Thermal image analysis using the serpentine method

NASA Astrophysics Data System (ADS)

Koprowski, Robert; Wilczyński, Sławomir

2018-03-01

Thermal imaging is an increasingly widespread alternative to other imaging methods. As a supplementary method in diagnostics, it can be used both statically and with dynamic temperature changes. The paper proposes a new image analysis method that allows for the acquisition of new diagnostic information as well as object segmentation. The proposed serpentine analysis uses known and new methods of image analysis and processing proposed by the authors. Affine transformations of an image and subsequent Fourier analysis provide a new diagnostic quality. The method is fully repeatable and automatic and independent of inter-individual variability in patients. The segmentation results are by 10% better than those obtained from the watershed method and the hybrid segmentation method based on the Canny detector. The first and second harmonics of serpentine analysis enable to determine the type of temperature changes in the region of interest (gradient, number of heat sources etc.). The presented serpentine method provides new quantitative information on thermal imaging and more. Since it allows for image segmentation and designation of contact points of two and more heat sources (local minimum), it can be used to support medical diagnostics in many areas of medicine.

A functional magnetic resonance imaging study mapping the episodic memory encoding network in temporal lobe epilepsy

PubMed Central

Sidhu, Meneka K.; Stretton, Jason; Winston, Gavin P.; Bonelli, Silvia; Centeno, Maria; Vollmar, Christian; Symms, Mark; Thompson, Pamela J.; Koepp, Matthias J.

2013-01-01

Functional magnetic resonance imaging has demonstrated reorganization of memory encoding networks within the temporal lobe in temporal lobe epilepsy, but little is known of the extra-temporal networks in these patients. We investigated the temporal and extra-temporal reorganization of memory encoding networks in refractory temporal lobe epilepsy and the neural correlates of successful subsequent memory formation. We studied 44 patients with unilateral temporal lobe epilepsy and hippocampal sclerosis (24 left) and 26 healthy control subjects. All participants performed a functional magnetic resonance imaging memory encoding paradigm of faces and words with subsequent out-of-scanner recognition assessments. A blocked analysis was used to investigate activations during encoding and neural correlates of subsequent memory were investigated using an event-related analysis. Event-related activations were then correlated with out-of-scanner verbal and visual memory scores. During word encoding, control subjects activated the left prefrontal cortex and left hippocampus whereas patients with left hippocampal sclerosis showed significant additional right temporal and extra-temporal activations. Control subjects displayed subsequent verbal memory effects within left parahippocampal gyrus, left orbitofrontal cortex and fusiform gyrus whereas patients with left hippocampal sclerosis activated only right posterior hippocampus, parahippocampus and fusiform gyrus. Correlational analysis showed that patients with left hippocampal sclerosis with better verbal memory additionally activated left orbitofrontal cortex, anterior cingulate cortex and left posterior hippocampus. During face encoding, control subjects showed right lateralized prefrontal cortex and bilateral hippocampal activations. Patients with right hippocampal sclerosis showed increased temporal activations within the superior temporal gyri bilaterally and no increased extra-temporal areas of activation compared with control subjects. Control subjects showed subsequent visual memory effects within right amygdala, hippocampus, fusiform gyrus and orbitofrontal cortex. Patients with right hippocampal sclerosis showed subsequent visual memory effects within right posterior hippocampus, parahippocampal and fusiform gyri, and predominantly left hemisphere extra-temporal activations within the insula and orbitofrontal cortex. Correlational analysis showed that patients with right hippocampal sclerosis with better visual memory activated the amygdala bilaterally, right anterior parahippocampal gyrus and left insula. Right sided extra-temporal areas of reorganization observed in patients with left hippocampal sclerosis during word encoding and bilateral lateral temporal reorganization in patients with right hippocampal sclerosis during face encoding were not associated with subsequent memory formation. Reorganization within the medial temporal lobe, however, is an efficient process. The orbitofrontal cortex is critical to subsequent memory formation in control subjects and patients. Activations within anterior cingulum and insula correlated with better verbal and visual subsequent memory in patients with left and right hippocampal sclerosis, respectively, representing effective extra-temporal recruitment. PMID:23674488

Low-cost digital image processing at the University of Oklahoma

NASA Technical Reports Server (NTRS)

Harrington, J. A., Jr.

1981-01-01

Computer assisted instruction in remote sensing at the University of Oklahoma involves two separate approaches and is dependent upon initial preprocessing of a LANDSAT computer compatible tape using software developed for an IBM 370/158 computer. In-house generated preprocessing algorithms permits students or researchers to select a subset of a LANDSAT scene for subsequent analysis using either general purpose statistical packages or color graphic image processing software developed for Apple II microcomputers. Procedures for preprocessing the data and image analysis using either of the two approaches for low-cost LANDSAT data processing are described.

Adaptive image inversion of contrast 3D echocardiography for enabling automated analysis.

PubMed

Shaheen, Anjuman; Rajpoot, Kashif

2015-08-01

Contrast 3D echocardiography (C3DE) is commonly used to enhance the visual quality of ultrasound images in comparison with non-contrast 3D echocardiography (3DE). Although the image quality in C3DE is perceived to be improved for visual analysis, however it actually deteriorates for the purpose of automatic or semi-automatic analysis due to higher speckle noise and intensity inhomogeneity. Therefore, the LV endocardial feature extraction and segmentation from the C3DE images remains a challenging problem. To address this challenge, this work proposes an adaptive pre-processing method to invert the appearance of C3DE image. The image inversion is based on an image intensity threshold value which is automatically estimated through image histogram analysis. In the inverted appearance, the LV cavity appears dark while the myocardium appears bright thus making it similar in appearance to a 3DE image. Moreover, the resulting inverted image has high contrast and low noise appearance, yielding strong LV endocardium boundary and facilitating feature extraction for segmentation. Our results demonstrate that the inverse appearance of contrast image enables the subsequent LV segmentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma

PubMed Central

Akbari, Hamed; Macyszyn, Luke; Da, Xiao; Bilello, Michel; Wolf, Ronald L.; Martinez-Lage, Maria; Biros, George; Alonso-Basanta, Michelle; O’Rourke, Donald M.; Davatzikos, Christos

2016-01-01

Background Glioblastoma is an aggressive and highly infiltrative brain cancer. Standard surgical resection is guided by enhancement on postcontrast T1-weighted (T1) magnetic resonance imaging (MRI), which is insufficient for delineating surrounding infiltrating tumor. Objective To develop imaging biomarkers that delineate areas of tumor infiltration and predict early recurrence in peritumoral tissue. Such markers would enable intensive, yet targeted, surgery and radiotherapy, thereby potentially delaying recurrence and prolonging survival. Methods Preoperative multiparametric MRIs (T1, T1-Gad, T2-weighted [T2], T2-fluid-attenuated inversion recovery [FLAIR], diffusion tensor imaging (DTI), and dynamic susceptibility contrast-enhanced [DSC]-MRI) from 31 patients were combined using machine learning methods, thereby creating predictive spatial maps of infiltrated peritumoral tissue. Cross validation was used in the retrospective cohort to achieve generalizable biomarkers. Subsequently, the imaging signatures learned from the retrospective study were used in a replication cohort of 34 new patients. Spatial maps representing likelihood of tumor infiltration and future early recurrence were compared to regions of recurrence on postresection follow-up studies with pathology confirmation. Results This technique produced predictions of early recurrence with a mean area under the curve (AUC) of 0.84, sensitivity of 91%, specificity of 93%, and odds ratio estimates of 9.29 (99% CI, 8.95–9.65) for tissue predicted to be heavily infiltrated in the replication study. Regions of tumor recurrence were found to have subtle, yet fairly distinctive multiparametric imaging signatures when analyzed quantitatively by pattern analysis and machine learning. Conclusion Visually imperceptible imaging patterns discovered via multiparametric pattern analysis methods were found to estimate the extent of infiltration and location of future tumor recurrence, paving the way for improved targeted treatment. PMID:26813856

Identification of suitable fundus images using automated quality assessment methods.

PubMed

Şevik, Uğur; Köse, Cemal; Berber, Tolga; Erdöl, Hidayet

2014-04-01

Retinal image quality assessment (IQA) is a crucial process for automated retinal image analysis systems to obtain an accurate and successful diagnosis of retinal diseases. Consequently, the first step in a good retinal image analysis system is measuring the quality of the input image. We present an approach for finding medically suitable retinal images for retinal diagnosis. We used a three-class grading system that consists of good, bad, and outlier classes. We created a retinal image quality dataset with a total of 216 consecutive images called the Diabetic Retinopathy Image Database. We identified the suitable images within the good images for automatic retinal image analysis systems using a novel method. Subsequently, we evaluated our retinal image suitability approach using the Digital Retinal Images for Vessel Extraction and Standard Diabetic Retinopathy Database Calibration level 1 public datasets. The results were measured through the F1 metric, which is a harmonic mean of precision and recall metrics. The highest F1 scores of the IQA tests were 99.60%, 96.50%, and 85.00% for good, bad, and outlier classes, respectively. Additionally, the accuracy of our suitable image detection approach was 98.08%. Our approach can be integrated into any automatic retinal analysis system with sufficient performance scores.

The evolution of solid density within a thermal explosion II. Dynamic proton radiography of cracking and solid consumption by burning

NASA Astrophysics Data System (ADS)

Smilowitz, L.; Henson, B. F.; Romero, J. J.; Asay, B. W.; Saunders, A.; Merrill, F. E.; Morris, C. L.; Kwiatkowski, K.; Grim, G.; Mariam, F.; Schwartz, C. L.; Hogan, G.; Nedrow, P.; Murray, M. M.; Thompson, T. N.; Espinoza, C.; Lewis, D.; Bainbridge, J.; McNeil, W.; Rightley, P.; Marr-Lyon, M.

2012-05-01

We report proton transmission images obtained subsequent to the laser assisted thermal ignition of a sample of PBX 9501 (a plastic bonded formulation of the explosive nitramine octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX)). We describe the laser assisted thermal ignition technique as a means to synchronize a non-linear thermal ignition event while preserving the subsequent post-ignition behavior. We have obtained dynamic proton transmission images at two spatial magnifications and viewed both the radial and transverse axis of a solid cylindrical sample encased in aluminum. Images have been obtained with 3 to 15 μs temporal resolution and approximately 100 μm spatial resolution at the higher magnification. We observe case expansion from very early in the experiment, until case fragmentation. We observe spatially anisotropic features in the transmission which we attribute to cracking in the solid explosive, in agreement with previous measurements conducted on two dimensional samples with optical viewing. Digital analysis of the images also reveals spatially isotropic features which we attribute to the evolution of the loss of density by burning subsequent to thermal ignition.

Prediction of subacute infarct size in acute middle cerebral artery stroke: comparison of perfusion-weighted imaging and apparent diffusion coefficient maps.

PubMed

Drier, Aurélie; Tourdias, Thomas; Attal, Yohan; Sibon, Igor; Mutlu, Gurkan; Lehéricy, Stéphane; Samson, Yves; Chiras, Jacques; Dormont, Didier; Orgogozo, Jean-Marc; Dousset, Vincent; Rosso, Charlotte

2012-11-01

To compare perfusion-weighted (PW) imaging and apparent diffusion coefficient (ADC) maps in prediction of infarct size and growth in patients with acute middle cerebral artery infarct. This study was approved by the local institutional review board. Written informed consent was obtained from all 80 patients. Subsequent infarct volume and growth on follow-up magnetic resonance (MR) images obtained within 6 days were compared with the predictions based on PW images by using a time-to-peak threshold greater than 4 seconds and ADC maps obtained less than 12 hours after middle cerebral artery infarct. ADC- and PW imaging-predicted infarct growth areas and infarct volumes were correlated with subsequent infarct growth and follow-up diffusion-weighted (DW) imaging volumes. The impact of MR imaging time delay on the correlation coefficient between the predicted and subsequent infarct volumes and individual predictions of infarct growth by using receiver operating characteristic curves were assessed. The infarct volume measurements were highly reproducible (concordance correlation coefficient [CCC] of 0.965 and 95% confidence interval [CI]: 0.949, 0.976 for acute DW imaging; CCC of 0.995 and 95% CI: 0.993, 0.997 for subacute DW imaging). The subsequent infarct volume correlated (P<.0001) with ADC- (ρ=0.853) and PW imaging- (ρ=0.669) predicted volumes. The correlation was higher for ADC-predicted volume than for PW imaging-predicted volume (P<.005), but not when the analysis was restricted to patients without recanalization (P=.07). The infarct growth correlated (P<.0001) with PW imaging-DW imaging mismatch (ρ=0.470) and ADC-DW imaging mismatch (ρ=0.438), without significant differences between both methods (P=.71). The correlations were similar among time delays with ADC-predicted volumes but decreased with PW imaging-based volumes beyond the therapeutic window. Accuracies of ADC- and PW imaging-based predictions of infarct growth in an individual prediction were similar (area under the receiver operating characteristic curve [AUC] of 0.698 and 95% CI: 0.585, 0.796 vs AUC of 0.749 and 95% CI: 0.640, 0.839; P=.48). The ADC-based method was as accurate as the PW imaging-based method for evaluating infarct growth and size in the subacute phase. © RSNA, 2012

Magnetomotive laser speckle imaging

PubMed Central

Kim, Jeehyun; Oh, Junghwan; Choi, Bernard

2010-01-01

Laser speckle imaging (LSI) involves analysis of reflectance images collected during coherent optical excitation of an object to compute wide-field maps of tissue blood flow. An intrinsic limitation of LSI for resolving microvascular architecture is that its signal depends on relative motion of interrogated red blood cells. Hence, with LSI, small-diameter arterioles, venules, and capillaries are difficult to resolve due to the slow flow speeds associated with such vasculature. Furthermore, LSI characterization of subsurface blood flow is subject to blurring due to scattering, further limiting the ability of LSI to resolve or quantify blood flow in small vessels. Here, we show that magnetic activation of superparamagnetic iron oxide (SPIO) nanoparticles modulate the speckle flow index (SFI) values estimated from speckle contrast analysis of collected images. With application of an ac magnetic field to a solution of stagnant SPIO particles, an apparent increase in SFI is induced. Furthermore, with application of a focused dc magnetic field, a focal decrease in SFI values is induced. Magnetomotive LSI may enable wide-field mapping of suspicious tissue regions, enabling subsequent high-resolution optical interrogation of these regions. Similarly, subsequent photoactivation of intravascular SPIO nanoparticles could then be performed to induce selective photothermal destruction of unwanted vasculature. PMID:20210436

Stand-off imaging Raman spectroscopy for forensic analysis of post-blast scenes: trace detection of ammonium nitrate and 2,4,6-trinitrotoluene

NASA Astrophysics Data System (ADS)

Ceco, Ema; Önnerud, Hans; Menning, Dennis; Gilljam, John L.; Bââth, Petra; Östmark, Henric

2014-05-01

The following paper presents a realistic forensic capability test of an imaging Raman spectroscopy based demonstrator system, developed at FOI, the Swedish Defence Research Agency. The system uses a 532 nm laser to irradiate a surface of 25×25mm. The backscattered radiation from the surface is collected by an 8" telescope with subsequent optical system, and is finally imaged onto an ICCD camera. We present here an explosives trace analysis study of samples collected from a realistic scenario after a detonation. A left-behind 5 kg IED, based on ammonium nitrate with a TNT (2,4,6-trinitrotoluene) booster, was detonated in a plastic garbage bin. Aluminum sample plates were mounted vertically on a holder approximately 6 m from the point of detonation. Minutes after the detonation, the samples were analyzed with stand-off imaging Raman spectroscopy from a distance of 10 m. Trace amounts could be detected from the secondary explosive (ammonium nitrate with an analysis time of 1 min. Measurement results also indicated detection of residues from the booster (TNT). The sample plates were subsequently swabbed and analyzed with HPLC and GC-MS analyses to confirm the results from the stand-off imaging Raman system. The presented findings indicate that it is possible to determine the type of explosive used in an IED from a distance, within minutes after the attack, and without tampering with physical evidence at the crime scene.

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.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Practical issues of hyperspectral imaging analysis of solid dosage forms.

PubMed

Amigo, José Manuel

2010-09-01

Hyperspectral imaging techniques have widely demonstrated their usefulness in different areas of interest in pharmaceutical research during the last decade. In particular, middle infrared, near infrared, and Raman methods have gained special relevance. This rapid increase has been promoted by the capability of hyperspectral techniques to provide robust and reliable chemical and spatial information on the distribution of components in pharmaceutical solid dosage forms. Furthermore, the valuable combination of hyperspectral imaging devices with adequate data processing techniques offers the perfect landscape for developing new methods for scanning and analyzing surfaces. Nevertheless, the instrumentation and subsequent data analysis are not exempt from issues that must be thoughtfully considered. This paper describes and discusses the main advantages and drawbacks of the measurements and data analysis of hyperspectral imaging techniques in the development of solid dosage forms.

Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

PubMed

Prescott, Jeffrey William

2013-02-01

The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

Controlled Source 4D Seismic Imaging

NASA Astrophysics Data System (ADS)

Luo, Y.; Morency, C.; Tromp, J.

2009-12-01

Earth's material properties may change after significant tectonic events, e.g., volcanic eruptions, earthquake ruptures, landslides, and hydrocarbon migration. While many studies focus on how to interpret observations in terms of changes in wavespeeds and attenuation, the oil industry is more interested in how we can identify and locate such temporal changes using seismic waves generated by controlled sources. 4D seismic analysis is indeed an important tool to monitor fluid movement in hydrocarbon reservoirs during production, improving fields management. Classic 4D seismic imaging involves comparing images obtained from two subsequent seismic surveys. Differences between the two images tell us where temporal changes occurred. However, when the temporal changes are small, it may be quite hard to reliably identify and characterize the differences between the two images. We propose to back-project residual seismograms between two subsequent surveys using adjoint methods, which results in images highlighting temporal changes. We use the SEG/EAGE salt dome model to illustrate our approach. In two subsequent surveys, the wavespeeds and density within a target region are changed, mimicking possible fluid migration. Due to changes in material properties induced by fluid migration, seismograms recorded in the two surveys differ. By back propagating these residuals, the adjoint images identify the location of the affected region. An important issue involves the nature of model. For instance, are we characterizing only changes in wavespeed, or do we also consider density and attenuation? How many model parameters characterize the model, e.g., is our model isotropic or anisotropic? Is acoustic wave propagation accurate enough or do we need to consider elastic or poroelastic effects? We will investigate how imaging strategies based upon acoustic, elastic and poroelastic simulations affect our imaging capabilities.

Electrophoresis gel image processing and analysis using the KODAK 1D software.

PubMed

Pizzonia, J

2001-06-01

The present article reports on the performance of the KODAK 1D Image Analysis Software for the acquisition of information from electrophoresis experiments and highlights the utility of several mathematical functions for subsequent image processing, analysis, and presentation. Digital images of Coomassie-stained polyacrylamide protein gels containing molecular weight standards and ethidium bromide stained agarose gels containing DNA mass standards are acquired using the KODAK Electrophoresis Documentation and Analysis System 290 (EDAS 290). The KODAK 1D software is used to optimize lane and band identification using features such as isomolecular weight lines. Mathematical functions for mass standard representation are presented, and two methods for estimation of unknown band mass are compared. Given the progressive transition of electrophoresis data acquisition and daily reporting in peer-reviewed journals to digital formats ranging from 8-bit systems such as EDAS 290 to more expensive 16-bit systems, the utility of algorithms such as Gaussian modeling, which can correct geometric aberrations such as clipping due to signal saturation common at lower bit depth levels, is discussed. Finally, image-processing tools that can facilitate image preparation for presentation are demonstrated.

Analysis of ERTS imagery using special electronic viewing/measuring equipment

NASA Technical Reports Server (NTRS)

Evans, W. E.; Serebreny, S. M.

1973-01-01

An electronic satellite image analysis console (ESIAC) is being employed to process imagery for use by USGS investigators in several different disciplines studying dynamic hydrologic conditions. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. Quantitative measurements of distances, areas, and brightness profiles can be extracted digitally under operator supervision. Initial results are presented for the display and measurement of snowfield extent, glacier development, sediment plumes from estuary discharge, playa inventory, phreatophyte and other vegetative changes.

Lessons Learned From Developing A Streaming Data Framework for Scientific Analysis

NASA Technical Reports Server (NTRS)

Wheeler. Kevin R.; Allan, Mark; Curry, Charles

2003-01-01

We describe the development and usage of a streaming data analysis software framework. The framework is used for three different applications: Earth science hyper-spectral imaging analysis, Electromyograph pattern detection, and Electroencephalogram state determination. In each application the framework was used to answer a series of science questions which evolved with each subsequent answer. This evolution is summarized in the form of lessons learned.

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

A Simple Instrument Designed to Provide Consistent Digital Facial Images in Dermatology

PubMed Central

Nirmal, Balakrishnan; Pai, Sathish B; Sripathi, Handattu

2013-01-01

Photography has proven to be a valuable tool in the field of dermatology. The major reason for poor photographs is the inability to produce comparable images in the subsequent follow ups. Combining digital photography with image processing software analysis brings consistency in tracking serial images. Digital photographs were taken with the aid of an instrument which we designed in our workshop to ensure that photographs were taken with identical patient positioning, camera angles and distance. It is of paramount importance in aesthetic dermatology to appreciate even subtle changes after each treatment session which can be achieved by taking consistent digital images. PMID:23723469

A simple instrument designed to provide consistent digital facial images in dermatology.

PubMed

Nirmal, Balakrishnan; Pai, Sathish B; Sripathi, Handattu

2013-05-01

Photography has proven to be a valuable tool in the field of dermatology. The major reason for poor photographs is the inability to produce comparable images in the subsequent follow ups. Combining digital photography with image processing software analysis brings consistency in tracking serial images. Digital photographs were taken with the aid of an instrument which we designed in our workshop to ensure that photographs were taken with identical patient positioning, camera angles and distance. It is of paramount importance in aesthetic dermatology to appreciate even subtle changes after each treatment session which can be achieved by taking consistent digital images.

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

PubMed

Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-02-01

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme. Copyright © 2016 Elsevier Inc. All rights reserved.

Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics

NASA Astrophysics Data System (ADS)

Großerueschkamp, Frederik; Bracht, Thilo; Diehl, Hanna C.; Kuepper, Claus; Ahrens, Maike; Kallenbach-Thieltges, Angela; Mosig, Axel; Eisenacher, Martin; Marcus, Katrin; Behrens, Thomas; Brüning, Thomas; Theegarten, Dirk; Sitek, Barbara; Gerwert, Klaus

2017-03-01

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics.

PubMed

Großerueschkamp, Frederik; Bracht, Thilo; Diehl, Hanna C; Kuepper, Claus; Ahrens, Maike; Kallenbach-Thieltges, Angela; Mosig, Axel; Eisenacher, Martin; Marcus, Katrin; Behrens, Thomas; Brüning, Thomas; Theegarten, Dirk; Sitek, Barbara; Gerwert, Klaus

2017-03-30

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

Control of the positional relationship between a sample collection instrument and a surface to be analyzed during a sampling procedure with image analysis

DOEpatents

Van Berkel, Gary J.; Kertesz, Vilmos

2011-08-09

A system and method utilizes an image analysis approach for controlling the collection instrument-to-surface distance in a sampling system for use, for example, with mass spectrometric detection. Such an approach involves the capturing of an image of the collection instrument or the shadow thereof cast across the surface and the utilization of line average brightness (LAB) techniques to determine the actual distance between the collection instrument and the surface. The actual distance is subsequently compared to a target distance for re-optimization, as necessary, of the collection instrument-to-surface during an automated surface sampling operation.

Chemical imaging of molecular changes in a hydrated single cell by dynamic secondary ion mass spectrometry and super-resolution microscopy

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

Hua, Xin; Szymanski, Craig; Wang, Zhaoying

2016-01-01

Chemical imaging of single cells is important in capturing biological dynamics. Single cell correlative imaging is realized between structured illumination microscopy (SIM) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) using System for Analysis at the Liquid Vacuum Interface (SALVI), a multimodal microreactor. SIM characterized cells and guided subsequent ToF-SIMS analysis. Dynamic ToF-SIMS provided time- and space-resolved cell molecular mapping. Lipid fragments were identified in the hydrated cell membrane. Principal component analysis was used to elucidate chemical component differences among mouse lung cells that uptake zinc oxide nanoparticles. Our results provided submicron chemical spatial mapping for investigations of cell dynamics atmore » the molecular level.« less

A new efficient method for color image compression based on visual attention mechanism

NASA Astrophysics Data System (ADS)

Shao, Xiaoguang; Gao, Kun; Lv, Lily; Ni, Guoqiang

2010-11-01

One of the key procedures in color image compression is to extract its region of interests (ROIs) and evaluate different compression ratios. A new non-uniform color image compression algorithm with high efficiency is proposed in this paper by using a biology-motivated selective attention model for the effective extraction of ROIs in natural images. When the ROIs have been extracted and labeled in the image, the subsequent work is to encode the ROIs and other regions with different compression ratios via popular JPEG algorithm. Furthermore, experiment results and quantitative and qualitative analysis in the paper show perfect performance when comparing with other traditional color image compression approaches.

An infra-red imaging system for the analysis of tropisms in Arabidopsis thaliana seedlings

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

Orbovic, V.; Poff, K.L.

1990-05-01

Since blue and green light will induce phototropism and red light is absorbed by phytochrome, no wavelength of visible radiation should be considered safe for any study of tropisms in etiolated seedlings. For this reason, we have developed an infra-red imaging system with a video camera with which we can monitor seedlings using radiation at wavelengths longer than 800 nm. The image of the seedlings can be observed in real time, recorded on a VCR and subsequently analyzed using the Java image analysis system. The time courses for curvature of seedlings differ in shape, amplitude, and lag time. This variabilitymore » accounts for much of the noise in the measurement of curvature for a population of seedlings.« less

Real-time color image processing for forensic fiber investigations

NASA Astrophysics Data System (ADS)

Paulsson, Nils

1995-09-01

This paper describes a system for automatic fiber debris detection based on color identification. The properties of the system are fast analysis and high selectivity, a necessity when analyzing forensic fiber samples. An ordinary investigation separates the material into well above 100,000 video images to analyze. The system is based on standard techniques such as CCD-camera, motorized sample table, and IBM-compatible PC/AT with add-on-boards for video frame digitalization and stepping motor control as the main parts. It is possible to operate the instrument at full video rate (25 image/s) with aid of the HSI-color system (hue- saturation-intensity) and software optimization. High selectivity is achieved by separating the analysis into several steps. The first step is fast direct color identification of objects in the analyzed video images and the second step analyzes detected objects with a more complex and time consuming stage of the investigation to identify single fiber fragments for subsequent analysis with more selective techniques.

Monitoring of activated sludge settling ability through image analysis: validation on full-scale wastewater treatment plants.

PubMed

Mesquita, D P; Dias, O; Amaral, A L; Ferreira, E C

2009-04-01

In recent years, a great deal of attention has been focused on the research of activated sludge processes, where the solid-liquid separation phase is frequently considered of critical importance, due to the different problems that severely affect the compaction and the settling of the sludge. Bearing that in mind, in this work, image analysis routines were developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in eight different wastewater treatment plants, for a combined period of 2 years. The monitoring of the activated sludge contents allowed for the detection of bulking events proving that the developed image analysis methodology is adequate for a continuous examination of the morphological changes in microbial aggregates and subsequent estimation of the sludge volume index. In fact, the obtained results proved that the developed image analysis methodology is a feasible method for the continuous monitoring of activated sludge systems and identification of disturbances.

Flame filtering and perimeter localization of wildfires using aerial thermal imagery

NASA Astrophysics Data System (ADS)

Valero, Mario M.; Verstockt, Steven; Rios, Oriol; Pastor, Elsa; Vandecasteele, Florian; Planas, Eulàlia

2017-05-01

Airborne thermal infrared (TIR) imaging systems are being increasingly used for wild fire tactical monitoring since they show important advantages over spaceborne platforms and visible sensors while becoming much more affordable and much lighter than multispectral cameras. However, the analysis of aerial TIR images entails a number of difficulties which have thus far prevented monitoring tasks from being totally automated. One of these issues that needs to be addressed is the appearance of flame projections during the geo-correction of off-nadir images. Filtering these flames is essential in order to accurately estimate the geographical location of the fuel burning interface. Therefore, we present a methodology which allows the automatic localisation of the active fire contour free of flame projections. The actively burning area is detected in TIR georeferenced images through a combination of intensity thresholding techniques, morphological processing and active contours. Subsequently, flame projections are filtered out by the temporal frequency analysis of the appropriate contour descriptors. The proposed algorithm was tested on footages acquired during three large-scale field experimental burns. Results suggest this methodology may be suitable to automatise the acquisition of quantitative data about the fire evolution. As future work, a revision of the low-pass filter implemented for the temporal analysis (currently a median filter) was recommended. The availability of up-to-date information about the fire state would improve situational awareness during an emergency response and may be used to calibrate data-driven simulators capable of emitting short-term accurate forecasts of the subsequent fire evolution.

An image analysis of TLC patterns for quality control of saffron based on soil salinity effect: A strategy for data (pre)-processing.

PubMed

Sereshti, Hassan; Poursorkh, Zahra; Aliakbarzadeh, Ghazaleh; Zarre, Shahin; Ataolahi, Sahar

2018-01-15

Quality of saffron, a valuable food additive, could considerably affect the consumers' health. In this work, a novel preprocessing strategy for image analysis of saffron thin layer chromatographic (TLC) patterns was introduced. This includes performing a series of image pre-processing techniques on TLC images such as compression, inversion, elimination of general baseline (using asymmetric least squares (AsLS)), removing spots shift and concavity (by correlation optimization warping (COW)), and finally conversion to RGB chromatograms. Subsequently, an unsupervised multivariate data analysis including principal component analysis (PCA) and k-means clustering was utilized to investigate the soil salinity effect, as a cultivation parameter, on saffron TLC patterns. This method was used as a rapid and simple technique to obtain the chemical fingerprints of saffron TLC images. Finally, the separated TLC spots were chemically identified using high-performance liquid chromatography-diode array detection (HPLC-DAD). Accordingly, the saffron quality from different areas of Iran was evaluated and classified. Copyright © 2017 Elsevier Ltd. All rights reserved.

AutoCNet: A Python library for sparse multi-image correspondence identification for planetary data

NASA Astrophysics Data System (ADS)

Laura, Jason; Rodriguez, Kelvin; Paquette, Adam C.; Dunn, Evin

2018-01-01

In this work we describe the AutoCNet library, written in Python, to support the application of computer vision techniques for n-image correspondence identification in remotely sensed planetary images and subsequent bundle adjustment. The library is designed to support exploratory data analysis, algorithm and processing pipeline development, and application at scale in High Performance Computing (HPC) environments for processing large data sets and generating foundational data products. We also present a brief case study illustrating high level usage for the Apollo 15 Metric camera.

An overview of state-of-the-art image restoration in electron microscopy.

PubMed

Roels, J; Aelterman, J; Luong, H Q; Lippens, S; Pižurica, A; Saeys, Y; Philips, W

2018-06-08

In Life Science research, electron microscopy (EM) is an essential tool for morphological analysis at the subcellular level as it allows for visualization at nanometer resolution. However, electron micrographs contain image degradations such as noise and blur caused by electromagnetic interference, electron counting errors, magnetic lens imperfections, electron diffraction, etc. These imperfections in raw image quality are inevitable and hamper subsequent image analysis and visualization. In an effort to mitigate these artefacts, many electron microscopy image restoration algorithms have been proposed in the last years. Most of these methods rely on generic assumptions on the image or degradations and are therefore outperformed by advanced methods that are based on more accurate models. Ideally, a method will accurately model the specific degradations that fit the physical acquisition settings. In this overview paper, we discuss different electron microscopy image degradation solutions and demonstrate that dedicated artefact regularisation results in higher quality restoration and is applicable through recently developed probabilistic methods. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

THELMA: a mobile app for crowdsourcing environmental data

NASA Astrophysics Data System (ADS)

Hintz, Kenneth J.; Hintz, Christopher J.; Almomen, Faris; Adounvo, Christian; D'Amato, Michael

2014-06-01

The collection of environmental light pollution data related to sea turtle nesting sites is a laborious and time consuming effort entailing the use of several pieces of measurement equipment, their transportation and calibration, the manual logging of results in the field, and subsequent transfer of the data to a computer for post-collection analysis. Serendipitously, the current generation of mobile smart phones (e.g., iPhone® 5) contains the requisite measurement capability, namely location data in aided GPS coordinates, magnetic compass heading, and elevation at the time an image is taken, image parameter data, and the image itself. The Turtle Habitat Environmental Light Measurement App (THELMA) is a mobile phone app whose graphical user interface (GUI) guides an untrained user through the image acquisition process in order to capture 360° of images with pointing guidance. It subsequently uploads the user-tagged images, all of the associated image parameters, and position, azimuth, elevation metadata to a central internet repository. Provision is also made for the capture of calibration images and the review of images before upload. THELMA allows for inexpensive, highly-efficient, worldwide crowdsourcing of calibratable beachfront lighting/light pollution data collected by untrained volunteers. This data can be later processed, analyzed, and used by scientists conducting sea turtle conservation in order to identify beach locations with hazardous levels of light pollution that may alter sea turtle behavior and necessitate human intervention after hatchling emergence.

High resolution imaging of latent fingerprints by localized corrosion on brass surfaces.

PubMed

Goddard, Alex J; Hillman, A Robert; Bond, John W

2010-01-01

The Atomic Force Microscope (AFM) is capable of imaging fingerprint ridges on polished brass substrates at an unprecedented level of detail. While exposure to elevated humidity at ambient or slightly raised temperatures does not change the image appreciably, subsequent brief heating in a flame results in complete loss of the sweat deposit and the appearance of pits and trenches. Localized elemental analysis (using EDAX, coupled with SEM imaging) shows the presence of the constituents of salt in the initial deposits. Together with water and atmospheric oxygen--and with thermal enhancement--these are capable of driving a surface corrosion process. This process is sufficiently localized that it has the potential to generate a durable negative topographical image of the fingerprint. AFM examination of surface regions between ridges revealed small deposits (probably microscopic "spatter" of sweat components or transferred particulates) that may ultimately limit the level of ridge detail analysis.

Data analysis for GOPEX image frames

NASA Technical Reports Server (NTRS)

Levine, B. M.; Shaik, K. S.; Yan, T.-Y.

1993-01-01

The data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between 9-16 Dec. 1992 is described. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mexico. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public release images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a daily basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. Processing steps are described and the theories are compared with the experimental results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimental planning to geometrically locate pulse positions with greater certainty.

Quantitative nanoscopy: Tackling sampling limitations in (S)TEM imaging of polymers and composites.

PubMed

Gnanasekaran, Karthikeyan; Snel, Roderick; de With, Gijsbertus; Friedrich, Heiner

2016-01-01

Sampling limitations in electron microscopy questions whether the analysis of a bulk material is representative, especially while analyzing hierarchical morphologies that extend over multiple length scales. We tackled this problem by automatically acquiring a large series of partially overlapping (S)TEM images with sufficient resolution, subsequently stitched together to generate a large-area map using an in-house developed acquisition toolbox (TU/e Acquisition ToolBox) and stitching module (TU/e Stitcher). In addition, we show that quantitative image analysis of the large scale maps provides representative information that can be related to the synthesis and process conditions of hierarchical materials, which moves electron microscopy analysis towards becoming a bulk characterization tool. We demonstrate the power of such an analysis by examining two different multi-phase materials that are structured over multiple length scales. Copyright © 2015 Elsevier B.V. All rights reserved.

2011 Tohoku tsunami video and TLS based measurements: hydrographs, currents, inundation flow velocities, and ship tracks

NASA Astrophysics Data System (ADS)

Fritz, H. M.; Phillips, D. A.; Okayasu, A.; Shimozono, T.; Liu, H.; Takeda, S.; Mohammed, F.; Skanavis, V.; Synolakis, C. E.; Takahashi, T.

2012-12-01

The March 11, 2011, magnitude Mw 9.0 earthquake off the coast of the Tohoku region caused catastrophic damage and loss of life in Japan. The mid-afternoon tsunami arrival combined with survivors equipped with cameras on top of vertical evacuation buildings provided spontaneous spatially and temporally resolved inundation recordings. This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Myako, Kamaishi, Kesennuma and Yoriisohama along Japan's Sanriku coast and the subsequent video image calibration, processing, tsunami hydrograph and flow velocity analysis. Selected tsunami video recording sites were explored, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance in April, 2011. A follow-up survey in June, 2011 focused on terrestrial laser scanning (TLS) at locations with high quality eyewitness videos. We acquired precise topographic data using TLS at the video sites producing a 3-dimensional "point cloud" dataset. A camera mounted on the Riegl VZ-400 scanner yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing. The original video recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). The analysis of the tsunami videos follows an adapted four step procedure originally developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on ground control points measured in the LiDAR data. In a second step the video image motion induced by the panning of the video camera was determined from subsequent images by particle image velocimetry (PIV) applied to fixed objects. The third step involves the transformation of the raw tsunami video images from image coordinates to world coordinates with a direct linear transformation (DLT) procedure. Finally, the instantaneous tsunami surface current and flooding velocity vector maps are determined by applying the digital PIV analysis method to the rectified tsunami video images with floating debris clusters. Tsunami currents up to 11 m/s per second were measured in Kesennuma Bay making navigation impossible. Tsunami hydrographs are derived from the videos based on water surface elevations at surface piercing objects identified in the acquired topographic TLS data. Apart from a dominant tsunami crest the hydrograph at Kamaishi also reveals a subsequent draw down to -10m exposing the harbor bottom. In some cases ship moorings resist the main tsunami crest only to be broken by the extreme draw down and setting vessels a drift for hours. Further we discuss the complex effects of coastal structures on inundation and outflow hydrographs and flow velocities.;

Digital imaging biomarkers feed machine learning for melanoma screening.

PubMed

Gareau, Daniel S; Correa da Rosa, Joel; Yagerman, Sarah; Carucci, John A; Gulati, Nicholas; Hueto, Ferran; DeFazio, Jennifer L; Suárez-Fariñas, Mayte; Marghoob, Ashfaq; Krueger, James G

2017-07-01

We developed an automated approach for generating quantitative image analysis metrics (imaging biomarkers) that are then analysed with a set of 13 machine learning algorithms to generate an overall risk score that is called a Q-score. These methods were applied to a set of 120 "difficult" dermoscopy images of dysplastic nevi and melanomas that were subsequently excised/classified. This approach yielded 98% sensitivity and 36% specificity for melanoma detection, approaching sensitivity/specificity of expert lesion evaluation. Importantly, we found strong spectral dependence of many imaging biomarkers in blue or red colour channels, suggesting the need to optimize spectral evaluation of pigmented lesions. © 2016 The Authors. Experimental Dermatology Published by John Wiley & Sons Ltd.

Evaluating the effectiveness of treatment of corneal ulcers via computer-based automatic image analysis

NASA Astrophysics Data System (ADS)

Otoum, Nesreen A.; Edirisinghe, Eran A.; Dua, Harminder; Faraj, Lana

2012-06-01

Corneal Ulcers are a common eye disease that requires prompt treatment. Recently a number of treatment approaches have been introduced that have been proven to be very effective. Unfortunately, the monitoring process of the treatment procedure remains manual and hence time consuming and prone to human errors. In this research we propose an automatic image analysis based approach to measure the size of an ulcer and its subsequent further investigation to determine the effectiveness of any treatment process followed. In Ophthalmology an ulcer area is detected for further inspection via luminous excitation of a dye. Usually in the imaging systems utilised for this purpose (i.e. a slit lamp with an appropriate dye) the ulcer area is excited to be luminous green in colour as compared to rest of the cornea which appears blue/brown. In the proposed approach we analyse the image in the HVS colour space. Initially a pre-processing stage that carries out a local histogram equalisation is used to bring back detail in any over or under exposed areas. Secondly we deal with the removal of potential reflections from the affected areas by making use of image registration of two candidate corneal images based on the detected corneal areas. Thirdly the exact corneal boundary is detected by initially registering an ellipse to the candidate corneal boundary detected via edge detection and subsequently allowing the user to modify the boundary to overlap with the boundary of the ulcer being observed. Although this step makes the approach semi automatic, it removes the impact of breakages of the corneal boundary due to occlusion, noise, image quality degradations. The ratio between the ulcer area confined within the corneal area to the corneal area is used as a measure of comparison. We demonstrate the use of the proposed tool in the analysis of the effectiveness of a treatment procedure adopted for corneal ulcers in patients by comparing the variation of corneal size over time.

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.

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.

Predictive assessment of kidney functional recovery following ischemic injury using optical spectroscopy

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

Raman, Rajesh N.; Pivetti, Christopher D.; Ramsamooj, Rajendra

Functional changes in rat kidneys during the induced ischemic injury and recovery phases were explored using multimodal autofluorescence and light scattering imaging. We aim to evaluate the use of noncontact optical signatures for rapid assessment of tissue function and viability. Specifically, autofluorescence images were acquired in vivo under 355, 325, and 266 nm illumination while light scattering images were collected at the excitation wavelengths as well as using relatively narrowband light centered at 500 nm. The images were simultaneously recorded using a multimodal optical imaging system. We also analyzed to obtain time constants, which were correlated to kidney dysfunction asmore » determined by a subsequent survival study and histopathological analysis. This analysis of both the light scattering and autofluorescence images suggests that changes in tissue microstructure, fluorophore emission, and blood absorption spectral characteristics, coupled with vascular response, contribute to the behavior of the observed signal, which may be used to obtain tissue functional information and offer the ability to predict posttransplant kidney function.« less

Predictive assessment of kidney functional recovery following ischemic injury using optical spectroscopy

DOE PAGES

Raman, Rajesh N.; Pivetti, Christopher D.; Ramsamooj, Rajendra; ...

