based image analysis system for grading plus disease in retinopathy of prematurity (ROP), and identified the image features, shapes, and sizes that best correlate with expert diagnosis. A dataset of 77 wide-angle retinal images from infants screened for ROP was collected. A reference standard diagnosis was determined for each image by combining image grading from 3 experts with the clinical diagnosis from ophthalmoscopic examination. Manually segmented images were cropped into a range of shapes and sizes, and a computer algorithm was developed to extract tortuosity and dilation features from arteries and veins. Each feature was fed into our system to identify the set of characteristics that yielded the highest-performing system compared to the reference standard, which we refer to as the "i-ROP" system. Among the tested crop shapes, sizes, and measured features, point-based measurements of arterial and venous tortuosity (combined), and a large circular cropped image (with radius 6 times the disc diameter), provided the highest diagnostic accuracy. The i-ROP system achieved 95% accuracy for classifying preplus and plus disease compared to the reference standard. This was comparable to the performance of the 3 individual experts (96%, 94%, 92%), and significantly higher than the mean performance of 31 nonexperts (81%). This comprehensive analysis of computer-based plus disease suggests that it may be feasible to develop a fully-automated system based on wide-angle retinal images that performs comparably to expert graders at three-level plus disease discrimination. Computer-based image analysis, using objective and quantitative retinal vascular features, has potential to complement clinical ROP diagnosis by ophthalmologists.

Nuclear morphometry in flat epithelial atypia of the breast as a predictor of malignancy: a digital image-based histopathologic analysis.

PubMed

Williams, Phillip A; Djordjevic, Bojana; Ayroud, Yasmine; Islam, Shahidul; Gravel, Denis; Robertson, Susan J; Parra-Herran, Carlos

2014-12-01

To identify morphometric features unique to flat epithelial atypia associated with cancer using digital image analysis. Cases with diagnosis of flat epithelial atypia were retrieved and divided into 2 groups: flat epithelial atypia associated with invasive or in situ carcinoma (n = 31) and those without malignancy (n = 27). Slides were digitally scanned. Nuclear features were analyzed on representative images at 20x magnification using digital morphometric software. Parameters related to nuclear shape and size (diameter, perimeter) were similar in both groups. However, cases with malignancy had significantly higher densitometric green (p = 0.02), red (p = 0.03), and grey (p = 0.02) scale levels as compared to cases without cancer. A mean grey densitometric level > 119.45 had 71% sensitivity and 70.4% specificity in detecting cases with concomitant carcinoma. Morphometry of features related to nuclear staining appears to be useful in predicting risk of concurrent malignancy in patients with flat epithelial atypia, when added to a comprehensive histopathologic evaluation.

Multicell migration tracking within angiogenic networks by deep learning-based segmentation and augmented Bayesian filtering.

PubMed

Wang, Mengmeng; Ong, Lee-Ling Sharon; Dauwels, Justin; Asada, H Harry

2018-04-01

Cell migration is a key feature for living organisms. Image analysis tools are useful in studying cell migration in three-dimensional (3-D) in vitro environments. We consider angiogenic vessels formed in 3-D microfluidic devices (MFDs) and develop an image analysis system to extract cell behaviors from experimental phase-contrast microscopy image sequences. The proposed system initializes tracks with the end-point confocal nuclei coordinates. We apply convolutional neural networks to detect cell candidates and combine backward Kalman filtering with multiple hypothesis tracking to link the cell candidates at each time step. These hypotheses incorporate prior knowledge on vessel formation and cell proliferation rates. The association accuracy reaches 86.4% for the proposed algorithm, indicating that the proposed system is able to associate cells more accurately than existing approaches. Cell culture experiments in 3-D MFDs have shown considerable promise for improving biology research. The proposed system is expected to be a useful quantitative tool for potential microscopy problems of MFDs.

Scanning capacitance microscopy of ErAs nanoparticles embedded in GaAs pn junctions

NASA Astrophysics Data System (ADS)

Park, K. W.; Nair, H. P.; Crook, A. M.; Bank, S. R.; Yu, E. T.

2011-09-01

Scanning capacitance microscopy is used to characterize the electronic properties of ErAs nanoparticles embedded in GaAs pn junctions grown by molecular beam epitaxy. Voltage-dependent capacitance images reveal localized variations in subsurface electronic structure near buried ErAs nanoparticles at lateral length scales of 20-30 nm. Numerical modeling indicates that these variations arise from inhomogeneities in charge modulation due to Fermi level pinning behavior associated with the embedded ErAs nanoparticles. Statistical analysis of image data yields an average particle radius of 6-8 nm—well below the direct resolution limit in scanning capacitance microscopy but discernible via analysis of patterns in nanoscale capacitance images.

Smartphone-based colorimetric analysis for detection of saliva alcohol concentration.

PubMed

Jung, Youngkee; Kim, Jinhee; Awofeso, Olumide; Kim, Huisung; Regnier, Fred; Bae, Euiwon

2015-11-01

A simple device and associated analytical methods are reported. We provide objective and accurate determination of saliva alcohol concentrations using smartphone-based colorimetric imaging. The device utilizes any smartphone with a miniature attachment that positions the sample and provides constant illumination for sample imaging. Analyses of histograms based on channel imaging of red-green-blue (RGB) and hue-saturation-value (HSV) color space provide unambiguous determination of blood alcohol concentration from color changes on sample pads. A smartphone-based sample analysis by colorimetry was developed and tested with blind samples that matched with the training sets. This technology can be adapted to any smartphone and used to conduct color change assays.

[Myocardial perfusion scintigraphy - short form of the German guideline].

PubMed

Lindner, O; Burchert, W; Hacker, M; Schaefer, W; Schmidt, M; Schober, O; Schwaiger, M; vom Dahl, J; Zimmermann, R; Schäfers, M

2013-01-01

This guideline is a short summary of the guideline for myocardial perfusion scintigraphy published by the Association of the Scientific Medical Societies in Ger-many (AWMF). The purpose of this guideline is to provide practical assistance for indication and examination procedures as well as image analysis and to present the state-of-the-art of myocardial-perfusion-scintigraphy. After a short introduction on the fundamentals of imaging, precise and detailed information is given on the indications, patient preparation, stress testing, radiopharmaceuticals, examination protocols and techniques, radiation exposure, data reconstruction as well as information on visual and quantitative image analysis and interpretation. In addition possible pitfalls, artefacts and key elements of reporting are described.

PhAst: A Flexible IDL Astronomical Image Viewer

NASA Astrophysics Data System (ADS)

Rehnberg, Morgan; Crawford, R.; Trueblood, M.; Mighell, K.

2012-01-01

We present near-Earth asteroid data analyzed with PhAst, a new IDL astronomical image viewer based on the existing application ATV. PhAst opens, displays, and analyzes an arbitrary number of FITS images. Analysis packages include image calibration, photometry, and astrometry (provided through an interface with SExtractor, SCAMP, and missFITS). PhAst has been designed to generate reports for Minor Planet Center reporting. PhAst is cross platform (Linux/Mac OSX/Windows for image viewing and Linux/Mac OSX for image analysis) and can be downloaded from the following website at NOAO: http://www.noao.edu/staff/mighell/phast/. Rehnberg was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program and the Department of Defense ASSURE program through Scientific Program Order No. 13 (AST-0754223) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF.

Exploratory analysis of TOF-SIMS data from biological surfaces

NASA Astrophysics Data System (ADS)

Vaidyanathan, Seetharaman; Fletcher, John S.; Henderson, Alex; Lockyer, Nicholas P.; Vickerman, John C.

2008-12-01

The application of multivariate analytical tools enables simplification of TOF-SIMS datasets so that useful information can be extracted from complex spectra and images, especially those that do not give readily interpretable results. There is however a challenge in understanding the outputs from such analyses. The problem is complicated when analysing images, given the additional dimensions in the dataset. Here we demonstrate how the application of simple pre-processing routines can enable the interpretation of TOF-SIMS spectra and images. For the spectral data, TOF-SIMS spectra used to discriminate bacterial isolates associated with urinary tract infection were studied. Using different criteria for picking peaks before carrying out PC-DFA enabled identification of the discriminatory information with greater certainty. For the image data, an air-dried salt stressed bacterial sample, discussed in another paper by us in this issue, was studied. Exploration of the image datasets with and without normalisation prior to multivariate analysis by PCA or MAF resulted in different regions of the image being highlighted by the techniques.

Detection of Glaucoma Using Image Processing Techniques: A Critique.

PubMed

Kumar, B Naveen; Chauhan, R P; Dahiya, Nidhi

2018-01-01

The primary objective of this article is to present a summary of different types of image processing methods employed for the detection of glaucoma, a serious eye disease. Glaucoma affects the optic nerve in which retinal ganglion cells become dead, and this leads to loss of vision. The principal cause is the increase in intraocular pressure, which occurs in open-angle and angle-closure glaucoma, the two major types affecting the optic nerve. In the early stages of glaucoma, no perceptible symptoms appear. As the disease progresses, vision starts to become hazy, leading to blindness. Therefore, early detection of glaucoma is needed for prevention. Manual analysis of ophthalmic images is fairly time-consuming and accuracy depends on the expertise of the professionals. Automatic analysis of retinal images is an important tool. Automation aids in the detection, diagnosis, and prevention of risks associated with the disease. Fundus images obtained from a fundus camera have been used for the analysis. Requisite pre-processing techniques have been applied to the image and, depending upon the technique, various classifiers have been used to detect glaucoma. The techniques mentioned in the present review have certain advantages and disadvantages. Based on this study, one can determine which technique provides an optimum result.

Performance of an image analysis processing system for hen tracking in an environmental preference chamber.

PubMed

Kashiha, Mohammad Amin; Green, Angela R; Sales, Tatiana Glogerley; Bahr, Claudia; Berckmans, Daniel; Gates, Richard S

2014-10-01

Image processing systems have been widely used in monitoring livestock for many applications, including identification, tracking, behavior analysis, occupancy rates, and activity calculations. The primary goal of this work was to quantify image processing performance when monitoring laying hens by comparing length of stay in each compartment as detected by the image processing system with the actual occurrences registered by human observations. In this work, an image processing system was implemented and evaluated for use in an environmental animal preference chamber to detect hen navigation between 4 compartments of the chamber. One camera was installed above each compartment to produce top-view images of the whole compartment. An ellipse-fitting model was applied to captured images to detect whether the hen was present in a compartment. During a choice-test study, mean ± SD success detection rates of 95.9 ± 2.6% were achieved when considering total duration of compartment occupancy. These results suggest that the image processing system is currently suitable for determining the response measures for assessing environmental choices. Moreover, the image processing system offered a comprehensive analysis of occupancy while substantially reducing data processing time compared with the time-intensive alternative of manual video analysis. The above technique was used to monitor ammonia aversion in the chamber. As a preliminary pilot study, different levels of ammonia were applied to different compartments while hens were allowed to navigate between compartments. Using the automated monitor tool to assess occupancy, a negative trend of compartment occupancy with ammonia level was revealed, though further examination is needed. ©2014 Poultry Science Association Inc.

A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

NASA Astrophysics Data System (ADS)

Aiello, Martina; Gianinetto, Marco

2017-10-01

Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

Can Imaging Parameters Provide Information Regarding Histopathology in Head and Neck Squamous Cell Carcinoma? A Meta-Analysis.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2018-04-01

Our purpose was to provide data regarding relationships between different imaging and histopathological parameters in HNSCC. MEDLINE library was screened for associations between different imaging parameters and histopathological features in HNSCC up to December 2017. Only papers containing correlation coefficients between different imaging parameters and histopathological findings were acquired for the analysis. Associations between 18 F-FDG positron emission tomography (PET) and KI 67 were reported in 8 studies (236 patients). The pooled correlation coefficient was 0.20 (95% CI = [-0.04; 0.44]). Furthermore, in 4 studies (64 patients), associations between 18 F-fluorothymidine PET and KI 67 were analyzed. The pooled correlation coefficient between SUV max and KI 67 was 0.28 (95% CI = [-0.06; 0.94]). In 2 studies (23 patients), relationships between KI 67 and dynamic contrast-enhanced magnetic resonance imaging were reported. The pooled correlation coefficient between K trans and KI 67 was -0.68 (95% CI = [-0.91; -0.44]). Two studies (31 patients) investigated correlation between apparent diffusion coefficient (ADC) and KI 67. The pooled correlation coefficient was -0.61 (95% CI = [-0.84; -0.38]). In 2 studies (117 patients), relationships between 18 F-FDG PET and p53 were analyzed. The pooled correlation coefficient was 0.0 (95% CI = [-0.87; 0.88]). There were 3 studies (48 patients) that investigated associations between ADC and tumor cell count in HNSCC. The pooled correlation coefficient was -0.53 (95% CI = [-0.74; -0.32]). Associations between 18 F-FDG PET and HIF-1α were investigated in 3 studies (72 patients). The pooled correlation coefficient was 0.44 (95% CI = [-0.20; 1.08]). ADC may predict cell count and proliferation activity, and SUV max may predict expression of HIF-1α in HNSCC. SUV max cannot be used as surrogate marker for expression of KI 67 and p53. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

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

Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features

PubMed Central

Seo, Mirinae; Jahng, Geon-Ho; Sohn, Yu-Mee; Rhee, Sun Jung; Oh, Jang-Hoon; Won, Kyu-Yeoun

2017-01-01

Objective The purpose of this study was to estimate the T2* relaxation time in breast cancer, and to evaluate the association between the T2* value with clinical-imaging-pathological features of breast cancer. Materials and Methods Between January 2011 and July 2013, 107 consecutive women with 107 breast cancers underwent multi-echo T2*-weighted imaging on a 3T clinical magnetic resonance imaging system. The Student's t test and one-way analysis of variance were used to compare the T2* values of cancer for different groups, based on the clinical-imaging-pathological features. In addition, multiple linear regression analysis was performed to find independent predictive factors associated with the T2* values. Results Of the 107 breast cancers, 92 were invasive and 15 were ductal carcinoma in situ (DCIS). The mean T2* value of invasive cancers was significantly longer than that of DCIS (p = 0.029). Signal intensity on T2-weighted imaging (T2WI) and histologic grade of invasive breast cancers showed significant correlation with T2* relaxation time in univariate and multivariate analysis. Breast cancer groups with higher signal intensity on T2WI showed longer T2* relaxation time (p = 0.005). Cancer groups with higher histologic grade showed longer T2* relaxation time (p = 0.017). Conclusion The T2* value is significantly longer in invasive cancer than in DCIS. In invasive cancers, T2* relaxation time is significantly longer in higher histologic grades and high signal intensity on T2WI. Based on these preliminary data, quantitative T2* mapping has the potential to be useful in the characterization of breast cancer. PMID:28096732

RootGraph: a graphic optimization tool for automated image analysis of plant roots

PubMed Central

Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N.; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J.

2015-01-01

This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. PMID:26224880

DNA origami-based shape IDs for single-molecule nanomechanical genotyping

NASA Astrophysics Data System (ADS)

Zhang, Honglu; Chao, Jie; Pan, Dun; Liu, Huajie; Qiang, Yu; Liu, Ke; Cui, Chengjun; Chen, Jianhua; Huang, Qing; Hu, Jun; Wang, Lianhui; Huang, Wei; Shi, Yongyong; Fan, Chunhai

2017-04-01

Variations on DNA sequences profoundly affect how we develop diseases and respond to pathogens and drugs. Atomic force microscopy (AFM) provides a nanomechanical imaging approach for genetic analysis with nanometre resolution. However, unlike fluorescence imaging that has wavelength-specific fluorophores, the lack of shape-specific labels largely hampers widespread applications of AFM imaging. Here we report the development of a set of differentially shaped, highly hybridizable self-assembled DNA origami nanostructures serving as shape IDs for magnified nanomechanical imaging of single-nucleotide polymorphisms. Using these origami shape IDs, we directly genotype single molecules of human genomic DNA with an ultrahigh resolution of ~10 nm and the multiplexing ability. Further, we determine three types of disease-associated, long-range haplotypes in samples from the Han Chinese population. Single-molecule analysis allows robust haplotyping even for samples with low labelling efficiency. We expect this generic shape ID-based nanomechanical approach to hold great potential in genetic analysis at the single-molecule level.

DNA origami-based shape IDs for single-molecule nanomechanical genotyping

PubMed Central

Zhang, Honglu; Chao, Jie; Pan, Dun; Liu, Huajie; Qiang, Yu; Liu, Ke; Cui, Chengjun; Chen, Jianhua; Huang, Qing; Hu, Jun; Wang, Lianhui; Huang, Wei; Shi, Yongyong; Fan, Chunhai

2017-01-01

Variations on DNA sequences profoundly affect how we develop diseases and respond to pathogens and drugs. Atomic force microscopy (AFM) provides a nanomechanical imaging approach for genetic analysis with nanometre resolution. However, unlike fluorescence imaging that has wavelength-specific fluorophores, the lack of shape-specific labels largely hampers widespread applications of AFM imaging. Here we report the development of a set of differentially shaped, highly hybridizable self-assembled DNA origami nanostructures serving as shape IDs for magnified nanomechanical imaging of single-nucleotide polymorphisms. Using these origami shape IDs, we directly genotype single molecules of human genomic DNA with an ultrahigh resolution of ∼10 nm and the multiplexing ability. Further, we determine three types of disease-associated, long-range haplotypes in samples from the Han Chinese population. Single-molecule analysis allows robust haplotyping even for samples with low labelling efficiency. We expect this generic shape ID-based nanomechanical approach to hold great potential in genetic analysis at the single-molecule level. PMID:28382928

Large-Scale medical image analytics: Recent methodologies, applications and Future directions.

PubMed

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

Despite the ever-increasing amount and complexity of annotated medical image data, the development of large-scale medical image analysis algorithms has not kept pace with the need for methods that bridge the semantic gap between images and diagnoses. The goal of this position paper is to discuss and explore innovative and large-scale data science techniques in medical image analytics, which will benefit clinical decision-making and facilitate efficient medical data management. Particularly, we advocate that the scale of image retrieval systems should be significantly increased at which interactive systems can be effective for knowledge discovery in potentially large databases of medical images. For clinical relevance, such systems should return results in real-time, incorporate expert feedback, and be able to cope with the size, quality, and variety of the medical images and their associated metadata for a particular domain. The design, development, and testing of the such framework can significantly impact interactive mining in medical image databases that are growing rapidly in size and complexity and enable novel methods of analysis at much larger scales in an efficient, integrated fashion. Copyright © 2016. Published by Elsevier B.V.

Human movement analysis with image processing in real time

NASA Astrophysics Data System (ADS)

Fauvet, Eric; Paindavoine, Michel; Cannard, F.

1991-04-01

In the field of the human sciences, a lot of applications needs to know the kinematic characteristics of the human movements Psycology is associating the characteristics with the control mechanism, sport and biomechariics are associating them with the performance of the sportman or of the patient. So the trainers or the doctors can correct the gesture of the subject to obtain a better performance if he knows the motion properties. Roherton's studies show the children motion evolution2 . Several investigations methods are able to measure the human movement But now most of the studies are based on image processing. Often the systems are working at the T.V. standard (50 frame per secund ). they permit only to study very slow gesture. A human operator analyses the digitizing sequence of the film manually giving a very expensive, especially long and unprecise operation. On these different grounds many human movement analysis systems were implemented. They consist of: - markers which are fixed to the anatomical interesting points on the subject in motion, - Image compression which is the art to coding picture data. Generally the compression Is limited to the centroid coordinates calculation tor each marker. These systems differ from one other in image acquisition and markers detection.

Image-guided automatic triggering of a fractional CO2 laser in aesthetic procedures.

PubMed

Wilczyński, Sławomir; Koprowski, Robert; Wiernek, Barbara K; Błońska-Fajfrowska, Barbara

2016-09-01

Laser procedures in dermatology and aesthetic medicine are associated with the need for manual laser triggering. This leads to pulse overlapping and side effects. Automatic laser triggering based on image analysis can provide a secure fit to each successive doses of radiation. A fractional CO2 laser was used in the study. 500 images of the human skin of healthy subjects were acquired. Automatic triggering was initiated by an application together with a camera which tracks and analyses the skin in visible light. The tracking algorithm uses the methods of image analysis to overlap images. After locating the characteristic points in analysed adjacent areas, the correspondence of graphs is found. The point coordinates derived from the images are the vertices of graphs with respect to which isomorphism is sought. When the correspondence of graphs is found, it is possible to overlap the neighbouring parts of the image. The proposed method of laser triggering owing to the automatic image fitting method allows for 100% repeatability. To meet this requirement, there must be at least 13 graph vertices obtained from the image. For this number of vertices, the time of analysis of a single image is less than 0.5s. The proposed method, applied in practice, may help reduce the number of side effects during dermatological laser procedures resulting from laser pulse overlapping. In addition, it reduces treatment time and enables to propose new techniques of treatment through controlled, precise laser pulse overlapping. Copyright © 2016 Elsevier Ltd. All rights reserved.

Advancements in mass spectrometry for biological samples: Protein chemical cross-linking and metabolite analysis of plant tissues

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

Klein, Adam

2015-01-01

This thesis presents work on advancements and applications of methodology for the analysis of biological samples using mass spectrometry. Included in this work are improvements to chemical cross-linking mass spectrometry (CXMS) for the study of protein structures and mass spectrometry imaging and quantitative analysis to study plant metabolites. Applications include using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) to further explore metabolic heterogeneity in plant tissues and chemical interactions at the interface between plants and pests. Additional work was focused on developing liquid chromatography-mass spectrometry (LC-MS) methods to investigate metabolites associated with plant-pest interactions.

Wavelet Analysis for Wind Fields Estimation

PubMed Central

Leite, Gladeston C.; Ushizima, Daniela M.; Medeiros, Fátima N. S.; de Lima, Gilson G.

2010-01-01

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B3 spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms−1. Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms. PMID:22219699

Event time analysis of longitudinal neuroimage data.

PubMed

Sabuncu, Mert R; Bernal-Rusiel, Jorge L; Reuter, Martin; Greve, Douglas N; Fischl, Bruce

2014-08-15

This paper presents a method for the statistical analysis of the associations between longitudinal neuroimaging measurements, e.g., of cortical thickness, and the timing of a clinical event of interest, e.g., disease onset. The proposed approach consists of two steps, the first of which employs a linear mixed effects (LME) model to capture temporal variation in serial imaging data. The second step utilizes the extended Cox regression model to examine the relationship between time-dependent imaging measurements and the timing of the event of interest. We demonstrate the proposed method both for the univariate analysis of image-derived biomarkers, e.g., the volume of a structure of interest, and the exploratory mass-univariate analysis of measurements contained in maps, such as cortical thickness and gray matter density. The mass-univariate method employs a recently developed spatial extension of the LME model. We applied our method to analyze structural measurements computed using FreeSurfer, a widely used brain Magnetic Resonance Image (MRI) analysis software package. We provide a quantitative and objective empirical evaluation of the statistical performance of the proposed method on longitudinal data from subjects suffering from Mild Cognitive Impairment (MCI) at baseline. Copyright © 2014 Elsevier Inc. All rights reserved.

Regret associated with the decision for breast reconstruction: the association of negative body image, distress and surgery characteristics with decision regret.

PubMed

Sheehan, Joanne; Sherman, Kerry A; Lam, Thomas; Boyages, John

2008-01-01

This study investigated the influence of psychosocial and surgical factors on decision regret among 123 women diagnosed with breast cancer who had undergone immediate (58%) or delayed (42%) breast reconstruction following mastectomy. The majority of participants (52.8%, n = 65) experienced no decision regret, 27.6% experienced mild regret and 19.5% moderate to strong regret. Bivariate analyses indicated that decision regret was associated with negative body image and psychological distress - intrusion and avoidance. There were no differences in decision regret either with respect to methods or timing patterns of reconstructive surgery. Multinominal logistic regression analysis showed that, when controlling for mood state and time since last reconstructive procedure, increases in negative body image were associated with increased likelihood of experiencing decision regret. These findings highlight the need for optimal input from surgeons and therapists in order to promote realistic expectations regarding the outcome of breast reconstruction and to reduce the likelihood of women experiencing decision regret.

Association between dynamic features of breast DCE-MR imaging and clinical response of neoadjuvant chemotherapy: a preliminary analysis

NASA Astrophysics Data System (ADS)

Huang, Lijuan; Fan, Ming; Li, Lihua; Zhang, Juan; Shao, Guoliang; Zheng, Bin

2016-03-01

Neoadjuvant chemotherapy (NACT) is being used increasingly in the management of patients with breast cancer for systemically reducing the size of primary tumor before surgery in order to improve survival. The clinical response of patients to NACT is correlated with reduced or abolished of their primary tumor, which is important for treatment in the next stage. Recently, the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used for evaluation of the response of patients to NACT. To measure this correlation, we extracted the dynamic features from the DCE- MRI and performed association analysis between these features and the clinical response to NACT. In this study, 59 patients are screened before NATC, of which 47 are complete or partial response, and 12 are no response. We segmented the breast areas depicted on each MR image by a computer-aided diagnosis (CAD) scheme, registered images acquired from the sequential MR image scan series, and calculated eighteen features extracted from DCE-MRI. We performed SVM with the 18 features for classification between patients of response and no response. Furthermore, 6 of the 18 features are selected to refine the classification by using Genetic Algorithm. The accuracy, sensitivity and specificity are 87%, 95.74% and 50%, respectively. The calculated area under a receiver operating characteristic (ROC) curve is 0.79+/-0.04. This study indicates that the features of DCE-MRI of breast cancer are associated with the response of NACT. Therefore, our method could be helpful for evaluation of NACT in treatment of breast cancer.

[Possibilities of modern imaging technologies in early diagnosis of Alzheimer disease].

PubMed

Unschuld, Paul G

2015-04-01

Recent advances in neuroimaging technology and image analysis algorithms have significantly contributed to a better understanding of spatial and temporal aspects of brain change associated with Alzheimer Disease. The current review will demonstrate how functional (fMRI) and structural magnetic resonance imaging (MRI) techniques may be used to identify distinct patterns of brain change associated with disease progression and also increased risk for Alzheimer Disease. Moreover, Positron Emission Tomography (PET) based measures of glucosemetabolism (Fluorodeoxyglucose, FDG) and Amyloid-beta plaque density (11-C-Pittsburgh Compound B, PiB and 18-F) will be reviewed regarding their diagnostic value for assessing the individual degree of Alzheimer -pathology and thus complement the information provided by MRI and other clinical measures.

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web.

PubMed

Taylor, Stephen; Noble, Roger

2014-09-15

Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. © The Author 2014. Published by Oxford University Press.

Automated image analysis method for detecting and quantifying macrovesicular steatosis in hematoxylin and eosin-stained histology images of human livers.

PubMed

Nativ, Nir I; Chen, Alvin I; Yarmush, Gabriel; Henry, Scot D; Lefkowitch, Jay H; Klein, Kenneth M; Maguire, Timothy J; Schloss, Rene; Guarrera, James V; Berthiaume, Francois; Yarmush, Martin L

2014-02-01

Large-droplet macrovesicular steatosis (ld-MaS) in more than 30% of liver graft hepatocytes is a major risk factor for liver transplantation. An accurate assessment of the ld-MaS percentage is crucial for determining liver graft transplantability, which is currently based on pathologists' evaluations of hematoxylin and eosin (H&E)-stained liver histology specimens, with the predominant criteria being the relative size of the lipid droplets (LDs) and their propensity to displace a hepatocyte's nucleus to the cell periphery. Automated image analysis systems aimed at objectively and reproducibly quantifying ld-MaS do not accurately differentiate large LDs from small-droplet macrovesicular steatosis and do not take into account LD-mediated nuclear displacement; this leads to a poor correlation with pathologists' assessments. Here we present an improved image analysis method that incorporates nuclear displacement as a key image feature for segmenting and classifying ld-MaS from H&E-stained liver histology slides. 52,000 LDs in 54 digital images from 9 patients were analyzed, and the performance of the proposed method was compared against the performance of current image analysis methods and the ld-MaS percentage evaluations of 2 trained pathologists from different centers. We show that combining nuclear displacement and LD size information significantly improves the separation between large and small macrovesicular LDs (specificity = 93.7%, sensitivity = 99.3%) and the correlation with pathologists' ld-MaS percentage assessments (linear regression coefficient of determination = 0.97). This performance vastly exceeds that of other automated image analyzers, which typically underestimate or overestimate pathologists' ld-MaS scores. This work demonstrates the potential of automated ld-MaS analysis in monitoring the steatotic state of livers. The image analysis principles demonstrated here may help to standardize ld-MaS scores among centers and ultimately help in the process of determining liver graft transplantability. © 2013 American Association for the Study of Liver Diseases.

Can we trust the calculation of texture indices of CT images? A phantom study.

PubMed

Caramella, Caroline; Allorant, Adrien; Orlhac, Fanny; Bidault, Francois; Asselain, Bernard; Ammari, Samy; Jaranowski, Patricia; Moussier, Aurelie; Balleyguier, Corinne; Lassau, Nathalie; Pitre-Champagnat, Stephanie

2018-04-01

Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images. © 2018 American Association of Physicists in Medicine.

Radiologic-Pathologic Analysis of Contrast-enhanced and Diffusion-weighted MR Imaging in Patients with HCC after TACE: Diagnostic Accuracy of 3D Quantitative Image Analysis

PubMed Central

Chapiro, Julius; Wood, Laura D.; Lin, MingDe; Duran, Rafael; Cornish, Toby; Lesage, David; Charu, Vivek; Schernthaner, Rüdiger; Wang, Zhijun; Tacher, Vania; Savic, Lynn Jeanette; Kamel, Ihab R.

2014-01-01

Purpose To evaluate the diagnostic performance of three-dimensional (3Dthree-dimensional) quantitative enhancement-based and diffusion-weighted volumetric magnetic resonance (MR) imaging assessment of hepatocellular carcinoma (HCChepatocellular carcinoma) lesions in determining the extent of pathologic tumor necrosis after transarterial chemoembolization (TACEtransarterial chemoembolization). Materials and Methods This institutional review board–approved retrospective study included 17 patients with HCChepatocellular carcinoma who underwent TACEtransarterial chemoembolization before surgery. Semiautomatic 3Dthree-dimensional volumetric segmentation of target lesions was performed at the last MR examination before orthotopic liver transplantation or surgical resection. The amount of necrotic tumor tissue on contrast material–enhanced arterial phase MR images and the amount of diffusion-restricted tumor tissue on apparent diffusion coefficient (ADCapparent diffusion coefficient) maps were expressed as a percentage of the total tumor volume. Visual assessment of the extent of tumor necrosis and tumor response according to European Association for the Study of the Liver (EASLEuropean Association for the Study of the Liver) criteria was performed. Pathologic tumor necrosis was quantified by using slide-by-slide segmentation. Correlation analysis was performed to evaluate the predictive values of the radiologic techniques. Results At histopathologic examination, the mean percentage of tumor necrosis was 70% (range, 10%–100%). Both 3Dthree-dimensional quantitative techniques demonstrated a strong correlation with tumor necrosis at pathologic examination (R2 = 0.9657 and R2 = 0.9662 for quantitative EASLEuropean Association for the Study of the Liver and quantitative ADCapparent diffusion coefficient, respectively) and a strong intermethod agreement (R2 = 0.9585). Both methods showed a significantly lower discrepancy with pathologically measured necrosis (residual standard error [RSEresidual standard error] = 6.38 and 6.33 for quantitative EASLEuropean Association for the Study of the Liver and quantitative ADCapparent diffusion coefficient, respectively), when compared with non-3Dthree-dimensional techniques (RSEresidual standard error = 12.18 for visual assessment). Conclusion This radiologic-pathologic correlation study demonstrates the diagnostic accuracy of 3Dthree-dimensional quantitative MR imaging techniques in identifying pathologically measured tumor necrosis in HCChepatocellular carcinoma lesions treated with TACEtransarterial chemoembolization. © RSNA, 2014 Online supplemental material is available for this article. PMID:25028783

Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

PubMed

Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

2008-12-01

Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.

Radiographic and MRI characteristics of lumbar disseminated idiopathic spinal hyperostosis and spondylosis deformans in dogs.

PubMed

Togni, A; Kranenburg, H J C; Morgan, J P; Steffen, F

2014-07-01

To evaluate clinical signs, describe lesions and differences in the magnetic resonance imaging appearance of spinal new bone formations classified as disseminated idiopathic spinal hyperostosis and/or spondylosis deformans on radiographs and compare degeneration status of the intervertebral discs using the Pfirrmann scale. Retrospective analysis of 18 dogs presented with spinal disorders using information from radiographic and magnetic resonance imaging examinations. All dogs were found to be affected with both disseminated idiopathic spinal hyperostosis and spondylosis deformans. Neurological signs due to foraminal stenosis associated with disseminated idiopathic spinal hyperostosis were found in two dogs. Spondylosis deformans was associated with foraminal stenosis and/or disc protrusion in 15 cases. The Pfirrmann score on magnetic resonance imaging was significantly higher in spondylosis deformans compared with disseminated idiopathic spinal hyperostosis and signal intensity of new bone due to disseminated idiopathic spinal hyperostosis was significantly higher compared to spondylosis deformans. Differences between disseminated idiopathic spinal hyperostosis and spondylosis deformans found on magnetic resonance imaging contribute to an increased differentiation between the two entities. Clinically relevant lesions in association with disseminated idiopathic spinal hyperostosis were rare compared to those seen with spondylosis deformans. © 2014 British Small Animal Veterinary Association.

TU-CD-BRB-07: Identification of Associations Between Radiologist-Annotated Imaging Features and Genomic Alterations in Breast Invasive Carcinoma, a TCGA Phenotype Research Group Study

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

Rao, A; Net, J; Brandt, K

2015-06-15

Purpose: To determine associations between radiologist-annotated MRI features and genomic measurements in breast invasive carcinoma (BRCA) from the Cancer Genome Atlas (TCGA). Methods: 98 TCGA patients with BRCA were assessed by a panel of radiologists (TCGA Breast Phenotype Research Group) based on a variety of mass and non-mass features according to the Breast Imaging Reporting and Data System (BI-RADS). Batch corrected gene expression data was obtained from the TCGA Data Portal. The Kruskal-Wallis test was used to assess correlations between categorical image features and tumor-derived genomic features (such as gene pathway activity, copy number and mutation characteristics). Image-derived features weremore » also correlated with estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2/neu) status. Multiple hypothesis correction was done using Benjamini-Hochberg FDR. Associations at an FDR of 0.1 were selected for interpretation. Results: ER status was associated with rim enhancement and peritumoral edema. PR status was associated with internal enhancement. Several components of the PI3K/Akt pathway were associated with rim enhancement as well as heterogeneity. In addition, several components of cell cycle regulation and cell division were associated with imaging characteristics.TP53 and GATA3 mutations were associated with lesion size. MRI features associated with TP53 mutation status were rim enhancement and peritumoral edema. Rim enhancement was associated with activity of RB1, PIK3R1, MAP3K1, AKT1,PI3K, and PIK3CA. Margin status was associated with HIF1A/ARNT, Ras/ GTP/PI3K, KRAS, and GADD45A. Axillary lymphadenopathy was associated with RB1 and BCL2L1. Peritumoral edema was associated with Aurora A/GADD45A, BCL2L1, CCNE1, and FOXA1. Heterogeneous internal nonmass enhancement was associated with EGFR, PI3K, AKT1, HF/MET, and EGFR/Erbb4/neuregulin 1. Diffuse nonmass enhancement was associated with HGF/MET/MUC20/SHIP, and HGF/MET/RANBP9. Linear nonmass enhancement was associated with PIK3R1 and AKT activity. Conclusion: MRI-genomic association analysis revealed that several BRCA-associated gene features were associated with radiologist-annotated image features.« less

Graphical Representation of University Image: A Correspondence Analysis.

ERIC Educational Resources Information Center

Yavas, Ugar; Shemwell, Donald J.

1996-01-01

Correspondence analysis, an easy-to-interpret interdependence technique, portrays data graphically to show associations of factors more clearly. A study used the technique with 58 students in one university to determine factors in college choice. Results identified the institution's closest competitors and its positioning in terms of college…

Novel methods for parameter-based analysis of myocardial tissue in MR images

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Behrens, S.; Kuehnel, C.; Oeltze, S.; Konrad, O.; Peitgen, H.-O.

2007-03-01

The analysis of myocardial tissue with contrast-enhanced MR yields multiple parameters, which can be used to classify the examined tissue. Perfusion images are often distorted by motion, while late enhancement images are acquired with a different size and resolution. Therefore, it is common to reduce the analysis to a visual inspection, or to the examination of parameters related to the 17-segment-model proposed by the American Heart Association (AHA). As this simplification comes along with a considerable loss of information, our purpose is to provide methods for a more accurate analysis regarding topological and functional tissue features. In order to achieve this, we implemented registration methods for the motion correction of the perfusion sequence and the matching of the late enhancement information onto the perfusion image and vice versa. For the motion corrected perfusion sequence, vector images containing the voxel enhancement curves' semi-quantitative parameters are derived. The resulting vector images are combined with the late enhancement information and form the basis for the tissue examination. For the exploration of data we propose different modes: the inspection of the enhancement curves and parameter distribution in areas automatically segmented using the late enhancement information, the inspection of regions segmented in parameter space by user defined threshold intervals and the topological comparison of regions segmented with different settings. Results showed a more accurate detection of distorted regions in comparison to the AHA-model-based evaluation.

Development of an Automated Imaging Pipeline for the Analysis of the Zebrafish Larval Kidney

PubMed Central

Westhoff, Jens H.; Giselbrecht, Stefan; Schmidts, Miriam; Schindler, Sebastian; Beales, Philip L.; Tönshoff, Burkhard; Liebel, Urban; Gehrig, Jochen

2013-01-01

The analysis of kidney malformation caused by environmental influences during nephrogenesis or by hereditary nephropathies requires animal models allowing the in vivo observation of developmental processes. The zebrafish has emerged as a useful model system for the analysis of vertebrate organ development and function, and it is suitable for the identification of organotoxic or disease-modulating compounds on a larger scale. However, to fully exploit its potential in high content screening applications, dedicated protocols are required allowing the consistent visualization of inner organs such as the embryonic kidney. To this end, we developed a high content screening compatible pipeline for the automated imaging of standardized views of the developing pronephros in zebrafish larvae. Using a custom designed tool, cavities were generated in agarose coated microtiter plates allowing for accurate positioning and orientation of zebrafish larvae. This enabled the subsequent automated acquisition of stable and consistent dorsal views of pronephric kidneys. The established pipeline was applied in a pilot screen for the analysis of the impact of potentially nephrotoxic drugs on zebrafish pronephros development in the Tg(wt1b:EGFP) transgenic line in which the developing pronephros is highlighted by GFP expression. The consistent image data that was acquired allowed for quantification of gross morphological pronephric phenotypes, revealing concentration dependent effects of several compounds on nephrogenesis. In addition, applicability of the imaging pipeline was further confirmed in a morpholino based model for cilia-associated human genetic disorders associated with different intraflagellar transport genes. The developed tools and pipeline can be used to study various aspects in zebrafish kidney research, and can be readily adapted for the analysis of other organ systems. PMID:24324758

Development of an automated imaging pipeline for the analysis of the zebrafish larval kidney.

PubMed

Westhoff, Jens H; Giselbrecht, Stefan; Schmidts, Miriam; Schindler, Sebastian; Beales, Philip L; Tönshoff, Burkhard; Liebel, Urban; Gehrig, Jochen

2013-01-01

The analysis of kidney malformation caused by environmental influences during nephrogenesis or by hereditary nephropathies requires animal models allowing the in vivo observation of developmental processes. The zebrafish has emerged as a useful model system for the analysis of vertebrate organ development and function, and it is suitable for the identification of organotoxic or disease-modulating compounds on a larger scale. However, to fully exploit its potential in high content screening applications, dedicated protocols are required allowing the consistent visualization of inner organs such as the embryonic kidney. To this end, we developed a high content screening compatible pipeline for the automated imaging of standardized views of the developing pronephros in zebrafish larvae. Using a custom designed tool, cavities were generated in agarose coated microtiter plates allowing for accurate positioning and orientation of zebrafish larvae. This enabled the subsequent automated acquisition of stable and consistent dorsal views of pronephric kidneys. The established pipeline was applied in a pilot screen for the analysis of the impact of potentially nephrotoxic drugs on zebrafish pronephros development in the Tg(wt1b:EGFP) transgenic line in which the developing pronephros is highlighted by GFP expression. The consistent image data that was acquired allowed for quantification of gross morphological pronephric phenotypes, revealing concentration dependent effects of several compounds on nephrogenesis. In addition, applicability of the imaging pipeline was further confirmed in a morpholino based model for cilia-associated human genetic disorders associated with different intraflagellar transport genes. The developed tools and pipeline can be used to study various aspects in zebrafish kidney research, and can be readily adapted for the analysis of other organ systems.

White Matter Injury and General Movements in High-Risk Preterm Infants.

PubMed

Peyton, C; Yang, E; Msall, M E; Adde, L; Støen, R; Fjørtoft, T; Bos, A F; Einspieler, C; Zhou, Y; Schreiber, M D; Marks, J D; Drobyshevsky, A

2017-01-01

Very preterm infants (birth weight, <1500 g) are at increased risk of cognitive and motor impairment, including cerebral palsy. These adverse neurodevelopmental outcomes are associated with white matter abnormalities on MR imaging at term-equivalent age. Cerebral palsy has been predicted by analysis of spontaneous movements in the infant termed "General Movement Assessment." The goal of this study was to determine the utility of General Movement Assessment in predicting adverse cognitive, language, and motor outcomes in very preterm infants and to identify brain imaging markers associated with both adverse outcomes and aberrant general movements. In this prospective study of 47 preterm infants of 24-30 weeks' gestation, brain MR imaging was performed at term-equivalent age. Infants underwent T1- and T2-weighted imaging for volumetric analysis and DTI. General movements were assessed at 10-15 weeks' postterm age, and neurodevelopmental outcomes were evaluated at 2 years by using the Bayley Scales of Infant and Toddler Development III. Nine infants had aberrant general movements and were more likely to have adverse neurodevelopmental outcomes, compared with infants with normal movements. In infants with aberrant movements, Tract-Based Spatial Statistics analysis identified significantly lower fractional anisotropy in widespread white matter tracts, including the corpus callosum, inferior longitudinal and fronto-occipital fasciculi, internal capsule, and optic radiation. The subset of infants having both aberrant movements and abnormal neurodevelopmental outcomes in cognitive, language, and motor skills had significantly lower fractional anisotropy in specific brain regions. Aberrant general movements at 10-15 weeks' postterm are associated with adverse neurodevelopmental outcomes and specific white matter microstructure abnormalities for cognitive, language, and motor delays. © 2017 by American Journal of Neuroradiology.

Differentiation of Uterine Leiomyosarcoma from Atypical Leiomyoma: Diagnostic Accuracy of Qualitative MR Imaging Features and Feasibility of Texture Analysis.

PubMed

Lakhman, Yulia; Veeraraghavan, Harini; Chaim, Joshua; Feier, Diana; Goldman, Debra A; Moskowitz, Chaya S; Nougaret, Stephanie; Sosa, Ramon E; Vargas, Hebert Alberto; Soslow, Robert A; Abu-Rustum, Nadeem R; Hricak, Hedvig; Sala, Evis

2017-07-01

To investigate whether qualitative magnetic resonance (MR) features can distinguish leiomyosarcoma (LMS) from atypical leiomyoma (ALM) and assess the feasibility of texture analysis (TA). This retrospective study included 41 women (ALM = 22, LMS = 19) imaged with MRI prior to surgery. Two readers (R1, R2) evaluated each lesion for qualitative MR features. Associations between MR features and LMS were evaluated with Fisher's exact test. Accuracy measures were calculated for the four most significant features. TA was performed for 24 patients (ALM = 14, LMS = 10) with uniform imaging following lesion segmentation on axial T2-weighted images. Texture features were pre-selected using Wilcoxon signed-rank test with Bonferroni correction and analyzed with unsupervised clustering to separate LMS from ALM. Four qualitative MR features most strongly associated with LMS were nodular borders, haemorrhage, "T2 dark" area(s), and central unenhanced area(s) (p ≤ 0.0001 each feature/reader). The highest sensitivity [1.00 (95%CI:0.82-1.00)/0.95 (95%CI: 0.74-1.00)] and specificity [0.95 (95%CI:0.77-1.00)/1.00 (95%CI:0.85-1.00)] were achieved for R1/R2, respectively, when a lesion had ≥3 of these four features. Sixteen texture features differed significantly between LMS and ALM (p-values: <0.001-0.036). Unsupervised clustering achieved accuracy of 0.75 (sensitivity: 0.70; specificity: 0.79). Combination of ≥3 qualitative MR features accurately distinguished LMS from ALM. TA was feasible. • Four qualitative MR features demonstrated the strongest statistical association with LMS. • Combination of ≥3 these features could accurately differentiate LMS from ALM. • Texture analysis was a feasible semi-automated approach for lesion categorization.

Isolating specific cell and tissue compartments from 3D images for quantitative regional distribution analysis using novel computer algorithms.

PubMed

Fenrich, Keith K; Zhao, Ethan Y; Wei, Yuan; Garg, Anirudh; Rose, P Ken

2014-04-15

Isolating specific cellular and tissue compartments from 3D image stacks for quantitative distribution analysis is crucial for understanding cellular and tissue physiology under normal and pathological conditions. Current approaches are limited because they are designed to map the distributions of synapses onto the dendrites of stained neurons and/or require specific proprietary software packages for their implementation. To overcome these obstacles, we developed algorithms to Grow and Shrink Volumes of Interest (GSVI) to isolate specific cellular and tissue compartments from 3D image stacks for quantitative analysis and incorporated these algorithms into a user-friendly computer program that is open source and downloadable at no cost. The GSVI algorithm was used to isolate perivascular regions in the cortex of live animals and cell membrane regions of stained spinal motoneurons in histological sections. We tracked the real-time, intravital biodistribution of injected fluorophores with sub-cellular resolution from the vascular lumen to the perivascular and parenchymal space following a vascular microlesion, and mapped the precise distributions of membrane-associated KCC2 and gephyrin immunolabeling in dendritic and somatic regions of spinal motoneurons. Compared to existing approaches, the GSVI approach is specifically designed for isolating perivascular regions and membrane-associated regions for quantitative analysis, is user-friendly, and free. The GSVI algorithm is useful to quantify regional differences of stained biomarkers (e.g., cell membrane-associated channels) in relation to cell functions, and the effects of therapeutic strategies on the redistributions of biomolecules, drugs, and cells in diseased or injured tissues. Copyright © 2014 Elsevier B.V. All rights reserved.

Shedding Light on the Molecular Pathology of Amyloid Plaques in Transgenic Alzheimer's Disease Mice Using Multimodal MALDI Imaging Mass Spectrometry.

PubMed

Kaya, Ibrahim; Zetterberg, Henrik; Blennow, Kaj; Hanrieder, Jörg

2018-05-04

Senile plaques formed by aggregated amyloid β peptides are one of the major pathological hallmarks of Alzheimer's disease (AD) which have been suggested to be the primary influence triggering the AD pathogenesis and the rest of the disease process. However, neurotoxic Aβ aggregation and progression are associated with a wide range of enigmatic biochemical, biophysical and genetic processes. MALDI imaging mass spectrometry (IMS) is a label-free method to elucidate the spatial distribution patterns of intact molecules in biological tissue sections. In this communication, we utilized multimodal MALDI-IMS analysis on 18 month old transgenic AD mice (tgArcSwe) brain tissue sections to enhance molecular information correlated to individual amyloid aggregates on the very same tissue section. Dual polarity MALDI-IMS analysis of lipids on the same pixel points revealed high throughput lipid molecular information including sphingolipids, phospholipids, and lysophospholipids which can be correlated to the ion images of individual amyloid β peptide isoforms at high spatial resolutions (10 μm). Further, multivariate image analysis was applied in order to probe the multimodal MALDI-IMS data in an unbiased way which verified the correlative accumulations of lipid species with dual polarity and Aβ peptides. This was followed by the lipid fragmentation obtained directly on plaque aggregates at higher laser pulse energies which provided tandem MS information useful for structural elucidation of several lipid species. Majority of the amyloid plaque-associated alterations of lipid species are for the first time reported here. The significance of this technique is that it allows correlating the biological discussion of all detected plaque-associated molecules to the very same individual amyloid plaques which can give novel insights into the molecular pathology of even a single amyloid plaque microenvironment in a specific brain region. Therefore, this allowed us to interpret the possible roles of lipids and amyloid peptides in amyloid plaque-associated pathological events such as focal demyelination, autophagic/lysosomal dysfunction, astrogliosis, inflammation, oxidative stress, and cell death.

Impact of motion-associated noise on intrinsic optical signal imaging in humans with optical coherence tomography

PubMed Central

Teussink, Michel M.; Cense, Barry; van Grinsven, Mark J.J.P.; Klevering, B. Jeroen; Hoyng, Carel B.; Theelen, Thomas

2015-01-01

A growing body of evidence suggests that phototransduction can be studied in the human eye in vivo by imaging of fast intrinsic optical signals (IOS). There is consensus concerning the limiting influence of motion-associated imaging noise on the reproducibility of IOS-measurements, especially in those employing spectral-domain optical coherence tomography (SD-OCT). However, no study to date has conducted a comprehensive analysis of this noise in the context of IOS-imaging. In this study, we discuss biophysical correlates of IOS, and we address motion-associated imaging noise by providing correctional post-processing methods. In order to avoid cross-talk of adjacent IOS of opposite signal polarity, cellular resolution and stability of imaging to the level of individual cones is likely needed. The optical Stiles-Crawford effect can be a source of significant IOS-imaging noise if alignment with the peak of the Stiles-Crawford function cannot be maintained. Therefore, complete head stabilization by implementation of a bite-bar may be critical to maintain a constant pupil entry position of the OCT beam. Due to depth-dependent sensitivity fall-off, heartbeat and breathing associated axial movements can cause tissue reflectivity to vary by 29% over time, although known methods can be implemented to null these effects. Substantial variations in reflectivity can be caused by variable illumination due to changes in the beam pupil entry position and angle, which can be reduced by an adaptive algorithm based on slope-fitting of optical attenuation in the choriocapillary lamina. PMID:26137369

Acoustic Waves in Medical Imaging and Diagnostics

PubMed Central

Sarvazyan, Armen P.; Urban, Matthew W.; Greenleaf, James F.

2013-01-01

Up until about two decades ago acoustic imaging and ultrasound imaging were synonymous. The term “ultrasonography,” or its abbreviated version “sonography” meant an imaging modality based on the use of ultrasonic compressional bulk waves. Since the 1990s numerous acoustic imaging modalities started to emerge based on the use of a different mode of acoustic wave: shear waves. It was demonstrated that imaging with these waves can provide very useful and very different information about the biological tissue being examined. We will discuss physical basis for the differences between these two basic modes of acoustic waves used in medical imaging and analyze the advantages associated with shear acoustic imaging. A comprehensive analysis of the range of acoustic wavelengths, velocities, and frequencies that have been used in different imaging applications will be presented. We will discuss the potential for future shear wave imaging applications. PMID:23643056

Detecting Multi-scale Structures in Chandra Images of Centaurus A

NASA Astrophysics Data System (ADS)

Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

1999-12-01

Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.

Mammographic images segmentation based on chaotic map clustering algorithm

PubMed Central

2014-01-01

Background This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads to its natural partitioning, which corresponds to a particular segmentation scheme of the initial mammographic image. Results The system provides a high recognition rate for small mass lesions (about 94% correctly segmented inside the breast) and the reproduction of the shape of regions with denser micro-calcifications in about 2/3 of the cases, while being less effective on identification of larger mass lesions. Conclusions We can summarize our analysis by asserting that due to the particularities of the mammographic images, the chaotic map clustering algorithm should not be used as the sole method of segmentation. It is rather the joint use of this method along with other segmentation techniques that could be successfully used for increasing the segmentation performance and for providing extra information for the subsequent analysis stages such as the classification of the segmented ROI. PMID:24666766

Magnetic resonance imaging-guided core needle breast biopsies resulting in high-risk histopathologic findings: upstage frequency and lesion characteristics.

PubMed

Weinfurtner, R Jared; Patel, Bhavika; Laronga, Christine; Lee, Marie C; Falcon, Shannon L; Mooney, Blaise P; Yue, Binglin; Drukteinis, Jennifer S

2015-06-01

Analysis of magnetic resonance imaging-guided breast biopsies yielding high-risk histopathologic features at a single institution found an overall upstage rate to malignancy of 14% at surgical excision. All upstaged lesions were associated with atypical ductal hyperplasia. Flat epithelial atypia and atypical lobular hyperplasia alone or with lobular carcinoma in situ were not associated with an upstage to malignancy. The purpose of the present study w as to determine the malignancy upstage rates and imaging features of high-risk histopathologic findings resulting from magnetic resonance imaging (MRI)-guided core needle breast biopsies. These features include atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), flat epithelial atypia (FEA), and lobular carcinoma in situ (LCIS). A retrospective medical record review was performed on all MRI-guided core needle breast biopsies at a single institution from June 1, 2007 to December 1, 2013 to select biopsies yielding high-risk histopathologic findings. The patient demographics, MRI lesion characteristics, and histopathologic features at biopsy and surgical excision were analyzed. A total of 257 MRI-guided biopsies had been performed, and 50 yielded high-risk histopathologic features (19%). Biopsy site and surgical excision site correlation was confirmed in 29 of 50 cases. Four of 29 lesions (14%) were upstaged: 1 case to invasive ductal carcinoma and 3 cases to ductal carcinoma in situ. ADH alone had an overall upstage rate of 7% (1 of 14), mixed ADH/ALH a rate of 75% (3 of 4), ALH alone or with LCIS a rate of 0% (0 of 7), and FEA a rate of 0% (0 of 4). Only mixed ADH/ALH had a statistically significant upstage rate to malignancy compared with the other high-risk histopathologic subtypes combined. No specific imaging characteristics on MRI were associated with an upstage to malignancy on the statistical analysis. MRI-guided breast biopsies yielding high-risk histopathologic features were associated with an overall upstage to malignancy rate of 14% at surgical excision. All upstaged lesions were associated with ADH. FEA and ALH alone or with LCIS were not associated with an upstage to malignancy. Copyright © 2015 Elsevier Inc. All rights reserved.

High Frequency Active Auroral Research Program (HAARP) imager. Final report, 29 August 1991-29 August 1993

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

Lance, C.; Eather, R.

1993-09-30

A low-light-level monochromatic imaging system was designed and fabricated which was optimized to detect and record optical emissions associated with high-power rf heating of the ionosphere. The instrument is capable of detecting very low intensities, of the order of 1 Rayleigh, from typical ionospheric atomic and molecular emissions. This is achieved through co-adding of ON images during heater pulses and subtraction of OFF (background) images between pulses. Images can be displayed and analyzed in real time and stored in optical disc for later analysis. Full image processing software is provided which was customized for this application and uses menu ormore » mouse user interaction.« less

Prospective Evaluation of Multimodal Optical Imaging with Automated Image Analysis to Detect Oral Neoplasia In Vivo.

PubMed

Quang, Timothy; Tran, Emily Q; Schwarz, Richard A; Williams, Michelle D; Vigneswaran, Nadarajah; Gillenwater, Ann M; Richards-Kortum, Rebecca

2017-10-01

The 5-year survival rate for patients with oral cancer remains low, in part because diagnosis often occurs at a late stage. Early and accurate identification of oral high-grade dysplasia and cancer can help improve patient outcomes. Multimodal optical imaging is an adjunctive diagnostic technique in which autofluorescence imaging is used to identify high-risk regions within the oral cavity, followed by high-resolution microendoscopy to confirm or rule out the presence of neoplasia. Multimodal optical images were obtained from 206 sites in 100 patients. Histologic diagnosis, either from a punch biopsy or an excised surgical specimen, was used as the gold standard for all sites. Histopathologic diagnoses of moderate dysplasia or worse were considered neoplastic. Images from 92 sites in the first 30 patients were used as a training set to develop automated image analysis methods for identification of neoplasia. Diagnostic performance was evaluated prospectively using images from 114 sites in the remaining 70 patients as a test set. In the training set, multimodal optical imaging with automated image analysis correctly classified 95% of nonneoplastic sites and 94% of neoplastic sites. Among the 56 sites in the test set that were biopsied, multimodal optical imaging correctly classified 100% of nonneoplastic sites and 85% of neoplastic sites. Among the 58 sites in the test set that corresponded to a surgical specimen, multimodal imaging correctly classified 100% of nonneoplastic sites and 61% of neoplastic sites. These findings support the potential of multimodal optical imaging to aid in the early detection of oral cancer. Cancer Prev Res; 10(10); 563-70. ©2017 AACR . ©2017 American Association for Cancer Research.

Health IT and inappropriate utilization of outpatient imaging: A cross-sectional study of U.S. hospitals.

PubMed

Appari, Ajit; Johnson, M Eric; Anthony, Denise L

2018-01-01

To determine whether the use of information technology (IT), measured by Meaningful Use capability, is associated with lower rates of inappropriate utilization of imaging services in hospital outpatient settings. A retrospective cross-sectional analysis of 3332 nonfederal U.S. hospitals using data from: Hospital Compare (2011 outpatient imaging efficiency measures), HIMSS Analytics (2009 health IT), and Health Indicator Warehouse (market characteristics). Hospitals were categorized for their health IT infrastructure including EHR Stage-1 capability, and three advanced imaging functionalities/systems including integrated picture archiving and communication system, Web-based image distribution, and clinical decision support (CDS) with physician pathways. Three imaging efficiency measures suggesting inappropriate utilization during 2011 included: percentage of "combined" (with and without contrast) computed tomography (CT) studies out of all CT studies for abdomen and chest respectively, and percentage of magnetic resonance imaging (MRI) studies of lumbar spine without antecedent conservative therapy within 60days. For each measure, three separate regression models (GLM with gamma-log link function, and denominator of imaging measure as exposure) were estimated adjusting for hospital characteristics, market characteristics, and state fixed effects. Additionally, Heckman's Inverse Mills Ratio and propensity for Stage-1 EHR capability were used to account for selection bias. We find support for association of each of the four health IT capabilities with inappropriate utilization rates of one or more imaging modality. Stage-1 EHR capability is associated with lower inappropriate utilization rates for chest CT (incidence rate ratio IRR=0.72, p-value <0.01) and lumbar MRI (IRR=0.87, p-value <0.05). Integrated PACS is associated with lower inappropriate utilization rate of abdomen CT (IRR=0.84, p-value <0.05). Imaging distribution over Web capability is associated with lower inappropriate utilization rates for chest CT (IRR=0.66, p-value <0.05) and lumbar MRI (IRR=0.86, p-value <0.05). CDS with physician pathways is associated with lower inappropriate utilization rates for abdomen CT (IRR=0.87, p-value <0.01) and lumbar MRI (IRR=0.90, p-value <0.05). All other cases showed no association. The study offers mixed results. Taken together, the results suggest that the use of Stage-1 Meaningful Use capable EHR systems along with advanced imaging related functionalities could have a beneficial impact on reducing some of the inappropriate utilization of outpatient imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

PDS Archive Release of Apollo 11, Apollo 12, and Apollo 17 Lunar Rock Sample Images

NASA Technical Reports Server (NTRS)

Garcia, P. A.; Stefanov, W. L.; Lofgren, G. E.; Todd, N. S.; Gaddis, L. R.

2013-01-01

Scientists at the Johnson Space Center (JSC) Lunar Sample Laboratory, Information Resources Directorate, and Image Science & Analysis Laboratory have been working to digitize (scan) the original film negatives of Apollo Lunar Rock Sample photographs [1, 2]. The rock samples, and associated regolith and lunar core samples, were obtained during the Apollo 11, 12, 14, 15, 16 and 17 missions. The images allow scientists to view the individual rock samples in their original or subdivided state prior to requesting physical samples for their research. In cases where access to the actual physical samples is not practical, the images provide an alternate mechanism for study of the subject samples. As the negatives are being scanned, they have been formatted and documented for permanent archive in the NASA Planetary Data System (PDS). The Astromaterials Research and Exploration Science Directorate (which includes the Lunar Sample Laboratory and Image Science & Analysis Laboratory) at JSC is working collaboratively with the Imaging Node of the PDS on the archiving of these valuable data. The PDS Imaging Node is now pleased to announce the release of the image archives for Apollo missions 11, 12, and 17.

Optimization of a Biometric System Based on Acoustic Images

PubMed Central

Izquierdo Fuente, Alberto; Del Val Puente, Lara; Villacorta Calvo, Juan J.; Raboso Mateos, Mariano

2014-01-01

On the basis of an acoustic biometric system that captures 16 acoustic images of a person for 4 frequencies and 4 positions, a study was carried out to improve the performance of the system. On a first stage, an analysis to determine which images provide more information to the system was carried out showing that a set of 12 images allows the system to obtain results that are equivalent to using all of the 16 images. Finally, optimization techniques were used to obtain the set of weights associated with each acoustic image that maximizes the performance of the biometric system. These results improve significantly the performance of the preliminary system, while reducing the time of acquisition and computational burden, since the number of acoustic images was reduced. PMID:24616643

A Semi-Automatic Method for Image Analysis of Edge Dynamics in Living Cells

PubMed Central

Huang, Lawrence; Helmke, Brian P.

2011-01-01

Spatial asymmetry of actin edge ruffling contributes to the process of cell polarization and directional migration, but mechanisms by which external cues control actin polymerization near cell edges remain unclear. We designed a quantitative image analysis strategy to measure the spatiotemporal distribution of actin edge ruffling. Time-lapse images of endothelial cells (ECs) expressing mRFP-actin were segmented using an active contour method. In intensity line profiles oriented normal to the cell edge, peak detection identified the angular distribution of polymerized actin within 1 µm of the cell edge, which was localized to lamellipodia and edge ruffles. Edge features associated with filopodia and peripheral stress fibers were removed. Circular statistical analysis enabled detection of cell polarity, indicated by a unimodal distribution of edge ruffles. To demonstrate the approach, we detected a rapid, nondirectional increase in edge ruffling in serum-stimulated ECs and a change in constitutive ruffling orientation in quiescent, nonpolarized ECs. Error analysis using simulated test images demonstrate robustness of the method to variations in image noise levels, edge ruffle arc length, and edge intensity gradient. These quantitative measurements of edge ruffling dynamics enable investigation at the cellular length scale of the underlying molecular mechanisms regulating actin assembly and cell polarization. PMID:21643526

Atlas-guided volumetric diffuse optical tomography enhanced by generalized linear model analysis to image risk decision-making responses in young adults.

PubMed

Lin, Zi-Jing; Li, Lin; Cazzell, Mary; Liu, Hanli

2014-08-01

Diffuse optical tomography (DOT) is a variant of functional near infrared spectroscopy and has the capability of mapping or reconstructing three dimensional (3D) hemodynamic changes due to brain activity. Common methods used in DOT image analysis to define brain activation have limitations because the selection of activation period is relatively subjective. General linear model (GLM)-based analysis can overcome this limitation. In this study, we combine the atlas-guided 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with risk decision-making processes. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The Balloon Analog Risk Task (BART) is a valid experimental model and has been commonly used to assess human risk-taking actions and tendencies while facing risks. We have used the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making from 37 human participants (22 males and 15 females). Voxel-wise GLM analysis was performed after a human brain atlas template and a depth compensation algorithm were combined to form atlas-guided DOT images. In this work, we wish to demonstrate the excellence of using voxel-wise GLM analysis with DOT to image and study cognitive functions in response to risk decision-making. Results have shown significant hemodynamic changes in the dorsal lateral prefrontal cortex (DLPFC) during the active-choice mode and a different activation pattern between genders; these findings correlate well with published literature in functional magnetic resonance imaging (fMRI) and fNIRS studies. Copyright © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Textural analysis of high resolution imagery to quantify bush encroachment in Madikwe Game Reserve, South Africa, 1955-1996

Treesearch

A. T. Hudak; C.A. Wessman

2001-01-01

Fire suppression associated with decades of cattle grazing can result in bush encroachment in savannas. Textural analyses of historical, high resolution images was used to characterize bush densities across a South African study landscape. A control site, where vegetation was assumed to have changed minimally for the duration of the image record (1955-1996), was used...

Signatures of personality on dense 3D facial images.

PubMed

Hu, Sile; Xiong, Jieyi; Fu, Pengcheng; Qiao, Lu; Tan, Jingze; Jin, Li; Tang, Kun

2017-03-06

It has long been speculated that cues on the human face exist that allow observers to make reliable judgments of others' personality traits. However, direct evidence of association between facial shapes and personality is missing from the current literature. This study assessed the personality attributes of 834 Han Chinese volunteers (405 males and 429 females), utilising the five-factor personality model ('Big Five'), and collected their neutral 3D facial images. Dense anatomical correspondence was established across the 3D facial images in order to allow high-dimensional quantitative analyses of the facial phenotypes. In this paper, we developed a Partial Least Squares (PLS) -based method. We used composite partial least squares component (CPSLC) to test association between the self-tested personality scores and the dense 3D facial image data, then used principal component analysis (PCA) for further validation. Among the five personality factors, agreeableness and conscientiousness in males and extraversion in females were significantly associated with specific facial patterns. The personality-related facial patterns were extracted and their effects were extrapolated on simulated 3D facial models.

Evolving Self View and Body Image Concerns in Female Post-Operative Bariatric Surgery Patients.

PubMed

Perdue, Tamara O; Schreier, Ann; Swanson, Melvin; Neil, Janice; Carels, Robert

2018-05-18

This research study explores the experience of post-operative bariatric surgery patients as they adjust to diminished weight and differentiates that adjustment from the more general concept of body image. Bariatric surgery is an effective way to reduce weight and co-morbidities associated with obesity. Complete success requires that patients must adjust psychologically as they lose weight. If this does not occur, bariatric patients may experience a 'mind-body lag' in which the patient's internal body image lags behind the external changes. Hermans' Dialogical Self Theory of 'I-positions' is a foundation with which to understand this problem. Descriptive correlational study of post-operative bariatric patients explored the concept of 'I-obese' and 'I-ex-obese' in an effort to quantify previous qualitative findings and develop a survey questionnaire. Bariatric patients (N=55) between 18-30 month post-operative completed one hour interviews. Cluster analysis and Chi-square analysis compared mean scores and explored the prevalence of 'I-positions' and body image concerns in the participants. Cluster analysis of the survey data identified participants as falling into either 'I-obese', 'I-ex-obese' or 'mixed I-obese' categories. There were significantly higher body image concerns in the 'I-obese' participants than those identified as 'I-ex-obese'. The majority of female participants reported high body image concerns. There was no significant association with weight loss percentage. This research establishes a connection in this study sample of women who experience body image concerns and prolonged 'I-obese' identification 18 to 30 months after their bariatric surgery. To date, the primary measure of bariatric surgery success has focused almost exclusively on the amount of weight lost. Implementing psychological as well as physiological care however, may be the key to full recovery and long-term success. Practitioners can use this new information to plan effective pre- and post-operative psychological preparation and support. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Localized sinonasal mucosal melanoma: Outcomes and associations with stage, radiotherapy, and positron emission tomography response.

PubMed

Samstein, Robert M; Carvajal, Richard D; Postow, Michael A; Callahan, Margaret K; Shoushtari, Alexander N; Patel, Snehal G; Lee, Nancy Y; Barker, Christopher A

2016-09-01

Sinonasal mucosal melanoma is a rare neoplasm with a poor prognosis. Retrospective analysis was conducted on 78 patients with localized sinonasal mucosal melanoma treated at Memorial Sloan Kettering Cancer Center (MSKCC from 1998-2013). Demographic, tumor, imaging, and treatment factors were recorded and survival and disease-control outcomes were analyzed. Median overall survival (OS) and disease-specific survival (DSS) were 32 and 50 months, respectively. Median locoregional recurrence-free survival (LRFS) and distant recurrence-free survival (DRFS) were 43 and 12 months, respectively. Multivariate analysis demonstrated greater OS in nasal cavity tumors and earlier T classification. Radiotherapy (RT) was associated with significantly greater LRFS (5-years; 35% vs 59%; p = .01), but no difference in OS. Post-RT positron emission tomography (PET) response was associated with greater OS. Distant metastasis is the predominant mode of recurrence in sinonasal mucosal melanoma, but local recurrence remains common. RT is associated with improved local control, but no survival benefit. The prognostic value of post-RT PET imaging warrants further investigation. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1310-1317, 2016. © 2016 Wiley Periodicals, Inc.

High-resolution measurements of the multilayer ultra-structure of articular cartilage and their translational potential

PubMed Central

2014-01-01

Current musculoskeletal imaging techniques usually target the macro-morphology of articular cartilage or use histological analysis. These techniques are able to reveal advanced osteoarthritic changes in articular cartilage but fail to give detailed information to distinguish early osteoarthritis from healthy cartilage, and this necessitates high-resolution imaging techniques measuring cells and the extracellular matrix within the multilayer structure of articular cartilage. This review provides a comprehensive exploration of the cellular components and extracellular matrix of articular cartilage as well as high-resolution imaging techniques, including magnetic resonance image, electron microscopy, confocal laser scanning microscopy, second harmonic generation microscopy, and laser scanning confocal arthroscopy, in the measurement of multilayer ultra-structures of articular cartilage. This review also provides an overview for micro-structural analysis of the main components of normal or osteoarthritic cartilage and discusses the potential and challenges associated with developing non-invasive high-resolution imaging techniques for both research and clinical diagnosis of early to late osteoarthritis. PMID:24946278

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

PubMed Central

Aerts, Hugo J. W. L.; Velazquez, Emmanuel Rios; Leijenaar, Ralph T. H.; Parmar, Chintan; Grossmann, Patrick; Cavalho, Sara; Bussink, Johan; Monshouwer, René; Haibe-Kains, Benjamin; Rietveld, Derek; Hoebers, Frank; Rietbergen, Michelle M.; Leemans, C. René; Dekker, Andre; Quackenbush, John; Gillies, Robert J.; Lambin, Philippe

2014-01-01

Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical imaging. Radiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features. Here we present a radiomic analysis of 440 features quantifying tumour image intensity, shape and texture, which are extracted from computed tomography data of 1,019 patients with lung or head-and-neck cancer. We find that a large number of radiomic features have prognostic power in independent data sets of lung and head-and-neck cancer patients, many of which were not identified as significant before. Radiogenomics analysis reveals that a prognostic radiomic signature, capturing intratumour heterogeneity, is associated with underlying gene-expression patterns. These data suggest that radiomics identifies a general prognostic phenotype existing in both lung and head-and-neck cancer. This may have a clinical impact as imaging is routinely used in clinical practice, providing an unprecedented opportunity to improve decision-support in cancer treatment at low cost. PMID:24892406

Breast MRI radiogenomics: Current status and research implications.

PubMed

Grimm, Lars J

2016-06-01

Breast magnetic resonance imaging (MRI) radiogenomics is an emerging area of research that has the potential to directly influence clinical practice. Clinical MRI scanners today are capable of providing excellent temporal and spatial resolution, which allows extraction of numerous imaging features via human extraction approaches or complex computer vision algorithms. Meanwhile, advances in breast cancer genetics research has resulted in the identification of promising genes associated with cancer outcomes. In addition, validated genomic signatures have been developed that allow categorization of breast cancers into distinct molecular subtypes as well as predict the risk of cancer recurrence and response to therapy. Current radiogenomics research has been directed towards exploratory analysis of individual genes, understanding tumor biology, and developing imaging surrogates to genetic analysis with the long-term goal of developing a meaningful tool for clinical care. The background of breast MRI radiogenomics research, image feature extraction techniques, approaches to radiogenomics research, and promising areas of investigation are reviewed. J. Magn. Reson. Imaging 2016;43:1269-1278. © 2015 Wiley Periodicals, Inc.

Computational pathology of pre-treatment biopsies identifies lymphocyte density as a predictor of response to neoadjuvant chemotherapy in breast cancer.

PubMed

Ali, H Raza; Dariush, Aliakbar; Provenzano, Elena; Bardwell, Helen; Abraham, Jean E; Iddawela, Mahesh; Vallier, Anne-Laure; Hiller, Louise; Dunn, Janet A; Bowden, Sarah J; Hickish, Tamas; McAdam, Karen; Houston, Stephen; Irwin, Mike J; Pharoah, Paul D P; Brenton, James D; Walton, Nicholas A; Earl, Helena M; Caldas, Carlos

2016-02-16

There is a need to improve prediction of response to chemotherapy in breast cancer in order to improve clinical management and this may be achieved by harnessing computational metrics of tissue pathology. We investigated the association between quantitative image metrics derived from computational analysis of digital pathology slides and response to chemotherapy in women with breast cancer who received neoadjuvant chemotherapy. We digitised tissue sections of both diagnostic and surgical samples of breast tumours from 768 patients enrolled in the Neo-tAnGo randomized controlled trial. We subjected digital images to systematic analysis optimised for detection of single cells. Machine-learning methods were used to classify cells as cancer, stromal or lymphocyte and we computed estimates of absolute numbers, relative fractions and cell densities using these data. Pathological complete response (pCR), a histological indicator of chemotherapy response, was the primary endpoint. Fifteen image metrics were tested for their association with pCR using univariate and multivariate logistic regression. Median lymphocyte density proved most strongly associated with pCR on univariate analysis (OR 4.46, 95 % CI 2.34-8.50, p < 0.0001; observations = 614) and on multivariate analysis (OR 2.42, 95 % CI 1.08-5.40, p = 0.03; observations = 406) after adjustment for clinical factors. Further exploratory analyses revealed that in approximately one quarter of cases there was an increase in lymphocyte density in the tumour removed at surgery compared to diagnostic biopsies. A reduction in lymphocyte density at surgery was strongly associated with pCR (OR 0.28, 95 % CI 0.17-0.47, p < 0.0001; observations = 553). A data-driven analysis of computational pathology reveals lymphocyte density as an independent predictor of pCR. Paradoxically an increase in lymphocyte density, following exposure to chemotherapy, is associated with a lack of pCR. Computational pathology can provide objective, quantitative and reproducible tissue metrics and represents a viable means of outcome prediction in breast cancer. ClinicalTrials.gov NCT00070278 ; 03/10/2003.

A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line.

PubMed

Collins, Adam; Huett, Alan

2018-05-15

We present a high-content screen (HCS) for the simultaneous analysis of multiple phenotypes in HeLa cells expressing an autophagy reporter (mcherry-LC3) and one of 224 GFP-fused proteins from the Crohn's Disease (CD)-associated bacterium, Adherent Invasive E. coli (AIEC) strain LF82. Using automated confocal microscopy and image analysis (CellProfiler), we localised GFP fusions within cells, and monitored their effects upon autophagy (an important innate cellular defence mechanism), cellular and nuclear morphology, and the actin cytoskeleton. This data will provide an atlas for the localisation of 224 AIEC proteins within human cells, as well as a dataset to analyse their effects upon many aspects of host cell morphology. We also describe an open-source, automated, image-analysis workflow to identify bacterial effectors and their roles via the perturbations induced in reporter cell lines when candidate effectors are exogenously expressed.

Large Deformation Diffeomorphism and Momentum Based Hippocampal Shape Discrimination in Dementia of the Alzheimer type

PubMed Central

Wang, Lei; Beg, Faisal; Ratnanather, Tilak; Ceritoglu, Can; Younes, Laurent; Morris, John C.; Csernansky, John G.; Miller, Michael I.

2010-01-01

In large-deformation diffeomorphic metric mapping (LDDMM), the diffeomorphic matching of images are modeled as evolution in time, or a flow, of an associated smooth velocity vector field v controlling the evolution. The initial momentum parameterizes the whole geodesic and encodes the shape and form of the target image. Thus, methods such as principal component analysis (PCA) of the initial momentum leads to analysis of anatomical shape and form in target images without being restricted to small-deformation assumption in the analysis of linear displacements. We apply this approach to a study of dementia of the Alzheimer type (DAT). The left hippocampus in the DAT group shows significant shape abnormality while the right hippocampus shows similar pattern of abnormality. Further, PCA of the initial momentum leads to correct classification of 12 out of 18 DAT subjects and 22 out of 26 control subjects. PMID:17427733

Body image predicts quality of life in men with prostate cancer.

PubMed

Taylor-Ford, Megan; Meyerowitz, Beth E; D'Orazio, Lina M; Christie, Kysa M; Gross, Mitchell E; Agus, David B

2013-04-01

Most men diagnosed with prostate cancer in the USA will survive. Of the many aspects of survivorship affected by prostate cancer, body image receives limited attention despite some indication that it may be important to men with the disease. The present study investigated how body image changes over time and the relations between changes in body image and quality of life (QOL) in men with prostate cancer. In a longitudinal design, patients (N = 74) completed questionnaires before treatment (T1) and at 1 month (T2) and 2 years (T3) following treatment completion. Growth curve modeling indicated that there was no significant change over time in group-level body image scores. However, hormone treatment was associated with a negative trajectory of change over 2 years. Also, analysis of individual difference scores indicated that ≥50% of patients demonstrated change of at least 0.5 standard deviation between time points. Hierarchical regression indicated that change in body image between T1 and T2 was significantly associated with change in QOL between T1 and T3, while controlling for demographic variables, treatment, treatment-related functioning, and general and treatment-specific positive expectations. In predicting change in body image between T1 and T2, treatment-specific positive expectation was the only significant predictor. The present study demonstrates that body image is an important component of the prostate cancer experience. Findings suggest that body image has a meaningful association with QOL among prostate cancer survivors. Copyright © 2012 John Wiley & Sons, Ltd.

Epstein-Barr DNA serology and positron-emission tomography imaging of the head and neck in pediatric transplant recipients.

PubMed

Sidell, Douglas; Venick, Robert S; Shapiro, Nina L

2014-05-01

Epstein-Barr virus (EBV) infection is a potential precursor of post-transplantation lymphoproliferative disorder (PTLD) in the pediatric transplant patient. Positron-emission tomography (PET) imaging is increasingly utilized in this population to monitor for neoplasia and PTLD. We assess the association between EBV serum titers and Waldeyer's ring and cervical lymph node PET positivity in the pediatric transplant recipient. Retrospective analysis of EBV serology and PET imaging results in pediatric orthotopic liver transplantation (OLT) recipients. Imaging results and laboratory data were reviewed for all pediatric OLT recipients from January 2005 to July 2011 at a single institution. Charts were evaluated for PET positivity at Waldeyer's ring or cervical lymphatics, and for EBV serology results. Demographic data extracted include patient sex and age at transplantation. A total of 122 pediatric OLT recipients were reviewed. Twelve patients (10%) underwent PET imaging. Overall, four patients (33%) had evidence of PET positivity at Waldeyer's ring or cervical lymphatics. Five patients (42%) had positive EBV serology. There was a significant association between PET imaging results and EBV DNA serology results (P = .01). PTLD surveillance in the pediatric transplant recipient is an important component of long-term care in this population. Although PET imaging is a new modality in monitoring pediatric transplant recipients for early signs of PTLD, an association between EBV serology and PET imaging results appears to exist. With increased implementation, PET imaging will likely prove valuable in its ability to monitor the transplant recipient at risk for PTLD. © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

Motivations for healthful dietary change.

PubMed

Satia, J A; Kristal, A R; Curry, S; Trudeau, E

2001-10-01

To describe scales that measure motivations for changing dietary behaviour, and to examine associations of these scales with current diet and dietary change. A secondary analysis of a randomised trial of a self-help intervention to promote lower fat and higher fruit and vegetable consumption. Participants were 1205 adults selected at random from enrolees of a large Health Maintenance Organization. At baseline, data were collected on motives for changing diet, fruit and vegetable intake, fat-related dietary habits, and demographic characteristics. Participants were then randomised to receive the intervention or to receive no materials. A follow-up survey was administered at 12 months. A majority of participants reported that it was very important to make dietary changes to feel better (72%) and to control an existing medical problem (57%), but very few (4%) were motivated by pressure from others. Factor analysis of the diet motivation items yielded two intrinsic ('self-image' and 'personal health') and one extrinsic ('social pressure') scales with fair internal consistency reliabilities (Cronbach's alpha = 0.59 to 0.68). Motivation scales were statistically significantly associated with demographic characteristics and baseline diet. For example, desire for a better self-image was a stronger motivator for changing diet among females, while personal health was more important to older persons and men (P < 0.001). Social pressure to change diet was statistically significantly associated with higher fat intake (r = 0.11) and self-image was associated with lower fat intake (r = -0.14, both P < 0.001). Motivation by social pressure and self-image were both significantly associated with greater fat reduction at 12 months post-intervention (P < 0.05). The intrinsic and extrinsic motivation scales were weakly associated with current diet and predicted response to dietary intervention. More research is needed to better characterise and measure motives for dietary change, and to test whether tailoring interventions based on individuals' motives for dietary change would improve intervention effectiveness.

Crowdsourcing and Automated Retinal Image Analysis for Diabetic Retinopathy.

PubMed

Mudie, Lucy I; Wang, Xueyang; Friedman, David S; Brady, Christopher J

2017-09-23

As the number of people with diabetic retinopathy (DR) in the USA is expected to increase threefold by 2050, the need to reduce health care costs associated with screening for this treatable disease is ever present. Crowdsourcing and automated retinal image analysis (ARIA) are two areas where new technology has been applied to reduce costs in screening for DR. This paper reviews the current literature surrounding these new technologies. Crowdsourcing has high sensitivity for normal vs abnormal images; however, when multiple categories for severity of DR are added, specificity is reduced. ARIAs have higher sensitivity and specificity, and some commercial ARIA programs are already in use. Deep learning enhanced ARIAs appear to offer even more improvement in ARIA grading accuracy. The utilization of crowdsourcing and ARIAs may be a key to reducing the time and cost burden of processing images from DR screening.

The New Possibilities from "Big Data" to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis.

PubMed

Kruse, Christian

2018-06-01

To review current practices and technologies within the scope of "Big Data" that can further our understanding of diabetes mellitus and osteoporosis from large volumes of data. "Big Data" techniques involving supervised machine learning, unsupervised machine learning, and deep learning image analysis are presented with examples of current literature. Supervised machine learning can allow us to better predict diabetes-induced osteoporosis and understand relative predictor importance of diabetes-affected bone tissue. Unsupervised machine learning can allow us to understand patterns in data between diabetic pathophysiology and altered bone metabolism. Image analysis using deep learning can allow us to be less dependent on surrogate predictors and use large volumes of images to classify diabetes-induced osteoporosis and predict future outcomes directly from images. "Big Data" techniques herald new possibilities to understand diabetes-induced osteoporosis and ascertain our current ability to classify, understand, and predict this condition.

MR imaging of patients with lateral epicondylitis of the elbow: is the common extensor tendon an isolated lesion?

PubMed

Qi, Liang; Zhu, Zheng-Feng; Li, Feng; Wang, Ren-Fa

2013-01-01

To investigate whether an injury of the common extensor tendon (CET) is associated with other abnormalities in the elbow joint and find the potential relationships between these imaging features by using a high-resolution magnetic resonance imaging (MRI). Twenty-three patients were examined with 3.0 T MR. Two reviewers were recruited for MR images evaluation. Image features were recorded in terms of (1) the injury degree of CET; (2) associated injuries in the elbow joint. Spearman's rank correlation analysis was performed to analyze the relationships between the injury degree of CET and associated abnormalities of the elbow joint, correlations were considered significant at p<0.05. Total 24 elbows in 23 patients were included. Various degrees of injuries were found in total 24 CETs (10 mild, 7 moderate and 7 severe). Associated abnormalities were detected in accompaniments of the elbow joints including ligaments, tendons, saccussynovialis and muscles. A significantly positive correlation (r = 0.877,p<0.01) was found in injuries of CET and lateral ulnar collateral ligament (LUCL). Injury of the CET is not an isolated lesion for lateral picondylitis, which is mostly accompanied with other abnormalities, of which the LUCL injury is the most commonly seen in lateral epicondylitis, and there is a positive correlation between the injury degree in CET and LUCL.

Neuroanatomical correlates of negative emotionality-related traits: A systematic review and meta-analysis.

PubMed

Mincic, Adina M

2015-10-01

Two central traits present in the most influential models of personality characterize the response to positive and, respectively, negative emotional events. Negative emotionality (NE)-related traits are linked to vulnerability to mood and anxiety disorders; this has fuelled a special interest in examining stable differences in brain morphology associated to these traits. Structural imaging methods including voxel-based morphometry, cortical thickness analysis and diffusion tensor imaging (DTI) have yielded inconclusive and sometimes contradictory results. This review summarizes the findings reported to date through these methods and discusses them in relation to the functional imaging results. To detect topographic convergence between studies showing positive and, respectively, negative grey matter associations with NE-traits, activation likelihood estimation (ALE) meta-analyses of VBM studies were performed. Individuals scoring high on NE-related traits show consistent morphological differences in a left-lateralized circuit: higher grey matter volume (GMV) in amygdala and anterior parahippocampal gyrus and lower GMV in the orbitofrontal cortex extending into perigenual anterior cingulate cortex. Most DTI studies indicate reduced white matter integrity in various brain regions and tracts, particularly in the uncinate fasciculus and in cingulum bundle. These results show that the behavioural phenotype associated to NE traits is reflected in structural differences within the cortico-limbic system, suggesting alterations in information processing and transmission. The results are discussed from the perspective of neuron-glia interactions. Future directions are outlined based on recent developments in structural imaging techniques. Copyright © 2015 Elsevier Ltd. All rights reserved.

Health information exchange reduces repeated diagnostic imaging for back pain.

PubMed

Bailey, James E; Pope, Rebecca A; Elliott, Elizabeth C; Wan, Jim Y; Waters, Teresa M; Frisse, Mark E

2013-07-01

This study seeks to determine whether health information exchange reduces repeated diagnostic imaging and related costs in emergency back pain evaluation. This was a longitudinal data analysis of health information exchange patient-visit data. All repeated emergency department (ED) patient visits for back pain with previous ED diagnostic imaging to a Memphis metropolitan area ED between August 1, 2007, and July 31, 2009, were included. Use of a regional health information exchange by ED personnel to access the patient's record during the emergency visit was the primary independent variable. Main outcomes included repeated lumbar or thoracic diagnostic imaging (radiograph, computed tomography [CT], or magnetic resonance imaging [MRI]) and total patient-visit estimated cost. One hundred seventy-nine (22.4%) of the 800 qualifying repeated back pain visits resulted in repeated diagnostic imaging (radiograph 84.9%, CT 6.1%, and MRI 9.5%). Health information exchange use in the study population was low, at 12.5%, and health care providers as opposed to administrative/nursing staff accounted for 80% of the total health information exchange use. Health information exchange use by any ED personnel was associated with reduced repeated diagnostic imaging (odds ratio 0.36; 95% confidence interval 0.18 to 0.71), as was physician or nurse practitioner health information exchange use (odds ratio 0.47; 95% confidence interval 0.23 to 0.96). No cost savings were associated with health information exchange use because of increased CT imaging when health care providers used health information exchange. Health information exchange use is associated with 64% lower odds of repeated diagnostic imaging in the emergency evaluation of back pain. Health information exchange effect on estimated costs was negligible. More studies are needed to evaluate specific strategies to increase health information exchange use and further decrease potentially unnecessary diagnostic imaging and associated costs of care. Copyright © 2013 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.

Merging Dietary Assessment with the Adolescent Lifestyle

PubMed Central

Schap, TusaRebecca E; Zhu, Fengqing M; Delp, Edward J; Boushey, Carol J

2013-01-01

The use of image-based dietary assessment methods shows promise for improving dietary self-report among children. The Technology Assisted Dietary Assessment (TADA) food record application is a self-administered food record specifically designed to address the burden and human error associated with conventional methods of dietary assessment. Users would take images of foods and beverages at all eating occasions using a mobile telephone or mobile device with an integrated camera, (e.g., Apple iPhone, Google Nexus One, Apple iPod Touch). Once the images are taken, the images are transferred to a back-end server for automated analysis. The first step in this process is image analysis, i.e., segmentation, feature extraction, and classification, allows for automated food identification. Portion size estimation is also automated via segmentation and geometric shape template modeling. The results of the automated food identification and volume estimation can be indexed with the Food and Nutrient Database for Dietary Studies (FNDDS) to provide a detailed diet analysis for use in epidemiologic or intervention studies. Data collected during controlled feeding studies in a camp-like setting have allowed for formative evaluation and validation of the TADA food record application. This review summarizes the system design and the evidence-based development of image-based methods for dietary assessment among children. PMID:23489518

Schooling mediates brain reserve in Alzheimer's disease: findings of fluoro-deoxy-glucose-positron emission tomography.

PubMed

Perneczky, R; Drzezga, A; Diehl-Schmid, J; Schmid, G; Wohlschläger, A; Kars, S; Grimmer, T; Wagenpfeil, S; Monsch, A; Kurz, A

2006-09-01

Functional imaging studies report that higher education is associated with more severe pathology in patients with Alzheimer's disease, controlling for disease severity. Therefore, schooling seems to provide brain reserve against neurodegeneration. To provide further evidence for brain reserve in a large sample, using a sensitive technique for the indirect assessment of brain abnormality (18F-fluoro-deoxy-glucose-positron emission tomography (FDG-PET)), a comprehensive measure of global cognitive impairment to control for disease severity (total score of the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Battery) and an approach unbiased by predefined regions of interest for the statistical analysis (statistical parametric mapping (SPM)). 93 patients with mild Alzheimer's disease and 16 healthy controls underwent 18F-FDG-PET imaging of the brain. A linear regression analysis with education as independent and glucose utilisation as dependent variables, adjusted for global cognitive status and demographic variables, was conducted in SPM2. The regression analysis showed a marked inverse association between years of schooling and glucose metabolism in the posterior temporo-occipital association cortex and the precuneus in the left hemisphere. In line with previous reports, the findings suggest that education is associated with brain reserve and that people with higher education can cope with brain damage for a longer time.

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis.

PubMed

Mayer, Christine; Windhager, Sonja; Schaefer, Katrin; Mitteroecker, Philipp

2017-01-01

Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI) and waist-to-hip ratio (WHR) with facial shape and texture (color pattern) in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3-10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception.

Beauty and thinness messages in children's media: a content analysis.

PubMed

Herbozo, Sylvia; Tantleff-Dunn, Stacey; Gokee-Larose, Jessica; Thompson, J Kevin

2004-01-01

Research suggests that young children have body image concerns, such as a desire for thinness and an avoidance of obesity. Surprisingly, few studies have investigated how children's body preferences and stereotypes are influenced by media aimed at children. In order to gain a better understanding of the content of such media, a content analysis was used to examine body image-related messages in popular children's videos and books. Results indicated that messages emphasizing the importance of physical appearance and portraying body stereotypes are present in many children's videos but relatively few books. Of the videos examined, the ones that exhibited the most body image-related messages were Cinderella and The Little Mermaid. Indian in the Cupboard and ET were the videos with the least number of body image-related messages. Of the books studied, the one with the highest number of body image-related messages was Rapunzel. Ginger and The Stinky Cheese Man were the only books studied that did not exhibit body image-related messages. Implications of an association of beauty and thinness in children's media are explored.

Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts.

PubMed

Shi, Peng; Zhong, Jing; Hong, Jinsheng; Huang, Rongfang; Wang, Kaijun; Chen, Yunbin

2016-08-26

Nasopharyngeal carcinoma is one of the malignant neoplasm with high incidence in China and south-east Asia. Ki-67 protein is strictly associated with cell proliferation and malignant degree. Cells with higher Ki-67 expression are always sensitive to chemotherapy and radiotherapy, the assessment of which is beneficial to NPC treatment. It is still challenging to automatically analyze immunohistochemical Ki-67 staining nasopharyngeal carcinoma images due to the uneven color distributions in different cell types. In order to solve the problem, an automated image processing pipeline based on clustering of local correlation features is proposed in this paper. Unlike traditional morphology-based methods, our algorithm segments cells by classifying image pixels on the basis of local pixel correlations from particularly selected color spaces, then characterizes cells with a set of grading criteria for the reference of pathological analysis. Experimental results showed high accuracy and robustness in nucleus segmentation despite image data variance. Quantitative indicators obtained in this essay provide a reliable evidence for the analysis of Ki-67 staining nasopharyngeal carcinoma microscopic images, which would be helpful in relevant histopathological researches.

Binary partition tree analysis based on region evolution and its application to tree simplification.

PubMed

Lu, Huihai; Woods, John C; Ghanbari, Mohammed

2007-04-01

Pyramid image representations via tree structures are recognized methods for region-based image analysis. Binary partition trees can be applied which document the merging process with small details found at the bottom levels and larger ones close to the root. Hindsight of the merging process is stored within the tree structure and provides the change histories of an image property from the leaf to the root node. In this work, the change histories are modelled by evolvement functions and their second order statistics are analyzed by using a knee function. Knee values show the reluctancy of each merge. We have systematically formulated these findings to provide a novel framework for binary partition tree analysis, where tree simplification is demonstrated. Based on an evolvement function, for each upward path in a tree, the tree node associated with the first reluctant merge is considered as a pruning candidate. The result is a simplified version providing a reduced solution space and still complying with the definition of a binary tree. The experiments show that image details are preserved whilst the number of nodes is dramatically reduced. An image filtering tool also results which preserves object boundaries and has applications for segmentation.

User Oriented Platform for Data Analytics in Medical Imaging Repositories.