2017-05-03

Functional changes in rat kidneys during the induced ischemic injury and recovery phases were explored using multimodal autofluorescence and light scattering imaging. We aim to evaluate the use of noncontact optical signatures for rapid assessment of tissue function and viability. Specifically, autofluorescence images were acquired in vivo under 355, 325, and 266 nm illumination while light scattering images were collected at the excitation wavelengths as well as using relatively narrowband light centered at 500 nm. The images were simultaneously recorded using a multimodal optical imaging system. We also analyzed to obtain time constants, which were correlated to kidney dysfunction asmore » determined by a subsequent survival study and histopathological analysis. This analysis of both the light scattering and autofluorescence images suggests that changes in tissue microstructure, fluorophore emission, and blood absorption spectral characteristics, coupled with vascular response, contribute to the behavior of the observed signal, which may be used to obtain tissue functional information and offer the ability to predict posttransplant kidney function.« less

System for objective assessment of image differences in digital cinema

NASA Astrophysics Data System (ADS)

Fliegel, Karel; Krasula, Lukáš; Páta, Petr; Myslík, Jiří; Pecák, Josef; Jícha, Marek

2014-09-01

There is high demand for quick digitization and subsequent image restoration of archived film records. Digitization is very urgent in many cases because various invaluable pieces of cultural heritage are stored on aging media. Only selected records can be reconstructed perfectly using painstaking manual or semi-automatic procedures. This paper aims to answer the question what are the quality requirements on the restoration process in order to obtain acceptably close visual perception of the digitally restored film in comparison to the original analog film copy. This knowledge is very important to preserve the original artistic intention of the movie producers. Subjective experiment with artificially distorted images has been conducted in order to answer the question what is the visual impact of common image distortions in digital cinema. Typical color and contrast distortions were introduced and test images were presented to viewers using digital projector. Based on the outcome of this subjective evaluation a system for objective assessment of image distortions has been developed and its performance tested. The system utilizes calibrated digital single-lens reflex camera and subsequent analysis of suitable features of images captured from the projection screen. The evaluation of captured image data has been optimized in order to obtain predicted differences between the reference and distorted images while achieving high correlation with the results of subjective assessment. The system can be used to objectively determine the difference between analog film and digital cinema images on the projection screen.

High-throughput image analysis of tumor spheroids: a user-friendly software application to measure the size of spheroids automatically and accurately.

PubMed

Chen, Wenjin; Wong, Chung; Vosburgh, Evan; Levine, Arnold J; Foran, David J; Xu, Eugenia Y

2014-07-08

The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application - SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary "Manual Initialize" and "Hand Draw" tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.

Do cognitive attributions for smoking predict subsequent smoking development?

PubMed

Guo, Qian; Unger, Jennifer B; Azen, Stanley P; MacKinnon, David P; Johnson, C Anderson

2012-03-01

To develop more effective anti-smoking programs, it is important to understand the factors that influence people to smoke. Guided by attribution theory, a longitudinal study was conducted to investigate how individuals' cognitive attributions for smoking were associated with subsequent smoking development and through which pathways. Middle and high school students in seven large cities in China (N=12,382; 48.5% boys and 51.5% girls) completed two annual surveys. Associations between cognitive attributions for smoking and subsequent smoking initiation and progression were tested with multilevel analysis, taking into account plausible moderation effects of gender and baseline smoking status. Mediation effects of susceptibility to smoking were investigated using statistical mediation analysis (MacKinnon, 2008). Six out of eight tested themes of cognitive attributions were associated with subsequent smoking development. Curiosity (β=0.11, p<0.001) and autonomy (β=0.08, p=0.019) were associated with smoking initiation among baseline non-smokers. Coping (β=0.07, p<0.001) and social image (β=0.10, p=<.0001) were associated with smoking progression among baseline lifetime smokers. Social image (β=0.05, p=0.043), engagement (β=0.07, p=0.003), and mental enhancement (β=0.15, p<0.001) were associated with smoking progression among baseline past 30-day smokers. More attributions were associated with smoking development among males than among females. Susceptibility to smoking partially mediated most of the associations, with the proportion of mediated effects ranging from 4.3% to 30.8%. This study identifies the roles that cognitive attributions for smoking play in subsequent smoking development. These attributions could be addressed in smoking prevention programs. Published by Elsevier Ltd.

Do Cognitive Attributions for Smoking Predict Subsequent Smoking Development?

PubMed Central

Guo, Qian; Unger, Jennifer B.; Azen, Stanley P.; MacKinnon, David P.; Johnson, C. Anderson

2011-01-01

To develop more effective anti-smoking programs, it is important to understand the factors that influence people to smoke. Guided by attribution theory, a longitudinal study was conducted to investigate how individuals’ cognitive attributions for smoking were associated with subsequent smoking development and through which pathways. Middle and high school students in seven large cities in China (N=12,382; 48.5% boys and 51.5% girls) completed two annual surveys. Associations between cognitive attributions for smoking and subsequent smoking initiation and progression were tested with multilevel analysis, taking into account plausible moderation effects of gender and baseline smoking status. Mediation effects of susceptibility to smoking were investigated using statistical mediation analysis (MacKinnon, 2008). Six out of eight tested themes of cognitive attributions were associated with subsequent smoking development. Curiosity (β=0.11, p<0.001) and autonomy (β=0.08, p=0.019) were associated with smoking initiation among baseline non-smokers. Coping (β=0.07, p<0.001) and social image (β=0.10, p=<.0001) were associated with smoking progression among baseline lifetime smokers. Social image (β=0.05, p=0.043), engagement (β=0.07, p=0.003), and mental enhancement (β=0.15, p<0.001) were associated with smoking progression among baseline past 30-day smokers. More attributions were associated with smoking development among males than among females. Susceptibility to smoking partially mediated most of the associations, with the proportion of mediated effects ranging from 4.3% to 30.8%. This study identifies the roles that cognitive attributions for smoking play in subsequent smoking development. These attributions could be addressed in smoking prevention programs. PMID:22112425

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

Image analysis of corrosion pit initiation on ASTM type A240 stainless steel and ASTM type A 1008 carbon steel

NASA Astrophysics Data System (ADS)

Nine, H. M. Zulker

The adversity of metallic corrosion is of growing concern to industrial engineers and scientists. Corrosion attacks metal surface and causes structural as well as direct and indirect economic losses. Multiple corrosion monitoring tools are available although those are time-consuming and costly. Due to the availability of image capturing devices in today's world, image based corrosion control technique is a unique innovation. By setting up stainless steel SS 304 and low carbon steel QD 1008 panels in distilled water, half-saturated sodium chloride and saturated sodium chloride solutions and subsequent RGB image analysis in Matlab, in this research, a simple and cost-effective corrosion measurement tool has identified and investigated. Additionally, the open circuit potential and electrochemical impedance spectroscopy results have been compared with RGB analysis to gratify the corrosion. Additionally, to understand the importance of ambiguity in crisis communication, the communication process between Union Carbide and Indian Government regarding the Bhopal incident in 1984 was analyzed.

Quantitative subsurface analysis using frequency modulated thermal wave imaging

NASA Astrophysics Data System (ADS)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

Integrating medical imaging analyses through a high-throughput bundled resource imaging system

NASA Astrophysics Data System (ADS)

Covington, Kelsie; Welch, E. Brian; Jeong, Ha-Kyu; Landman, Bennett A.

2011-03-01

Exploitation of advanced, PACS-centric image analysis and interpretation pipelines provides well-developed storage, retrieval, and archival capabilities along with state-of-the-art data providence, visualization, and clinical collaboration technologies. However, pursuit of integrated medical imaging analysis through a PACS environment can be limiting in terms of the overhead required to validate, evaluate and integrate emerging research technologies. Herein, we address this challenge through presentation of a high-throughput bundled resource imaging system (HUBRIS) as an extension to the Philips Research Imaging Development Environment (PRIDE). HUBRIS enables PACS-connected medical imaging equipment to invoke tools provided by the Java Imaging Science Toolkit (JIST) so that a medical imaging platform (e.g., a magnetic resonance imaging scanner) can pass images and parameters to a server, which communicates with a grid computing facility to invoke the selected algorithms. Generated images are passed back to the server and subsequently to the imaging platform from which the images can be sent to a PACS. JIST makes use of an open application program interface layer so that research technologies can be implemented in any language capable of communicating through a system shell environment (e.g., Matlab, Java, C/C++, Perl, LISP, etc.). As demonstrated in this proof-of-concept approach, HUBRIS enables evaluation and analysis of emerging technologies within well-developed PACS systems with minimal adaptation of research software, which simplifies evaluation of new technologies in clinical research and provides a more convenient use of PACS technology by imaging scientists.

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1990-01-01

A process is disclosed for x ray registration and differencing which results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

Digital Data Registration and Differencing Compression System

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1996-01-01

A process for X-ray registration and differencing results in more efficient compression. Differencing of registered modeled subject image with a modeled reference image forms a differenced image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three-dimensional model, which three-dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either a remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic X-ray digital images.

Digital data registration and differencing compression system

NASA Technical Reports Server (NTRS)

Ransford, Gary A. (Inventor); Cambridge, Vivien J. (Inventor)

1992-01-01

A process for x ray registration and differencing results in more efficient compression is discussed. Differencing of registered modeled subject image with a modeled reference image forms a differential image for compression with conventional compression algorithms. Obtention of a modeled reference image includes modeling a relatively unrelated standard reference image upon a three dimensional model, which three dimensional model is also used to model the subject image for obtaining the modeled subject image. The registration process of the modeled subject image and modeled reference image translationally correlates such modeled images for resulting correlation thereof in spatial and spectral dimensions. Prior to compression, a portion of the image falling outside a designated area of interest may be eliminated, for subsequent replenishment with a standard reference image. The compressed differenced image may be subsequently transmitted and/or stored, for subsequent decompression and addition to a standard reference image so as to form a reconstituted or approximated subject image at either remote location and/or at a later moment in time. Overall effective compression ratios of 100:1 are possible for thoracic x ray digital images.

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.

Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials

DOEpatents

Boucheron, Laura E

2013-07-16

Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

A Novel Method for Block Size Forensics Based on Morphological Operations

NASA Astrophysics Data System (ADS)

Luo, Weiqi; Huang, Jiwu; Qiu, Guoping

Passive forensics analysis aims to find out how multimedia data is acquired and processed without relying on pre-embedded or pre-registered information. Since most existing compression schemes for digital images are based on block processing, one of the fundamental steps for subsequent forensics analysis is to detect the presence of block artifacts and estimate the block size for a given image. In this paper, we propose a novel method for blind block size estimation. A 2×2 cross-differential filter is first applied to detect all possible block artifact boundaries, morphological operations are then used to remove the boundary effects caused by the edges of the actual image contents, and finally maximum-likelihood estimation (MLE) is employed to estimate the block size. The experimental results evaluated on over 1300 nature images show the effectiveness of our proposed method. Compared with existing gradient-based detection method, our method achieves over 39% accuracy improvement on average.

Color image analysis technique for measuring of fat in meat: an application for the meat industry

NASA Astrophysics Data System (ADS)

Ballerini, Lucia; Hogberg, Anders; Lundstrom, Kerstin; Borgefors, Gunilla

2001-04-01

Intramuscular fat content in meat influences some important meat quality characteristics. The aim of the present study was to develop and apply image processing techniques to quantify intramuscular fat content in beefs together with the visual appearance of fat in meat (marbling). Color images of M. longissimus dorsi meat samples with a variability of intramuscular fat content and marbling were captured. Image analysis software was specially developed for the interpretation of these images. In particular, a segmentation algorithm (i.e. classification of different substances: fat, muscle and connective tissue) was optimized in order to obtain a proper classification and perform subsequent analysis. Segmentation of muscle from fat was achieved based on their characteristics in the 3D color space, and on the intrinsic fuzzy nature of these structures. The method is fully automatic and it combines a fuzzy clustering algorithm, the Fuzzy c-Means Algorithm, with a Genetic Algorithm. The percentages of various colors (i.e. substances) within the sample are then determined; the number, size distribution, and spatial distributions of the extracted fat flecks are measured. Measurements are correlated with chemical and sensory properties. Results so far show that advanced image analysis is useful for quantify the visual appearance of meat.

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling

NASA Astrophysics Data System (ADS)

Comi, Troy J.; Neumann, Elizabeth K.; Do, Thanh D.; Sweedler, Jonathan V.

2017-09-01

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. [Figure not available: see fulltext.

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling.

PubMed

Comi, Troy J; Neumann, Elizabeth K; Do, Thanh D; Sweedler, Jonathan V

2017-09-01

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. Graphical Abstract ᅟ.

Lumbar Imaging with Reporting of Epidemiology (LIRE)- Protocol for a Pragmatic Cluster Randomized Trial

PubMed Central

Jarvik, Jeffrey G.; Comstock, Bryan A.; James, Kathryn T.; Avins, Andrew L.; Bresnahan, Brian W.; Deyo, Richard A.; Luetmer, Patrick H.; Friedly, Janna L.; Meier, Eric N.; Cherkin, Daniel C.; Gold, Laura S.; Rundell, Sean D.; Halabi, Safwan S.; Kallmes, David F.; Tan, Katherine W.; Turner, Judith A.; Kessler, Larry G.; Lavallee, Danielle C.; Stephens, Kari A.; Heagerty, Patrick J.

2015-01-01

Background Diagnostic imaging is often the first step in evaluating patients with back pain and likely functions as a “gateway” to a subsequent cascade of interventions. However, lumbar spine imaging frequently reveals incidental findings among normal, pain-free individuals suggesting that treatment of these “abnormalities” may not be warranted. Our prior work suggested that inserting the prevalence of imaging findings in patients without back pain into spine imaging reports may reduce subsequent interventions. We are now conducting a pragmatic cluster randomized clinical trial to test the hypothesis that inserting this prevalence data into lumbar spine imaging reports for studies ordered by primary care providers will reduce subsequent spine-related interventions. Methods/Design We are using a stepped wedge design that sequentially randomizes 100 primary care clinics at four health systems to receive either standard lumbar spine imaging reports, or reports containing prevalence data for common imaging findings in patients without back pain. We capture all outcomes passively through the electronic medical record. Our primary outcome is spine-related intervention intensity based on Relative Value Units (RVUs) during the following year. Secondary outcomes include subsequent prescriptions for opioid analgesics and cross-sectional lumbar spine re-imaging. Discussion If our study shows that adding prevalence data to spine imaging reports decreases subsequent back-related RVUs, this intervention could be easily generalized and applied to other kinds of testing, as well as other conditions where incidental findings may be common. Our study also serves as a model for cluster randomized trials that are minimal risk and highly pragmatic. PMID:26493088

Rapid and non-destructive identification of water-injected beef samples using multispectral imaging analysis.

PubMed

Liu, Jinxia; Cao, Yue; Wang, Qiu; Pan, Wenjuan; Ma, Fei; Liu, Changhong; Chen, Wei; Yang, Jianbo; Zheng, Lei

2016-01-01

Water-injected beef has aroused public concern as a major food-safety issue in meat products. In the study, the potential of multispectral imaging analysis in the visible and near-infrared (405-970 nm) regions was evaluated for identifying water-injected beef. A multispectral vision system was used to acquire images of beef injected with up to 21% content of water, and partial least squares regression (PLSR) algorithm was employed to establish prediction model, leading to quantitative estimations of actual water increase with a correlation coefficient (r) of 0.923. Subsequently, an optimized model was achieved by integrating spectral data with feature information extracted from ordinary RGB data, yielding better predictions (r = 0.946). Moreover, the prediction equation was transferred to each pixel within the images for visualizing the distribution of actual water increase. These results demonstrate the capability of multispectral imaging technology as a rapid and non-destructive tool for the identification of water-injected beef. Copyright © 2015 Elsevier Ltd. All rights reserved.

2011 Tohoku tsunami hydrographs, currents, flow velocities and ship tracks based on video and TLS measurements

NASA Astrophysics Data System (ADS)

Fritz, Hermann M.; Phillips, David A.; Okayasu, Akio; Shimozono, Takenori; Liu, Haijiang; Takeda, Seiichi; Mohammed, Fahad; Skanavis, Vassilis; Synolakis, Costas E.; Takahashi, Tomoyuki

2013-04-01

The March 11, 2011, magnitude Mw 9.0 earthquake off the Tohoku coast of Japan caused catastrophic damage and loss of life to a tsunami aware population. The mid-afternoon tsunami arrival combined with survivors equipped with cameras on top of vertical evacuation buildings provided fragmented spatially and temporally resolved inundation recordings. This report focuses on the surveys at 9 tsunami eyewitness video recording locations in Myako, Kamaishi, Kesennuma and Yoriisohama along Japan's Sanriku coast and the subsequent video image calibration, processing, tsunami hydrograph and flow velocity analysis. Selected tsunami video recording sites were explored, eyewitnesses interviewed and some ground control points recorded during the initial tsunami reconnaissance in April, 2011. A follow-up survey in June, 2011 focused on terrestrial laser scanning (TLS) at locations with high quality eyewitness videos. We acquired precise topographic data using TLS at the video sites producing a 3-dimensional "point cloud" dataset. A camera mounted on the Riegl VZ-400 scanner yields photorealistic 3D images. Integrated GPS measurements allow accurate georeferencing. The original video recordings were recovered from eyewitnesses and the Japanese Coast Guard (JCG). The analysis of the tsunami videos follows an adapted four step procedure originally developed for the analysis of 2004 Indian Ocean tsunami videos at Banda Aceh, Indonesia (Fritz et al., 2006). The first step requires the calibration of the sector of view present in the eyewitness video recording based on ground control points measured in the LiDAR data. In a second step the video image motion induced by the panning of the video camera was determined from subsequent images by particle image velocimetry (PIV) applied to fixed objects. The third step involves the transformation of the raw tsunami video images from image coordinates to world coordinates with a direct linear transformation (DLT) procedure. Finally, the instantaneous tsunami surface current and flooding velocity vector maps are determined by applying the digital PIV analysis method to the rectified tsunami video images with floating debris clusters. Tsunami currents up to 11 m/s were measured in Kesennuma Bay making navigation impossible (Fritz et al., 2012). Tsunami hydrographs are derived from the videos based on water surface elevations at surface piercing objects identified in the acquired topographic TLS data. Apart from a dominant tsunami crest the hydrograph at Kamaishi also reveals a subsequent draw down to minus 10m exposing the harbor bottom. In some cases ship moorings resist the main tsunami crest only to be broken by the extreme draw down and setting vessels a drift for hours. Further we discuss the complex effects of coastal structures on inundation and outflow hydrographs and flow velocities. Lastly a perspective on the recovery and reconstruction process is provided based on numerous revisits of identical sites between April 2011 and July 2012.

One Size Fits All: Evaluation of the Transferability of a New "Learning" Histologic Image Analysis Application.

PubMed

Arlt, Janine; Homeyer, André; Sänger, Constanze; Dahmen, Uta; Dirsch, Olaf

2016-01-01

Quantitative analysis of histologic slides is of importance for pathology and also to address surgical questions. Recently, a novel application was developed for the automated quantification of whole-slide images. The aim of this study was to test and validate the underlying image analysis algorithm with respect to user friendliness, accuracy, and transferability to different histologic scenarios. The algorithm splits the images into tiles of a predetermined size and identifies the tissue class of each tile. In the training procedure, the user specifies example tiles of the different tissue classes. In the subsequent analysis procedure, the algorithm classifies each tile into the previously specified classes. User friendliness was evaluated by recording training time and testing reproducibility of the training procedure of users with different background. Accuracy was determined with respect to single and batch analysis. Transferability was demonstrated by analyzing tissue of different organs (rat liver, kidney, small bowel, and spleen) and with different stainings (glutamine synthetase and hematoxylin-eosin). Users of different educational background could apply the program efficiently after a short introduction. When analyzing images with similar properties, accuracy of >90% was reached in single images as well as in batch mode. We demonstrated that the novel application is user friendly and very accurate. With the "training" procedure the application can be adapted to novel image characteristics simply by giving examples of relevant tissue structures. Therefore, it is suitable for the fast and efficient analysis of high numbers of fully digitalized histologic sections, potentially allowing "high-throughput" quantitative "histomic" analysis.

Strategies for rare-event detection: an approach for automated fetal cell detection in maternal blood.

PubMed Central

Oosterwijk, J C; Knepflé, C F; Mesker, W E; Vrolijk, H; Sloos, W C; Pattenier, H; Ravkin, I; van Ommen, G J; Kanhai, H H; Tanke, H J

1998-01-01

This article explores the feasibility of the use of automated microscopy and image analysis to detect the presence of rare fetal nucleated red blood cells (NRBCs) circulating in maternal blood. The rationales for enrichment and for automated image analysis for "rare-event" detection are reviewed. We also describe the application of automated image analysis to 42 maternal blood samples, using a protocol consisting of one-step enrichment followed by immunocytochemical staining for fetal hemoglobin (HbF) and FISH for X- and Y-chromosomal sequences. Automated image analysis consisted of multimode microscopy and subsequent visual evaluation of image memories containing the selected objects. The FISH results were compared with the results of conventional karyotyping of the chorionic villi. By use of manual screening, 43% of the slides were found to be positive (>=1 NRBC), with a mean number of 11 NRBCs (range 1-40). By automated microscopy, 52% were positive, with on average 17 NRBCs (range 1-111). There was a good correlation between both manual and automated screening, but the NRBC yield from automated image analysis was found to be superior to that from manual screening (P=.0443), particularly when the NRBC count was >15. Seven (64%) of 11 XY fetuses were correctly diagnosed by FISH analysis of automatically detected cells, and all discrepancies were restricted to the lower cell-count range. We believe that automated microscopy and image analysis reduce the screening workload, are more sensitive than manual evaluation, and can be used to detect rare HbF-containing NRBCs in maternal blood. PMID:9837832

Six-month atrophy in MTL structures is associated with subsequent memory decline in elderly controls

PubMed Central

Murphy, E.A.; Holland, D.; Donohue, M.; McEvoy, L.K.; Hagler, D.J.; Dale, A.M.; Brewer, J. B.

2010-01-01

Neurodegeneration precedes the onset of dementias such as Alzheimer’s by several years. Recent advances in volumetric imaging allow quantification of subtle neuroanatomical change over time periods as short as six months. This study investigates whether neuroanatomical change in medial temporal lobe subregions is associated with later memory decline in elderly controls. Using high-resolution, T1-weighted magnetic resonance images acquired at baseline and six months follow-up, change in cortical thickness and subcortical volumes was measured in 142 healthy elderly subjects (aged 59 – 90 years) from the ADNI cohort. Regression analysis was used to identify whether change in fourteen subregions, selected a priori, was associated with declining performance on memory tests from baseline to two years follow-up. Percent thickness change in the right fusiform and inferior temporal cortices and expansion of the right inferior lateral ventricle were found to be significant predictors of subsequent decline on memory-specific neuropsychological measures. These results demonstrate that six-month regional neurodegeneration can be quantified in the healthy elderly and might help identify those at risk for subsequent cognitive decline. PMID:20633660

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping1[C][W][OPEN

PubMed Central

Klukas, Christian; Chen, Dijun; Pape, Jean-Michel

2014-01-01

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays ‘Fernandez’) plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable. PMID:24760818

The optimal algorithm for Multi-source RS image fusion.

PubMed

Fu, Wei; Huang, Shui-Guang; Li, Zeng-Shun; Shen, Hao; Li, Jun-Shuai; Wang, Peng-Yuan

2016-01-01

In order to solve the issue which the fusion rules cannot be self-adaptively adjusted by using available fusion methods according to the subsequent processing requirements of Remote Sensing (RS) image, this paper puts forward GSDA (genetic-iterative self-organizing data analysis algorithm) by integrating the merit of genetic arithmetic together with the advantage of iterative self-organizing data analysis algorithm for multi-source RS image fusion. The proposed algorithm considers the wavelet transform of the translation invariance as the model operator, also regards the contrast pyramid conversion as the observed operator. The algorithm then designs the objective function by taking use of the weighted sum of evaluation indices, and optimizes the objective function by employing GSDA so as to get a higher resolution of RS image. As discussed above, the bullet points of the text are summarized as follows.•The contribution proposes the iterative self-organizing data analysis algorithm for multi-source RS image fusion.•This article presents GSDA algorithm for the self-adaptively adjustment of the fusion rules.•This text comes up with the model operator and the observed operator as the fusion scheme of RS image based on GSDA. The proposed algorithm opens up a novel algorithmic pathway for multi-source RS image fusion by means of GSDA.

Differential diagnosis of lung carcinoma with three-dimensional quantitative molecular vibrational imaging

NASA Astrophysics Data System (ADS)

Gao, Liang; Hammoudi, Ahmad A.; Li, Fuhai; Thrall, Michael J.; Cagle, Philip T.; Chen, Yuanxin; Yang, Jian; Xia, Xiaofeng; Fan, Yubo; Massoud, Yehia; Wang, Zhiyong; Wong, Stephen T. C.

2012-06-01

The advent of molecularly targeted therapies requires effective identification of the various cell types of non-small cell lung carcinomas (NSCLC). Currently, cell type diagnosis is performed using small biopsies or cytology specimens that are often insufficient for molecular testing after morphologic analysis. Thus, the ability to rapidly recognize different cancer cell types, with minimal tissue consumption, would accelerate diagnosis and preserve tissue samples for subsequent molecular testing in targeted therapy. We report a label-free molecular vibrational imaging framework enabling three-dimensional (3-D) image acquisition and quantitative analysis of cellular structures for identification of NSCLC cell types. This diagnostic imaging system employs superpixel-based 3-D nuclear segmentation for extracting such disease-related features as nuclear shape, volume, and cell-cell distance. These features are used to characterize cancer cell types using machine learning. Using fresh unstained tissue samples derived from cell lines grown in a mouse model, the platform showed greater than 97% accuracy for diagnosis of NSCLC cell types within a few minutes. As an adjunct to subsequent histology tests, our novel system would allow fast delineation of cancer cell types with minimum tissue consumption, potentially facilitating on-the-spot diagnosis, while preserving specimens for additional tests. Furthermore, 3-D measurements of cellular structure permit evaluation closer to the native state of cells, creating an alternative to traditional 2-D histology specimen evaluation, potentially increasing accuracy in diagnosing cell type of lung carcinomas.

Proposal to National Aeronautics and Space Administration for continuation of a grazing incidence imaging telescope for X-ray astronomy using sounding rockets

NASA Technical Reports Server (NTRS)

Murray, B.

1976-01-01

The construction of a high resolution imaging telescope experiment payload suitable for launch on an Astrobee F sounding rocket was proposed. Also integration, launch, and subsequent data analysis effort were included. The payload utilizes major component subassemblies from the HEAO-B satellite program which were nonflight development units for that program. These were the X ray mirror and high resolution imager brassboard detector. The properties of the mirror and detector were discussed. The availability of these items for a sounding rocket experiment were explored with the HEAO-B project office.

An Integrative Object-Based Image Analysis Workflow for Uav Images

NASA Astrophysics Data System (ADS)

Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

2016-06-01

In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

Improvement of automatic hemorrhage detection methods using brightness correction on fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Kakogawa, Masakatsu; Sawada, Akira; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

We have been developing several automated methods for detecting abnormalities in fundus images. The purpose of this study is to improve our automated hemorrhage detection method to help diagnose diabetic retinopathy. We propose a new method for preprocessing and false positive elimination in the present study. The brightness of the fundus image was changed by the nonlinear curve with brightness values of the hue saturation value (HSV) space. In order to emphasize brown regions, gamma correction was performed on each red, green, and blue-bit image. Subsequently, the histograms of each red, blue, and blue-bit image were extended. After that, the hemorrhage candidates were detected. The brown regions indicated hemorrhages and blood vessels and their candidates were detected using density analysis. We removed the large candidates such as blood vessels. Finally, false positives were removed by using a 45-feature analysis. To evaluate the new method for the detection of hemorrhages, we examined 125 fundus images, including 35 images with hemorrhages and 90 normal images. The sensitivity and specificity for the detection of abnormal cases was were 80% and 88%, respectively. These results indicate that the new method may effectively improve the performance of our computer-aided diagnosis system for hemorrhages.

Radiomics: Images Are More than Pictures, They Are Data

PubMed Central

Kinahan, Paul E.; Hricak, Hedvig

2016-01-01

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer. PMID:26579733

A New Test Method of Circuit Breaker Spring Telescopic Characteristics Based Image Processing

NASA Astrophysics Data System (ADS)

Huang, Huimin; Wang, Feifeng; Lu, Yufeng; Xia, Xiaofei; Su, Yi

2018-06-01

This paper applied computer vision technology to the fatigue condition monitoring of springs, and a new telescopic characteristics test method is proposed for circuit breaker operating mechanism spring based on image processing technology. High-speed camera is utilized to capture spring movement image sequences when high voltage circuit breaker operated. Then the image-matching method is used to obtain the deformation-time curve and speed-time curve, and the spring expansion and deformation parameters are extracted from it, which will lay a foundation for subsequent spring force analysis and matching state evaluation. After performing simulation tests at the experimental site, this image analyzing method could solve the complex problems of traditional mechanical sensor installation and monitoring online, status assessment of the circuit breaker spring.

Rapid Prototyping Integrated With Nondestructive Evaluation and Finite Element Analysis

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Baaklini, George Y.

2001-01-01

Most reverse engineering approaches involve imaging or digitizing an object then creating a computerized reconstruction that can be integrated, in three dimensions, into a particular design environment. Rapid prototyping (RP) refers to the practical ability to build high-quality physical prototypes directly from computer aided design (CAD) files. Using rapid prototyping, full-scale models or patterns can be built using a variety of materials in a fraction of the time required by more traditional prototyping techniques (refs. 1 and 2). Many software packages have been developed and are being designed to tackle the reverse engineering and rapid prototyping issues just mentioned. For example, image processing and three-dimensional reconstruction visualization software such as Velocity2 (ref. 3) are being used to carry out the construction process of three-dimensional volume models and the subsequent generation of a stereolithography file that is suitable for CAD applications. Producing three-dimensional models of objects from computed tomography (CT) scans is becoming a valuable nondestructive evaluation methodology (ref. 4). Real components can be rendered and subjected to temperature and stress tests using structural engineering software codes. For this to be achieved, accurate high-resolution images have to be obtained via CT scans and then processed, converted into a traditional file format, and translated into finite element models. Prototyping a three-dimensional volume of a composite structure by reading in a series of two-dimensional images generated via CT and by using and integrating commercial software (e.g. Velocity2, MSC/PATRAN (ref. 5), and Hypermesh (ref. 6)) is being applied successfully at the NASA Glenn Research Center. The building process from structural modeling to the analysis level is outlined in reference 7. Subsequently, a stress analysis of a composite cooling panel under combined thermomechanical loading conditions was performed to validate this process.

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.

The MARTE VNIR imaging spectrometer experiment: design and analysis.

PubMed

Brown, Adrian J; Sutter, Brad; Dunagan, Stephen

2008-10-01

We report on the design, operation, and data analysis methods employed on the VNIR imaging spectrometer instrument that was part of the Mars Astrobiology Research and Technology Experiment (MARTE). The imaging spectrometer is a hyperspectral scanning pushbroom device sensitive to VNIR wavelengths from 400-1000 nm. During the MARTE project, the spectrometer was deployed to the Río Tinto region of Spain. We analyzed subsets of three cores from Río Tinto using a new band modeling technique. We found most of the MARTE drill cores to contain predominantly goethite, though spatially coherent areas of hematite were identified in Core 23. We also distinguished non Fe-bearing minerals that were subsequently analyzed by X-ray diffraction (XRD) and found to be primarily muscovite. We present drill core maps that include spectra of goethite, hematite, and non Fe-bearing minerals.

The MARTE VNIR Imaging Spectrometer Experiment: Design and Analysis

NASA Astrophysics Data System (ADS)

Brown, Adrian J.; Sutter, Brad; Dunagan, Stephen

2008-10-01

We report on the design, operation, and data analysis methods employed on the VNIR imaging spectrometer instrument that was part of the Mars Astrobiology Research and Technology Experiment (MARTE). The imaging spectrometer is a hyperspectral scanning pushbroom device sensitive to VNIR wavelengths from 400-1000 nm. During the MARTE project, the spectrometer was deployed to the Río Tinto region of Spain. We analyzed subsets of three cores from Río Tinto using a new band modeling technique. We found most of the MARTE drill cores to contain predominantly goethite, though spatially coherent areas of hematite were identified in Core 23. We also distinguished non Fe-bearing minerals that were subsequently analyzed by X-ray diffraction (XRD) and found to be primarily muscovite. We present drill core maps that include spectra of goethite, hematite, and non Fe-bearing minerals.

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

Greenberg, S.D.; Smith, S.; Swank, P.R.

Visual cell profiles were used to analyze the distribution of atypical bronchial cells in sputum specimens from cigarette-smoking volunteers, cigarette-smoking asbestos workers and cigarette-smoking uranium miners. The preliminary results of these sputum visual cell profile studies have demonstrated distinctive distributions of bronchial cell atypias in progressive patterns of squamous metaplasia, mild, moderate and severe atypias and carcinoma, similar to those the authors have previously reported using cell image analysis techniques to determine an atypia status index (ASI). The information gained from this study will be helpful in further validating this ASI and subsequently achieving the ultimate goal of employing cellmore » image analysis for the rapid and precise identification of premalignant atypias in sputum.« less

Coincident Aerosol and H2O Retrievals versus HSI Imager Field Campaign ReportH2O Retrievals versus HSI Imager Field Campaign Report

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

Anderson, Gail P.; Cipar, John; Armstrong, Peter S.

Two spectrally calibrated tarpaulins (tarps) were co-located at a fixed Global Positioning System (GPS) position on the gravel antenna field at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site. Their placement was timed to coincide with the overflight of a new hyperspectral imaging satellite. The intention was to provide an analysis of the data obtained, including the measured and retrieved spectral albedos for the calibration tarps. Subsequently, a full suite of retrieved values of H2O column, and the aerosol overburden, were to be compared to those determined by alternate SGPmore » ground truth assets. To the extent possible, the down-looking cloud images would be assessed against the all-sky images. Because cloud contamination above a certain level precludes the inversion processing of the satellite data, coupled with infrequent targeting opportunities, clear-sky conditions were imposed. The SGP site was chosen not only as a target of opportunity for satellite validation, but as perhaps the best coincident field measurement site, as established by DOE’s ARM Facility. The satellite team had every expectation of using the information obtained from the SGP to improve the inversion products for all subsequent satellite images, including the cloud and radiative models and parameterizations and, thereby, the performance assessment for subsequent and historic image collections. Coordinating with the SGP onsite team, four visits, all in 2009, to the Central Facility occurred: • June 6-8 (successful exploratory visit to plan tarp placements, etc.) • July 18-24 (canceled because of forecast for heavy clouds) • Sep 9-12 (ground tarps placed, onset of clouds) • Nov 7-9 (visit ultimately canceled because of weather predictions). As noted, in each instance, any significant overcast prediction precluded image collection from the satellite. Given the long task-scheduling procedures (which were in place for each time period), coupled with other priorities and the satellite lifetime, no alternate SGP images could be obtained.« less

Mirion--a software package for automatic processing of mass spectrometric images.

PubMed

Paschke, C; Leisner, A; Hester, A; Maass, K; Guenther, S; Bouschen, W; Spengler, B

2013-08-01

Mass spectrometric imaging (MSI) techniques are of growing interest for the Life Sciences. In recent years, the development of new instruments employing ion sources that are tailored for spatial scanning allowed the acquisition of large data sets. A subsequent data processing, however, is still a bottleneck in the analytical process, as a manual data interpretation is impossible within a reasonable time frame. The transformation of mass spectrometric data into spatial distribution images of detected compounds turned out to be the most appropriate method to visualize the results of such scans, as humans are able to interpret images faster and easier than plain numbers. Image generation, thus, is a time-consuming and complex yet very efficient task. The free software package "Mirion," presented in this paper, allows the handling and analysis of data sets acquired by mass spectrometry imaging. Mirion can be used for image processing of MSI data obtained from many different sources, as it uses the HUPO-PSI-based standard data format imzML, which is implemented in the proprietary software of most of the mass spectrometer companies. Different graphical representations of the recorded data are available. Furthermore, automatic calculation and overlay of mass spectrometric images promotes direct comparison of different analytes for data evaluation. The program also includes tools for image processing and image analysis.

Efficient bias correction for magnetic resonance image denoising.

PubMed

Mukherjee, Partha Sarathi; Qiu, Peihua

2013-05-30

Magnetic resonance imaging (MRI) is a popular radiology technique that is used for visualizing detailed internal structure of the body. Observed MRI images are generated by the inverse Fourier transformation from received frequency signals of a magnetic resonance scanner system. Previous research has demonstrated that random noise involved in the observed MRI images can be described adequately by the so-called Rician noise model. Under that model, the observed image intensity at a given pixel is a nonlinear function of the true image intensity and of two independent zero-mean random variables with the same normal distribution. Because of such a complicated noise structure in the observed MRI images, denoised images by conventional denoising methods are usually biased, and the bias could reduce image contrast and negatively affect subsequent image analysis. Therefore, it is important to address the bias issue properly. To this end, several bias-correction procedures have been proposed in the literature. In this paper, we study the Rician noise model and the corresponding bias-correction problem systematically and propose a new and more effective bias-correction formula based on the regression analysis and Monte Carlo simulation. Numerical studies show that our proposed method works well in various applications. Copyright © 2012 John Wiley & Sons, Ltd.

Isolation and measurement of the features of arrays of cell aggregates formed by dielectrophoresis using the user-specified Multi Regions Masking (MRM) technique

NASA Astrophysics Data System (ADS)

Yusvana, Rama; Headon, Denis; Markx, Gerard H.

2009-08-01

The use of dielectrophoresis for the construction of artificial skin tissue with skin cells in follicle-like 3D cell aggregates in well-defined patterns is demonstrated. To analyse the patterns produced and to study their development after their formation a Virtual Instrument (VI) system was developed using the LabVIEW IMAQ Vision Development Module. A series of programming functions (algorithms) was used to isolate the features on the image (in our case; the patterned aggregates) and separate them from all other unwanted regions on the image. The image was subsequently converted into a binary version, covering only the desired microarray regions which could then be analysed by computer for automatic object measurements. The analysis utilized the simple and easy-to-use User-Specified Multi-Regions Masking (MRM) technique, which allows one to concentrate the analysis on the desired regions specified in the mask. This simplified the algorithms for the analysis of images of cell arrays having similar geometrical properties. By having a collection of scripts containing masks of different patterns, it was possible to quickly and efficiently develop sets of custom virtual instruments for the offline or online analysis of images of cell arrays in the database.

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.

Roles of universal three-dimensional image analysis devices that assist surgical operations.

PubMed

Sakamoto, Tsuyoshi

2014-04-01

The circumstances surrounding medical image analysis have undergone rapid evolution. In such a situation, it can be said that "imaging" obtained through medical imaging modality and the "analysis" that we employ have become amalgamated. Recently, we feel the distance between "imaging" and "analysis" has become closer regarding the imaging analysis of any organ system, as if both terms mentioned above have become integrated. The history of medical image analysis started with the appearance of the computer. The invention of multi-planar reconstruction (MPR) used in the helical scan had a significant impact and became the basis for recent image analysis. Subsequently, curbed MPR (CPR) and other methods were developed, and the 3D diagnostic imaging and image analysis of the human body have started on a full scale. Volume rendering: the development of a new rendering algorithm and the significant improvement of memory and CPUs contributed to the development of "volume rendering," which allows 3D views with retained internal information. A new value was created by this development; computed tomography (CT) images that used to be for "diagnosis" before that time have become "applicable to treatment." In the past, before the development of volume rendering, a clinician had to mentally reconstruct an image reconfigured for diagnosis into a 3D image, but these developments have allowed the depiction of a 3D image on a monitor. Current technology: Currently, in Japan, the estimation of the liver volume and the perfusion area of the portal vein and hepatic vein are vigorously being adopted during preoperative planning for hepatectomy. Such a circumstance seems to be brought by the substantial improvement of said basic techniques and by upgrading the user interface, allowing doctors easy manipulation by themselves. The following describes the specific techniques. Future of post-processing technology: It is expected, in terms of the role of image analysis, for better or worse, that computer-aided diagnosis (CAD) will develop to a highly advanced level in every diagnostic field. Further, it is also expected in the treatment field that a technique coordinating various devices will be strongly required as a surgery navigator. Actually, surgery using an image navigator is being widely studied, and coordination with hardware, including robots, will also be developed. © 2014 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

TAMEE: data management and analysis for tissue microarrays.

PubMed

Thallinger, Gerhard G; Baumgartner, Kerstin; Pirklbauer, Martin; Uray, Martina; Pauritsch, Elke; Mehes, Gabor; Buck, Charles R; Zatloukal, Kurt; Trajanoski, Zlatko

2007-03-07

With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from http://genome.tugraz.at/Software/TAMEE.

Knowledge discovery from structured mammography reports using inductive logic programming.

PubMed

Burnside, Elizabeth S; Davis, Jesse; Costa, Victor Santos; Dutra, Inês de Castro; Kahn, Charles E; Fine, Jason; Page, David

2005-01-01

The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.

Hyperspectral imaging with in-line interferometric femtosecond stimulated Raman scattering spectroscopy

NASA Astrophysics Data System (ADS)

Dobner, Sven; Fallnich, Carsten

2014-02-01

We present the hyperspectral imaging capabilities of in-line interferometric femtosecond stimulated Raman scattering. The beneficial features of this method, namely, the improved signal-to-background ratio compared to other applicable broadband stimulated Raman scattering methods and the simple experimental implementation, allow for a rather fast acquisition of three-dimensional raster-scanned hyperspectral data-sets, which is shown for PMMA beads and a lipid droplet in water as a demonstration. A subsequent application of a principle component analysis displays the chemical selectivity of the method.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Application of modern autoradiography to nuclear forensic analysis

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

Parsons-Davis, Tashi; Knight, Kim; Fitzgerald, Marc

Modern autoradiography techniques based on phosphorimaging technology using image plates (IPs) and digital scanning can identify heterogeneities in activity distributions and reveal material properties, serving to inform subsequent analyses. Here, we have adopted these advantages for applications in nuclear forensics, the technical analysis of radioactive or nuclear materials found outside of legal control to provide data related to provenance, production history, and trafficking route for the materials. IP autoradiography is a relatively simple, non-destructive method for sample characterization that records an image reflecting the relative intensity of alpha and beta emissions from a two-dimensional surface. Such data are complementary tomore » information gathered from radiochemical characterization via bulk counting techniques, and can guide the application of other spatially resolved techniques such as scanning electron microscopy (SEM) and secondary ion mass spectrometry (SIMS). IP autoradiography can image large 2-dimenstional areas (up to 20 × 40 cm), with relatively low detection limits for actinides and other radioactive nuclides, and sensitivity to a wide dynamic range (10 5) of activity density in a single image. Distributions of radioactivity in nuclear materials can be generated with a spatial resolution of approximately 50 μm using IP autoradiography and digital scanning. While the finest grain silver halide films still provide the best possible resolution (down to ~10 μm), IP autoradiography has distinct practical advantages such as shorter exposure times, no chemical post-processing, reusability, rapid plate scanning, and automated image digitization. Sample preparation requirements are minimal, and the analytical method does not consume or alter the sample. These advantages make IP autoradiography ideal for routine screening of nuclear materials, and for the identification of areas of interest for subsequent micro-characterization methods. Here in this article we present a summary of our setup, as modified for nuclear forensic sample analysis and related research, and provide examples of data from select samples from the nuclear fuel cycle and historical nuclear test debris.« less

Application of modern autoradiography to nuclear forensic analysis

DOE PAGES

Parsons-Davis, Tashi; Knight, Kim; Fitzgerald, Marc; ...

2018-05-20

Modern autoradiography techniques based on phosphorimaging technology using image plates (IPs) and digital scanning can identify heterogeneities in activity distributions and reveal material properties, serving to inform subsequent analyses. Here, we have adopted these advantages for applications in nuclear forensics, the technical analysis of radioactive or nuclear materials found outside of legal control to provide data related to provenance, production history, and trafficking route for the materials. IP autoradiography is a relatively simple, non-destructive method for sample characterization that records an image reflecting the relative intensity of alpha and beta emissions from a two-dimensional surface. Such data are complementary tomore » information gathered from radiochemical characterization via bulk counting techniques, and can guide the application of other spatially resolved techniques such as scanning electron microscopy (SEM) and secondary ion mass spectrometry (SIMS). IP autoradiography can image large 2-dimenstional areas (up to 20 × 40 cm), with relatively low detection limits for actinides and other radioactive nuclides, and sensitivity to a wide dynamic range (10 5) of activity density in a single image. Distributions of radioactivity in nuclear materials can be generated with a spatial resolution of approximately 50 μm using IP autoradiography and digital scanning. While the finest grain silver halide films still provide the best possible resolution (down to ~10 μm), IP autoradiography has distinct practical advantages such as shorter exposure times, no chemical post-processing, reusability, rapid plate scanning, and automated image digitization. Sample preparation requirements are minimal, and the analytical method does not consume or alter the sample. These advantages make IP autoradiography ideal for routine screening of nuclear materials, and for the identification of areas of interest for subsequent micro-characterization methods. Here in this article we present a summary of our setup, as modified for nuclear forensic sample analysis and related research, and provide examples of data from select samples from the nuclear fuel cycle and historical nuclear test debris.« less

Application of modern autoradiography to nuclear forensic analysis.

PubMed

Parsons-Davis, Tashi; Knight, Kim; Fitzgerald, Marc; Stone, Gary; Caldeira, Lee; Ramon, Christina; Kristo, Michael

2018-05-01

Modern autoradiography techniques based on phosphorimaging technology using image plates (IPs) and digital scanning can identify heterogeneities in activity distributions and reveal material properties, serving to inform subsequent analyses. Here, we have adopted these advantages for applications in nuclear forensics, the technical analysis of radioactive or nuclear materials found outside of legal control to provide data related to provenance, production history, and trafficking route for the materials. IP autoradiography is a relatively simple, non-destructive method for sample characterization that records an image reflecting the relative intensity of alpha and beta emissions from a two-dimensional surface. Such data are complementary to information gathered from radiochemical characterization via bulk counting techniques, and can guide the application of other spatially resolved techniques such as scanning electron microscopy (SEM) and secondary ion mass spectrometry (SIMS). IP autoradiography can image large 2-dimenstional areas (up to 20×40cm), with relatively low detection limits for actinides and other radioactive nuclides, and sensitivity to a wide dynamic range (10 5 ) of activity density in a single image. Distributions of radioactivity in nuclear materials can be generated with a spatial resolution of approximately 50μm using IP autoradiography and digital scanning. While the finest grain silver halide films still provide the best possible resolution (down to ∼10μm), IP autoradiography has distinct practical advantages such as shorter exposure times, no chemical post-processing, reusability, rapid plate scanning, and automated image digitization. Sample preparation requirements are minimal, and the analytical method does not consume or alter the sample. These advantages make IP autoradiography ideal for routine screening of nuclear materials, and for the identification of areas of interest for subsequent micro-characterization methods. In this paper we present a summary of our setup, as modified for nuclear forensic sample analysis and related research, and provide examples of data from select samples from the nuclear fuel cycle and historical nuclear test debris. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantifying floral shape variation in 3D using microcomputed tomography: a case study of a hybrid line between actinomorphic and zygomorphic flowers.

PubMed

Wang, Chun-Neng; Hsu, Hao-Chun; Wang, Cheng-Chun; Lee, Tzu-Kuei; Kuo, Yan-Fu

2015-01-01

The quantification of floral shape variations is difficult because flower structures are both diverse and complex. Traditionally, floral shape variations are quantified using the qualitative and linear measurements of two-dimensional (2D) images. The 2D images cannot adequately describe flower structures, and thus lead to unsatisfactory discrimination of the flower shape. This study aimed to acquire three-dimensional (3D) images by using microcomputed tomography (μCT) and to examine the floral shape variations by using geometric morphometrics (GM). To demonstrate the advantages of the 3D-μCT-GM approach, we applied the approach to a second-generation population of florist's gloxinia (Sinningia speciosa) crossed from parents of zygomorphic and actinomorphic flowers. The flowers in the population considerably vary in size and shape, thereby served as good materials to test the applicability of the proposed phenotyping approach. Procedures were developed to acquire 3D volumetric flower images using a μCT scanner, to segment the flower regions from the background, and to select homologous characteristic points (i.e., landmarks) from the flower images for the subsequent GM analysis. The procedures identified 95 landmarks for each flower and thus improved the capability of describing and illustrating the flower shapes, compared with typically lower number of landmarks in 2D analyses. The GM analysis demonstrated that flower opening and dorsoventral symmetry were the principal shape variations of the flowers. The degrees of flower opening and corolla asymmetry were then subsequently quantified directly from the 3D flower images. The 3D-μCT-GM approach revealed shape variations that could not be identified using typical 2D approaches and accurately quantified the flower traits that presented a challenge in 2D images. The approach opens new avenues to investigate floral shape variations.

Rock fracture skeleton tracing by image processing and quantitative analysis by geometry features

NASA Astrophysics Data System (ADS)

Liang, Yanjie

2016-06-01

In rock engineering, fracture measurement is important for many applications. This paper proposes a novel method for rock fracture skeleton tracing and analyzing. As for skeleton localizing, the curvilinear fractures are multiscale enhanced based on a Hessian matrix, after image binarization, and clutters are post-processed by image analysis; subsequently, the fracture skeleton is extracted via ridge detection combined with a distance transform and thinning algorithm, after which gap sewing and burrs removal repair the skeleton. In regard to skeleton analyzing, the roughness and distribution of a fracture network are respectively described by the fractal dimensions D s and D b; the intersection and fragmentation of a fracture network are respectively characterized by the average number of ends and junctions per fracture N average and the average length per fracture L average. Three rock fracture surfaces are analyzed for experiments and the results verify that both the fracture tracing accuracy and the analysis feasibility are satisfactory using the new method.

Detection of Pigment Networks in Dermoscopy Images

NASA Astrophysics Data System (ADS)

Eltayef, Khalid; Li, Yongmin; Liu, Xiaohui

2017-02-01

One of the most important structures in dermoscopy images is the pigment network, which is also one of the most challenging and fundamental task for dermatologists in early detection of melanoma. This paper presents an automatic system to detect pigment network from dermoscopy images. The design of the proposed algorithm consists of four stages. First, a pre-processing algorithm is carried out in order to remove the noise and improve the quality of the image. Second, a bank of directional filters and morphological connected component analysis are applied to detect the pigment networks. Third, features are extracted from the detected image, which can be used in the subsequent stage. Fourth, the classification process is performed by applying feed-forward neural network, in order to classify the region as either normal or abnormal skin. The method was tested on a dataset of 200 dermoscopy images from Hospital Pedro Hispano (Matosinhos), and better results were produced compared to previous studies.

A feasibility study of X-ray phase-contrast mammographic tomography at the Imaging and Medical beamline of the Australian Synchrotron.

PubMed

Nesterets, Yakov I; Gureyev, Timur E; Mayo, Sheridan C; Stevenson, Andrew W; Thompson, Darren; Brown, Jeremy M C; Kitchen, Marcus J; Pavlov, Konstantin M; Lockie, Darren; Brun, Francesco; Tromba, Giuliana

2015-11-01

Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low-dose high-sensitivity three-dimensional mammographic phase-contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X-ray energy, source size, detector resolution, sample-to-detector distance, scanning and data processing strategies in the case of propagation-based phase-contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast-tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation-based phase contrast and demonstrated significant improvement of the quality of phase-contrast CT imaging compared with conventional (absorption-based) CT, at medically acceptable radiation doses.

Use of Landsat Thematic Mapper images in regional correlation of syntectonic strata, Colorado river extensional corridor, California and Arizona

NASA Technical Reports Server (NTRS)

Beratan, K. K.; Blom, R. G.; Crippen, R. E.; Nielson, J. E.

1990-01-01

Enhanced Landsat TM images were used in conjunction with field work to investigate the regional correlation of Miocene rocks in the Colorado River extensional corridor of California and Arizona. Based on field investigations, four sequences of sedimentary and volcanic strata could be recognized in the Mohave Mountains (Arizona) and the eastern Whipple Mountains (California), which display significantly different relative volumes and organization of lithologies. The four sequences were also found to have distinctive appearances on the TM image. The recognition criteria derived from field mapping and image interpretation in the Mohave Mountains and Whipple Mountains were applied to an adjacent area in which stratigraphic affinities were less well known. The results of subsequent field work confirmed the stratigraphic and structural relations suggested by the Tm image analysis.

The cognitive and neural basis of option generation and subsequent choice.

PubMed

Kaiser, Stefan; Simon, Joe J; Kalis, Annemarie; Schweizer, Sophie; Tobler, Philippe N; Mojzisch, Andreas

2013-12-01

Decision-making research has thoroughly investigated how people choose from a set of externally provided options. However, in ill-structured real-world environments, possible options for action are not defined by the situation but have to be generated by the agent. Here, we apply behavioral analysis (Study 1) and functional magnetic resonance imaging (Study 2) to investigate option generation and subsequent choice. For this purpose, we employ a new experimental task that requires participants to generate options for simple real-world scenarios and to subsequently decide among the generated options. Correlational analysis with a cognitive test battery suggests that retrieval of options from long-term memory is a relevant process during option generation. The results of the fMRI study demonstrate that option generation in simple real-world scenarios recruits the anterior prefrontal cortex. Furthermore, we show that choice behavior and its neural correlates differ between self-generated and externally provided options. Specifically, choice between self-generated options is associated with stronger recruitment of the dorsal anterior cingulate cortex. This impact of option generation on subsequent choice underlines the need for an expanded model of decision making to accommodate choice between self-generated options.

Collaborative classification of hyperspectral and visible images with convolutional neural network

NASA Astrophysics Data System (ADS)

Zhang, Mengmeng; Li, Wei; Du, Qian

2017-10-01

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

Ex vivo micro-CT imaging of murine brain models using non-ionic iodinated contrast

NASA Astrophysics Data System (ADS)

Salas Bautista, N.; Martínez-Dávalos, A.; Rodríguez-Villafuerte, M.; Murrieta-Rodríguez, T.; Manjarrez-Marmolejo, J.; Franco-Pérez, J.; Calvillo-Velasco, M. E.

2014-11-01

Preclinical investigation of brain tumors is frequently carried out by means of intracranial implantation of brain tumor xenografts or allografts, with subsequent analysis of tumor growth using conventional histopathology. However, very little has been reported on the use contrast-enhanced techniques in micro-CT imaging for the study of malignant brain tumors in small animal models. The aim of this study has been to test a protocol for ex vivo imaging of murine brain models of glioblastoma multiforme (GBM) after treatment with non-ionic iodinated solution, using an in-house developed laboratory micro-CT. We have found that the best compromise between acquisition time and image quality is obtained using a 50 kVp, 0.5 mAs, 1° angular step on a 360 degree orbit acquisition protocol, with 70 μm reconstructed voxel size using the Feldkamp algorithm. With this parameters up to 4 murine brains can be scanned in tandem in less than 15 minutes. Image segmentation and analysis of three sample brains allowed identifying tumor volumes as small as 0.4 mm3.

Automated Age-related Macular Degeneration screening system using fundus images.

PubMed

Kunumpol, P; Umpaipant, W; Kanchanaranya, N; Charoenpong, T; Vongkittirux, S; Kupakanjana, T; Tantibundhit, C

2017-07-01

This work proposed an automated screening system for Age-related Macular Degeneration (AMD), and distinguishing between wet or dry types of AMD using fundus images to assist ophthalmologists in eye disease screening and management. The algorithm employs contrast-limited adaptive histogram equalization (CLAHE) in image enhancement. Subsequently, discrete wavelet transform (DWT) and locality sensitivity discrimination analysis (LSDA) were used to extract features for a neural network model to classify the results. The results showed that the proposed algorithm was able to distinguish between normal eyes, dry AMD, or wet AMD with 98.63% sensitivity, 99.15% specificity, and 98.94% accuracy, suggesting promising potential as a medical support system for faster eye disease screening at lower costs.

Investigation of methods to search for the boundaries on the image and their use on lung hardware of methods finding saliency map

NASA Astrophysics Data System (ADS)

Semenishchev, E. A.; Marchuk, V. I.; Fedosov, V. P.; Stradanchenko, S. G.; Ruslyakov, D. V.

2015-05-01

This work aimed to study computationally simple method of saliency map calculation. Research in this field received increasing interest for the use of complex techniques in portable devices. A saliency map allows increasing the speed of many subsequent algorithms and reducing the computational complexity. The proposed method of saliency map detection based on both image and frequency space analysis. Several examples of test image from the Kodak dataset with different detalisation considered in this paper demonstrate the effectiveness of the proposed approach. We present experiments which show that the proposed method providing better results than the framework Salience Toolbox in terms of accuracy and speed.

Images of recovery: a photo-elicitation study on the hospital ward.

PubMed

Radley, Alan; Taylor, Diane

2003-01-01

The authors attempted to discover the part the physical setting of the ward plays in patients' recovery by asking patients to take photographs of their ward, its spaces and objects, and then interviewing them about these images in hospital and subsequently in their homes. Photography allowed the patients to identify and capture aspects of the setting that they found salient and provided the photo-elicitation material for the interviews. Based on these data, the authors present (a) a critical discussion of the use of photography as method and its implications for qualitative analysis, (b) an overview of the kinds of image taken with respect to the ward and the course of patients' recovery, and (c) a theoretical analysis, employing Walter Benjamin's use of the concept of mimesis, that understands recovery as a bodily act in response to the shock to the senses that hospitalization and surgery produce.

Computed microtomography visualization and quantification of mouse ischemic brain lesion by nonionic radio contrast agents

PubMed Central

Dobrivojević, Marina; Bohaček, Ivan; Erjavec, Igor; Gorup, Dunja; Gajović, Srećko

2013-01-01

Aim To explore the possibility of brain imaging by microcomputed tomography (microCT) using x-ray contrasting methods to visualize mouse brain ischemic lesions after middle cerebral artery occlusion (MCAO). Methods Isolated brains were immersed in ionic or nonionic radio contrast agent (RCA) for 5 days and subsequently scanned using microCT scanner. To verify whether ex-vivo microCT brain images can be used to characterize ischemic lesions, they were compared to Nissl stained serial histological sections of the same brains. To verify if brains immersed in RCA may be used afterwards for other methods, subsequent immunofluorescent labeling with anti-NeuN was performed. Results Nonionic RCA showed better gray to white matter contrast in the brain, and therefore was selected for further studies. MicroCT measurement of ischemic lesion size and cerebral edema significantly correlated with the values determined by Nissl staining (ischemic lesion size: P=0.0005; cerebral edema: P=0.0002). Brain immersion in nonionic RCA did not affect subsequent immunofluorescent analysis and NeuN immunoreactivity. Conclusion MicroCT method was proven to be suitable for delineation of the ischemic lesion from the non-infarcted tissue, and quantification of lesion volume and cerebral edema. PMID:23444240

Computed microtomography visualization and quantification of mouse ischemic brain lesion by nonionic radio contrast agents.

PubMed

Dobrivojević, Marina; Bohaček, Ivan; Erjavec, Igor; Gorup, Dunja; Gajović, Srećko

2013-02-01

To explore the possibility of brain imaging by microcomputed tomography (microCT) using x-ray contrasting methods to visualize mouse brain ischemic lesions after middle cerebral artery occlusion (MCAO). Isolated brains were immersed in ionic or nonionic radio contrast agent (RCA) for 5 days and subsequently scanned using microCT scanner. To verify whether ex-vivo microCT brain images can be used to characterize ischemic lesions, they were compared to Nissl stained serial histological sections of the same brains. To verify if brains immersed in RCA may be used afterwards for other methods, subsequent immunofluorescent labeling with anti-NeuN was performed. Nonionic RCA showed better gray to white matter contrast in the brain, and therefore was selected for further studies. MicroCT measurement of ischemic lesion size and cerebral edema significantly correlated with the values determined by Nissl staining (ischemic lesion size: P=0.0005; cerebral edema: P=0.0002). Brain immersion in nonionic RCA did not affect subsequent immunofluorescent analysis and NeuN immunoreactivity. MicroCT method was proven to be suitable for delineation of the ischemic lesion from the non-infarcted tissue, and quantification of lesion volume and cerebral edema.

An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

NASA Astrophysics Data System (ADS)

Li, Shuo; Jin, Weiqi; Li, Li; Li, Yiyang

2018-05-01

Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images.

Radar image processing for rock-type discrimination

NASA Technical Reports Server (NTRS)

Blom, R. G.; Daily, M.

1982-01-01

Image processing and enhancement techniques for improving the geologic utility of digital satellite radar images are reviewed. Preprocessing techniques such as mean and variance correction on a range or azimuth line by line basis to provide uniformly illuminated swaths, median value filtering for four-look imagery to eliminate speckle, and geometric rectification using a priori elevation data. Examples are presented of application of preprocessing methods to Seasat and Landsat data, and Seasat SAR imagery was coregistered with Landsat imagery to form composite scenes. A polynomial was developed to distort the radar picture to fit the Landsat image of a 90 x 90 km sq grid, using Landsat color ratios with Seasat intensities. Subsequent linear discrimination analysis was employed to discriminate rock types from known areas. Seasat additions to the Landsat data improved rock identification by 7%.

Nanomanipulation-Coupled Matrix-Assisted Laser Desorption/ Ionization-Direct Organelle Mass Spectrometry: A Technique for the Detailed Analysis of Single Organelles

NASA Astrophysics Data System (ADS)

Phelps, Mandy S.; Sturtevant, Drew; Chapman, Kent D.; Verbeck, Guido F.

2016-02-01

We describe a novel technique combining precise organelle microextraction with deposition and matrix-assisted laser desorption/ionization (MALDI) for a rapid, minimally invasive mass spectrometry (MS) analysis of single organelles from living cells. A dual-positioner nanomanipulator workstation was utilized for both extraction of organelle content and precise co-deposition of analyte and matrix solution for MALDI-direct organelle mass spectrometry (DOMS) analysis. Here, the triacylglycerol (TAG) profiles of single lipid droplets from 3T3-L1 adipocytes were acquired and results validated with nanoelectrospray ionization (NSI) MS. The results demonstrate the utility of the MALDI-DOMS technique as it enabled longer mass analysis time, higher ionization efficiency, MS imaging of the co-deposited spot, and subsequent MS/MS capabilities of localized lipid content in comparison to NSI-DOMS. This method provides selective organellar resolution, which complements current biochemical analyses and prompts for subsequent subcellular studies to be performed where limited samples and analyte volume are of concern.

Imaging samples in silica aerogel using an experimental point spread function.

PubMed

White, Amanda J; Ebel, Denton S

2015-02-01

Light microscopy is a powerful tool that allows for many types of samples to be examined in a rapid, easy, and nondestructive manner. Subsequent image analysis, however, is compromised by distortion of signal by instrument optics. Deconvolution of images prior to analysis allows for the recovery of lost information by procedures that utilize either a theoretically or experimentally calculated point spread function (PSF). Using a laser scanning confocal microscope (LSCM), we have imaged whole impact tracks of comet particles captured in silica aerogel, a low density, porous SiO2 solid, by the NASA Stardust mission. In order to understand the dynamical interactions between the particles and the aerogel, precise grain location and track volume measurement are required. We report a method for measuring an experimental PSF suitable for three-dimensional deconvolution of imaged particles in aerogel. Using fluorescent beads manufactured into Stardust flight-grade aerogel, we have applied a deconvolution technique standard in the biological sciences to confocal images of whole Stardust tracks. The incorporation of an experimentally measured PSF allows for better quantitative measurements of the size and location of single grains in aerogel and more accurate measurements of track morphology.

Face sketch recognition based on edge enhancement via deep learning

NASA Astrophysics Data System (ADS)

Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.

A Sensitive TLRH Targeted Imaging Technique for Ultrasonic Molecular Imaging

PubMed Central

Hu, Xiaowen; Zheng, Hairong; Kruse, Dustin E.; Sutcliffe, Patrick; Stephens, Douglas N.; Ferrara, Katherine W.

2010-01-01

The primary goals of ultrasound molecular imaging are the detection and imaging of ultrasound contrast agents (microbubbles), which are bound to specific vascular surface receptors. Imaging methods that can sensitively and selectively detect and distinguish bound microbubbles from freely circulating microbubbles (free microbubbles) and surrounding tissue are critically important for the practical application of ultrasound contrast molecular imaging. Microbubbles excited by low frequency acoustic pulses emit wide-band echoes with a bandwidth extending beyond 20 MHz; we refer to this technique as TLRH (transmission at a low frequency and reception at a high frequency). Using this wideband, transient echo, we have developed and implemented a targeted imaging technique incorporating a multi-frequency co-linear array and the Siemens Antares® imaging system. The multi-frequency co-linear array integrates a center 5.4 MHz array, used to receive echoes and produce radiation force, and two outer 1.5 MHz arrays used to transmit low frequency incident pulses. The targeted imaging technique makes use of an acoustic radiation force sub-sequence to enhance accumulation and a TLRH imaging sub-sequence to detect bound microbubbles. The radiofrequency (RF) data obtained from the TLRH imaging sub-sequence are processsed to separate echo signatures between tissue, free microbubbles, and bound microbubbles. By imaging biotin-coated microbubbles targeted to avidin-coated cellulose tubes, we demonstrate that the proposed method has a high contrast-to-tissue ratio (up to 34 dB) and a high sensitivity to bound microbubbles (with the ratio of echoes from bound microbubbles versus free microbubbles extending up to 23 dB). The effects of the imaging pulse acoustic pressure, the radiation force sub-sequence and the use of various slow-time filters on the targeted imaging quality are studied. The TLRH targeted imaging method is demonstrated in this study to provide sensitive and selective detection of bound microbubbles for ultrasound molecularly-targeted imaging. PMID:20178897

Estimating Trabecular Bone Mechanical Properties From Non-Invasive Imaging

NASA Technical Reports Server (NTRS)

Hogan, Harry A.; Webster, Laurie

1997-01-01

An important component in developing countermeasures for maintaining musculoskeletal integrity during long-term space flight is an effective and meaningful method of monitoring skeletal condition. Magnetic resonance imaging (MRI) is an attractive non-invasive approach because it avoids the exposure to radiation associated with X-ray based imaging and also provides measures related to bone microstructure rather than just density. The purpose of the research for the 1996 Summer Faculty Fellowship period was to extend the usefulness of the MRI data to estimate the mechanical properties of trabecular bone. The main mechanical properties of interest are the elastic modulus and ultimate strength. Correlations are being investigated between these and fractal analysis parameters, MRI relaxation times, apparent densities, and bone mineral densities. Bone specimens from both human and equine donors have been studied initially to ensure high-quality MR images. Specimens were prepared and scanned from human proximal tibia bones as well as the equine distal radius. The quality of the images from the human bone appeared compromised due to freezing artifact, so only equine bone was included in subsequent procedures since these specimens could be acquired and imaged fresh before being frozen. MRI scans were made spanning a 3.6 cm length on each of 5 equine distal radius specimens. The images were then sent to Dr. Raj Acharya of the State University of New York at Buffalo for fractal analysis. Each piece was cut into 3 slabs approximately 1.2 cm thick and high-resolution contact radiographs were made to provide images for comparing fractal analysis with MR images. Dual energy X-ray absorptiometry (DEXA) scans were also made of each slab for subsequent bone mineral density determination. Slabs were cut into cubes for mechanical using a slow-speed diamond blade wafering saw (Buehler Isomet). The dimensions and wet weights of each cube specimen were measured and recorded. Wet weights were also recorded. Each specimen was labeled and marked to denote anatomic orientations, i.e. superior/inferior (S/I), media/lateral (M/L), and anterior/posterior (A/P). The actual locations of each cube cut were documented and images distributed to define ROI locations for other analyses (to Raj Acharya for fractal analysis, to Jon Richardson at Baylor College of Medicine for DEXA, and to Chen Lin at Baylor College of Medicine for T2* MRI analysis). Quasistatic mechanical testing consisted of compressive loading in all three mutually perpendicular anatomic directions. Cyclic loading was applied for 10 cycles to precondition the specimen and results calculated for the eleventh. For one of three directions tested on each specimen, the 10 cycles were followed with loading to failure. Testing is currently proceeding and once completed the results will be correlated with data from the other analyses. One of the main points of interest is the relationship between fractal dimension and mechanical properties. Throughout preparation and testing all specimens were maintained hydrated with physiological saline and stored frozen when not being used.

The utility of repeat sestamibi scans in patients with primary hyperparathyroidism after an initial negative scan.

PubMed

Krishnamurthy, Vikram D; Sound, Sara; Okoh, Alexis K; Yazici, Pinar; Yigitbas, Hakan; Neumann, Donald; Doshi, Krupa; Berber, Eren

2017-06-01

We analyzed the utility of repeated sestambi scans in patients with primary hyperparathyroidism and its effects on operative referral. We carried out a retrospective review of patients with primary hyperparathyroidism who underwent repeated sestambi scans exclusively within our health system between 1996-2015. Patient demographic, presentation, laboratory, imaging, operative, and pathologic data were reviewed. Univariate analysis with JMP Pro v12 was used to identify factors associated with conversion from an initial negative to a subsequent positive scan. After exclusion criteria (including reoperations), we identified 49 patients in whom 59% (n = 29) of subsequent scans remained negative and 41% (n = 20) converted to positive. Factors associated with an initial negative to a subsequent positive scan included classic presentation and second scans with iodine subtraction (P = .04). Nonsurgeons were less likely to order an iodine-subtraction scan (P < .05). Fewer patients with negative imaging were referred to surgery (33% vs 100%, P = .005), and median time to operation after the first negative scan was 25 months (range 1.4-119). Surgeon-performed ultrasonography had greater sensitivity and positive predictive value than repeated sestamibi scans. Negative sestambi scans decreased and delayed operative referral. Consequently, we identified several process improvement initiatives, including education regarding superior institutional imaging. Combining all findings, we created an algorithm for evaluating patients with primary hyperparathyroidism after initially negative sestamibi scans, which incorporates surgeon-performed ultrasonography. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of multispectral imaging to determine quality attributes and ripeness stage in strawberry fruit.

PubMed

Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2014-01-01

Multispectral imaging with 19 wavelengths in the range of 405-970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit.

Accuracy and precision of computer-assisted analysis of bone density via conventional and digital radiography in relation to dual-energy x-ray absorptiometry.

PubMed

Vaccaro, Calogero; Busetto, Roberto; Bernardini, Daniele; Anselmi, Carlo; Zotti, Alessandro

2012-03-01

To evaluate the precision and accuracy of assessing bone mineral density (BMD) by use of mean gray value (MGV) on digitalized and digital images of conventional and digital radiographs, respectively, of ex vivo bovine and equine bone specimens in relation to the gold-standard technique of dual-energy x-ray absorptiometry (DEXA). Left and right metatarsal bones from 11 beef cattle and right femurs from 2 horses. Bovine specimens were imaged by use of conventional radiography, whereas equine specimens were imaged by use of computed radiography (digital radiography). Each specimen was subsequently scanned by use of the same DEXA equipment. The BMD values resulting from each DEXA scan were paired with the MGVs obtained by use of software on the corresponding digitalized or digital radiographic image. The MGV analysis of digitalized and digital x-ray images was a precise (coefficient of variation, 0.1 and 0.09, respectively) and highly accurate method for assessing BMD, compared with DEXA (correlation coefficient, 0.910 and 0.937 for conventional and digital radiography, respectively). The high correlation between MGV and BMD indicated that MGV analysis may be a reliable alternative to DEXA in assessing radiographic bone density. This may provide a new, inexpensive, and readily available estimate of BMD.

Portable Video/Digital Retinal Funduscope

NASA Technical Reports Server (NTRS)

Taylor, Gerald R.; Meehan, Richard; Hunter, Norwood; Caputo, Michael; Gibson, C. Robert

1991-01-01

Lightweight, inexpensive electronic and photographic instrument developed for detection, monitoring, and objective quantification of ocular/systemic disease or physiological alterations of retina, blood vessels, or other structures in anterior and posterior chambers of eye. Operated with little training. Functions with human or animal subject seated, recumbent, inverted, or in almost any other orientation; and in hospital, laboratory, field, or other environment. Produces video images viewed directly and/or digitized for simultaneous or subsequent analysis. Also equipped to produce photographs and/or fitted with adaptors to produce stereoscopic or magnified images of skin, nose, ear, throat, or mouth to detect lesions or diseases.

Spine stereotactic body radiotherapy utilizing cone-beam CT image-guidance with a robotic couch: intrafraction motion analysis accounting for all six degrees of freedom.

PubMed

Hyde, Derek; Lochray, Fiona; Korol, Renee; Davidson, Melanie; Wong, C Shun; Ma, Lijun; Sahgal, Arjun

2012-03-01

To evaluate the residual setup error and intrafraction motion following kilovoltage cone-beam CT (CBCT) image guidance, for immobilized spine stereotactic body radiotherapy (SBRT) patients, with positioning corrected for in all six degrees of freedom. Analysis is based on 42 consecutive patients (48 thoracic and/or lumbar metastases) treated with a total of 106 fractions and 307 image registrations. Following initial setup, a CBCT was acquired for patient alignment and a pretreatment CBCT taken to verify shifts and determine the residual setup error, followed by a midtreatment and posttreatment CBCT image. For 13 single-fraction SBRT patients, two midtreatment CBCT images were obtained. Initially, a 1.5-mm and 1° tolerance was used to reposition the patient following couch shifts which was subsequently reduced to 1 mm and 1° degree after the first 10 patients. Small positioning errors after the initial CBCT setup were observed, with 90% occurring within 1 mm and 97% within 1°. In analyzing the impact of the time interval for verification imaging (10 ± 3 min) and subsequent image acquisitions (17 ± 4 min), the residual setup error was not significantly different (p > 0.05). A significant difference (p = 0.04) in the average three-dimensional intrafraction positional deviations favoring a more strict tolerance in translation (1 mm vs. 1.5 mm) was observed. The absolute intrafraction motion averaged over all patients and all directions along x, y, and z axis (± SD) were 0.7 ± 0.5 mm and 0.5 ± 0.4 mm for the 1.5 mm and 1 mm tolerance, respectively. Based on a 1-mm and 1° correction threshold, the target was localized to within 1.2 mm and 0.9° with 95% confidence. Near-rigid body immobilization, intrafraction CBCT imaging approximately every 15-20 min, and strict repositioning thresholds in six degrees of freedom yields minimal intrafraction motion allowing for safe spine SBRT delivery. Copyright © 2012 Elsevier Inc. All rights reserved.

IEEE International Symposium on Biomedical Imaging.

PubMed

2017-01-01

The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2018 meeting will include tutorials, and a scientific program composed of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers. High-quality papers are requested containing original contributions to the topics of interest including image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological, and statistical modeling. Accepted 4-page regular papers will be published in the symposium proceedings published by IEEE and included in IEEE Xplore. To encourage attendance by a broader audience of imaging scientists and offer additional presentation opportunities, ISBI 2018 will continue to have a second track featuring posters selected from 1-page abstract submissions without subsequent archival publication.

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.

IOTA: integration optimization, triage and analysis tool for the processing of XFEL diffraction images.

PubMed

Lyubimov, Artem Y; Uervirojnangkoorn, Monarin; Zeldin, Oliver B; Brewster, Aaron S; Murray, Thomas D; Sauter, Nicholas K; Berger, James M; Weis, William I; Brunger, Axel T

2016-06-01

Serial femtosecond crystallography (SFX) uses an X-ray free-electron laser to extract diffraction data from crystals not amenable to conventional X-ray light sources owing to their small size or radiation sensitivity. However, a limitation of SFX is the high variability of the diffraction images that are obtained. As a result, it is often difficult to determine optimal indexing and integration parameters for the individual diffraction images. Presented here is a software package, called IOTA , which uses a grid-search technique to determine optimal spot-finding parameters that can in turn affect the success of indexing and the quality of integration on an image-by-image basis. Integration results can be filtered using a priori information about the Bravais lattice and unit-cell dimensions and analyzed for unit-cell isomorphism, facilitating an improvement in subsequent data-processing steps.

Analysis of Vaginal Microbicide Film Hydration Kinetics by Quantitative Imaging Refractometry

PubMed Central

Rinehart, Matthew; Grab, Sheila; Rohan, Lisa; Katz, David; Wax, Adam

2014-01-01

We have developed a quantitative imaging refractometry technique, based on holographic phase microscopy, as a tool for investigating microscopic structural changes in water-soluble polymeric materials. Here we apply the approach to analyze the structural degradation of vaginal topical microbicide films due to water uptake. We implemented transmission imaging of 1-mm diameter film samples loaded into a flow chamber with a 1.5×2 mm field of view. After water was flooded into the chamber, interference images were captured and analyzed to obtain high resolution maps of the local refractive index and subsequently the volume fraction and mass density of film material at each spatial location. Here, we compare the hydration dynamics of a panel of films with varying thicknesses and polymer compositions, demonstrating that quantitative imaging refractometry can be an effective tool for evaluating and characterizing the performance of candidate microbicide film designs for anti-HIV drug delivery. PMID:24736376

Analysis of vaginal microbicide film hydration kinetics by quantitative imaging refractometry.

PubMed

Rinehart, Matthew; Grab, Sheila; Rohan, Lisa; Katz, David; Wax, Adam

2014-01-01

We have developed a quantitative imaging refractometry technique, based on holographic phase microscopy, as a tool for investigating microscopic structural changes in water-soluble polymeric materials. Here we apply the approach to analyze the structural degradation of vaginal topical microbicide films due to water uptake. We implemented transmission imaging of 1-mm diameter film samples loaded into a flow chamber with a 1.5×2 mm field of view. After water was flooded into the chamber, interference images were captured and analyzed to obtain high resolution maps of the local refractive index and subsequently the volume fraction and mass density of film material at each spatial location. Here, we compare the hydration dynamics of a panel of films with varying thicknesses and polymer compositions, demonstrating that quantitative imaging refractometry can be an effective tool for evaluating and characterizing the performance of candidate microbicide film designs for anti-HIV drug delivery.

A comparative analysis of the dependences of the hemodynamic parameters on changes in ROI's position in perfusion CT scans

NASA Astrophysics Data System (ADS)

Choi, Yong-Seok; Cho, Jae-Hwan; Namgung, Jang-Sun; Kim, Hyo-Jin; Yoon, Dae-Young; Lee, Han-Joo

2013-05-01

This study performed a comparative analysis of cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and mean time-to-peak (TTP) obtained by changing the region of interest's (ROI) anatomical positions, during CT brain perfusion. We acquired axial source images of perfusion CT from 20 patients undergoing CT perfusion exams due to brain trauma. Subsequently, the CBV, CBF, MTT, and TTP values were calculated through data-processing of the perfusion CT images. The color scales for the CBV, CBF, MTT, and TTP maps were obtained using the image data. Anterior cerebral artery (ACA) was taken as the standard ROI for the calculations of the perfusion values. Differences in the hemodynamic average values were compared in a quantitative analysis by placing ROI and the dividing axial images into proximal, middle, and distal segments anatomically. By performing the qualitative analysis using a blind test, we observed changes in the sensory characteristics by using the color scales of the CBV, CBF, and MTT maps in the proximal, middle, and distal segments. According to the qualitative analysis, no differences were found in CBV, CBF, MTT, and TTP values of the proximal, middle, and distal segments and no changes were detected in the color scales of the the CBV, CBF, MTT, and TTP maps in the proximal, middle, and distal segments. We anticipate that the results of the study will useful in assessing brain trauma patients using by perfusion imaging.

On Statistical Analysis of Neuroimages with Imperfect Registration

PubMed Central

Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas

2016-01-01

A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168

Retina vascular network recognition

NASA Astrophysics Data System (ADS)

Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

1993-09-01

The analysis of morphological and structural modifications of the retina vascular network is an interesting investigation method in the study of diabetes and hypertension. Normally this analysis is carried out by qualitative evaluations, according to standardized criteria, though medical research attaches great importance to quantitative analysis of vessel color, shape and dimensions. The paper describes a system which automatically segments and recognizes the ocular fundus circulation and micro circulation network, and extracts a set of features related to morphometric aspects of vessels. For this class of images the classical segmentation methods seem weak. We propose a computer vision system in which segmentation and recognition phases are strictly connected. The system is hierarchically organized in four modules. Firstly the Image Enhancement Module (IEM) operates a set of custom image enhancements to remove blur and to prepare data for subsequent segmentation and recognition processes. Secondly the Papilla Border Analysis Module (PBAM) automatically recognizes number, position and local diameter of blood vessels departing from optical papilla. Then the Vessel Tracking Module (VTM) analyses vessels comparing the results of body and edge tracking and detects branches and crossings. Finally the Feature Extraction Module evaluates PBAM and VTM output data and extracts some numerical indexes. Used algorithms appear to be robust and have been successfully tested on various ocular fundus images.

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.

Hybrid network modeling and the effect of image resolution on digitally-obtained petrophysical and two-phase flow properties

NASA Astrophysics Data System (ADS)

Aghaei, A.

2017-12-01

Digital imaging and modeling of rocks and subsequent simulation of physical phenomena in digitally-constructed rock models are becoming an integral part of core analysis workflows. One of the inherent limitations of image-based analysis, at any given scale, is image resolution. This limitation becomes more evident when the rock has multiple scales of porosity such as in carbonates and tight sandstones. Multi-scale imaging and constructions of hybrid models that encompass images acquired at multiple scales and resolutions are proposed as a solution to this problem. In this study, we investigate the effect of image resolution and unresolved porosity on petrophysical and two-phase flow properties calculated based on images. A helical X-ray micro-CT scanner with a high cone-angle is used to acquire digital rock images that are free of geometric distortion. To remove subjectivity from the analyses, a semi-automated image processing technique is used to process and segment the acquired data into multiple phases. Direct and pore network based models are used to simulate physical phenomena and obtain absolute permeability, formation factor and two-phase flow properties such as relative permeability and capillary pressure. The effect of image resolution on each property is investigated. Finally a hybrid network model incorporating images at multiple resolutions is built and used for simulations. The results from the hybrid model are compared against results from the model built at the highest resolution and those from laboratory tests.