PubMed

Valerio, Miguel; Godinho, Tiago Marques; Costa, Carlos

2016-01-01

The production of medical imaging studies and associated data has been growing in the last decades. Their primary use is to support medical diagnosis and treatment processes. However, the secondary use of the tremendous amount of stored data is generally more limited. Nowadays, medical imaging repositories have turned into rich databanks holding not only the images themselves, but also a wide range of metadata related to the medical practice. Exploring these repositories through data analysis and business intelligence techniques has the potential of increasing the efficiency and quality of the medical practice. Nevertheless, the continuous production of tremendous amounts of data makes their analysis difficult by conventional approaches. This article proposes a novel automated methodology to derive knowledge from medical imaging repositories that does not disrupt the regular medical practice. Our method is able to apply statistical analysis and business intelligence techniques directly on top of live institutional repositories. It is a Web-based solution that provides extensive dashboard capabilities, including complete charting and reporting options, combined with data mining components. Moreover, it enables the operator to set a wide multitude of query parameters and operators through the use of an intuitive graphical interface.

High-speed digital phonoscopy images analyzed by Nyquist plots

NASA Astrophysics Data System (ADS)

Yan, Yuling

2012-02-01

Vocal-fold vibration is a key dynamic event in voice production, and the vibratory characteristics of the vocal fold correlate closely with voice quality and health condition. Laryngeal imaging provides direct means to observe the vocal fold vibration; in the past, however, available modalities were either too slow or impractical to resolve the actual vocal fold vibrations. This limitation has now been overcome by high-speed digital imaging (HSDI) (or high-speed digital phonoscopy), which records images of the vibrating vocal folds at a rate of 2000 frames per second or higher- fast enough to resolve a specific, sustained phonatory vocal fold vibration. The subsequent image-based functional analysis of voice is essential to better understanding the mechanism underlying voice production, as well as assisting the clinical diagnosis of voice disorders. Our primary objective is to develop a comprehensive analytical platform for voice analysis using the HSDI recordings. So far, we have developed various analytical approaches for the HSDI-based voice analyses. These include Nyquist plots and associated analysese that are used along with FFT and Spectrogram in the analysis of the HSDI data representing normal voice and specific voice pathologies.

A comparison of autonomous techniques for multispectral image analysis and classification

NASA Astrophysics Data System (ADS)

Valdiviezo-N., Juan C.; Urcid, Gonzalo; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso

2012-10-01

Multispectral imaging has given place to important applications related to classification and identification of objects from a scene. Because of multispectral instruments can be used to estimate the reflectance of materials in the scene, these techniques constitute fundamental tools for materials analysis and quality control. During the last years, a variety of algorithms has been developed to work with multispectral data, whose main purpose has been to perform the correct classification of the objects in the scene. The present study introduces a brief review of some classical as well as a novel technique that have been used for such purposes. The use of principal component analysis and K-means clustering techniques as important classification algorithms is here discussed. Moreover, a recent method based on the min-W and max-M lattice auto-associative memories, that was proposed for endmember determination in hyperspectral imagery, is introduced as a classification method. Besides a discussion of their mathematical foundation, we emphasize their main characteristics and the results achieved for two exemplar images conformed by objects similar in appearance, but spectrally different. The classification results state that the first components computed from principal component analysis can be used to highlight areas with different spectral characteristics. In addition, the use of lattice auto-associative memories provides good results for materials classification even in the cases where some spectral similarities appears in their spectral responses.

Using computer assisted image analysis to determine the optimal Ki67 threshold for predicting outcome of invasive breast cancer

PubMed Central

Tay, Timothy Kwang Yong; Thike, Aye Aye; Pathmanathan, Nirmala; Jara-Lazaro, Ana Richelia; Iqbal, Jabed; Sng, Adeline Shi Hui; Ye, Heng Seow; Lim, Jeffrey Chun Tatt; Koh, Valerie Cui Yun; Tan, Jane Sie Yong; Yeong, Joe Poh Sheng; Chow, Zi Long; Li, Hui Hua; Cheng, Chee Leong; Tan, Puay Hoon

2018-01-01

Background Ki67 positivity in invasive breast cancers has an inverse correlation with survival outcomes and serves as an immunohistochemical surrogate for molecular subtyping of breast cancer, particularly ER positive breast cancer. The optimal threshold of Ki67 in both settings, however, remains elusive. We use computer assisted image analysis (CAIA) to determine the optimal threshold for Ki67 in predicting survival outcomes and differentiating luminal B from luminal A breast cancers. Methods Quantitative scoring of Ki67 on tissue microarray (TMA) sections of 440 invasive breast cancers was performed using Aperio ePathology ImmunoHistochemistry Nuclear Image Analysis algorithm, with TMA slides digitally scanned via Aperio ScanScope XT System. Results On multivariate analysis, tumours with Ki67 ≥14% had an increased likelihood of recurrence (HR 1.941, p=0.021) and shorter overall survival (HR 2.201, p=0.016). Similar findings were observed in the subset of 343 ER positive breast cancers (HR 2.409, p=0.012 and HR 2.787, p=0.012 respectively). The value of Ki67 associated with ER+HER2-PR<20% tumours (Luminal B subtype) was found to be <17%. Conclusion Using CAIA, we found optimal thresholds for Ki67 that predict a poorer prognosis and an association with the Luminal B subtype of breast cancer. Further investigation and validation of these thresholds are recommended. PMID:29545924

Routine perioperative ketorolac administration is not associated with hemorrhage in pediatric neurosurgery patients.

PubMed

Richardson, Marlin Dustin; Palmeri, Nicholas O; Williams, Sarah A; Torok, Michelle R; O'Neill, Brent R; Handler, Michael H; Hankinson, Todd C

2016-01-01

OBJECT NSAIDs are effective perioperative analgesics. Many surgeons are reluctant to use NSAIDs perioperatively because of a theoretical increase in the risk for bleeding events. The authors assessed the effect of routine perioperative ketorolac use on intracranial hemorrhage in children undergoing a wide range of neurosurgical procedures. METHODS A retrospective single-institution analysis of 1451 neurosurgical cases was performed. Data included demographics, type of surgery, and perioperative ketorolac use. Outcomes included bleeding events requiring return to the operating room, bleeding seen on postoperative imaging, and the development of renal failure or gastrointestinal tract injury. Variables associated with both the exposure and outcomes (p < 0.20) were evaluated as potential confounders for bleeding on postoperative imaging, and multivariable logistic regression was performed. Bivariable analysis was performed for bleeding events. Odds ratios and 95% CIs were estimated. RESULTS Of the 1451 patients, 955 received ketorolac. Multivariate regression analysis demonstrated no significant association between clinically significant bleeding events (OR 0.69; 95% CI 0.15-3.1) or radiographic hemorrhage (OR 0.81; 95% CI 0.43-1.51) and the perioperative administration of ketorolac. Treatment with a medication that creates a known bleeding risk (OR 3.11; 95% CI 1.01-9.57), surgical procedure (OR 2.35; 95% CI 1.11-4.94), and craniotomy/craniectomy (OR 2.43; 95% CI 1.19-4.94) were associated with a significantly elevated risk for radiographically identified hemorrhage. CONCLUSIONS Short-term ketorolac therapy does not appear to be associated with a statistically significant increase in the risk of bleeding documented on postoperative imaging in pediatric neurosurgical patients and may be considered as part of a perioperative analgesic regimen. Although no association was found between ketorolac and clinically significant bleeding events, a larger study needs to be conducted to control for confounding factors, because of the rarity of these events.

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

PubMed Central

Ashman, Amy M.; Collins, Clare E.; Brown, Leanne J.; Rae, Kym M.; Rollo, Megan E.

2017-01-01

Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05), and for micronutrients both including (r = 0.47–0.94, all p < 0.05) and excluding (r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women. PMID:28106758

New breast cancer prognostic factors identified by computer-aided image analysis of HE stained histopathology images

PubMed Central

Chen, Jia-Mei; Qu, Ai-Ping; Wang, Lin-Wei; Yuan, Jing-Ping; Yang, Fang; Xiang, Qing-Ming; Maskey, Ninu; Yang, Gui-Fang; Liu, Juan; Li, Yan

2015-01-01

Computer-aided image analysis (CAI) can help objectively quantify morphologic features of hematoxylin-eosin (HE) histopathology images and provide potentially useful prognostic information on breast cancer. We performed a CAI workflow on 1,150 HE images from 230 patients with invasive ductal carcinoma (IDC) of the breast. We used a pixel-wise support vector machine classifier for tumor nests (TNs)-stroma segmentation, and a marker-controlled watershed algorithm for nuclei segmentation. 730 morphologic parameters were extracted after segmentation, and 12 parameters identified by Kaplan-Meier analysis were significantly associated with 8-year disease free survival (P < 0.05 for all). Moreover, four image features including TNs feature (HR 1.327, 95%CI [1.001 - 1.759], P = 0.049), TNs cell nuclei feature (HR 0.729, 95%CI [0.537 - 0.989], P = 0.042), TNs cell density (HR 1.625, 95%CI [1.177 - 2.244], P = 0.003), and stromal cell structure feature (HR 1.596, 95%CI [1.142 - 2.229], P = 0.006) were identified by multivariate Cox proportional hazards model to be new independent prognostic factors. The results indicated that CAI can assist the pathologist in extracting prognostic information from HE histopathology images for IDC. The TNs feature, TNs cell nuclei feature, TNs cell density, and stromal cell structure feature could be new prognostic factors. PMID:26022540

Selectivity analysis of an incoherent grating imaged in a photorefractive crystal

NASA Astrophysics Data System (ADS)

Tebaldi, Myrian; Forte, Gustavo; Bolognini, Nestor; Lasprilla A., Maria del Carmen

2018-04-01

In this work, the diffraction efficiency of a volume phase grating incoherently stored in a photorefractive BSO crystal is theoretically and experimentally analyzed. The results confirm the theoretical proposal based on the coupled wave theory adopting a new grating depth parameter associated to the write-in incoherent optical system. The selectivity behavior is governed by the exit pupil diameter of the imaging recording system that controls the depth of the tridimensional image distribution along the propagation direction. Two incoherent gratings are multiplexed in a single crystal and reconstructed without cross-talk.

Wavelet transform analysis of the small-scale X-ray structure of the cluster Abell 1367

NASA Technical Reports Server (NTRS)

Grebeney, S. A.; Forman, W.; Jones, C.; Murray, S.

1995-01-01

We have developed a new technique based on a wavelet transform analysis to quantify the small-scale (less than a few arcminutes) X-ray structure of clusters of galaxies. We apply this technique to the ROSAT position sensitive proportional counter (PSPC) and Einstein high-resolution imager (HRI) images of the central region of the cluster Abell 1367 to detect sources embedded within the diffuse intracluster medium. In addition to detecting sources and determining their fluxes and positions, we show that the wavelet analysis allows a characterization of the sources extents. In particular, the wavelet scale at which a given source achieves a maximum signal-to-noise ratio in the wavelet images provides an estimate of the angular extent of the source. To account for the widely varying point response of the ROSAT PSPC as a function of off-axis angle requires a quantitative measurement of the source size and a comparison to a calibration derived from the analysis of a Deep Survey image. Therefore, we assume that each source could be described as an isotropic two-dimensional Gaussian and used the wavelet amplitudes, at different scales, to determine the equivalent Gaussian Full Width Half-Maximum (FWHM) (and its uncertainty) appropriate for each source. In our analysis of the ROSAT PSPC image, we detect 31 X-ray sources above the diffuse cluster emission (within a radius of 24 min), 16 of which are apparently associated with cluster galaxies and two with serendipitous, background quasars. We find that the angular extents of 11 sources exceed the nominal width of the PSPC point-spread function. Four of these extended sources were previously detected by Bechtold et al. (1983) as 1 sec scale features using the Einstein HRI. The same wavelet analysis technique was applied to the Einstein HRI image. We detect 28 sources in the HRI image, of which nine are extended. Eight of the extended sources correspond to sources previously detected by Bechtold et al. Overall, using both the PSPC and the HRI observations, we detect 16 extended features, of which nine have galaxies coincided with the X-ray-measured positions (within the positional error circles). These extended sources have luminosities lying in the range (3 - 30) x 10(exp 40) ergs/s and gas masses of approximately (1 - 30) x 10(exp 9) solar mass, if the X-rays are of thermal origin. We confirm the presence of extended features in A1367 first reported by Bechtold et al. (1983). The nature of these systems remains uncertain. The luminosities are large if the emission is attributed to single galaxies, and several of the extended features have no associated galaxy counterparts. The extended features may be associated with galaxy groups, as suggested by Canizares, Fabbiano, & Trinchieri (1987), although the number required is large.

Framing Service, Benefit, and Credibility Through Images and Texts: A Content Analysis of Online Promotional Messages of Korean Medical Tourism Industry.

PubMed

Jun, Jungmi

2016-07-01

This study examines how the Korean medical tourism industry frames its service, benefit, and credibility issues through texts and images of online brochures. The results of content analysis suggest that the Korean medical tourism industry attempts to frame their medical/health services as "excellence in surgeries and cancer care" and "advanced health technology and facilities." However, the use of cost-saving appeals was limited, which can be seen as a strategy to avoid consumers' association of lower cost with lower quality services, and to stress safety and credibility.

Magnetic resonance imaging as a tool for extravehicular activity analysis

NASA Technical Reports Server (NTRS)

Dickenson, R.; Lorenz, C.; Peterson, S.; Strauss, A.; Main, J.

1992-01-01

The purpose of this research is to examine the value of magnetic resonance imaging (MRI) as a means of conducting kinematic studies of the hand for the purpose of EVA capability enhancement. After imaging the subject hand using a magnetic resonance scanner, the resulting 2D slices were reconstructed into a 3D model of the proximal phalanx of the left hand. Using the coordinates of several landmark positions, one is then able to decompose the motion of the rigid body. MRI offers highly accurate measurements due to its tomographic nature without the problems associated with other imaging modalities for in vivo studies.

Brain imaging registry for neurologic diagnosis and research

NASA Astrophysics Data System (ADS)

Hoo, Kent S., Jr.; Wong, Stephen T. C.; Knowlton, Robert C.; Young, Geoffrey S.; Walker, John; Cao, Xinhua; Dillon, William P.; Hawkins, Randall A.; Laxer, Kenneth D.

2002-05-01

The purpose of this paper is to demonstrate the importance of building a brain imaging registry (BIR) on top of existing medical information systems including Picture Archiving Communication Systems (PACS) environment. We describe the design framework for a cluster of data marts whose purpose is to provide clinicians and researchers efficient access to a large volume of raw and processed patient images and associated data originating from multiple operational systems over time and spread out across different hospital departments and laboratories. The framework is designed using object-oriented analysis and design methodology. The BIR data marts each contain complete image and textual data relating to patients with a particular disease.

Shadow analysis via the C+K Visioline: A technical note.

PubMed

Houser, T; Zerweck, C; Grove, G; Wickett, R

2017-11-01

This research investigated the ability of shadow analysis (via the Courage + Khazaka Visioline and Image Pro Premiere 9.0 software) to accurately assess the differences in skin topography associated with photo aging. Analyses were performed on impressions collected from a microfinish comparator scale (GAR Electroforming) as well a series of impressions collected from the crow's feet region of 9 women who represent each point on the Zerweck Crow's Feet classification scale. Analyses were performed using a Courage + Khazaka Visioline VL 650 as well as Image Pro Premiere 9.0 software. Shadow analysis showed an ability to accurately measure the groove depth when measuring impressions collected from grooves of known depth. Several shadow analysis parameters showed a correlation with the expert grader ratings of crow's feet when averaging measurements taken from the North and South directions. The Max Depth parameter in particular showed a strong correlation with the expert grader's ratings which improved when a more sophisticated analysis was performed using Image Pro Premiere. When used properly, shadow analysis is effective at accurately measuring skin surface impressions for differences in skin topography. Shadow analysis is shown to accurately assess the differences across a range of crow's feet severity correlating to a 0-8 grader scale. The Visioline VL 650 is a good tool for this measurement, with room for improvement in analysis which can be achieved through third party image analysis software. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

ACCOUNTING FOR ERROR PROPAGATION IN THE DEVELOPMENT OF A LEAF AREA INDEX (LAI) REFERENCE MAP TO ASSESS THE MODIS LAI MODI5A LAI PRODUCT

EPA Science Inventory

The ability to effectively use remotely sensed data for environmental spatial analysis is dependent on understanding the underlying procedures and associated variances attributed to the data processing and image analysis technique. Equally important, also, is understanding the er...

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

PubMed

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

2011-09-10

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

Plaque levels of patients with fixed orthodontic appliances measured by digital plaque image analysis.

PubMed

Klukowska, Malgorzata; Bader, Annike; Erbe, Christina; Bellamy, Philip; White, Donald J; Anastasia, Mary Kay; Wehrbein, Heiner

2011-05-01

A digital plaque image analysis system was developed to objectively assess dental plaque formation and coverage in patients treated with fixed orthodontic appliances. The technique was used to assess plaque levels of 52 patients undergoing treatment with fixed appliances in the Department of Orthodontics at Johannes Gutenberg University in Mainz, Germany. Plaque levels ranged from 5.1% to 85.3% of the analyzed tooth areas. About 37% of the patients had plaque levels over 50% of the dentition, but only 10% exhibited plaque levels below 15% of tooth coverage. The mean plaque coverage was 41.9% ± 18.8%. Plaque was mostly present along the gum line and around the orthodontic brackets and wires. The digital plaque image analysis system might provide a convenient quantitative technique to assess oral hygiene in orthodontic patients with multi-bracket appliances. Plaque coverage in orthodontic patients is extremely high and is 2 to 3 times higher than levels observed in high plaque-forming adults without appliances participating in clinical studies of the digital plaque image analysis system. Improved hygiene, chemotherapeutic regimens, and compliance are necessary in these patients. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Evaluation of a global algorithm for wavefront reconstruction for Shack-Hartmann wave-front sensors and thick fundus reflectors.

PubMed

Liu, Tao; Thibos, Larry; Marin, Gildas; Hernandez, Martha

2014-01-01

Conventional aberration analysis by a Shack-Hartmann aberrometer is based on the implicit assumption that an injected probe beam reflects from a single fundus layer. In fact, the biological fundus is a thick reflector and therefore conventional analysis may produce errors of unknown magnitude. We developed a novel computational method to investigate this potential failure of conventional analysis. The Shack-Hartmann wavefront sensor was simulated by computer software and used to recover by two methods the known wavefront aberrations expected from a population of normally-aberrated human eyes and bi-layer fundus reflection. The conventional method determines the centroid of each spot in the SH data image, from which wavefront slopes are computed for least-squares fitting with derivatives of Zernike polynomials. The novel 'global' method iteratively adjusted the aberration coefficients derived from conventional centroid analysis until the SH image, when treated as a unitary picture, optimally matched the original data image. Both methods recovered higher order aberrations accurately and precisely, but only the global algorithm correctly recovered the defocus coefficients associated with each layer of fundus reflection. The global algorithm accurately recovered Zernike coefficients for mean defocus and bi-layer separation with maximum error <0.1%. The global algorithm was robust for bi-layer separation up to 2 dioptres for a typical SH wavefront sensor design. For 100 randomly generated test wavefronts with 0.7 D axial separation, the retrieved mean axial separation was 0.70 D with standard deviations (S.D.) of 0.002 D. Sufficient information is contained in SH data images to measure the dioptric thickness of dual-layer fundus reflection. The global algorithm is superior since it successfully recovered the focus value associated with both fundus layers even when their separation was too small to produce clearly separated spots, while the conventional analysis misrepresents the defocus component of the wavefront aberration as the mean defocus for the two reflectors. Our novel global algorithm is a promising method for SH data image analysis in clinical and visual optics research for human and animal eyes. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.

Prediction of Esophageal Varices in Patients with Cirrhosis: Usefulness of Three-dimensional MR Elastography with Echo-planar Imaging Technique

PubMed Central

Shin, Sung Ui; Yu, Mi Hye; Yoon, Jeong Hee; Han, Joon Koo; Choi, Byung-Ihn; Glaser, Kevin J.; Ehman, Richard L.

2014-01-01

Purpose To determine the diagnostic performance of magnetic resonance (MR) elastography in comparison to spleen length and dynamic contrast material–enhanced (DCE) MR imaging in association with esophageal varices in patients with liver cirrhosis by using endoscopy as the reference standard. Materials and Methods This retrospective study received institutional review board approval, and informed consent was waived. One hundred thirty-nine patients with liver cirrhosis who underwent liver DCE MR imaging, including MR elastography, were included. Hepatic stiffness (HS) and spleen stiffness (SS) values assessed with MR elastography, as well as spleen length, were correlated with the presence of esophageal varices and high-risk varices by using Spearman correlation analysis. The diagnostic performance of MR elastography was compared with that of DCE MR imaging and combined assessment of MR elastography and DCE MR imaging by using receiver operating characteristic analysis. MR elastography reproducibility was assessed prospectively, with informed consent, in another 15 patients by using intraclass correlation coefficients. Results There were significant positive linear correlations between HS, SS, and spleen length and the grade of esophageal varices (r = 0.46, r = 0.48, and r = 0.36, respectively; all P < .0001). HS and SS values (>4.81 kPa and >7.60 kPa, respectively) showed better performance than did spleen length in the association with esophageal varices (P = .0306 and P = .0064, respectively). Diagnostic performance of HS and SS in predicting high-risk varices was comparable to that of DCE MR imaging (P = .1282 and P = .1371, respectively). When MR elastography and DCE MR imaging were combined, sensitivity improved significantly (P = .0004). MR elastography was highly reproducible (intraclass correlation coefficient > 0.9). Conclusion HS and SS are associated with esophageal varices and showed better performance than did spleen length in assessing the presence of esophageal varices. MR elastography is comparable to DCE MR imaging in predicting the presence of esophageal varices and high-risk varices, but, when assessed in combination, sensitivity is higher. © RSNA, 2014 Online supplemental material is available for this article. PMID:24620910

Molecular imaging biomarkers of resistance to radiation therapy for spontaneous nasal tumors in canines.

PubMed

Bradshaw, Tyler J; Bowen, Stephen R; Deveau, Michael A; Kubicek, Lyndsay; White, Pamela; Bentzen, Søren M; Chappell, Richard J; Forrest, Lisa J; Jeraj, Robert

2015-03-15

Imaging biomarkers of resistance to radiation therapy can inform and guide treatment management. Most studies have so far focused on assessing a single imaging biomarker. The goal of this study was to explore a number of different molecular imaging biomarkers as surrogates of resistance to radiation therapy. Twenty-two canine patients with spontaneous sinonasal tumors were treated with accelerated hypofractionated radiation therapy, receiving either 10 fractions of 4.2 Gy each or 10 fractions of 5.0 Gy each to the gross tumor volume. Patients underwent fluorodeoxyglucose (FDG)-, fluorothymidine (FLT)-, and Cu(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM)-labeled positron emission tomography/computed tomography (PET/CT) imaging before therapy and FLT and Cu-ATSM PET/CT imaging during therapy. In addition to conventional maximum and mean standardized uptake values (SUV(max); SUV(mean)) measurements, imaging metrics providing response and spatiotemporal information were extracted for each patient. Progression-free survival was assessed according to response evaluation criteria in solid tumor. The prognostic value of each imaging biomarker was evaluated using univariable Cox proportional hazards regression. Multivariable analysis was also performed but was restricted to 2 predictor variables due to the limited number of patients. The best bivariable model was selected according to pseudo-R(2). The following variables were significantly associated with poor clinical outcome following radiation therapy according to univariable analysis: tumor volume (P=.011), midtreatment FLT SUV(mean) (P=.018), and midtreatment FLT SUV(max) (P=.006). Large decreases in FLT SUV(mean) from pretreatment to midtreatment were associated with worse clinical outcome (P=.013). In the bivariable model, the best 2-variable combination for predicting poor outcome was high midtreatment FLT SUV(max) (P=.022) in combination with large FLT response from pretreatment to midtreatment (P=.041). In addition to tumor volume, pronounced tumor proliferative response quantified using FLT PET, especially when associated with high residual FLT PET at midtreatment, is a negative prognostic biomarker of outcome in canine tumors following radiation therapy. Neither FDG PET nor Cu-ATSM PET were predictive of outcome. Copyright © 2015 Elsevier Inc. All rights reserved.

A philosophy for CNS radiotracer design.

PubMed

Van de Bittner, Genevieve C; Ricq, Emily L; Hooker, Jacob M

2014-10-21

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test-retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood-brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.

Surface analysis of lipids by mass spectrometry: more than just imaging.

PubMed

Ellis, Shane R; Brown, Simon H; In Het Panhuis, Marc; Blanksby, Stephen J; Mitchell, Todd W

2013-10-01

Mass spectrometry is now an indispensable tool for lipid analysis and is arguably the driving force in the renaissance of lipid research. In its various forms, mass spectrometry is uniquely capable of resolving the extensive compositional and structural diversity of lipids in biological systems. Furthermore, it provides the ability to accurately quantify molecular-level changes in lipid populations associated with changes in metabolism and environment; bringing lipid science to the "omics" age. The recent explosion of mass spectrometry-based surface analysis techniques is fuelling further expansion of the lipidomics field. This is evidenced by the numerous papers published on the subject of mass spectrometric imaging of lipids in recent years. While imaging mass spectrometry provides new and exciting possibilities, it is but one of the many opportunities direct surface analysis offers the lipid researcher. In this review we describe the current state-of-the-art in the direct surface analysis of lipids with a focus on tissue sections, intact cells and thin-layer chromatography substrates. The suitability of these different approaches towards analysis of the major lipid classes along with their current and potential applications in the field of lipid analysis are evaluated. Copyright © 2013 Elsevier Ltd. All rights reserved.

A fractal image analysis methodology for heat damage inspection in carbon fiber reinforced composites

NASA Astrophysics Data System (ADS)

Haridas, Aswin; Crivoi, Alexandru; Prabhathan, P.; Chan, Kelvin; Murukeshan, V. M.

2017-06-01

The use of carbon fiber-reinforced polymer (CFRP) composite materials in the aerospace industry have far improved the load carrying properties and the design flexibility of aircraft structures. A high strength to weight ratio, low thermal conductivity, and a low thermal expansion coefficient gives it an edge for applications demanding stringent loading conditions. Specifically, this paper focuses on the behavior of CFRP composites under stringent thermal loads. The properties of composites are largely affected by external thermal loads, especially when the loads are beyond the glass temperature, Tg, of the composite. Beyond this, the composites are subject to prominent changes in mechanical and thermal properties which may further lead to material decomposition. Furthermore, thermal damage formation being chaotic, a strict dimension cannot be associated with the formed damage. In this context, this paper focuses on comparing multiple speckle image analysis algorithms to effectively characterize the formed thermal damages on the CFRP specimen. This would provide us with a fast method for quantifying the extent of heat damage in carbon composites, thus reducing the required time for inspection. The image analysis methods used for the comparison include fractal dimensional analysis of the formed speckle pattern and analysis of number and size of various connecting elements in the binary image.

Students' Approaches to Groupwork in a Blended Course, Associations with Perceptions of the Online Environment and Academic Achievement--When Is Learning Engaged?

ERIC Educational Resources Information Center

Ellis, Robert A.

2016-01-01

University teachers provided first year Arts students with hundreds of cinematic images online to analyse as a key part of their predominantly face-to-face undergraduate course. This qualitative study investigates the extent to which the groups engaged in learning involving their analysis of the images and how this was related to their perception…

Infrared spectral imaging as a novel approach for histopathological recognition in colon cancer diagnosis

NASA Astrophysics Data System (ADS)

Nallala, Jayakrupakar; Gobinet, Cyril; Diebold, Marie-Danièle; Untereiner, Valérie; Bouché, Olivier; Manfait, Michel; Sockalingum, Ganesh Dhruvananda; Piot, Olivier

2012-11-01

Innovative diagnostic methods are the need of the hour that could complement conventional histopathology for cancer diagnosis. In this perspective, we propose a new concept based on spectral histopathology, using IR spectral micro-imaging, directly applied to paraffinized colon tissue array stabilized in an agarose matrix without any chemical pre-treatment. In order to correct spectral interferences from paraffin and agarose, a mathematical procedure is implemented. The corrected spectral images are then processed by a multivariate clustering method to automatically recover, on the basis of their intrinsic molecular composition, the main histological classes of the normal and the tumoral colon tissue. The spectral signatures from different histological classes of the colonic tissues are analyzed using statistical methods (Kruskal-Wallis test and principal component analysis) to identify the most discriminant IR features. These features allow characterizing some of the biomolecular alterations associated with malignancy. Thus, via a single analysis, in a label-free and nondestructive manner, main changes associated with nucleotide, carbohydrates, and collagen features can be identified simultaneously between the compared normal and the cancerous tissues. The present study demonstrates the potential of IR spectral imaging as a complementary modern tool, to conventional histopathology, for an objective cancer diagnosis directly from paraffin-embedded tissue arrays.

Evaluation of glymphatic system activity with the diffusion MR technique: diffusion tensor image analysis along the perivascular space (DTI-ALPS) in Alzheimer's disease cases.

PubMed

Taoka, Toshiaki; Masutani, Yoshitaka; Kawai, Hisashi; Nakane, Toshiki; Matsuoka, Kiwamu; Yasuno, Fumihiko; Kishimoto, Toshifumi; Naganawa, Shinji

2017-04-01

The activity of the glymphatic system is impaired in animal models of Alzheimer's disease (AD). We evaluated the activity of the human glymphatic system in cases of AD with a diffusion-based technique called diffusion tensor image analysis along the perivascular space (DTI-ALPS). Diffusion tensor images were acquired to calculate diffusivities in the x, y, and z axes of the plane of the lateral ventricle body in 31 patients. We evaluated the diffusivity along the perivascular spaces as well as projection fibers and association fibers separately, to acquire an index for diffusivity along the perivascular space (ALPS-index) and correlated them with the mini mental state examinations (MMSE) score. We found a significant negative correlation between diffusivity along the projection fibers and association fibers. We also observed a significant positive correlation between diffusivity along perivascular spaces shown as ALPS-index and the MMSE score, indicating lower water diffusivity along the perivascular space in relation to AD severity. Activity of the glymphatic system may be evaluated with diffusion images. Lower diffusivity along the perivascular space on DTI-APLS seems to reflect impairment of the glymphatic system. This method may be useful for evaluating the activity of the glymphatic system.

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

USGS Publications Warehouse

Wallace, C.S.A.; Marsh, S.E.

2005-01-01

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

Imaging systems and methods for obtaining and using biometric information

DOEpatents

McMakin, Douglas L [Richland, WA; Kennedy, Mike O [Richland, WA

2010-11-30

Disclosed herein are exemplary embodiments of imaging systems and methods of using such systems. In one exemplary embodiment, one or more direct images of the body of a clothed subject are received, and a motion signature is determined from the one or more images. In this embodiment, the one or more images show movement of the body of the subject over time, and the motion signature is associated with the movement of the subject's body. In certain implementations, the subject can be identified based at least in part on the motion signature. Imaging systems for performing any of the disclosed methods are also disclosed herein. Furthermore, the disclosed imaging, rendering, and analysis methods can be implemented, at least in part, as one or more computer-readable media comprising computer-executable instructions for causing a computer to perform the respective methods.

Does the nephrostomy tract length impact the outcomes of percutaneous nephrolithotomy (PNL)?

PubMed

Astroza, Gaston M; Neisius, Andreas; Tsivian, Matvey; Wang, Agnes J; Preminger, Glenn M; Lipkin, Michael E

2014-12-01

Different factors can determine the outcomes of percutaneous nephrolithotomy (PNL). We analyzed the effect of tract length (TL) on outcomes after PNL. We performed a retrospective review of patients undergoing PNL between 2006 and 2011. Patients with preoperative computed tomography (CT), one percutaneous access tract and follow-up imaging within 3 months were included. TL was defined as distance between the skin to the calyx of puncture as measured on preoperative CT. Measurements were independently performed by two urologists and the average was used for analysis. Stone-free rate (SFR) was defined as zero fragments on follow-up imaging. Factors independently associated with the likelihood of being stone-free after PNL were determined using multivariable analysis adjusted for TL, location of access, the presence of incomplete or complete staghorn calculi and type of follow-up imaging. Complications (Clavien score) were independently assessed. A total of 222 patients were included. Median stone burden and body mass index (BMI) was 239.4 mm(2) and 30.5 [interquartile range (IQR): 25.7-36.2]. The median TL was 85.0 mm (IQR: 70.3-100.0) and highly correlated with BMI (ρ = 0.66, p < 0.001). A total of 101 patients (45.5 %) were stone-free. TL was not associated with SFR (p = 0.53). Clavien 1 and 2 complications occurred in 38 (17 %) while Clavien 3 and 4 complications occurred in 17 (8 %) patients. Multivariable analysis revealed no association between complications and TL even when adjusted for gender. Percutaneous TL is not associated with outcomes of PNL. PNL is a safe and effective treatment for stones in patients with differing body habitus.

The effects of radiation therapy on height and spine MRI characteristics in children with neuroblastoma.

PubMed

Yu, Jeong Il; Lim, Do Hoon; Jung, Sang Hoon; Sung, Ki Woong; Yoo, So-Young; Nam, Heerim

2015-03-01

To investigate the effect of radiotherapy (RT) on height and spine using magnetic resonance imaging (MRI) analysis in children with neuroblastoma and to identify parameters related to patient height. We performed a retrospective cohort study of neuroblastoma patients treated between January 1997 and December 2007. Twenty-seven children were enrolled. Whole spine MRI was completed and height percentiles were compared with national growth charts. The median ages were 28, 43, and 126 months at diagnosis, RT, and analysis, respectively. All of the enrolled children received local RT, and 15 patients received total body irradiation (TBI). Median growth percentiles were 67.0, 54.0, and 4.9 at diagnosis, RT, and analysis, respectively. The number of irradiated vertebrae (P=0.009) and having undergone TBI (P=0.03) were significantly associated with shorter stature. Among the MRI parameters for irradiated vertebrae, signal intensity was higher (P=0.05) and more heterogeneous (P=0.02) in T1-weighted images and roundness was lower (P=0.03) in T2-weighted images. Height of children with neuroblastoma was significantly affected by RT. The number of irradiated vertebrae and having undergone TBI were significantly associated with lower height. Irradiated spine showed changes in both signal and shape on MRI. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Design of an automated imaging system for use in a space experiment

NASA Technical Reports Server (NTRS)

Hartz, William G.; Bozzolo, Nora G.; Lewis, Catherine C.; Pestak, Christopher J.

1991-01-01

An experiment, occurring in an orbiting platform, examines the mass transfer across gas-liquid and liquid-liquid interfaces. It employs an imaging system with real time image analysis. The design includes optical design, imager selection and integration, positioner control, image recording, software development for processing and interfaces to telemetry. It addresses the constraints of weight, volume, and electric power associated with placing the experiment in the Space Shuttle cargo bay. Challenging elements of the design are: imaging and recording of a 200-micron-diameter bubble with a resolution of 2 microns to serve a primary source of data; varying frame rates from 500 per second to 1 frame per second, depending on the experiment phase; and providing three-dimensional information to determine the shape of the bubble.

Texture Analysis of Chaotic Coupled Map Lattices Based Image Encryption Algorithm

NASA Astrophysics Data System (ADS)

Khan, Majid; Shah, Tariq; Batool, Syeda Iram

2014-09-01

As of late, data security is key in different enclosures like web correspondence, media frameworks, therapeutic imaging, telemedicine and military correspondence. In any case, a large portion of them confronted with a few issues, for example, the absence of heartiness and security. In this letter, in the wake of exploring the fundamental purposes of the chaotic trigonometric maps and the coupled map lattices, we have presented the algorithm of chaos-based image encryption based on coupled map lattices. The proposed mechanism diminishes intermittent impact of the ergodic dynamical systems in the chaos-based image encryption. To assess the security of the encoded image of this scheme, the association of two nearby pixels and composition peculiarities were performed. This algorithm tries to minimize the problems arises in image encryption.

Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures.

PubMed

Wong, Kelvin K L; Wang, Defeng; Ko, Jacky K L; Mazumdar, Jagannath; Le, Thu-Thao; Ghista, Dhanjoo

2017-03-21

Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.

Signal intensity on fluid-attenuated inversion recovery images of condylar marrow changes correspond with slight pain in patients with temporomandibular joint disorders.

PubMed

Kodama, Sayaka; Otonari-Yamamoto, Mika; Sano, Tsukasa; Sakamoto, Junichirou; Imoto, Kenichi; Wakoh, Mamoru

2014-01-01

Edema and necrosis of the temporomandibular joint (TMJ) have been described in terms of bone marrow signal abnormalities in magnetic resonance imaging (MRI). However, painful joints often show no such signaling abnormalities, making the diagnosis of TMJ disorders difficult in the clinical setting. An association has been suggested between TMJ bone marrow change and TMJ pain, but even when such change results in slight pain, it may be too slight to be visually apparent on MR images. We hypothesized that fluid-attenuated inversion recovery (FLAIR) can be used to detect such minimal changes. The purpose of this study was to determine whether there is an association between signal intensity on FLAIR images and pain in the TMJ. The study included 85 TMJs in 45 patients referred to our department for MRI. The signal intensity on FLAIR images was measured. Pain was evaluated based on the visual analog scale. An unpaired t test and Pearson's product-moment correlation coefficient were used for the statistical analysis. A p value of <0.05 was considered statistically significant. Signal intensity on the FLAIR images was significantly higher in painful than in nonpainful TMJs, although a significant correlation was not observed between the signal intensity and the pain score. The results of this study suggest an association between abnormalities in the marrow of the mandibular condyle and pain. They also indicate that FLAIR imaging is a useful tool in the clinical diagnosis of painful TMJs.

Food and drug cues activate similar brain regions: a meta-analysis of functional MRI studies.

PubMed

Tang, D W; Fellows, L K; Small, D M; Dagher, A

2012-06-06

In healthy individuals, food cues can trigger hunger and feeding behavior. Likewise, smoking cues can trigger craving and relapse in smokers. Brain imaging studies report that structures involved in appetitive behaviors and reward, notably the insula, striatum, amygdala and orbital frontal cortex, tend to be activated by both visual food and smoking cues. Here, by carrying out a meta-analysis of human neuro-imaging studies, we investigate the neural network activated by: 1) food versus neutral cues (14 studies, 142 foci) 2) smoking versus neutral cues (15 studies, 176 foci) 3) smoking versus neutral cues when correlated with craving scores (7 studies, 108 foci). PubMed was used to identify cue-reactivity imaging studies that compared brain response to visual food or smoking cues to neutral cues. Fourteen articles were identified for the food meta-analysis and fifteen articles were identified for the smoking meta-analysis. Six articles were identified for the smoking cue correlated with craving analysis. Meta-analyses were carried out using activation likelihood estimation. Food cues were associated with increased blood oxygen level dependent (BOLD) response in the left amygdala, bilateral insula, bilateral orbital frontal cortex, and striatum. Smoking cues were associated with increased BOLD signal in the same areas, with the exception of the insula. However, the smoking meta-analysis of brain maps correlating cue-reactivity with subjective craving did identify the insula, suggesting that insula activation is only found when craving levels are high. The brain areas identified here are involved in learning, memory and motivation, and their cue-induced activity is an index of the incentive salience of the cues. Using meta-analytic techniques to combine a series of studies, we found that food and smoking cues activate comparable brain networks. There is significant overlap in brain regions responding to conditioned cues associated with natural and drug rewards. Copyright © 2012 Elsevier Inc. All rights reserved.

Accuracy of Presurgical Functional MR Imaging for Language Mapping of Brain Tumors: A Systematic Review and Meta-Analysis.

PubMed

Weng, Hsu-Huei; Noll, Kyle R; Johnson, Jason M; Prabhu, Sujit S; Tsai, Yuan-Hsiung; Chang, Sheng-Wei; Huang, Yen-Chu; Lee, Jiann-Der; Yang, Jen-Tsung; Yang, Cheng-Ta; Tsai, Ying-Huang; Yang, Chun-Yuh; Hazle, John D; Schomer, Donald F; Liu, Ho-Ling

2018-02-01

Purpose To compare functional magnetic resonance (MR) imaging for language mapping (hereafter, language functional MR imaging) with direct cortical stimulation (DCS) in patients with brain tumors and to assess factors associated with its accuracy. Materials and Methods PubMed/MEDLINE and related databases were searched for research articles published between January 2000 and September 2016. Findings were pooled by using bivariate random-effects and hierarchic summary receiver operating characteristic curve models. Meta-regression and subgroup analyses were performed to evaluate whether publication year, functional MR imaging paradigm, magnetic field strength, statistical threshold, and analysis software affected classification accuracy. Results Ten articles with a total of 214 patients were included in the analysis. On a per-patient basis, the pooled sensitivity and specificity of functional MR imaging was 44% (95% confidence interval [CI]: 14%, 78%) and 80% (95% CI: 54%, 93%), respectively. On a per-tag basis (ie, each DCS stimulation site or "tag" was considered a separate data point across all patients), the pooled sensitivity and specificity were 67% (95% CI: 51%, 80%) and 55% (95% CI: 25%, 82%), respectively. The per-tag analysis showed significantly higher sensitivity for studies with shorter functional MR imaging session times (P = .03) and relaxed statistical threshold (P = .05). Significantly higher specificity was found when expressive language task (P = .02), longer functional MR imaging session times (P < .01), visual presentation of stimuli (P = .04), and stringent statistical threshold (P = .01) were used. Conclusion Results of this study showed moderate accuracy of language functional MR imaging when compared with intraoperative DCS, and the included studies displayed significant methodologic heterogeneity. © RSNA, 2017 Online supplemental material is available for this article.

Measurement of Galactic Logarithmic Spiral Arm Pitch Angle Using Two-dimensional Fast Fourier Transform Decomposition

NASA Astrophysics Data System (ADS)

Davis, Benjamin L.; Berrier, Joel C.; Shields, Douglas W.; Kennefick, Julia; Kennefick, Daniel; Seigar, Marc S.; Lacy, Claud H. S.; Puerari, Ivânio

2012-04-01

A logarithmic spiral is a prominent feature appearing in a majority of observed galaxies. This feature has long been associated with the traditional Hubble classification scheme, but historical quotes of pitch angle of spiral galaxies have been almost exclusively qualitative. We have developed a methodology, utilizing two-dimensional fast Fourier transformations of images of spiral galaxies, in order to isolate and measure the pitch angles of their spiral arms. Our technique provides a quantitative way to measure this morphological feature. This will allow comparison of spiral galaxy pitch angle to other galactic parameters and test spiral arm genesis theories. In this work, we detail our image processing and analysis of spiral galaxy images and discuss the robustness of our analysis techniques.

Visual analytics for semantic queries of TerraSAR-X image content

NASA Astrophysics Data System (ADS)

Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

2015-10-01

With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain the image content using semantic terms and the relations between them answering questions such as what is the percentage of urban area in a region? or what is the distribution of water bodies in a city?

Factors associated with body image dissatisfaction among adolescents in public schools students in Salvador, Brazil.

PubMed

Santana, Mônica L P; Silva, Rita de Cássia R; Assis, Ana M O; Raich, Rosa M; Machado, Maria Ester P C; de J Pinto, Elizabete; de Moraes, Lia T L P; Ribeiro Júnior, Hugo da C

2013-01-01

To identify the prevalence of body image dissatisfaction and associated factors among students in Salvador, Brazil. A cross-sectional study involving a random sample of 1,494 (852 girls and 642 boys) adolescents between 11 and 17 years of age who were students in the public schools in Salvador, Brazil. Participants completed the Body Shape Questionnaire and the Eating Attitudes Test-26. Body image was characterized as satisfactory or unsatisfactory. We obtained demographic, anthropometric and economic information and information regarding the stage of maturation, self-perception of body weight, and consumption of sweetened beverages and diet soft drinks. To identify associated factors we used Poisson regression analysis. Body image dissatisfaction was present in 19.5% of the adolescents, with a prevalence of 26.6% among the girls and 10% among the boys. Independent of sex, the prevalence of body image dissatisfaction was higher among adolescents who were overweight or obese (girls, PR: 1.38, CI: 1.09-1.73 and boys, PR: 2.26, CI: 1.08-4.75), higher among those who perceived themselves as fat (girls, PR: 2.85, CI: 2.07-3.93 and boys, PR: 3.17, CI: 1.39-7.23), and higher among those who had negative attitudes toward eating (girls, PR: 2.42, CI: 1.91-3.08 and boys, PR: 4.67, CI: 2.85-7.63).. A reduction in body image dissatisfaction was only identified among underweight girls (PR: 0.12, CI: 0.03-0.49). A high occurrence of body image dissatisfaction was observed among the adolescents, and biological and behavioral factors were associated with this dissatisfaction. Copyright © AULA MEDICA EDICIONES 2013. Published by AULA MEDICA. All rights reserved.

Analysis of Parametric Adaptive Signal Detection with Applications to Radars and Hyperspectral Imaging

DTIC Science & Technology

2010-02-01

98 8.4.5 Training Screening ............................. .................................................................99 8.5 Experimental...associated with the proposed parametric model. Several im- portant issues are discussed, including model order selection, training screening , and time...parameters associated with the NS-AR model. In addition, we develop model order selection, training screening , and time-series based whitening and

Association of red coloration with senescence of sugar maple leaves in autumn

Treesearch

P.G. Schaberg; P.F. Murakami; M.R. Turner; H.K. Heitz; G.J. Hawley

2008-01-01

We evaluated the association of red coloration with senescence in sugar maple (Acer saccharum Marsh.) leaves by assessing differences in leaf retention strength and the progression of the abscission layer through the vascular bundle of green, yellow, and red leaves of 14 mature open-grown trees in October 2002. Computer image analysis confirmed...

Brain imaging and behavioral outcome in traumatic brain injury.

PubMed

Bigler, E D

1996-09-01

Brain imaging studies have become an essential diagnostic assessment procedure in evaluating the effects of traumatic brain injury (TBI). Such imaging studies provide a wealth of information about structural and functional deficits following TBI. But how pathologic changes identified by brain imaging methods relate to neurobehavioral outcome is not as well known. Thus, the focus of this article is on brain imaging findings and outcome following TBI. The article starts with an overview of current research dealing with the cellular pathology associated with TBI. Understanding the cellular elements of pathology permits extrapolation to what is observed with brain imaging. Next, this article reviews the relationship of brain imaging findings to underlying pathology and how that pathology relates to neurobehavioral outcome. The brain imaging techniques of magnetic resonance imaging, computerized tomography, and single photon emission computed tomography are reviewed. Various image analysis procedures, and how such findings relate to neuropsychological testing, are discussed. The importance of brain imaging in evaluating neurobehavioral deficits following brain injury is stressed.