An investigation of density measurement method for yarn-dyed woven fabrics based on dual-side fusion technique

NASA Astrophysics Data System (ADS)

Zhang, Rui; Xin, Binjie

2016-08-01

Yarn density is always considered as the fundamental structural parameter used for the quality evaluation of woven fabrics. The conventional yarn density measurement method is based on one-side analysis. In this paper, a novel density measurement method is developed for yarn-dyed woven fabrics based on a dual-side fusion technique. Firstly, a lab-used dual-side imaging system is established to acquire both face-side and back-side images of woven fabric and the affine transform is used for the alignment and fusion of the dual-side images. Then, the color images of the woven fabrics are transferred from the RGB to the CIE-Lab color space, and the intensity information of the image extracted from the L component is used for texture fusion and analysis. Subsequently, three image fusion methods are developed and utilized to merge the dual-side images: the weighted average method, wavelet transform method and Laplacian pyramid blending method. The fusion efficacy of each method is evaluated by three evaluation indicators and the best of them is selected to do the reconstruction of the complete fabric texture. Finally, the yarn density of the fused image is measured based on the fast Fourier transform, and the yarn alignment image could be reconstructed using the inverse fast Fourier transform. Our experimental results show that the accuracy of density measurement by using the proposed method is close to 99.44% compared with the traditional method and the robustness of this new proposed method is better than that of conventional analysis methods.

Intrusive images and intrusive thoughts as different phenomena: two experimental studies.

PubMed

Hagenaars, Muriel A; Brewin, Chris R; van Minnen, Agnes; Holmes, Emily A; Hoogduin, Kees A L

2010-01-01

According to the dual representation theory of PTSD, intrusive trauma images and intrusive verbal thoughts are produced by separate memory systems. In a previous article it was shown that after watching an aversive film, participants in non-movement conditions reported more intrusive images than participants in a free-to-move control condition (Hagenaars, Van Minnen, Holmes, Brewin, & Hoogduin, 2008). The present study investigates whether the experimental conditions of the Hagenaars et al. study had a different effect on intrusive thoughts than on intrusive images. Experiment 2 further investigated the image-thoughts distinction by manipulating stimulus valence (trauma film versus neutral film) and assessing the subsequent development of intrusive images and thoughts. In addition, both experiments studied the impact of peri-traumatic emotions on subsequent intrusive images and thoughts frequency across conditions. Results showed that experimental manipulations (non-movement and trauma film) caused higher levels of intrusive images relative to control conditions (free movement and neutral film) but they did not affect intrusive thoughts. Peri-traumatic anxiety and horror were associated with subsequent higher levels of intrusive images, but not intrusive thoughts. Correlations were inconclusive for anger and sadness. The results suggest intrusive images and thoughts can be manipulated independently and as such can be considered different phenomena.

The complexity of body image following bariatric surgery: a systematic review of the literature.

PubMed

Ivezaj, V; Grilo, C M

2018-06-13

Poor body image is common among individuals seeking bariatric surgery and is associated with adverse psychosocial sequelae. Following massive weight loss secondary to bariatric surgery, many individuals experience excess skin and associated concerns, leading to subsequent body contouring procedures. Little is known, however, about body image changes and associated features from pre-to post-bariatric surgery and subsequent body contouring. The objective of the present study was to conduct a comprehensive literature review of body image following bariatric surgery to help inform future clinical research and care. The articles for the current review were identified by searching PubMed and SCOPUS and references from relevant articles. A total of 60 articles examining body image post-bariatric surgery were identified, and 45 did not include body contouring surgery. Overall, there was great variation in standards of reporting sample characteristics and body image terms. When examining broad levels of body image dissatisfaction, the literature suggests general improvements in certain aspects of body image following bariatric surgery; however, few studies have systematically examined various body image domains from pre-to post-bariatric surgery and subsequent body contouring surgery. In conclusion, there is a paucity of research that examines the multidimensional elements of body image following bariatric surgery. © 2018 World Obesity Federation.

Atmospheric correction analysis on LANDSAT data over the Amazon region. [Manaus, Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dias, L. A. V.; Dossantos, J. R.; Formaggio, A. R.

1983-01-01

The Amazon Region natural resources were studied in two ways and compared. A LANDSAT scene and its attributes were selected, and a maximum likelihood classification was made. The scene was atmospherically corrected, taking into account Amazonic peculiarities revealed by (ground truth) of the same area, and the subsequent classification. Comparison shows that the classification improves with the atmospherically corrected images.

X-Ray Processing of ChaMPlane Fields: Methods and Initial Results for Selected Anti-Galactic Center Fields

NASA Astrophysics Data System (ADS)

Hong, JaeSub; van den Berg, Maureen; Schlegel, Eric M.; Grindlay, Jonathan E.; Koenig, Xavier; Laycock, Silas; Zhao, Ping

2005-12-01

We describe the X-ray analysis procedure of the ongoing Chandra Multiwavelength Plane (ChaMPlane) Survey and report the initial results from the analysis of 15 selected anti-Galactic center observations (90deg

Sparsity-based image monitoring of crystal size distribution during crystallization

NASA Astrophysics Data System (ADS)

Liu, Tao; Huo, Yan; Ma, Cai Y.; Wang, Xue Z.

2017-07-01

To facilitate monitoring crystal size distribution (CSD) during a crystallization process by using an in-situ imaging system, a sparsity-based image analysis method is proposed for real-time implementation. To cope with image degradation arising from in-situ measurement subject to particle motion, solution turbulence, and uneven illumination background in the crystallizer, sparse representation of a real-time captured crystal image is developed based on using an in-situ image dictionary established in advance, such that the noise components in the captured image can be efficiently removed. Subsequently, the edges of a crystal shape in a captured image are determined in terms of the salience information defined from the denoised crystal images. These edges are used to derive a blur kernel for reconstruction of a denoised image. A non-blind deconvolution algorithm is given for the real-time reconstruction. Consequently, image segmentation can be easily performed for evaluation of CSD. The crystal image dictionary and blur kernels are timely updated in terms of the imaging conditions to improve the restoration efficiency. An experimental study on the cooling crystallization of α-type L-glutamic acid (LGA) is shown to demonstrate the effectiveness and merit of the proposed method.

Earth science research

NASA Technical Reports Server (NTRS)

Botkin, Daniel B.

1987-01-01

The analysis of ground-truth data from the boreal forest plots in the Superior National Forest, Minnesota, was completed. Development of statistical methods was completed for dimension analysis (equations to estimate the biomass of trees from measurements of diameter and height). The dimension-analysis equations were applied to the data obtained from ground-truth plots, to estimate the biomass. Classification and analyses of remote sensing images of the Superior National Forest were done as a test of the technique to determine forest biomass and ecological state by remote sensing. Data was archived on diskette and tape and transferred to UCSB to be used in subsequent research.

Pipeline monitoring with unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Kochetkova, L. I.

2018-05-01

Pipeline leakage during transportation of combustible substances leads to explosion and fire thus causing death of people and destruction of production and accommodation facilities. Continuous pipeline monitoring allows identifying leaks in due time and quickly taking measures for their elimination. The paper describes the solution of identification of pipeline leakage using unmanned aerial vehicles. It is recommended to apply the spectral analysis with input RGB signal to identify pipeline damages. The application of multi-zone digital images allows defining potential spill of oil hydrocarbons as well as possible soil pollution. The method of multi-temporal digital images within the visible region makes it possible to define changes in soil morphology for its subsequent analysis. The given solution is cost efficient and reliable thus allowing reducing timing and labor resources in comparison with other methods of pipeline monitoring.

Automated analysis of clonal cancer cells by intravital imaging

PubMed Central

Coffey, Sarah Earley; Giedt, Randy J; Weissleder, Ralph

2013-01-01

Longitudinal analyses of single cell lineages over prolonged periods have been challenging particularly in processes characterized by high cell turn-over such as inflammation, proliferation, or cancer. RGB marking has emerged as an elegant approach for enabling such investigations. However, methods for automated image analysis continue to be lacking. Here, to address this, we created a number of different multicolored poly- and monoclonal cancer cell lines for in vitro and in vivo use. To classify these cells in large scale data sets, we subsequently developed and tested an automated algorithm based on hue selection. Our results showed that this method allows accurate analyses at a fraction of the computational time required by more complex color classification methods. Moreover, the methodology should be broadly applicable to both in vitro and in vivo analyses. PMID:24349895

Interferogram conditioning for improved Fourier analysis and application to X-ray phase imaging by grating interferometry.

PubMed

Montaux-Lambert, Antoine; Mercère, Pascal; Primot, Jérôme

2015-11-02

An interferogram conditioning procedure, for subsequent phase retrieval by Fourier demodulation, is presented here as a fast iterative approach aiming at fulfilling the classical boundary conditions imposed by Fourier transform techniques. Interference fringe patterns with typical edge discontinuities were simulated in order to reveal the edge artifacts that classically appear in traditional Fourier analysis, and were consecutively used to demonstrate the correction efficiency of the proposed conditioning technique. Optimization of the algorithm parameters is also presented and discussed. Finally, the procedure was applied to grating-based interferometric measurements performed in the hard X-ray regime. The proposed algorithm enables nearly edge-artifact-free retrieval of the phase derivatives. A similar enhancement of the retrieved absorption and fringe visibility images is also achieved.

Magnetic resonance signal moment determination using the Earth's magnetic field.

PubMed

Fridjonsson, E O; Creber, S A; Vrouwenvelder, J S; Johns, M L

2015-03-01

We demonstrate a method to manipulate magnetic resonance data such that the moments of the signal spatial distribution are readily accessible. Usually, magnetic resonance imaging relies on data acquired in so-called k-space which is subsequently Fourier transformed to render an image. Here, via analysis of the complex signal in the vicinity of the centre of k-space we are able to access the first three moments of the signal spatial distribution, ultimately in multiple directions. This is demonstrated for biofouling of a reverse osmosis (RO) membrane module, rendering unique information and an early warning of the onset of fouling. The analysis is particularly applicable for the use of mobile magnetic resonance spectrometers; here we demonstrate it using an Earth's magnetic field system. Copyright © 2015 Elsevier Inc. All rights reserved.

Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens

NASA Astrophysics Data System (ADS)

Litjens, G.; Ehteshami Bejnordi, B.; Timofeeva, N.; Swadi, G.; Kovacs, I.; Hulsbergen-van de Kaa, C.; van der Laak, J.

2015-03-01

Automated detection of prostate cancer in digitized H and E whole-slide images is an important first step for computer-driven grading. Most automated grading algorithms work on preselected image patches as they are too computationally expensive to calculate on the multi-gigapixel whole-slide images. An automated multi-resolution cancer detection system could reduce the computational workload for subsequent grading and quantification in two ways: by excluding areas of definitely normal tissue within a single specimen or by excluding entire specimens which do not contain any cancer. In this work we present a multi-resolution cancer detection algorithm geared towards the latter. The algorithm methodology is as follows: at a coarse resolution the system uses superpixels, color histograms and local binary patterns in combination with a random forest classifier to assess the likelihood of cancer. The five most suspicious superpixels are identified and at a higher resolution more computationally expensive graph and gland features are added to refine classification for these superpixels. Our methods were evaluated in a data set of 204 digitized whole-slide H and E stained images of MR-guided biopsy specimens from 163 patients. A pathologist exhaustively annotated the specimens for areas containing cancer. The performance of our system was evaluated using ten-fold cross-validation, stratified according to patient. Image-based receiver operating characteristic (ROC) analysis was subsequently performed where a specimen containing cancer was considered positive and specimens without cancer negative. We obtained an area under the ROC curve of 0.96 and a 0.4 specificity at a 1.0 sensitivity.

Immobilization of 99-Technetium (VII) by Fe(II)-Goethite and Limited Reoxidation

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

Um, Wooyong; Chang, Hyun-Shik; Icenhower, Jonathan P.

2011-05-04

Synthesized goethite was successfully used with addition of Fe(II) to sequester Tc present in both deionized water and simulated off-gas scrubber waste solutions. Pertechnetate concentration in solution decreased immediately when the pH was raised above 7 by addition of sodium hydroxide. Removal of Tc(VII) from solution occurred most likely as a result of heterogeneous surface-catalyzed reduction to Tc(IV) and subsequent co-precipitation onto the goethite. The final Tc-bearing solid was identified as goethite-dominated Fe(III)-(oxy)hydroxide based on XRD analysis, confirming the widespread observation of its characteristic acicular habit by TEM/SEM images. Analysis of the solid precipitate by XAFS showed that the dominantmore » oxidation state of Tc was Tc(IV) and was in octahedral coordination with Tc-O, Fe-O, and Tc-Fe bond distances that are consistent with direct substitution of Tc for Fe in the goethite structure. In some experiments the final Tc-goethite product was subsequently armored with additional layers of freshly precipitated goethite. Successful incorporation of Tc(IV) within the goethite mineral lattice and subsequent goethite armoring can limit re-oxidation of Tc(IV) and its subsequent release from Tc-goethite waste forms, even when the final product is placed in oxidizing environments that typify shallow waste burial facilities.« less

FIM, a Novel FTIR-Based Imaging Method for High Throughput Locomotion Analysis

PubMed Central

Otto, Nils; Löpmeier, Tim; Valkov, Dimitar; Jiang, Xiaoyi; Klämbt, Christian

2013-01-01

We designed a novel imaging technique based on frustrated total internal reflection (FTIR) to obtain high resolution and high contrast movies. This FTIR-based Imaging Method (FIM) is suitable for a wide range of biological applications and a wide range of organisms. It operates at all wavelengths permitting the in vivo detection of fluorescent proteins. To demonstrate the benefits of FIM, we analyzed large groups of crawling Drosophila larvae. The number of analyzable locomotion tracks was increased by implementing a new software module capable of preserving larval identity during most collision events. This module is integrated in our new tracking program named FIMTrack which subsequently extracts a number of features required for the analysis of complex locomotion phenotypes. FIM enables high throughput screening for even subtle behavioral phenotypes. We tested this newly developed setup by analyzing locomotion deficits caused by the glial knockdown of several genes. Suppression of kinesin heavy chain (khc) or rab30 function led to contraction pattern or head sweeping defects, which escaped in previous analysis. Thus, FIM permits forward genetic screens aimed to unravel the neural basis of behavior. PMID:23349775

Sensitivity and specificity of automated analysis of single-field non-mydriatic fundus photographs by Bosch DR Algorithm—Comparison with mydriatic fundus photography (ETDRS) for screening in undiagnosed diabetic retinopathy

PubMed Central

Bawankar, Pritam; Shanbhag, Nita; K., S. Smitha; Dhawan, Bodhraj; Palsule, Aratee; Kumar, Devesh; Chandel, Shailja

2017-01-01

Diabetic retinopathy (DR) is a leading cause of blindness among working-age adults. Early diagnosis through effective screening programs is likely to improve vision outcomes. The ETDRS seven-standard-field 35-mm stereoscopic color retinal imaging (ETDRS) of the dilated eye is elaborate and requires mydriasis, and is unsuitable for screening. We evaluated an image analysis application for the automated diagnosis of DR from non-mydriatic single-field images. Patients suffering from diabetes for at least 5 years were included if they were 18 years or older. Patients already diagnosed with DR were excluded. Physiologic mydriasis was achieved by placing the subjects in a dark room. Images were captured using a Bosch Mobile Eye Care fundus camera. The images were analyzed by the Retinal Imaging Bosch DR Algorithm for the diagnosis of DR. All subjects also subsequently underwent pharmacological mydriasis and ETDRS imaging. Non-mydriatic and mydriatic images were read by ophthalmologists. The ETDRS readings were used as the gold standard for calculating the sensitivity and specificity for the software. 564 consecutive subjects (1128 eyes) were recruited from six centers in India. Each subject was evaluated at a single outpatient visit. Forty-four of 1128 images (3.9%) could not be read by the algorithm, and were categorized as inconclusive. In four subjects, neither eye provided an acceptable image: these four subjects were excluded from the analysis. This left 560 subjects for analysis (1084 eyes). The algorithm correctly diagnosed 531 of 560 cases. The sensitivity, specificity, and positive and negative predictive values were 91%, 97%, 94%, and 95% respectively. The Bosch DR Algorithm shows favorable sensitivity and specificity in diagnosing DR from non-mydriatic images, and can greatly simplify screening for DR. This also has major implications for telemedicine in the use of screening for retinopathy in patients with diabetes mellitus. PMID:29281690

Sensitivity and specificity of automated analysis of single-field non-mydriatic fundus photographs by Bosch DR Algorithm-Comparison with mydriatic fundus photography (ETDRS) for screening in undiagnosed diabetic retinopathy.

PubMed

Bawankar, Pritam; Shanbhag, Nita; K, S Smitha; Dhawan, Bodhraj; Palsule, Aratee; Kumar, Devesh; Chandel, Shailja; Sood, Suneet

2017-01-01

Diabetic retinopathy (DR) is a leading cause of blindness among working-age adults. Early diagnosis through effective screening programs is likely to improve vision outcomes. The ETDRS seven-standard-field 35-mm stereoscopic color retinal imaging (ETDRS) of the dilated eye is elaborate and requires mydriasis, and is unsuitable for screening. We evaluated an image analysis application for the automated diagnosis of DR from non-mydriatic single-field images. Patients suffering from diabetes for at least 5 years were included if they were 18 years or older. Patients already diagnosed with DR were excluded. Physiologic mydriasis was achieved by placing the subjects in a dark room. Images were captured using a Bosch Mobile Eye Care fundus camera. The images were analyzed by the Retinal Imaging Bosch DR Algorithm for the diagnosis of DR. All subjects also subsequently underwent pharmacological mydriasis and ETDRS imaging. Non-mydriatic and mydriatic images were read by ophthalmologists. The ETDRS readings were used as the gold standard for calculating the sensitivity and specificity for the software. 564 consecutive subjects (1128 eyes) were recruited from six centers in India. Each subject was evaluated at a single outpatient visit. Forty-four of 1128 images (3.9%) could not be read by the algorithm, and were categorized as inconclusive. In four subjects, neither eye provided an acceptable image: these four subjects were excluded from the analysis. This left 560 subjects for analysis (1084 eyes). The algorithm correctly diagnosed 531 of 560 cases. The sensitivity, specificity, and positive and negative predictive values were 91%, 97%, 94%, and 95% respectively. The Bosch DR Algorithm shows favorable sensitivity and specificity in diagnosing DR from non-mydriatic images, and can greatly simplify screening for DR. This also has major implications for telemedicine in the use of screening for retinopathy in patients with diabetes mellitus.

Modeling ECM fiber formation: structure information extracted by analysis of 2D and 3D image sets

NASA Astrophysics Data System (ADS)

Wu, Jun; Voytik-Harbin, Sherry L.; Filmer, David L.; Hoffman, Christoph M.; Yuan, Bo; Chiang, Ching-Shoei; Sturgis, Jennis; Robinson, Joseph P.

2002-05-01

Recent evidence supports the notion that biological functions of extracellular matrix (ECM) are highly correlated to its structure. Understanding this fibrous structure is very crucial in tissue engineering to develop the next generation of biomaterials for restoration of tissues and organs. In this paper, we integrate confocal microscopy imaging and image-processing techniques to analyze the structural properties of ECM. We describe a 2D fiber middle-line tracing algorithm and apply it via Euclidean distance maps (EDM) to extract accurate fibrous structure information, such as fiber diameter, length, orientation, and density, from single slices. Based on a 2D tracing algorithm, we extend our analysis to 3D tracing via Euclidean distance maps to extract 3D fibrous structure information. We use computer simulation to construct the 3D fibrous structure which is subsequently used to test our tracing algorithms. After further image processing, these models are then applied to a variety of ECM constructions from which results of 2D and 3D traces are statistically analyzed.

Photofragment image analysis using the Onion-Peeling Algorithm

NASA Astrophysics Data System (ADS)

Manzhos, Sergei; Loock, Hans-Peter

2003-07-01

With the growing popularity of the velocity map imaging technique, a need for the analysis of photoion and photoelectron images arose. Here, a computer program is presented that allows for the analysis of cylindrically symmetric images. It permits the inversion of the projection of the 3D charged particle distribution using the Onion Peeling Algorithm. Further analysis includes the determination of radial and angular distributions, from which velocity distributions and spatial anisotropy parameters are obtained. Identification and quantification of the different photolysis channels is therefore straightforward. In addition, the program features geometry correction, centering, and multi-Gaussian fitting routines, as well as a user-friendly graphical interface and the possibility of generating synthetic images using either the fitted or user-defined parameters. Program summaryTitle of program: Glass Onion Catalogue identifier: ADRY Program Summary URL:http://cpc.cs.qub.ac.uk/summaries/ADRY Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: none Computer: IBM PC Operating system under which the program has been tested: Windows 98, Windows 2000, Windows NT Programming language used: Delphi 4.0 Memory required to execute with typical data: 18 Mwords No. of bits in a word: 32 No. of bytes in distributed program, including test data, etc.: 9 911 434 Distribution format: zip file Keywords: Photofragment image, onion peeling, anisotropy parameters Nature of physical problem: Information about velocity and angular distributions of photofragments is the basis on which the analysis of the photolysis process resides. Reconstructing the three-dimensional distribution from the photofragment image is the first step, further processing involving angular and radial integration of the inverted image to obtain velocity and angular distributions. Provisions have to be made to correct for slight distortions of the image, and to verify the accuracy of the analysis process. Method of solution: The "Onion Peeling" algorithm described by Helm [Rev. Sci. Instrum. 67 (6) (1996)] is used to perform the image reconstruction. Angular integration with a subsequent multi-Gaussian fit supplies information about the velocity distribution of the photofragments, whereas radial integration with subsequent expansion of the angular distributions over Legendre Polynomials gives the spatial anisotropy parameters. Fitting algorithms have been developed to centre the image and to correct for image distortion. Restrictions on the complexity of the problem: The maximum image size (1280×1280) and resolution (16 bit) are restricted by available memory and can be changed in the source code. Initial centre coordinates within 5 pixels may be required for the correction and the centering algorithm to converge. Peaks on the velocity profile separated by less then the peak width may not be deconvolved. In the charged particle image reconstruction, it is assumed that the kinetic energy released in the dissociation process is small compared to the energy acquired in the electric field. For the fitting parameters to be physically meaningful, cylindrical symmetry of the image has to be assumed but the actual inversion algorithm is stable to distortions of such symmetry in experimental images. Typical running time: The analysis procedure can be divided into three parts: inversion, fitting, and geometry correction. The inversion time grows approx. as R3, where R is the radius of the region of interest: for R=200 pixels it is less than a minute, for R=400 pixels less then 6 min on a 400 MHz IBM personal computer. The time for the velocity fitting procedure to converge depends strongly on the number of peaks in the velocity profile and the convergence criterion. It ranges between less then a second for simple curves and a few minutes for profiles with up to twenty peaks. The time taken for the image correction scales as R2 and depends on the curve profile. It is on the order of a few minutes for images with R=500 pixels. Unusual features of the program: Our centering and image correction algorithm is based on Fourier analysis of the radial distribution to insure the sharpest velocity profile and is insensitive to an uneven intensity distribution. There exists an angular averaging option to stabilize the inversion algorithm and not to loose the resolution at the same time.

Volumetric Abnormalities Predating the Onset of Schizophrenia and Affective Psychoses: An MRI Study in Subjects at Ultrahigh Risk of Psychosis

PubMed Central

Dazzan, Paola; Soulsby, Bridget; Mechelli, Andrea; Wood, Stephen J.; Velakoulis, Dennis; Phillips, Lisa J.; Yung, Alison R.; Chitnis, Xavier; Lin, Ashleigh; Murray, Robin M.; McGorry, Patrick D.; McGuire, Philip K.; Pantelis, Christos

2012-01-01

It remains unclear whether brain structural abnormalities observed before the onset of psychosis are specific to schizophrenia or are common to all psychotic disorders. This study aimed to measure regional gray matter volume prior to the onset of schizophreniform and of affective psychoses. We investigated 102 subjects at ultrahigh risk (UHR) of developing psychosis recruited from the Personal Assessment and Crisis Evaluation Clinic in Melbourne, Australia. Twenty-eight of these subjects developed psychosis subsequent to scanning: 19 schizophrenia, 7 affective psychoses, and 2 other psychoses. We examined regional gray matter volume using 1.5 mm thick, coronal, 1.5 Tesla magnetic resonance imaging and voxel-based morphometry methods of image analysis. Subjects were scanned at presentation and were followed up clinically for a minimum of 12 months, to detect later transition to psychosis. We found that both groups of subjects who subsequently developed psychosis (schizophrenia and affective psychosis) showed reductions in the frontal cortex relative to UHR subjects who did not develop psychosis. The subgroup that subsequently developed schizophrenia also showed smaller volumes in the parietal cortex and, at trend level, in the temporal cortex, whereas those who developed an affective psychosis had significantly smaller subgenual cingulate volumes. These preliminary findings suggest that volumetric abnormalities in UHR individuals developing schizophrenia vs affective psychoses comprise a combination of features that predate both disorders and others that may be specific to the nature of the subsequent disorder. PMID:21518921

Generation of synthetic image sequences for the verification of matching and tracking algorithms for deformation analysis

NASA Astrophysics Data System (ADS)

Bethmann, F.; Jepping, C.; Luhmann, T.

2013-04-01

This paper reports on a method for the generation of synthetic image data for almost arbitrary static or dynamic 3D scenarios. Image data generation is based on pre-defined 3D objects, object textures, camera orientation data and their imaging properties. The procedure does not focus on the creation of photo-realistic images under consideration of complex imaging and reflection models as they are used by common computer graphics programs. In contrast, the method is designed with main emphasis on geometrically correct synthetic images without radiometric impact. The calculation process includes photogrammetric distortion models, hence cameras with arbitrary geometric imaging characteristics can be applied. Consequently, image sets can be created that are consistent to mathematical photogrammetric models to be used as sup-pixel accurate data for the assessment of high-precision photogrammetric processing methods. In the first instance the paper describes the process of image simulation under consideration of colour value interpolation, MTF/PSF and so on. Subsequently the geometric quality of the synthetic images is evaluated with ellipse operators. Finally, simulated image sets are used to investigate matching and tracking algorithms as they have been developed at IAPG for deformation measurement in car safety testing.

Spectrally optimal illuminations for diabetic retinopathy detection in retinal imaging

NASA Astrophysics Data System (ADS)

Bartczak, Piotr; Fält, Pauli; Penttinen, Niko; Ylitepsa, Pasi; Laaksonen, Lauri; Lensu, Lasse; Hauta-Kasari, Markku; Uusitalo, Hannu

2017-04-01

Retinal photography is a standard method for recording retinal diseases for subsequent analysis and diagnosis. However, the currently used white light or red-free retinal imaging does not necessarily provide the best possible visibility of different types of retinal lesions, important when developing diagnostic tools for handheld devices, such as smartphones. Using specifically designed illumination, the visibility and contrast of retinal lesions could be improved. In this study, spectrally optimal illuminations for diabetic retinopathy lesion visualization are implemented using a spectrally tunable light source based on digital micromirror device. The applicability of this method was tested in vivo by taking retinal monochrome images from the eyes of five diabetic volunteers and two non-diabetic control subjects. For comparison to existing methods, we evaluated the contrast of retinal images taken with our method and red-free illumination. The preliminary results show that the use of optimal illuminations improved the contrast of diabetic lesions in retinal images by 30-70%, compared to the traditional red-free illumination imaging.

Applying a CAD-generated imaging marker to assess short-term breast cancer risk

NASA Astrophysics Data System (ADS)

Mirniaharikandehei, Seyedehnafiseh; Zarafshani, Ali; Heidari, Morteza; Wang, Yunzhi; Aghaei, Faranak; Zheng, Bin

2018-02-01

Although whether using computer-aided detection (CAD) helps improve radiologists' performance in reading and interpreting mammograms is controversy due to higher false-positive detection rates, objective of this study is to investigate and test a new hypothesis that CAD-generated false-positives, in particular, the bilateral summation of false-positives, is a potential imaging marker associated with short-term breast cancer risk. An image dataset involving negative screening mammograms acquired from 1,044 women was retrospectively assembled. Each case involves 4 images of craniocaudal (CC) and mediolateral oblique (MLO) view of the left and right breasts. In the next subsequent mammography screening, 402 cases were positive for cancer detected and 642 remained negative. A CAD scheme was applied to process all "prior" negative mammograms. Some features from CAD scheme were extracted, which include detection seeds, the total number of false-positive regions, an average of detection scores and the sum of detection scores in CC and MLO view images. Then the features computed from two bilateral images of left and right breasts from either CC or MLO view were combined. In order to predict the likelihood of each testing case being positive in the next subsequent screening, two logistic regression models were trained and tested using a leave-one-case-out based cross-validation method. Data analysis demonstrated the maximum prediction accuracy with an area under a ROC curve of AUC=0.65+/-0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of [2.95, 6.83]. The results also illustrated an increasing trend in the adjusted odds ratio and risk prediction scores (p<0.01). Thus, the study showed that CAD-generated false-positives might provide a new quantitative imaging marker to help assess short-term breast cancer risk.

An arc control and protection system for the JET lower hybrid antenna based on an imaging system.

PubMed

Figueiredo, J; Mailloux, J; Kirov, K; Kinna, D; Stamp, M; Devaux, S; Arnoux, G; Edwards, J S; Stephen, A V; McCullen, P; Hogben, C

2014-11-01

Arcs are the potentially most dangerous events related to Lower Hybrid (LH) antenna operation. If left uncontrolled they can produce damage and cause plasma disruption by impurity influx. To address this issue an arc real time control and protection imaging system for the Joint European Torus (JET) LH antenna has been implemented. The LH system is one of the additional heating systems at JET. It comprises 24 microwave generators (klystrons, operating at 3.7 GHz) providing up to 5 MW of heating and current drive to the JET plasma. This is done through an antenna composed of an array of waveguides facing the plasma. The protection system presented here is based primarily on an imaging arc detection and real time control system. It has adapted the ITER like wall hotspot protection system using an identical CCD camera and real time image processing unit. A filter has been installed to avoid saturation and spurious system triggers caused by ionization light. The antenna is divided in 24 Regions Of Interest (ROIs) each one corresponding to one klystron. If an arc precursor is detected in a ROI, power is reduced locally with subsequent potential damage and plasma disruption avoided. The power is subsequently reinstated if, during a defined interval of time, arcing is confirmed not to be present by image analysis. This system was successfully commissioned during the restart phase and beginning of the 2013 scientific campaign. Since its installation and commissioning, arcs and related phenomena have been prevented. In this contribution we briefly describe the camera, image processing, and real time control systems. Most importantly, we demonstrate that an LH antenna arc protection system based on CCD camera imaging systems works. Examples of both controlled and uncontrolled LH arc events and their consequences are shown.

Greater neural pattern similarity across repetitions is associated with better memory.

PubMed

Xue, Gui; Dong, Qi; Chen, Chuansheng; Lu, Zhonglin; Mumford, Jeanette A; Poldrack, Russell A

2010-10-01

Repeated study improves memory, but the underlying neural mechanisms of this improvement are not well understood. Using functional magnetic resonance imaging and representational similarity analysis of brain activity, we found that, compared with forgotten items, subsequently remembered faces and words showed greater similarity in neural activation across multiple study in many brain regions, including (but not limited to) the regions whose mean activities were correlated with subsequent memory. This result addresses a longstanding debate in the study of memory by showing that successful episodic memory encoding occurs when the same neural representations are more precisely reactivated across study episodes, rather than when patterns of activation are more variable across time.

Automatic recognition of ship types from infrared images using superstructure moment invariants

NASA Astrophysics Data System (ADS)

Li, Heng; Wang, Xinyu

2007-11-01

Automatic object recognition is an active area of interest for military and commercial applications. In this paper, a system addressing autonomous recognition of ship types in infrared images is proposed. Firstly, an approach of segmentation based on detection of salient features of the target with subsequent shadow removing is proposed, as is the base of the subsequent object recognition. Considering the differences between the shapes of various ships mainly lie in their superstructures, we then use superstructure moment functions invariant to translation, rotation and scale differences in input patterns and develop a robust algorithm of obtaining ship superstructure. Subsequently a back-propagation neural network is used as a classifier in the recognition stage and projection images of simulated three-dimensional ship models are used as the training sets. Our recognition model was implemented and experimentally validated using both simulated three-dimensional ship model images and real images derived from video of an AN/AAS-44V Forward Looking Infrared(FLIR) sensor.

A Complete Color Normalization Approach to Histopathology Images Using Color Cues Computed From Saturation-Weighted Statistics.

PubMed

Li, Xingyu; Plataniotis, Konstantinos N

2015-07-01

In digital histopathology, tasks of segmentation and disease diagnosis are achieved by quantitative analysis of image content. However, color variation in image samples makes it challenging to produce reliable results. This paper introduces a complete normalization scheme to address the problem of color variation in histopathology images jointly caused by inconsistent biopsy staining and nonstandard imaging condition. Method : Different from existing normalization methods that either address partial cause of color variation or lump them together, our method identifies causes of color variation based on a microscopic imaging model and addresses inconsistency in biopsy imaging and staining by an illuminant normalization module and a spectral normalization module, respectively. In evaluation, we use two public datasets that are representative of histopathology images commonly received in clinics to examine the proposed method from the aspects of robustness to system settings, performance consistency against achromatic pixels, and normalization effectiveness in terms of histological information preservation. As the saturation-weighted statistics proposed in this study generates stable and reliable color cues for stain normalization, our scheme is robust to system parameters and insensitive to image content and achromatic colors. Extensive experimentation suggests that our approach outperforms state-of-the-art normalization methods as the proposed method is the only approach that succeeds to preserve histological information after normalization. The proposed color normalization solution would be useful to mitigate effects of color variation in pathology images on subsequent quantitative analysis.

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.

Automated image analysis for quantification of reactive oxygen species in plant leaves.

PubMed

Sekulska-Nalewajko, Joanna; Gocławski, Jarosław; Chojak-Koźniewska, Joanna; Kuźniak, Elżbieta

2016-10-15

The paper presents an image processing method for the quantitative assessment of ROS accumulation areas in leaves stained with DAB or NBT for H 2 O 2 and O 2 - detection, respectively. Three types of images determined by the combination of staining method and background color are considered. The method is based on the principle of supervised machine learning with manually labeled image patterns used for training. The method's algorithm is developed as a JavaScript macro in the public domain Fiji (ImageJ) environment. It allows to select the stained regions of ROS-mediated histochemical reactions, subsequently fractionated according to the weak, medium and intense staining intensity and thus ROS accumulation. It also evaluates total leaf blade area. The precision of ROS accumulation area detection is validated by the Dice Similarity Coefficient in the case of manual patterns. The proposed framework reduces the computation complexity, once prepared, requires less image processing expertise than the competitive methods and represents a routine quantitative imaging assay for a general histochemical image classification. Copyright © 2016 Elsevier Inc. All rights reserved.

The costs and effects of contrast-enhanced magnetic resonance angiography and digital substraction angiography on quality of life in patients with peripheral arterial disease.

PubMed

Bosma, Jan; Dijksman, Lea M; Lam, Kayan; Wisselink, Willem; van Swijndregt, Alexander D Montauban; Vahl, Anco

2014-04-01

Contrast-enhanced magnetic resonance angiography (MRA) and intra-arterial digital subtraction angiography (DSA) both have a high diagnostic performance in the imaging of peripheral arterial occlusive disease (PAOD). However, little is known about the effects of initial, preoperative imaging using MRA or DSA on quality of life (QoL) in relation to costs (cost-utility). To compare cost-utility of treatment strategies using either MRA or DSA as the principal imaging tool, related to QoL, in patients with PAOD. In a prospective subgroup analysis of patients randomized between MRA and DSA (n = 79) for preoperative imaging, QoL questionnaires (SF-36) were obtained at randomization and at 4-month follow-up. Cost-effectiveness from hospital perspective was subsequently compared between groups and the difference in gained or lost QoL per € spent assessed using bootstrap analysis. No difference in quality of life was found. A treatment trajectory employing MRA as the principal imaging modality was almost 20% cheaper, leading to a better cost-utility ratio in favor of MRA. A treatment plan for peripheral arterial occlusive disease employing MRA versus DSA as the principal imaging modality yields a better cost/QoL ratio for MRA.

Research on Optimization of GLCM Parameter in Cell Classification

NASA Astrophysics Data System (ADS)

Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua

2016-05-01

Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.

Accuracy of specimen-specific nonlinear finite element analysis for evaluation of radial diaphysis strength in cadaver material.

PubMed

Matsuura, Yusuke; Kuniyoshi, Kazuki; Suzuki, Takane; Ogawa, Yasufumi; Sukegawa, Koji; Rokkaku, Tomoyuki; Thoreson, Andrew Ryan; An, Kai-Nan; Takahashi, Kazuhisa

2015-01-01

The feasibility of a user-specific finite element model for predicting the in situ strength of the radius after implantation of bone plates for open fracture reduction was established. The effect of metal artifact in CT imaging was characterized. The results were verified against biomechanical test data. Fourteen cadaveric radii were divided into two groups: (1) intact radii for evaluating the accuracy of radial diaphysis strength predictions with finite element analysis and (2) radii with a locking plate affixed for evaluating metal artifact. All bones were imaged with CT. In the plated group, radii were first imaged with the plates affixed (for simulating digital plate removal). They were then subsequently imaged with the locking plates and screws removed (actual plate removal). Fracture strength of the radius diaphysis under axial compression was predicted with a three-dimensional, specimen-specific, nonlinear finite element analysis for both the intact and plated bones (bones with and without the plate captured in the scan). Specimens were then loaded to failure using a universal testing machine to verify the actual fracture load. In the intact group, the physical and predicted fracture loads were strongly correlated. For radii with plates affixed, the physical and predicted (simulated plate removal and actual plate removal) fracture loads were strongly correlated. This study demonstrates that our specimen-specific finite element analysis can accurately predict the strength of the radial diaphysis. The metal artifact from CT imaging was shown to produce an overestimate of strength.

A method for the automated processing and analysis of images of ULVWF-platelet strings.

PubMed

Reeve, Scott R; Abbitt, Katherine B; Cruise, Thomas D; Hose, D Rodney; Lawford, Patricia V

2013-01-01

We present a method for identifying and analysing unusually large von Willebrand factor (ULVWF)-platelet strings in noisy low-quality images. The method requires relatively inexpensive, non-specialist equipment and allows multiple users to be employed in the capture of images. Images are subsequently enhanced and analysed, using custom-written software to perform the processing tasks. The formation and properties of ULVWF-platelet strings released in in vitro flow-based assays have recently become a popular research area. Endothelial cells are incorporated into a flow chamber, chemically stimulated to induce ULVWF release and perfused with isolated platelets which are able to bind to the ULVWF to form strings. The numbers and lengths of the strings released are related to characteristics of the flow. ULVWF-platelet strings are routinely identified by eye from video recordings captured during experiments and analysed manually using basic NIH image software to determine the number of strings and their lengths. This is a laborious, time-consuming task and a single experiment, often consisting of data from four to six dishes of endothelial cells, can take 2 or more days to analyse. The method described here allows analysis of the strings to provide data such as the number and length of strings, number of platelets per string and the distance between each platelet to be found. The software reduces analysis time, and more importantly removes user subjectivity, producing highly reproducible results with an error of less than 2% when compared with detailed manual analysis.

DRAQ5 and Eosin (‘D&E’) as an Analog to Hematoxylin and Eosin for Rapid Fluorescence Histology of Fresh Tissues

PubMed Central

Elfer, Katherine N.; Sholl, Andrew B.; Wang, Mei; Tulman, David B.; Mandava, Sree H.; Lee, Benjamin R.; Brown, J. Quincy

2016-01-01

Real-time on-site histopathology review of biopsy tissues at the point-of-procedure has great potential for significant clinical value and improved patient care. For instance, on-site review can aid in rapid screening of diagnostic biopsies to reduce false-negative results, or in quantitative assessment of biospecimen quality to increase the efficacy of downstream laboratory and histopathology analysis. However, the only currently available rapid pathology method, frozen section analysis (FSA), is too time- and labor-intensive for use in screening large quantities of biopsy tissues and is too destructive for maximum tissue conservation in multiple small needle core biopsies. In this work we demonstrate the spectrally-compatible combination of the nuclear stain DRAQ5 and the anionic counterstain eosin as a dual-component fluorescent staining analog to hematoxylin and eosin intended for use on fresh, unsectioned tissues. Combined with optical sectioning fluorescence microscopy and pseudo-coloring algorithms, DRAQ5 and eosin (“D&E”) enables very fast, non-destructive psuedohistological imaging of tissues at the point-of-acquisition with minimal tissue handling and processing. D&E was validated against H&E on a one-to-one basis on formalin-fixed paraffin-embedded and frozen section tissues of various human organs using standard epi-fluorescence microscopy, demonstrating high fidelity of the staining mechanism as an H&E analog. The method was then applied to fresh, whole 18G renal needle core biopsies and large needle core prostate biospecimen biopsies using fluorescence structured illumination optical sectioning microscopy. We demonstrate the ability to obtain high-resolution histology-like images of unsectioned, fresh tissues similar to subsequent H&E staining of the tissue. The application of D&E does not interfere with subsequent standard-of-care H&E staining and imaging, preserving the integrity of the tissue for thorough downstream analysis. These results indicate that this dual-stain pseudocoloring method could provide a real-time histology-like image at the time of acquisition and valuable objective tissue analysis for the clinician at the time of service. PMID:27788264

Study of time-lapse processing for dynamic hydrologic conditions. [electronic satellite image analysis console for Earth Resources Technology Satellites imagery

NASA Technical Reports Server (NTRS)

Serebreny, S. M.; Evans, W. E.; Wiegman, E. J.