Body Image Concern and its Correlates among Male and Female Undergraduate Students at Assuit University in Egypt

PubMed Central

Ansari, Walid El; Dibba, Emily; Labeeb, Shokria; Stock, Christiane

2014-01-01

Introduction: This cross-sectional study examined variables associated with body image concern (BIC) and whether these associations differed between female and male students in Egypt. During the period 2009-2010, 3271 undergraduate students (1663 females, 1504 males) at Assuit University in Egypt completed a self-administered questionnaire that assessed BIC and other socio-demographic and health related variables. Methods: Based on Cooper et al.’s Body Shape Questionnaire the authors categorized BIC into ‘no BIC’; ‘mild BIC’; and ‘moderate/marked BIC’. Multifactorial linear regression analysis examined the association between BIC and BMI, body image perception, lifestyle (physical activity, nutrition, smoking) and mental well-being variables (quality of life, finances-related stress, perceived stress, perceived health, depressive symptoms). Results: About 40% of the female students and 25.6% of male students reported having mild to marked BIC. The correlates of BIC did not exhibit striking differences between male and female students. For both genders, BIC was positively associated with BMI, body image perception as being too fat and with depressive symptoms. Self-rated health was inversely associated with BIC. Conclusion: These findings suggest that health promoting strategies should address the co-occurrence of depressive symptoms and BIC, and should furthermore pay due attention to higher prevalence of BIC among female students. PMID:25168990

Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images

NASA Astrophysics Data System (ADS)

Navarro, Gabriel; Vicent, Jorge; Caballero, Isabel; Gómez-Enri, Jesús; Morris, Edward P.; Sabater, Neus; Macías, Diego; Bolado-Penagos, Marina; Gomiz, Juan Jesús; Bruno, Miguel; Caldeira, Rui; Vázquez, Águeda

2018-05-01

High Amplitude Internal Waves (HAIWs) are physical processes observed in the Strait of Gibraltar (the narrow channel between the Atlantic Ocean and the Mediterranean Sea). These internal waves are generated over the Camarinal Sill (western side of the strait) during the tidal outflow (toward the Atlantic Ocean) when critical hydraulic conditions are established. HAIWs remain over the sill for up to 4 h until the outflow slackens, being then released (mostly) towards the Mediterranean Sea. These have been previously observed using Synthetic Aperture Radar (SAR), which captures variations in surface water roughness. However, in this work we use high resolution optical remote sensing, with the aim of examining the influence of HAIWs on biogeochemical processes. We used hyperspectral images from the Hyperspectral Imager for the Coastal Ocean (HICO) and high spatial resolution (10 m) images from the MultiSpectral Instrument (MSI) onboard the Sentinel-2A satellite. This work represents the first attempt to examine the relation between internal wave generation and the water constituents of the Camarinal Sill using hyperspectral and high spatial resolution remote sensing images. This enhanced spatial and spectral resolution revealed the detailed biogeochemical patterns associated with the internal waves and suggests local enhancements of productivity associated with internal waves trains.

Cost-effectiveness of angiographic imaging in isolated perimesencephalic subarachnoid hemorrhage.

PubMed

Kalra, Vivek B; Wu, Xiao; Forman, Howard P; Malhotra, Ajay

2014-12-01

The purpose of this study is to perform a comprehensive cost-effectiveness analysis of all possible permutations of computed tomographic angiography (CTA) and digital subtraction angiography imaging strategies for both initial diagnosis and follow-up imaging in patients with perimesencephalic subarachnoid hemorrhage on noncontrast CT. Each possible imaging strategy was evaluated in a decision tree created with TreeAge Pro Suite 2014, with parameters derived from a meta-analysis of 40 studies and literature values. Base case and sensitivity analyses were performed to assess the cost-effectiveness of each strategy. A Monte Carlo simulation was conducted with distributional variables to evaluate the robustness of the optimal strategy. The base case scenario showed performing initial CTA with no follow-up angiographic studies in patients with perimesencephalic subarachnoid hemorrhage to be the most cost-effective strategy ($5422/quality adjusted life year). Using a willingness-to-pay threshold of $50 000/quality adjusted life year, the most cost-effective strategy based on net monetary benefit is CTA with no follow-up when the sensitivity of initial CTA is >97.9%, and CTA with CTA follow-up otherwise. The Monte Carlo simulation reported CTA with no follow-up to be the optimal strategy at willingness-to-pay of $50 000 in 99.99% of the iterations. Digital subtraction angiography, whether at initial diagnosis or as part of follow-up imaging, is never the optimal strategy in our model. CTA without follow-up imaging is the optimal strategy for evaluation of patients with perimesencephalic subarachnoid hemorrhage when modern CT scanners and a strict definition of perimesencephalic subarachnoid hemorrhage are used. Digital subtraction angiography and follow-up imaging are not optimal as they carry complications and associated costs. © 2014 American Heart Association, Inc.

Structural scene analysis and content-based image retrieval applied to bone age assessment

NASA Astrophysics Data System (ADS)

Fischer, Benedikt; Brosig, André; Deserno, Thomas M.; Ott, Bastian; Günther, Rolf W.

2009-02-01

Radiological bone age assessment is based on global or local image regions of interest (ROI), such as epiphyseal regions or the area of carpal bones. Usually, these regions are compared to a standardized reference and a score determining the skeletal maturity is calculated. For computer-assisted diagnosis, automatic ROI extraction is done so far by heuristic approaches. In this work, we apply a high-level approach of scene analysis for knowledge-based ROI segmentation. Based on a set of 100 reference images from the IRMA database, a so called structural prototype (SP) is trained. In this graph-based structure, the 14 phalanges and 5 metacarpal bones are represented by nodes, with associated location, shape, as well as texture parameters modeled by Gaussians. Accordingly, the Gaussians describing the relative positions, relative orientation, and other relative parameters between two nodes are associated to the edges. Thereafter, segmentation of a hand radiograph is done in several steps: (i) a multi-scale region merging scheme is applied to extract visually prominent regions; (ii) a graph/sub-graph matching to the SP robustly identifies a subset of the 19 bones; (iii) the SP is registered to the current image for complete scene-reconstruction (iv) the epiphyseal regions are extracted from the reconstructed scene. The evaluation is based on 137 images of Caucasian males from the USC hand atlas. Overall, an error rate of 32% is achieved, for the 6 middle distal and medial/distal epiphyses, 23% of all extractions need adjustments. On average 9.58 of the 14 epiphyseal regions were extracted successfully per image. This is promising for further use in content-based image retrieval (CBIR) and CBIR-based automatic bone age assessment.

Increased anatomic severity predicts outcomes: Validation of the American Association for the Surgery of Trauma's Emergency General Surgery score in appendicitis.

PubMed

Hernandez, Matthew C; Aho, Johnathon M; Habermann, Elizabeth B; Choudhry, Asad J; Morris, David S; Zielinski, Martin D

2017-01-01

Determination and reporting of disease severity in emergency general surgery lacks standardization. Recently, the American Association for the Surgery of Trauma (AAST) proposed an anatomic severity grading system. We aimed to validate this system in patients with appendicitis and determine if cross-sectional imaging correlates with disease severity at operation. Patients 18 years or older undergoing treatment for acute appendicitis between 2013 and 2015 were identified. Baseline demographics, procedure types were recorded, and AAST grades were assigned based on intraoperative and radiologic findings. Outcomes including length of stay, 30-day mortality, and complications based on Clavien-Dindo categories and National Surgical Quality Improvement Program variables. Summary statistical univariate, nominal logistic, and standard least squares analyses were performed comparing AAST grade with key outcomes. Bland-Altman analysis compared operative findings with preoperative cross-sectional imaging to compare assigning grades. Three hundred thirty-four patients with mean (±SD) age of 39.3 years (±16.5) were included (53% men), and all patients had cross-sectional imaging. Two hundred ninety-nine underwent appendectomy, and 85% completed laparoscopic. Thirty-day mortality rate was 0.9%, complication rate was 21%. Increased (median [interquartile range, IQR]) AAST grade was recorded in patients with complications (2 [1-4]) compared with those without (1 [1-1], p = 0.001). For operative management, (median [IQR]) AAST grades were significantly associated with procedure type: laparoscopic (1 [1-1]), open (4 [2-5]), conversion to open (3 [1-4], p = 0.001). Increased (median [IQR]) AAST grades were significantly associated in nonoperative management: patients having a complication had a higher median AAST grade (4 [3-5]) compared with those without (3 [2-3], p = 0.001). Bland-Altman analysis comparing AAST grade and cross-sectional imaging demonstrated no difference (-0.02 ± 0.02; p = 0.2; coefficient of repeatability 0.9). The AAST grading system is valid in our population. Increased AAST grade is associated with open procedures, complications, and length of stay. The AAST emergency general surgery grade determined by preoperative imaging strongly correlated to operative findings. Epidemiologic/prognostic study, level III.

Increased anatomic severity predicts outcomes: validation of the American Association for the Surgery of Trauma's emergency general surgery score in appendicitis

PubMed Central

Hernandez, Matthew; Aho, Johnathan M.; Habermann, Elizabeth B.; Choudhry, Asad; Morris, David; Zielinski, Martin

2016-01-01

Background Determination and reporting of disease severity in emergency general surgery (EGS) lacks standardization. Recently, the American Association for the Surgery of Trauma (AAST) proposed an anatomic severity grading system. We aimed to validate this system in patients with appendicitis, and determine if cross sectional imaging correlates with disease severity at operation. Methods Patients 18 years or older undergoing treatment for acute appendicitis between 2013 and 2015 were identified. Baseline demographics, procedure types were recorded, and AAST grades were assigned based on intraoperative and radiologic findings. Outcomes including length of stay, 30 day mortality, and complications based on Clavien-Dindo categories and National Surgical Quality Improvement Program variables. Summary statistical univariate, nominal logistic and standard least squares analyses were performed comparing AAST grade with key outcomes. Bland-Altman analysis compared operative findings to preoperative cross sectional imaging to compare assigning grades. Results 334 patients with mean (±SD) age of 39.3 years (±16.5) were included (53% male) and all patients had cross sectional imaging. 299 underwent appendectomy, and 85% completed laparoscopic. 30 day mortality rate was 0.9%, complication rate 21%. Increased median [IQR] AAST grade was recorded in patients with complications 2 [1-4] compared to those without 1 [1-1], p=0.001. For operative management, a median [IQR] AAST grades were significantly associated with procedure type: laparoscopic 1 [1-1], open 4 [2-5] conversion to open 3 [1-4], p=0.001. Increased median [IQR] AAST grades were significantly associated in non-operative management: patients having a complication had a higher median AAST grade of 4 [3-5], compared to those without 3 [2-3], p=0.001. Bland Altman analysis comparing AAST grade and cross sectional imaging demonstrated no difference; −0.02 ±0.02 p = 0.2 coefficient of repeatability 0.9. Conclusions The AAST grading system is valid in our population. Increased AAST grade is associated with open procedures, complications, and length of stay. AAST EGS grade determined by preoperative imaging strongly correlated to operative findings. PMID:27805996

HoloMonitor M4: holographic imaging cytometer for real-time kinetic label-free live-cell analysis of adherent cells

NASA Astrophysics Data System (ADS)

Sebesta, Mikael; Egelberg, Peter J.; Langberg, Anders; Lindskov, Jens-Henrik; Alm, Kersti; Janicke, Birgit

2016-03-01

Live-cell imaging enables studying dynamic cellular processes that cannot be visualized in fixed-cell assays. An increasing number of scientists in academia and the pharmaceutical industry are choosing live-cell analysis over or in addition to traditional fixed-cell assays. We have developed a time-lapse label-free imaging cytometer HoloMonitorM4. HoloMonitor M4 assists researchers to overcome inherent disadvantages of fluorescent analysis, specifically effects of chemical labels or genetic modifications which can alter cellular behavior. Additionally, label-free analysis is simple and eliminates the costs associated with staining procedures. The underlying technology principle is based on digital off-axis holography. While multiple alternatives exist for this type of analysis, we prioritized our developments to achieve the following: a) All-inclusive system - hardware and sophisticated cytometric analysis software; b) Ease of use enabling utilization of instrumentation by expert- and entrylevel researchers alike; c) Validated quantitative assay end-points tracked over time such as optical path length shift, optical volume and multiple derived imaging parameters; d) Reliable digital autofocus; e) Robust long-term operation in the incubator environment; f) High throughput and walk-away capability; and finally g) Data management suitable for single- and multi-user networks. We provide examples of HoloMonitor applications of label-free cell viability measurements and monitoring of cell cycle phase distribution.

Periapical and endodontic status scale based on periapical bone lesions and endodontic treatment quality evaluation using cone-beam computed tomography.

PubMed

Venskutonis, Tadas; Plotino, Gianluca; Tocci, Luigi; Gambarini, Gianluca; Maminskas, Julius; Juodzbalys, Gintaras

2015-02-01

The purpose of this study was to present a new periapical and endodontic status scale (PESS) that is based on the complex periapical index (COPI), which was designed for the identification and classification of periapical bone lesions in cases of apical periodontitis, and the endodontically treated tooth index, which was designed for endodontic treatment quality evaluation by means of cone-beam computed tomographic (CBCT) analysis. Periapical and endodontic status parameters were selected from the already known indexes and scientific literature for radiologic evaluation. Radiographic images (CBCT imaging, digital orthopantomography [DOR], and digital periapical radiography) from 55 patients were analyzed. All parameters were evaluated on CBCT, DOR, and digital periapical radiographic images by 2 external observers. The statistical analysis was performed with software SPSS version 19.0 (SPSS Inc, Chicago, IL). Chi-square tests were used to compare frequencies of qualitative variables. The level of significance was set at P ≤ .05. Overall intraobserver and interobserver agreements were very good and good, respectively. CBCT analysis found more lesions and lesions of bigger dimension (P < .001). CBCT imaging was also superior in locating lesions in the apical part on the side compared with DOR and in the diagnosis of cortical bone destruction compared with both methods (P < .001). Through CBCT analysis, more root canals and more canals associated with lesions were found. The most informative and reproducible periapical and endodontic status parameters were selected, and a new PESS was proposed. The classification proposed in the present study seems to be reproducible and objective and adds helpful information with respect to the existing indexes. Future studies need to be conducted to validate PESS. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Lifestyle Factors and Visible Skin Aging in a Population of Japanese Elders

PubMed Central

Asakura, Keiko; Nishiwaki, Yuji; Milojevic, Ai; Michikawa, Takehiro; Kikuchi, Yuriko; Nakano, Makiko; Iwasawa, Satoko; Hillebrand, Greg; Miyamoto, Kukizo; Ono, Masaji; Kinjo, Yoshihide; Akiba, Suminori; Takebayashi, Toru

2009-01-01

Background The number of studies that use objective and quantitative methods to evaluate facial skin aging in elderly people is extremely limited, especially in Japan. Therefore, in this cross-sectional study we attempted to characterize the condition of facial skin (hyperpigmentation, pores, texture, and wrinkling) in Japanese adults aged 65 years or older by using objective and quantitative imaging methods. In addition, we aimed to identify lifestyle factors significantly associated with these visible signs of aging. Methods The study subjects were 802 community-dwelling Japanese men and women aged at least 65 years and living in the town of Kurabuchi (Takasaki City, Gunma Prefecture, Japan), a mountain community with a population of approximately 4800. The facial skin condition of subjects was assessed quantitatively using a standardized facial imaging system and subsequent computer image analysis. Lifestyle information was collected using a structured questionnaire. The association between skin condition and lifestyle factors was examined using multivariable regression analysis. Results Among women, the mean values for facial texture, hyperpigmentation, and pores were generally lower than those among age-matched men. There was no significant difference between sexes in the severity of facial wrinkling. Older age was associated with worse skin condition among women only. After adjusting for age, smoking status and topical sun protection were significantly associated with skin condition among both men and women. Conclusions Our study revealed significant differences between sexes in the severity of hyperpigmentation, texture, and pores, but not wrinkling. Smoking status and topical sun protection were significantly associated with signs of visible skin aging in this study population. PMID:19700917

Bodies in nature: Associations between exposure to nature, connectedness to nature, and body image in U.S. adults.

PubMed

Swami, Viren; Barron, David; Weis, Laura; Furnham, Adrian

2016-09-01

Here, we sought to replicate previous work showing a relationship between connectedness to nature and body appreciation, and extend it by examining associations between exposure to natural environments and other body image-related variables. An online sample of 399 U.S. women and men (Mage=34.55 years) completed measures of body appreciation, connectedness to nature, nature exposure, appearance investment, sociocultural attitudes towards appearance, and self-esteem. Path analysis showed that nature exposure and connectedness to nature, respectively, were associated with body appreciation in women and men, both directly and indirectly via self-esteem. Connectedness to nature also mediated the link between nature exposure and body appreciation. In men, but not women, the link between connectedness to nature and body appreciation was also mediated by appearance investment and internalisation of a muscular ideal. These results may point to novel methods for promoting more positive body image in adults through engagement with nature. Copyright © 2016 Elsevier Ltd. All rights reserved.

Perceived and Ideal Body Image in Young Women in South Western Saudi Arabia.

PubMed

Khalaf, Atika; Westergren, Albert; Berggren, Vanja; Ekblom, Örjan; Al-Hazzaa, Hazzaa M

2015-01-01

The aim of this study was to investigate perceived and ideal body image (BI) and associated factors among female university students in Saudi Arabia. This cross-sectional study included 663 university female students. Anthropometric measurements including weight, height, BMI, and BI perception (the 9-figure silhouette) were obtained. Descriptive and logistic regression analysis were conducted. An agreement between actual, perceived, and ideal BI was found in 23% of the participants. Behavioral (activity levels), social (presence of obese parents and fathers' level of education), and economic factors (households' monthly income, number of cars in the household, and kind of residence) were positively and significantly associated with the desire to be thinner. Similarly, socioeconomic associations (number of sisters and number of cars in the household) correlated positively and significantly with the desire to be heavier. The whole family should rather be considered in interventions related to appearance concerns and BI discrepancies. Furthermore, campaigns targeting improvement of adolescents' physical self-image should be a major priority of the public health sector.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Real Time Intelligent Target Detection and Analysis with Machine Vision

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Padgett, Curtis; Brown, Kenneth

2000-01-01

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

Regional tau deposition and subregion atrophy of medial temporal structures in early Alzheimer's disease: A combined positron emission tomography/magnetic resonance imaging study.

PubMed

Sone, Daichi; Imabayashi, Etsuko; Maikusa, Norihide; Okamura, Nobuyuki; Furumoto, Shozo; Kudo, Yukitsuka; Ogawa, Masayo; Takano, Harumasa; Yokoi, Yuma; Sakata, Masuhiro; Tsukamoto, Tadashi; Kato, Koichi; Matsuda, Hiroshi

2017-01-01

Molecular imaging and selective hippocampal subfield atrophy are a focus of recent Alzheimer's disease (AD) research. Here, we investigated correlations between molecular imaging and hippocampal subfields in early AD. We investigated 18 patients with early AD and 18 healthy control subjects using 11 C-Pittsburgh compound-B (PIB) positron emission tomography (PET) and 18 F-THK5351 PET and automatic segmentation of hippocampal subfields with high-resolution T2-weighted magnetic resonance imaging. The PET images were normalized and underwent voxelwise regression analysis with each subregion volumes using SPM12. As for 18 F-THK5351 PET, the bilateral perirhinal cortex volumes were significantly associated with the ipsilateral or bilateral temporal lobar uptakes, whereas hippocampal subfields showed no correlations. 11 C-PIB PET showed relatively broad negative correlation with the right cornu ammonis 3 volumes. Regional tau deposition was correlated with extrahippocampal subregional atrophy and not with hippocampal subfields, possibly reflecting different underlying mechanisms of atrophy in early AD. Amyloid might be associated with right cornu ammonis 3 atrophy.

Low Back Imaging When Not Indicated: A Descriptive Cross-System Analysis.

PubMed

Gold, Rachel; Esterberg, Elizabeth; Hollombe, Celine; Arkind, Jill; Vakarcs, Patricia A; Tran, Huong; Burdick, Tim; Devoe, Jennifer E; Horberg, Michael A

2016-01-01

Guideline-discordant imaging to evaluate incident low back pain is common. We compared rates of guideline-discordant imaging in patients with low back pain in two care delivery systems with differing abilities to track care through an electronic health record (EHR), and in their patients' insurance status, to measure the association between these factors and rates of ordered low back imaging. We used data from two Kaiser Permanente (KP) Regions and from OCHIN, a community health center network. We extracted data on imaging performed after index visits for low back pain from June 1, 2011, to May 31, 2012, in these systems. Adjusted logistic regression measured associations between system-level factors and imaging rates. Imaging rates for incident low back pain using 2 national quality metrics: Clinical Quality Measure 0052, a measure for assessing Meaningful Use of EHRs, and the Healthcare Effectiveness Data and Information Set measure "Use of Imaging Studies for Low Back Pain." Among 19,503 KP patients and 2694 OCHIN patients with incident low back pain, ordered imaging was higher among men and whites but did not differ across health care systems. OCHIN's publicly insured patients had higher rates of imaging compared with those with private or no insurance. Rates of ordered imaging to evaluate incident low back pain among uninsured OCHIN patients were lower than in KP overall; among insured OCHIN patients, rates were higher than in KP overall. Research is needed to establish causality and develop interventions.

Prostate Specific Membrane Antigen Positron Emission Tomography May Improve the Diagnostic Accuracy of Multiparametric Magnetic Resonance Imaging in Localized Prostate Cancer.

PubMed

Rhee, H; Thomas, P; Shepherd, B; Gustafson, S; Vela, I; Russell, P J; Nelson, C; Chung, E; Wood, G; Malone, G; Wood, S; Heathcote, P

2016-10-01

Positron emission tomography using ligands targeting prostate specific membrane antigen has recently been introduced. Positron emission tomography imaging with (68)Ga-PSMA-HBED-CC has been shown to detect metastatic prostate cancer lesions at a high rate. In this study we compare multiparametric magnetic resonance imaging and prostate specific membrane antigen positron emission tomography of the prostate with whole mount ex vivo prostate histopathology to determine the true sensitivity and specificity of these imaging modalities for detecting and locating tumor foci within the prostate. In a prospective clinical trial setting 20 patients with localized prostate cancer and a planned radical prostatectomy were recruited. All patients underwent multiparametric magnetic resonance imaging and positron emission tomography before surgery, and whole mount histopathology slides were directly compared to the images. European Society of Urogenital Radiology guidelines for reporting magnetic resonance imaging were used as a template for regional units of analysis. The uropathologist and radiologists were blinded to individual components of the study, and the final correlation was performed by visual and deformable registration analysis. A total of 50 clinically significant lesions were identified from the whole mount histopathological analysis. Based on regional analysis the sensitivity, specificity, positive predictive value and negative predictive value for multiparametric magnetic resonance imaging were 44%, 94%, 81% and 76%, respectively. With prostate specific membrane antigen positron emission tomography the sensitivity, specificity, positive predictive value and negative predictive value were 49%, 95%, 85% and 88%, respectively. Prostate specific membrane antigen positron emission tomography yielded a higher specificity and positive predictive value. A significant proportion of cancers are potentially missed and underestimated by both imaging modalities. Prostate specific membrane antigen positron emission tomography may be used in addition to multiparametric magnetic resonance imaging to help improve local staging in those patients undergoing retropubic radical prostatectomy. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

SU-E-J-06: A Time Dependence Analysis of CBCT Image Quality and Mechanical Stability.

PubMed

Oves, S; Stenbeck, J; Gebreamlak, W; Alkhatib, H

2012-06-01

To quantify the change, if any, in flexmap correction factors and image quality with the XVI system over a course of several years and from these results, assess their clinical impact. Flexmap, a calibration procedure which corrects for imperfect gantry rotation for cone-beam CT reconstruction, and image quality tests were performed on three Elekta Synergy linacs equipped with XVI. Data was collected per month over three years. U and V values, corresponding to lateral and longitudinal shifts respectively, were acquired through the XVI software. Image quality parameters were obtained through CT imaging of the Catphan 500®. For each reconstruction, pixel values for low density polyethylene (LDPE) and polystyrene materials were recorded. For all three linacs, analysis of the flexmap showed a significant change in the U factor for both month-to-month comparisons and comparisons between machines. The V correction factor exhibited a small variation month to month, and showed a slight, gradual increase over time (0.2 +/-0.08 mm). Image quality analysis showed a near consistent decrease (5-10%) in LDPE and polystyrene. Despite this decrease in pixel values, the ratio of the two pixel values remained constant, thus a similar decreasing trend in contrast was not observed. Analysis of monthly flexmap calibration showed the general monthly change in correction shifts and their general trend over several years. For image quality, our research exhibited roughly 0.5% per month decrease in pixel values of the Catphan®. Our results imply that CBCT images obtained from XVI are not appropriate for treatment planning and despite the decrease in panel response over time, image quality with respect to contrast will remain within acceptable clinical standards. Future studies may be carried out to assess any correlation between image quality and XVI source strength. © 2012 American Association of Physicists in Medicine.

Association between Embolic Stroke Patterns, ESUS Etiology, and New Diagnosis of Atrial Fibrillation: A Secondary Data Analysis of the Find-AF Trial

PubMed Central

Schregel, Katharina; Karch, André; Weber-Krueger, Mark; Stahrenberg, Raoul; Gröschel, Klaus; Knauth, Michael; Psychogios, Marios-Nikos; Wachter, Rolf; Liman, Jan

2017-01-01

Background. Atrial fibrillation (AF) is an important cause of embolic stroke of undetermined source (ESUS). Imaging-patterns like multiple infarcts, simultaneous involvement of different circulations, infarcts of different ages, and isolated cortical infarcts are likely to indicate cardioembolic stroke. The aim of our study was to evaluate the association between embolic stroke patterns, ESUS, and the new diagnosis of AF. Methods. Stroke etiology and imaging characteristics from patients included in the Find-AF study were obtained. Embolic stroke patterns in CT- or MR-imaging were correlated with the diagnosis of ESUS as well as the short- (on baseline ECG and during 7-day Holter) and long-term (12-month follow-up) diagnosis of AF. Results. From 281 patients included in the Find-AF study, 127 (45.2%) patients with ischemic lesions detected in CT or MRI were included. 26 (20.5%) of these patients had ESUS. At least one embolic stroke pattern was detected in 67 (52.7%) patients. Embolic stroke patterns were not associated with ESUS (OR 1.57, 0.65–3.79, p = 0.317), the short-term (OR 0.64, 0.26–1.58, p = 0.327) or long-term diagnosis of AF (OR 0.72, 0.31–1.68, p = 0.448). Conclusions. This secondary data analysis of the Find-AF study could not provide evidence for an association between embolic stroke patterns, ESUS, and the new diagnosis of AF. PMID:28536667

Association between Embolic Stroke Patterns, ESUS Etiology, and New Diagnosis of Atrial Fibrillation: A Secondary Data Analysis of the Find-AF Trial.

PubMed

Maier, Ilko L; Schregel, Katharina; Karch, André; Weber-Krueger, Mark; Mikolajczyk, Rafael T; Stahrenberg, Raoul; Gröschel, Klaus; Bähr, Mathias; Knauth, Michael; Psychogios, Marios-Nikos; Wachter, Rolf; Liman, Jan

2017-01-01

Background . Atrial fibrillation (AF) is an important cause of embolic stroke of undetermined source (ESUS). Imaging-patterns like multiple infarcts, simultaneous involvement of different circulations, infarcts of different ages, and isolated cortical infarcts are likely to indicate cardioembolic stroke. The aim of our study was to evaluate the association between embolic stroke patterns, ESUS, and the new diagnosis of AF. Methods . Stroke etiology and imaging characteristics from patients included in the Find-AF study were obtained. Embolic stroke patterns in CT- or MR-imaging were correlated with the diagnosis of ESUS as well as the short- (on baseline ECG and during 7-day Holter) and long-term (12-month follow-up) diagnosis of AF. Results . From 281 patients included in the Find-AF study, 127 (45.2%) patients with ischemic lesions detected in CT or MRI were included. 26 (20.5%) of these patients had ESUS. At least one embolic stroke pattern was detected in 67 (52.7%) patients. Embolic stroke patterns were not associated with ESUS (OR 1.57, 0.65-3.79, p = 0.317), the short-term (OR 0.64, 0.26-1.58, p = 0.327) or long-term diagnosis of AF (OR 0.72, 0.31-1.68, p = 0.448). Conclusions . This secondary data analysis of the Find-AF study could not provide evidence for an association between embolic stroke patterns, ESUS, and the new diagnosis of AF.

Investigation of magnetic resonance imaging texture analysis as an aid tool for characterization of refractory epilepsies.

PubMed

Baldissin, Maurício Martins; Souza, Edna Marina de

2013-12-01

Refractory epilepsies are syndromes for which therapies that employ two or more antiepileptic drugs, separately or in association, do not result in control of crisis. Patients may present focal cortical dysplasia or diffuse dysplasia and/or hippocampal atrophic alterations that may not be detectable by a simple visual analysis in magnetic resonance imaging. The aim of this study was to evaluate MRI texture in regions of interest located in the hippocampi, limbic association cortex and prefrontal cortex of 20 patients with refractory epilepsy and to compare them with the same areas in 20 healthy individuals, in order to find out if the texture parameters could be related to the presence of the disease. Of the 11 texture parameters calculated, three indicated the existence of statistically significant differences between the studied groups. Such findings suggest the possibility of this technique contributing to studies of refractory epilepsies.

Saphenous vein graft near-infrared spectroscopy imaging insights from the lipid core plaque association with clinical events near-infrared spectroscopy (ORACLE-NIRS) registry.

PubMed

Danek, Barbara A; Karatasakis, Aris; Alame, Aya J; Nguyen-Trong, Phuong-Khanh J; Karacsonyi, Judit; Rangan, Bavana; Roesle, Michele; Atwell, Amy; Resendes, Erica; Martinez-Parachini, Jose Roberto; Iwnetu, Rahel; Kalsaria, Pratik; Siddiqui, Furqan; Muller, James E; Banerjee, Subhash; Brilakis, Emmanouil

2017-05-01

We sought to examine near-infrared spectroscopy (NIRS) imaging findings of aortocoronary saphenous vein grafts (SVGs). SVGs are prone to develop atherosclerosis similar to native coronary arteries. They have received little study using NIRS. We examined the clinical characteristics and imaging findings from 43 patients who underwent NIRS imaging of 45 SVGs at our institution between 2009 and 2016. The mean patient age was 67 ± 7 years and 98% were men, with high prevalence of diabetes mellitus (56%), hypertension (95%), and dyslipidemia (95%). Mean SVG age was 7 ± 7 years, mean SVG lipid core burden index (LCBI) was 53 ± 60 and mean maxLCBI 4 mm was 194 ± 234. Twelve SVGs (27%) had lipid core plaques (2 yellow blocks on the block chemogram), with a higher prevalence in SVGs older than 5 years (46% vs. 5%, P = 0.002). Older SVG age was associated with higher LCBI (r = 0.480, P < 0.001) and higher maxLCBI 4 mm (r = 0.567, P < 0.001). On univariate analysis, greater annual total cholesterol exposure was associated with higher SVG LCBI (r = 0.30, P = 0.042) and annual LDL-cholesterol and triglyceride exposure were associated with higher SVG maxLCBI 4 mm (LDL-C: r = 0.41, P = 0.020; triglycerides: r = 0.36, P = 0.043). On multivariate analysis, the only independent predictor of SVG LCBI and maxLCBI 4mm was SVG age. SVG percutaneous coronary intervention was performed in 63% of the patients. An embolic protection device was used in 96% of SVG PCIs. Periprocedural myocardial infarction occurred in one patient. Older SVG age and greater lipid exposure are associated with higher SVG lipid burden. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

PubMed

Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method frequently correspond to subregions of visible spots that may represent post-translational modifications or co-migrating proteins that cannot be visually resolved from adjacent, more abundant proteins on the gel image. Thus, it is possible that this image-based approach may actually improve the realized resolution of the gel, revealing differentially expressed proteins that would not have even been detected as spots by modern spot-based analyses.

Clarifying the relationship between nonradiologists' financial interest in imaging and their utilization of imaging.

PubMed

Bhargavan, Mythreyi; Sunshine, Jonathan H; Hughes, Danny R

2011-11-01

Several limitations and deficiencies have been identified in existing studies of physician financial interest in imaging that show financial interest is associated with more imaging. We conducted extensive quantitative analysis of seven deficiencies that have been identified. Using Symmetry's Episode Grouper, we created episodes of care from all the 2004-2007 health care claims for a random 5% sample of Medicare fee-for-service beneficiaries. We compared utilization of imaging in nonhospital episodes having a nonradiologist physician who had a financial interest in imaging with utilization in episodes with no such physician. We studied 23 combinations of medical conditions with imaging modalities commonly used for these conditions. Across four different definitions of financial interest and the 23 combinations, the relative probability (risk ratio) of imaging was uniformly higher for episodes of physicians with a financial interest, predominantly at p < 0.001. The mean relative probability was 1.87. This mean was little affected by the definition of financial interest used or the definition of the physician deemed responsible for the imaging. Controlling for patient characteristics, illness severity, and physician specialty likewise had little effect. Physicians who had acquired a financial interest averaged a 49% increase in the odds of imaging relative to physicians who had not. Physicians with a financial interest in an imaging modality used other modalities more than did physicians without a financial interest in the index modality. The Deficit Reduction Act's 2007 payment reductions had little effect. A financial interest in imaging is associated with higher utilization, probably causally. Limiting nonradiologists' financial interest in imaging may be desirable.

Image watermarking capacity analysis based on Hopfield neural network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhang, Hongbin

2004-11-01

In watermarking schemes, watermarking can be viewed as a form of communication problems. Almost all of previous works on image watermarking capacity are based on information theory, using Shannon formula to calculate the capacity of watermarking. In this paper, we present a blind watermarking algorithm using Hopfield neural network, and analyze watermarking capacity based on neural network. In our watermarking algorithm, watermarking capacity is decided by attraction basin of associative memory.

Interictal scalp electroencephalography and intraoperative electrocorticography in magnetic resonance imaging-negative temporal lobe epilepsy surgery.

PubMed

Burkholder, David B; Sulc, Vlastimil; Hoffman, E Matthew; Cascino, Gregory D; Britton, Jeffrey W; So, Elson L; Marsh, W Richard; Meyer, Fredric B; Van Gompel, Jamie J; Giannini, Caterina; Wass, C Thomas; Watson, Robert E; Worrell, Gregory A

2014-06-01

Scalp electroencephalography (EEG) and intraoperative electrocorticography (ECoG) are routinely used in the evaluation of magnetic resonance imaging-negative temporal lobe epilepsy (TLE) undergoing standard anterior temporal lobectomy with amygdalohippocampectomy (ATL), but the utility of interictal epileptiform discharge (IED) identification and its role in outcome are poorly defined. To determine whether the following are associated with surgical outcomes in patients with magnetic resonance imaging-negative TLE who underwent standard ATL: (1) unilateral-only IEDs on preoperative scalp EEG; (2) complete resection of tissue generating IEDs on ECoG; (3) complete resection of opioid-induced IEDs recorded on ECoG; and (4) location of IEDs recorded on ECoG. Data were gathered through retrospective medical record review at a tertiary referral center. Adult and pediatric patients with TLE who underwent standard ATL between January 1, 1990, and October 15, 2010, were considered for inclusion. Inclusion criteria were magnetic resonance imaging-negative TLE, standard ECoG performed at the time of surgery, and a minimum follow-up of 12 months. Univariate analysis was performed using log-rank time-to-event analysis. Variables reaching significance with log-rank testing were further analyzed using Cox proportional hazards. Excellent or nonexcellent outcome at time of last follow-up. An excellent outcome was defined as Engel class I and a nonexcellent outcome as Engel classes II through IV. Eighty-seven patients met inclusion criteria, with 48 (55%) achieving an excellent outcome following ATL. Unilateral IEDs on scalp EEG (P = .001) and complete resection of brain regions generating IEDs on baseline intraoperative ECoG (P = .02) were associated with excellent outcomes in univariate analysis. Both were associated with excellent outcomes when analyzed with Cox proportional hazards (unilateral-only IEDs, relative risk = 0.31 [95% CI, 0.16-0.64]; complete resection of IEDs on baseline ECoG, relative risk = 0.39 [95% CI, 0.20-0.76]). Overall, 25 of 35 patients (71%) with both unilateral-only IEDs and complete resection of baseline ECoG IEDs had an excellent outcome. Unilateral-only IEDs on preoperative scalp EEG and complete resection of IEDs on baseline ECoG are associated with better outcomes following standard ATL in magnetic resonance imaging-negative TLE. Prospective evaluation is needed to clarify the use of ECoG in tailoring temporal lobectomy.

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

Altered functional MR imaging language activation in elderly individuals with cerebral leukoaraiosis.

PubMed

Welker, Kirk M; De Jesus, Reordan O; Watson, Robert E; Machulda, Mary M; Jack, Clifford R

2012-10-01

To test the hypothesis that leukoaraiosis alters functional activation during a semantic decision language task. With institutional review board approval and written informed consent, 18 right-handed, cognitively healthy elderly participants with an aggregate leukoaraiosis lesion volume of more than 25 cm(3) and 18 age-matched control participants with less than 5 cm(3) of leukoaraiosis underwent functional MR imaging to allow comparison of activation during semantic decisions with that during visual perceptual decisions. Brain statistical maps were derived from the general linear model. Spatially normalized group t maps were created from individual contrast images. A cluster extent threshold of 215 voxels was used to correct for multiple comparisons. Intergroup random effects analysis was performed. Language laterality indexes were calculated for each participant. In control participants, semantic decisions activated the bilateral visual cortex, left posteroinferior temporal lobe, left posterior cingulate gyrus, left frontal lobe expressive language regions, and left basal ganglia. Visual perceptual decisions activated the right parietal and posterior temporal lobes. Participants with leukoaraiosis showed reduced activation in all regions associated with semantic decisions; however, activation associated with visual perceptual decisions increased in extent. Intergroup analysis showed significant activation decreases in the left anterior occipital lobe (P=.016), right posterior temporal lobe (P=.048), and right basal ganglia (P=.009) in particpants with leukoariosis. Individual participant laterality indexes showed a strong trend (P=.059) toward greater left lateralization in the leukoaraiosis group. Moderate leukoaraiosis is associated with atypical functional activation during semantic decision tasks. Consequently, leukoaraiosis is an important confounding variable in functional MR imaging studies of elderly individuals. © RSNA, 2012.

Unpacking religious affiliation: Exploring associations between Christian children's religious cultural context, God image, and self-esteem across development.

PubMed

Smith, Erin I; Crosby, Robert G

2017-03-01

In developmental research, religiousness is typically measured with omnibus affiliation or attendance variables that underspecify how the religious cultural contexts and experiences that affiliation represents influence developmental outcomes. This study explores associations between five aspects of a religious cultural context (family religiosity, religious schooling, church-based relationships with peers and adults, and view of God) in 844 seven- to 12-year-old Christian children to examine how they differentially predict self-esteem. Results of a structural equation model (SEM) analysis indicated that God image and peer church relationships directly predicted self-esteem, whereas God image mediated the influence of adult church relationships and family religious practices on self-esteem. A multiple group SEM analysis met the criterion for weak, but not strong, evidence that self-esteem is more related to younger children's adult church relationships but older children's peer church relationships. God image tended to be more related to younger children's family religious practices but older children's adult church relationships. Implications for developmental researchers and practitioners are discussed. Statement of contribution What is already known on this subject? Religious affiliation is an omnibus variable representing multiple contexts of development. Self-esteem is an important outcome variable with different influences across development. Religious affiliation is associated with increased self-esteem. What does this study add? Children's experience in the contexts of religious affiliation influences development differently. It is not just affiliation, but specific religious contexts that influence children's self-esteem. The role of religious contexts in shaping children's self-esteem shifts across development. © 2016 The British Psychological Society.

Functional mapping of language networks in the normal brain using a word-association task.

PubMed

Ghosh, Shantanu; Basu, Amrita; Kumaran, Senthil S; Khushu, Subash

2010-08-01

Language functions are known to be affected in diverse neurological conditions, including ischemic stroke, traumatic brain injury, and brain tumors. Because language networks are extensive, interpretation of functional data depends on the task completed during evaluation. The aim was to map the hemodynamic consequences of word association using functional magnetic resonance imaging (fMRI) in normal human subjects. Ten healthy subjects underwent fMRI scanning with a postlexical access semantic association task vs lexical processing task. The fMRI protocol involved a T2*-weighted gradient-echo echo-planar imaging (GE-EPI) sequence (TR 4523 ms, TE 64 ms, flip angle 90°) with alternate baseline and activation blocks. A total of 78 scans were taken (interscan interval = 3 s) with a total imaging time of 587 s. Functional data were processed in Statistical Parametric Mapping software (SPM2) with 8-mm Gaussian kernel by convolving the blood oxygenation level-dependent (BOLD) signal with an hemodynamic response function estimated by general linear method to generate SPM{t} and SPM{F} maps. Single subject analysis of the functional data (FWE-corrected, P≤0.001) revealed extensive activation in the frontal lobes, with overlaps among middle frontal gyrus (MFG), superior, and inferior frontal gyri. BOLD activity was also found in the medial frontal gyrus, middle occipital gyrus (MOG), anterior fusiform gyrus, superior and inferior parietal lobules, and to a smaller extent, the thalamus and right anterior cerebellum. Group analysis (FWE-corrected, P≤0.001) revealed neural recruitment of bilateral lingual gyri, left MFG, bilateral MOG, left superior occipital gyrus, left fusiform gyrus, bilateral thalami, and right cerebellar areas. Group data analysis revealed a cerebellar-occipital-fusiform-thalamic network centered around bilateral lingual gyri for word association, thereby indicating how these areas facilitate language comprehension by activating a semantic association network of words processed postlexical access. This finding is important when assessing the extent of cognitive damage and/or recovery and can be used for presurgical planning after optimization.

Mathematical imaging methods for mitosis analysis in live-cell phase contrast microscopy.

PubMed

Grah, Joana Sarah; Harrington, Jennifer Alison; Koh, Siang Boon; Pike, Jeremy Andrew; Schreiner, Alexander; Burger, Martin; Schönlieb, Carola-Bibiane; Reichelt, Stefanie

2017-02-15

In this paper we propose a workflow to detect and track mitotic cells in time-lapse microscopy image sequences. In order to avoid the requirement for cell lines expressing fluorescent markers and the associated phototoxicity, phase contrast microscopy is often preferred over fluorescence microscopy in live-cell imaging. However, common specific image characteristics complicate image processing and impede use of standard methods. Nevertheless, automated analysis is desirable due to manual analysis being subjective, biased and extremely time-consuming for large data sets. Here, we present the following workflow based on mathematical imaging methods. In the first step, mitosis detection is performed by means of the circular Hough transform. The obtained circular contour subsequently serves as an initialisation for the tracking algorithm based on variational methods. It is sub-divided into two parts: in order to determine the beginning of the whole mitosis cycle, a backwards tracking procedure is performed. After that, the cell is tracked forwards in time until the end of mitosis. As a result, the average of mitosis duration and ratios of different cell fates (cell death, no division, division into two or more daughter cells) can be measured and statistics on cell morphologies can be obtained. All of the tools are featured in the user-friendly MATLAB®Graphical User Interface MitosisAnalyser. Copyright © 2017. Published by Elsevier Inc.

Semi-automatic measuring of arteriovenous relation as a possible silent brain infarction risk index in hypertensive patients.

PubMed

Vázquez Dorrego, X M; Manresa Domínguez, J M; Heras Tebar, A; Forés, R; Girona Marcé, A; Alzamora Sas, M T; Delgado Martínez, P; Riba-Llena, I; Ugarte Anduaga, J; Beristain Iraola, A; Barandiaran Martirena, I; Ruiz Bilbao, S M; Torán Monserrat, P

2016-11-01

To evaluate the usefulness of a semiautomatic measuring system of arteriovenous relation (RAV) from retinographic images of hypertensive patients in assessing their cardiovascular risk and silent brain ischemia (ICS) detection. Semi-automatic measurement of arterial and venous width were performed with the aid of Imedos software and conventional fundus examination from the analysis of retinal images belonging to the 976 patients integrated in the cohort Investigating Silent Strokes in Hypertensives: a magnetic resonance imaging study (ISSYS), group of hypertensive patients. All patients have been subjected to a cranial magnetic resonance imaging (RMN) to assess the presence or absence of brain silent infarct. Retinal images of 768 patients were studied. Among the clinical findings observed, association with ICS was only detected in patients with microaneurysms (OR 2.50; 95% CI: 1.05-5.98) or altered RAV (<0.666) (OR: 4.22; 95% CI: 2.56-6.96). In multivariate logistic regression analysis adjusted by age and sex, only altered RAV continued demonstrating as a risk factor (OR: 3.70; 95% CI: 2.21-6.18). The results show that the semiautomatic analysis of the retinal vasculature from retinal images has the potential to be considered as an important vascular risk factor in hypertensive population. Copyright © 2016 Sociedad Española de Oftalmología. Publicado por Elsevier España, S.L.U. All rights reserved.

HTML5 PivotViewer: high-throughput visualization and querying of image data on the web

PubMed Central

Taylor, Stephen; Noble, Roger

2014-01-01

Motivation: Visualization and analysis of large numbers of biological images has generated a bottle neck in research. We present HTML5 PivotViewer, a novel, open source, platform-independent viewer making use of the latest web technologies that allows seamless access to images and associated metadata for each image. This provides a powerful method to allow end users to mine their data. Availability and implementation: Documentation, examples and links to the software are available from http://www.cbrg.ox.ac.uk/data/pivotviewer/. The software is licensed under GPLv2. Contact:  stephen.taylor@imm.ox.ac.uk and roger@coritsu.com PMID:24849578

Automated image quality assessment for chest CT scans.

PubMed

Reeves, Anthony P; Xie, Yiting; Liu, Shuang

2018-02-01

Medical image quality needs to be maintained at standards sufficient for effective clinical reading. Automated computer analytic methods may be applied to medical images for quality assessment. For chest CT scans in a lung cancer screening context, an automated quality assessment method is presented that characterizes image noise and image intensity calibration. This is achieved by image measurements in three automatically segmented homogeneous regions of the scan: external air, trachea lumen air, and descending aorta blood. Profiles of CT scanner behavior are also computed. The method has been evaluated on both phantom and real low-dose chest CT scans and results show that repeatable noise and calibration measures may be realized by automated computer algorithms. Noise and calibration profiles show relevant differences between different scanners and protocols. Automated image quality assessment may be useful for quality control for lung cancer screening and may enable performance improvements to automated computer analysis methods. © 2017 American Association of Physicists in Medicine.

Functional recognition imaging using artificial neural networks: applications to rapid cellular identification via broadband electromechanical response

NASA Astrophysics Data System (ADS)

Nikiforov, M. P.; Reukov, V. V.; Thompson, G. L.; Vertegel, A. A.; Guo, S.; Kalinin, S. V.; Jesse, S.

2009-10-01

Functional recognition imaging in scanning probe microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses at a single spatial location to identify the target behavior, which is reminiscent of associative thinking in the human brain, obviating the need for analytical models. We demonstrate, as an example of recognition imaging, rapid identification of cellular organisms using the difference in electromechanical activity over a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method.

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis

PubMed Central

Mayer, Christine; Windhager, Sonja; Schaefer, Katrin; Mitteroecker, Philipp

2017-01-01

Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI) and waist-to-hip ratio (WHR) with facial shape and texture (color pattern) in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3–10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception. PMID:28052103

Segmentation and Morphometric Analysis of Cells from Fluorescence Microscopy Images of Cytoskeletons

PubMed Central

Ujihara, Yoshihiro; Nakamura, Masanori; Miyazaki, Hiroshi; Wada, Shigeo

2013-01-01

We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures. PMID:23762186

Segmentation and morphometric analysis of cells from fluorescence microscopy images of cytoskeletons.