1974-01-01

The usefulness of dynamic display techniques in exploiting the repetitive nature of ERTS imagery was investigated. A specially designed Electronic Satellite Image Analysis Console (ESIAC) was developed and employed to process data for seven ERTS principal investigators studying dynamic hydrological conditions for diverse applications. These applications include measurement of snowfield extent and sediment plumes from estuary discharge, Playa Lake inventory, and monitoring of phreatophyte and other vegetation changes. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The most unique feature of the system is the capability to time lapse the imagery and analytic displays of the imagery. Data products included quantitative measurements of distances and areas, binary thematic maps based on monospectral or multispectral decisions, radiance profiles, and movie loops. Applications of animation for uses other than creating time-lapse sequences are identified. Input to the ESIAC can be either digital or via photographic transparencies.

MTI science, data products, and ground-data processing overview

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Atkins, William H.; Balick, Lee K.; Borel, Christoph C.; Clodius, William B.; Christensen, R. Wynn; Davis, Anthony B.; Echohawk, J. C.; Galbraith, Amy E.; Hirsch, Karen L.; Krone, James B.; Little, Cynthia K.; McLachlan, Peter M.; Morrison, Aaron; Pollock, Kimberly A.; Pope, Paul A.; Novak, Curtis; Ramsey, Keri A.; Riddle, Emily E.; Rohde, Charles A.; Roussel-Dupre, Diane C.; Smith, Barham W.; Smith, Kathy; Starkovich, Kim; Theiler, James P.; Weber, Paul G.

2001-08-01

The mission of the Multispectral Thermal Imager (MTI) satellite is to demonstrate the efficacy of highly accurate multispectral imaging for passive characterization of urban and industrial areas, as well as sites of environmental interest. The satellite makes top-of-atmosphere radiance measurements that are subsequently processed into estimates of surface properties such as vegetation health, temperatures, material composition and others. The MTI satellite also provides simultaneous data for atmospheric characterization at high spatial resolution. To utilize these data the MTI science program has several coordinated components, including modeling, comprehensive ground-truth measurements, image acquisition planning, data processing and data interpretation and analysis. Algorithms have been developed to retrieve a multitude of physical quantities and these algorithms are integrated in a processing pipeline architecture that emphasizes automation, flexibility and programmability. In addition, the MTI science team has produced detailed site, system and atmospheric models to aid in system design and data analysis. This paper provides an overview of the MTI research objectives, data products and ground data processing.

Application of Photoshop and Scion Image analysis to quantification of signals in histochemistry, immunocytochemistry and hybridocytochemistry.

PubMed

Tolivia, Jorge; Navarro, Ana; del Valle, Eva; Perez, Cristina; Ordoñez, Cristina; Martínez, Eva

2006-02-01

To describe a simple method to achieve the differential selection and subsequent quantification of the strength signal using only one section. Several methods for performing quantitative histochemistry, immunocytochemistry or hybridocytochemistry, without use of specific commercial image analysis systems, rely on pixel-counting algorithms, which do not provide information on the amount of chromogen present in the section. Other techniques use complex algorithms to calculate the cumulative signal strength using two consecutive sections. To separate the chromogen signal we used the "Color range" option of the Adobe Photoshop program, which provides a specific file for a particular chromogen selection that could be applied on similar sections. The measurement of the chromogen signal strength of the specific staining is achieved with the Scion Image software program. The method described in this paper can also be applied to simultaneous detection of different signals on the same section or different parameters (area of particles, number of particles, etc.) when the "Analyze particles" tool of the Scion program is used.

The design and validation of a magnetic resonance imaging-compatible device for obtaining mechanical properties of plantar soft tissue via gated acquisition.

PubMed

Williams, Evan D; Stebbins, Michael J; Cavanagh, Peter R; Haynor, David R; Chu, Baocheng; Fassbind, Michael J; Isvilanonda, Vara; Ledoux, William R

2015-10-01

Changes in the mechanical properties of the plantar soft tissue in people with diabetes may contribute to the formation of plantar ulcers. Such ulcers have been shown to be in the causal pathway for lower extremity amputation. The hydraulic plantar soft tissue reducer (HyPSTER) was designed to measure in vivo, rate-dependent plantar soft tissue compressive force and three-dimensional deformations to help understand, predict, and prevent ulcer formation. These patient-specific values can then be used in an inverse finite element analysis to determine tissue moduli, and subsequently used in a foot model to show regions of high stress under a wide variety of loading conditions. The HyPSTER uses an actuator to drive a magnetic resonance imaging-compatible hydraulic loading platform. Pressure and actuator position were synchronized with gated magnetic resonance imaging acquisition. Achievable loading rates were slower than those found in normal walking because of a water-hammer effect (pressure wave ringing) in the hydraulic system when the actuator direction was changed rapidly. The subsequent verification tests were, therefore, performed at 0.2 Hz. The unloaded displacement accuracy of the system was within 0.31%. Compliance, presumably in the system's plastic components, caused a displacement loss of 5.7 mm during a 20-mm actuator test at 1354 N. This was accounted for with a target to actual calibration curve. The positional accuracy of the HyPSTER during loaded displacement verification tests from 3 to 9 mm against a silicone backstop was 95.9% with a precision of 98.7%. The HyPSTER generated minimal artifact in the magnetic resonance imaging scanner. Careful analysis of the synchronization of the HyPSTER and the magnetic resonance imaging scanner was performed. With some limitations, the HyPSTER provided key functionality in measuring dynamic, patient-specific plantar soft tissue mechanical properties. © IMechE 2015.

A Microfluidic Technique to Probe Cell Deformability

PubMed Central

Hoelzle, David J.; Varghese, Bino A.; Chan, Clara K.; Rowat, Amy C.

2014-01-01

Here we detail the design, fabrication, and use of a microfluidic device to evaluate the deformability of a large number of individual cells in an efficient manner. Typically, data for ~102 cells can be acquired within a 1 hr experiment. An automated image analysis program enables efficient post-experiment analysis of image data, enabling processing to be complete within a few hours. Our device geometry is unique in that cells must deform through a series of micron-scale constrictions, thereby enabling the initial deformation and time-dependent relaxation of individual cells to be assayed. The applicability of this method to human promyelocytic leukemia (HL-60) cells is demonstrated. Driving cells to deform through micron-scale constrictions using pressure-driven flow, we observe that human promyelocytic (HL-60) cells momentarily occlude the first constriction for a median time of 9.3 msec before passaging more quickly through the subsequent constrictions with a median transit time of 4.0 msec per constriction. By contrast, all-trans retinoic acid-treated (neutrophil-type) HL-60 cells occlude the first constriction for only 4.3 msec before passaging through the subsequent constrictions with a median transit time of 3.3 msec. This method can provide insight into the viscoelastic nature of cells, and ultimately reveal the molecular origins of this behavior. PMID:25226269

Is the spatial distribution of brain lesions associated with closed-head injury in children predictive of subsequent development of posttraumatic stress disorder?

NASA Technical Reports Server (NTRS)

Herskovits, Edward H.; Gerring, Joan P.; Davatzikos, Christos; Bryan, R. Nick

2002-01-01

PURPOSE: To determine whether there is an association between the spatial distributions of lesions detected at magnetic resonance (MR) imaging of the brain in children, adolescents, and young adults after closed-head injury (CHI) and development of the reexperiencing symptoms of posttraumatic stress disorder (PTSD). MATERIALS AND METHODS: Data obtained in 94 subjects without a history of PTSD as determined by parental interview were analyzed. MR images were obtained 3 months after CHI. Lesions were manually delineated and registered to the Talairach coordinate system. Mann-Whitney analysis of lesion distribution and PTSD status at 1 year (again, as determined by parental interview) was performed, consisting of an analysis of lesion distribution versus the major symptoms of PTSD: reexperiencing, hyperarousal, and avoidance. RESULTS: Of the 94 subjects, 41 met the PTSD reexperiencing criterion and nine met all three PTSD criteria. Subjects who met the reexperiencing criterion had fewer lesions in limbic system structures (eg, the cingulum) on the right than did subjects who did not meet this criterion (Mann-Whitney, P =.003). CONCLUSION: Lesions induced by CHI in the limbic system on the right may inhibit subsequent manifestation of PTSD reexperiencing symptoms in children, adolescents, and young adults. Copyright RSNA, 2002.

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

Omniview motionless camera orientation system

NASA Technical Reports Server (NTRS)

Martin, H. Lee (Inventor); Kuban, Daniel P. (Inventor); Zimmermann, Steven D. (Inventor); Busko, Nicholas (Inventor)

2010-01-01

An apparatus and method is provided for converting digital images for use in an imaging system. The apparatus includes a data memory which stores digital data representing an image having a circular or spherical field of view such as an image captured by a fish-eye lens, a control input for receiving a signal for selecting a portion of the image, and a converter responsive to the control input for converting digital data corresponding to the selected portion into digital data representing a planar image for subsequent display. Various methods include the steps of storing digital data representing an image having a circular or spherical field of view, selecting a portion of the image, and converting the stored digital data corresponding to the selected portion into digital data representing a planar image for subsequent display. In various embodiments, the data converter and data conversion step may use an orthogonal set of transformation algorithms.

Application of Multispectral Imaging to Determine Quality Attributes and Ripeness Stage in Strawberry Fruit

PubMed Central

Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2014-01-01

Multispectral imaging with 19 wavelengths in the range of 405–970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit. PMID:24505317

Anatomic and functional imaging of tagged molecules in animals

DOEpatents

Weisenberger, Andrew G [Yorktown, VA; Majewski, Stanislaw [Grafton, VA; Paulus, Michael J [Knoxville, TN; Gleason, Shaun S [Knoxville, VA

2007-04-24

A novel functional imaging system for use in the imaging of unrestrained and non-anesthetized small animals or other subjects and a method for acquiring such images and further registering them with anatomical X-ray images previously or subsequently acquired. The apparatus comprises a combination of an IR laser profilometry system and gamma, PET and/or SPECT, imaging system, all mounted on a rotating gantry, that permits simultaneous acquisition of positional and orientational information and functional images of an unrestrained subject that are registered, i.e. integrated, using image processing software to produce a functional image of the subject without the use of restraints or anesthesia. The functional image thus obtained can be registered with a previously or subsequently obtained X-ray CT image of the subject. The use of the system described herein permits functional imaging of a subject in an unrestrained/non-anesthetized condition thereby reducing the stress on the subject and eliminating any potential interference with the functional testing that such stress might induce.

Image interpolation allows accurate quantitative bone morphometry in registered micro-computed tomography scans.

PubMed

Schulte, Friederike A; Lambers, Floor M; Mueller, Thomas L; Stauber, Martin; Müller, Ralph

2014-04-01

Time-lapsed in vivo micro-computed tomography is a powerful tool to analyse longitudinal changes in the bone micro-architecture. Registration can overcome problems associated with spatial misalignment between scans; however, it requires image interpolation which might affect the outcome of a subsequent bone morphometric analysis. The impact of the interpolation error itself, though, has not been quantified to date. Therefore, the purpose of this ex vivo study was to elaborate the effect of different interpolator schemes [nearest neighbour, tri-linear and B-spline (BSP)] on bone morphometric indices. None of the interpolator schemes led to significant differences between interpolated and non-interpolated images, with the lowest interpolation error found for BSPs (1.4%). Furthermore, depending on the interpolator, the processing order of registration, Gaussian filtration and binarisation played a role. Independent from the interpolator, the present findings suggest that the evaluation of bone morphometry should be done with images registered using greyscale information.

Bias correction for magnetic resonance images via joint entropy regularization.

PubMed

Wang, Shanshan; Xia, Yong; Dong, Pei; Luo, Jianhua; Huang, Qiu; Feng, Dagan; Li, Yuanxiang

2014-01-01

Due to the imperfections of the radio frequency (RF) coil or object-dependent electrodynamic interactions, magnetic resonance (MR) images often suffer from a smooth and biologically meaningless bias field, which causes severe troubles for subsequent processing and quantitative analysis. To effectively restore the original signal, this paper simultaneously exploits the spatial and gradient features of the corrupted MR images for bias correction via the joint entropy regularization. With both isotropic and anisotropic total variation (TV) considered, two nonparametric bias correction algorithms have been proposed, namely IsoTVBiasC and AniTVBiasC. These two methods have been applied to simulated images under various noise levels and bias field corruption and also tested on real MR data. The test results show that the proposed two methods can effectively remove the bias field and also present comparable performance compared to the state-of-the-art methods.

Geostatistical borehole image-based mapping of karst-carbonate aquifer pores

USGS Publications Warehouse

Michael Sukop,; Cunningham, Kevin J.

2016-01-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes.

Applications of LANDSAT data to the integrated economic development of Mindoro, Phillipines

NASA Technical Reports Server (NTRS)

Wagner, T. W.; Fernandez, J. C.

1977-01-01

LANDSAT data is seen as providing essential up-to-date resource information for the planning process. LANDSAT data of Mindoro Island in the Philippines was processed to provide thematic maps showing patterns of agriculture, forest cover, terrain, wetlands and water turbidity. A hybrid approach using both supervised and unsupervised classification techniques resulted in 30 different scene classes which were subsequently color-coded and mapped at a scale of 1:250,000. In addition, intensive image analysis is being carried out in evaluating the images. The images, maps, and aerial statistics are being used to provide data to seven technical departments in planning the economic development of Mindoro. Multispectral aircraft imagery was collected to compliment the application of LANDSAT data and validate the classification results.

Fast and accurate automated cell boundary determination for fluorescence microscopy

NASA Astrophysics Data System (ADS)

Arce, Stephen Hugo; Wu, Pei-Hsun; Tseng, Yiider

2013-07-01

Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology.

A new method of SC image processing for confluence estimation.

PubMed

Soleimani, Sajjad; Mirzaei, Mohsen; Toncu, Dana-Cristina

2017-10-01

Stem cells images are a strong instrument in the estimation of confluency during their culturing for therapeutic processes. Various laboratory conditions, such as lighting, cell container support and image acquisition equipment, effect on the image quality, subsequently on the estimation efficiency. This paper describes an efficient image processing method for cell pattern recognition and morphological analysis of images that were affected by uneven background. The proposed algorithm for enhancing the image is based on coupling a novel image denoising method through BM3D filter with an adaptive thresholding technique for improving the uneven background. This algorithm works well to provide a faster, easier, and more reliable method than manual measurement for the confluency assessment of stem cell cultures. The present scheme proves to be valid for the prediction of the confluency and growth of stem cells at early stages for tissue engineering in reparatory clinical surgery. The method used in this paper is capable of processing the image of the cells, which have already contained various defects due to either personnel mishandling or microscope limitations. Therefore, it provides proper information even out of the worst original images available. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic SAR/optical cross-matching for GCP monograph generation

NASA Astrophysics Data System (ADS)

Nutricato, Raffaele; Morea, Alberto; Nitti, Davide Oscar; La Mantia, Claudio; Agrimano, Luigi; Samarelli, Sergio; Chiaradia, Maria Teresa

2016-10-01

Ground Control Points (GCP), automatically extracted from Synthetic Aperture Radar (SAR) images through 3D stereo analysis, can be effectively exploited for an automatic orthorectification of optical imagery if they can be robustly located in the basic optical images. The present study outlines a SAR/Optical cross-matching procedure that allows a robust alignment of radar and optical images, and consequently to derive automatically the corresponding sub-pixel position of the GCPs in the optical image in input, expressed as fractional pixel/line image coordinates. The cross-matching in performed in two subsequent steps, in order to gradually gather a better precision. The first step is based on the Mutual Information (MI) maximization between optical and SAR chips while the last one uses the Normalized Cross-Correlation as similarity metric. This work outlines the designed algorithmic solution and discusses the results derived over the urban area of Pisa (Italy), where more than ten COSMO-SkyMed Enhanced Spotlight stereo images with different beams and passes are available. The experimental analysis involves different satellite images, in order to evaluate the performances of the algorithm w.r.t. the optical spatial resolution. An assessment of the performances of the algorithm has been carried out, and errors are computed by measuring the distance between the GCP pixel/line position in the optical image, automatically estimated by the tool, and the "true" position of the GCP, visually identified by an expert user in the optical images.

Influence of speckle image reconstruction on photometric precision for large solar telescopes

NASA Astrophysics Data System (ADS)

Peck, C. L.; Wöger, F.; Marino, J.

2017-11-01

Context. High-resolution observations from large solar telescopes require adaptive optics (AO) systems to overcome image degradation caused by Earth's turbulent atmosphere. AO corrections are, however, only partial. Achieving near-diffraction limited resolution over a large field of view typically requires post-facto image reconstruction techniques to reconstruct the source image. Aims: This study aims to examine the expected photometric precision of amplitude reconstructed solar images calibrated using models for the on-axis speckle transfer functions and input parameters derived from AO control data. We perform a sensitivity analysis of the photometric precision under variations in the model input parameters for high-resolution solar images consistent with four-meter class solar telescopes. Methods: Using simulations of both atmospheric turbulence and partial compensation by an AO system, we computed the speckle transfer function under variations in the input parameters. We then convolved high-resolution numerical simulations of the solar photosphere with the simulated atmospheric transfer function, and subsequently deconvolved them with the model speckle transfer function to obtain a reconstructed image. To compute the resulting photometric precision, we compared the intensity of the original image with the reconstructed image. Results: The analysis demonstrates that high photometric precision can be obtained for speckle amplitude reconstruction using speckle transfer function models combined with AO-derived input parameters. Additionally, it shows that the reconstruction is most sensitive to the input parameter that characterizes the atmospheric distortion, and sub-2% photometric precision is readily obtained when it is well estimated.

Effects of aging on functional connectivity of the amygdala for subsequent memory of negative pictures: a network analysis of functional magnetic resonance imaging data.

PubMed

St Jacques, Peggy L; Dolcos, Florin; Cabeza, Roberto

2009-01-01

Aging is associated with preserved enhancement of emotional memory, as well as with age-related reductions in memory for negative stimuli, but the neural networks underlying such alterations are not clear. We used a subsequent-memory paradigm to identify brain activity predicting enhanced emotional memory in young and older adults. Activity in the amygdala predicted enhanced emotional memory, with subsequent-memory activity greater for negative stimuli than for neutral stimuli, across age groups, a finding consistent with an overall enhancement of emotional memory. However, older adults recruited greater activity in anterior regions and less activity in posterior regions in general for negative stimuli that were subsequently remembered. Functional connectivity of the amygdala with the rest of the brain was consistent with age-related reductions in memory for negative stimuli: Older adults showed decreased functional connectivity between the amygdala and the hippocampus, but increased functional connectivity between the amygdala and dorsolateral prefrontal cortices. These findings suggest that age-related differences in the enhancement of emotional memory might reflect decreased connectivity between the amygdala and typical subsequent-memory regions, as well as the engagement of regulatory processes that inhibit emotional responses.

Quantitative graphical analysis of simultaneous dynamic PET/MRI for assessment of prostate cancer.

PubMed

Rosenkrantz, Andrew B; Koesters, Thomas; Vahle, Anne-Kristin; Friedman, Kent; Bartlett, Rachel M; Taneja, Samir S; Ding, Yu-Shin; Logan, Jean

2015-04-01

Dynamic FDG imaging for prostate cancer characterization is limited by generally small size and low uptake in prostate tumors. Our aim in this pilot study was to explore feasibility of simultaneous PET/MRI to guide localization of prostate lesions for dynamic FDG analysis using a graphical approach. Three patients with biopsy-proven prostate cancer underwent simultaneous FDG PET/MRI, incorporating dynamic prostate imaging. Histology and multiparametric MRI findings were used to localize tumors, which in turn guided identification of tumors on FDG images. Regions of interest were manually placed on tumor and benign prostate tissue. Blood activity was extracted from a region of interest placed on the femoral artery on PET images. FDG data were analyzed by graphical analysis using the influx constant Ki (Patlak analysis) when FDG binding seemed irreversible and distribution volume VT (reversible graphical analysis) when FDG binding seemed reversible given the presence of washout. Given inherent coregistration, simultaneous acquisition facilitated use of MRI data to localize small lesions on PET and subsequent graphical analysis in all cases. In 2 cases with irreversible binding, tumor had higher Ki than benign using Patlak analysis (0.023 vs 0.006 and 0.019 vs 0.008 mL/cm3 per minute). In 1 case appearing reversible, tumor had higher VT than benign using reversible graphical analysis (0.68 vs 0.52 mL/cm3). Simultaneous PET/MRI allows localization of small prostate tumors for dynamic PET analysis. By taking advantage of inclusion of the femoral arteries in the FOV, we applied advanced PET data analysis methods beyond conventional static measures and without blood sampling.

Resin embedded multicycle imaging (REMI): a tool to evaluate protein domains.

PubMed

Busse, B L; Bezrukov, L; Blank, P S; Zimmerberg, J

2016-08-08

Protein complexes associated with cellular processes comprise a significant fraction of all biology, but our understanding of their heterogeneous organization remains inadequate, particularly for physiological densities of multiple protein species. Towards resolving this limitation, we here present a new technique based on resin-embedded multicycle imaging (REMI) of proteins in-situ. By stabilizing protein structure and antigenicity in acrylic resins, affinity labels were repeatedly applied, imaged, removed, and replaced. In principle, an arbitrarily large number of proteins of interest may be imaged on the same specimen with subsequent digital overlay. A series of novel preparative methods were developed to address the problem of imaging multiple protein species in areas of the plasma membrane or volumes of cytoplasm of individual cells. For multiplexed examination of antibody staining we used straightforward computational techniques to align sequential images, and super-resolution microscopy was used to further define membrane protein colocalization. We give one example of a fibroblast membrane with eight multiplexed proteins. A simple statistical analysis of this limited membrane proteomic dataset is sufficient to demonstrate the analytical power contributed by additional imaged proteins when studying membrane protein domains.

Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study

NASA Astrophysics Data System (ADS)

Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they typically rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this chapter we present a semantically enabled image annotation and retrieval engine that is designed to satisfy the requirements of commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as presenting our initial thoughts on exploiting lexical databases for explicit semantic-based query expansion.

Resin embedded multicycle imaging (REMI): a tool to evaluate protein domains

PubMed Central

Busse, B. L.; Bezrukov, L.; Blank, P. S.; Zimmerberg, J.

2016-01-01

Protein complexes associated with cellular processes comprise a significant fraction of all biology, but our understanding of their heterogeneous organization remains inadequate, particularly for physiological densities of multiple protein species. Towards resolving this limitation, we here present a new technique based on resin-embedded multicycle imaging (REMI) of proteins in-situ. By stabilizing protein structure and antigenicity in acrylic resins, affinity labels were repeatedly applied, imaged, removed, and replaced. In principle, an arbitrarily large number of proteins of interest may be imaged on the same specimen with subsequent digital overlay. A series of novel preparative methods were developed to address the problem of imaging multiple protein species in areas of the plasma membrane or volumes of cytoplasm of individual cells. For multiplexed examination of antibody staining we used straightforward computational techniques to align sequential images, and super-resolution microscopy was used to further define membrane protein colocalization. We give one example of a fibroblast membrane with eight multiplexed proteins. A simple statistical analysis of this limited membrane proteomic dataset is sufficient to demonstrate the analytical power contributed by additional imaged proteins when studying membrane protein domains. PMID:27499335

An accurate and reliable method of thermal data analysis in thermal imaging of the anterior knee for use in cryotherapy research.

PubMed

Selfe, James; Hardaker, Natalie; Thewlis, Dominic; Karki, Anna

2006-12-01

To develop an anatomic marker system (AMS) as an accurate, reliable method of thermal imaging data analysis, for use in cryotherapy research. Investigation of the accuracy of new thermal imaging technique. Hospital orthopedic outpatient department in England. Consecutive sample of 9 patients referred to anterior knee pain clinic. Not applicable. Thermally inert markers were placed at specific anatomic locations, defining an area over the anterior knee of patients with anterior knee pain. A baseline thermal image was taken. Patients underwent a 3-minute thermal washout of the affected knee. Thermal images were collected at a rate of 1 image per minute for a 20-minute re-warming period. A Matlab (version 7.0) program was written to digitize the marker positions and subsequently calculate the mean of the area over the anterior knee. Virtual markers were then defined as 15% distal from the proximal marker, 30% proximal from the distal markers, 15% lateral from the medial marker, and 15% medial from the lateral marker. The virtual markers formed an ellipse, which defined an area representative of the patella shape. Within the ellipse, the mean value of the full pixels determined the mean temperature of this region. Ten raters were recruited to use the program and interrater reliability was investigated. The intraclass correlation coefficient produced coefficients within acceptable bounds, ranging from .82 to .97, indicating adequate interrater reliability. The AMS provides an accurate, reliable method for thermal imaging data analysis and is a reliable tool with which to advance cryotherapy research.

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images

PubMed Central

Korbar, Bruno; Olofson, Andrea M.; Miraflor, Allen P.; Nicka, Catherine M.; Suriawinata, Matthew A.; Torresani, Lorenzo; Suriawinata, Arief A.; Hassanpour, Saeed

2017-01-01

Context: Histopathological characterization of colorectal polyps is critical for determining the risk of colorectal cancer and future rates of surveillance for patients. However, this characterization is a challenging task and suffers from significant inter- and intra-observer variability. Aims: We built an automatic image analysis method that can accurately classify different types of colorectal polyps on whole-slide images to help pathologists with this characterization and diagnosis. Setting and Design: Our method is based on deep-learning techniques, which rely on numerous levels of abstraction for data representation and have shown state-of-the-art results for various image analysis tasks. Subjects and Methods: Our method covers five common types of polyps (i.e., hyperplastic, sessile serrated, traditional serrated, tubular, and tubulovillous/villous) that are included in the US Multisociety Task Force guidelines for colorectal cancer risk assessment and surveillance. We developed multiple deep-learning approaches by leveraging a dataset of 2074 crop images, which were annotated by multiple domain expert pathologists as reference standards. Statistical Analysis: We evaluated our method on an independent test set of 239 whole-slide images and measured standard machine-learning evaluation metrics of accuracy, precision, recall, and F1 score and their 95% confidence intervals. Results: Our evaluation shows that our method with residual network architecture achieves the best performance for classification of colorectal polyps on whole-slide images (overall accuracy: 93.0%, 95% confidence interval: 89.0%–95.9%). Conclusions: Our method can reduce the cognitive burden on pathologists and improve their efficacy in histopathological characterization of colorectal polyps and in subsequent risk assessment and follow-up recommendations. PMID:28828201

Association between background parenchymal enhancement of breast MRI and BIRADS rating change in the subsequent screening

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-03-01

Although breast magnetic resonance imaging (MRI) has been used as a breast cancer screening modality for high-risk women, its cancer detection yield remains low (i.e., <= 3%). Thus, increasing breast MRI screening efficacy and cancer detection yield is an important clinical issue in breast cancer screening. In this study, we investigated association between the background parenchymal enhancement (BPE) of breast MRI and the change of diagnostic (BIRADS) status in the next subsequent breast MRI screening. A dataset with 65 breast MRI screening cases was retrospectively assembled. All cases were rated BIRADS-2 (benign findings). In the subsequent screening, 4 cases were malignant (BIRADS-6), 48 remained BIRADS-2 and 13 were downgraded to negative (BIRADS-1). A computer-aided detection scheme was applied to process images of the first set of breast MRI screening. Total of 33 features were computed including texture feature and global BPE features. Texture features were computed from either a gray-level co-occurrence matrix or a gray level run length matrix. Ten global BPE features were also initially computed from two breast regions and bilateral difference between the left and right breasts. Box-plot based analysis shows positive association between texture features and BIRADS rating levels in the second screening. Furthermore, a logistic regression model was built using optimal features selected by a CFS based feature selection method. Using a leave-one-case-out based cross-validation method, classification yielded an overall 75% accuracy in predicting the improvement (or downgrade) of diagnostic status (to BIRAD-1) in the subsequent breast MRI screening. This study demonstrated potential of developing a new quantitative imaging marker to predict diagnostic status change in the short-term, which may help eliminate a high fraction of unnecessary repeated breast MRI screenings and increase the cancer detection yield.

Functional magnetic resonance imaging (fMRI) response to alcohol pictures predicts subsequent transition to heavy drinking in college students.

PubMed

Dager, Alecia D; Anderson, Beth M; Rosen, Rivkah; Khadka, Sabin; Sawyer, Broderick; Jiantonio-Kelly, Rachel E; Austad, Carol S; Raskin, Sarah A; Tennen, Howard; Wood, Rebecca M; Fallahi, Carolyn R; Pearlson, Godfrey D

2014-04-01

Young adults show the highest rates of escalating drinking, yet the neural risk mechanisms remain unclear. Heavy drinkers show variant functional magnetic resonance imaging (fMRI) blood oxygen level-dependent (BOLD) response to alcohol cues, which may presage increasing drinking. In this longitudinal study, we ascertained whether BOLD response to alcohol pictures predicted subsequent heavy drinking among college students. Participants were 43 18-21-year-olds in the United States who underwent BOLD scanning and completed monthly substance use surveys over the following year. Participants were categorized according to baseline and follow-up drinking into 13 continuously moderate drinkers, 16 continuously heavy drinkers and 14 transitioners who drank moderately at baseline but heavily by follow-up. During fMRI scanning at baseline, participants viewed alcohol and matched non-alcohol beverage images. We observed group differences in alcohol cue-elicited BOLD response in bilateral caudate, orbitofrontal cortex, medial frontal cortex/anterior cingulate and left insula (clusters > 2619 ml, voxelwise F(2,40)  > 3.23, P < 0.05, whole-brain corrected P < 0.05), where transitioners hyperactivated compared with moderate and heavy drinkers (all Tukey P < 0.05). Exploratory factor analysis revealed a single brain network differentiating those who subsequently increased drinking. Exploratory regressions showed that, compared with other risk factors (e.g., alcoholism family history, impulsivity), BOLD response best predicted escalating drinking amount and alcohol-related problems. Neural response to pictures of alcohol is substantially enhanced among United States college students who subsequently escalate drinking. Greater cue-reactivity is associated with larger increases in drinking and alcohol-related problems, regardless of other baseline factors. Thus, neural cue-reactivity could uniquely facilitate identifying individuals at greatest risk for future problematic drinking. © 2013 Society for the Study of Addiction.

System description and analysis. Part 1: Feasibility study for helicopter/VTOL wide-angle simulation image generation display system

NASA Technical Reports Server (NTRS)

1977-01-01

A preliminary design for a helicopter/VSTOL wide angle simulator image generation display system is studied. The visual system is to become part of a simulator capability to support Army aviation systems research and development within the near term. As required for the Army to simulate a wide range of aircraft characteristics, versatility and ease of changing cockpit configurations were primary considerations of the study. Due to the Army's interest in low altitude flight and descents into and landing in constrained areas, particular emphasis is given to wide field of view, resolution, brightness, contrast, and color. The visual display study includes a preliminary design, demonstrated feasibility of advanced concepts, and a plan for subsequent detail design and development. Analysis and tradeoff considerations for various visual system elements are outlined and discussed.

Object detection and tracking system

DOEpatents

Ma, Tian J.

2017-05-30

Methods and apparatuses for analyzing a sequence of images for an object are disclosed herein. In a general embodiment, the method identifies a region of interest in the sequence of images. The object is likely to move within the region of interest. The method divides the region of interest in the sequence of images into sections and calculates signal-to-noise ratios for a section in the sections. A signal-to-noise ratio for the section is calculated using the section in the image, a prior section in a prior image to the image, and a subsequent section in a subsequent image to the image. The signal-to-noise ratios are for potential velocities of the object in the section. The method also selects a velocity from the potential velocities for the object in the section using a potential velocity in the potential velocities having a highest signal-to-noise ratio in the signal-to-noise ratios.

The importance of correcting for signal drift in diffusion MRI.

PubMed

Vos, Sjoerd B; Tax, Chantal M W; Luijten, Peter R; Ourselin, Sebastien; Leemans, Alexander; Froeling, Martijn

2017-01-01

To investigate previously unreported effects of signal drift as a result of temporal scanner instability on diffusion MRI data analysis and to propose a method to correct this signal drift. We investigated the signal magnitude of non-diffusion-weighted EPI volumes in a series of diffusion-weighted imaging experiments to determine whether signal magnitude changes over time. Different scan protocols and scanners from multiple vendors were used to verify this on phantom data, and the effects on diffusion kurtosis tensor estimation in phantom and in vivo data were quantified. Scalar metrics (eigenvalues, fractional anisotropy, mean diffusivity, mean kurtosis) and directional information (first eigenvectors and tractography) were investigated. Signal drift, a global signal decrease with subsequently acquired images in the scan, was observed in phantom data on all three scanners, with varying magnitudes up to 5% in a 15-min scan. The signal drift has a noticeable effect on the estimation of diffusion parameters. All investigated quantitative parameters as well as tractography were affected by this artifactual signal decrease during the scan. By interspersing the non-diffusion-weighted images throughout the session, the signal decrease can be estimated and compensated for before data analysis; minimizing the detrimental effects on subsequent MRI analyses. Magn Reson Med 77:285-299, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Iron overload in a teenager with xerocytosis: the importance of nuclear magnetic resonance imaging.

PubMed

Assis, Reijâne Alves de; Kassab, Carolina; Seguro, Fernanda Salles; Costa, Fernando Ferreira; Silveira, Paulo Augusto Achucarro; Wood, John; Hamerschlak, Nelson

2013-12-01

To report a case of iron overload secondary to xerocytosis, a rare disease in a teenager, diagnosed, by T2* magnetic resonance imaging. We report the case of a symptomatic patient with xerocytosis, a ferritin level of 350ng/mL and a significant cardiac iron overload. She was diagnosed by T2* magnetic resonance imaging and received chelation therapy Ektacytometric analysis confirmed the diagnosis of hereditary xerocytosis. Subsequent T2* magnetic resonance imaging demonstrated complete resolution of the iron overload in various organs, as a new echocardiography revealed a complete resolution of previous cardiac alterations. The patient remains in chelation therapy. Xerocytosis is a rare autosomal dominant genetic disorder characterized by dehydrated stomatocytosis. The patient may present with intense fatigue and iron overload. We suggest the regular use of T2* magnetic resonance imaging for the diagnosis and control of the response to iron chelation in xerocytosis, and we believe it can be used also in other hemolytic anemia requiring transfusions.

A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage

PubMed Central

Faure, Emmanuel; Savy, Thierry; Rizzi, Barbara; Melani, Camilo; Stašová, Olga; Fabrèges, Dimitri; Špir, Róbert; Hammons, Mark; Čúnderlík, Róbert; Recher, Gaëlle; Lombardot, Benoît; Duloquin, Louise; Colin, Ingrid; Kollár, Jozef; Desnoulez, Sophie; Affaticati, Pierre; Maury, Benoît; Boyreau, Adeline; Nief, Jean-Yves; Calvat, Pascal; Vernier, Philippe; Frain, Monique; Lutfalla, Georges; Kergosien, Yannick; Suret, Pierre; Remešíková, Mariana; Doursat, René; Sarti, Alessandro; Mikula, Karol; Peyriéras, Nadine; Bourgine, Paul

2016-01-01

The quantitative and systematic analysis of embryonic cell dynamics from in vivo 3D+time image data sets is a major challenge at the forefront of developmental biology. Despite recent breakthroughs in the microscopy imaging of living systems, producing an accurate cell lineage tree for any developing organism remains a difficult task. We present here the BioEmergences workflow integrating all reconstruction steps from image acquisition and processing to the interactive visualization of reconstructed data. Original mathematical methods and algorithms underlie image filtering, nucleus centre detection, nucleus and membrane segmentation, and cell tracking. They are demonstrated on zebrafish, ascidian and sea urchin embryos with stained nuclei and membranes. Subsequent validation and annotations are carried out using Mov-IT, a custom-made graphical interface. Compared with eight other software tools, our workflow achieved the best lineage score. Delivered in standalone or web service mode, BioEmergences and Mov-IT offer a unique set of tools for in silico experimental embryology. PMID:26912388

High-Speed and Scalable Whole-Brain Imaging in Rodents and Primates.

PubMed

Seiriki, Kaoru; Kasai, Atsushi; Hashimoto, Takeshi; Schulze, Wiebke; Niu, Misaki; Yamaguchi, Shun; Nakazawa, Takanobu; Inoue, Ken-Ichi; Uezono, Shiori; Takada, Masahiko; Naka, Yuichiro; Igarashi, Hisato; Tanuma, Masato; Waschek, James A; Ago, Yukio; Tanaka, Kenji F; Hayata-Takano, Atsuko; Nagayasu, Kazuki; Shintani, Norihito; Hashimoto, Ryota; Kunii, Yasuto; Hino, Mizuki; Matsumoto, Junya; Yabe, Hirooki; Nagai, Takeharu; Fujita, Katsumasa; Matsuda, Toshio; Takuma, Kazuhiro; Baba, Akemichi; Hashimoto, Hitoshi

2017-06-21

Subcellular resolution imaging of the whole brain and subsequent image analysis are prerequisites for understanding anatomical and functional brain networks. Here, we have developed a very high-speed serial-sectioning imaging system named FAST (block-face serial microscopy tomography), which acquires high-resolution images of a whole mouse brain in a speed range comparable to that of light-sheet fluorescence microscopy. FAST enables complete visualization of the brain at a resolution sufficient to resolve all cells and their subcellular structures. FAST renders unbiased quantitative group comparisons of normal and disease model brain cells for the whole brain at a high spatial resolution. Furthermore, FAST is highly scalable to non-human primate brains and human postmortem brain tissues, and can visualize neuronal projections in a whole adult marmoset brain. Thus, FAST provides new opportunities for global approaches that will allow for a better understanding of brain systems in multiple animal models and in human diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Ranging Apparatus and Method Implementing Stereo Vision System

NASA Technical Reports Server (NTRS)

Li, Larry C. (Inventor); Cox, Brian J. (Inventor)

1997-01-01

A laser-directed ranging system for use in telerobotics applications and other applications involving physically handicapped individuals. The ranging system includes a left and right video camera mounted on a camera platform, and a remotely positioned operator. The position of the camera platform is controlled by three servo motors to orient the roll axis, pitch axis and yaw axis of the video cameras, based upon an operator input such as head motion. A laser is provided between the left and right video camera and is directed by the user to point to a target device. The images produced by the left and right video cameras are processed to eliminate all background images except for the spot created by the laser. This processing is performed by creating a digital image of the target prior to illumination by the laser, and then eliminating common pixels from the subsequent digital image which includes the laser spot. The horizontal disparity between the two processed images is calculated for use in a stereometric ranging analysis from which range is determined.

Hyperspectral imaging of the human iris

NASA Astrophysics Data System (ADS)

Di Cecilia, Luca; Marazzi, Francesco; Rovati, Luigi

2017-07-01

We describe an optical system and a method for measuring the human iris spectral reflectance in vivo by hyperspectral imaging analysis. It is important to monitor age-related changes in the reflectance properties of the iris as they are a prognostic factor for several eye pathologies. In this paper, we report the outcomes of our most recent research, resulting from the improvement of our imaging system. In particular, a custom tunable light source was developed: the images are now acquired in the spectral range 440 - 900 nm. With this system, we are able to obtain a spectral resolution of 20nm, while each image of 2048 x 1536 pixels has a spatial resolution of 10.7 μm. The results suggest that the instrument could be exploited for measuring iris pigmentation changes over time. These measurements could provide new diagnostic capabilities in ophthalmology. Further studies are required to determine the measurements' repeatability and to develop a spectral library for results evaluation and to detect differences among subsequent screenings of the same subject.

Iodine imaging using spectral analysis. [radiography for visualization of small blood vessels

NASA Technical Reports Server (NTRS)

Macovski, A.

1978-01-01

Existing radiographic imaging systems provide images which represent an integration or averaging over the energy spectrum. In order to provide noninvasive angiography it is necessary to image the relatively small amounts of iodine which are available following an intravenous administration. This is accomplished by making use of the special spectral characteristics of iodine. Two methods will be presented. One involves a special grating for encoding the iodine information in the form of a fine line pattern. This is subsequently decoded to provide images of iodinated structures which are otherwise almost invisible. The second method utilizes a scanned X-ray beam which is rapidly switched in the high energy region. In this region, iodine experiences significant variations in the attenuation coefficient while bone and soft tissue do not. An efficient and accurate X-ray detector can be used with scanned X-ray beams. This provides a high degree of sensitivity enabling the visualization of small vessels containing relatively dilute iodine.

Does breast reconstruction impact the decision of patients to pursue cosmetic surgery?