PubMed

Ujihara, Yoshihiro; Nakamura, Masanori; Miyazaki, Hiroshi; Wada, Shigeo

2013-01-01

We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures.

Lattice algebra approach to multispectral analysis of ancient documents.

PubMed

Valdiviezo-N, Juan C; Urcid, Gonzalo

2013-02-01

This paper introduces a lattice algebra procedure that can be used for the multispectral analysis of historical documents and artworks. Assuming the presence of linearly mixed spectral pixels captured in a multispectral scene, the proposed method computes the scaled min- and max-lattice associative memories to determine the purest pixels that best represent the spectra of single pigments. The estimation of fractional proportions of pure spectra at each image pixel is used to build pigment abundance maps that can be used for subsequent restoration of damaged parts. Application examples include multispectral images acquired from the Archimedes Palimpsest and a Mexican pre-Hispanic codex.

Probabilistic image modeling with an extended chain graph for human activity recognition and image segmentation.

PubMed

Zhang, Lei; Zeng, Zhi; Ji, Qiang

2011-09-01

Chain graph (CG) is a hybrid probabilistic graphical model (PGM) capable of modeling heterogeneous relationships among random variables. So far, however, its application in image and video analysis is very limited due to lack of principled learning and inference methods for a CG of general topology. To overcome this limitation, we introduce methods to extend the conventional chain-like CG model to CG model with more general topology and the associated methods for learning and inference in such a general CG model. Specifically, we propose techniques to systematically construct a generally structured CG, to parameterize this model, to derive its joint probability distribution, to perform joint parameter learning, and to perform probabilistic inference in this model. To demonstrate the utility of such an extended CG, we apply it to two challenging image and video analysis problems: human activity recognition and image segmentation. The experimental results show improved performance of the extended CG model over the conventional directed or undirected PGMs. This study demonstrates the promise of the extended CG for effective modeling and inference of complex real-world problems.

Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome.

PubMed

O'Connor, James P B; Rose, Chris J; Waterton, John C; Carano, Richard A D; Parker, Geoff J M; Jackson, Alan

2015-01-15

Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care. ©2014 American Association for Cancer Research.

Quantification of Estrogen Receptor Expression in Normal Breast Tissue in Postmenopausal Women With Breast Cancer and Association With Tumor Subtypes.

PubMed

Gulbahce, H Evin; Blair, Cindy K; Sweeney, Carol; Salama, Mohamed E

2017-09-01

Estrogen exposure is important in the pathogenesis of breast cancer and is a contributing risk factor. In this study we quantified estrogen receptor (ER) alpha expression in normal breast epithelium (NBR) in women with breast cancer and correlated it with breast cancer subtypes. Tissue microarrays were constructed from 204 breast cancer patients for whom normal breast tissue away from tumor was available. Slides stained with ER were scanned and expression in normal terminal duct lobular epithelium was quantitated using computer-assisted image analysis. ER expression in normal terminal duct lobular epithelium of postmenopausal women with breast cancer was significantly associated with estrogen and triple (estrogen, progesterone receptors, and HER2) negative phenotypes. Also increased age at diagnosis was significantly associated with ER expression in NBR. ER positivity in normal epithelium did not vary by tumor size, lymph node status, tumor grade, or stage. On the basis of quantitative image analysis, we confirm that ER expression in NBR increases with age in women with breast cancer, and report for the first time, a significant association between ER expression in NBR with ER-negative and triple-negative cancers in postmenopausal women.

Quantitative characterization of brain β-amyloid using a joint PiB/FDG PET image histogram

NASA Astrophysics Data System (ADS)

Camp, Jon J.; Hanson, Dennis P.; Holmes, David R.; Kemp, Bradley J.; Senjem, Matthew L.; Murray, Melissa E.; Dickson, Dennis W.; Parisi, Joseph; Petersen, Ronald C.; Lowe, Val J.; Robb, Richard A.

2014-03-01

A complex analysis performed by spatial registration of PiB and MRI patient images in order to localize the PiB signal to specific cortical brain regions has been proven effective in identifying imaging characteristics associated with underlying Alzheimer's Disease (AD) and Lewy Body Disease (LBD) pathology. This paper presents an original method of image analysis and stratification of amyloid-related brain disease based on the global spatial correlation of PiB PET images with 18F-FDG PET images (without MR images) to categorize the PiB signal arising from the cortex. Rigid registration of PiB and 18F-FDG images is relatively straightforward, and in registration the 18F-FDG signal serves to identify the cortical region in which the PiB signal is relevant. Cortical grey matter demonstrates the highest levels of amyloid accumulation and therefore the greatest PiB signal related to amyloid pathology. The highest intensity voxels in the 18F-FDG image are attributed to the cortical grey matter. The correlation of the highest intensity PiB voxels with the highest 18F-FDG values indicates the presence of β-amyloid protein in the cortex in disease states, while correlation of the highest intensity PiB voxels with mid-range 18F-FDG values indicates only nonspecific binding in the white matter.

Clinical evaluation of JPEG2000 compression for digital mammography

NASA Astrophysics Data System (ADS)

Sung, Min-Mo; Kim, Hee-Joung; Kim, Eun-Kyung; Kwak, Jin-Young; Yoo, Jae-Kyung; Yoo, Hyung-Sik

2002-06-01

Medical images, such as computed radiography (CR), and digital mammographic images will require large storage facilities and long transmission times for picture archiving and communications system (PACS) implementation. American College of Radiology and National Equipment Manufacturers Association (ACR/NEMA) group is planning to adopt a JPEG2000 compression algorithm in digital imaging and communications in medicine (DICOM) standard to better utilize medical images. The purpose of the study was to evaluate the compression ratios of JPEG2000 for digital mammographic images using peak signal-to-noise ratio (PSNR), receiver operating characteristic (ROC) analysis, and the t-test. The traditional statistical quality measures such as PSNR, which is a commonly used measure for the evaluation of reconstructed images, measures how the reconstructed image differs from the original by making pixel-by-pixel comparisons. The ability to accurately discriminate diseased cases from normal cases is evaluated using ROC curve analysis. ROC curves can be used to compare the diagnostic performance of two or more reconstructed images. The t test can be also used to evaluate the subjective image quality of reconstructed images. The results of the t test suggested that the possible compression ratios using JPEG2000 for digital mammographic images may be as much as 15:1 without visual loss or with preserving significant medical information at a confidence level of 99%, although both PSNR and ROC analyses suggest as much as 80:1 compression ratio can be achieved without affecting clinical diagnostic performance.

High-Speed Tandem Mass Spectrometric in Situ Imaging by Nanospray Desorption Electrospray Ionization Mass Spectrometry

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

Lanekoff, Ingela T.; Burnum-Johnson, Kristin E.; Thomas, Mathew

Nanospray desorption electrospray ionization (nano-DESI) combined with tandem mass spectrometry (MS/MS), high-resolution mass analysis (m/m=17,500 at m/z 200), and rapid spectral acquisition enabled simultaneous imaging and identification of more than 300 molecules from 92 selected m/z windows (± 1 Da) with a spatial resolution of better than 150 um. Uterine sections of implantation sites on day 6 of pregnancy were analyzed in the ambient environment without any sample pre-treatment. MS/MS imaging was performed by scanning the sample under the nano-DESI probe at 10 um/s while acquiring higher-energy collision-induced dissociation (HCD) spectra for a targeted inclusion list of 92 m/z valuesmore » at a rate of ~6.3 spectra/s. Molecular ions and their corresponding fragments, separated using high-resolution mass analysis, were assigned based on accurate mass measurement. Using this approach, we were able to identify and image both abundant and low-abundance isobaric species within each m/z window. MS/MS analysis enabled efficient separation and identification of isobaric sodium and potassium adducts of phospholipids. Furthermore, we identified several metabolites associated with early pregnancy and obtained the first 2D images of these molecules.« less

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

PubMed

Attiyeh, Marc A; Chakraborty, Jayasree; Doussot, Alexandre; Langdon-Embry, Liana; Mainarich, Shiana; Gönen, Mithat; Balachandran, Vinod P; D'Angelica, Michael I; DeMatteo, Ronald P; Jarnagin, William R; Kingham, T Peter; Allen, Peter J; Simpson, Amber L; Do, Richard K

2018-04-01

Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

MRI texture analysis (MRTA) of T2-weighted images in Crohn's disease may provide information on histological and MRI disease activity in patients undergoing ileal resection.

PubMed

Makanyanga, Jesica; Ganeshan, Balaji; Rodriguez-Justo, Manuel; Bhatnagar, Gauraang; Groves, Ashley; Halligan, Steve; Miles, Ken; Taylor, Stuart A

2017-02-01

To associate MRI textural analysis (MRTA) with MRI and histological Crohn's disease (CD) activity. Sixteen patients (mean age 39.5 years, 9 male) undergoing MR enterography before ileal resection were retrospectively analysed. Thirty-six small (≤3 mm) ROIs were placed on T2-weighted images and location-matched histological acute inflammatory scores (AIS) measured. MRI activity (mural thickness, T2 signal, T1 enhancement) (CDA) was scored in large ROIs. MRTA features (mean, standard deviation, mean of positive pixels (MPP), entropy, kurtosis, skewness) were extracted using a filtration histogram technique. Spatial scale filtration (SSF) ranged from 2 to 5 mm. Regression (linear/logistic) tested associations between MRTA and AIS (small ROIs), and CDA/constituent parameters (large ROIs). Skewness (SSF = 2 mm) was associated with AIS [regression coefficient (rc) 4.27, p = 0.02]. Of 120 large ROI analyses (for each MRI, MRTA feature and SSF), 15 were significant. Entropy (SSF = 2, 3 mm) and kurtosis (SSF = 3 mm) were associated with CDA (rc 0.9, 1.0, -0.45, p = 0.006-0.01). Entropy and mean (SSF = 2-4 mm) were associated with T2 signal [odds ratio (OR) 2.32-3.16, p = 0.02-0.004], [OR 1.22-1.28, p = 0.03-0.04]. MPP (SSF = 2 mm) was associated with mural thickness (OR 0.91, p = 0.04). Kurtosis (SSF = 3 mm), standard deviation (SSF = 5 mm) were associated with decreased T1 enhancement (OR 0.59, 0.42, p = 0.004, 0.007). MRTA features may be associated with CD activity. • MR texture analysis features may be associated with Crohn's disease histological activity. • Texture analysis features may correlate with MR-dependent Crohn's disease activity scores. • The utility of MR texture analysis in Crohn's disease merits further investigation.

Scanning transmission electron microscopy methods for the analysis of nanoparticles.

PubMed

Ponce, Arturo; Mejía-Rosales, Sergio; José-Yacamán, Miguel

2012-01-01

Here we review the scanning transmission electron microscopy (STEM) characterization technique and STEM imaging methods. We describe applications of STEM for studying inorganic nanoparticles, and other uses of STEM in biological and health sciences and discuss how to interpret STEM results. The STEM imaging mode has certain benefits compared with the broad-beam illumination mode; the main advantage is the collection of the information about the specimen using a high angular annular dark field (HAADF) detector, in which the images registered have different levels of contrast related to the chemical composition of the sample. Another advantage of its use in the analysis of biological samples is its contrast for thick stained sections, since HAADF images of samples with thickness of 100-120 nm have notoriously better contrast than those obtained by other techniques. Combining the HAADF-STEM imaging with the new aberration correction era, the STEM technique reaches a direct way to imaging the atomistic structure and composition of nanostructures at a sub-angstrom resolution. Thus, alloying in metallic nanoparticles is directly resolved at atomic scale by the HAADF-STEM imaging, and the comparison of the STEM images with results from simulations gives a very powerful way of analysis of structure and composition. The use of X-ray energy dispersive spectroscopy attached to the electron microscope for STEM mode is also described. In issues where characterization at the atomic scale of the interaction between metallic nanoparticles and biological systems is needed, all the associated techniques to STEM become powerful tools for the best understanding on how to use these particles in biomedical applications.

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

Bradshaw, Tyler J.; Bowen, Stephen R.; Deveau, Michael A.

Purpose: Imaging biomarkers of resistance to radiation therapy can inform and guide treatment management. Most studies have so far focused on assessing a single imaging biomarker. The goal of this study was to explore a number of different molecular imaging biomarkers as surrogates of resistance to radiation therapy. Methods and Materials: Twenty-two canine patients with spontaneous sinonasal tumors were treated with accelerated hypofractionated radiation therapy, receiving either 10 fractions of 4.2 Gy each or 10 fractions of 5.0 Gy each to the gross tumor volume. Patients underwent fluorodeoxyglucose (FDG)-, fluorothymidine (FLT)-, and Cu(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM)-labeled positron emission tomography/computed tomography (PET/CT) imaging before therapymore » and FLT and Cu-ATSM PET/CT imaging during therapy. In addition to conventional maximum and mean standardized uptake values (SUV{sub max}; SUV{sub mean}) measurements, imaging metrics providing response and spatiotemporal information were extracted for each patient. Progression-free survival was assessed according to response evaluation criteria in solid tumor. The prognostic value of each imaging biomarker was evaluated using univariable Cox proportional hazards regression. Multivariable analysis was also performed but was restricted to 2 predictor variables due to the limited number of patients. The best bivariable model was selected according to pseudo-R{sup 2}. Results: The following variables were significantly associated with poor clinical outcome following radiation therapy according to univariable analysis: tumor volume (P=.011), midtreatment FLT SUV{sub mean} (P=.018), and midtreatment FLT SUV{sub max} (P=.006). Large decreases in FLT SUV{sub mean} from pretreatment to midtreatment were associated with worse clinical outcome (P=.013). In the bivariable model, the best 2-variable combination for predicting poor outcome was high midtreatment FLT SUV{sub max} (P=.022) in combination with large FLT response from pretreatment to midtreatment (P=.041). Conclusions: In addition to tumor volume, pronounced tumor proliferative response quantified using FLT PET, especially when associated with high residual FLT PET at midtreatment, is a negative prognostic biomarker of outcome in canine tumors following radiation therapy. Neither FDG PET nor Cu-ATSM PET were predictive of outcome.« less

Proceedings of the National Conference on Energy Resource Management. Volume 1: Techniques, Procedures and Data Bases

NASA Technical Reports Server (NTRS)

Brumfield, J. O. (Editor); Schiffman, Y. M. (Editor)

1982-01-01

Topics dealing with the integration of remotely sensed data with geographic information system for application in energy resources management are discussed. Associated remote sensing and image analysis techniques are also addressed.

The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation model.

PubMed

Mongkolwat, Pattanasak; Kleper, Vladimir; Talbot, Skip; Rubin, Daniel

2014-12-01

Knowledge contained within in vivo imaging annotated by human experts or computer programs is typically stored as unstructured text and separated from other associated information. The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation information model is an evolution of the National Institute of Health's (NIH) National Cancer Institute's (NCI) Cancer Bioinformatics Grid (caBIG®) AIM model. The model applies to various image types created by various techniques and disciplines. It has evolved in response to the feedback and changing demands from the imaging community at NCI. The foundation model serves as a base for other imaging disciplines that want to extend the type of information the model collects. The model captures physical entities and their characteristics, imaging observation entities and their characteristics, markups (two- and three-dimensional), AIM statements, calculations, image source, inferences, annotation role, task context or workflow, audit trail, AIM creator details, equipment used to create AIM instances, subject demographics, and adjudication observations. An AIM instance can be stored as a Digital Imaging and Communications in Medicine (DICOM) structured reporting (SR) object or Extensible Markup Language (XML) document for further processing and analysis. An AIM instance consists of one or more annotations and associated markups of a single finding along with other ancillary information in the AIM model. An annotation describes information about the meaning of pixel data in an image. A markup is a graphical drawing placed on the image that depicts a region of interest. This paper describes fundamental AIM concepts and how to use and extend AIM for various imaging disciplines.

Ashamed and Fused with Body Image and Eating: Binge Eating as an Avoidance Strategy.

PubMed

Duarte, Cristiana; Pinto-Gouveia, José; Ferreira, Cláudia

2017-01-01

Binge Eating Disorder (BED) is currently recognized as a severe disorder associated with relevant psychiatric and physical comorbidity, and marked emotional distress. Shame is a specific negative emotion that has been highlighted as central in eating disorders. However, the effect of shame and underlying mechanisms on binge eating symptomatology severity remained unclear. This study examines the role of shame, depressive symptoms, weight and shape concerns and eating concerns, and body image-related cognitive fusion, on binge eating symptomatology severity. Participated in this study 73 patients with the diagnosis of BED, established through a clinical interview-Eating Disorder Examination 17.0D-who completed measures of external shame, body-image related cognitive fusion, depressive symptoms and binge eating symptomatology. Results revealed positive associations between binge eating severity and depressive symptoms, shame, weight and shape concerns, eating concerns and body image-related cognitive fusion. A path analysis showed that, when controlling for the effect of depressive symptoms, external shame has a direct effect on binge eating severity, and an indirect effect mediated by increased eating concern and higher levels of body image-related cognitive fusion. Results confirmed the plausibility of the model, which explained 43% of the severity of binge eating symptoms. The proposed model suggests that, in BED patients, perceiving that others see the self negatively may be associated with an entanglement with body image-related thoughts and concerns about eating, which may, in turn, fuel binge eating symptoms. Findings have important clinical implications supporting the relevance of addressing shame and associated processes in binge eating. Copyright © 2015 John Wiley & Sons, Ltd. Shame is a significant predictor of symptomatology severity of BED patients. Shame significantly impacts binge eating, even controlling for depressive symptoms. Shame significantly predicts body image-related cognitive fusion and eating concern. Body image-fusion and eating concern mediate the link between shame and binge eating. Binge eating may be seen as an avoidance strategy from negative self-evaluations. Copyright © 2015 John Wiley & Sons, Ltd.

Free lipid and computerized determination of adipocyte size.

PubMed

Svensson, Henrik; Olausson, Daniel; Holmäng, Agneta; Jennische, Eva; Edén, Staffan; Lönn, Malin

2018-06-21

The size distribution of adipocytes in a suspension, after collagenase digestion of adipose tissue, can be determined by computerized image analysis. Free lipid, forming droplets, in such suspensions implicates a bias since droplets present in the images may be identified as adipocytes. This problem is not always adjusted for and some reports state that distinguishing droplets and cells is a considerable problem. In addition, if the droplets originate mainly from rupture of large adipocytes, as often described, this will also bias size analysis. We here confirm that our ordinary manual means of distinguishing droplets and adipocytes in the images ensure correct and rapid identification before exclusion of the droplets. Further, in our suspensions, prepared with focus on gentle handling of tissue and cells, we find no association between the amount of free lipid and mean adipocyte size or proportion of large adipocytes.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study.

PubMed

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-04-06

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10 -3 mm 2 /s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study

PubMed Central

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-01-01

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10−3mm2/s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction. PMID:29719621

Three-Year Prospective Cohort Study of Factors Associated with Return to Work After Breast Cancer Diagnosis.

PubMed

Lee, Myung Kyung; Kang, Han Sung; Lee, Keun Seok; Lee, Eun Sook

2017-12-01

Purpose The purpose of this prospective cohort study of breast cancer survivors was to identify factors before diagnosis, during treatment, and after treatment that are associated with return to work (RTW). Methods A total of 288 women with breast cancer (stage I-III) and whose age were 18-65 years-old answered questionnaires at 4-6, 12, 24, and 36 months after diagnosis. The surveys asked about performance of regular exercise and health-related quality of life issues. "RTW at 36 months" was assigned to patients who reported any of the following: working at least twice; no job at baseline but working more than once; job at baseline, stopped working, and then started working again; and working during all 3 years. Results We classified 107 of 288 of the women (37.1%) as having returned to work. Analysis of pre-diagnostic factors indicated that more education and practice of regular endurance exercise were positively associated with RTW. Analysis of factors during treatment indicated that appetite loss and fatigue were negatively associated with RTW. Analysis of factors at post-treatment indicated that better body image, better physical function, better existential well-being, and participation in regular endurance and resistance exercise were positively associated with RTW. Childbirth at 12-24 months was negatively associated with RTW. Conclusion Women who participate in exercise before, during, and after treatment for breast cancer are more likely to RTW. A woman's need to care for children, perceived body image, and existential well-being may also affect her RTW.

Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging.

PubMed

Sala, E; Mema, E; Himoto, Y; Veeraraghavan, H; Brenton, J D; Snyder, A; Weigelt, B; Vargas, H A

2017-01-01

Tumour heterogeneity in cancers has been observed at the histological and genetic levels, and increased levels of intra-tumour genetic heterogeneity have been reported to be associated with adverse clinical outcomes. This review provides an overview of radiomics, radiogenomics, and habitat imaging, and examines the use of these newly emergent fields in assessing tumour heterogeneity and its implications. It reviews the potential value of radiomics and radiogenomics in assisting in the diagnosis of cancer disease and determining cancer aggressiveness. This review discusses how radiogenomic analysis can be further used to guide treatment therapy for individual tumours by predicting drug response and potential therapy resistance and examines its role in developing radiomics as biomarkers of oncological outcomes. Lastly, it provides an overview of the obstacles in these emergent fields today including reproducibility, need for validation, imaging analysis standardisation, data sharing and clinical translatability and offers potential solutions to these challenges towards the realisation of precision oncology. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

MRI predictors of treatment response for perianal fistulizing Crohn disease in children and young adults.

PubMed

Shenoy-Bhangle, Anuradha; Nimkin, Katherine; Goldner, Dana; Bradley, William F; Israel, Esther J; Gee, Michael S

2014-01-01

Magnetic resonance imaging (MRI) is considered the imaging standard for diagnosis and characterization of perianal complications associated with Crohn disease in children and adults. To define MRI criteria that could act as potential predictors of treatment response in fistulizing Crohn disease in children, in order to guide more informed study interpretation. We performed a retrospective database query to identify all children and young adults with Crohn disease who underwent serial MRI studies for assessment of perianal symptoms between 2003 and 2010. We examined imaging features of perianal disease including fistula number, type and length, presence and size of associated abscess, and disease response/progression on follow-up MRI. We reviewed imaging studies and electronic medical records. Statistical analysis, including logistic regression, was performed to associate MR imaging features with treatment response and disease progression. We included 36 patients (22 male, 14 female; age range 8-21 years). Of these, 32 had a second MRI exam and 4 had clinical evidence of complete response, obviating the need for repeat imaging. Of the parameters analyzed, presence of abscess, type of fistula according to the Parks classification, and multiplicity were not predictors of treatment outcome. Maximum length of the dominant fistula and aggregate fistula length in the case of multiple fistulae were the best predictors of treatment outcome. Maximum fistula length <2.5 cm was a predictor of treatment response, while aggregate fistula length ≥2.5 cm was a predictor of disease progression. Perianal fistula length is an important imaging feature to assess on MRI of fistulizing Crohn disease.

Diagnostic value of history and physical examination in patients suspected of lumbosacral nerve root compression

PubMed Central

Vroomen, P; de Krom, M C T F M; Wilmink, J; Kester, A; Knottnerus, J

2002-01-01

Objective: To evaluate patient characteristics, symptoms, and examination findings in the clinical diagnosis of lumbosacral nerve root compression causing sciatica. Methods: The study involved 274 patients with pain radiating into the leg. All had a standardised clinical assessment and magnetic resonance (MR) imaging. The associations between patient characteristics, clinical findings, and lumbosacral nerve root compression on MR imaging were analysed. Results: Nerve root compression was associated with three patient characteristics, three symptoms, and four physical examination findings (paresis, absence of tendon reflexes, a positive straight leg raising test, and increased finger-floor distance). Multivariate analysis, analysing the independent diagnostic value of the tests, showed that nerve root compression was predicted by two patient characteristics, four symptoms, and two signs (increased finger-floor distance and paresis). The straight leg raise test was not predictive. The area under the curve of the receiver-operating characteristic was 0.80 for the history items. It increased to 0.83 when the physical examination items were added. Conclusions: Various clinical findings were found to be associated with nerve root compression on MR imaging. While this set of findings agrees well with those commonly used in daily practice, the tests tended to have lower sensitivity and specificity than previously reported. Stepwise multivariate analysis showed that most of the diagnostic information revealed by physical examination findings had already been revealed by the history items. PMID:11971050

A systematic review and meta-analysis of structural magnetic resonance imaging studies investigating cognitive and social activity levels in older adults.

PubMed

Anatürk, M; Demnitz, N; Ebmeier, K P; Sexton, C E

2018-06-22

Population aging has prompted considerable interest in identifying modifiable factors that may help protect the brain and its functions. Collectively, epidemiological studies show that leisure activities with high mental and social demands are linked with better cognition in old age. The extent to which socio-intellectual activities relate to the brain's structure is, however, not yet fully understood. This systematic review and meta-analysis summarizes magnetic resonance imaging studies that have investigated whether cognitive and social activities correlate with measures of gray and white matter volume, white matter microstructure and white matter lesions. Across eighteen included studies (total n = 8429), activity levels were associated with whole-brain white matter volume, white matter lesions and regional gray matter volume, although effect sizes were small. No associations were found for global gray matter volume and the evidence concerning white matter microstructure was inconclusive. While the causality of the reviewed associations needs to be established, our findings implicate socio-intellectual activity levels as promising targets for interventions aimed at promoting healthy brain aging. Copyright © 2018. Published by Elsevier Ltd.

Positron emission tomography-based evidence of low-amplitude respiratory motion in patients with chronic obstructive pulmonary disease.

PubMed

Daouk, Joël; Bailly, Pascal; Kamimura, Mitsuhiro; Sacksick, David; Jounieaux, Vincent; Meyer, Marc-Etienne

2015-05-01

Chronic obstructive pulmonary disease (COPD) is characterized by low vital capacity and tidal volume, which translate into smaller respiratory motions. We sought to demonstrate the limited respiratory motion in COPD by comparing respiratory-gated and free-breathing positron emission tomography (PET) images of lung nodules ("CT-based" and "Ungated" images) in patients with and without COPD. We studied 74 lung lesions (37 malignant) in 60 patients (23 patients with COPD; 37 without). An Ungated PET examination was followed by a CT-based acquisition. Maximum standard uptake value (SUVmax) for each lesion on PET images was measured. On CT images, we checked for the presence of emphysema and pleural adhesions or indentations associated with the nodules. Lastly, we used univariate and then multivariate analyses to determine the lung function parameters possibly affecting respiratory motion in patients with and without COPD. The mean "CT-based" vs. "Ungated" difference in SUVmax was 0.3 and 0.6 for patients with and without COPD, respectively. Statistical analysis revealed that lesion site, hyperinflation and pleural indentation were independently associated with a difference in SUVmax. PET lung lesion images in patients with COPD are barely influenced by respiratory motion. Thoracic hyperinflation in patients with COPD was found to be independently associated with an effect of respiratory motion on PET images. Moreover, pleural indentation limits the respiratory motion of lung nodules, regardless of the presence or absence of COPD.

Semi-Automated Digital Image Analysis of Pick’s Disease and TDP-43 Proteinopathy

PubMed Central

Irwin, David J.; Byrne, Matthew D.; McMillan, Corey T.; Cooper, Felicia; Arnold, Steven E.; Lee, Edward B.; Van Deerlin, Vivianna M.; Xie, Sharon X.; Lee, Virginia M.-Y.; Grossman, Murray; Trojanowski, John Q.

2015-01-01

Digital image analysis of histology sections provides reliable, high-throughput methods for neuropathological studies but data is scant in frontotemporal lobar degeneration (FTLD), which has an added challenge of study due to morphologically diverse pathologies. Here, we describe a novel method of semi-automated digital image analysis in FTLD subtypes including: Pick’s disease (PiD, n=11) with tau-positive intracellular inclusions and neuropil threads, and TDP-43 pathology type C (FTLD-TDPC, n=10), defined by TDP-43-positive aggregates predominantly in large dystrophic neurites. To do this, we examined three FTLD-associated cortical regions: mid-frontal gyrus (MFG), superior temporal gyrus (STG) and anterior cingulate gyrus (ACG) by immunohistochemistry. We used a color deconvolution process to isolate signal from the chromogen and applied both object detection and intensity thresholding algorithms to quantify pathological burden. We found object-detection algorithms had good agreement with gold-standard manual quantification of tau- and TDP-43-positive inclusions. Our sampling method was reliable across three separate investigators and we obtained similar results in a pilot analysis using open-source software. Regional comparisons using these algorithms finds differences in regional anatomic disease burden between PiD and FTLD-TDP not detected using traditional ordinal scale data, suggesting digital image analysis is a powerful tool for clinicopathological studies in morphologically diverse FTLD syndromes. PMID:26538548

Semi-Automated Digital Image Analysis of Pick's Disease and TDP-43 Proteinopathy.

PubMed

Irwin, David J; Byrne, Matthew D; McMillan, Corey T; Cooper, Felicia; Arnold, Steven E; Lee, Edward B; Van Deerlin, Vivianna M; Xie, Sharon X; Lee, Virginia M-Y; Grossman, Murray; Trojanowski, John Q

2016-01-01

Digital image analysis of histology sections provides reliable, high-throughput methods for neuropathological studies but data is scant in frontotemporal lobar degeneration (FTLD), which has an added challenge of study due to morphologically diverse pathologies. Here, we describe a novel method of semi-automated digital image analysis in FTLD subtypes including: Pick's disease (PiD, n=11) with tau-positive intracellular inclusions and neuropil threads, and TDP-43 pathology type C (FTLD-TDPC, n=10), defined by TDP-43-positive aggregates predominantly in large dystrophic neurites. To do this, we examined three FTLD-associated cortical regions: mid-frontal gyrus (MFG), superior temporal gyrus (STG) and anterior cingulate gyrus (ACG) by immunohistochemistry. We used a color deconvolution process to isolate signal from the chromogen and applied both object detection and intensity thresholding algorithms to quantify pathological burden. We found object-detection algorithms had good agreement with gold-standard manual quantification of tau- and TDP-43-positive inclusions. Our sampling method was reliable across three separate investigators and we obtained similar results in a pilot analysis using open-source software. Regional comparisons using these algorithms finds differences in regional anatomic disease burden between PiD and FTLD-TDP not detected using traditional ordinal scale data, suggesting digital image analysis is a powerful tool for clinicopathological studies in morphologically diverse FTLD syndromes. © The Author(s) 2015.

Image quality and radiation dose of brain computed tomography in children: effects of decreasing tube voltage from 120 kVp to 80 kVp.

PubMed

Park, Ji Eun; Choi, Young Hun; Cheon, Jung-Eun; Kim, Woo Sun; Kim, In-One; Cho, Hyun Suk; Ryu, Young Jin; Kim, Yu Jin

2017-05-01

Computed tomography (CT) has generated public concern associated with radiation exposure, especially for children. Lowering the tube voltage is one strategy to reduce radiation dose. To assess the image quality and radiation dose of non-enhanced brain CT scans acquired at 80 kilo-voltage peak (kVp) compared to those at 120 kVp in children. Thirty children who had undergone both 80- and 120-kVp non-enhanced brain CT were enrolled. For quantitative analysis, the mean attenuation of white and gray matter, attenuation difference, noise, signal-to-noise ratio, contrast-to-noise ratio and posterior fossa artifact index were measured. For qualitative analysis, noise, gray-white matter differentiation, artifact and overall image quality were scored. Radiation doses were evaluated by CT dose index, dose-length product and effective dose. The mean attenuations of gray and white matter and contrast-to-noise ratio were significantly increased at 80 kVp, while parameters related to image noise, i.e. noise, signal-to-noise ratio and posterior fossa artifact index were higher at 80 kVp than at 120 kVp. In qualitative analysis, 80-kVp images showed improved gray-white differentiation but more artifacts compared to 120-kVp images. Subjective image noise and overall image quality scores were similar between the two scans. Radiation dose parameters were significantly lower at 80 kVp than at 120 kVp. In pediatric non-enhanced brain CT scans, a decrease in tube voltage from 120 kVp to 80 kVp resulted in improved gray-white matter contrast, comparable image quality and decreased radiation dose.

Body image concerns during pregnancy are associated with a shorter breast feeding duration.

PubMed

Brown, Amy; Rance, J; Warren, L

2015-01-01

breast feeding is affected by numerous psycho-social factors. Antenatal concerns such as embarrassment regarding public feeding and the impact of breast feeding upon breast shape are known to lead to artificial milk use. However, although work has explored the relationship between maternal weight and infant feeding, wider body image concerns have not been examined. The aim of the current study was to explore the association between maternal body image concerns during pregnancy upon intended and actual breast feeding duration. a two stage self report questionnaire completed during pregnancy and at six months post partum. mothers were recruited from local mother and infant groups, nurseries and online mother and infant forums. 128 pregnant women completed both stages. phase one: completion of a questionnaire exploring body image during pregnancy (concerns about stretch marks, weight gain and appearance) and planned breast feeding duration during the second/third trimester of pregnancy (body image, weight, intended duration) followed by a second questionnaire measuring actual breast feeding duration and breast feeding experiences. factor analysis revealed three primary body image concerns: pregnancy body image, prospective postnatal body image and dieting during pregnancy. Higher concerns on all three factors were associated with both intended and actual shorter breast feeding duration. Amongst mothers who stopped breast feeding before six months, those with higher body image concerns were more likely to report stopping due to embarrassment or the perceived impact upon their breast shape. The relationship was not explained by maternal weight, although a higher residual weight gain at six months was associated with a shorter breast feeding duration. mothers who are affected negatively by changes to their body during pregnancy may be less likely to plan to or initiate breast feeding potentially due to underlying issues such as embarrassment or perceived impact of feeding upon their appearance. The findings are important to those working with women during pregnancy and the postpartum period in understanding the impact of body image upon intention and ability to initiate and continue breast feeding. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of an image analysis system to monitor the retention of residual cytoplasm by human spermatozoa: correlation with biochemical markers of the cytoplasmic space, oxidative stress, and sperm function.

PubMed

Gomez, E; Buckingham, D W; Brindle, J; Lanzafame, F; Irvine, D S; Aitken, R J

1996-01-01

A method has been developed for quantifying the residual cytoplasm present in the midpiece of human spermatozoa, based upon the imaging of NADH oxidoreductase activity. This procedure used NADH and nitroblue tetrazolium as electron donor and acceptor, respectively, and resulted in the discrete staining of the entire midpiece area, including the residual cytoplasm. Image analysis techniques were then used to generate binary images of the midpiece, from which objective measurements of this cellular domain could be undertaken. Such data were found to be highly correlated with biochemical markers of the cytoplasmic space, such as creatine kinase (CK) and glucose-6-phosphate dehydrogenase (G-6-PDH), in sperm populations depleted of detectable leukocyte contamination. Morphometric analysis of the sperm midpiece was also found to reflect semen quality in that it predicted the proportion of the ejaculate that would be recovered from the high-density region of Percoll gradients and was negatively correlated with the movement and morphology of the spermatozoa in semen. Variation in the retention of excess residual cytoplasm was also associated with differences in the functional competence of washed sperm preparations, both within and between ejaculates. Thus, within-ejaculate comparisons of high- and low-density sperm subpopulations revealed a relative disruption of sperm function in the low-density fraction. This disruption was associated with the presence of excess residual cytoplasm in the midpiece, high concentrations of cytoplasmic enzymes, and the enhanced-generation reactive oxygen species (ROS). Functional differences between individual high-density Percoll preparations were also negatively correlated with the area of the midpiece and the corresponding capacity of the spermatozoa to generate ROS. These findings suggest that one of the factors involved in the etiology of defective sperm function is the incomplete extrusion of germ cell cytoplasm during spermiogenesis as a consequence of which the spermatozoa experience a loss of function associated with the induction of oxidative stress.

IMAGEP - A FORTRAN ALGORITHM FOR DIGITAL IMAGE PROCESSING

NASA Technical Reports Server (NTRS)

Roth, D. J.

1994-01-01

IMAGEP is a FORTRAN computer algorithm containing various image processing, analysis, and enhancement functions. It is a keyboard-driven program organized into nine subroutines. Within the subroutines are other routines, also, selected via keyboard. Some of the functions performed by IMAGEP include digitization, storage and retrieval of images; image enhancement by contrast expansion, addition and subtraction, magnification, inversion, and bit shifting; display and movement of cursor; display of grey level histogram of image; and display of the variation of grey level intensity as a function of image position. This algorithm has possible scientific, industrial, and biomedical applications in material flaw studies, steel and ore analysis, and pathology, respectively. IMAGEP is written in VAX FORTRAN for DEC VAX series computers running VMS. The program requires the use of a Grinnell 274 image processor which can be obtained from Mark McCloud Associates, Campbell, CA. An object library of the required GMR series software is included on the distribution media. IMAGEP requires 1Mb of RAM for execution. The standard distribution medium for this program is a 1600 BPI 9track magnetic tape in VAX FILES-11 format. It is also available on a TK50 tape cartridge in VAX FILES-11 format. This program was developed in 1991. DEC, VAX, VMS, and TK50 are trademarks of Digital Equipment Corporation.

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

Open source software projects of the caBIG In Vivo Imaging Workspace Software special interest group.

PubMed

Prior, Fred W; Erickson, Bradley J; Tarbox, Lawrence

2007-11-01

The Cancer Bioinformatics Grid (caBIG) program was created by the National Cancer Institute to facilitate sharing of IT infrastructure, data, and applications among the National Cancer Institute-sponsored cancer research centers. The program was launched in February 2004 and now links more than 50 cancer centers. In April 2005, the In Vivo Imaging Workspace was added to promote the use of imaging in cancer clinical trials. At the inaugural meeting, four special interest groups (SIGs) were established. The Software SIG was charged with identifying projects that focus on open-source software for image visualization and analysis. To date, two projects have been defined by the Software SIG. The eXtensible Imaging Platform project has produced a rapid application development environment that researchers may use to create targeted workflows customized for specific research projects. The Algorithm Validation Tools project will provide a set of tools and data structures that will be used to capture measurement information and associated needed to allow a gold standard to be defined for the given database against which change analysis algorithms can be tested. Through these and future efforts, the caBIG In Vivo Imaging Workspace Software SIG endeavors to advance imaging informatics and provide new open-source software tools to advance cancer research.

Image fusion of Secondary Ion Mass Spectrometry and Energy-dispersive X-Ray Spectroscopy data for the characterization of uranium-molybdenum fuel foils

NASA Astrophysics Data System (ADS)

Willingham, David; Naes, Benjamin E.; Tarolli, Jay G.; Schemer-Kohrn, Alan; Rhodes, Mark; Dahl, Michael; Guzman, Anthony; Burkes, Douglas E.

2018-01-01

Uranium-molybdenum (U-Mo) monolithic fuels represent one option for converting civilian research and test reactors operating with high enriched uranium (HEU) to low enriched uranium (LEU), effectively reducing the threat of nuclear proliferation world-wide. However, processes associated with fabrication of U-Mo monolithic fuels result in regions of elemental heterogeneity, observed as bands traversing the cross-section of representative samples. Isotopic variations (e.g., 235U and 238U) could also be introduced because of associated processing steps, particularly since HEU feedstock is melted with natural or depleted uranium diluent to produce LEU. This study demonstrates the utility of correlative analysis of Energy-Dispersive X-ray Spectroscopy (EDS) and Secondary Ion Mass Spectrometry (SIMS) with their image data streams using image fusion, resulting in a comprehensive microanalytical characterization toolbox. Elemental and isotopic measurements were made on a sample from the Advanced Test Reactor (ATR) Full-sized plate In-center flux trap Position (AFIP)-7 experiment and compared to previous optical and electron microscopy results. The image fusion results are characteristic of SIMS isotopic maps, but with the spatial resolution of EDS images and, therefore, can be used to increase the effective spatial resolution of the SIMS imaging results to better understand homogeneity or heterogeneity that persists because of processing selections. Visual inspection using the image fusion methodology indicated slight variations in the 235U/238U ratio and quantitative analysis using the image intensities across several FoVs revealed an average 235U atom percent value of 17.9 ± 2.4%, which was indicative of a non-uniform U isotopic distribution in the area sampled. Further development of this capability is useful for understanding the connections between the properties of LEU fuel alternatives and the ability to predict performance under irradiation.

Accuracy for detection of simulated lesions: comparison of fluid-attenuated inversion-recovery, proton density--weighted, and T2-weighted synthetic brain MR imaging

NASA Technical Reports Server (NTRS)

Herskovits, E. H.; Itoh, R.; Melhem, E. R.

2001-01-01

OBJECTIVE: The objective of our study was to determine the effects of MR sequence (fluid-attenuated inversion-recovery [FLAIR], proton density--weighted, and T2-weighted) and of lesion location on sensitivity and specificity of lesion detection. MATERIALS AND METHODS: We generated FLAIR, proton density-weighted, and T2-weighted brain images with 3-mm lesions using published parameters for acute multiple sclerosis plaques. Each image contained from zero to five lesions that were distributed among cortical-subcortical, periventricular, and deep white matter regions; on either side; and anterior or posterior in position. We presented images of 540 lesions, distributed among 2592 image regions, to six neuroradiologists. We constructed a contingency table for image regions with lesions and another for image regions without lesions (normal). Each table included the following: the reviewer's number (1--6); the MR sequence; the side, position, and region of the lesion; and the reviewer's response (lesion present or absent [normal]). We performed chi-square and log-linear analyses. RESULTS: The FLAIR sequence yielded the highest true-positive rates (p < 0.001) and the highest true-negative rates (p < 0.001). Regions also differed in reviewers' true-positive rates (p < 0.001) and true-negative rates (p = 0.002). The true-positive rate model generated by log-linear analysis contained an additional sequence-location interaction. The true-negative rate model generated by log-linear analysis confirmed these associations, but no higher order interactions were added. CONCLUSION: We developed software with which we can generate brain images of a wide range of pulse sequences and that allows us to specify the location, size, shape, and intrinsic characteristics of simulated lesions. We found that the use of FLAIR sequences increases detection accuracy for cortical-subcortical and periventricular lesions over that associated with proton density- and T2-weighted sequences.

Changes in landscape patterns and associated forest succession on the western slope of the Rocky Mountains, Colorado

Treesearch

Daniel J. Manier; Richard D. Laven

2001-01-01

Using repeat photography, we conducted a qualitative and quantitative analysis of changes in forest cover on the western slope of the Rocky Mountains in Colorado. For the quantitative analysis, both images in a pair were classified using remote sensing and geographic information system (GIS) technologies. Comparisons were made using three landscape metrics: total...

Quantitative imaging of protein targets in the human brain with PET

NASA Astrophysics Data System (ADS)

Gunn, Roger N.; Slifstein, Mark; Searle, Graham E.; Price, Julie C.

2015-11-01

PET imaging of proteins in the human brain with high affinity radiolabelled molecules has a history stretching back over 30 years. During this period the portfolio of protein targets that can be imaged has increased significantly through successes in radioligand discovery and development. This portfolio now spans six major categories of proteins; G-protein coupled receptors, membrane transporters, ligand gated ion channels, enzymes, misfolded proteins and tryptophan-rich sensory proteins. In parallel to these achievements in radiochemical sciences there have also been significant advances in the quantitative analysis and interpretation of the imaging data including the development of methods for image registration, image segmentation, tracer compartmental modeling, reference tissue kinetic analysis and partial volume correction. In this review, we analyze the activity of the field around each of the protein targets in order to give a perspective on the historical focus and the possible future trajectory of the field. The important neurobiology and pharmacology is introduced for each of the six protein classes and we present established radioligands for each that have successfully transitioned to quantitative imaging in humans. We present a standard quantitative analysis workflow for these radioligands which takes the dynamic PET data, associated blood and anatomical MRI data as the inputs to a series of image processing and bio-mathematical modeling steps before outputting the outcome measure of interest on either a regional or parametric image basis. The quantitative outcome measures are then used in a range of different imaging studies including tracer discovery and development studies, cross sectional studies, classification studies, intervention studies and longitudinal studies. Finally we consider some of the confounds, challenges and subtleties that arise in practice when trying to quantify and interpret PET neuroimaging data including motion artifacts, partial volume effects, age effects, image registration and normalization, input functions and metabolites, parametric imaging, receptor internalization and genetic factors.

Scanning fluorescent microthermal imaging apparatus and method

DOEpatents

Barton, Daniel L.; Tangyunyong, Paiboon

1998-01-01

A scanning fluorescent microthermal imaging (FMI) apparatus and method is disclosed, useful for integrated circuit (IC) failure analysis, that uses a scanned and focused beam from a laser to excite a thin fluorescent film disposed over the surface of the IC. By collecting fluorescent radiation from the film, and performing point-by-point data collection with a single-point photodetector, a thermal map of the IC is formed to measure any localized heating associated with defects in the IC.

Predictors of seizure freedom after surgery for malformations of cortical development.

PubMed

Chang, Edward F; Wang, Doris D; Barkovich, A James; Tihan, Tarik; Auguste, Kurtis I; Sullivan, Joseph E; Garcia, Paul A; Barbaro, Nicholas M

2011-07-01

Malformations of cortical development (MCDs) are a major cause of medically refractory epilepsy. Our aim was to examine a surgical series of patients with cortical malformations to determine the prognostic factors associated with long-term seizure control. We conducted a retrospective review of 143 patients with MCD who underwent resective surgery for medically refractory epilepsy. Demographic, imaging, histopathologic, and surgical variables were analyzed for potential association with seizure freedom. Preoperative magnetic resonance imaging (MRI) was evaluated in a blind fashion and classified according to a new imaging/embryologic MCD classification system. Gray-white blurring on MRI, smaller lesions, complete resection of structural lesions, complete resection of abnormal electrocorticographic areas, and locally confined electrocorticographic abnormalities are favorable prognosticators of seizure freedom on univariate analysis. Imaging features consistent with abnormal proliferation (Barkovich class I) were associated with better outcome compared to those related to abnormal neuronal migration (class II) or abnormal cortical organization (class III). Multivariate logistic regression revealed complete resection of tissue manifesting electrocorticographic and/or MRI anatomic abnormalities as the main independent predictor of seizure freedom. Other histopathologic or demographic factors were not associated with seizure control. Long-term follow-up of patients demonstrated sustained overall rates of seizure control (72% at 2 years, 65% at 5 years, and 67% at 10 years). Surgery for MCDs can result in high rates of seizure freedom. Complete resection of electrocorticographic and anatomic abnormalities appears to be most predictive of long-term seizure control. Copyright © 2011 American Neurological Association.