PubMed

Hsu, Vivian M; Tahiri, Youssef; Wes, Ari M; Yan, Chen; Selber, Jesse C; Nelson, Jonas A; Kovach, Stephen J; Serletti, Joseph M; Wu, Liza C

2014-12-01

Breast reconstruction is an integral component of breast cancer treatment, often aiding in restoring a patient's sense of femininity. However, many patients choose to have subsequent cosmetic surgery. The purpose of this study is to investigate the reasons that motivate patients to have cosmetic surgery after breast reconstruction. The authors performed a retrospective study examining patients who had breast reconstruction and subsequent cosmetic surgery at the University of Pennsylvania Health System between January 2005 and June 2012. This cohort received a questionnaire assessing the influences and impact of their reconstructive and cosmetic procedures. A total of 1,214 patients had breast reconstruction, with 113 patients (9.3%) undergoing cosmetic surgery after reconstruction. Of 42 survey respondents, 35 had autologous breast reconstruction (83.3%). Fifty-two cosmetic procedures were performed in survey respondents, including liposuction (26.9%) and facelift (15.4%). The most common reason for pursuing cosmetic surgery was the desire to improve self-image (n = 26, 61.9%), with 29 (69.0%) patients feeling more self-conscious of appearance after reconstruction. Body image satisfaction was significantly higher after cosmetic surgery (P = 0.0081). Interestingly, a multivariate analysis revealed that patients who experienced an improvement in body image after breast reconstruction were more likely to experience a further improvement after a cosmetic procedure (P = 0.031, OR = 17.83). Patients who were interested in cosmetic surgery prior to reconstruction were also more likely to experience an improvement in body image after cosmetic surgery (P = 0.012, OR = 22.63). Cosmetic surgery may improve body image satisfaction of breast reconstruction patients and help to further meet their expectations.

NeuronRead, an open source semi-automated tool for morphometric analysis of phase contrast and fluorescence neuronal images.

PubMed

Dias, Roberto A; Gonçalves, Bruno P; da Rocha, Joana F; da Cruz E Silva, Odete A B; da Silva, Augusto M F; Vieira, Sandra I

2017-12-01

Neurons are specialized cells of the Central Nervous System whose function is intricately related to the neuritic network they develop to transmit information. Morphological evaluation of this network and other neuronal structures is required to establish relationships between neuronal morphology and function, and may allow monitoring physiological and pathophysiologic alterations. Fluorescence-based microphotographs are the most widely used in cellular bioimaging, but phase contrast (PhC) microphotographs are easier to obtain, more affordable, and do not require invasive, complicated and disruptive techniques. Despite the various freeware tools available for fluorescence-based images analysis, few exist that can tackle the more elusive and harder-to-analyze PhC images. To surpass this, an interactive semi-automated image processing workflow was developed to easily extract relevant information (e.g. total neuritic length, average cell body area) from both PhC and fluorescence neuronal images. This workflow, named 'NeuronRead', was developed in the form of an ImageJ macro. Its robustness and adaptability were tested and validated on rat cortical primary neurons under control and differentiation inhibitory conditions. Validation included a comparison to manual determinations and to a golden standard freeware tool for fluorescence image analysis. NeuronRead was subsequently applied to PhC images of neurons at distinct differentiation days and exposed or not to DAPT, a pharmacological inhibitor of the γ-secretase enzyme, which cleaves the well-known Alzheimer's amyloid precursor protein (APP) and the Notch receptor. Data obtained confirms a neuritogenic regulatory role for γ-secretase products and validates NeuronRead as a time- and cost-effective useful monitoring tool. Copyright © 2017. Published by Elsevier Inc.

Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

PubMed

Lim, Kyungjae; Kwon, Heejin; Cho, Jinhan; Oh, Jongyoung; Yoon, Seongkuk; Kang, Myungjin; Ha, Dongho; Lee, Jinhwa; Kang, Eunju

2015-01-01

The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image. We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V. At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P < 0.001). At qualitative analysis of the third study, it also showed that the images reconstructed using ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P < 0.001). Our phantom studies showed that ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

PubMed Central

Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M.; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V.; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L.; Bilello, Michel; O'Rourke, Donald M.; Davatzikos, Christos

2016-01-01

Background MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). Methods One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Results Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. Conclusions By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood–brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. PMID:26188015

Infrared and visible image fusion based on robust principal component analysis and compressed sensing

NASA Astrophysics Data System (ADS)

Li, Jun; Song, Minghui; Peng, Yuanxi

2018-03-01

Current infrared and visible image fusion methods do not achieve adequate information extraction, i.e., they cannot extract the target information from infrared images while retaining the background information from visible images. Moreover, most of them have high complexity and are time-consuming. This paper proposes an efficient image fusion framework for infrared and visible images on the basis of robust principal component analysis (RPCA) and compressed sensing (CS). The novel framework consists of three phases. First, RPCA decomposition is applied to the infrared and visible images to obtain their sparse and low-rank components, which represent the salient features and background information of the images, respectively. Second, the sparse and low-rank coefficients are fused by different strategies. On the one hand, the measurements of the sparse coefficients are obtained by the random Gaussian matrix, and they are then fused by the standard deviation (SD) based fusion rule. Next, the fused sparse component is obtained by reconstructing the result of the fused measurement using the fast continuous linearized augmented Lagrangian algorithm (FCLALM). On the other hand, the low-rank coefficients are fused using the max-absolute rule. Subsequently, the fused image is superposed by the fused sparse and low-rank components. For comparison, several popular fusion algorithms are tested experimentally. By comparing the fused results subjectively and objectively, we find that the proposed framework can extract the infrared targets while retaining the background information in the visible images. Thus, it exhibits state-of-the-art performance in terms of both fusion effects and timeliness.

Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification

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

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Giger, Maryellen L.; Li, Hui

2014-03-15

Purpose: To investigate whether biologic image composition of mammographic lesions can improve upon existing mammographic quantitative image analysis (QIA) in estimating the probability of malignancy. Methods: The study population consisted of 45 breast lesions imaged with dual-energy mammography prior to breast biopsy with final diagnosis resulting in 10 invasive ductal carcinomas, 5 ductal carcinomain situ, 11 fibroadenomas, and 19 other benign diagnoses. Analysis was threefold: (1) The raw low-energy mammographic images were analyzed with an established in-house QIA method, “QIA alone,” (2) the three-compartment breast (3CB) composition measure—derived from the dual-energy mammography—of water, lipid, and protein thickness were assessed, “3CBmore » alone”, and (3) information from QIA and 3CB was combined, “QIA + 3CB.” Analysis was initiated from radiologist-indicated lesion centers and was otherwise fully automated. Steps of the QIA and 3CB methods were lesion segmentation, characterization, and subsequent classification for malignancy in leave-one-case-out cross-validation. Performance assessment included box plots, Bland–Altman plots, and Receiver Operating Characteristic (ROC) analysis. Results: The area under the ROC curve (AUC) for distinguishing between benign and malignant lesions (invasive and DCIS) was 0.81 (standard error 0.07) for the “QIA alone” method, 0.72 (0.07) for “3CB alone” method, and 0.86 (0.04) for “QIA+3CB” combined. The difference in AUC was 0.043 between “QIA + 3CB” and “QIA alone” but failed to reach statistical significance (95% confidence interval [–0.17 to + 0.26]). Conclusions: In this pilot study analyzing the new 3CB imaging modality, knowledge of the composition of breast lesions and their periphery appeared additive in combination with existing mammographic QIA methods for the distinction between different benign and malignant lesion types.« less

The impact of ischemia-reperfusion injuries on skin resident murine dendritic cells.

PubMed

Goh, Chi Ching; Evrard, Maximilien; Chong, Shu Zhen; Tan, Yingrou; Tan, Leonard De Li; Teng, Karen Wei Weng; Weninger, Wolfgang; Becker, David Laurence; Tey, Hong Liang; Newell, Evan William; Liu, Bin; Ng, Lai Guan

2018-06-01

Pressure ulcers are a chronic problem for patients or the elderly who require extended periods of bed rest. The formation of ulcers is due to repeated cycles of ischemia-reperfusion (IR), which initiates an inflammatory response. Advanced ulcers disrupt the skin barrier, resulting in further complications. To date, the immunological aspect of skin IR has been understudied, partly due to the complexity of the skin immune cells. Through a combination of mass cytometry, confocal imaging and intravital multiphoton imaging, this study establishes a workflow for multidimensionality single cell analysis of skin myeloid cell responses in the context of IR injury with high spatiotemporal resolution. The data generated has provided us with previously uncharacterized insights into the distinct cellular behavior of resident dendritic cells (DCs) and recruited neutrophils post IR. Of interest, we observed a drop in DDC numbers in the IR region, which was subsequently replenished 48h post IR. More importantly, in these cells, we observe an attenuated response to repeated injuries, which may have implications in the subsequent wound healing process. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Principles of Quantitative MR Imaging with Illustrated Review of Applicable Modular Pulse Diagrams.

PubMed

Mills, Andrew F; Sakai, Osamu; Anderson, Stephan W; Jara, Hernan

2017-01-01

Continued improvements in diagnostic accuracy using magnetic resonance (MR) imaging will require development of methods for tissue analysis that complement traditional qualitative MR imaging studies. Quantitative MR imaging is based on measurement and interpretation of tissue-specific parameters independent of experimental design, compared with qualitative MR imaging, which relies on interpretation of tissue contrast that results from experimental pulse sequence parameters. Quantitative MR imaging represents a natural next step in the evolution of MR imaging practice, since quantitative MR imaging data can be acquired using currently available qualitative imaging pulse sequences without modifications to imaging equipment. The article presents a review of the basic physical concepts used in MR imaging and how quantitative MR imaging is distinct from qualitative MR imaging. Subsequently, the article reviews the hierarchical organization of major applicable pulse sequences used in this article, with the sequences organized into conventional, hybrid, and multispectral sequences capable of calculating the main tissue parameters of T1, T2, and proton density. While this new concept offers the potential for improved diagnostic accuracy and workflow, awareness of this extension to qualitative imaging is generally low. This article reviews the basic physical concepts in MR imaging, describes commonly measured tissue parameters in quantitative MR imaging, and presents the major available pulse sequences used for quantitative MR imaging, with a focus on the hierarchical organization of these sequences. © RSNA, 2017.

Experimental Design and Data Analysis in Receiver Operating Characteristic Studies: Lessons Learned from Reports in Radiology from 1997 to 20061

PubMed Central

Shiraishi, Junji; Pesce, Lorenzo L.; Metz, Charles E.; Doi, Kunio

2009-01-01

Purpose: To provide a broad perspective concerning the recent use of receiver operating characteristic (ROC) analysis in medical imaging by reviewing ROC studies published in Radiology between 1997 and 2006 for experimental design, imaging modality, medical condition, and ROC paradigm. Materials and Methods: Two hundred ninety-five studies were obtained by conducting a literature search with PubMed with two criteria: publication in Radiology between 1997 and 2006 and occurrence of the phrase “receiver operating characteristic.” Studies returned by the query that were not diagnostic imaging procedure performance evaluations were excluded. Characteristics of the remaining studies were tabulated. Results: Two hundred thirty-three (79.0%) of the 295 studies reported findings based on observers' diagnostic judgments or objective measurements. Forty-three (14.6%) did not include human observers, with most of these reporting an evaluation of a computer-aided diagnosis system or functional data obtained with computed tomography (CT) or magnetic resonance (MR) imaging. The remaining 19 (6.4%) studies were classified as reviews or meta-analyses and were excluded from our subsequent analysis. Among the various imaging modalities, MR imaging (46.0%) and CT (25.7%) were investigated most frequently. Approximately 60% (144 of 233) of ROC studies with human observers published in Radiology included three or fewer observers. Conclusion: ROC analysis is widely used in radiologic research, confirming its fundamental role in assessing diagnostic performance. However, the ROC studies reported in Radiology were not always adequate to support clear and clinically relevant conclusions. © RSNA, 2009 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.2533081632/-/DC1 PMID:19864510

Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

PubMed

Sun, Xiaofei; Shi, Lin; Luo, Yishan; Yang, Wei; Li, Hongpeng; Liang, Peipeng; Li, Kuncheng; Mok, Vincent C T; Chu, Winnie C W; Wang, Defeng

2015-07-28

Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed a histogram-based MRI intensity normalization method. The method can normalize scans which were acquired on different MRI units. We have validated that the method can greatly improve the image analysis performance. Furthermore, it is demonstrated that with the help of our normalization method, we can create a higher quality Chinese brain template.

Evaluation of color grading impact in restoration process of archive films

NASA Astrophysics Data System (ADS)

Fliegel, Karel; Vítek, Stanislav; Páta, Petr; Janout, Petr; Myslík, Jiří; Pecák, Josef; Jícha, Marek

2016-09-01

Color grading of archive films is a very particular task in the process of their restoration. The ultimate goal of color grading here is to achieve the same look of the movie as intended at the time of its first presentation. The role of the expert restorer, expert group and a digital colorist in this complicated process is to find the optimal settings of the digital color grading system so that the resulting image look is as close as possible to the estimate of the original reference release print adjusted by the expert group of cinematographers. A methodology for subjective assessment of perceived differences between the outcomes of color grading is introduced, and results of a subjective study are presented. Techniques for objective assessment of perceived differences are discussed, and their performance is evaluated using ground truth obtained from the subjective experiment. In particular, a solution based on calibrated digital single-lens reflex camera and subsequent analysis of image features captured from the projection screen is described. The system based on our previous work is further developed so that it can be used for the analysis of projected images. It allows assessing color differences in these images and predict their impact on the perceived difference in image look.

Image denoising and deblurring using multispectral data

NASA Astrophysics Data System (ADS)

Semenishchev, E. A.; Voronin, V. V.; Marchuk, V. I.

2017-05-01

Currently decision-making systems get widespread. These systems are based on the analysis video sequences and also additional data. They are volume, change size, the behavior of one or a group of objects, temperature gradient, the presence of local areas with strong differences, and others. Security and control system are main areas of application. A noise on the images strongly influences the subsequent processing and decision making. This paper considers the problem of primary signal processing for solving the tasks of image denoising and deblurring of multispectral data. The additional information from multispectral channels can improve the efficiency of object classification. In this paper we use method of combining information about the objects obtained by the cameras in different frequency bands. We apply method based on simultaneous minimization L2 and the first order square difference sequence of estimates to denoising and restoring the blur on the edges. In case of loss of the information will be applied an approach based on the interpolation of data taken from the analysis of objects located in other areas and information obtained from multispectral camera. The effectiveness of the proposed approach is shown in a set of test images.

Evaluation of thresholding techniques for segmenting scaffold images in tissue engineering

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Yaszemski, Michael J.; Robb, Richard A.

2004-05-01

Tissue engineering attempts to address the ever widening gap between the demand and supply of organ and tissue transplants using natural and biomimetic scaffolds. The regeneration of specific tissues aided by synthetic materials is dependent on the structural and morphometric properties of the scaffold. These properties can be derived non-destructively using quantitative analysis of high resolution microCT scans of scaffolds. Thresholding of the scanned images into polymeric and porous phase is central to the outcome of the subsequent structural and morphometric analysis. Visual thresholding of scaffolds produced using stochastic processes is inaccurate. Depending on the algorithmic assumptions made, automatic thresholding might also be inaccurate. Hence there is a need to analyze the performance of different techniques and propose alternate ones, if needed. This paper provides a quantitative comparison of different thresholding techniques for segmenting scaffold images. The thresholding algorithms examined include those that exploit spatial information, locally adaptive characteristics, histogram entropy information, histogram shape information, and clustering of gray-level information. The performance of different techniques was evaluated using established criteria, including misclassification error, edge mismatch, relative foreground error, and region non-uniformity. Algorithms that exploit local image characteristics seem to perform much better than those using global information.

Recognition of skin melanoma through dermoscopic image analysis

NASA Astrophysics Data System (ADS)

Gómez, Catalina; Herrera, Diana Sofia

2017-11-01

Melanoma skin cancer diagnosis can be challenging due to the similarities of the early stage symptoms with regular moles. Standardized visual parameters can be determined and characterized to suspect a melanoma cancer type. The automation of this diagnosis could have an impact in the medical field by providing a tool to support the specialists with high accuracy. The objective of this study is to develop an algorithm trained to distinguish a highly probable melanoma from a non-dangerous mole by the segmentation and classification of dermoscopic mole images. We evaluate our approach on the dataset provided by the International Skin Imaging Collaboration used in the International Challenge Skin Lesion Analysis Towards Melanoma Detection. For the segmentation task, we apply a preprocessing algorithm and use Otsu's thresholding in the best performing color space; the average Jaccard Index in the test dataset is 70.05%. For the subsequent classification stage, we use joint histograms in the YCbCr color space, a RBF Gaussian SVM trained with five features concerning circularity and irregularity of the segmented lesion, and the Gray Level Co-occurrence matrix features for texture analysis. These features are combined to obtain an Average Classification Accuracy of 63.3% in the test dataset.

dPIRPLE: a joint estimation framework for deformable registration and penalized-likelihood CT image reconstruction using prior images

NASA Astrophysics Data System (ADS)

Dang, H.; Wang, A. S.; Sussman, Marc S.; Siewerdsen, J. H.; Stayman, J. W.

2014-09-01

Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration, and prior image penalized-likelihood estimation with rigid registration of a prior image (PIRPLE) over a wide range of sampling sparsity and exposure levels.

Subsequent development of fibroatheromas with inflamed fibrous caps can be predicted by intracoronary near infrared spectroscopy.

PubMed

Patel, Dhavalkumar; Hamamdzic, Damir; Llano, Raul; Patel, Daivesh; Cheng, Lan; Fenning, Robert S; Bannan, Khalid; Wilensky, Robert L

2013-02-01

To prospectively evaluate whether the development of fibroatheromas exhibiting features of potential instability can be detected and predicted by serial invasive imaging. Multivessel intravascular ultrasound and near infrared spectroscopy (NIRS) were performed in diabetic/hypercholesterolemic pigs 3, 6, and 9 months after induction. Animals were euthanized at 9 months and histological/immunohistochemical evaluation of the arteries was performed (n=304 arterial segments). Intravascular ultrasound demonstrated, over time, a progressive increase in plaque + media and necrotic core areas and positive vascular remodeling. By histology, NIRS+ lesions were significantly more likely to be a high-risk fibroatheroma (P=0.0001) containing larger plaque (P<0.0001) and necrotic core areas (P<0.0019) and thinner fibrous caps (P=0.04). NIRS + fibroatheromas possessed a greater concentration of inflammatory cells demonstrating protease activity (P=0.006), and proliferating (P=0.016), and apoptotic cells (P=0.04) within the fibrous cap. Eighty-eight percent of NIRS+ lesions at 3 and 6 months subsequently developed into a fibroatheroma at 9 months (P<0.01). By multivariate analysis NIRS positivity at 6 months predicted the subsequent presence of a fibroatheroma at 9 months (P=0.005; odds ratio, 2.71). The future development of inflamed fibroatheromas with thinner fibrous caps, greater plaque, and necrotic core areas, and posessing characteristics of increased plaque instability were detected by intravascular ultrasound/NIRS imaging.

Mediated Leader Effects: The Impact of Newspapers' Portrayal of Party Leadership on Electoral Support.

PubMed

Aaldering, Loes; van der Meer, Tom; Van der Brug, Wouter

2018-01-01

Conventional wisdom holds that party leaders matter in democratic elections. As very few voters have direct contact with party leaders, media are voters' primary source of information about these leaders and, thus, the likely origin of leader effects on party support. Our study focuses on these supposed electoral effects of the media coverage of party leaders. We examine the positive and negative effects of specific leadership images in Dutch newspapers on vote intentions. To this end, we combine an extensive automated content analysis of leadership images in the media with a panel data set, the Dutch 1Vandaag Opinion Panel (1VOP), consisting of more than fifty thousand unique respondents and 110 waves of interviews conducted between September 2006 and September 2012. The results confirm that media coverage of party leaders' character traits affects voters: Positive mediated leadership images increase support for the leader's party, while negative images decrease this support. However, this influence is not unconditional: During campaign periods, positive leadership images have a stronger effect, while negative images no longer have an impact on subsequent vote intentions.

Mediated Leader Effects: The Impact of Newspapers’ Portrayal of Party Leadership on Electoral Support

PubMed Central

Aaldering, Loes; van der Meer, Tom; Van der Brug, Wouter

2017-01-01

Conventional wisdom holds that party leaders matter in democratic elections. As very few voters have direct contact with party leaders, media are voters’ primary source of information about these leaders and, thus, the likely origin of leader effects on party support. Our study focuses on these supposed electoral effects of the media coverage of party leaders. We examine the positive and negative effects of specific leadership images in Dutch newspapers on vote intentions. To this end, we combine an extensive automated content analysis of leadership images in the media with a panel data set, the Dutch 1Vandaag Opinion Panel (1VOP), consisting of more than fifty thousand unique respondents and 110 waves of interviews conducted between September 2006 and September 2012. The results confirm that media coverage of party leaders’ character traits affects voters: Positive mediated leadership images increase support for the leader’s party, while negative images decrease this support. However, this influence is not unconditional: During campaign periods, positive leadership images have a stronger effect, while negative images no longer have an impact on subsequent vote intentions. PMID:29527251

A Complete System for Automatic Extraction of Left Ventricular Myocardium From CT Images Using Shape Segmentation and Contour Evolution

PubMed Central

Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen

2014-01-01

The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated. PMID:24723531

Optic for industrial endoscope/borescope with narrow field of view and low distortion

DOEpatents

Stone, Gary F.; Trebes, James E.

2005-08-16

An optic for the imaging optics on the distal end of a flexible fiberoptic endoscope or rigid borescope inspection tool. The image coverage is over a narrow (<20 degrees) field of view with very low optical distortion (<5% pin cushion or barrel distortion), compared to the typical <20% distortion. The optic will permit non-contact surface roughness measurements using optical techniques. This optic will permit simultaneous collection of selected image plane data, which data can then be subsequently optically processed. The image analysis will yield non-contact surface topology data for inspection where access to the surface does not permit a mechanical styles profilometer verification of surface topology. The optic allows a very broad spectral band or range of optical inspection. It is capable of spectroscopic imaging and fluorescence induced imaging when a scanning illumination source is used. The total viewing angle for this optic is 10 degrees for the full field of view of 10 degrees, compared to 40-70 degrees full angle field of view of the conventional gradient index or GRIN's lens systems.

Imaging of blood cells based on snapshot Hyper-Spectral Imaging systems

NASA Astrophysics Data System (ADS)

Robison, Christopher J.; Kolanko, Christopher; Bourlai, Thirimachos; Dawson, Jeremy M.

2015-05-01

Snapshot Hyper-Spectral imaging systems are capable of capturing several spectral bands simultaneously, offering coregistered images of a target. With appropriate optics, these systems are potentially able to image blood cells in vivo as they flow through a vessel, eliminating the need for a blood draw and sample staining. Our group has evaluated the capability of a commercial Snapshot Hyper-Spectral imaging system, the Arrow system from Rebellion Photonics, in differentiating between white and red blood cells on unstained blood smear slides. We evaluated the imaging capabilities of this hyperspectral camera; attached to a microscope at varying objective powers and illumination intensity. Hyperspectral data consisting of 25, 443x313 hyperspectral bands with ~3nm spacing were captured over the range of 419 to 494nm. Open-source hyper-spectral data cube analysis tools, used primarily in Geographic Information Systems (GIS) applications, indicate that white blood cells features are most prominent in the 428-442nm band for blood samples viewed under 20x and 50x magnification over a varying range of illumination intensities. These images could potentially be used in subsequent automated white blood cell segmentation and counting algorithms for performing in vivo white blood cell counting.

Characteristic extraction and matching algorithms of ballistic missile in near-space by hyperspectral image analysis

NASA Astrophysics Data System (ADS)

Lu, Li; Sheng, Wen; Liu, Shihua; Zhang, Xianzhi

2014-10-01

The ballistic missile hyperspectral data of imaging spectrometer from the near-space platform are generated by numerical method. The characteristic of the ballistic missile hyperspectral data is extracted and matched based on two different kinds of algorithms, which called transverse counting and quantization coding, respectively. The simulation results show that two algorithms extract the characteristic of ballistic missile adequately and accurately. The algorithm based on the transverse counting has the low complexity and can be implemented easily compared to the algorithm based on the quantization coding does. The transverse counting algorithm also shows the good immunity to the disturbance signals and speed up the matching and recognition of subsequent targets.

General tensor discriminant analysis and gabor features for gait recognition.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2007-10-01

The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine state of the art classification methods in gait recognition.

Quantification of Impervious Surfaces Along the Wasatch Front, Utah: AN Object-Based Image Analysis Approach to Identifying AN Indicator for Wetland Stress

NASA Astrophysics Data System (ADS)

Leydsman-McGinty, E. I.; Ramsey, R. D.; McGinty, C.

2013-12-01

The Remote Sensing/GIS Laboratory at Utah State University, in cooperation with the United States Environmental Protection Agency, is quantifying impervious surfaces for three watershed sub-basins in Utah. The primary objective of developing watershed-scale quantifications of impervious surfaces is to provide an indicator of potential impacts to wetlands that occur within the Wasatch Front and along the Great Salt Lake. A geospatial layer of impervious surfaces can assist state agencies involved with Utah's Wetlands Program Plan (WPP) in understanding the impacts of impervious surfaces on wetlands, as well as support them in carrying out goals and actions identified in the WPP. The three watershed sub-basins, Lower Bear-Malad, Lower Weber, and Jordan, span the highly urbanized Wasatch Front and are consistent with focal areas in need of wetland monitoring and assessment as identified in Utah's WPP. Geospatial layers of impervious surface currently exist in the form of national and regional land cover datasets; however, these datasets are too coarse to be utilized in fine-scale analyses. In addition, the pixel-based image processing techniques used to develop these coarse datasets have proven insufficient in smaller scale or detailed studies, particularly when applied to high-resolution satellite imagery or aerial photography. Therefore, object-based image analysis techniques are being implemented to develop the geospatial layer of impervious surfaces. Object-based image analysis techniques employ a combination of both geospatial and image processing methods to extract meaningful information from high-resolution imagery. Spectral, spatial, textural, and contextual information is used to group pixels into image objects and then subsequently used to develop rule sets for image classification. eCognition, an object-based image analysis software program, is being utilized in conjunction with one-meter resolution National Agriculture Imagery Program (NAIP) aerial photography from 2011.

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

PubMed Central

Jang, Min Jee; Nam, Yoonkey

2015-01-01

Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973

Texture analysis of ultrahigh field T2*-weighted MR images of the brain: application to Huntington's disease.

PubMed

Doan, Nhat Trung; van den Bogaard, Simon J A; Dumas, Eve M; Webb, Andrew G; van Buchem, Mark A; Roos, Raymund A C; van der Grond, Jeroen; Reiber, Johan H C; Milles, Julien

2014-03-01

To develop a framework for quantitative detection of between-group textural differences in ultrahigh field T2*-weighted MR images of the brain. MR images were acquired using a three-dimensional (3D) T2*-weighted gradient echo sequence on a 7 Tesla MRI system. The phase images were high-pass filtered to remove phase wraps. Thirteen textural features were computed for both the magnitude and phase images of a region of interest based on 3D Gray-Level Co-occurrence Matrix, and subsequently evaluated to detect between-group differences using a Mann-Whitney U-test. We applied the framework to study textural differences in subcortical structures between premanifest Huntington's disease (HD), manifest HD patients, and controls. In premanifest HD, four phase-based features showed a difference in the caudate nucleus. In manifest HD, 7 magnitude-based features showed a difference in the pallidum, 6 phase-based features in the caudate nucleus, and 10 phase-based features in the putamen. After multiple comparison correction, significant differences were shown in the putamen in manifest HD by two phase-based features (both adjusted P values=0.04). This study provides the first evidence of textural heterogeneity of subcortical structures in HD. Texture analysis of ultrahigh field T2*-weighted MR images can be useful for noninvasive monitoring of neurodegenerative diseases. Copyright © 2013 Wiley Periodicals, Inc.

Dosimetry of heavy ions by use of CCD detectors

NASA Technical Reports Server (NTRS)

Schott, J. U.

1994-01-01

The design and the atomic composition of Charge Coupled Devices (CCD's) make them unique for investigations of single energetic particle events. As detector system for ionizing particles they detect single particles with local resolution and near real time particle tracking. In combination with its properties as optical sensor, particle transversals of single particles are to be correlated to any objects attached to the light sensitive surface of the sensor by simple imaging of their shadow and subsequent image analysis of both, optical image and particle effects, observed in affected pixels. With biological objects it is possible for the first time to investigate effects of single heavy ions in tissue or extinguished organs of metabolizing (i.e. moving) systems with a local resolution better than 15 microns. Calibration data for particle detection in CCD's are presented for low energetic protons and heavy ions.

ESIAC: A data products system for ERTS imagery (time-lapse viewing and measuring)

NASA Technical Reports Server (NTRS)

Evans, W. E.; Serebreny, S. M.

1974-01-01

An Electronic Satellite Image Analysis Console (ESIAC) has been developed for visual analysis and objective measurement of earth resources imagery. The system is being employed to process imagery for use by USGS investigators in several different disciplines studying dynamic hydrologic conditions. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. The unique feature of the system is the capability to time-lapse the ERTS imagery and/or analytic displays of the imagery. Data products have included quantitative measurements of distances and areas, brightness profiles, and movie loops of selected themes. The applications of these data products are identified and include such diverse problem areas as measurement of snowfield extent, sediment plumes from estuary dicharge, playa inventory, phreatophyte and other vegetation changes. A comparative ranking of the electronic system in terms of accuracy, cost effectiveness and data output shows it to be a viable means of data analysis.

Analysis of Protein Kinetics Using Fluorescence Recovery After Photobleaching (FRAP).

PubMed

Giakoumakis, Nickolaos Nikiforos; Rapsomaniki, Maria Anna; Lygerou, Zoi

2017-01-01

Fluorescence recovery after photobleaching (FRAP) is a cutting-edge live-cell functional imaging technique that enables the exploration of protein dynamics in individual cells and thus permits the elucidation of protein mobility, function, and interactions at a single-cell level. During a typical FRAP experiment, fluorescent molecules in a defined region of interest within the cell are bleached by a short and powerful laser pulse, while the recovery of the fluorescence in the region is monitored over time by time-lapse microscopy. FRAP experimental setup and image acquisition involve a number of steps that need to be carefully executed to avoid technical artifacts. Equally important is the subsequent computational analysis of FRAP raw data, to derive quantitative information on protein diffusion and binding parameters. Here we present an integrated in vivo and in silico protocol for the analysis of protein kinetics using FRAP. We focus on the most commonly encountered challenges and technical or computational pitfalls and their troubleshooting so that valid and robust insight into protein dynamics within living cells is gained.

The use of morphokinetics as a predictor of embryo implantation.

PubMed

Meseguer, Marcos; Herrero, Javier; Tejera, Alberto; Hilligsøe, Karen Marie; Ramsing, Niels Birger; Remohí, Jose

2011-10-01

Time-lapse observation presents an opportunity for optimizing embryo selection based on morphological grading as well as providing novel kinetic parameters, which may further improve accurate selection of viable embryos. The objective of this retrospective study was to identify the morphokinetic parameters specific to embryos that were capable of implanting. In order to compare a large number of embryos, with minimal variation in culture conditions, we have used an automatic embryo monitoring system. Using a tri-gas IVF incubator with a built-in camera designed to automatically acquire images at defined time points, we have simultaneously monitored up to 72 individual embryos without removing the embryos from the controlled environment. Images were acquired every 15 min in five different focal planes for at least 64 h for each embryo. We have monitored the development of transferred embryos from 285 couples undergoing their first ICSI cycle. The total number of transferred embryos was 522, of which 247 either failed to implant or fully implanted, with full implantation meaning that all transferred embryos in a treatment implanted. A detailed retrospective analysis of cleavage times, blastomere size and multinucleation was made for the 247 transferred embryos with either failed or full implantation. We found that several parameters were significantly correlated with subsequent implantation (e.g. time of first and subsequent cleavages as well as the time between cleavages). The most predictive parameters were: (i) time of division to 5 cells, t5 (48.8-56.6 h after ICSI); (ii) time between division to 3 cells and subsequent division to 4 cells, s2 (≤ 0.76 h) and (iii) duration of cell cycle two, i.e. time between division to 2 cells and division to 3 cells, cc2 (≤ 11.9 h). We also observed aberrant behavior such as multinucleation at the 4 cell stage, uneven blastomere size at the 2 cell stage and abrupt cell division to three or more cells, which appeared to largely preclude implantation. The image acquisition and time-lapse analysis system makes it possible to determine exact timing of embryo cleavages in a clinical setting. We propose a multivariable model based on our findings to classify embryos according to their probability of implantation. The efficacy of this classification will be evaluated in a prospective randomized study that ultimately will determine if implantation rates can be improved by time-lapse analysis.

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Tate, Lanetra C.; Wright, M. Clara; Caraccio, Anne

2013-01-01

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

Image guided constitutive modeling of the silicone brain phantom

NASA Astrophysics Data System (ADS)

Puzrin, Alexander; Skrinjar, Oskar; Ozan, Cem; Kim, Sihyun; Mukundan, Srinivasan

2005-04-01

The goal of this work is to develop reliable constitutive models of the mechanical behavior of the in-vivo human brain tissue for applications in neurosurgery. We propose to define the mechanical properties of the brain tissue in-vivo, by taking the global MR or CT images of a brain response to ventriculostomy - the relief of the elevated intracranial pressure. 3D image analysis translates these images into displacement fields, which by using inverse analysis allow for the constitutive models of the brain tissue to be developed. We term this approach Image Guided Constitutive Modeling (IGCM). The presented paper demonstrates performance of the IGCM in the controlled environment: on the silicone brain phantoms closely simulating the in-vivo brain geometry, mechanical properties and boundary conditions. The phantom of the left hemisphere of human brain was cast using silicon gel. An inflatable rubber membrane was placed inside the phantom to model the lateral ventricle. The experiments were carried out in a specially designed setup in a CT scanner with submillimeter isotropic voxels. The non-communicative hydrocephalus and ventriculostomy were simulated by consequently inflating and deflating the internal rubber membrane. The obtained images were analyzed to derive displacement fields, meshed, and incorporated into ABAQUS. The subsequent Inverse Finite Element Analysis (based on Levenberg-Marquardt algorithm) allowed for optimization of the parameters of the Mooney-Rivlin non-linear elastic model for the phantom material. The calculated mechanical properties were consistent with those obtained from the element tests, providing justification for the future application of the IGCM to in-vivo brain tissue.

Automatic quantitative analysis of in-stent restenosis using FD-OCT in vivo intra-arterial imaging.

PubMed

Mandelias, Kostas; Tsantis, Stavros; Spiliopoulos, Stavros; Katsakiori, Paraskevi F; Karnabatidis, Dimitris; Nikiforidis, George C; Kagadis, George C

2013-06-01

A new segmentation technique is implemented for automatic lumen area extraction and stent strut detection in intravascular optical coherence tomography (OCT) images for the purpose of quantitative analysis of in-stent restenosis (ISR). In addition, a user-friendly graphical user interface (GUI) is developed based on the employed algorithm toward clinical use. Four clinical datasets of frequency-domain OCT scans of the human femoral artery were analyzed. First, a segmentation method based on fuzzy C means (FCM) clustering and wavelet transform (WT) was applied toward inner luminal contour extraction. Subsequently, stent strut positions were detected by utilizing metrics derived from the local maxima of the wavelet transform into the FCM membership function. The inner lumen contour and the position of stent strut were extracted with high precision. Compared to manual segmentation by an expert physician, the automatic lumen contour delineation had an average overlap value of 0.917 ± 0.065 for all OCT images included in the study. The strut detection procedure achieved an overall accuracy of 93.80% and successfully identified 9.57 ± 0.5 struts for every OCT image. Processing time was confined to approximately 2.5 s per OCT frame. A new fast and robust automatic segmentation technique combining FCM and WT for lumen border extraction and strut detection in intravascular OCT images was designed and implemented. The proposed algorithm integrated in a GUI represents a step forward toward the employment of automated quantitative analysis of ISR in clinical practice.

Label-free imaging of trabecular meshwork cells using Coherent Anti-Stokes Raman Scattering (CARS) microscopy

PubMed Central

Lei, Tim C.; Ammar, David A.; Masihzadeh, Omid; Gibson, Emily A.

2011-01-01

Purpose To image the human trabecular meshwork (TM) using a non-invasive, non-destructive technique without the application of exogenous label. Methods Flat-mounted TM samples from a human cadaver eye were imaged using two nonlinear optical techniques: coherent anti-Stokes Raman scattering (CARS) and two-photon autofluorescence (TPAF). In TPAF, two optical photons are simultaneously absorbed and excite molecules in the sample that then emit a higher energy photon. The signal is predominately from collagen and elastin. The CARS technique uses two laser frequencies to specifically excite carbon-hydrogen bonds, allowing the visualization of lipid-rich cell membranes. Multiple images were taken along an axis perpendicular to the surface of the TM for subsequent analysis. Results Analysis of multiple TPAF images of the TM reveals the characteristic overlapping bundles of collagen of various sizes. Simultaneous CARS imaging revealed elliptical structures of ~7×10 µm in diameter populating the meshwork which were consistent with TM cells. Irregularly shaped objects of ~4 µm diameter appeared in both the TPAF and CARS channels, and are consistent with melanin granules. Conclusions CARS techniques were successful in imaging live TM cells in freshly isolated human TM samples. Similar images have been obtained with standard histological techniques, however the method described here has the advantage of being performed on unprocessed, unfixed tissue free from the potential distortions of the fine tissue morphology that can occur due to infusion of fixatives and treatment with alcohols. CARS imaging of the TM represents a new avenue for exploring details of aqueous outflow and TM cell physiology. PMID:22025898

Internal Carotid Artery Web as the Cause of Recurrent Cryptogenic Ischemic Stroke.

PubMed

Antigüedad-Muñoz, Jon; de la Riva, Patricia; Arenaza Choperena, Gorka; Muñoz Lopetegi, Amaia; Andrés Marín, Naiara; Fernández-Eulate, Gorka; Moreno Valladares, Manuel; Martínez Zabaleta, Maite

2018-05-01

Carotid artery web is considered an exceptional cause of recurrent ischemic strokes in the affected arterial territory. The underlying pathology proposed for this entity is an atypical fibromuscular dysplasia. We present the case of a 43-year-old woman with no cardiovascular risk factors who had experienced 2 cryptogenic ischemic strokes in the same arterial territory within an 11-month period. Although all diagnostic tests initially yielded normal results, detailed analysis of the computed tomography angiography images revealed a carotid web; catheter angiography subsequently confirmed the diagnosis. Carotid surgery was performed, since which time the patient has remained completely asymptomatic. The histological finding of intimal hyperplasia is consistent with previously reported cases of carotid artery web. Carotid artery web is an infrequent cause of stroke, and this diagnosis requires a high level of suspicion plus a detailed analysis of vascular imaging studies. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Study of living single cells in culture: automated recognition of cell behavior.

PubMed

Bodin, P; Papin, S; Meyer, C; Travo, P

1988-07-01

An automated system capable of analyzing the behavior, in real time, of single living cells in culture, in a noninvasive and nondestructive way, has been developed. A large number of cell positions in single culture dishes were recorded using a computer controlled, robotized microscope. During subsequent observations, binary images obtained from video image analysis of the microscope visual field allowed the identification of the recorded cells. These cells could be revisited automatically every few minutes. Long-term studies of the behavior of cells make possible the analysis of cellular locomotary and mitotic activities as well as determination of cell shape (chosen from a defined library) for several hours or days in a fully automated way with observations spaced up to 30 minutes. Short-term studies of the behavior of cells permit the study, in a semiautomatic way, of acute effects of drugs (5 to 15 minutes) on changes of surface area and length of cells.

Factors Affecting the Changes of Ice Crystal Form in Ice Cream

NASA Astrophysics Data System (ADS)

Wang, Xin; Watanabe, Manabu; Suzuki, Toru

In this study, the shape of ice crystals in ice cream was quantitatively evaluated by introducing fractal analysis. A small droplet of commercial ice cream mix was quickly cooled to about -30°C on the cold stage of microscope. Subsequently, it was heated to -5°C or -10°C and then held for various holding time. Based on the captured images at each holding time, the cross-sectional area and the length of circumference for each ice crystal were measured to calculate fractal dimension using image analysis software. The results showed that the ice crystals were categorized into two groups, e.g. simple-shape and complicated-shape, according to their fractal dimensions. The fractal dimension of ice crystals became lower with increasing holding time and holding temperature. It was also indicated that the growing rate of complicated-shape ice crystals was relatively higher because of aggregation.

High-speed imaging of submerged jet: visualization analysis using proper orthogonality decomposition

NASA Astrophysics Data System (ADS)

Liu, Yingzheng; He, Chuangxin

2016-11-01

In the present study, the submerged jet at low Reynolds numbers was visualized using laser induced fluoresce and high-speed imaging in a water tank. Well-controlled calibration was made to determine linear dependency region of the fluoresce intensity on its concentration. Subsequently, the jet fluid issuing from a circular pipe was visualized using a high-speed camera. The animation sequence of the visualized jet flow field was supplied for the snapshot proper orthogonality decomposition (POD) analysis. Spatio-temporally varying structures superimposed in the unsteady fluid flow were identified, e.g., the axisymmetric mode and the helical mode, which were reflected from the dominant POD modes. The coefficients of the POD modes give strong indication of temporal and spectral features of the corresponding unsteady events. The reconstruction using the time-mean visualization and the selected POD modes was conducted to reveal the convective motion of the buried vortical structures. National Natural Science Foundation of China.

Effect of relevance on amygdala activation and association with the ventral striatum.

PubMed

Ousdal, Olga Therese; Reckless, Greg E; Server, Andres; Andreassen, Ole A; Jensen, Jimmy

2012-08-01

While the amygdala historically has been implicated in emotional stimuli processing, recent data suggest a general role in parceling out the relevance of stimuli, regardless of their emotional properties. Using functional magnetic resonance imaging, we tested the relevance hypothesis by investigating human amygdala responses to emotionally neutral stimuli while manipulating their relevance. The task was operationalized as highly relevant if a subsequent opportunity to respond for a reward depended on response accuracy of the task, and less relevant if the reward opportunity was independent of task performance. A region of interest analysis revealed bilateral amygdala activations in response to the high relevance condition compared to the low relevance condition. An exploratory whole-brain analysis yielded robust similar results in bilateral ventral striatum. A subsequent functional connectivity analysis demonstrated increased connectivity between amygdala and ventral striatum for the highly relevant stimuli compared to the less relevant stimuli. These findings suggest that the amygdala's processing profile goes beyond detection of emotions per se, and directly support the proposed role in relevance detection. In addition, the findings suggest a close relationship between amygdala and ventral striatal activity when processing relevant stimuli. Thus, the results may indicate that human amygdala modulates ventral striatum activity and subsequent behaviors beyond that observed for emotional cues, to encompass a broader range of relevant stimuli. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluation of clinical image processing algorithms used in digital mammography.

PubMed

Zanca, Federica; Jacobs, Jurgen; Van Ongeval, Chantal; Claus, Filip; Celis, Valerie; Geniets, Catherine; Provost, Veerle; Pauwels, Herman; Marchal, Guy; Bosmans, Hilde

2009-03-01

Screening is the only proven approach to reduce the mortality of breast cancer, but significant numbers of breast cancers remain undetected even when all quality assurance guidelines are implemented. With the increasing adoption of digital mammography systems, image processing may be a key factor in the imaging chain. Although to our knowledge statistically significant effects of manufacturer-recommended image processings have not been previously demonstrated, the subjective experience of our radiologists, that the apparent image quality can vary considerably between different algorithms, motivated this study. This article addresses the impact of five such algorithms on the detection of clusters of microcalcifications. A database of unprocessed (raw) images of 200 normal digital mammograms, acquired with the Siemens Novation DR, was collected retrospectively. Realistic simulated microcalcification clusters were inserted in half of the unprocessed images. All unprocessed images were subsequently processed with five manufacturer-recommended image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OPVIEW v2, and Siemens OPVIEW v1). Four breast imaging radiologists were asked to locate and score the clusters in each image on a five point rating scale. The free-response data were analyzed by the jackknife free-response receiver operating characteristic (JAFROC) method and, for comparison, also with the receiver operating characteristic (ROC) method. JAFROC analysis revealed highly significant differences between the image processings (F = 8.51, p < 0.0001), suggesting that image processing strongly impacts the detectability of clusters. Siemens OPVIEW2 and Siemens OPVIEW1 yielded the highest and lowest performances, respectively. ROC analysis of the data also revealed significant differences between the processing but at lower significance (F = 3.47, p = 0.0305) than JAFROC. Both statistical analysis methods revealed that the same six pairs of modalities were significantly different, but the JAFROC confidence intervals were about 32% smaller than ROC confidence intervals. This study shows that image processing has a significant impact on the detection of microcalcifications in digital mammograms. Objective measurements, such as described here, should be used by the manufacturers to select the optimal image processing algorithm.

Single cell imaging of the chick retina with adaptive optics.

PubMed

Headington, Kenneth; Choi, Stacey S; Nickla, Debora; Doble, Nathan

2011-10-01

The chick eye is extensively used as a model in the study of myopia and its progression; however, analysis of the photoreceptor mosaic has required the use of excised retina due to the uncorrected optical aberrations in the lens and cornea. This study implemented high resolution adaptive optics (AO) retinal imaging to visualize the chick cone mosaic in vivo. The New England College of Optometry (NECO) AO fundus camera was modified to allow high resolution in vivo imaging on two 6-week-old White Leghorn chicks (Gallus gallus domesticus)-labeled chick A and chick B. Multiple, adjacent images, each with a 2.5(o) field of view, were taken and subsequently montaged together. This process was repeated at varying retinal locations measured from the tip of the pecten. Automated software was used to determine the cone spacing and density at each location. Voronoi analysis was applied to determine the packing arrangement of the cones. In both chicks, cone photoreceptors were clearly visible at all retinal locations imaged. Cone densities measured at 36(o) nasal-12(o) superior retina from the pecten tip for chick A and 40(o) nasal-12(o) superior retina for chick B were 21,714 ± 543 and 26,105 ± 653 cones/mm(2) respectively. For chick B, a further 11 locations immediately surrounding the pecten were imaged, with cone densities ranging from 20,980 ± 524 to 25,148 ± 629 cones/mm(2). In vivo analysis of the cone density and its packing characteristics are now possible in the chick eye through AO imaging, which has important implications for future studies of myopia and ocular disease research.

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

PubMed

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

2013-01-01

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

A model-based approach for detection of runways and other objects in image sequences acquired using an on-board camera

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Devadiga, Sadashiva; Tang, Yuan-Liang

1994-01-01

This research was initiated as a part of the Advanced Sensor and Imaging System Technology (ASSIST) program at NASA Langley Research Center. The primary goal of this research is the development of image analysis algorithms for the detection of runways and other objects using an on-board camera. Initial effort was concentrated on images acquired using a passive millimeter wave (PMMW) sensor. The images obtained using PMMW sensors under poor visibility conditions due to atmospheric fog are characterized by very low spatial resolution but good image contrast compared to those images obtained using sensors operating in the visible spectrum. Algorithms developed for analyzing these images using a model of the runway and other objects are described in Part 1 of this report. Experimental verification of these algorithms was limited to a sequence of images simulated from a single frame of PMMW image. Subsequent development and evaluation of algorithms was done using video image sequences. These images have better spatial and temporal resolution compared to PMMW images. Algorithms for reliable recognition of runways and accurate estimation of spatial position of stationary objects on the ground have been developed and evaluated using several image sequences. These algorithms are described in Part 2 of this report. A list of all publications resulting from this work is also included.

DNA Probe for Lactobacillus delbrueckii

PubMed Central

Delley, Michèle; Mollet, Beat; Hottinger, Herbert

1990-01-01

From a genomic DNA library of Lactobacillus delbrueckii subsp. bulgaricus, a clone was isolated which complements a leucine auxotrophy of an Escherichia coli strain (GE891). Subsequent analysis of the clone indicated that it could serve as a specific DNA probe. Dot-blot hybridizations with over 40 different Lactobacillus strains showed that this clone specifically recognizes L. delbrueckii subsp. delbrueckii, bulgaricus, and lactis. The sensitivity of the method was tested by using an α-32P-labeled DNA probe. Images PMID:16348233

Integrating TV/digital data spectrograph system

NASA Technical Reports Server (NTRS)

Duncan, B. J.; Fay, T. D.; Miller, E. R.; Wamsteker, W.; Brown, R. M.; Neely, P. L.

1975-01-01

A 25-mm vidicon camera was previously modified to allow operation in an integration mode for low-light-level astronomical work. The camera was then mated to a low-dispersion spectrograph for obtaining spectral information in the 400 to 750 nm range. A high speed digital video image system was utilized to digitize the analog video signal, place the information directly into computer-type memory, and record data on digital magnetic tape for permanent storage and subsequent analysis.

Dynamic Real-time Microscopy of the Urinary Tract Using Confocal Laser Endomicroscopy

PubMed Central

Wu, Katherine; Liu, Jen-Jane; Adams, Winifred; Sonn, Geoffrey A.; Mach, Kathleen E.; Pan, Ying; Beck, Andrew H.; Jensen, Kristin C.; Liao, Joseph C.

2014-01-01

OBJECTIVES To develop the diagnostic criteria for benign and neoplastic conditions of the urinary tract using probe-based confocal laser endomicroscopy (pCLE), a new technology for dynamic, in vivo imaging with micron-scale resolution. The suggested diagnostic criteria will formulate a guide for pCLE image interpretation in urology. METHODS Patients scheduled for transurethral resection of bladder tumor (TURBT) or nephrectomy were recruited. After white-light cystoscopy (WLC), fluorescein was administered as contrast. Different areas of the urinary tract were imaged with pCLE via direct contact between the confocal probe and the area of interest. Confocal images were subsequently compared with standard hematoxylin and eosin analysis. RESULTS pCLE images were collected from 66 participants, including 2 patients who underwent nephrectomy. We identified key features associated with different anatomic landmarks of the urinary tract, including the kidney, ureter, bladder, prostate, and urethra. In vivo pCLE of the bladder demonstrated distinct differences between normal mucosa and neoplastic tissue. Using mosaicing, a post hoc image-processing algorithm, individual image frames were juxtaposed to form wideangle views to better evaluate tissue microarchitecture. CONCLUSIONS In contrast to standard pathologic analysis of fixed tissue with hematoxylin and eosin, pCLE provides real time microscopy of the urinary tract to enable dynamic interrogation of benign and neoplastic tissues in vivo. The diagnostic criteria developed in this study will facilitate adaptation of pCLE for use in conjunction with WLC to expedite diagnosis of urinary tract pathology, particularly bladder cancer. PMID:21601243

a Sensor Aided H.264/AVC Video Encoder for Aerial Video Sequences with in the Loop Metadata Correction

NASA Astrophysics Data System (ADS)

Cicala, L.; Angelino, C. V.; Ruatta, G.; Baccaglini, E.; Raimondo, N.

2015-08-01

Unmanned Aerial Vehicles (UAVs) are often employed to collect high resolution images in order to perform image mosaicking and/or 3D reconstruction. Images are usually stored on board and then processed with on-ground desktop software. In such a way the computational load, and hence the power consumption, is moved on ground, leaving on board only the task of storing data. Such an approach is important in the case of small multi-rotorcraft UAVs because of their low endurance due to the short battery life. Images can be stored on board with either still image or video data compression. Still image system are preferred when low frame rates are involved, because video coding systems are based on motion estimation and compensation algorithms which fail when the motion vectors are significantly long and when the overlapping between subsequent frames is very small. In this scenario, UAVs attitude and position metadata from the Inertial Navigation System (INS) can be employed to estimate global motion parameters without video analysis. A low complexity image analysis can be still performed in order to refine the motion field estimated using only the metadata. In this work, we propose to use this refinement step in order to improve the position and attitude estimation produced by the navigation system in order to maximize the encoder performance. Experiments are performed on both simulated and real world video sequences.

Untangling cell tracks: Quantifying cell migration by time lapse image data analysis.

PubMed

Svensson, Carl-Magnus; Medyukhina, Anna; Belyaev, Ivan; Al-Zaben, Naim; Figge, Marc Thilo

2018-03-01

Automated microscopy has given researchers access to great amounts of live cell imaging data from in vitro and in vivo experiments. Much focus has been put on extracting cell tracks from such data using a plethora of segmentation and tracking algorithms, but further analysis is normally required to draw biologically relevant conclusions. Such relevant conclusions may be whether the migration is directed or not, whether the population has homogeneous or heterogeneous migration patterns. This review focuses on the analysis of cell migration data that are extracted from time lapse images. We discuss a range of measures and models used to analyze cell tracks independent of the biological system or the way the tracks were obtained. For single-cell migration, we focus on measures and models giving examples of biological systems where they have been applied, for example, migration of bacteria, fibroblasts, and immune cells. For collective migration, we describe the model systems wound healing, neural crest migration, and Drosophila gastrulation and discuss methods for cell migration within these systems. We also discuss the role of the extracellular matrix and subsequent differences between track analysis in vitro and in vivo. Besides methods and measures, we are putting special focus on the need for openly available data and code, as well as a lack of common vocabulary in cell track analysis. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Resting state network topology of the ferret brain.

PubMed

Zhou, Zhe Charles; Salzwedel, Andrew P; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K; Gilmore, John H; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-12-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

Ultrasound Assessment of Human Meniscus.

PubMed

Viren, Tuomas; Honkanen, Juuso T; Danso, Elvis K; Rieppo, Lassi; Korhonen, Rami K; Töyräs, Juha

2017-09-01

The aim of the present study was to evaluate the applicability of ultrasound imaging to quantitative assessment of human meniscus in vitro. Meniscus samples (n = 26) were harvested from 13 knee joints of non-arthritic human cadavers. Subsequently, three locations (anterior, center and posterior) from each meniscus were imaged with two ultrasound transducers (frequencies 9 and 40 MHz), and quantitative ultrasound parameters were determined. Furthermore, partial-least-squares regression analysis was applied for ultrasound signal to determine the relations between ultrasound scattering and meniscus integrity. Significant correlations between measured and predicted meniscus compositions and mechanical properties were obtained (R 2  = 0.38-0.69, p < 0.05). The relationship between conventional ultrasound parameters and integrity of the meniscus was weaker. To conclude, ultrasound imaging exhibited a potential for evaluation of meniscus integrity. Higher ultrasound frequency combined with multivariate analysis of ultrasound backscattering was found to be the most sensitive for evaluation of meniscus integrity. Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Tracking and Motion Analysis of Crack Propagations in Crystals for Molecular Dynamics

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

Tsap, L V; Duchaineau, M; Goldgof, D B

2001-05-14

This paper presents a quantitative analysis for a discovery in molecular dynamics. Recent simulations have shown that velocities of crack propagations in crystals under certain conditions can become supersonic, which is contrary to classical physics. In this research, they present a framework for tracking and motion analysis of crack propagations in crystals. It includes line segment extraction based on Canny edge maps, feature selection based on physical properties, and subsequent tracking of primary and secondary wavefronts. This tracking is completely automated; it runs in real time on three 834-image sequences using forty 250 MHZ processors. Results supporting physical observations aremore » presented in terms of both feature tracking and velocity analysis.« less

An inkjet vision measurement technique for high-frequency jetting

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

Kwon, Kye-Si, E-mail: kskwon@sch.ac.kr; Jang, Min-Hyuck; Park, Ha Yeong

2014-06-15

Inkjet technology has been used as manufacturing a tool for printed electronics. To increase the productivity, the jetting frequency needs to be increased. When using high-frequency jetting, the printed pattern quality could be non-uniform since the jetting performance characteristics including the jetting speed and droplet volume could vary significantly with increases in jet frequency. Therefore, high-frequency jetting behavior must be evaluated properly for improvement. However, it is difficult to measure high-frequency jetting behavior using previous vision analysis methods, because subsequent droplets are close or even merged. In this paper, we present vision measurement techniques to evaluate the drop formation ofmore » high-frequency jetting. The proposed method is based on tracking target droplets such that subsequent droplets can be excluded in the image analysis by focusing on the target droplet. Finally, a frequency sweeping method for jetting speed and droplet volume is presented to understand the overall jetting frequency effects on jetting performance.« less

An arc control and protection system for the JET lower hybrid antenna based on an imaging system

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

Figueiredo, J., E-mail: joao.figueiredo@jet.efda.org; Mailloux, J.; Kirov, K.

Arcs are the potentially most dangerous events related to Lower Hybrid (LH) antenna operation. If left uncontrolled they can produce damage and cause plasma disruption by impurity influx. To address this issue an arc real time control and protection imaging system for the Joint European Torus (JET) LH antenna has been implemented. The LH system is one of the additional heating systems at JET. It comprises 24 microwave generators (klystrons, operating at 3.7 GHz) providing up to 5 MW of heating and current drive to the JET plasma. This is done through an antenna composed of an array of waveguidesmore » facing the plasma. The protection system presented here is based primarily on an imaging arc detection and real time control system. It has adapted the ITER like wall hotspot protection system using an identical CCD camera and real time image processing unit. A filter has been installed to avoid saturation and spurious system triggers caused by ionization light. The antenna is divided in 24 Regions Of Interest (ROIs) each one corresponding to one klystron. If an arc precursor is detected in a ROI, power is reduced locally with subsequent potential damage and plasma disruption avoided. The power is subsequently reinstated if, during a defined interval of time, arcing is confirmed not to be present by image analysis. This system was successfully commissioned during the restart phase and beginning of the 2013 scientific campaign. Since its installation and commissioning, arcs and related phenomena have been prevented. In this contribution we briefly describe the camera, image processing, and real time control systems. Most importantly, we demonstrate that an LH antenna arc protection system based on CCD camera imaging systems works. Examples of both controlled and uncontrolled LH arc events and their consequences are shown.« less

Metabolite mapping by consecutive nanostructure and silver-assisted mass spectrometry imaging on tissue sections.

PubMed

Gustafsson, O J R; Guinan, T M; Rudd, D; Kobus, H; Benkendorff, K; Voelcker, N H

2017-06-30

Nanostructure-based mass spectrometry imaging (MSI) is a promising technology for molecular imaging of small molecules, without the complex chemical background typically encountered in matrix-assisted molecular imaging approaches. Here, we have enhanced these surfaces with silver (Ag) to provide a second tier of MSI data from a single sample. MSI data was acquired through the application of laser desorption/ionization mass spectrometry to biological samples imprinted onto desorption/ionization on silicon (DIOS) substrates. Following initial analysis, ultra-thin Ag layers were overlaid onto the followed by MSI analysis (Ag-DIOS MSI). This approach was first demonstrated for fingermark small molecules including environmental contaminants and sebum components. Subsequently, this bimodal method was translated to lipids and metabolites in fore-stomach sections from a 6-bromoisatin chemopreventative murine mouse model. DIOS MSI allowed mapping of common ions in fingermarks as well as 6-bromoisatin metabolites and lipids in murine fore-stomach. Furthermore, DIOS MSI was complemented by the Ag-DIOS MSI of Ag-adductable lipids such as wax esters in fingermarks and cholesterol in murine fore-stomach. Gastrointestinal acid condensation products of 6-bromoisatin, such as the 6,6'-dibromoindirubin mapped herein, are very challenging to isolate and characterize. By re-analyzing the same tissue imprints, this metabolite was readily detected by DIOS, placed in a tissue-specific spatial context, and subsequently overlaid with additional lipid distributions acquired using Ag-DIOS MSI. The ability to place metabolite and lipid classes in a tissue-specific context makes this novel method suited to MSI analyses where the collection of additional information from the same sample maximises resource use, and also maximises the number of annotated small molecules, in particular for metabolites that are typically undetectable with traditional platforms. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Label-free optical imaging of membrane patches for atomic force microscopy

PubMed Central

Churnside, Allison B.; King, Gavin M.; Perkins, Thomas T.

2010-01-01

In atomic force microscopy (AFM), finding sparsely distributed regions of interest can be difficult and time-consuming. Typically, the tip is scanned until the desired object is located. This process can mechanically or chemically degrade the tip, as well as damage fragile biological samples. Protein assemblies can be detected using the back-scattered light from a focused laser beam. We previously used back-scattered light from a pair of laser foci to stabilize an AFM. In the present work, we integrate these techniques to optically image patches of purple membranes prior to AFM investigation. These rapidly acquired optical images were aligned to the subsequent AFM images to ~40 nm, since the tip position was aligned to the optical axis of the imaging laser. Thus, this label-free imaging efficiently locates sparsely distributed protein assemblies for subsequent AFM study while simultaneously minimizing degradation of the tip and the sample. PMID:21164738

Subsequent health-care utilization associated with early physical therapy for new episodes of low back pain in older adults.

PubMed

Karvelas, Deven A; Rundell, Sean D; Friedly, Janna L; Gellhorn, Alfred C; Gold, Laura S; Comstock, Bryan A; Heagerty, Patrick J; Bresnahan, Brian W; Nerenz, David R; Jarvik, Jeffrey G

2017-03-01

The association between early physical therapy (PT) and subsequent health-care utilization following a new visit for low back pain is not clear, particularly in the setting of acute low back pain. This study aimed to estimate the association between initiating early PT following a new visit for an episode of low back pain and subsequent back pain-specific health-care utilization in older adults. This is a prospective cohort study. Data were collected at three integrated health-care systems in the United States through the Back Pain Outcomes using Longitudinal Data (BOLD) registry. We recruited 4,723 adults, aged 65 and older, presenting to a primary care setting with a new episode of low back pain. Primary outcome was total back pain-specific relative value units (RVUs), from days 29 to 365. Secondary outcomes included overall RVUs for all health care and use of specific health-care services including imaging (x-ray and magnetic resonance imaging [MRI] or computed tomography [CT]), emergency department visits, physician visits, PT, spinal injections, spinal surgeries, and opioid use. We compared patients who had early PT (initiated within 28 days of the index visit) with those not initiating early PT using appropriate, generalized linear models to adjust for potential confounding variables. Adjusted analysis found no statistically significant difference in total spine RVUs between the two groups (ratio of means 1.19, 95% CI of 0.72-1.96, p=.49). For secondary outcomes, only the difference between total spine imaging RVUs and total PT RVUs was statistically significant. The early PT group had greater PT RVUs; the ratio of means was 2.56 (95% CI of 2.17-3.03, p<.001). The early PT group had greater imaging RVUs; the ratio of means was 1.37 (95% CI of 1.09-1.71, p=.01.) CONCLUSIONS: We found that in a group of older adults presenting for a new episode of low back pain, the use of early PT is not associated with any statistically significant difference in subsequent back pain-specific health-care utilization compared with patients not receiving early PT. Copyright © 2016 Elsevier Inc. All rights reserved.

Understanding and improving optical coherence tomography imaging depth in selective laser sintering nylon 12 parts and powder

NASA Astrophysics Data System (ADS)

Lewis, Adam D.; Katta, Nitesh; McElroy, Austin; Milner, Thomas; Fish, Scott; Beaman, Joseph

2018-04-01

Optical coherence tomography (OCT) has shown promise as a process sensor in selective laser sintering (SLS) due to its ability to yield depth-resolved data not attainable with conventional sensors. However, OCT images of nylon 12 powder and nylon 12 components fabricated via SLS contain artifacts that have not been previously investigated in the literature. A better understanding of light interactions with SLS powder and components is foundational for further research expanding the utility of OCT imaging in SLS and other additive manufacturing (AM) sensing applications. Specifically, in this work, nylon powder and sintered parts were imaged in air and in an index matching liquid. Subsequent image analysis revealed the cause of "signal-tail" OCT image artifacts to be a combination of both inter and intraparticle multiple-scattering and reflections. Then, the OCT imaging depth of nylon 12 powder and the contrast-to-noise ratio of a sintered part were improved through the use of an index matching liquid. Finally, polymer crystals were identified as the main source of intraparticle scattering in nylon 12 powder. Implications of these results on future research utilizing OCT in SLS are also given.

Cortical Enhanced Tissue Segmentation of Neonatal Brain MR Images Acquired by a Dedicated Phased Array Coil

PubMed Central

Shi, Feng; Yap, Pew-Thian; Fan, Yong; Cheng, Jie-Zhi; Wald, Lawrence L.; Gerig, Guido; Lin, Weili; Shen, Dinggang

2010-01-01

The acquisition of high quality MR images of neonatal brains is largely hampered by their characteristically small head size and low tissue contrast. As a result, subsequent image processing and analysis, especially for brain tissue segmentation, are often hindered. To overcome this problem, a dedicated phased array neonatal head coil is utilized to improve MR image quality by effectively combing images obtained from 8 coil elements without lengthening data acquisition time. In addition, a subject-specific atlas based tissue segmentation algorithm is specifically developed for the delineation of fine structures in the acquired neonatal brain MR images. The proposed tissue segmentation method first enhances the sheet-like cortical gray matter (GM) structures in neonatal images with a Hessian filter for generation of cortical GM prior. Then, the prior is combined with our neonatal population atlas to form a cortical enhanced hybrid atlas, which we refer to as the subject-specific atlas. Various experiments are conducted to compare the proposed method with manual segmentation results, as well as with additional two population atlas based segmentation methods. Results show that the proposed method is capable of segmenting the neonatal brain with the highest accuracy, compared to other two methods. PMID:20862268

Archeological Echocardiography: Digitization and Speckle Tracking Analysis of Archival Echocardiograms in the HyperGEN Study.

PubMed

Aguilar, Frank G; Selvaraj, Senthil; Martinez, Eva E; Katz, Daniel H; Beussink, Lauren; Kim, Kwang-Youn A; Ping, Jie; Rasmussen-Torvik, Laura; Goyal, Amita; Sha, Jin; Irvin, Marguerite R; Arnett, Donna K; Shah, Sanjiv J

2016-03-01

Several large epidemiologic studies and clinical trials have included echocardiography, but images were stored in analog format and these studies predated tissue Doppler imaging (TDI) and speckle tracking echocardiography (STE). We hypothesized that digitization of analog echocardiograms, with subsequent quantification of cardiac mechanics using STE, is feasible, reproducible, accurate, and produces clinically valid results. In the NHLBI HyperGEN study (N = 2234), archived analog echocardiograms were digitized and subsequently analyzed using STE to obtain tissue velocities/strain. Echocardiograms were assigned quality scores and inter-/intra-observer agreement was calculated. Accuracy was evaluated in: (1) a separate second study (N = 50) comparing prospective digital strain versus post hoc analog-to-digital strain, and (2) in a third study (N = 95) comparing prospectively obtained TDI e' velocities with post hoc STE e' velocities. Finally, we replicated previously known associations between tissue velocities/strain, conventional echocardiographic measurements, and clinical data. Of the 2234 HyperGEN echocardiograms, 2150 (96.2%) underwent successful digitization and STE analysis. Inter/intra-observer agreement was high for all STE parameters, especially longitudinal strain (LS). In accuracy studies, LS performed best when comparing post hoc STE to prospective digital STE for strain analysis. STE-derived e' velocities correlated with, but systematically underestimated, TDI e' velocity. Several known associations between clinical variables and cardiac mechanics were replicated in HyperGEN. We also found a novel independent inverse association between fasting glucose and LS (adjusted β = -2.4 [95% CI -3.6, -1.2]% per 1-SD increase in fasting glucose; P < 0.001). Archeological echocardiography, the digitization and speckle tracking analysis of archival echocardiograms, is feasible and generates indices of cardiac mechanics similar to contemporary studies. © 2015, Wiley Periodicals, Inc.

Archeological Echocardiography: Digitization and Speckle-Tracking Analysis of Archival Echocardiograms in the HyperGEN Study

PubMed Central

Aguilar, Frank G.; Selvaraj, Senthil; Martinez, Eva E.; Katz, Daniel H.; Beussink, Lauren; Kim, Kwang-Youn A.; Ping, Jie; Rasmussen-Torvik, Laura; Goyal, Amita; Sha, Jin; Irvin, Marguerite R.; Arnett, Donna K.; Shah, Sanjiv J.

2015-01-01

Background Several large epidemiologic studies and clinical trials have included echocardiography, but images were stored in analog format and these studies predated tissue Doppler imaging (TDI) and speckle-tracking echocardiography (STE). We hypothesized that digitization of analog echocardiograms, with subsequent quantification of cardiac mechanics using STE, is feasible, reproducible, accurate, and produces clinically valid results. Methods In the NHLBI HyperGEN study (N=2234), archived analog echocardiograms were digitized and subsequently analyzed using STE to obtain tissue velocities/strain. Echocardiograms were assigned quality scores and inter/intraobserver agreement was calculated. Accuracy was evaluated in (1) a separate second study (N=50) comparing prospective digital strain vs. post-hoc analog-to-digital strain; and (2) in a third study (N=95) comparing prospectively-obtained TDI e′ velocities with post-hoc STE e′ velocities. Finally, we replicated previously known associations between tissue velocities/strain, conventional echocardiographic measurements, and clinical data. Results Of the 2234 HyperGEN echocardiograms, 2150 (96.2%) underwent successful digitization and STE analysis. Inter/intraobserver agreement was high for all STE parameters, especially longitudinal strain (LS). In accuracy studies, LS performed best when comparing post-hoc STE to prospective digital STE for strain analysis. STE-derived e′ velocities correlated with, but systematically underestimated, TDI e′ velocity. Several known associations between clinical variables and cardiac mechanics were replicated in HyperGEN. We also found a novel independent inverse association between fasting glucose and LS (adjusted β =−2.4 [95% CI −3.6,−1.2]% per 1-SD increase in fasting glucose; P<0.001). Conclusions Archeological echocardiography, the digitization and speckle-tracking analysis of archival echocardiograms, is feasible and generates parameters of cardiac mechanics similar to contemporary studies. PMID:26525308

Time-resolved contrast-enhanced MR angiography of the thorax in adults with congenital heart disease.

PubMed

Mohrs, Oliver K; Petersen, Steffen E; Voigtlaender, Thomas; Peters, Jutta; Nowak, Bernd; Heinemann, Markus K; Kauczor, Hans-Ulrich

2006-10-01

The aim of this study was to evaluate the diagnostic value of time-resolved contrast-enhanced MR angiography in adults with congenital heart disease. Twenty patients with congenital heart disease (mean age, 38 +/- 14 years; range, 16-73 years) underwent contrast-enhanced turbo fast low-angle shot MR angiography. Thirty consecutive coronal 3D slabs with a frame rate of 1-second duration were acquired. The mask defined as the first data set was subtracted from subsequent images. Image quality was evaluated using a 5-point scale (from 1, not assessable, to 5, excellent image quality). Twelve diagnostic parameters yielded 1 point each in case of correct diagnosis (binary analysis into normal or abnormal) and were summarized into three categories: anatomy of the main thoracic vessels (maximum, 5 points), sequential cardiac anatomy (maximum, 5 points), and shunt detection (maximum, 2 points). The results were compared with a combined clinical reference comprising medical or surgical reports and other imaging studies. Diagnostic accuracies were calculated for each of the parameters as well as for the three categories. The mean image quality was 3.7 +/- 1.0. Using a binary approach, 220 (92%) of the 240 single diagnostic parameters could be analyzed. The percentage of maximum diagnostic points, the sensitivity, the specificity, and the positive and the negative predictive values were all 100% for the anatomy of the main thoracic vessels; 97%, 87%, 100%, 100%, and 96% for sequential cardiac anatomy; and 93%, 93%, 92%, 88%, and 96% for shunt detection. Time-resolved contrast-enhanced MR angiography provides, in one breath-hold, anatomic and qualitative functional information in adult patients with congenital heart disease. The high diagnostic accuracy allows the investigator to tailor subsequent specific MR sequences within the same session.

Dissecting hemisphere-specific contributions to visual spatial imagery using parametric brain mapping.

PubMed

Bien, Nina; Sack, Alexander T

2014-07-01

In the current study we aimed to empirically test previously proposed accounts of a division of labour between the left and right posterior parietal cortices during visuospatial mental imagery. The representation of mental images in the brain has been a topic of debate for several decades. Although the posterior parietal cortex is involved bilaterally, previous studies have postulated that hemispheric specialisation might result in a division of labour between the left and right parietal cortices. In the current fMRI study, we used an elaborated version of a behaviourally-controlled spatial imagery paradigm, the mental clock task, which involves mental image generation and a subsequent spatial comparison between two angles. By systematically varying the difference between the two angles that are mentally compared, we induced a symbolic distance effect: smaller differences between the two angles result in higher task difficulty. We employed parametrically weighed brain imaging to reveal brain areas showing a graded activation pattern in accordance with the induced distance effect. The parametric difficulty manipulation influenced behavioural data and brain activation patterns in a similar matter. Moreover, since this difficulty manipulation only starts to play a role from the angle comparison phase onwards, it allows for a top-down dissociation between the initial mental image formation, and the subsequent angle comparison phase of the spatial imagery task. Employing parametrically weighed fMRI analysis enabled us to top-down disentangle brain activation related to mental image formation, and activation reflecting spatial angle comparison. The results provide first empirical evidence for the repeatedly proposed division of labour between the left and right posterior parietal cortices during spatial imagery. Copyright © 2014 Elsevier Inc. All rights reserved.

Cutaneous paragonimiasis due to triploid Paragonimus westermani presenting as a non-migratory subcutaneous nodule: a case report

PubMed Central

2014-01-01

Introduction Paragonimiasis is a food-borne infection caused by Paragonimus parasites. The lungs and pleura are the primary sites for the infection; however, ectopic infection can occur in other organs such as skin, liver and brain. It is difficult to make a diagnosis of ectopic paragonimiasis due to an ignorance of, and unfamiliarity with the disease. We report the case of a patient with subcutaneous paragonimiasis diagnosed by histopathological analysis and serological testing. Case presentation A 39-year-old Chinese immigrant woman presented with a subcutaneous nodule in her left lower back. The nodule was initially suspected of lipoma and she was followed up on without any treatment. However, it gradually indurated and the nodule was resected surgically. A magnetic resonance imaging scan revealed a polycystic lesion with inhomogeneous low or high intensity on T1- or T2-weighted images, respectively. The rim of the lesion was enhanced after contrast enhancement, but the inside did not show high-signal intensity. A histological analysis of the surgically resected specimen revealed variable-sized tubulo-cystic structures. The cyst wall showed a granulomatous change with scant eosinophilic infiltration. A number of parasite ova were observed in the necrotic tissue inside the cysts, and a parasite body with a presumed oral sucker and reproductive organ was also detected, suggesting a trematode infection. A subsequent serological examination showed a positive reaction of her serum to the Paragonimus westermani antigen. No abnormal findings were found on her chest computed tomography scan. The diagnosis of subcutaneous paragonimiasis caused by Paragonimus westermani was made. Conclusions We report a case presenting only as a non-migratory subcutaneous nodule without any pleuropulmonary lesion, which was initially suspected of lipoma but denied by magnetic resonance imaging scan results. The case was subsequently diagnosed as subcutaneous paragonimiasis from the results of histopathological analysis and serological testing. PMID:25322860

Effects of exposure to bodies of different sizes on perception of and satisfaction with own body size: two randomized studies.

PubMed

Bould, Helen; Carnegie, Rebecca; Allward, Heather; Bacon, Emily; Lambe, Emily; Sapseid, Megan; Button, Katherine S; Lewis, Glyn; Skinner, Andy; Broome, Matthew R; Park, Rebecca; Harmer, Catherine J; Penton-Voak, Ian S; Munafò, Marcus R

2018-05-01

Body dissatisfaction is prevalent among women and associated with subsequent obesity and eating disorders. Exposure to images of bodies of different sizes has been suggested to change the perception of 'normal' body size in others. We tested whether exposure to different-sized (otherwise identical) bodies changes perception of own and others' body size, satisfaction with body size and amount of chocolate consumed. In Study 1, 90 18-25-year-old women with normal BMI were randomized into one of three groups to complete a 15 min two-back task using photographs of women either of 'normal weight' (Body Mass Index (BMI) 22-23 kg m -2 ), or altered to appear either under- or over-weight. Study 2 was identical except the 96 participants had high baseline body dissatisfaction and were followed up after 24 h. We also conducted a mega-analysis combining both studies. Participants rated size of others' bodies, own size, and satisfaction with size pre- and post-task. Post-task ratings were compared between groups, adjusting for pre-task ratings. Participants exposed to over- or normal-weight images subsequently perceived others' bodies as smaller, in comparison to those shown underweight bodies ( p  < 0.001). They also perceived their own bodies as smaller (Study 1, p  = 0.073; Study 2, p  = 0.018; mega-analysis, p  = 0.001), and felt more satisfied with their size (Study 1, p  = 0.046; Study 2, p  = 0.004; mega-analysis, p  = 0.006). There were no differences in chocolate consumption. This study suggests that a move towards using images of women with a BMI in the healthy range in the media may help to reduce body dissatisfaction, and the associated risk of eating disorders.

Effects of exposure to bodies of different sizes on perception of and satisfaction with own body size: two randomized studies

PubMed Central

Carnegie, Rebecca; Allward, Heather; Bacon, Emily; Lambe, Emily; Sapseid, Megan; Button, Katherine S.; Lewis, Glyn; Skinner, Andy; Broome, Matthew R.; Park, Rebecca; Penton-Voak, Ian S.

2018-01-01

Body dissatisfaction is prevalent among women and associated with subsequent obesity and eating disorders. Exposure to images of bodies of different sizes has been suggested to change the perception of ‘normal’ body size in others. We tested whether exposure to different-sized (otherwise identical) bodies changes perception of own and others' body size, satisfaction with body size and amount of chocolate consumed. In Study 1, 90 18–25-year-old women with normal BMI were randomized into one of three groups to complete a 15 min two-back task using photographs of women either of ‘normal weight’ (Body Mass Index (BMI) 22–23 kg m−2), or altered to appear either under- or over-weight. Study 2 was identical except the 96 participants had high baseline body dissatisfaction and were followed up after 24 h. We also conducted a mega-analysis combining both studies. Participants rated size of others' bodies, own size, and satisfaction with size pre- and post-task. Post-task ratings were compared between groups, adjusting for pre-task ratings. Participants exposed to over- or normal-weight images subsequently perceived others' bodies as smaller, in comparison to those shown underweight bodies (p < 0.001). They also perceived their own bodies as smaller (Study 1, p = 0.073; Study 2, p = 0.018; mega-analysis, p = 0.001), and felt more satisfied with their size (Study 1, p = 0.046; Study 2, p = 0.004; mega-analysis, p = 0.006). There were no differences in chocolate consumption. This study suggests that a move towards using images of women with a BMI in the healthy range in the media may help to reduce body dissatisfaction, and the associated risk of eating disorders. PMID:29892352

ADC texture—An imaging biomarker for high-grade glioma?

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

Brynolfsson, Patrik; Hauksson, Jón; Karlsson, Mikael

2014-10-15

Purpose: Survival for high-grade gliomas is poor, at least partly explained by intratumoral heterogeneity contributing to treatment resistance. Radiological evaluation of treatment response is in most cases limited to assessment of tumor size months after the initiation of therapy. Diffusion-weighted magnetic resonance imaging (MRI) and its estimate of the apparent diffusion coefficient (ADC) has been widely investigated, as it reflects tumor cellularity and proliferation. The aim of this study was to investigate texture analysis of ADC images in conjunction with multivariate image analysis as a means for identification of pretreatment imaging biomarkers. Methods: Twenty-three consecutive high-grade glioma patients were treatedmore » with radiotherapy (2 Gy/60 Gy) with concomitant and adjuvant temozolomide. ADC maps and T1-weighted anatomical images with and without contrast enhancement were collected prior to treatment, and (residual) tumor contrast enhancement was delineated. A gray-level co-occurrence matrix analysis was performed on the ADC maps in a cuboid encapsulating the tumor in coronal, sagittal, and transversal planes, giving a total of 60 textural descriptors for each tumor. In addition, similar examinations and analyses were performed at day 1, week 2, and week 6 into treatment. Principal component analysis (PCA) was applied to reduce dimensionality of the data, and the five largest components (scores) were used in subsequent analyses. MRI assessment three months after completion of radiochemotherapy was used for classifying tumor progression or regression. Results: The score scatter plots revealed that the first, third, and fifth components of the pretreatment examinations exhibited a pattern that strongly correlated to survival. Two groups could be identified: one with a median survival after diagnosis of 1099 days and one with 345 days, p = 0.0001. Conclusions: By combining PCA and texture analysis, ADC texture characteristics were identified, which seems to hold pretreatment prognostic information, independent of known prognostic factors such as age, stage, and surgical procedure. These findings encourage further studies with a larger patient cohort.« less

Co-registered Topographical, Band Excitation Nanomechanical, and Mass Spectral Imaging Using a Combined Atomic Force Microscopy/Mass Spectrometry Platform

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

Ovchinnikova, Olga S.; Tai, Tamin; Bocharova, Vera

The advancement of a hybrid atomic force microscopy/mass spectrometry imaging platform demonstrating for the first time co-registered topographical, band excitation nanomechanical, and mass spectral imaging of a surface using a single instrument is reported. The mass spectrometry-based chemical imaging component of the system utilized nanothermal analysis probes for pyrolytic surface sampling followed by atmospheric pressure chemical ionization of the gas phase species produced with subsequent mass analysis. We discuss the basic instrumental setup and operation and the multimodal imaging capability and utility are demonstrated using a phase separated polystyrene/poly(2-vinylpyridine) polymer blend thin film. The topography and band excitation images showedmore » that the valley and plateau regions of the thin film surface were comprised primarily of one of the two polymers in the blend with the mass spectral chemical image used to definitively identify the polymers at the different locations. Data point pixel size for the topography (390 nm x 390 nm), band excitation (781 nm x 781 nm), mass spectrometry (690 nm x 500 nm) images was comparable and submicrometer in all three cases, but the data voxel size for each of the three images was dramatically different. The topography image was uniquely a surface measurement, whereas the band excitation image included information from an estimated 10 nm deep into the sample and the mass spectral image from 110-140 nm in depth. Moreover, because of this dramatic sampling depth variance, some differences in the band excitation and mass spectrometry chemical images were observed and were interpreted to indicate the presence of a buried interface in the sample. The spatial resolution of the mass spectral image was estimated to be between 1.5 m 2.6 m, based on the ability to distinguish surface features in that image that were also observed in the other images.« less

Co-registered Topographical, Band Excitation Nanomechanical, and Mass Spectral Imaging Using a Combined Atomic Force Microscopy/Mass Spectrometry Platform

DOE PAGES

Ovchinnikova, Olga S.; Tai, Tamin; Bocharova, Vera; ...