Should I Stop or Should I Go? The Role of Associations and Expectancies

PubMed Central

2015-01-01

Following exposure to consistent stimulus–stop mappings, response inhibition can become automatized with practice. What is learned is less clear, even though this has important theoretical and practical implications. A recent analysis indicates that stimuli can become associated with a stop signal or with a stop goal. Furthermore, expectancy may play an important role. Previous studies that have used stop or no-go signals to manipulate stimulus–stop learning cannot distinguish between stimulus-signal and stimulus-goal associations, and expectancy has not been measured properly. In the present study, participants performed a task that combined features of the go/no-go task and the stop-signal task in which the stop-signal rule changed at the beginning of each block. The go and stop signals were superimposed over 40 task-irrelevant images. Our results show that participants can learn direct associations between images and the stop goal without mediation via the stop signal. Exposure to the image-stop associations influenced task performance during training, and expectancies measured following task completion or measured within the task. But, despite this, we found an effect of stimulus–stop learning on test performance only when the task increased the task-relevance of the images. This could indicate that the influence of stimulus–stop learning on go performance is strongly influenced by attention to both task-relevant and task-irrelevant stimulus features. More generally, our findings suggest a strong interplay between automatic and controlled processes. PMID:26322688

Analysis of southwest propagating TIDs in the western United States

NASA Astrophysics Data System (ADS)

Kendall, E. A.; Bhatt, A.

2016-12-01

The MANGO network of 630 nm all-sky imagers in the continental United States has observed a number of westward propagating traveling ionospheric disturbances (TIDs). These TIDs include southwestward waves typically associated with Perkins electrodynamic instability, and also northwestward waves of unknown cause. A peak in the wave activity was observed during the summer of 2016 in the western US. Many of the observed structures evolve during their passage through the camera field of view. The southwestward propagating TIDs observed over California are often tilted westward or slightly northward, which may be a function of magnetic field declination. We will present analysis of MANGO network data along with GPS TEC data. This analysis will include shapes and sizes of the observed structures along with their velocities. We will present results from geomagnetic, seasonal and local time variations associated with observed TIDs. Wherever possible, we will include data from the broader MANGO network that is now taking data over the continental United States and compare with data from Boston University imagers in Massachusetts and Texas.

The variability of software scoring of the CDMAM phantom associated with a limited number of images

NASA Astrophysics Data System (ADS)

Yang, Chang-Ying J.; Van Metter, Richard

2007-03-01

Software scoring approaches provide an attractive alternative to human evaluation of CDMAM images from digital mammography systems, particularly for annual quality control testing as recommended by the European Protocol for the Quality Control of the Physical and Technical Aspects of Mammography Screening (EPQCM). Methods for correlating CDCOM-based results with human observer performance have been proposed. A common feature of all methods is the use of a small number (at most eight) of CDMAM images to evaluate the system. This study focuses on the potential variability in the estimated system performance that is associated with these methods. Sets of 36 CDMAM images were acquired under carefully controlled conditions from three different digital mammography systems. The threshold visibility thickness (TVT) for each disk diameter was determined using previously reported post-analysis methods from the CDCOM scorings for a randomly selected group of eight images for one measurement trial. This random selection process was repeated 3000 times to estimate the variability in the resulting TVT values for each disk diameter. The results from using different post-analysis methods, different random selection strategies and different digital systems were compared. Additional variability of the 0.1 mm disk diameter was explored by comparing the results from two different image data sets acquired under the same conditions from the same system. The magnitude and the type of error estimated for experimental data was explained through modeling. The modeled results also suggest a limitation in the current phantom design for the 0.1 mm diameter disks. Through modeling, it was also found that, because of the binomial statistic nature of the CDMAM test, the true variability of the test could be underestimated by the commonly used method of random re-sampling.

View synthesis using parallax invariance

NASA Astrophysics Data System (ADS)

Dornaika, Fadi

2001-06-01

View synthesis becomes a focus of attention of both the computer vision and computer graphics communities. It consists of creating novel images of a scene as it would appear from novel viewpoints. View synthesis can be used in a wide variety of applications such as video compression, graphics generation, virtual reality and entertainment. This paper addresses the following problem. Given a dense disparity map between two reference images, we would like to synthesize a novel view of the same scene associated with a novel viewpoint. Most of the existing work is relying on building a set of 3D meshes which are then projected onto the new image (the rendering process is performed using texture mapping). The advantages of our view synthesis approach are as follows. First, the novel view is specified by a rotation and a translation which are the most natural way to express the virtual location of the camera. Second, the approach is able to synthesize highly realistic images whose viewing position is significantly far away from the reference viewpoints. Third, the approach is able to handle the visibility problem during the synthesis process. Our developed framework has two main steps. The first step (analysis step) consists of computing the homography at infinity, the epipoles, and thus the parallax field associated with the reference images. The second step (synthesis step) consists of warping the reference image into a new one, which is based on the invariance of the computed parallax field. The analysis step is working directly on the reference views, and only need to be performed once. Examples of synthesizing novel views using either feature correspondences or dense disparity map have demonstrated the feasibility of the proposed approach.

The challenge of cerebral magnetic resonance imaging in neonates: A new method using mathematical morphology for the segmentation of structures including diffuse excessive high signal intensities.

PubMed

Xu, Yongchao; Morel, Baptiste; Dahdouh, Sonia; Puybareau, Élodie; Virzì, Alessio; Urien, Héléne; Géraud, Thierry; Adamsbaum, Catherine; Bloch, Isabelle

2018-05-17

Preterm birth is a multifactorial condition associated with increased morbidity and mortality. Diffuse excessive high signal intensity (DEHSI) has been recently described on T2-weighted MR sequences in this population and thought to be associated with neuropathologies. To date, no robust and reproducible method to assess the presence of white matter hyperintensities has been developed, perhaps explaining the current controversy over their prognostic value. The aim of this paper is to propose a new semi-automated framework to detect DEHSI on neonatal brain MR images having a particular pattern due to the physiological lack of complete myelination of the white matter. A novel method for semi- automatic segmentation of neonatal brain structures and DEHSI, based on mathematical morphology and on max-tree representations of the images is thus described. It is a mandatory first step to identify and clinically assess homogeneous cohorts of neonates for DEHSI and/or volume of any other segmented structures. Implemented in a user-friendly interface, the method makes it straightforward to select relevant markers of structures to be segmented, and if needed, apply eventually manual corrections. This method responds to the increasing need for providing medical experts with semi-automatic tools for image analysis, and overcomes the limitations of visual analysis alone, prone to subjectivity and variability. Experimental results demonstrate that the method is accurate, with excellent reproducibility and with very few manual corrections needed. Although the method was intended initially for images acquired at 1.5T, which corresponds to the usual clinical practice, preliminary results on images acquired at 3T suggest that the proposed approach can be generalized. Copyright © 2018 Elsevier B.V. All rights reserved.

The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis.

PubMed

Debette, Stéphanie; Markus, H S

2010-07-26

To review the evidence for an association of white matter hyperintensities with risk of stroke, cognitive decline, dementia, and death. Systematic review and meta-analysis. PubMed from 1966 to 23 November 2009. Prospective longitudinal studies that used magnetic resonance imaging and assessed the impact of white matter hyperintensities on risk of incident stroke, cognitive decline, dementia, and death, and, for the meta-analysis, studies that provided risk estimates for a categorical measure of white matter hyperintensities, assessing the impact of these lesions on risk of stroke, dementia, and death. Population studied, duration of follow-up, method used to measure white matter hyperintensities, definition of the outcome, and measure of the association of white matter hyperintensities with the outcome. 46 longitudinal studies evaluated the association of white matter hyperintensities with risk of stroke (n=12), cognitive decline (n=19), dementia (n=17), and death (n=10). 22 studies could be included in a meta-analysis (nine of stroke, nine of dementia, eight of death). White matter hyperintensities were associated with an increased risk of stroke (hazard ratio 3.3, 95% confidence interval 2.6 to 4.4), dementia (1.9, 1.3 to 2.8), and death (2.0, 1.6 to 2.7). An association of white matter hyperintensities with a faster decline in global cognitive performance, executive function, and processing speed was also suggested. White matter hyperintensities predict an increased risk of stroke, dementia, and death. Therefore white matter hyperintensities indicate an increased risk of cerebrovascular events when identified as part of diagnostic investigations, and support their use as an intermediate marker in a research setting. Their discovery should prompt detailed screening for risk factors of stroke and dementia.

Classification of pulmonary airway disease based on mucosal color analysis

NASA Astrophysics Data System (ADS)

Suter, Melissa; Reinhardt, Joseph M.; Riker, David; Ferguson, John Scott; McLennan, Geoffrey

2005-04-01

Airway mucosal color changes occur in response to the development of bronchial diseases including lung cancer, cystic fibrosis, chronic bronchitis, emphysema and asthma. These associated changes are often visualized using standard macro-optical bronchoscopy techniques. A limitation to this form of assessment is that the subtle changes that indicate early stages in disease development may often be missed as a result of this highly subjective assessment, especially in inexperienced bronchoscopists. Tri-chromatic CCD chip bronchoscopes allow for digital color analysis of the pulmonary airway mucosa. This form of analysis may facilitate a greater understanding of airway disease response. A 2-step image classification approach is employed: the first step is to distinguish between healthy and diseased bronchoscope images and the second is to classify the detected abnormal images into 1 of 4 possible disease categories. A database of airway mucosal color constructed from healthy human volunteers is used as a standard against which statistical comparisons are made from mucosa with known apparent airway abnormalities. This approach demonstrates great promise as an effective detection and diagnosis tool to highlight potentially abnormal airway mucosa identifying a region possibly suited to further analysis via airway forceps biopsy, or newly developed micro-optical biopsy strategies. Following the identification of abnormal airway images a neural network is used to distinguish between the different disease classes. We have shown that classification of potentially diseased airway mucosa is possible through comparative color analysis of digital bronchoscope images. The combination of the two strategies appears to increase the classification accuracy in addition to greatly decreasing the computational time.

Schizophrenia symptomatic associations with diffusion tensor imaging measured fractional anisotropy of brain: a meta-analysis.

PubMed

Yang, Xu; Cao, Ding; Liang, Xiumei; Zhao, Jiannong

2017-07-01

Several studies have examined the relationships between diffusion tensor imaging (DTI)-measured fractional anisotropy (FA) and the symptoms of schizophrenia, but results vary across the studies. The aim of this study was to carry out a meta-analysis of correlation coefficients reported by relevant studies to evaluate the correlative relationships between FA of various parts of the brain and schizophrenia symptomatic assessments. Literature was searched in several electronic databases, and study selection was based on précised eligibility criteria. Correlation coefficients between FA of a part of the brain and schizophrenia symptom were first converted into Fisher's z-scores for meta-analyses, and then overall effect sizes were back transformed to correlation coefficients. Thirty-three studies (1121 schizophrenia patients; age 32.66 years [95% confidence interval (CI) 30.19, 35.13]; 65.95 % [57.63, 74.28] males) were included in this meta-analysis. Age was inversely associated with brain FA (z-scores [95% CI] -0.23 [-0.14, -0.32]; p ˂ 0.00001). Brain FA of various areas was inversely associated with negative symptoms of schizophrenia (z-score -0.30 [-0.23, -0.36]; p ˂ 0.00001) but was positively associated with positive symptoms of schizophrenia (z-score 0.16 [0.04, 0.27]; p = 0.007) and general psychopathology of schizophrenia (z-score 0.26 [0.15, 0.37]; p = 0.00001). Although, DTI-measured brain FA is found to be inversely associated with negative symptoms and positively associated with positive symptoms and general psychopathology of schizophrenia, the effect sizes of these correlations are low and may not be clinically significant. Moreover, brain FA was also negatively associated with age of patients.

Challenges in contrast-enhanced spectral mammography interpretation: artefacts lexicon.

PubMed

Yagil, Y; Shalmon, A; Rundstein, A; Servadio, Y; Halshtok, O; Gotlieb, M; Sklair-Levy, M

2016-05-01

To review and describe commonly encountered artefacts in contrast-enhanced spectral mammography (CESM). This retrospective study included 200 women who underwent CESM examinations for screening and diagnostic purposes. Analysis was performed on the image data sets of these women, comprising of a total of 774 subtracted images. Images were reviewed with focus on the presence of four artefacts: rim ("breast within breast"), ripple (black and white lines), axillary line, and skin-line enhancement (skin-line highlighting). Statistical cross-correlation and association with acquisition parameters (tube current, tube voltage, compression force, breast thickness, paddle size) was compared using Fisher's exact test and t-test. The rim artefact was highly common (97-99%) in every projection. The ripple artefact was increasingly more common on the oblique projections (80-82%) and found to be associated with higher breast thickness values. The axillary line artefact was detected only on oblique projections (63%) and associated with the use of a small compression paddle. The skin-line enhancement artefact was seen in 19-46% of projections. None of the artefacts interfered with image interpretation. Two main artefacts commonly seen on CESM are rim and ripple artefacts. They do not hamper with image interpretation. It is important to be aware of them and prevent misinterpretation of these artefacts as real breast pathology. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Imaging manifestations of autoimmune disease-associated lymphoproliferative disorders of the lung.

PubMed

Lee, Geewon; Lee, Ho Yun; Lee, Kyung Soo; Lee, Kyung Jong; Cha, Hoon-Suk; Han, Joungho; Chung, Man Pyo

2013-10-01

Lymphoproliferative disorders (LPDs) may involve intrathoracic organs in patients with autoimmune disease, but little is known about the radiologic manifestations of autoimmune disease-associated LPDs (ALPDs) of the lungs. The purpose of our work was to identify the radiologic characteristics of pulmonary involvement in ALPDs. A comprehensive search for PubMed database was conducted with the combination of MeSH words. All articles which had original images or description on radiologic findings were included in this analysis. Also, CT images of eight patients with biopsy-proven lymphoproliferative disorder observed from our institution were added. Overall, 44 cases of ALPD were identified, and consisted of 24 cases of bronchus-associated lymphoid tissue lymphoma (BALToma), eight cases of non-Hodgkin's lymphoma (NHL), six cases of lymphoid interstitial pneumonia (LIP), two cases of nodular lymphoid hyperplasia, two cases of unclassified lymphoproliferative disorder, and one case each of lymphomatoid granulomatosis and hyperblastic BALT. Multiple nodules (n = 14, 32 %) and single mass (n = 8, 18 %) were the predominant radiologic manifestations. The imaging findings conformed to previously described findings of BALToma, NHL, or LIP. Data suggest that BALToma, NHL, and LIP are the predominant ALPDs of the lung, and ALPD generally shared common radiologic features with sporadic LPDs. Familiarity with ALPDs and their imaging findings may enable radiologists or clinicians to include the disease as a potential differential diagnosis and thus, to prompt early biopsy followed by appropriate treatment.

Subcutaneous Fascial Bands—A Qualitative and Morphometric Analysis

PubMed Central

Li, Weihui; Ahn, Andrew C.

2011-01-01

Background Although fascial bands within the subcutaneous (SQ) layer are commonly seen in ultrasound images, little is known about their functional role, much less their structural characteristics. This study's objective is to describe the morphological features of SQ fascial bands and to systematically evaluate the bands using image analyses tools and morphometric measures. Methods In 28 healthy volunteers, ultrasound images were obtained at three body locations: the lateral aspect of the upper arm, medial aspect of the thigh and posterior aspect of lower leg. Using image analytical techniques, the total SQ band area, fascial band number, fascial band thickness, and SQ zone (layer) thickness were determined. In addition, the SQ spatial coherence was calculated based on the eigenvalues associated with the largest and smallest eigenvectors of the images. Results Fascial bands at these sites were contiguous with the dermis and the epimysium forming an interconnected network within the subcutaneous tissue. Subcutaneous blood vessels were also frequently encased by these fascial bands. The total SQ fascial band area was greater at the thigh and calf compared to the arm and was unrelated to SQ layer (zone) thickness. The thigh was associated with highest average number of fascial bands while calf was associated with the greatest average fascial band thickness. Across body regions, greater SQ zone thickness was associated with thinner fascial bands. SQ coherence was significantly associated with SQ zone thickness and body location (calf with statistically greater coherence compared to arm). Conclusion Fascial bands are structural bridges that mechanically link the skin, subcutaneous layer, and deeper muscle layers. This cohesive network also encases subcutaneous vessels and may indirectly mediate blood flow. The quantity and morphological characteristics of the SQ fascial band may reflect the composite mechanical forces experienced by the body part. PMID:21931632

Haralick textural features on T2 -weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer.

PubMed

Gnep, Khémara; Fargeas, Auréline; Gutiérrez-Carvajal, Ricardo E; Commandeur, Frédéric; Mathieu, Romain; Ospina, Juan D; Rolland, Yan; Rohou, Tanguy; Vincendeau, Sébastien; Hatt, Mathieu; Acosta, Oscar; de Crevoisier, Renaud

2017-01-01

To explore the association between magnetic resonance imaging (MRI), including Haralick textural features, and biochemical recurrence following prostate cancer radiotherapy. In all, 74 patients with peripheral zone localized prostate adenocarcinoma underwent pretreatment 3.0T MRI before external beam radiotherapy. Median follow-up of 47 months revealed 11 patients with biochemical recurrence. Prostate tumors were segmented on T 2 -weighted sequences (T 2 -w) and contours were propagated onto the coregistered apparent diffusion coefficient (ADC) images. We extracted 140 image features from normalized T 2 -w and ADC images corresponding to first-order (n = 6), gradient-based (n = 4), and second-order Haralick textural features (n = 130). Four geometrical features (tumor diameter, perimeter, area, and volume) were also computed. Correlations between Gleason score and MRI features were assessed. Cox regression analysis and random survival forests (RSF) were performed to assess the association between MRI features and biochemical recurrence. Three T 2 -w and one ADC Haralick textural features were significantly correlated with Gleason score (P < 0.05). Twenty-eight T 2 -w Haralick features and all four geometrical features were significantly associated with biochemical recurrence (P < 0.05). The most relevant features were Haralick features T 2 -w contrast, T 2 -w difference variance, ADC median, along with tumor volume and tumor area (C-index from 0.76 to 0.82; P < 0.05). By combining these most powerful features in an RSF model, the obtained C-index was 0.90. T 2 -w Haralick features appear to be strongly associated with biochemical recurrence following prostate cancer radiotherapy. 3 J. Magn. Reson. Imaging 2017;45:103-117. © 2016 International Society for Magnetic Resonance in Medicine.

Low Back Imaging When Not Indicated: A Descriptive Cross-System Analysis

PubMed Central

Gold, Rachel; Esterberg, Elizabeth; Hollombe, Celine; Arkind, Jill; Vakarcs, Patricia A; Tran, Huong; Burdick, Tim; DeVoe, Jennifer E; Horberg, Michael A

2016-01-01

Context: Guideline-discordant imaging to evaluate incident low back pain is common. Objective: We compared rates of guideline-discordant imaging in patients with low back pain in two care delivery systems with differing abilities to track care through an electronic health record (EHR), and in their patients’ insurance status, to measure the association between these factors and rates of ordered low back imaging. Design: We used data from two Kaiser Permanente (KP) Regions and from OCHIN, a community health center network. We extracted data on imaging performed after index visits for low back pain from June 1, 2011, to May 31, 2012, in these systems. Adjusted logistic regression measured associations between system-level factors and imaging rates. Main Outcome Measures: Imaging rates for incident low back pain using 2 national quality metrics: Clinical Quality Measure 0052, a measure for assessing Meaningful Use of EHRs, and the Healthcare Effectiveness Data and Information Set measure “Use of Imaging Studies for Low Back Pain.” Results: Among 19,503 KP patients and 2694 OCHIN patients with incident low back pain, ordered imaging was higher among men and whites but did not differ across health care systems. OCHIN’s publicly insured patients had higher rates of imaging compared with those with private or no insurance. Conclusion: Rates of ordered imaging to evaluate incident low back pain among uninsured OCHIN patients were lower than in KP overall; among insured OCHIN patients, rates were higher than in KP overall. Research is needed to establish causality and develop interventions. PMID:26934626

Mass Spectrometry Imaging Can Distinguish on a Proteomic Level Between Proliferative Nodules Within a Benign Congenital Nevus and Malignant Melanoma.

PubMed

Lazova, Rossitza; Yang, Zhe; El Habr, Constantin; Lim, Young; Choate, Keith Adam; Seeley, Erin H; Caprioli, Richard M; Yangqun, Li

2017-09-01

Histopathological interpretation of proliferative nodules occurring in association with congenital melanocytic nevi can be very challenging due to their similarities with congenital malignant melanoma and malignant melanoma arising in association with congenital nevi. We hereby report a diagnostically challenging case of congenital melanocytic nevus with proliferative nodules and ulcerations, which was originally misdiagnosed as congenital malignant melanoma. Subsequent histopathological examination in consultation by one of the authors (R.L.) and mass spectrometry imaging analysis rendered a diagnosis of congenital melanocytic nevus with proliferative nodules. In this case, mass spectrometry imaging, a novel method capable of distinguishing benign from malignant melanocytic lesions on a proteomic level, was instrumental in making the diagnosis of a benign nevus. We emphasize the importance of this method as an ancillary tool in the diagnosis of difficult melanocytic lesions.

Long-term follow-up after near-infrared spectroscopy coronary imaging: Insights from the lipid cORe plaque association with CLinical events (ORACLE-NIRS) registry.

PubMed

Danek, Barbara Anna; Karatasakis, Aris; Karacsonyi, Judit; Alame, Aya; Resendes, Erica; Kalsaria, Pratik; Nguyen-Trong, Phuong-Khanh J; Rangan, Bavana V; Roesle, Michele; Abdullah, Shuaib; Banerjee, Subhash; Brilakis, Emmanouil S

Coronary lipid core plaque may be associated with the incidence of subsequent cardiovascular events. We analyzed outcomes of 239 patients who underwent near-infrared spectroscopy (NIRS) coronary imaging between 2009-2011. Multivariable Cox regression was used to identify variables independently associated with the incidence of major adverse cardiovascular events (MACE; cardiac mortality, acute coronary syndromes (ACS), stroke, and unplanned revascularization) during follow-up. Mean patient age was 64±9years, 99% were men, and 50% were diabetic, presenting with stable coronary artery disease (61%) or an acute coronary syndrome (ACS, 39%). Target vessel pre-stenting median lipid core burden index (LCBI) was 88 [interquartile range, IQR 50-130]. Median LCBI in non-target vessels was 57 [IQR 26-94]. Median follow-up was 5.3years. The 5-year MACE rate was 37.5% (cardiac mortality was 15.0%). On multivariable analysis the following variables were associated with MACE: diabetes mellitus, prior percutaneous coronary intervention performed at index angiography, and non-target vessel LCBI. Non-target vessel LCBI of 77 was determined using receiver-operating characteristic curve analysis to be a threshold for prediction of MACE in our cohort. The adjusted hazard ratio (HR) for non-target vessel LCBI ≥77 was 14.05 (95% confidence interval (CI) 2.47-133.51, p=0.002). The 5-year cumulative incidence of events in the above-threshold group was 58.0% vs. 13.1% in the below-threshold group. During long-term follow-up of patients who underwent NIRS imaging, high LCBI in a non-PCI target vessel was associated with increased incidence of MACE. Published by Elsevier Inc.

Dopamine transporter availability in clinically normal aging is associated with individual differences in white matter integrity.

PubMed

Rieckmann, Anna; Hedden, Trey; Younger, Alayna P; Sperling, Reisa A; Johnson, Keith A; Buckner, Randy L

2016-02-01

Aging-related differences in white matter integrity, the presence of amyloid plaques, and density of biomarkers indicative of dopamine functions can be detected and quantified with in vivo human imaging. The primary aim of the present study was to investigate whether these imaging-based measures constitute independent imaging biomarkers in older adults, which would speak to the hypothesis that the aging brain is characterized by multiple independent neurobiological cascades. We assessed MRI-based markers of white matter integrity and PET-based marker of dopamine transporter density and amyloid deposition in the same set of 53 clinically normal individuals (age 65-87). A multiple regression analysis demonstrated that dopamine transporter availability is predicted by white matter integrity, which was detectable even after controlling for chronological age. Further post-hoc exploration revealed that dopamine transporter availability was further associated with systolic blood pressure, mirroring the established association between cardiovascular health and white matter integrity. Dopamine transporter availability was not associated with the presence of amyloid burden. Neurobiological correlates of dopamine transporter measures in aging are therefore likely unrelated to Alzheimer's disease but are aligned with white matter integrity and cardiovascular risk. More generally, these results suggest that two common imaging markers of the aging brain that are typically investigated separately do not reflect independent neurobiological processes. Hum Brain Mapp 37:621-631, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Recent Updates in the Endoscopic Diagnosis of Barrett's Oesophagus.

PubMed

Sharma, Neel; Ho, Khek Yu

2016-10-01

Barrett's oesophagus (BO) is a premalignant condition associated with the development of oesophageal adenocarcinoma (OAC). Despite the low risk of progression per annum, OAC is associated with significant morbidity and mortality, with an estimated 5-year survival of 10%. Furthermore, the incidence of OAC continues to rise globally. Therefore, it is imperative to detect the premalignant phase of BO and follow up such patients accordingly. The mainstay diagnosis of BO is endoscopy and biopsy sampling. However, limitations with white light endoscopy (WLE) and undertaking biopsies have shifted the current focus towards real-time image analysis. Utilization of additional tools such as chromoendoscopy, narrow-band imaging (NBI), confocal laser endomicroscopy (CLE), and optical coherence tomography (OCT) are proving beneficial. Furthermore, it is also becoming more apparent that often these tools are utilized by experts in the field. Therefore, for the non-expert, training in these systems is key. Currently as yet, the methodologies used for training optimization require further inquiry. (1) Real-time imaging can serve to minimize excess biopsies. (2) Tools such as chromoendoscopy, NBI, CLE, and OCT can help to compliment WLE. WLE is associated with limited sensitivity. Biopsy sampling is cost-ineffective and associated with sampling error. Hence, from a practical perspective, endoscopists should aim to utilize additional tools to help in real-time image interpretation and minimize an overreliance on histology.

Recent Updates in the Endoscopic Diagnosis of Barrett's Oesophagus

PubMed Central

Sharma, Neel; Ho, Khek Yu

2016-01-01

Background Barrett's oesophagus (BO) is a premalignant condition associated with the development of oesophageal adenocarcinoma (OAC). Despite the low risk of progression per annum, OAC is associated with significant morbidity and mortality, with an estimated 5-year survival of 10%. Furthermore, the incidence of OAC continues to rise globally. Therefore, it is imperative to detect the premalignant phase of BO and follow up such patients accordingly. Summary The mainstay diagnosis of BO is endoscopy and biopsy sampling. However, limitations with white light endoscopy (WLE) and undertaking biopsies have shifted the current focus towards real-time image analysis. Utilization of additional tools such as chromoendoscopy, narrow-band imaging (NBI), confocal laser endomicroscopy (CLE), and optical coherence tomography (OCT) are proving beneficial. Furthermore, it is also becoming more apparent that often these tools are utilized by experts in the field. Therefore, for the non-expert, training in these systems is key. Currently as yet, the methodologies used for training optimization require further inquiry. Key Message (1) Real-time imaging can serve to minimize excess biopsies. (2) Tools such as chromoendoscopy, NBI, CLE, and OCT can help to compliment WLE. Practical Implications WLE is associated with limited sensitivity. Biopsy sampling is cost-ineffective and associated with sampling error. Hence, from a practical perspective, endoscopists should aim to utilize additional tools to help in real-time image interpretation and minimize an overreliance on histology. PMID:27904863

Scanning gate microscopy of quantum rings: effects of an external magnetic field and of charged defects.

PubMed

Pala, M G; Baltazar, S; Martins, F; Hackens, B; Sellier, H; Ouisse, T; Bayot, V; Huant, S

2009-07-01

We study scanning gate microscopy (SGM) in open quantum rings obtained from buried semiconductor InGaAs/InAlAs heterostructures. By performing a theoretical analysis based on the Keldysh-Green function approach we interpret the radial fringes observed in experiments as the effect of randomly distributed charged defects. We associate SGM conductance images with the local density of states (LDOS) of the system. We show that such an association cannot be made with the current density distribution. By varying an external magnetic field we are able to reproduce recursive quasi-classical orbits in LDOS and conductance images, which bear the same periodicity as the Aharonov-Bohm effect.

Ratioed scatter diagrams - An erotetic method for phase identification on complex surfaces using scanning Auger microscopy

NASA Technical Reports Server (NTRS)

Browning, R.

1984-01-01

By ratioing multiple Auger intensities and plotting a two-dimensional occupational scatter diagram while digitally scanning across an area, the number and elemental association of surface phases can be determined. This can prove a useful tool in scanning Auger microscopic analysis of complex materials. The technique is illustrated by results from an anomalous region on the reaction zone of a SiC/Ti-6Al-4V metal matrix composite material. The anomalous region is shown to be a single phase associated with sulphur and phosphorus impurities. Imaging of a selected phase from the ratioed scatter diagram is possible and may be a useful technique for presenting multiple scanning Auger images.

Remote sensing by ERTS satellite of vegetational resources believed to be under possible threat of environmental stress

NASA Technical Reports Server (NTRS)

Poonai, P.; Floyd, W. J.; Hall, R.

1974-01-01

The distribution of natural vegetation types on North Merritt Island, Florida, was studied by analysis of ERTS multispectral scanner data on the image-100 computer system. The boundaries of six distinct plant associations were located on photos made on the image analyzer, with an insignificant mean error of -24.38 meters. The six plant associations are described; each had a characteristic spectral signature. The difference in average reflectance grey level between the lowest of the four spectral scanning bands and the highest spectral scanning band for the six vegetation types was determined. The decreasing trend of the differences is strongly negatively correlated with height of land.

A data model and database for high-resolution pathology analytical image informatics.

PubMed

Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

2011-01-01

The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming increasingly feasible for basic, clinical, and translational research studies to produce thousands of whole-slide images. Systematic analysis of these large datasets requires efficient data management support for representing and indexing results from hundreds of interrelated analyses generating very large volumes of quantifications such as shape and texture and of classifications of the quantified features. We have designed a data model and a database to address the data management requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines. The data model represents virtual slide related image, annotation, markup and feature information. The database supports a wide range of metadata and spatial queries on images, annotations, markups, and features. We currently have three databases running on a Dell PowerEdge T410 server with CentOS 5.5 Linux operating system. The database server is IBM DB2 Enterprise Edition 9.7.2. The set of databases consists of 1) a TMA database containing image analysis results from 4740 cases of breast cancer, with 641 MB storage size; 2) an algorithm validation database, which stores markups and annotations from two segmentation algorithms and two parameter sets on 18 selected slides, with 66 GB storage size; and 3) an in silico brain tumor study database comprising results from 307 TCGA slides, with 365 GB storage size. The latter two databases also contain human-generated annotations and markups for regions and nuclei. Modeling and managing pathology image analysis results in a database provide immediate benefits on the value and usability of data in a research study. The database provides powerful query capabilities, which are otherwise difficult or cumbersome to support by other approaches such as programming languages. Standardized, semantic annotated data representation and interfaces also make it possible to more efficiently share image data and analysis results.

A philosophy for CNS radiotracer design

DOE PAGES

Van de Bittner, Genevieve C.; Ricq, Emily L.; Hooker, Jacob M.

2014-10-01

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfallsmore » of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test–retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood–brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Lastly, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.« less

A Philosophy for CNS Radiotracer Design

PubMed Central

2015-01-01

Conspectus Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test–retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood–brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible. PMID:25272291

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalisedcross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalised cross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Structural brain network analysis in families multiply affected with bipolar I disorder.

PubMed

Forde, Natalie J; O'Donoghue, Stefani; Scanlon, Cathy; Emsell, Louise; Chaddock, Chris; Leemans, Alexander; Jeurissen, Ben; Barker, Gareth J; Cannon, Dara M; Murray, Robin M; McDonald, Colm

2015-10-30

Disrupted structural connectivity is associated with psychiatric illnesses including bipolar disorder (BP). Here we use structural brain network analysis to investigate connectivity abnormalities in multiply affected BP type I families, to assess the utility of dysconnectivity as a biomarker and its endophenotypic potential. Magnetic resonance diffusion images for 19 BP type I patients in remission, 21 of their first degree unaffected relatives, and 18 unrelated healthy controls underwent tractography. With the automated anatomical labelling atlas being used to define nodes, a connectivity matrix was generated for each subject. Network metrics were extracted with the Brain Connectivity Toolbox and then analysed for group differences, accounting for potential confounding effects of age, gender and familial association. Whole brain analysis revealed no differences between groups. Analysis of specific mainly frontal regions, previously implicated as potentially endophenotypic by functional magnetic resonance imaging analysis of the same cohort, revealed a significant effect of group in the right medial superior frontal gyrus and left middle frontal gyrus driven by reduced organisation in patients compared with controls. The organisation of whole brain networks of those affected with BP I does not differ from their unaffected relatives or healthy controls. In discreet frontal regions, however, anatomical connectivity is disrupted in patients but not in their unaffected relatives. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Cytological study of DNA content and nuclear morphometric analysis for aid in the diagnosis of high-grade dysplasia within oral leukoplakia.

PubMed

Yang, Xi; Xiao, Xuan; Wu, Wenyan; Shen, Xuemin; Zhou, Zengtong; Liu, Wei; Shi, Linjun

2017-09-01

To quantitatively examine the DNA content and nuclear morphometric status of oral leukoplakia (OL) and investigate its association with the degree of dysplasia in a cytologic study. Oral cytobrush biopsy was carried out to obtain exfoliative epithelial cells from lesions before scalpel biopsy at the same location in a blinded series of 70 patients with OL. Analysis of nuclear morphometry and DNA content status using image cytometry was performed with oral smears stained with the Feulgen-thionin method. Nuclear morphometric analysis revealed significant differences in DNA content amount, DNA index, nuclear area, nuclear radius, nuclear intensity, sphericity, entropy, and fractal dimension (all P < .01) between low-grade and high-grade dysplasia. DNA content analysis identified 34 patients with OL (48.6%) with DNA content abnormality. Nonhomogeneous lesion (P = .018) and high-grade dysplasia (P = .008) were significantly associated with abnormal DNA content. Importantly, the positive correlation between the degree of oral dysplasia and DNA content status was significant (P = .004, correlation coefficient = 0.342). Cytology analysis of DNA content and nuclear morphometric status using image cytometry may support their use as a screening and monitoring tool for OL progression. Copyright © 2017 Elsevier Inc. All rights reserved.

Probing of multiple magnetic responses in magnetic inductors using atomic force microscopy.

PubMed

Park, Seongjae; Seo, Hosung; Seol, Daehee; Yoon, Young-Hwan; Kim, Mi Yang; Kim, Yunseok

2016-02-08

Even though nanoscale analysis of magnetic properties is of significant interest, probing methods are relatively less developed compared to the significance of the technique, which has multiple potential applications. Here, we demonstrate an approach for probing various magnetic properties associated with eddy current, coil current and magnetic domains in magnetic inductors using multidimensional magnetic force microscopy (MMFM). The MMFM images provide combined magnetic responses from the three different origins, however, each contribution to the MMFM response can be differentiated through analysis based on the bias dependence of the response. In particular, the bias dependent MMFM images show locally different eddy current behavior with values dependent on the type of materials that comprise the MI. This approach for probing magnetic responses can be further extended to the analysis of local physical features.

A generalized parametric response mapping method for analysis of multi-parametric imaging: A feasibility study with application to glioblastoma.

PubMed

Lausch, Anthony; Yeung, Timothy Pok-Chi; Chen, Jeff; Law, Elton; Wang, Yong; Urbini, Benedetta; Donelli, Filippo; Manco, Luigi; Fainardi, Enrico; Lee, Ting-Yim; Wong, Eugene

2017-11-01

Parametric response map (PRM) analysis of functional imaging has been shown to be an effective tool for early prediction of cancer treatment outcomes and may also be well-suited toward guiding personalized adaptive radiotherapy (RT) strategies such as sub-volume boosting. However, the PRM method was primarily designed for analysis of longitudinally acquired pairs of single-parameter image data. The purpose of this study was to demonstrate the feasibility of a generalized parametric response map analysis framework, which enables analysis of multi-parametric data while maintaining the key advantages of the original PRM method. MRI-derived apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps acquired at 1 and 3-months post-RT for 19 patients with high-grade glioma were used to demonstrate the algorithm. Images were first co-registered and then standardized using normal tissue image intensity values. Tumor voxels were then plotted in a four-dimensional Cartesian space with coordinate values equal to a voxel's image intensity in each of the image volumes and an origin defined as the multi-parametric mean of normal tissue image intensity values. Voxel positions were orthogonally projected onto a line defined by the origin and a pre-determined response vector. The voxels are subsequently classified as positive, negative or nil, according to whether projected positions along the response vector exceeded a threshold distance from the origin. The response vector was selected by identifying the direction in which the standard deviation of tumor image intensity values was maximally different between responding and non-responding patients within a training dataset. Voxel classifications were visualized via familiar three-class response maps and then the fraction of tumor voxels associated with each of the classes was investigated for predictive utility analogous to the original PRM method. Independent PRM and MPRM analyses of the contrast-enhancing lesion (CEL) and a 1 cm shell of surrounding peri-tumoral tissue were performed. Prediction using tumor volume metrics was also investigated. Leave-one-out cross validation (LOOCV) was used in combination with permutation testing to assess preliminary predictive efficacy and estimate statistically robust P-values. The predictive endpoint was overall survival (OS) greater than or equal to the median OS of 18.2 months. Single-parameter PRM and multi-parametric response maps (MPRMs) were generated for each patient and used to predict OS via the LOOCV. Tumor volume metrics (P ≥ 0.071 ± 0.01) and single-parameter PRM analyses (P ≥ 0.170 ± 0.01) were not found to be predictive of OS within this study. MPRM analysis of the peri-tumoral region but not the CEL was found to be predictive of OS with a classification sensitivity, specificity and accuracy of 80%, 100%, and 89%, respectively (P = 0.001 ± 0.01). The feasibility of a generalized MPRM analysis framework was demonstrated with improved prediction of overall survival compared to the original single-parameter method when applied to a glioblastoma dataset. The proposed algorithm takes the spatial heterogeneity in multi-parametric response into consideration and enables visualization. MPRM analysis of peri-tumoral regions was shown to have predictive potential supporting further investigation of a larger glioblastoma dataset. © 2017 American Association of Physicists in Medicine.

A picture tells a thousand words: A content analysis of concussion-related images online.

PubMed

Ahmed, Osman H; Lee, Hopin; Struik, Laura L

2016-09-01

Recently image-sharing social media platforms have become a popular medium for sharing health-related images and associated information. However within the field of sports medicine, and more specifically sports related concussion, the content of images and meta-data shared through these popular platforms have not been investigated. The aim of this study was to analyse the content of concussion-related images and its accompanying meta-data on image-sharing social media platforms. We retrieved 300 images from Pinterest, Instagram and Flickr by using a standardised search strategy. All images were screened and duplicate images were removed. We excluded images if they were: non-static images; illustrations; animations; or screenshots. The content and characteristics of each image was evaluated using a customised coding scheme to determine major content themes, and images were referenced to the current international concussion management guidelines. From 300 potentially relevant images, 176 images were included for analysis; 70 from Pinterest, 63 from Flickr, and 43 from Instagram. Most images were of another person or a scene (64%), with the primary content depicting injured individuals (39%). The primary purposes of the images were to share a concussion-related incident (33%) and to dispense education (19%). For those images where it could be evaluated, the majority (91%) were found to reflect the Sports Concussion Assessment Tool 3 (SCAT3) guidelines. The ability to rapidly disseminate rich information though photos, images, and infographics to a wide-reaching audience suggests that image-sharing social media platforms could be used as an effective communication tool for sports concussion. Public health strategies could direct educative content to targeted populations via the use of image-sharing platforms. Further research is required to understand how image-sharing platforms can be used to effectively relay evidence-based information to patients and sports medicine clinicians. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

PubMed

Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

2015-01-01

A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image.

Arterial compression of the retro-olivary sulcus of the medulla in essential hypertension: a multivariate analysis.

PubMed

Coffee, Robert E; Nicholas, Joyce S; Egan, Brent M; Rumboldt, Zoran; D'Agostino, Sabino; Patel, Sunil J

2005-11-01

Pulsatile arterial compression (AC) of the ventrolateral medulla (VLM) has been postulated to cause neurogenically mediated essential hypertension (EHTN). We aimed to establish whether the association between AC of specifically the retro-olivary sulcus (ROS) of the VLM and EHTN was significant, while controlling for other risks associated with EHTN. Case-control study. Posterior fossa magnetic resonance imaging scans of 131 subjects, including 58 subjects with EHTN and 73 normotensives, were reviewed to determine the presence of AC in the ROS. The history of other risk factors for EHTN was obtained by reviewing medical records. Multivariate logistic regression analysis of these data shows a significant association between AC in the ROS (right and/or left) and EHTN [odds ratio (OR) = 3.03, 95% confidence interval (CI) = 1.30, 7.06]. This analysis was done controlling for other known EHTN risk factors such as age, race, sex, diabetes, and obesity. A secondary analysis also controlling for these variables shows that AC of both the right and left ROS are independently associated with EHTN (right AC: OR = 5.04, 95% CI = 1.33, 19.17; left AC: OR = 3.39, 95% CI = 1.20, 9.60). In this retrospective study of subjects with EHTN and normotensive controls that had undergone magnetic resonance imaging of the posterior fossa, AC of the ROS on either side of the medulla is a significant independent risk factor in EHTN. Further studies are required to determine whether this is true for the general population of patients with neurogenically mediated EHTN.

Stigma models: Testing hypotheses of how images of Nevada are acquired and values are attached to them

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

Jenkins-Smith, H.C.

1994-12-01

This report analyzes data from surveys on the effects that images associated with nuclear power and waste (i.e., nuclear images) have on people`s preference to vacation in Nevada. The analysis was stimulated by a model of imagery and stigma which assumes that information about a potentially hazardous facility generates signals that elicit negative images about the place in which it is located. Individuals give these images negative values (valences) that lessen their desire to vacation, relocate, or retire in that place. The model has been used to argue that the proposed Yucca Mountain high-level nuclear waste repository could elicit imagesmore » of nuclear waste that would stigmatize Nevada and thus impose substantial economic losses there. This report proposes a revised model that assumes that the acquisition and valuation of images depend on individuals` ideological and cultural predispositions and that the ways in which new images will affect their preferences and behavior partly depend on these predispositions. The report tests these hypotheses: (1) individuals with distinct cultural and ideological predispositions have different propensities for acquiring nuclear images, (2) these people attach different valences to these images, (3) the variations in these valences are important, and (4) the valences of the different categories of images within an individual`s image sets for a place correlate very well. The analysis largely confirms these hypotheses, indicating that the stigma model should be revised to (1) consider the relevant ideological and cultural predispositions of the people who will potentially acquire and attach value to the image, (2) specify the kinds of images that previously attracted people to the host state, and (3) consider interactions between the old and potential new images of the place. 37 refs., 18 figs., 17 tabs.« less

More than looking good: impact on quality of life moderates the relationship between functional body image and physical activity in men with SCI.

PubMed

Bassett, R L; Martin Ginis, K A

2009-03-01

Cross-sectional. To examine the relationship between body image and leisure time physical activity (LTPA) among men with spinal cord injury (SCI). Specifically, to examine the moderating function of the perceived impact of body image on quality of life (QOL). Ontario, Canada. Men with SCI (N=50, 50% paraplegic) reported, (a) their functional and appearance body image (Adult Body Satisfaction Questionnaire), (b) their perceived impact of body image on QOL and (c) LTPA performed over the previous 3 days. Body image was in the 'normal' range compared with the general population. Linear regression analysis found a significant LTPA x body image impact on QOL interaction beta=0.39, P<0.05. Post hoc analysis showed that among individuals who reported a negative effect of body image on QOL, those who engaged in LTPA were less satisfied with their physical function than those who did not. For those who did not perceive their body image to negatively impact their QOL, there was generally no difference in functional body image between those who engaged in LTPA and those who did not. Appearance body image is not related to LTPA for men with SCI. It has been suggested that body dissatisfaction may motivate some individuals to engage in LTPA. However, for men living with SCI, functional body image may be associated with LTPA only when a negative effect on QOL is perceived. Future research should consider the moderating function of the perceived impact of body image on QOL when examining the relationship between LTPA and body image among men living with SCI.

Second harmonic generation imaging of the collagen in myocardium for atrial fibrillation diagnosis

NASA Astrophysics Data System (ADS)

Tsai, Ming-Rung; Chiou, Yu-We; Sun, Chi-Kuang

2009-02-01

Myocardial fibrosis, a common sequela of cardiac hypertrophy, has been shown to be associated with arrhythmias in experimental models. Some research has indicated that myocardial fibrosis plays an important role in predisposing patients to atrial fibrillation. Second harmonic generation (SHG) is an optically nonlinear coherent process to image the collagen network. In this presentation, we observe the SHG images of the collagen matrix in atrial myocardium and we analyzed of collagen fibers arrangement by using Fourier-transform analysis. Moreover, comparing the SHG images of the collagen fibers in atrial myocardium between normal sinus rhythm (NSR) and atrial fibrillation (AF), our result indicated that it is possible to realize the relation between myocardial fibrosis and AF.

Near-field microscopy and fluorescence spectroscopy: application to chromosomes labelled with different fluorophores.

PubMed

Mahieu-Williame, L; Falgayrettes, P; Nativel, L; Gall-Borrut, P; Costa, L; Salehzada, T; Bisbal, C

2010-04-01

We have coupled a spectrophotometer with a scanning near-field optical microscope to obtain, with a single scan, simultaneously scanning near-field optical microscope fluorescence images at different wavelengths as well as topography and transmission images. Extraction of the fluorescence spectra enabled us to decompose the different wavelengths of the fluorescence signals which normally overlap. We thus obtained images of the different fluorescence emissions of acridine orange bound to single or double stranded nucleic acids in human metaphase chromosomes before and after DNAse I or RNAse A treatment. The analysis of these images allowed us to visualize some specific chromatin areas where RNA is associated with DNA showing that such a technique could be used to identify multiple components within a cell.

Association between mammogram density and background parenchymal enhancement of breast MRI

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Danala, Gopichandh; Wang, Yunzhi; Zarafshani, Ali; Qian, Wei; Liu, Hong; Zheng, Bin

2018-02-01

Breast density has been widely considered as an important risk factor for breast cancer. The purpose of this study is to examine the association between mammogram density results and background parenchymal enhancement (BPE) of breast MRI. A dataset involving breast MR images was acquired from 65 high-risk women. Based on mammography density (BIRADS) results, the dataset was divided into two groups of low and high breast density cases. The Low-Density group has 15 cases with mammographic density (BIRADS 1 and 2), while the High-density group includes 50 cases, which were rated by radiologists as mammographic density BIRADS 3 and 4. A computer-aided detection (CAD) scheme was applied to segment and register breast regions depicted on sequential images of breast MRI scans. CAD scheme computed 20 global BPE features from the entire two breast regions, separately from the left and right breast region, as well as from the bilateral difference between left and right breast regions. An image feature selection method namely, CFS method, was applied to remove the most redundant features and select optimal features from the initial feature pool. Then, a logistic regression classifier was built using the optimal features to predict the mammogram density from the BPE features. Using a leave-one-case-out validation method, the classifier yields the accuracy of 82% and area under ROC curve, AUC=0.81+/-0.09. Also, the box-plot based analysis shows a negative association between mammogram density results and BPE features in the MRI images. This study demonstrated a negative association between mammogram density and BPE of breast MRI images.

Brain response to images of food varying in energy density is associated with body composition in 7- to 10-year-old children: Results of an exploratory study.

PubMed

Fearnbach, S Nicole; English, Laural K; Lasschuijt, Marlou; Wilson, Stephen J; Savage, Jennifer S; Fisher, Jennifer O; Rolls, Barbara J; Keller, Kathleen L

2016-08-01

Energy balance is regulated by a multifaceted system of physiological signals that influence energy intake and expenditure. Therefore, variability in the brain's response to food may be partially explained by differences in levels of metabolically active tissues throughout the body, including fat-free mass (FFM) and fat mass (FM). The purpose of this study was to test the hypothesis that children's body composition would be related to their brain response to food images varying in energy density (ED), a measure of energy content per weight of food. Functional magnetic resonance imaging (fMRI) was used to measure brain response to High (>1.5kcal/g) and Low (<1.5kcal/g) ED food images, and Control images, in 36 children ages 7-10years. Body composition was measured using bioelectrical impedance analysis. Multi-subject random effects general linear model (GLM) and two-factor repeated measures analysis of variance (ANOVA) were used to test for main effects of ED (High ED vs. Low ED) in a priori defined brain regions of interest previously implicated in energy homeostasis and reward processing. Pearson's correlations were then calculated between activation in these regions for various contrasts (High ED-Low ED, High ED-Control, Low ED-Control) and child body composition (FFM index, FM index, % body fat). Relative to Low ED foods, High ED foods elicited greater BOLD activation in the left thalamus. In the right substantia nigra, BOLD activation for the contrast of High ED-Low ED foods was positively associated with child FFM. There were no significant results for the High ED-Control or Low ED-Control contrasts. Our findings support literature on FFM as an appetitive driver, such that greater amounts of lean mass were associated with greater activation for High ED foods in an area of the brain associated with dopamine signaling and reward (substantia nigra). These results confirm our hypothesis that brain response to foods varying in energy content is related to measures of child body composition. Copyright © 2016 Elsevier Inc. All rights reserved.

Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion.

PubMed

Guo, Kun; Soornack, Yoshi; Settle, Rebecca

2018-03-05

Our capability of recognizing facial expressions of emotion under different viewing conditions implies the existence of an invariant expression representation. As natural visual signals are often distorted and our perceptual strategy changes with external noise level, it is essential to understand how expression perception is susceptible to face distortion and whether the same facial cues are used to process high- and low-quality face images. We systematically manipulated face image resolution (experiment 1) and blur (experiment 2), and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. Our analysis revealed a reasonable tolerance to face distortion in expression perception. Reducing image resolution up to 48 × 64 pixels or increasing image blur up to 15 cycles/image had little impact on expression assessment and associated gaze behaviour. Further distortion led to decreased expression categorization accuracy and intensity rating, increased reaction time and fixation duration, and stronger central fixation bias which was not driven by distortion-induced changes in local image saliency. Interestingly, the observed distortion effects were expression-dependent with less deterioration impact on happy and surprise expressions, suggesting this distortion-invariant facial expression perception might be achieved through the categorical model involving a non-linear configural combination of local facial features. Copyright © 2018 Elsevier Ltd. All rights reserved.

High-Resolution In Vivo Imaging of Regimes of Laser Damage to the Primate Retina

PubMed Central

Pocock, Ginger M.; Oliver, Jeffrey W.; Specht, Charles S.; Estep, J. Scot; Noojin, Gary D.; Schuster, Kurt; Rockwell, Benjamin A.

2014-01-01

Purpose. To investigate fundamental mechanisms of regimes of laser induced damage to the retina and the morphological changes associated with the damage response. Methods. Varying grades of photothermal, photochemical, and photomechanical retinal laser damage were produced in eyes of eight cynomolgus monkeys. An adaptive optics confocal scanning laser ophthalmoscope and spectral domain optical coherence tomographer were combined to simultaneously collect complementary in vivo images of retinal laser damage during and following exposure. Baseline color fundus photography was performed to complement high-resolution imaging. Monkeys were perfused with 10% buffered formalin and eyes were enucleated for histological analysis. Results. Laser energies for visible retinal damage in this study were consistent with previously reported damage thresholds. Lesions were identified in OCT images that were not visible in direct ophthalmoscopic examination or fundus photos. Unique diagnostic characteristics, specific to each damage regime, were identified and associated with shape and localization of lesions to specific retinal layers. Previously undocumented retinal healing response to blue continuous wave laser exposure was recorded through a novel experimental methodology. Conclusion. This study revealed increased sensitivity of lesion detection and improved specificity to the laser of origin utilizing high-resolution imaging when compared to traditional ophthalmic imaging techniques in the retina. PMID:24891943

Texture analysis applied to second harmonic generation image data for disease classification and development of a multi-view second harmonic generation imaging platform

NASA Astrophysics Data System (ADS)

Wen, Lianggong

Many diseases, e.g. ovarian cancer, breast cancer and pulmonary fibrosis, are commonly associated with drastic alterations in surrounding connective tissue, and changes in the extracellular matrix (ECM) are associated with the vast majority of cellular processes in disease progression and carcinogenesis: cell differentiation, proliferation, biosynthetic ability, polarity, and motility. We use second harmonic generation (SHG) microscopy for imaging the ECM because it is a non-invasive, non-linear laser scanning technique with high sensitivity and specificity for visualizing fibrillar collagen. In this thesis, we are interested in developing imaging techniques to understand how the ECM, especially the collagen architecture, is remodeled in diseases. To quantitate remodeling, we implement a 3D texture analysis to delineate the collagen fibrillar morphology observed in SHG microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"---frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations---is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective mages, we then perform classification between normal and high grade malignant ovarian tissues classification based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features. Further, we describe the development of a multi-view 3D SHG imaging platform. Unlike fluorescence microscopy, SHG excites intrinsic characteristics of collagen, bypassing the need for additional primary and secondary imaging labels. However, single view image collection from endogenous SHG contrast of collagen molecules is not "a true 3D technique", because collagen fibers oriented along the plane of the lasers used to excite them are invisible to the excitation The loss of information means that researchers cannot resolve the 3D structure of the ECM using this technique. We are developing a new, multi-view approach that involves rotation of agarose embedded sample in FEP tubing, so that the excitation beam path travels to from multiple angles, to reveal new insight in understanding the 3D collagen structure and its role in normal and diseased tissue.

Image acquisition with immersion objective lenses using electrons emitted with several tenths of an electron volt energies: towards high spatial resolution ESCA analysis.

PubMed

Bernheim, M

2006-03-01

This study aims to evaluate the spatial resolution achievable with photoelectrons in order to perform localised UPS or XPS analyses on various heterogeneous samples. This investigation is intentionally restricted to direct image acquisition by immersion objective lenses, involving electrons ejected with initial energies of several tenths of an electron-volt. In order to characterise the contribution of all optical elements, analytical investigations were associated to numerical simulations based on SIMION 7 software. The acquisition of high-quality images implies a simultaneous reduction in spherical and chromatic aberrations by a narrow aperture stop placed at the output pupil of the objective. With such limitations in useful emission angles, it is shown that monochromatic electron beams build images with a resolution of about 1 nm, especially for the acceleration bias mode where the focussing electrode is biased at a positive high voltage. Even energy dispersed electron beams, limited by a 4 eV band pass spectrometer, can produce images convenient for highly localised ESCA analyses (resolution 3 nm), where the objective lens is associated with an aperture stop of 30 microm in diameter without using acceleration voltages above 5000 V.

Advanced imaging technologies increase detection of dysplasia and neoplasia in patients with Barrett's esophagus: a meta-analysis and systematic review.

PubMed

Qumseya, Bashar J; Wang, Haibo; Badie, Nicole; Uzomba, Rosemary N; Parasa, Sravanthi; White, Donna L; Wolfsen, Herbert; Sharma, Prateek; Wallace, Michael B

2013-12-01

US guidelines recommend surveillance of patients with Barrett's esophagus (BE) to detect dysplasia. BE conventionally is monitored via white-light endoscopy (WLE) and a collection of random biopsy specimens. However, this approach does not definitively or consistently detect areas of dysplasia. Advanced imaging technologies can increase the detection of dysplasia and cancer. We investigated whether these imaging technologies can increase the diagnostic yield for the detection of neoplasia in patients with BE, compared with WLE and analysis of random biopsy specimens. We performed a systematic review, using Medline and Embase, to identify relevant peer-review studies. Fourteen studies were included in the final analysis, with a total of 843 patients. Our metameter (estimate) of interest was the paired-risk difference (RD), defined as the difference in yield of the detection of dysplasia or cancer using advanced imaging vs WLE. The estimated paired-RD and 95% confidence interval (CI) were obtained using random-effects models. Heterogeneity was assessed by means of the Q statistic and the I(2) statistic. An exploratory meta-regression was performed to look for associations between the metameter and potential confounders or modifiers. Overall, advanced imaging techniques increased the diagnostic yield for detection of dysplasia or cancer by 34% (95% CI, 20%-56%; P < .0001). A subgroup analysis showed that virtual chromoendoscopy significantly increased the diagnostic yield (RD, 0.34; 95% CI, 0.14-0.56; P < .0001). The RD for chromoendoscopy was 0.35 (95% CI, 0.13-0.56; P = .0001). There was no significant difference between virtual chromoendoscopy and chromoendoscopy, based on Student t test analysis (P = .45). Based on a meta-analysis, advanced imaging techniques such as chromoendoscopy or virtual chromoendoscopy significantly increase the diagnostic yield for identification of dysplasia or cancer in patients with BE. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

Quantitative Multispectral Analysis Of Discrete Subcellular Particles By Digital Imaging Fluorescence Microscopy (DIFM)

NASA Astrophysics Data System (ADS)

Dorey, C. K.; Ebenstein, David B.

1988-10-01

Subcellular localization of multiple biochemical markers is readily achieved through their characteristic autofluorescence or through use of appropriately labelled antibodies. Recent development of specific probes has permitted elegant studies in calcium and pH in living cells. However, each of these methods measured fluorescence at one wavelength; precise quantitation of multiple fluorophores at individual sites within a cell has not been possible. Using DIFM, we have achieved spectral analysis of discrete subcellular particles 1-2 gm in diameter. The fluorescence emission is broken into narrow bands by an interference monochromator and visualized through the combined use of a silicon intensified target (SIT) camera, a microcomputer based framegrabber with 8 bit resolution, and a color video monitor. Image acquisition, processing, analysis and display are under software control. The digitized image can be corrected for the spectral distortions induced by the wavelength dependent sensitivity of the camera, and the displayed image can be enhanced or presented in pseudocolor to facilitate discrimination of variation in pixel intensity of individual particles. For rapid comparison of the fluorophore composition of granules, a ratio image is produced by dividing the image captured at one wavelength by that captured at another. In the resultant ratio image, a granule which has a fluorophore composition different from the majority is selectively colored. This powerful system has been utilized to obtain spectra of endogenous autofluorescent compounds in discrete cellular organelles of human retinal pigment epithelium, and to measure immunohistochemically labelled components of the extracellular matrix associated with the human optic nerve.

The Diagnostic Efficacy of Cone-beam Computed Tomography in Endodontics: A Systematic Review and Analysis by a Hierarchical Model of Efficacy.

PubMed

Rosen, Eyal; Taschieri, Silvio; Del Fabbro, Massimo; Beitlitum, Ilan; Tsesis, Igor

2015-07-01

The aim of this study was to evaluate the diagnostic efficacy of cone-beam computed tomographic (CBCT) imaging in endodontics based on a systematic search and analysis of the literature using an efficacy model. A systematic search of the literature was performed to identify studies evaluating the use of CBCT imaging in endodontics. The identified studies were subjected to strict inclusion criteria followed by an analysis using a hierarchical model of efficacy (model) designed for appraisal of the literature on the levels of efficacy of a diagnostic imaging modality. Initially, 485 possible relevant articles were identified. After title and abstract screening and a full-text evaluation, 58 articles (12%) that met the inclusion criteria were analyzed and allocated to levels of efficacy. Most eligible articles (n = 52, 90%) evaluated technical characteristics or the accuracy of CBCT imaging, which was defined in this model as low levels of efficacy. Only 6 articles (10%) proclaimed to evaluate the efficacy of CBCT imaging to support the practitioner's decision making; treatment planning; and, ultimately, the treatment outcome, which was defined as higher levels of efficacy. The expected ultimate benefit of CBCT imaging to the endodontic patient as evaluated by its level of diagnostic efficacy is unclear and is mainly limited to its technical and diagnostic accuracy efficacies. Even for these low levels of efficacy, current knowledge is limited. Therefore, a cautious and rational approach is advised when considering CBCT imaging for endodontic purposes. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Comprehensive, powerful, efficient, intuitive: a new software framework for clinical imaging applications

NASA Astrophysics Data System (ADS)

Augustine, Kurt E.; Holmes, David R., III; Hanson, Dennis P.; Robb, Richard A.

2006-03-01

One of the greatest challenges for a software engineer is to create a complex application that is comprehensive enough to be useful to a diverse set of users, yet focused enough for individual tasks to be carried out efficiently with minimal training. This "powerful yet simple" paradox is particularly prevalent in advanced medical imaging applications. Recent research in the Biomedical Imaging Resource (BIR) at Mayo Clinic has been directed toward development of an imaging application framework that provides powerful image visualization/analysis tools in an intuitive, easy-to-use interface. It is based on two concepts very familiar to physicians - Cases and Workflows. Each case is associated with a unique patient and a specific set of routine clinical tasks, or a workflow. Each workflow is comprised of an ordered set of general-purpose modules which can be re-used for each unique workflow. Clinicians help describe and design the workflows, and then are provided with an intuitive interface to both patient data and analysis tools. Since most of the individual steps are common to many different workflows, the use of general-purpose modules reduces development time and results in applications that are consistent, stable, and robust. While the development of individual modules may reflect years of research by imaging scientists, new customized workflows based on the new modules can be developed extremely fast. If a powerful, comprehensive application is difficult to learn and complicated to use, it will be unacceptable to most clinicians. Clinical image analysis tools must be intuitive and effective or they simply will not be used.

Continuous monitoring of arthritis in animal models using optical imaging modalities

NASA Astrophysics Data System (ADS)

Son, Taeyoon; Yoon, Hyung-Ju; Lee, Saseong; Jang, Won Seuk; Jung, Byungjo; Kim, Wan-Uk

2014-10-01

Given the several difficulties associated with histology, including difficulty in continuous monitoring, this study aimed to investigate the feasibility of optical imaging modalities-cross-polarization color (CPC) imaging, erythema index (EI) imaging, and laser speckle contrast (LSC) imaging-for continuous evaluation and monitoring of arthritis in animal models. C57BL/6 mice, used for the evaluation of arthritis, were divided into three groups: arthritic mice group (AMG), positive control mice group (PCMG), and negative control mice group (NCMG). Complete Freund's adjuvant, mineral oil, and saline were injected into the footpad for AMG, PCMG, and NCMG, respectively. LSC and CPC images were acquired from 0 through 144 h after injection for all groups. EI images were calculated from CPC images. Variations in feet area, EI, and speckle index for each mice group over time were calculated for quantitative evaluation of arthritis. Histological examinations were performed, and the results were found to be consistent with those from optical imaging analysis. Thus, optical imaging modalities may be successfully applied for continuous evaluation and monitoring of arthritis in animal models.

Visualizing Calcium Flux in Freely Moving Nematode Embryos.

PubMed

Ardiel, Evan L; Kumar, Abhishek; Marbach, Joseph; Christensen, Ryan; Gupta, Rishi; Duncan, William; Daniels, Jonathan S; Stuurman, Nico; Colón-Ramos, Daniel; Shroff, Hari

2017-05-09

The lack of physiological recordings from Caenorhabditis elegans embryos stands in stark contrast to the comprehensive anatomical and gene expression datasets already available. Using light-sheet fluorescence microscopy to address the challenges associated with functional imaging at this developmental stage, we recorded calcium dynamics in muscles and neurons and developed analysis strategies to relate activity and movement. In muscles, we found that the initiation of twitching was associated with a spreading calcium wave in a dorsal muscle bundle. Correlated activity in muscle bundles was linked with early twitching and eventual coordinated movement. To identify neuronal correlates of behavior, we monitored brainwide activity with subcellular resolution and identified a particularly active cell associated with muscle contractions. Finally, imaging neurons of a well-defined adult motor circuit, we found that reversals in the eggshell correlated with calcium transients in AVA interneurons. Published by Elsevier Inc.

Membrane Transfer Phenomena (MTP)

NASA Technical Reports Server (NTRS)

Mason, Larry

1996-01-01

Progress has been made in several areas of the definition, design, and development of the Membrane Transport Apparatus (MTA) instrument and associated sensors and systems. Progress is also reported in the development of software modules for instrument control, experimental image and data acquisition, and data analysis.

Detection of changes in semi-natural grasslands by cross correlation analysis with WorldView-2 images and new Landsat 8 data.

PubMed

Tarantino, Cristina; Adamo, Maria; Lucas, Richard; Blonda, Palma

2016-03-15

Focusing on a Mediterranean Natura 2000 site in Italy, the effectiveness of the cross correlation analysis (CCA) technique for quantifying change in the area of semi-natural grasslands at different spatial resolutions (grain) was evaluated. In a fine scale analysis (2 m), inputs to the CCA were a) a semi-natural grasslands layer extracted from an existing validated land cover/land use (LC/LU) map (1:5000, time T 1 ) and b) a more recent single date very high resolution (VHR) WorldView-2 image (time T 2 ), with T 2  > T 1 . The changes identified through the CCA were compared against those detected by applying a traditional post-classification comparison (PCC) technique to the same reference T 1 map and an updated T 2 map obtained by a knowledge driven classification of four multi-seasonal Worldview-2 input images. Specific changes observed were those associated with agricultural intensification and fires. The study concluded that prior knowledge (spectral class signatures, awareness of local agricultural practices and pressures) was needed for the selection of the most appropriate image (in terms of seasonality) to be acquired at T 2 . CCA was also applied to the comparison of the existing T 1 map with recent high resolution (HR) Landsat 8 OLS images. The areas of change detected at VHR and HR were broadly similar with larger error values in HR change images.

Inferring diagnosis and trajectory of wet age-related macular degeneration from OCT imagery of retina

NASA Astrophysics Data System (ADS)

Irvine, John M.; Ghadar, Nastaran; Duncan, Steve; Floyd, David; O'Dowd, David; Lin, Kristie; Chang, Tom

2017-03-01

Quantitative biomarkers for assessing the presence, severity, and progression of age-related macular degeneration (AMD) would benefit research, diagnosis, and treatment. This paper explores development of quantitative biomarkers derived from OCT imagery of the retina. OCT images for approximately 75 patients with Wet AMD, Dry AMD, and no AMD (healthy eyes) were analyzed to identify image features indicative of the patients' conditions. OCT image features provide a statistical characterization of the retina. Healthy eyes exhibit a layered structure, whereas chaotic patterns indicate the deterioration associated with AMD. Our approach uses wavelet and Frangi filtering, combined with statistical features that do not rely on image segmentation, to assess patient conditions. Classification analysis indicates clear separability of Wet AMD from other conditions, including Dry AMD and healthy retinas. The probability of correct classification of was 95.7%, as determined from cross validation. Similar classification analysis predicts the response of Wet AMD patients to treatment, as measured by the Best Corrected Visual Acuity (BCVA). A statistical model predicts BCVA from the imagery features with R2 = 0.846. Initial analysis of OCT imagery indicates that imagery-derived features can provide useful biomarkers for characterization and quantification of AMD: Accurate assessment of Wet AMD compared to other conditions; image-based prediction of outcome for Wet AMD treatment; and features derived from the OCT imagery accurately predict BCVA; unlike many methods in the literature, our techniques do not rely on segmentation of the OCT image. Next steps include larger scale testing and validation.

Multispectral imaging based on a Smartphone with an external C-MOS camera for detection of seborrheic dermatitis on the scalp

NASA Astrophysics Data System (ADS)

Kim, Manjae; Kim, Sewoong; Hwang, Minjoo; Kim, Jihun; Je, Minkyu; Jang, Jae Eun; Lee, Dong Hun; Hwang, Jae Youn

2017-02-01

To date, the incident rates of various skin diseases have increased due to hereditary and environmental factors including stress, irregular diet, pollution, etc. Among these skin diseases, seborrheic dermatitis and psoriasis are a chronic/relapsing dermatitis involving infection and temporary alopecia. However, they typically exhibit similar symptoms, thus resulting in difficulty in discrimination between them. To prevent their associated complications and appropriate treatments for them, it is crucial to discriminate between seborrheic dermatitis and psoriasis with high specificity and sensitivity and further continuously/quantitatively to monitor the skin lesions during their treatment at other locations besides a hospital. Thus, we here demonstrate a mobile multispectral imaging system connected to a smartphone for selfdiagnosis of seborrheic dermatitis and further discrimination between seborrheic dermatitis and psoriasis on the scalp, which is the more challenging case. Using the system developed, multispectral imaging and analysis of seborrheic dermatitis and psoriasis on the scalp was carried out. It was here found that the spectral signatures of seborrheic dermatitis and psoriasis were discernable and thus seborrheic dermatitis on the scalp could be distinguished from psoriasis by using the system. In particular, the smartphone-based multispectral imaging and analysis moreover offered better discrimination between seborrheic dermatitis and psoriasis than the RGB imaging and analysis. These results suggested that the multispectral imaging system based on a smartphone has the potential for self-diagnosis of seborrheic dermatitis with high portability and specificity.

Converging evidence for abnormalities of the prefrontal cortex and evaluation of midsagittal structures in pediatric PTSD: an MRI study

PubMed Central

Carrion, Victor G.; Weems, Carl F.; Watson, Christa; Eliez, Stephan; Menon, Vinod; Reiss, Allan L.

2009-01-01

Objective Volumetric imaging research has shown abnormal brain morphology in posttraumatic stress disorder (PTSD) when compared to controls. We present results on a study of brain morphology in the prefrontal cortex (PFC) and midline structures, via indices of gray matter volume and density, in pediatric PTSD. We hypothesized that both methods would demonstrate aberrant morphology in the PFC. Further, we hypothesized aberrant brainstem anatomy and reduced corpus collosum volume in children with PTSD. Methods Twenty-four children (aged 7-14) with history of interpersonal trauma and 24 age, and gender matched controls underwent structural magnetic resonance imaging. Images of the PFC and midline brain structures were first analyzed using volumetric image analysis. The PFC data were then compared with whole-brain voxel-based techniques using statistical parametric mapping (SPM). Results The PTSD group showed significant increased gray matter volume in the right and left inferior and superior quadrants of the prefrontal cortex and smaller gray matter volume in pons, and posterior vermis areas by volumetric image analysis. The voxel-byvoxel group comparisons demonstrated increased gray matter density mostly localized to ventral PFC as compared to the control group. Conclusions Abnormal frontal lobe morphology, as revealed by separate-complementary image analysis methods, and reduced pons and posterior vermis areas are associated with pediatric PTSD. Voxel-based morphometry may help to corroborate and further localize data obtained by volume of interest methods in PTSD. PMID:19349151

Hurricane Maria Puerto Rico Landsat Analysis

DOE Data Explorer

Feng, Yanlei; Chambers, Jeff [LBNL; Negron-Juarez, Robinson [LBNL; Patricola, Chris; Clinton, Nick; Uriarte, Maria; Hall, Jaz; Collins, William

2018-01-01

Hurricane Maria made landfall as a strong Category 4 storm in southeast Puerto Rico on September 20th, 2018. The powerful storm traversed the island in a northwesterly direction causing widespread destruction. This study focused on a rapid assessment of Hurricane Marias impact to Puerto Ricos forests. Calibrated and corrected Landsat 8 image composites for the entire island were generated using Google Earth Engine for a comparable pre-Maria and post-Maria time period that accounted for phenology. Spectral mixture analysis (SMA) using image-derived end members was carried out on both composites to calculate the change in the non-photosynthetic vegetation (Delta-NPV) spectral response, a metric that quantifies the increased fraction of exposed wood and surface litter associated with tree mortality and crown damage from the storm. Hurricane simulations were also conducted using the Weather Research and Forecasting (WRF) regional climate model to estimate wind speeds associated with forest disturbance. Dramatic changes in forest structure across the entire island were evident from pre- and post-Maria composited Landsat 8 images. A Delta-NPV map for only the forested pixels illustrated significant spatial variability in disturbance, with patterns that associated with factors such as slope, aspect and elevation. An initial order-of-magnitude impact estimate based on previous work indicated that Hurricane Maria may have caused mortality and severe damage to 23-31 million trees. Additional field work and image analyses are required to further detail the impact of Hurricane Maria to Puerto Rico forests. A minor update to this dataset was posted on April 20, 2018. The previous version is being retired. If you need access to the prior version of the data, email ngee-tropics-archive@lbl.gov.

Near-Infrared Spectroscopy Enhances Intravascular Ultrasound Assessment of Vulnerable Coronary Plaque: A Combined Pathological and In Vivo Study.

PubMed

Puri, Rishi; Madder, Ryan D; Madden, Sean P; Sum, Stephen T; Wolski, Kathy; Muller, James E; Andrews, Jordan; King, Karilane L; Kataoka, Yu; Uno, Kiyoko; Kapadia, Samir R; Tuzcu, E Murat; Nissen, Steven E; Virmani, Renu; Maehara, Akiko; Mintz, Gary S; Nicholls, Stephen J

2015-11-01

Pathological studies demonstrate the dual significance of plaque burden (PB) and lipid composition for mediating coronary plaque vulnerability. We evaluated relationships between intravascular ultrasound (IVUS)-derived PB and arterial remodeling with near-infrared spectroscopy (NIRS)-derived lipid content in ex vivo and in vivo human coronary arteries. Ex vivo coronary NIRS and IVUS imaging was performed through blood in 116 coronary arteries of 51 autopsied hearts, followed by 2-mm block sectioning (n=2070) and histological grading according to modified American Heart Association criteria. Lesions were defined as the most heavily diseased 2-mm block per imaged artery on IVUS. IVUS-derived PB and NIRS-derived lipid core burden index (LCBI) of each block and lesion were analyzed. Block-level analysis demonstrated significant trends of increasing PB and LCBI across more complex atheroma (Ptrend <0.001 for both LCBI and PB). Lesion-based analyses demonstrated the highest LCBI and remodeling index within coronary fibroatheroma (Ptrend <0.001 and 0.02 versus all plaque groups, respectively). Prediction models demonstrated similar abilities of PB, LCBI, and remodeling index for discriminating fibroatheroma (c indices: 0.675, 0.712, and 0.672, respectively). A combined PB+LCBI analysis significantly improved fibroatheroma detection accuracy (c index 0.77, P=0.028 versus PB; net-reclassification index 43%, P=0.003), whereas further adding remodeling index did not (c index 0.80, P=0.27 versus PB+LCBI). In vivo comparisons of 43 age- and sex-matched patients (to the autopsy cohort) undergoing combined NIRS-IVUS coronary imaging yielded similar associations to those demonstrated ex vivo. Adding NIRS to conventional IVUS-derived PB imaging significantly improves the ability to detect more active, potentially vulnerable coronary atheroma. © 2015 American Heart Association, Inc.

Fluorescence endoscopic imaging for evaluation of gastric mucosal blood flow: a preliminary study

NASA Astrophysics Data System (ADS)

Bocquillon, Nicolas; Mordon, Serge R.; Mathieu, D.; Maunoury, Vincent; Marechal, Xavier-Marie; Neviere, Remi; Wattel, Francis; Chopin, Claude

1999-02-01

Microcirculatory disorders of the gastrointestinal tract appear to be a major compound of the multiple organ dysfunction syndrome secondary to sepsis or septic shock. A better analysis of mucosal hypoperfusion in critically ill patients with sepsis may be helpful for the comprehension of this high mortality-associated syndrome. Fluorescence endoscopy has been recognized as a non-invasive method for both spatial and temporal evaluation of gastrointestinal mucosal perfusion. We performed this imaging technique during routine gastric endoscopy in patients with sepsis criteria. The study included gastric observation and appearance time of gastric fluorescence after an intravenous 10% sodium - fluorescein bolus. Qualitative analysis of high fluorescence areas was compared with mucosal blood flow measurements by laser - Doppler flowmetry. We concluded that the fluorescence endoscopic imaging in critically ill patients with sepsis may reveal spacial and temporal differences in the mucosal microcirculation distribution.

Disability in physical education textbooks: an analysis of image content.

PubMed

Táboas-Pais, María Inés; Rey-Cao, Ana

2012-10-01

The aim of this paper is to show how images of disability are portrayed in physical education textbooks for secondary schools in Spain. The sample was composed of 3,316 images published in 36 textbooks by 10 publishing houses. A content analysis was carried out using a coding scheme based on categories employed in other similar studies and adapted to the requirements of this study with additional categories. The variables were camera angle, gender, type of physical activity, field of practice, space, and level. Univariate and bivariate descriptive analyses were also carried out. The Pearson chi-square statistic was used to identify associations between the variables. Results showed a noticeable imbalance between people with disabilities and people without disabilities, and women with disabilities were less frequently represented than men with disabilities. People with disabilities were depicted as participating in a very limited variety of segregated, competitive, and elite sports activities.

Self-organizing maps: a versatile tool for the automatic analysis of untargeted imaging datasets.

PubMed

Franceschi, Pietro; Wehrens, Ron

2014-04-01

MS-based imaging approaches allow for location-specific identification of chemical components in biological samples, opening up possibilities of much more detailed understanding of biological processes and mechanisms. Data analysis, however, is challenging, mainly because of the sheer size of such datasets. This article presents a novel approach based on self-organizing maps, extending previous work in order to be able to handle the large number of variables present in high-resolution mass spectra. The key idea is to generate prototype images, representing spatial distributions of ions, rather than prototypical mass spectra. This allows for a two-stage approach, first generating typical spatial distributions and associated m/z bins, and later analyzing the interesting bins in more detail using accurate masses. The possibilities and advantages of the new approach are illustrated on an in-house dataset of apple slices. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Measurement of Galactic Logarithmic Spiral Arm Pitch Angle Using Two-Dimensional Fast Fourier Transform Decomposition

NASA Astrophysics Data System (ADS)

Davis, Benjamin L.; Berrier, J. C.; Shields, D. W.; Kennefick, J.; Kennefick, D.; Seigar, M. S.; Lacy, C. H. S.; Puerari, I.

2012-01-01

A logarithmic spiral is a prominent feature appearing in a majority of observed galaxies. This feature has long been associated with the traditional Hubble classification scheme, but historical quotes of pitch angle of spiral galaxies have been almost exclusively qualitative. We have developed a methodology, utilizing Two-Dimensional Fast Fourier Transformations of images of spiral galaxies, in order to isolate and measure the pitch angles of their spiral arms. Our technique provides a quantitative way to measure this morphological feature. This will allow the precise comparison of spiral galaxy evolution to other galactic parameters and test spiral arm genesis theories. In this work, we detail our image processing and analysis of spiral galaxy images and discuss the robustness of our analysis techniques. The authors gratefully acknowledge support for this work from NASA Grant NNX08AW03A.

Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis

NASA Astrophysics Data System (ADS)

Pu, Huangsheng; Zhang, Guanglei; He, Wei; Liu, Fei; Guang, Huizhi; Zhang, Yue; Bai, Jing; Luo, Jianwen

2014-09-01

It is a challenging problem to resolve and identify drug (or non-specific fluorophore) distribution throughout the whole body of small animals in vivo. In this article, an algorithm of unmixing multispectral fluorescence tomography (MFT) images based on independent component analysis (ICA) is proposed to solve this problem. ICA is used to unmix the data matrix assembled by the reconstruction results from MFT. Then the independent components (ICs) that represent spatial structures and the corresponding spectrum courses (SCs) which are associated with spectral variations can be obtained. By combining the ICs with SCs, the recovered MFT images can be generated and fluorophore concentration can be calculated. Simulation studies, phantom experiments and animal experiments with different concentration contrasts and spectrum combinations are performed to test the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can not only provide the spatial information of fluorophores, but also recover the actual reconstruction of MFT images.

Prevalence of Imaging Biomarkers to Guide the Planning of Acute Stroke Reperfusion Trials.

PubMed

Jiang, Bin; Ball, Robyn L; Michel, Patrik; Jovin, Tudor; Desai, Manisha; Eskandari, Ashraf; Naqvi, Zack; Wintermark, Max

2017-06-01

Imaging biomarkers are increasingly used as selection criteria for stroke clinical trials. The goal of our study was to determine the prevalence of commonly studied imaging biomarkers in different time windows after acute ischemic stroke onset to better facilitate the design of stroke clinical trials using such biomarkers for patient selection. This retrospective study included 612 patients admitted with a clinical suspicion of acute ischemic stroke with symptom onset no more than 24 hours before completing baseline imaging. Patients with subacute/chronic/remote infarcts and hemorrhage were excluded from this study. Imaging biomarkers were extracted from baseline imaging, which included a noncontrast head computed tomography (CT), perfusion CT, and CT angiography. The prevalence of dichotomized versions of each of the imaging biomarkers in several time windows (time since symptom onset) was assessed and statistically modeled to assess time dependence (not lack thereof). We created tables showing the prevalence of the imaging biomarkers pertaining to the core, the penumbra and the arterial occlusion for different time windows. All continuous imaging features vary over time. The dichotomized imaging features that vary significantly over time include: noncontrast head computed tomography Alberta Stroke Program Early CT (ASPECT) score and dense artery sign, perfusion CT infarct volume, and CT angiography collateral score and visible clot. The dichotomized imaging features that did not vary significantly over time include the thresholded perfusion CT penumbra volumes. As part of the feasibility analysis in stroke clinical trials, this analysis and the resulting tables can help investigators determine sample size and the number needed to screen. © 2017 American Heart Association, Inc.

Body image and college women's quality of life: The importance of being self-compassionate.

PubMed

Duarte, Cristiana; Ferreira, Cláudia; Trindade, Inês A; Pinto-Gouveia, José

2015-06-01

This study explored self-compassion as a mediator between body dissatisfaction, social comparison based on body image and quality of life in 662 female college students. Path analysis revealed that while controlling for body mass index, self-compassion mediated the impact of body dissatisfaction and unfavourable social comparisons on psychological quality of life. The path model accounted for 33 per cent of psychological quality of life variance. Findings highlight the importance of self-compassion as a mechanism that may operate on the association between negative body image evaluations and young women's quality of life. © The Author(s) 2015.

SLAR image interpretation keys for geographic analysis

NASA Technical Reports Server (NTRS)

Coiner, J. C.

1972-01-01

A means for side-looking airborne radar (SLAR) imagery to become a more widely used data source in geoscience and agriculture is suggested by providing interpretation keys as an easily implemented interpretation model. Interpretation problems faced by the researcher wishing to employ SLAR are specifically described, and the use of various types of image interpretation keys to overcome these problems is suggested. With examples drawn from agriculture and vegetation mapping, direct and associate dichotomous image interpretation keys are discussed and methods of constructing keys are outlined. Initial testing of the keys, key-based automated decision rules, and the role of the keys in an information system for agriculture are developed.

CoBOP: Electro-Optic Identification Laser Line Sean Sensors

DTIC Science & Technology

1998-01-01

Electro - Optic Identification Sensors Project[1] is to develop and demonstrate high resolution underwater electro - optic (EO) imaging sensors, and associated image processing/analysis methods, for rapid visual identification of mines and mine-like contacts (MLCs). Identification of MLCs is a pressing Fleet need. During MCM operations, sonar contacts are classified as mine-like if they are sufficiently similar to signatures of mines. Each contact classified as mine-like must be identified as a mine or not a mine. During MCM operations in littoral areas,

Scanning fluorescent microthermal imaging apparatus and method

DOEpatents

Barton, D.L.; Tangyunyong, P.

1998-01-06

A scanning fluorescent microthermal imaging (FMI) apparatus and method is disclosed, useful for integrated circuit (IC) failure analysis, that uses a scanned and focused beam from a laser to excite a thin fluorescent film disposed over the surface of the IC. By collecting fluorescent radiation from the film, and performing point-by-point data collection with a single-point photodetector, a thermal map of the IC is formed to measure any localized heating associated with defects in the IC. 1 fig.

NGEE Arctic TIR and Digital Photos, Drained Thaw Lake Basin, Barrow, Alaska, July 2015

DOE Data Explorer

Shawn Serbin; Wil Lieberman-Cribbin; Kim Ely; Alistair Rogers

2016-11-01

FLIR thermal infrared (TIR), digital camera photos, and plot notes across the Barrow, Alaska DTLB site. Data were collected together with measurements of canopy spectral reflectance (see associated metadata record (NGEE Arctic HR1024i Canopy Spectral Reflectance, Drained Thaw Lake Basin, Barrow, Alaska, July 2015 ). Data contained within this archive include exported FLIR images (analyzed with FLIR-Tools), digital photos, TIR report, and sample notes. Further TIR image analysis can be conducted in FLIR-Tools.

Factors associated with mixed dementia vs Alzheimer disease in elderly Mexican adults.

PubMed

Moreno Cervantes, C; Mimenza Alvarado, A; Aguilar Navarro, S; Alvarado Ávila, P; Gutiérrez Gutiérrez, L; Juárez Arellano, S; Ávila Funes, J A

2017-06-01

Mixed dementia (DMix) refers to dementia resulting from Alzheimer disease in addition to cerebrovascular disease. The study objectives were to determine the clinical and imaging factors associated with Dmix and compare them to those associated with Alzheimer disease. Cross-sectional study including 225 subjects aged 65 years and over from a memory clinic in a tertiary hospital in Mexico City. All patients underwent clinical, neuropsychological, and brain imaging studies. We included patients diagnosed with DMix or Alzheimer disease (AD). A multivariate analysis was used to determine factors associated with DMix. We studied 137 subjects diagnosed with Dmix. Compared to patients with AD, Dmix patients were older and more likely to present diabetes, hypertension, dyslipidaemia, and history of cerebrovascular disease (P<.05). The multivariate analysis showed that hypertension (OR 1.92, CI 1.62-28.82; P=.009), white matter disease (OR 3.61, CI 8.55-159.80; P<.001), and lacunar infarcts (OR 3.35, CI 1.97-412.34; P=.014) were associated with Dmix, whereas a history of successfully treated depression showed an inverse association (OR 0.11, CI 0.02-0-47; P=.004) CONCLUSIONS: DMix may be more frequent than AD. Risk factors such as advanced age and other potentially modifiable factors were associated with this type of dementia. Clinicians should understand and be able to define Dmix. Copyright © 2016 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Dynamic contrast–enhanced magnetic resonance imaging in patients with pulmonary arterial hypertension

PubMed Central

Condliffe, Robin; Marshall, Helen; Elliot, Charlie; Kiely, David G.; Wild, Jim M.

2014-01-01

Abstract Dynamic contrast–enhanced (DCE) time-resolved magnetic resonance (MR) imaging is a technique whereby the passage of an intravenous contrast bolus can be tracked through the pulmonary vascular system. The aim of this study was to investigate the prognostic significance of DCE-MR pulmonary blood transit times in patients with pulmonary arterial hypertension (PAH). Seventy-nine patients diagnosed with PAH underwent pulmonary DCE imaging at 1.5 T using a time-resolved three-dimensional spoiled gradient echo sequence. The prognostic significance of two DCE parameters, full width at half maximum (FWHM) of the first-pass clearance curve and pulmonary transit time (PTT), along with demographic and invasive catheter measurements, was evaluated by univariate and bivariate Cox proportional hazards regression and Kaplan-Meier analysis. DCE-MR transit times were most closely correlated with cardiac index (CI) and pulmonary vascular resistance index (PVRI) and were both found to be accurate for detecting reduced CI (FWHM area under the curve [AUC] at receiver operating characteristic analysis = 0.91 and PTT AUC = 0.92, respectively) and for detecting elevated PVRI (FWHM AUC = 0.88 and PTT AUC = 0.84, respectively). During the follow-up period, 25 patients died. Patients with longer measurements of FWHM (P = 0.0014) and PTT (P = 0.004) were associated with poor outcome at Kaplan-Meier analysis, and both parameters were strong predictors of adverse outcome from Cox proportional hazards analysis (P = 0.013 and 0.010, respectively). At bivariate analysis, DCE measurements predicted mortality independent of age, gender, and World Health Organization functional class; however, invasive hemodynamic indexes CI, PVRI, and DCE measurements were not independent of one another. In conclusion, DCE-MR transit times predict mortality in patients with PAH and are closely associated with clinical gold standards CI and PVRI. PMID:25006422

Dynamic contrast-enhanced magnetic resonance imaging in patients with pulmonary arterial hypertension.

PubMed

Swift, Andrew J; Telfer, Adam; Rajaram, Smitha; Condliffe, Robin; Marshall, Helen; Capener, Dave; Hurdman, Judith; Elliot, Charlie; Kiely, David G; Wild, Jim M

2014-03-01

Dynamic contrast-enhanced (DCE) time-resolved magnetic resonance (MR) imaging is a technique whereby the passage of an intravenous contrast bolus can be tracked through the pulmonary vascular system. The aim of this study was to investigate the prognostic significance of DCE-MR pulmonary blood transit times in patients with pulmonary arterial hypertension (PAH). Seventy-nine patients diagnosed with PAH underwent pulmonary DCE imaging at 1.5 T using a time-resolved three-dimensional spoiled gradient echo sequence. The prognostic significance of two DCE parameters, full width at half maximum (FWHM) of the first-pass clearance curve and pulmonary transit time (PTT), along with demographic and invasive catheter measurements, was evaluated by univariate and bivariate Cox proportional hazards regression and Kaplan-Meier analysis. DCE-MR transit times were most closely correlated with cardiac index (CI) and pulmonary vascular resistance index (PVRI) and were both found to be accurate for detecting reduced CI (FWHM area under the curve [AUC] at receiver operating characteristic analysis = 0.91 and PTT AUC = 0.92, respectively) and for detecting elevated PVRI (FWHM AUC = 0.88 and PTT AUC = 0.84, respectively). During the follow-up period, 25 patients died. Patients with longer measurements of FWHM (P = 0.0014) and PTT (P = 0.004) were associated with poor outcome at Kaplan-Meier analysis, and both parameters were strong predictors of adverse outcome from Cox proportional hazards analysis (P = 0.013 and 0.010, respectively). At bivariate analysis, DCE measurements predicted mortality independent of age, gender, and World Health Organization functional class; however, invasive hemodynamic indexes CI, PVRI, and DCE measurements were not independent of one another. In conclusion, DCE-MR transit times predict mortality in patients with PAH and are closely associated with clinical gold standards CI and PVRI.

White matter microstructure and developmental improvement of hyperactive/impulsive symptoms in attention-deficit/hyperactivity disorder.

PubMed

Francx, Winke; Zwiers, Marcel P; Mennes, Maarten; Oosterlaan, Jaap; Heslenfeld, Dirk; Hoekstra, Pieter J; Hartman, Catharina A; Franke, Barbara; Faraone, Stephen V; O'Dwyer, Laurence; Buitelaar, Jan K

2015-12-01

A developmental improvement of symptoms in attention-deficit/hyperactivity disorder (ADHD) is frequently reported, but the underlying neurobiological substrate has not been identified. The aim of this study was to determine whether white matter microstructure is related to developmental improvement of ADHD symptoms. A cross-sectional magnetic resonance imaging (MRI) analysis was embedded in a prospective follow-up of an adolescent cohort of ADHD and control subjects (NeuroIMAGE). Mean age at baseline was 11.9 years, mean interval of follow-up was 5.9 years. About 75.3% of the original cohort was retained successfully. Data of 101 participants with ADHD combined type at baseline and 40 healthy controls were analysed. ADHD symptoms were measured with semistructured, investigator-based interviews and Conners' questionnaires, on the basis of DSM-IV criteria. Fractional anisotropy (FA) and mean diffusivity (MD) indices of white matter microstructure were measured using whole brain diffusion tensor imaging at follow-up only. In a dimensional analysis FA and MD were related to change in ADHD symptoms. To link this analysis to DSM-IV diagnoses, a post hoc categorical group analysis was conducted comparing participants with persistent (n = 59) versus remittent (n = 42) ADHD and controls. Over time, participants with ADHD showed improvement mainly in hyperactive/impulsive symptoms. This improvement was associated with lower FA and higher MD values in the left corticospinal tract at follow-up. Findings of the dimensional and the categorical analysis strongly converged. Changes in inattentive symptoms over time were minimal and not related to white matter microstructure. The corticospinal tract is important in the control of voluntary movements, suggesting the importance of the motor system in the persistence of hyperactive/impulsive symptoms. © 2015 Association for Child and Adolescent Mental Health.

Discrimination of iron ore deposits of granulite terrain of Southern Peninsular India using ASTER data

NASA Astrophysics Data System (ADS)

Rajendran, Sankaran; Thirunavukkarasu, A.; Balamurugan, G.; Shankar, K.

2011-04-01

This work describes a new image processing technique for discriminating iron ores (magnetite quartzite deposits) and associated lithology in high-grade granulite region of Salem, Southern Peninsular India using visible, near-infrared and short wave infrared reflectance data of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Image spectra show that the magnetite quartzite and associated lithology of garnetiferrous pyroxene granulite, hornblende biotite gneiss, amphibolite, dunite, and pegmatite have absorption features around spectral bands 1, 3, 5, and 7. ASTER band ratios ((1 + 3)/2, (3 + 5)/4, (5 + 7)/6) in RGB are constructed by summing the bands representing the shoulders of absorption features as a numerator, and the band located nearest the absorption feature as a denominator to map iron ores and band ratios ((2 + 4)/3, (5 + 7)/6, (7 + 9)/8) in RGB for associated lithology. The results show that ASTER band ratios ((1 + 3)/2, (3 + 5)/4, (5 + 7)/6) in a Red-Green-Blue (RGB) color combination identifies the iron ores much better than previously published ASTER band ratios analysis. A Principal Component Analysis (PCA) is applied to reduce redundant information in highly correlated bands. PCA (3, 2, and 1 for iron ores and 5, 4, 2 for granulite rock) in RGB enabled the discrimination between the iron ores and garnetiferrous pyroxene granulite rock. Thus, this image processing technique is very much suitable for discriminating the different types of rocks of granulite region. As outcome of the present work, the geology map of Salem region is provided based on the interpretation of ASTER image results and field verification work. It is recommended that the proposed methods have great potential for mapping of iron ores and associated lithology of granulite region with similar rock units of granulite regions of Southern Peninsular India. This work also demonstrates the ability of ASTER's to provide information on iron ores, which is valuable for mineral prospecting and exploration activities.

Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force

NASA Astrophysics Data System (ADS)

Sivalingam, Udhayaraj; Wels, Michael; Rempfler, Markus; Grosskopf, Stefan; Suehling, Michael; Menze, Bjoern H.

2016-03-01

In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing Active Contour Model-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the active contour model, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.

PubMed

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando; Treviño, Victor

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer

PubMed Central

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures. PMID:29596496

Diagnostic yield of cystoscopy in the evaluation of recurrent urinary tract infection in women.

PubMed

Pagano, Matthew J; Barbalat, Yanina; Theofanides, Marissa C; Edokpolo, Leonard; James, Maxwell B; Cooper, Kimberly L

2017-03-01

Due to a paucity of evidence-based guidelines, anecdotal practice patterns often dictate clinical management of recurrent urinary tract infection (UTI) in women. Our aim was to identify pathologic findings of the urinary tract through cystoscopy and imaging in women with recurrent UTI, and to determine if specific risk factors are associated with a higher rate of abnormal findings. In a single-institutional cohort, cystoscopy was performed for women with recurrent UTI between 1/2010 and 7/2014. All eligible patients were included in a maintained database and those with gross or microscopic hematuria were excluded. Abdominopelvic imaging was recommended and included in study data when completed. Associations between clinical risk factors (history of renal transplant, urogynecologic surgery, or urolithiasis) and abnormal findings were analyzed by Fisher's exact test. A total of 163 women (mean age 60.6 years) were included in final analysis. Abdominopelvic imaging was available in 133 (82%) cases. Cystoscopy identified 9 (5.5%) cases of significant clinical findings. Of these only 5 (3.8%) cases were uniquely identified on cystoscopy and missed on imaging modalities. When imaging was normal, cystoscopy was also normal in 94% of cases. The examined clinical risk factors were not associated with higher risk of abnormal cystoscopy (P = 0.49) or imaging (P = 0.42). Cystoscopy performed solely for recurrent UTI is low yield in patients with normal imaging studies, but a small number of abnormal findings may be missed by foregoing this element of the patient workup. No studied risk factor was predictive of an abnormal workup. Neurourol. Urodynam. 36:692-696, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies.

PubMed

Fornasaro, Stefano; Vicario, Annalisa; De Leo, Luigina; Bonifacio, Alois; Not, Tarcisio; Sergo, Valter

2018-05-14

Raman hyperspectral imaging is an emerging practice in biological and biomedical research for label free analysis of tissues and cells. Using this method, both spatial distribution and spectral information of analyzed samples can be obtained. The current study reports the first Raman microspectroscopic characterisation of colon tissues from patients with Coeliac Disease (CD). The aim was to assess if Raman imaging coupled with hyperspectral multivariate image analysis is capable of detecting the alterations in the biochemical composition of intestinal tissues associated with CD. The analytical approach was based on a multi-step methodology: duodenal biopsies from healthy and coeliac patients were measured and processed with Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). Based on the distribution maps and the pure spectra of the image constituents obtained from MCR-ALS, interesting biochemical differences between healthy and coeliac patients has been derived. Noticeably, a reduced distribution of complex lipids in the pericryptic space, and a different distribution and abundance of proteins rich in beta-sheet structures was found in CD patients. The output of the MCR-ALS analysis was then used as a starting point for two clustering algorithms (k-means clustering and hierarchical clustering methods). Both methods converged with similar results providing precise segmentation over multiple Raman images of studied tissues.

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

PubMed Central

Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano

2008-01-01

Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177

Semiquantitative analysis of atherosclerotic plaque using optical coherence tomography and time-of-flight secondary ion mass spectrometry

NASA Astrophysics Data System (ADS)

Korol, Renee M.; Togonu-Bickersteth, Babajide; Yang, Victor X.; Dimov, Stamen; Vatsya, Pracha; Gordon, Maggie; Vitkin, Alex; Liu, Liying; Canham, Peter; Clarke, Sharon; Lucas, Alexandra

2003-10-01

Atherosclerosis is the underlying vascular pathology that initiates arterial thromboembolic occlusions (myocardial infarctions, strokes and peripheral vessel blockage). Two imaging modalities, Optical Coherence Tomography (OCT) and Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS), were investigated for detection and compositional analysis of unstable plaque associated with plaque erosion and sudden occlusion. OCT produces high resolution images whereas mass spectrometry images provide information on the spatial distribution of chemical elements. Diseased carotid arteries taken from patients with high-risk lesions were imaged with OCT and ToF-SIMS to give molecular and metabolic information, and matched with histopathology. OCT results show clear indications of vascular remodeling by the presence of fatty acid deposits, fibrous tissue and calcifications. ToF-SIMS further characterized changes based on secondary ion topography analysis where a high 23Na/39K ratio was indicative of arterial tissue degradation and the amount of 40Ca corresponded with late stage atherosclerosis. This pilot experiment has demonstrated that in vitro OCT imaging and ToF-SIMS of diseased carotid arteries have scientific merit for targeting clinically relevant morphology and metabolic changes to compare stable and unstable plaque. These optical techniques provide complimentary metabolic and molecular information on unstable plaque, specifically cell break-down with altered ion ratios of 23Na, 39K and 40Ca.

Centered reduced moments and associate density functions applied to alkaline comet assay.

PubMed

Castaneda, Roman; Pelaez, Alejandro; Marquez, Maria-Elena; Abad, Pablo

2005-01-01

The single cell gel electrophoresis assay is a sensitive, rapid, and visual technique for deoxyribonucleic acid (DNA) strand-break detection in individual mammalian cells, whose application has significantly increased in the past few years. The cells are embedded in agarose on glass slides followed by lyses of the cell membrane. Thereafter, damaged DNA strands are electrophoresed away from the nucleus towards the anode giving the appearance of a comet tail. Nowadays, charge coupled device cameras are attached at optical microscopes for recording the images of the cells, and digital image processing is applied for obtaining quantitative descriptors. However, the conventional software is usually expensive, inflexible and, in many cases, can only provide low-order descriptors based in image segmentation, determination of centers of mass, and Euclidean distances. Associated density functions and centered reduced moments offer an effective and flexible alternative for quantitative analysis of the comet cells. We will show how the position of the center of mass, the lengths and orientation of the main semiaxes, and the eccentricity of such images can be accurately determined by this method.

"I don't need people to tell me I'm pretty on social media:" A qualitative study of social media and body image in early adolescent girls.

PubMed

Burnette, C Blair; Kwitowski, Melissa A; Mazzeo, Suzanne E

2017-12-01

Social media appear to contribute to body dissatisfaction in adolescents, although few empirical studies exist. This study used six focus groups (total N=38) to explore relations between social media use and body image in early adolescent girls (ages 12-14). Thematic analysis identified patterns in the data. In this sample, social media use was high. Girls endorsed some appearance concerns and social comparison, particularly with peers. However, they displayed high media literacy, appreciation of differences, and confidence, strategies that appeared helpful in mitigating the potential negative association between social media exposure and body image. Girls reported these characteristics were nurtured by positive parental influence and a supportive school environment. Results support an ecological approach to the prevention of body dissatisfaction. Although peer influence strengthens throughout adolescence, current findings suggest that parents and the school environment are associated with girls' attitudes and behaviors regarding social media and body image. Copyright © 2017 Elsevier Ltd. All rights reserved.

Time-Dependent Computed Tomographic Perfusion Thresholds for Patients With Acute Ischemic Stroke.

PubMed

d'Esterre, Christopher D; Boesen, Mari E; Ahn, Seong Hwan; Pordeli, Pooneh; Najm, Mohamed; Minhas, Priyanka; Davari, Paniz; Fainardi, Enrico; Rubiera, Marta; Khaw, Alexander V; Zini, Andrea; Frayne, Richard; Hill, Michael D; Demchuk, Andrew M; Sajobi, Tolulope T; Forkert, Nils D; Goyal, Mayank; Lee, Ting Y; Menon, Bijoy K

2015-12-01

Among patients with acute ischemic stroke, we determine computed tomographic perfusion (CTP) thresholds associated with follow-up infarction at different stroke onset-to-CTP and CTP-to-reperfusion times. Acute ischemic stroke patients with occlusion on computed tomographic angiography were acutely imaged with CTP. Noncontrast computed tomography and magnectic resonance diffusion-weighted imaging between 24 and 48 hours were used to delineate follow-up infarction. Reperfusion was assessed on conventional angiogram or 4-hour repeat computed tomographic angiography. Tmax, cerebral blood flow, and cerebral blood volume derived from delay-insensitive CTP postprocessing were analyzed using receiver-operator characteristic curves to derive optimal thresholds for combined patient data (pooled analysis) and individual patients (patient-level analysis) based on time from stroke onset-to-CTP and CTP-to-reperfusion. One-way ANOVA and locally weighted scatterplot smoothing regression was used to test whether the derived optimal CTP thresholds were different by time. One hundred and thirty-two patients were included. Tmax thresholds of >16.2 and >15.8 s and absolute cerebral blood flow thresholds of <8.9 and <7.4 mL·min(-1)·100 g(-1) were associated with infarct if reperfused <90 min from CTP with onset <180 min. The discriminative ability of cerebral blood volume was modest. No statistically significant relationship was noted between stroke onset-to-CTP time and the optimal CTP thresholds for all parameters based on discrete or continuous time analysis (P>0.05). A statistically significant relationship existed between CTP-to-reperfusion time and the optimal thresholds for cerebral blood flow (P<0.001; r=0.59 and 0.77 for gray and white matter, respectively) and Tmax (P<0.001; r=-0.68 and -0.60 for gray and white matter, respectively) parameters. Optimal CTP thresholds associated with follow-up infarction depend on time from imaging to reperfusion. © 2015 American Heart Association, Inc.

Diffusion-Tensor Imaging Findings and Cognitive Function Following Hospitalized Mixed-Mechanism Mild Traumatic Brain Injury: A Systematic Review and Meta-Analysis.

PubMed

Oehr, Lucy; Anderson, Jacqueline

2017-11-01

To undertake a systematic review and meta-analysis of the relationship between microstructural damage and cognitive function after hospitalized mixed-mechanism (HMM) mild traumatic brain injury (mTBI). PsycInfo, EMBASE, and MEDLINE were used to find relevant empirical articles published between January 2002 and January 2016. Studies that examined the specific relationship between diffusion tensor imaging (DTI) and cognitive test performance were included. The final sample comprised previously medically and psychiatrically healthy adults with HMM mTBI. Specific data were extracted including mTBI definitional criteria, descriptive statistics, outcome measures, and specific results of associations between DTI metrics and cognitive test performance. Of the 248 original articles retrieved and reviewed, 8 studies met all inclusion criteria and were included in the meta-analysis. The meta-analysis revealed statistically significant associations between reduced white matter integrity and poor performance on measures of attention (fractional anisotropy [FA]: d=.413, P<.001; mean diffusivity [MD]: d=-.407, P=.001), memory (FA: d=.347, P<.001; MD: d=-.568, P<.001), and executive function (FA: d=.246, P<.05), which persisted beyond 1 month postinjury. The findings from the meta-analysis provide clear support for an association between in vivo markers of underlying neuropathology and cognitive function after mTBI. Furthermore, these results demonstrate clearly for the first time that in vivo markers of structural neuropathology are associated with cognitive dysfunction within the domains of attention, memory, and executive function. These findings provide an avenue for future research to examine the causal relationship between mTBI-related neuropathology and cognitive dysfunction. Furthermore, they have important implications for clinical management of patients with mTBI because they provide a more comprehensive understanding of factors that are associated with cognitive dysfunction after mTBI. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John; Lui, Su

2017-12-05

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta­-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular ­gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia. 2017 Joule Inc., or its licensors

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2018-03-01

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2017-12-15

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.

WE-B-BRC-02: Risk Analysis and Incident Learning

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

Fraass, B.

Prospective quality management techniques, long used by engineering and industry, have become a growing aspect of efforts to improve quality management and safety in healthcare. These techniques are of particular interest to medical physics as scope and complexity of clinical practice continue to grow, thus making the prescriptive methods we have used harder to apply and potentially less effective for our interconnected and highly complex healthcare enterprise, especially in imaging and radiation oncology. An essential part of most prospective methods is the need to assess the various risks associated with problems, failures, errors, and design flaws in our systems. Wemore » therefore begin with an overview of risk assessment methodologies used in healthcare and industry and discuss their strengths and weaknesses. The rationale for use of process mapping, failure modes and effects analysis (FMEA) and fault tree analysis (FTA) by TG-100 will be described, as well as suggestions for the way forward. This is followed by discussion of radiation oncology specific risk assessment strategies and issues, including the TG-100 effort to evaluate IMRT and other ways to think about risk in the context of radiotherapy. Incident learning systems, local as well as the ASTRO/AAPM ROILS system, can also be useful in the risk assessment process. Finally, risk in the context of medical imaging will be discussed. Radiation (and other) safety considerations, as well as lack of quality and certainty all contribute to the potential risks associated with suboptimal imaging. The goal of this session is to summarize a wide variety of risk analysis methods and issues to give the medical physicist access to tools which can better define risks (and their importance) which we work to mitigate with both prescriptive and prospective risk-based quality management methods. Learning Objectives: Description of risk assessment methodologies used in healthcare and industry Discussion of radiation oncology-specific risk assessment strategies and issues Evaluation of risk in the context of medical imaging and image quality E. Samei: Research grants from Siemens and GE.« less

Multimodal Chemical Imaging of Amyloid Plaque Polymorphism Reveals Aβ Aggregation Dependent Anionic Lipid Accumulations and Metabolism.

PubMed

Michno, Wojciech; Kaya, Ibrahim; Nyström, Sofie; Guerard, Laurent; Nilsson, K Peter R; Hammarström, Per; Blennow, Kaj; Zetterberg, Henrik; Hanrieder, Jörg

2018-06-01

Amyloid plaque formation constitutes one of the main pathological hallmark of Alzheimer's disease (AD) and is suggested to be a critical factor driving disease pathogenesis. Interestingly, in patients that display amyloid pathology but remain cognitively normal, Aβ deposits are predominantly of diffuse morphology suggesting that cored plaque formation is primarily associated with cognitive deterioration and AD pathogenesis. Little is known about the molecular mechanism responsible for conversion of monomeric Aβ into neurotoxic aggregates and the predominantly cored deposits observed in AD. The structural diversity among Aβ plaques, including cored/compact- and diffuse, may be linked to their distinct Aβ profile and other chemical species including neuronal lipids. We developed a novel, chemical imaging paradigm combining matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) and fluorescent amyloid staining. This multimodal imaging approach was used to probe the lipid chemistry associated with structural plaque heterogeneity in transgenic AD mice (tgAPPSwe) and was correlated to Aβ profiles determined by subsequent laser microdissection and immunoprecipitation-mass spectrometry. Multivariate image analysis revealed an inverse localization of ceramides and their matching metabolites to diffuse and cored structures within single plaques, respectively. Moreover, phosphatidylinositols implicated in AD pathogenesis, were found to localise to the diffuse Aβ structures and correlate with Aβ1-42. Further, lysophospholipids implicated in neuroinflammation were increased in all Aβ deposits. The results support previous clinical findings on the importance of lipid disturbances in AD pathophysiology and associated sphingolipid processing. These data highlight the potential of multimodal imaging as a powerful technology to probe neuropathological mechanisms.

Magnetic Resonance Imaging Measurement of Transmission of Arterial Pulsation to the Brain on Propranolol Versus Amlodipine.

PubMed

Webb, Alastair J S; Rothwell, Peter M

2016-06-01

Cerebral arterial pulsatility is associated with leukoaraiosis and depends on central arterial pulsatility and arterial stiffness. The effect of antihypertensive drugs on transmission of central arterial pulsatility to the cerebral circulation is unknown, partly because of limited methods of assessment. In a technique-development pilot study, 10 healthy volunteers were randomized to crossover treatment with amlodipine and propranolol. At baseline and on each drug, we assessed aortic (Sphygmocor) and middle cerebral artery pulsatility (TCDtranscranial ultrasound). We also performed whole-brain, 3-tesla multiband blood-oxygen level dependent magnetic resonance imaging (multiband factor 6, repetition time=0.43s), concurrent with a novel method of continuous noninvasive blood pressure monitoring. Drug effects on relationships between cardiac cycle variation in blood pressure and blood-oxygen level dependent imaging were determined (fMRI Expert Analysis Tool, fMRIB Software Library [FEAT-FSL]). Aortic pulsatility was similar on amlodipine (27.3 mm Hg) and propranolol (27.9 mm Hg, P diff=0.33), while MCA pulsatility increased nonsignificantly more from baseline on propranolol (+6%; P=0.09) than amlodipine (+1.5%; P=0.58). On magnetic resonance imaging, cardiac frequency blood pressure variations were found to be significantly more strongly associated with blood-oxygen level dependent imaging on propranolol than amlodipine. We piloted a novel method of assessment of arterial pulsatility with concurrent high-frequency blood-oxygen level dependent magnetic resonance imaging and noninvasive blood pressure monitoring. This method was able to identify greater transmission of aortic pulsation on propranolol than amlodipine, which warrants further investigation. © 2016 American Heart Association, Inc.

Impact of imaging guidelines on X-ray use among American provider network chiropractors: interrupted time series analysis.

PubMed

Bussières, André E; Sales, Anne E; Ramsay, Timothy; Hilles, Steven M; Grimshaw, Jeremy M

2014-08-01

Overuse and misuse of spine X-ray imaging for nonspecific back and neck pain persists among chiropractors. Distribution of educational materials among physicians results in small-to-modest improvements in appropriate care, such as ordering spine X-ray studies, but little is known about its impact among North American chiropractors. To evaluate the impact of web-based dissemination of a diagnostic imaging guideline on the use of spine X-ray images among chiropractors. Quasi-experimental design that used interrupted time series to evaluate the effect of guidelines dissemination on spine X-ray imaging claims by chiropractors enlisted in managed care network in the United States. Consecutive adult patients consulting for complaints of spine disorders. A change in level (the mean number of spine X-ray imaging claims per month immediately after the introduction of the guidelines), change in trend (any differences between preintervention and postintervention slopes), estimation of monthly average intervention effect after the intervention. The imaging guideline was disseminated online in April 2008. Administrative claims data were extracted between January 2006 and December 2010. Segmented regression analysis with autoregressive error was used to estimate the impact of guideline recommendations on the rate of spine X-ray studies. Sensitivity analysis considered the effect of two additional quality improvement strategies, a policy change and an education intervention. Time series analysis revealed a significant change in the level of spine X-ray study ordering weeks after introduction of the guidelines (-0.01; 95% confidence interval=-0.01, -0.002; p=.01), but no change in trend of the regression lines. The monthly mean rate of spine X-ray studies within 5 days of initial visit per new patient exams decreased by 10 per 1000, a 5.26% relative decrease after guideline dissemination. Controlling for two quality improvement strategies did not change the results. Web-based guideline dissemination was associated with an immediate reduction in spine X-ray imaging claims. Sensitivity analysis suggests our results are robust. This passive strategy is likely cost-effective in a chiropractic network setting. Copyright © 2014 Elsevier Inc. All rights reserved.

Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

PubMed

Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

2017-08-01

The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

Differentiation between benign and malignant palatal tumors using conventional MRI: a retrospective analysis of 130 cases.

PubMed

Zheng, Yingyan; Xiao, Zebin; Zhang, Hua; She, Dejun; Lin, Xuehua; Lin, Yu; Cao, Dairong

2018-04-01

To evaluate the discriminative value of conventional magnetic resonance imaging between benign and malignant palatal tumors. Conventional magnetic resonance imaging features of 130 patients with palatal tumors confirmed by histopathologic examination were retrospectively reviewed. Clinical data and imaging findings were assessed between benign and malignant tumors and between benign and low-grade malignant salivary gland tumors. The variables that were significant in differentiating benign from malignant lesions were further identified using logistic regression analysis. Moreover, imaging features of each common palatal histologic entity were statistically analyzed with the rest of the tumors to define their typical imaging features. Older age, partially defined and ill-defined margins, and absence of a capsule were highly suggestive of malignant palatal tumors, especially ill-defined margins (β = 6.400). The precision in determining malignant palatal tumors achieved a sensitivity of 92.8% and a specificity of 85.6%. In addition, irregular shape, ill-defined margins, lack of a capsule, perineural spread, and invasion of surrounding structures were more often associated with low-grade malignant salivary gland tumors. Conventional magnetic resonance imaging is useful for differentiating benign from malignant palatal tumors as well as benign salivary gland tumors from low-grade salivary gland malignancies. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Gender and Ethnic Differences in the Association Between Body Image Dissatisfaction and Binge Eating Disorder among Blacks.

PubMed

Blostein, Freida; Assari, Shervin; Caldwell, Cleopatra Howard

2017-08-01

The research on binge eating has overwhelmingly focused on Whites. We aimed to study gender and ethnic differences in the association between body image dissatisfaction and binge eating in a nationally representative sample of Black adults in the USA. This cross-sectional study used data from the National Survey of American Life (NSAL), 2003-2004. Self-identified Caribbean Black (n = 1621) and African American (3570) adults aged 18 and older were enrolled. The independent variable was body dissatisfaction measured with two items. Using the World Health Organization Composite International Diagnostic Interview (WHO-CIDI), outcome was lifetime binge eating without hierarchy according to the DSM-IV criteria. Covariates included age, socioeconomic factors (i.e., education and marital status), and body mass index. Ethnicity and gender were focal moderators. Logistic regressions were used for data analysis. Despite comparable prevalence of lifetime binge eating (5 vs 4 %, p > 0.05), African Americans reported higher body image dissatisfaction than Caribbean Blacks (36 vs 29 %, p > 0.05). In the pooled sample, body dissatisfaction was a strong predictor of lifetime binge eating disorders. There was a significant interaction (p = 0.039) between ethnicity and body image dissatisfaction on binge eating, suggesting a stronger association between body image dissatisfaction and lifetime binge eating for Caribbean Blacks (OR = 11.65, 95 % 6.89-19.72) than African Americans (OR = 6.72, 95 % CI 3.97-11.37). Gender did not interact with body image dissatisfaction on binge eating. Ethnic variation in the link between body image dissatisfaction and binge eating may be due to within-race cultural differences in body image between African Americans and Caribbean Blacks. This may include different definitions, norms, and expectations regarding the body size. Findings suggest that ethnicity may bias relevance of body image dissatisfaction as a diagnostic criterion for binge eating disorders among diverse populations of Blacks.

Security of Color Image Data Designed by Public-Key Cryptosystem Associated with 2D-DWT

NASA Astrophysics Data System (ADS)

Mishra, D. C.; Sharma, R. K.; Kumar, Manish; Kumar, Kuldeep

2014-08-01

In present times the security of image data is a major issue. So, we have proposed a novel technique for security of color image data by public-key cryptosystem or asymmetric cryptosystem. In this technique, we have developed security of color image data using RSA (Rivest-Shamir-Adleman) cryptosystem with two-dimensional discrete wavelet transform (2D-DWT). Earlier proposed schemes for security of color images designed on the basis of keys, but this approach provides security of color images with the help of keys and correct arrangement of RSA parameters. If the attacker knows about exact keys, but has no information of exact arrangement of RSA parameters, then the original information cannot be recovered from the encrypted data. Computer simulation based on standard example is critically examining the behavior of the proposed technique. Security analysis and a detailed comparison between earlier developed schemes for security of color images and proposed technique are also mentioned for the robustness of the cryptosystem.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging Reveals Stress-Induced Angiogenesis in MCF7 Human Breast Tumors

NASA Astrophysics Data System (ADS)

Furman-Haran, Edna; Margalit, Raanan; Grobgeld, Dov; Degani, Hadassa

1996-06-01

The mechanism of contrast enhancement of tumors using magnetic resonance imaging was investigated in MCF7 human breast cancer implanted in nude mice. Dynamic contrast-enhanced images recorded at high spatial resolution were analyzed by an image analysis method based on a physiological model, which included the blood circulation, the tumor, the remaining tissues, and clearance via the kidneys. This analysis enabled us to map in rapidly enhancing regions within the tumor, the capillary permeability factor (capillary permeability times surface area per voxel volume) and the fraction of leakage space. Correlation of these maps with T2-weighted spin echo images, with histopathology, and with immunohistochemical staining of endothelial cells demonstrated the presence of dense permeable microcapillaries in the tumor periphery and in intratumoral regions that surrounded necrotic loci. The high leakage from the intratumoral permeable capillaries indicated an induction of a specific angiogenic process associated with stress conditions that cause necrosis. This induction was augmented in tumors responding to tamoxifen treatment. Determination of the distribution and extent of this stress-induced angiogenic activity by contrast-enhanced MRI might be of diagnostic and of prognostic value.

A study on using texture analysis methods for identifying lobar fissure regions in isotropic CT images.

PubMed

Wei, Q; Hu, Y

2009-01-01

The major hurdle for segmenting lung lobes in computed tomographic (CT) images is to identify fissure regions, which encase lobar fissures. Accurate identification of these regions is difficult due to the variable shape and appearance of the fissures, along with the low contrast and high noise associated with CT images. This paper studies the effectiveness of two texture analysis methods - the gray level co-occurrence matrix (GLCM) and the gray level run length matrix (GLRLM) - in identifying fissure regions from isotropic CT image stacks. To classify GLCM and GLRLM texture features, we applied a feed-forward back-propagation neural network and achieved the best classification accuracy utilizing 16 quantized levels for computing the GLCM and GLRLM texture features and 64 neurons in the input/hidden layers of the neural network. Tested on isotropic CT image stacks of 24 patients with the pathologic lungs, we obtained accuracies of 86% and 87% for identifying fissure regions using the GLCM and GLRLM methods, respectively. These accuracies compare favorably with surgeons/radiologists' accuracy of 80% for identifying fissure regions in clinical settings. This shows promising potential for segmenting lung lobes using the GLCM and GLRLM methods.

Nonlinear optical microscopy: use of second harmonic generation and two-photon microscopy for automated quantitative liver fibrosis studies.

PubMed

Sun, Wanxin; Chang, Shi; Tai, Dean C S; Tan, Nancy; Xiao, Guangfa; Tang, Huihuan; Yu, Hanry

2008-01-01

Liver fibrosis is associated with an abnormal increase in an extracellular matrix in chronic liver diseases. Quantitative characterization of fibrillar collagen in intact tissue is essential for both fibrosis studies and clinical applications. Commonly used methods, histological staining followed by either semiquantitative or computerized image analysis, have limited sensitivity, accuracy, and operator-dependent variations. The fibrillar collagen in sinusoids of normal livers could be observed through second-harmonic generation (SHG) microscopy. The two-photon excited fluorescence (TPEF) images, recorded simultaneously with SHG, clearly revealed the hepatocyte morphology. We have systematically optimized the parameters for the quantitative SHG/TPEF imaging of liver tissue and developed fully automated image analysis algorithms to extract the information of collagen changes and cell necrosis. Subtle changes in the distribution and amount of collagen and cell morphology are quantitatively characterized in SHG/TPEF images. By comparing to traditional staining, such as Masson's trichrome and Sirius red, SHG/TPEF is a sensitive quantitative tool for automated collagen characterization in liver tissue. Our system allows for enhanced detection and quantification of sinusoidal collagen fibers in fibrosis research and clinical diagnostics.

Semi-automated confocal imaging of fungal pathogenesis on plants: microscopic analysis of macroscopic specimens

USDA-ARS?s Scientific Manuscript database

Contextualizing natural genetic variation in plant disease resistance in terms of pathogenesis can provide information about the function of causal genes. Cellular mechanisms associated with pathogenesis can be elucidated with confocal microscopy, but systematic phenotyping platforms—from sample pro...

Single Aflatoxin Contaminated Corn Kernel Analysis with Fluorescence Hyperspectral Image

USDA-ARS?s Scientific Manuscript database

Aflatoxins are toxic secondary metabolites of the fungi Aspergillus flavus and Aspergillus parasiticus, among others. Aflatoxin contaminated corn is toxic to domestic animals when ingested in feed and is a known carcinogen associated with liver and lung cancer in humans. Consequently, aflatoxin leve...

Technical design and system implementation of region-line primitive association framework

NASA Astrophysics Data System (ADS)

Wang, Min; Xing, Jinjin; Wang, Jie; Lv, Guonian

2017-08-01

Apart from regions, image edge lines are an important information source, and they deserve more attention in object-based image analysis (OBIA) than they currently receive. In the region-line primitive association framework (RLPAF), we promote straight-edge lines as line primitives to achieve powerful OBIAs. Along with regions, straight lines become basic units for subsequent extraction and analysis of OBIA features. This study develops a new software system called remote-sensing knowledge finder (RSFinder) to implement RLPAF for engineering application purposes. This paper introduces the extended technical framework, a comprehensively designed feature set, key technology, and software implementation. To our knowledge, RSFinder is the world's first OBIA system based on two types of primitives, namely, regions and lines. It is fundamentally different from other well-known region-only-based OBIA systems, such as eCogntion and ENVI feature extraction module. This paper has important reference values for the development of similarly structured OBIA systems and line-involved extraction algorithms of remote sensing information.

Mapping Hydrothermal Alterations in the Muteh Gold Mining Area in Iran by using ASTER satellite Imagery data

NASA Astrophysics Data System (ADS)

Asadi Haroni, Hooshang; Hassan Tabatabaei, Seyed

2016-04-01

Muteh gold mining area is located in 160 km NW of Isfahan town. Gold mineralization is meso-thermal type and associated with silisic, seresitic and carbonate alterations as well as with hematite and goethite. Image processing and interpretation were applied on the ASTER satellite imagery data of about 400 km2 at the Muteh gold mining area to identify hydrothermal alterations and iron oxides associated with gold mineralization. After applying preprocessing methods such as radiometric and geometric corrections, image processing methods of Principal Components Analysis (PCA), Least Square Fit (Ls-Fit) and Spectral Angle Mapper (SAM) were applied on the ASTER data to identify hydrothermal alterations and iron oxides. In this research reference spectra of minerals such as chlorite, hematite, clay minerals and phengite identified from laboratory spectral analysis of collected samples were used to map the hydrothermal alterations. Finally, identified hydrothermal alteration and iron oxides were validated by visiting and sampling some of the mapped hydrothermal alterations.

Multivariate Associations Among Behavioral, Clinical, and Multimodal Imaging Phenotypes in Patients With Psychosis.

PubMed

Moser, Dominik A; Doucet, Gaelle E; Lee, Won Hee; Rasgon, Alexander; Krinsky, Hannah; Leibu, Evan; Ing, Alex; Schumann, Gunter; Rasgon, Natalie; Frangou, Sophia

2018-04-01

Alterations in multiple neuroimaging phenotypes have been reported in psychotic disorders. However, neuroimaging measures can be influenced by factors that are not directly related to psychosis and may confound the interpretation of case-control differences. Therefore, a detailed characterization of the contribution of these factors to neuroimaging phenotypes in psychosis is warranted. To quantify the association between neuroimaging measures and behavioral, health, and demographic variables in psychosis using an integrated multivariate approach. This imaging study was conducted at a university research hospital from June 26, 2014, to March 9, 2017. High-resolution multimodal magnetic resonance imaging data were obtained from 100 patients with schizophrenia, 40 patients with bipolar disorder, and 50 healthy volunteers; computed were cortical thickness, subcortical volumes, white matter fractional anisotropy, task-related brain activation (during working memory and emotional recognition), and resting-state functional connectivity. Ascertained in all participants were nonimaging measures pertaining to clinical features, cognition, substance use, psychological trauma, physical activity, and body mass index. The association between imaging and nonimaging measures was modeled using sparse canonical correlation analysis with robust reliability testing. Multivariate patterns of the association between nonimaging and neuroimaging measures in patients with psychosis and healthy volunteers. The analyses were performed in 92 patients with schizophrenia (23 female [25.0%]; mean [SD] age, 27.0 [7.6] years), 37 patients with bipolar disorder (12 female [32.4%]; mean [SD] age, 27.5 [8.1] years), and 48 healthy volunteers (20 female [41.7%]; mean [SD] age, 29.8 [8.5] years). The imaging and nonimaging data sets showed significant covariation (r = 0.63, P < .001), which was independent of diagnosis. Among the nonimaging variables examined, age (r = -0.53), IQ (r = 0.36), and body mass index (r = -0.25) were associated with multiple imaging phenotypes; cannabis use (r = 0.23) and other substance use (r = 0.33) were associated with subcortical volumes, and alcohol use was associated with white matter integrity (r = -0.15). Within the multivariate models, positive symptoms retained associations with the global neuroimaging (r = -0.13), the cortical thickness (r = -0.22), and the task-related activation variates (r = -0.18); negative symptoms were mostly associated with measures of subcortical volume (r = 0.23), and depression/anxiety was associated with measures of white matter integrity (r = 0.12). Multivariate analyses provide a more accurate characterization of the association between brain alterations and psychosis because they enable the modeling of other key factors that influence neuroimaging phenotypes.

Fuller's earth (montmorillonite) pneumoconiosis.

PubMed Central

Gibbs, A R; Pooley, F D

1994-01-01

A fuller's earth worker developed signs of pneumoconiosis. Pathological examination of the lung tissues showed interstitial collections of dust laden macrophages associated with mild fibrosis. Mineralogical analysis showed a high content of montmorillonite. This study shows that a pneumoconiosis can result from prolonged heavy exposure to calcium montmorillonite (fuller's earth) in the absence of quartz. The disease is relatively mild and associated with little clinical disability. Images Figure 1 Figure 2 PMID:7951799

Lumbar subcutaneous edema and degenerative spinal disease in patients with low back pain: a retrospective MRI study.

PubMed

Quattrocchi, C C; Giona, A; Di Martino, A; Gaudino, F; Mallio, C A; Errante, Y; Occhicone, F; Vitali, M A; Zobel, B B; Denaro, V

2015-08-01

This study was designed to determine the association between LSE, spondylolisthesis, facet arthropathy, lumbar canal stenosis, BMI, radiculopathy and bone marrow edema at conventional lumbar spine MR imaging. This is a retrospective radiological study; 441 consecutive patients with low back pain (224 men and 217 women; mean age 57.3 years; mean BMI 26) underwent conventional lumbar MRI using a 1.5-T magnet (Avanto, Siemens). Lumbar MR images were reviewed by consensus for the presence of LSE, spondylolisthesis, facet arthropathy, lumbar canal stenosis, radiculopathy and bone marrow edema. Descriptive statistics and association studies were conducted using STATA software 11.0. Association studies have been performed using linear univariate regression analysis and multivariate regression analysis, considering LSE as response variable. The overall prevalence of LSE was 40%; spondylolisthesis (p = 0.01), facet arthropathy (p < 0.001), BMI (p = 0.008) and lumbar canal stenosis (p < 0.001) were included in the multivariate regression model, whereas bone marrow edema, radiculopathy and age were not. LSE is highly associated with spondylolisthesis, facet arthropathy and BMI, suggesting underestimation of its clinical impact as an integral component in chronic lumbar back pain. Longitudinal simultaneous X-ray/MRI studies should be conducted to test the relationship of LSE with lumbar spinal instability and low back pain.

LesionTracker: Extensible Open-Source Zero-Footprint Web Viewer for Cancer Imaging Research and Clinical Trials.

PubMed

Urban, Trinity; Ziegler, Erik; Lewis, Rob; Hafey, Chris; Sadow, Cheryl; Van den Abbeele, Annick D; Harris, Gordon J

2017-11-01

Oncology clinical trials have become increasingly dependent upon image-based surrogate endpoints for determining patient eligibility and treatment efficacy. As therapeutics have evolved and multiplied in number, the tumor metrics criteria used to characterize therapeutic response have become progressively more varied and complex. The growing intricacies of image-based response evaluation, together with rising expectations for rapid and consistent results reporting, make it difficult for site radiologists to adequately address local and multicenter imaging demands. These challenges demonstrate the need for advanced cancer imaging informatics tools that can help ensure protocol-compliant image evaluation while simultaneously promoting reviewer efficiency. LesionTracker is a quantitative imaging package optimized for oncology clinical trial workflows. The goal of the project is to create an open source zero-footprint viewer for image analysis that is designed to be extensible as well as capable of being integrated into third-party systems for advanced imaging tools and clinical trials informatics platforms. Cancer Res; 77(21); e119-22. ©2017 AACR . ©2017 American Association for Cancer Research.

Evaluation of lunar rocks and soils for resource utilization: Detailed image analysis of raw materials and beneficiated products

NASA Technical Reports Server (NTRS)

Taylor, Lawrence A.; Chambers, John G.; Patchen, Allan; Jerde, Eric A.; Mckay, David S.; Graf, John; Oder, Robin R.

1993-01-01

The rocks and soils of the Moon will be the raw materials for fuels and construction needs at a lunar base. This includes sources of materials for the generation of hydrogen, oxygen, metals, and other potential construction materials. For most of the bulk material needs, the regolith, and its less than 1 cm fraction, the soil, will suffice. But for specific mineral resources, it may be necessary to concentrate minerals from rocks or soils, and it is not always obvious which is the more appropriate feedstock. Besides an appreciation of site geology, the mineralogy and petrography of local rocks and soils is important for consideration of the resources which can provide feedstocks of ilmenite, glass, agglutinates, anorthite, etc. In such studies, it is very time-consuming and practically impossible to correlate particle counts (the traditional method of characterizing lunar soil petrography) with accurate modal analyses and with mineral associations in multi-mineralic grains. But x ray digital imaging, using x rays characteristic of each element, makes all this possible and much more (e.g., size and shape analysis). An application of beneficiation image analysis, in use in our lab (Oxford Instr. EDS and Cameca SX-50 EMP), was demonstrated to study mineral liberation from lunar rocks and soils. Results of x ray image analysis are presented.

Effects of dose reduction on bone strength prediction using finite element analysis

NASA Astrophysics Data System (ADS)

Anitha, D.; Subburaj, Karupppasamy; Mei, Kai; Kopp, Felix K.; Foehr, Peter; Noel, Peter B.; Kirschke, Jan S.; Baum, Thomas

2016-12-01

This study aimed to evaluate the effect of dose reduction, by means of tube exposure reduction, on bone strength prediction from finite-element (FE) analysis. Fresh thoracic mid-vertebrae specimens (n = 11) were imaged, using multi-detector computed tomography (MDCT), at different intensities of X-ray tube exposures (80, 150, 220 and 500 mAs). Bone mineral density (BMD) was estimated from the mid-slice of each specimen from MDCT images. Differences in image quality and geometry of each specimen were measured. FE analysis was performed on all specimens to predict fracture load. Paired t-tests were used to compare the results obtained, using the highest CT dose (500 mAs) as reference. Dose reduction had no significant impact on FE-predicted fracture loads, with significant correlations obtained with reference to 500 mAs, for 80 mAs (R2  = 0.997, p < 0.001), 150 mAs (R2 = 0.998, p < 0.001) and 220 mAs (R2 = 0.987, p < 0.001). There were no significant differences in volume quantification between the different doses examined. CT imaging radiation dose could be reduced substantially to 64% with no impact on strength estimates obtained from FE analysis. Reduced CT dose will enable early diagnosis and advanced monitoring of osteoporosis and associated fracture risk.

Enhanced identification of trace element fingerprint of prehistoric pigments by PIXE mapping

NASA Astrophysics Data System (ADS)

Lebon, M.; Pichon, L.; Beck, L.

2018-02-01

The elemental composition of Fe rich rocks used as pigment during prehistoric periods can provide valuable information about the type of material used and their geological origin. However, these materials present several analytical constraints since their patrimonial value involve using non-invasive techniques maintaining a high sensitivity of the detection and the quantification of trace elements. Micro-beam techniques also require to take into account the heterogeneity of these geomaterials from the macroscopic to microscopic scales. Several previous studies have demonstrated that PIXE analysis satisfies these analytical conditions. However, application of micro-PIXE analysis is still complex when thin and discontinuous layer of pigment is deposed on the surface of other materials such as rocks or bones. In such case, PIXE imaging could improve the ability to take into account the high heterogeneity of such archaeological objects. In study, we used PIXE imaging system developed at the NewAGLAE facility in order to visualize distribution of elements associated with iron-rich pigment phase. The results obtained show that PIXE maps can improve the identification of the main trace elements specific to the iron mineral phase. By grouping pixels of iron-rich areas and performing quantitative treatment, it was possible to reveal additional trace elements associated to pigment. This study highlights the contribution of PIXE imaging to the identification of elements associated with mineral phases of interest and to use them as proxies to discriminate different geological materials used in archaeological context.

The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software

NASA Technical Reports Server (NTRS)

Ponomarev, Artem; Cucinotta, F.

2011-01-01

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

Body image perception, satisfaction and somatotype in male and female athletes and non-athletes: results using a novel morphing technique.

PubMed

Stewart, Arthur D; Benson, Philip J; Michanikou, Evangelia G; Tsiota, Dimitra G; Narli, Margarita K

2003-10-01

Thirty-six adults (24 males, 12 females) were assessed for anthropometric somatotype and body image (perception and satisfaction) by a novel technique using quantitative distortion of a digital still image. Software produced random distortions in nine body regions. The participants manipulated interactive slider controls to adjust each body feature in turn, recreate their perceived image and indicate their desired image. There were no differences in perception between the sexes. However, the ideal-actual differences (i.e. satisfaction) indicated that males desired larger and females smaller features, respectively, in the chest and thighs (P < 0.001) and arms and calves (P < 0.01). When the male-derived data were partitioned by sport (strength, endurance, team-sport and controls), differences were found in the perceived image size in the chest and rib regions (P < 0.01 and P < 0.05, respectively). Strength athletes perceived these areas to be smaller and the control group perceived these areas to be larger than the true values. Somatotype analysis indicated that the physique associated with minimal dissatisfaction was 2.0-5.0-3.0 for males and 3.0-2.5-3.0 for females. Cluster analysis, combining anthropometric and satisfaction data, revealed seven distinct subgroups distinguished by particular attributes of physical appearance. We conclude that the method is reliable and that body image includes sex-specific, anthropometric, perceptual and personality-related components.

Carotid plaque characterization using CT and MRI scans for synergistic image analysis

NASA Astrophysics Data System (ADS)

Getzin, Matthew; Xu, Yiqin; Rao, Arhant; Madi, Saaussan; Bahadur, Ali; Lennartz, Michelle R.; Wang, Ge

2014-09-01

Noninvasive determination of plaque vulnerability has been a holy grail of medical imaging. Despite advances in tomographic technologies , there is currently no effective way to identify vulnerable atherosclerotic plaques with high sensitivity and specificity. Computed tomography (CT) and magnetic resonance imaging (MRI) are widely used, but neither provides sufficient information of plaque properties. Thus, we are motivated to combine CT and MRI imaging to determine if the composite information can better reflect the histological determination of plaque vulnerability. Two human endarterectomy specimens (1 symptomatic carotid and 1 stable femoral) were imaged using Scanco Medical Viva CT40 and Bruker Pharmascan 16cm 7T Horizontal MRI / MRS systems. μCT scans were done at 55 kVp and tube current of 70 mA. Samples underwent RARE-VTR and MSME pulse sequences to measure T1, T2 values, and proton density. The specimens were processed for histology and scored for vulnerability using the American Heart Association criteria. Single modality-based analyses were performed through segmentation of key imaging biomarkers (i.e. calcification and lumen), image registration, measurement of fibrous capsule, and multi-component T1 and T2 decay modeling. Feature differences were analyzed between the unstable and stable controls, symptomatic carotid and femoral plaque, respectively. By building on the techniques used in this study, synergistic CT+MRI analysis may provide a promising solution for plaque characterization in vivo.

A Time of Flight Fast Neutron Imaging System Design Study

NASA Astrophysics Data System (ADS)

Canion, Bonnie; Glenn, Andrew; Sheets, Steven; Wurtz, Ron; Nakae, Les; Hausladen, Paul; McConchie, Seth; Blackston, Matthew; Fabris, Lorenzo; Newby, Jason

2017-09-01

LLNL and ORNL are designing an active/passive fast neutron imaging system that is flexible to non-ideal detector positioning. It is often not possible to move an inspection object in fieldable imager applications such as safeguards, arms control treaty verification, and emergency response. Particularly, we are interested in scenarios which inspectors do not have access to all sides of an inspection object, due to interfering objects or walls. This paper will present the results of a simulation-based design parameter study, that will determine the optimum system design parameters for a fieldable system to perform time-of-flight based imaging analysis. The imaging analysis is based on the use of an associated particle imaging deuterium-tritium (API DT) neutron generator to get the time-of-flight of radiation induced within an inspection object. This design study will investigate the optimum design parameters for such a system (e.g. detector size, ideal placement, etc.), as well as the upper and lower feasible design parameters that the system can expect to provide results within a reasonable amount of time (e.g. minimum/maximum detector efficiency, detector standoff, etc.). Ideally the final prototype from this project will be capable of using full-access techniques, such as transmission imaging, when the measurement circumstances allow, but with the additional capability of producing results at reduced accessibility.

tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles.

PubMed

He, Sijin; Yong, May; Matthews, Paul M; Guo, Yike

2017-03-01

TranSMART has a wide range of functionalities for translational research and a large user community, but it does not support imaging data. In this context, imaging data typically includes 2D or 3D sets of magnitude data and metadata information. Imaging data may summarise complex feature descriptions in a less biased fashion than user defined plain texts and numeric numbers. Imaging data also is contextualised by other data sets and may be analysed jointly with other data that can explain features or their variation. Here we describe the tranSMART-XNAT Connector we have developed. This connector consists of components for data capture, organisation and analysis. Data capture is responsible for imaging capture either from PACS system or directly from an MRI scanner, or from raw data files. Data are organised in a similar fashion as tranSMART and are stored in a format that allows direct analysis within tranSMART. The connector enables selection and download of DICOM images and associated resources using subjects' clinical phenotypic and genotypic criteria. tranSMART-XNAT connector is written in Java/Groovy/Grails. It is maintained and available for download at https://github.com/sh107/transmart-xnat-connector.git. sijin@ebi.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

MR and CT image fusion for postimplant analysis in permanent prostate seed implants.

PubMed

Polo, Alfredo; Cattani, Federica; Vavassori, Andrea; Origgi, Daniela; Villa, Gaetano; Marsiglia, Hugo; Bellomi, Massimo; Tosi, Giampiero; De Cobelli, Ottavio; Orecchia, Roberto

2004-12-01

To compare the outcome of two different image-based postimplant dosimetry methods in permanent seed implantation. Between October 1999 and October 2002, 150 patients with low-risk prostate carcinoma were treated with (125)I and (103)Pd in our institution. A CT-MRI image fusion protocol was used in 21 consecutive patients treated with exclusive brachytherapy. The accuracy and reproducibility of the method was calculated, and then the CT-based dosimetry was compared with the CT-MRI-based dosimetry using the dose-volume histogram (DVH) related parameters recommended by the American Brachytherapy Society and the American Association of Physicists in Medicine. Our method for CT-MRI image fusion was accurate and reproducible (median shift <1 mm). Differences in prostate volume were found, depending on the image modality used. Quality assurance DVH-related parameters strongly depended on the image modality (CT vs. CT-MRI): V(100) = 82% vs. 88%, p < 0.05. D(90) = 96% vs. 115%, p < 0.05. Those results depend on the institutional implant technique and reflect the importance of lowering inter- and intraobserver discrepancies when outlining prostate and organs at risk for postimplant dosimetry. Computed tomography-MRI fused images allow accurate determination of prostate size, significantly improving the dosimetric evaluation based on DVH analysis. This provides a consistent method to judge a prostate seed implant's quality.