2015-03-18

The advancement of a hybrid atomic force microscopy/mass spectrometry imaging platform demonstrating for the first time co-registered topographical, band excitation nanomechanical, and mass spectral imaging of a surface using a single instrument is reported. The mass spectrometry-based chemical imaging component of the system utilized nanothermal analysis probes for pyrolytic surface sampling followed by atmospheric pressure chemical ionization of the gas phase species produced with subsequent mass analysis. We discuss the basic instrumental setup and operation and the multimodal imaging capability and utility are demonstrated using a phase separated polystyrene/poly(2-vinylpyridine) polymer blend thin film. The topography and band excitation images showedmore » that the valley and plateau regions of the thin film surface were comprised primarily of one of the two polymers in the blend with the mass spectral chemical image used to definitively identify the polymers at the different locations. Data point pixel size for the topography (390 nm x 390 nm), band excitation (781 nm x 781 nm), mass spectrometry (690 nm x 500 nm) images was comparable and submicrometer in all three cases, but the data voxel size for each of the three images was dramatically different. The topography image was uniquely a surface measurement, whereas the band excitation image included information from an estimated 10 nm deep into the sample and the mass spectral image from 110-140 nm in depth. Moreover, because of this dramatic sampling depth variance, some differences in the band excitation and mass spectrometry chemical images were observed and were interpreted to indicate the presence of a buried interface in the sample. The spatial resolution of the mass spectral image was estimated to be between 1.5 m 2.6 m, based on the ability to distinguish surface features in that image that were also observed in the other images.« less

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques.

PubMed

Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L; Bilello, Michel; O'Rourke, Donald M; Davatzikos, Christos

2016-03-01

MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood-brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images.

PubMed

Xu, Jun; Xiang, Lei; Liu, Qingshan; Gilmore, Hannah; Wu, Jianzhong; Tang, Jinghai; Madabhushi, Anant

2016-01-01

Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of breast cancer tissue specimens. The Nottingham Histologic Score system is highly correlated with the shape and appearance of breast cancer nuclei in histopathological images. However, automated nucleus detection is complicated by 1) the large number of nuclei and the size of high resolution digitized pathology images, and 2) the variability in size, shape, appearance, and texture of the individual nuclei. Recently there has been interest in the application of "Deep Learning" strategies for classification and analysis of big image data. Histopathology, given its size and complexity, represents an excellent use case for application of deep learning strategies. In this paper, a Stacked Sparse Autoencoder (SSAE), an instance of a deep learning strategy, is presented for efficient nuclei detection on high-resolution histopathological images of breast cancer. The SSAE learns high-level features from just pixel intensities alone in order to identify distinguishing features of nuclei. A sliding window operation is applied to each image in order to represent image patches via high-level features obtained via the auto-encoder, which are then subsequently fed to a classifier which categorizes each image patch as nuclear or non-nuclear. Across a cohort of 500 histopathological images (2200 × 2200) and approximately 3500 manually segmented individual nuclei serving as the groundtruth, SSAE was shown to have an improved F-measure 84.49% and an average area under Precision-Recall curve (AveP) 78.83%. The SSAE approach also out-performed nine other state of the art nuclear detection strategies.

The applicability of frame imaging from a spinning spacecraft. Volume 1: Summary report

NASA Technical Reports Server (NTRS)

Botticelli, R. A.; Johnson, R. O.; Wallmark, G. N.

1973-01-01

A detailed study was made of frame-type imaging systems for use on board a spin stabilized spacecraft for outer planets applications. All types of frame imagers capable of performing this mission were considered, regardless of the current state of the art. Detailed sensor models of these systems were developed at the component level and used in the subsequent analyses. An overall assessment was then made of the various systems based upon results of a worst-case performance analysis, foreseeable technology problems, and the relative reliability and radiation tolerance of the systems. Special attention was directed at restraints imposed by image motion and the limited data transmission and storage capability of the spacecraft. Based upon this overall assessment, the most promising systems were selected and then examined in detail for a specified Jupiter orbiter mission. The relative merits of each selected system were then analyzed, and the system design characteristics were demonstrated using preliminary configurations, block diagrams, and tables of estimated weights, volumes and power consumption.

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue.

PubMed

Macedo, Nayana Damiani; Buzin, Aline Rodrigues; de Araujo, Isabela Bastos Binotti Abreu; Nogueira, Breno Valentim; de Andrade, Tadeu Uggere; Endringer, Denise Coutinho; Lenz, Dominik

2017-02-01

The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation. A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software. Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively. Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

TuMore: generation of synthetic brain tumor MRI data for deep learning based segmentation approaches

NASA Astrophysics Data System (ADS)

Lindner, Lydia; Pfarrkirchner, Birgit; Gsaxner, Christina; Schmalstieg, Dieter; Egger, Jan

2018-03-01

Accurate segmentation and measurement of brain tumors plays an important role in clinical practice and research, as it is critical for treatment planning and monitoring of tumor growth. However, brain tumor segmentation is one of the most challenging tasks in medical image analysis. Since manual segmentations are subjective, time consuming and neither accurate nor reliable, there exists a need for objective, robust and fast automated segmentation methods that provide competitive performance. Therefore, deep learning based approaches are gaining interest in the field of medical image segmentation. When the training data set is large enough, deep learning approaches can be extremely effective, but in domains like medicine, only limited data is available in the majority of cases. Due to this reason, we propose a method that allows to create a large dataset of brain MRI (Magnetic Resonance Imaging) images containing synthetic brain tumors - glioblastomas more specifically - and the corresponding ground truth, that can be subsequently used to train deep neural networks.

The Novel Object and Unusual Name (NOUN) Database: A collection of novel images for use in experimental research.

PubMed

Horst, Jessica S; Hout, Michael C

2016-12-01

Many experimental research designs require images of novel objects. Here we introduce the Novel Object and Unusual Name (NOUN) Database. This database contains 64 primary novel object images and additional novel exemplars for ten basic- and nine global-level object categories. The objects' novelty was confirmed by both self-report and a lack of consensus on questions that required participants to name and identify the objects. We also found that object novelty correlated with qualifying naming responses pertaining to the objects' colors. The results from a similarity sorting task (and a subsequent multidimensional scaling analysis on the similarity ratings) demonstrated that the objects are complex and distinct entities that vary along several featural dimensions beyond simply shape and color. A final experiment confirmed that additional item exemplars comprised both sub- and superordinate categories. These images may be useful in a variety of settings, particularly for developmental psychology and other research in the language, categorization, perception, visual memory, and related domains.

Geostatistical Borehole Image-Based Mapping of Karst-Carbonate Aquifer Pores.

PubMed

Sukop, Michael C; Cunningham, Kevin J

2016-03-01

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next-generation, high-resolution groundwater flow simulations. Digital, optical, borehole-wall image data from three closely spaced boreholes in the karst-carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two-dimensional models of vuggy megaporosity and matrix-porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple-point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes. © 2015, National Ground Water Association.

The spectrum of genomic signatures: from dinucleotides to chaos game representation.

PubMed

Wang, Yingwei; Hill, Kathleen; Singh, Shiva; Kari, Lila

2005-02-14

In the post genomic era, access to complete genome sequence data for numerous diverse species has opened multiple avenues for examining and comparing primary DNA sequence organization of entire genomes. Previously, the concept of a genomic signature was introduced with the observation of species-type specific Dinucleotide Relative Abundance Profiles (DRAPs); dinucleotides were identified as the subsequences with the greatest bias in representation in a majority of genomes. Herein, we demonstrate that DRAP is one particular genomic signature contained within a broader spectrum of signatures. Within this spectrum, an alternative genomic signature, Chaos Game Representation (CGR), provides a unique visualization of patterns in sequence organization. A genomic signature is associated with a particular integer order or subsequence length that represents a measure of the resolution or granularity in the analysis of primary DNA sequence organization. We quantitatively explore the organizational information provided by genomic signatures of different orders through different distance measures, including a novel Image Distance. The Image Distance and other existing distance measures are evaluated by comparing the phylogenetic trees they generate for 26 complete mitochondrial genomes from a diversity of species. The phylogenetic tree generated by the Image Distance is compatible with the known relatedness of species. Quantitative evaluation of the spectrum of genomic signatures may be used to ultimately gain insight into the determinants and biological relevance of the genome signatures.

Isolation, electron microscopic imaging, and 3-D visualization of native cardiac thin myofilaments.

PubMed

Spiess, M; Steinmetz, M O; Mandinova, A; Wolpensinger, B; Aebi, U; Atar, D

1999-06-15

An increasing number of cardiac diseases are currently pinpointed to reside at the level of the thin myofilaments (e.g., cardiomyopathies, reperfusion injury). Hence the aim of our study was to develop a new method for the isolation of mammalian thin myofilaments suitable for subsequent high-resolution electron microscopic imaging. Native cardiac thin myofilaments were extracted from glycerinated porcine myocardial tissue in the presence of protease inhibitors. Separation of thick and thin myofilaments was achieved by addition of ATP and several centrifugation steps. Negative staining and subsequent conventional and scanning transmission electron microscopy (STEM) of thin myofilaments permitted visualization of molecular details; unlike conventional preparations of thin myofilaments, our method reveals the F-actin moiety and allows direct recognition of thin myofilament-associated porcine cardiac troponin complexes. They appear as "bulges" at regular intervals of approximately 36 nm along the actin filaments. Protein analysis using SDS-polyacrylamide gel electrophoresis revealed that only approximately 20% troponin I was lost during the isolation procedure. In a further step, 3-D helical reconstructions were calculated using STEM dark-field images. These 3-D reconstructions will allow further characterization of molecular details, and they will be useful for directly visualizing molecular alterations related to diseased cardiac thin myofilaments (e.g., reperfusion injury, alterations of Ca2+-mediated tropomyosin switch). Copyright 1999 Academic Press.

A positive SeHCAT test results in fewer subsequent investigations in patients with chronic diarrhoea.

PubMed

Turner, James M; Pattni, Sanjeev S; Appleby, Richard N; Walters, Julian Rf

2017-10-01

Chronic diarrhoea is a common condition, resulting from a number of different disorders. Bile acid diarrhoea, occurring in about a third of these patients, is often undiagnosed. We hypothesised that a positive diagnosis of bile acid diarrhoea would reduce the need for subsequent investigations for alternative diagnoses. Patients previously recruited to a study of chronic diarrhoea who had selenium homocholic acid taurine (SeHCAT) testing and subsequent follow-up at our institution were identified. In a retrospective analysis, the numbers of defined investigations undertaken from the first 3 months after SeHCAT in the following 5 years were compared. 90 patients were identified with primary bile acid diarrhoea (SeHCAT retention <15%, n=36) or idiopathic diarrhoea (SeHCAT retention >15%, n=54). Follow-up had been performed on 29 and 39 subjects, respectively, with no differences in previous investigations or the last contact date. In the follow-up period, the proportions of these patients who had undergone endoscopic procedures (gastroscopy, colonoscopy and sigmoidoscopy) were the same. However, there was a higher proportion of patients in the SeHCAT-negative group who had other investigations, including imaging, physiological tests and blood tests (p=0.037). The use of cross-sectional imaging was significantly higher in this group (p=0.015) with greater proportions having CT (0.44 vs 0.10) and MRI (0.26 vs 0.07). Ultrasound use and the number of blood tests were higher in the SeHCAT-negative group whereas the SeHCAT-positive group attended more clinic appointments (p=0.013). A positive diagnosis of bile acid diarrhoea, made by a SeHCAT test, resulted in reduced use of diagnostic investigations over the subsequent 5 years.

Outcomes of Nonoperative Management of Uncomplicated Appendicitis.

PubMed

Bachur, Richard G; Lipsett, Susan C; Monuteaux, Michael C

2017-07-01

Nonoperative management (NOM) of uncomplicated pediatric appendicitis has promise but remains poorly studied. NOM may lead to an increase in resource utilization. Our objective was to investigate the trends in NOM for uncomplicated appendicitis and study the relevant clinical outcomes including subsequent appendectomy, complications, and resource utilization. Retrospective analysis of administrative data from 45 US pediatric hospitals. Patients <19 years of age presenting to the emergency department (ED) with appendicitis between 2010 and 2016 were studied. NOM was defined by an ED visit for uncomplicated appendicitis treated with antibiotics and the absence of appendectomy at the index encounter. The main outcomes included trends in NOM among children with uncomplicated appendicitis and frequency of subsequent diagnostic imaging, ED visits, hospitalizations, and appendectomy during 12-month follow-up. 99 001 children with appendicitis were identified, with a median age of 10.9 years. Sixty-six percent were diagnosed with nonperforated appendicitis, of which 4190 (6%) were managed nonoperatively. An increasing number of nonoperative cases were observed over 6 years (absolute difference, +20.4%). During the 12-month follow-up period, NOM patients were more likely to have the following: advanced imaging (+8.9% [95% confidence interval (CI) 7.6% to 10.3%]), ED visits (+11.2% [95% CI 9.3% to 13.2%]), and hospitalizations (+43.7% [95% CI 41.7% to 45.8%]). Among patients managed nonoperatively, 46% had a subsequent appendectomy. A significant increase in NOM of nonperforated appendicitis was observed over 6 years. Patients with NOM had more subsequent ED visits and hospitalizations compared with those managed operatively at the index visit. A substantial proportion of patients initially managed nonoperatively eventually had an appendectomy. Copyright © 2017 by the American Academy of Pediatrics.

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

PubMed

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

2011-01-01

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

50 CFR 216.45 - General Authorization for Level B harassment for scientific research.

Code of Federal Regulations, 2013 CFR

2013-10-01

... likely qualify for inclusion under the General Authorization: Photo-identification studies, behavioral..., and the date the image was taken. This statement must accompany the image(s) in all subsequent uses or sales. The annual report must note incidental scientific, educational, or commercial uses of the images...

Photogrammetric Processing Using ZY-3 Satellite Imagery

NASA Astrophysics Data System (ADS)

Kornus, W.; Magariños, A.; Pla, M.; Soler, E.; Perez, F.

2015-03-01

This paper evaluates the stereoscopic capacities of the Chinese sensor ZiYuan-3 (ZY-3) for the generation of photogrammetric products. The satellite was launched on January 9, 2012 and carries three high-resolution panchromatic cameras viewing in forward (22º), nadir (0º) and backward direction (-22º) and an infrared multi-spectral scanner (IRMSS), which is slightly looking forward (6º). The ground sampling distance (GSD) is 2.1m for the nadir image, 3.5m for the two oblique stereo images and 5.8m for the multispectral image. The evaluated ZY-3 imagery consists of a full set of threefold-stereo and a multi-spectral image covering an area of ca. 50km x 50km north-west of Barcelona, Spain. The complete photogrammetric processing chain was executed including image orientation, the generation of a digital surface model (DSM), radiometric image correction, pansharpening, orthoimage generation and digital stereo plotting. All 4 images are oriented by estimating affine transformation parameters between observed and nominal RPC (rational polynomial coefficients) image positions of 17 ground control points (GCP) and a subsequent calculation of refined RPC. From 10 independent check points RMS errors of 2.2m, 2.0m and 2.7m in X, Y and H are obtained. Subsequently, a DSM of 5m grid spacing is generated fully automatically. A comparison with the Lidar data results in an overall DSM accuracy of approximately 3m. In moderate and flat terrain higher accuracies in the order of 2.5m and better are achieved. In a next step orthoimages from the high resolution nadir image and the multispectral image are generated using the refined RPC geometry and the DSM. After radiometric corrections a fused high resolution colour orthoimage with 2.1m pixel size is created using an adaptive HSL method. The pansharpen process is performed after the individual geocorrection due to the different viewing angles between the two images. In a detailed analysis of the colour orthoimage artifacts are detected covering an area of 4691ha, corresponding to less than 2% of the imaged area. Most of the artifacts are caused by clouds (4614ha). A minor part (77ha) is affected by colour patch, stripping or blooming effects. For the final qualitative analysis on the usability of the ZY-3 imagery for stereo plotting purposes stereo combinations of the nadir and an oblique image are discarded, mainly due to the different pixel size, which produces difficulties in the stereoscopic vision and poor accuracy in positioning and measuring. With the two oblique images a level of detail equivalent to 1:25.000 scale is achieved for transport network, hydrography, vegetation and elements to model the terrain as break lines. For settlement, including buildings and other constructions a lower level of detail is achieved equivalent to 1:50.000 scale.

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.

Using Optical Coherence Tomography to Evaluate Skin Sun Damage and Precancer

PubMed Central

Korde, Vrushali R.; Bonnema, Garret T.; Xu, Wei; Krishnamurthy, Chetankumar; Ranger-Moore, James; Saboda, Kathylynn; Slayton, Lisa D.; Salasche, Stuart J.; Warneke, James A.; Alberts, David S.; Barton, Jennifer K.

2008-01-01

Background and Objectives Optical coherence tomography (OCT) is a depth resolved imaging modality that may aid in identifying sun damaged skin and the precancerous condition actinic keratosis (AK). Study Design/Materials and Methods OCT images were acquired of 112 patients at 2 sun protected and 2 sun exposed sites, with a subsequent biopsy. Each site received a dermatological evaluation, a histological diagnosis, and a solar elastosis (SE) score. OCT images were examined visually and statistically analyzed. Results Characteristic OCT image features were identified of sun protected, undiseased, sun damaged, and AK skin. A statistically significant difference (P < 0.0001) between the average attenuation values of skin with minimal and severe solar elastosis was observed. Significant differences (P < 0.0001) were also found between undiseased skin and AK using a gradient analysis. Using image features, AK could be distinguished from undiseased skin with 86% sensitivity and 83% specificity. Conclusion OCT has the potential to guide biopsies and provide non-invasive measures of skin sun damage and disease state, possibly increasing efficiency of chemopreventive agent trials. PMID:17960754

An integrated centrifugo-opto-microfluidic platform for arraying, analysis, identification and manipulation of individual cells.

PubMed

Burger, R; Kurzbuch, D; Gorkin, R; Kijanka, G; Glynn, M; McDonagh, C; Ducrée, J

2015-01-21

In this work we present a centrifugal microfluidic system enabling highly efficient collective trapping and alignment of particles such as microbeads and cells, their multi-colour fluorescent detection and subsequent manipulation by optical tweezers. We demonstrate array-based capture and imaging followed by "cherry-picking" of individual particles, first for fluorescently labelled polystyrene (PS) beads and then for cells. Different cell lines are discriminated based on intracellular as well as surface-based markers.

Multispectral assessment of skin malformations using a modified video-microscope

NASA Astrophysics Data System (ADS)

Bekina, A.; Diebele, I.; Rubins, U.; Zaharans, J.; Derjabo, A.; Spigulis, J.

2012-10-01

A simplified method is proposed for alternative clinical diagnostics of skin malformations. A modified digital microscope, additionally equipped with a fourcolour LED (450 nm, 545 nm, 660 nm and 940 nm) subsequent illumination system, was applied for assessment of skin cancerous lesions and cutaneous inflammations. Multispectral image analysis was performed to map distributions of skin erythema index, bilirubin index, melanoma/nevus differentiation parameter, and fluorescence indicator. The skin malformation monitoring has shown that it is possible to differentiate melanoma from other pathologies.

Compiled visualization with IPI method for analysing of liquid liquid mixing process

NASA Astrophysics Data System (ADS)

Jasikova, Darina; Kotek, Michal; Kysela, Bohus; Sulc, Radek; Kopecky, Vaclav

2018-06-01

The article deals with the research of mixing process using visualization techniques and IPI method. Characteristics of the size distribution and the evolution of two liquid-liquid phase's disintegration were studied. A methodology has been proposed for visualization and image analysis of data acquired during the initial phase of the mixing process. IPI method was used for subsequent detailed study of the disintegrated droplets. The article describes advantages of usage of appropriate method, presents the limits of each method, and compares them.

Stochastic Models for Closed Boundary Analysis: Part I. Representation and Reconstruction.

DTIC Science & Technology

1980-07-01

discussed. In a subsequent paper we will consider the classification problem. C> * School of Electrical Engineering, Purdue University, West Lafayette, IN...1972. 2. T. S. Huang, "Coding of Two Tone Images," TR EE 77-10, School of Elec. Engr., Purdue University, W. Lafeyette, IN 47907. 3. A. Oosterlink, A...Jan. 1977. 5. A. Ambler et al., "A Versatile computer controlled assembly system," Third Intl. Conf. on Art . Intel., 1973, pp. 298-303. 6. C. Rosen

Getting the Bigger Picture With Digital Surveillance

NASA Technical Reports Server (NTRS)

2002-01-01

Through a Space Act Agreement, Diebold, Inc., acquired the exclusive rights to Glenn Research Center's patented video observation technology, originally designed to accelerate video image analysis for various ongoing and future space applications. Diebold implemented the technology into its AccuTrack digital, color video recorder, a state-of- the-art surveillance product that uses motion detection for around-the- clock monitoring. AccuTrack captures digitally signed images and transaction data in real-time. This process replaces the onerous tasks involved in operating a VCR-based surveillance system, and subsequently eliminates the need for central viewing and tape archiving locations altogether. AccuTrack can monitor an entire bank facility, including four automated teller machines, multiple teller lines, and new account areas, all from one central location.

The retinal funduscope demonstration project

NASA Technical Reports Server (NTRS)

Wilhelm, Jim

1994-01-01

A lightweight, relatively inexpensive electronic and photographic instrument has been re-developed for the detection, monitoring, and objective quantification of ocular/ systemic disease or physiological alterations of the retina, blood vessels, or other structures in the anterior and posterior chambers of the eye. The instrument can be operated with little training. It can function with a human or animal subject seated, recumbent, inverted, or in almost any other orientation; and in a hospital, laboratory, field, or other environment. The instrument produces video images that can be viewed directly and/or digitized for simultaneous or subsequent analysis. It can also be equipped to produce photographs and/or fitted with adaptors to produce stereoscopic or magnified images ot the skin, nose, ear, throat, or mouth to detect lesions or diseases.

Differential diagnosis of left ventricular hypertrophy: usefulness of multimodality imaging and tissue characterization with cardiac magnetic resonance.

PubMed

Izgi, Cemil; Vassiliou, Vassilis; Baksi, A John; Prasad, Sanjay K

2016-11-01

Differential diagnosis of asymmetrical left ventricular hypertrophy may be challenging, particularly in patients with history of hypertension. A middle-aged man underwent an echocardiographic examination during workup for hypertension, which unexpectedly showed significant asymmetrical septal hypertrophy and raised suspicion for hypertrophic cardiomyopathy. Cardiovascular magnetic resonance confirmed the asymmetrical hypertrophy. No myocardial late gadolinium contrast enhancement was seen. However, precontrast T1 mapping revealed a low native myocardial T1 value. This was highly suggestive of Anderson-Fabry disease, which was subsequently proved with very low alpha galactosidase enzyme levels and mutation analysis. The case illustrates clinical usefulness of multimodality imaging and the novel tissue characterization techniques for assessment of left ventricular hypertrophy. © 2016, Wiley Periodicals, Inc.

ImagePAD, a Novel Counting Application for the Apple iPad®, Used to Quantify Axons in the Mouse Optic Nerve

PubMed Central

Templeton, Justin P.; Struebing, Felix L.; Lemmon, Andrew; Geisert, Eldon E.

2014-01-01

The present article introduces a new and easy to use counting application for the Apple iPad. The application “ImagePAD” takes advantage of the advanced user interface features offered by the Apple iOS® platform, simplifying the rather tedious task of quantifying features in anatomical studies. For example, the image under analysis can be easily panned and zoomed using iOS-supported multi-touch gestures without losing the spatial context of the counting task, which is extremely important for ensuring count accuracy. This application allows one to quantify up to 5 different types of objects in a single field and output the data in a tab-delimited format for subsequent analysis. We describe two examples of the use of the application: quantifying axons in the optic nerve of the C57BL/6J mouse and determining the percentage of cells labeled with NeuN or ChAT in the retinal ganglion cell layer. For the optic nerve, contiguous images at 60× magnification were taken and transferred onto an Apple iPad®. Axons were counted by tapping on the touch-sensitive screen using ImagePAD. Nine optic nerves were sampled and the number of axons in the nerves ranged from 38872 axons to 50196 axons with an average of 44846 axons per nerve (SD = 3980 axons). PMID:25281829

Removing cosmic spikes using a hyperspectral upper-bound spectrum method

DOE PAGES

Anthony, Stephen Michael; Timlin, Jerilyn A.

2016-11-04

Cosmic ray spikes are especially problematic for hyperspectral imaging because of the large number of spikes often present and their negative effects upon subsequent chemometric analysis. Fortunately, while the large number of spectra acquired in a hyperspectral imaging data set increases the probability and number of cosmic spikes observed, the multitude of spectra can also aid in the effective recognition and removal of the cosmic spikes. Zhang and Ben-Amotz were perhaps the first to leverage the additional spatial dimension of hyperspectral data matrices (DM). They integrated principal component analysis (PCA) into the upper bound spectrum method (UBS), resulting in amore » hybrid method (UBS-DM) for hyperspectral images. Here, we expand upon their use of PCA, recognizing that principal components primarily present in only a few pixels most likely correspond to cosmic spikes. Eliminating the contribution of those principal components in those pixels improves the cosmic spike removal. Both simulated and experimental hyperspectral Raman image data sets are used to test the newly developed UBS-DM-hyperspectral (UBS-DM-HS) method which extends the UBS-DM method by leveraging characteristics of hyperspectral data sets. As a result, a comparison is provided between the performance of the UBS-DM-HS method and other methods suitable for despiking hyperspectral images, evaluating both their ability to remove cosmic ray spikes and the extent to which they introduce spectral bias.« less

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.

Removing cosmic spikes using a hyperspectral upper-bound spectrum method

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

Anthony, Stephen Michael; Timlin, Jerilyn A.

Cosmic ray spikes are especially problematic for hyperspectral imaging because of the large number of spikes often present and their negative effects upon subsequent chemometric analysis. Fortunately, while the large number of spectra acquired in a hyperspectral imaging data set increases the probability and number of cosmic spikes observed, the multitude of spectra can also aid in the effective recognition and removal of the cosmic spikes. Zhang and Ben-Amotz were perhaps the first to leverage the additional spatial dimension of hyperspectral data matrices (DM). They integrated principal component analysis (PCA) into the upper bound spectrum method (UBS), resulting in amore » hybrid method (UBS-DM) for hyperspectral images. Here, we expand upon their use of PCA, recognizing that principal components primarily present in only a few pixels most likely correspond to cosmic spikes. Eliminating the contribution of those principal components in those pixels improves the cosmic spike removal. Both simulated and experimental hyperspectral Raman image data sets are used to test the newly developed UBS-DM-hyperspectral (UBS-DM-HS) method which extends the UBS-DM method by leveraging characteristics of hyperspectral data sets. As a result, a comparison is provided between the performance of the UBS-DM-HS method and other methods suitable for despiking hyperspectral images, evaluating both their ability to remove cosmic ray spikes and the extent to which they introduce spectral bias.« less

Removing Cosmic Spikes Using a Hyperspectral Upper-Bound Spectrum Method.

PubMed

Anthony, Stephen M; Timlin, Jerilyn A

2017-03-01

Cosmic ray spikes are especially problematic for hyperspectral imaging because of the large number of spikes often present and their negative effects upon subsequent chemometric analysis. Fortunately, while the large number of spectra acquired in a hyperspectral imaging data set increases the probability and number of cosmic spikes observed, the multitude of spectra can also aid in the effective recognition and removal of the cosmic spikes. Zhang and Ben-Amotz were perhaps the first to leverage the additional spatial dimension of hyperspectral data matrices (DM). They integrated principal component analysis (PCA) into the upper bound spectrum method (UBS), resulting in a hybrid method (UBS-DM) for hyperspectral images. Here, we expand upon their use of PCA, recognizing that principal components primarily present in only a few pixels most likely correspond to cosmic spikes. Eliminating the contribution of those principal components in those pixels improves the cosmic spike removal. Both simulated and experimental hyperspectral Raman image data sets are used to test the newly developed UBS-DM-hyperspectral (UBS-DM-HS) method which extends the UBS-DM method by leveraging characteristics of hyperspectral data sets. A comparison is provided between the performance of the UBS-DM-HS method and other methods suitable for despiking hyperspectral images, evaluating both their ability to remove cosmic ray spikes and the extent to which they introduce spectral bias.

Global detection approach for clustered microcalcifications in mammograms using a deep learning network.

PubMed

Wang, Juan; Nishikawa, Robert M; Yang, Yongyi

2017-04-01

In computerized detection of clustered microcalcifications (MCs) from mammograms, the traditional approach is to apply a pattern detector to locate the presence of individual MCs, which are subsequently grouped into clusters. Such an approach is often susceptible to the occurrence of false positives (FPs) caused by local image patterns that resemble MCs. We investigate the feasibility of a direct detection approach to determining whether an image region contains clustered MCs or not. Toward this goal, we develop a deep convolutional neural network (CNN) as the classifier model to which the input consists of a large image window ([Formula: see text] in size). The multiple layers in the CNN classifier are trained to automatically extract image features relevant to MCs at different spatial scales. In the experiments, we demonstrated this approach on a dataset consisting of both screen-film mammograms and full-field digital mammograms. We evaluated the detection performance both on classifying image regions of clustered MCs using a receiver operating characteristic (ROC) analysis and on detecting clustered MCs from full mammograms by a free-response receiver operating characteristic analysis. For comparison, we also considered a recently developed MC detector with FP suppression. In classifying image regions of clustered MCs, the CNN classifier achieved 0.971 in the area under the ROC curve, compared to 0.944 for the MC detector. In detecting clustered MCs from full mammograms, at 90% sensitivity, the CNN classifier obtained an FP rate of 0.69 clusters/image, compared to 1.17 clusters/image by the MC detector. These results indicate that using global image features can be more effective in discriminating clustered MCs from FPs caused by various sources, such as linear structures, thereby providing a more accurate detection of clustered MCs on mammograms.

Routine Cross-Sectional Head Imaging Before Electroconvulsive Therapy: A Tertiary Center Experience.

PubMed

Sajedi, Payam I; Mitchell, Jason; Herskovits, Edward H; Raghavan, Prashant

2016-04-01

Electroconvulsive therapy (ECT) is generally contraindicated in patients with intracranial mass lesions or in the presence of increased intracranial pressure. The purpose of this study was to determine the prevalence of incidental abnormalities on routine cross-sectional head imaging, including CT and MRI, that would preclude subsequent ECT. This retrospective study involved a review of the electronic medical records of 105 patients (totaling 108 imaging studies) between April 27, 2007, and March 20, 2015, referred for cranial CT or MRI with the primary indication of pre-ECT evaluation. The probability of occurrence of imaging findings that would preclude ECT was computed. A cost analysis was also performed on the practice of routine pre-ECT imaging. Of the 105 patients who presented with the primary indication of ECT clearance (totaling 108 scans), 1 scan (0.93%) revealed findings that precluded ECT. None of the studies demonstrated findings that indicated increased intracranial pressure. A cost analysis revealed that at least $18,662.70 and 521.97 relative value units must be expended to identify one patient with intracranial pathology precluding ECT. The findings of this study demonstrate an extremely low prevalence of findings that preclude ECT on routine cross-sectional head imaging. The costs incurred in identifying a potential contraindication are high. The authors suggest that the performance of pre-ECT neuroimaging be driven by the clinical examination. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Connectomic correlates of response to treatment in first-episode psychosis

PubMed Central

Crossley, Nicolas A; Marques, Tiago Reis; Taylor, Heather; Chaddock, Chris; Dell’Acqua, Flavio; Reinders, Antje A T S; Mondelli, Valeria; DiForti, Marta; Simmons, Andrew; David, Anthony S; Kapur, Shitij; Pariante, Carmine M; Murray, Robin M; Dazzan, Paola

2017-01-01

Abstract Connectomic approaches using diffusion tensor imaging have contributed to our understanding of brain changes in psychosis, and could provide further insights into the neural mechanisms underlying response to antipsychotic treatment. We here studied the brain network organization in patients at their first episode of psychosis, evaluating whether connectome-based descriptions of brain networks predict response to treatment, and whether they change after treatment. Seventy-six patients with a first episode of psychosis and 74 healthy controls were included. Thirty-three patients were classified as responders after 12 weeks of antipsychotic treatment. Baseline brain structural networks were built using whole-brain diffusion tensor imaging tractography, and analysed using graph analysis and network-based statistics to explore baseline characteristics of patients who subsequently responded to treatment. A subgroup of 43 patients was rescanned at the 12-week follow-up, to study connectomic changes over time in relation to treatment response. At baseline, those subjects who subsequently responded to treatment, compared to those that did not, showed higher global efficiency in their structural connectomes, a network configuration that theoretically facilitates the flow of information. We did not find specific connectomic changes related to treatment response after 12 weeks of treatment. Our data suggest that patients who have an efficiently-wired connectome at first onset of psychosis show a better subsequent response to antipsychotics. However, response is not accompanied by specific structural changes over time detectable with this method. PMID:28007987

Computer-aided analysis for the Mechanics of Granular Materials (MGM) experiment

NASA Technical Reports Server (NTRS)

Parker, Joey K.

1986-01-01

The Mechanics of Granular Materials (MGM) program is planned to provide experimental determinations of the mechanics of granular materials under very low gravity conditions. The initial experiments will use small glass beads as the granular material, and a precise tracking of individual beads during the test is desired. Real-time video images of the experimental specimen were taken with a television camera, and subsequently digitized by a frame grabber installed in a microcomputer. Easily identified red tracer beads were randomly scattered throughout the test specimen. A set of Pascal programs was written for processing and analyzing the digitized images. Filtering the image with Laplacian, dilation, and blurring filters when using a threshold function produced a binary (black on white) image which clearly identified the red beads. The centroids and areas for each bead were then determined. Analyzing a series of the images determined individual red bead displacements throughout the experiment. The system can provide displacement accuracies on the order of 0.5 to 1 pixel is the image is taken directly from the video camera. Digitizing an image from a video cassette recorder introduces an additional repeatability error of 0.5 to 1 pixel. Other programs were written to provide hardcopy prints of the digitized images on a dot-matrix printer.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy.

PubMed

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R; Tulchin-Francis, Kirsten; Shierk, Angela; Roberts, Heather; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2014-10-01

Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy

PubMed Central

Hervey, Nathan; Khan, Bilal; Shagman, Laura; Tian, Fenghua; Delgado, Mauricio R.; Tulchin-Francis, Kirsten; Shierk, Angela; Roberts, Heather; Smith, Linsley; Reid, Dahlia; Clegg, Nancy J.; Liu, Hanli; MacFarlane, Duncan; Alexandrakis, George

2014-01-01

Abstract. Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images. PMID:26157980

Validation of DWI pre-processing procedures for reliable differentiation between human brain gliomas.

PubMed

Vellmer, Sebastian; Tonoyan, Aram S; Suter, Dieter; Pronin, Igor N; Maximov, Ivan I

2018-02-01

Diffusion magnetic resonance imaging (dMRI) is a powerful tool in clinical applications, in particular, in oncology screening. dMRI demonstrated its benefit and efficiency in the localisation and detection of different types of human brain tumours. Clinical dMRI data suffer from multiple artefacts such as motion and eddy-current distortions, contamination by noise, outliers etc. In order to increase the image quality of the derived diffusion scalar metrics and the accuracy of the subsequent data analysis, various pre-processing approaches are actively developed and used. In the present work we assess the effect of different pre-processing procedures such as a noise correction, different smoothing algorithms and spatial interpolation of raw diffusion data, with respect to the accuracy of brain glioma differentiation. As a set of sensitive biomarkers of the glioma malignancy grades we chose the derived scalar metrics from diffusion and kurtosis tensor imaging as well as the neurite orientation dispersion and density imaging (NODDI) biophysical model. Our results show that the application of noise correction, anisotropic diffusion filtering, and cubic-order spline interpolation resulted in the highest sensitivity and specificity for glioma malignancy grading. Thus, these pre-processing steps are recommended for the statistical analysis in brain tumour studies. Copyright © 2017. Published by Elsevier GmbH.

A morphing-based scheme for large deformation analysis with stereo-DIC

NASA Astrophysics Data System (ADS)

Genovese, Katia; Sorgente, Donato

2018-05-01

A key step in the DIC-based image registration process is the definition of the initial guess for the non-linear optimization routine aimed at finding the parameters describing the pixel subset transformation. This initialization may result very challenging and possibly fail when dealing with pairs of largely deformed images such those obtained from two angled-views of not-flat objects or from the temporal undersampling of rapidly evolving phenomena. To address this problem, we developed a procedure that generates a sequence of intermediate synthetic images for gradually tracking the pixel subset transformation between the two extreme configurations. To this scope, a proper image warping function is defined over the entire image domain through the adoption of a robust feature-based algorithm followed by a NURBS-based interpolation scheme. This allows a fast and reliable estimation of the initial guess of the deformation parameters for the subsequent refinement stage of the DIC analysis. The proposed method is described step-by-step by illustrating the measurement of the large and heterogeneous deformation of a circular silicone membrane undergoing axisymmetric indentation. A comparative analysis of the results is carried out by taking as a benchmark a standard reference-updating approach. Finally, the morphing scheme is extended to the most general case of the correspondence search between two largely deformed textured 3D geometries. The feasibility of this latter approach is demonstrated on a very challenging case: the full-surface measurement of the severe deformation (> 150% strain) suffered by an aluminum sheet blank subjected to a pneumatic bulge test.

Profiling and Imaging Ion Mobility-Mass Spectrometry Analysis of Cholesterol and 7-Dehydrocholesterol in Cells Via Sputtered Silver MALDI

PubMed Central

Xu, Libin; Kliman, Michal; Forsythe, Jay G.; Korade, Zeljka; Hmelo, Anthony B.; Porter, Ned A.; McLean, John A.

2015-01-01

Profiling and imaging of cholesterol and its precursors by mass spectrometry (MS) are important in a number of cholesterol biosynthesis disorders, such as in Smith-Lemli-Opitz syndrome (SLOS), where 7-dehydrocholesterol (7-DHC) is accumulated in affected individuals. SLOS is caused by defects in the enzyme that reduces 7-DHC to cholesterol. However, analysis of sterols is challenging because these hydrophobic olefins are difficult to ionize for MS detection. We report here sputtered silver matrix-assisted laser desorption/ionization (MALDI)-ion mobility-MS (IM-MS) analysis of cholesterol and 7-DHC. In comparison with liquid-based AgNO3 and colloidal Ag nanoparticle (AgNP), sputtered silver NP (10–25 nm) provided the lowest limits-of-detection based on the silver coordinated [cholesterol+Ag]+ and [7-DHC+Ag]+ signals while minimizing dehydrogenation products ([M+Ag-2H]+). When analyzing human fibroblasts that were directly grown on poly-L-lysine-coated ITO glass plates with this technique, in situ, the 7-DHC/cholesterol ratios for both control and SLOS human fibroblasts are readily obtained. The m/z of 491 (specific for [7-DHC+107Ag]+) and 495 (specific for [cholesterol+109Ag]+) were subsequently imaged using MALDI-IM-MS. MS images were co-registered with optical images of the cells for metabolic ratio determination. From these comparisons, ratios of 7-DHC/cholesterol for SLOS human fibroblasts are distinctly higher than in control human fibroblasts. Thus, this strategy demonstrates the utility for diagnosing/assaying the severity of cholesterol biosynthesis disorders in vitro. PMID:25822928

Deep Learning in Gastrointestinal Endoscopy.

PubMed

Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

2016-01-01

Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

Estimation of the stand ages of tropical secondary forests after shifting cultivation based on the combination of WorldView-2 and time-series Landsat images

NASA Astrophysics Data System (ADS)

Fujiki, Shogoro; Okada, Kei-ichi; Nishio, Shogo; Kitayama, Kanehiro

2016-09-01

We developed a new method to estimate stand ages of secondary vegetation in the Bornean montane zone, where local people conduct traditional shifting cultivation and protected areas are surrounded by patches of recovering secondary vegetation of various ages. Identifying stand ages at the landscape level is critical to improve conservation policies. We combined a high-resolution satellite image (WorldView-2) with time-series Landsat images. We extracted stand ages (the time elapsed since the most recent slash and burn) from a change-detection analysis with Landsat time-series images and superimposed the derived stand ages on the segments classified by object-based image analysis using WorldView-2. We regarded stand ages as a response variable, and object-based metrics as independent variables, to develop regression models that explain stand ages. Subsequently, we classified the vegetation of the target area into six age units and one rubber plantation unit (1-3 yr, 3-5 yr, 5-7 yr, 7-30 yr, 30-50 yr, >50 yr and 'rubber plantation') using regression models and linear discriminant analyses. Validation demonstrated an accuracy of 84.3%. Our approach is particularly effective in classifying highly dynamic pioneer vegetation younger than 7 years into 2-yr intervals, suggesting that rapid changes in vegetation canopies can be detected with high accuracy. The combination of a spectral time-series analysis and object-based metrics based on high-resolution imagery enabled the classification of dynamic vegetation under intensive shifting cultivation and yielded an informative land cover map based on stand ages.

Profiling and Imaging Ion Mobility-Mass Spectrometry Analysis of Cholesterol and 7-Dehydrocholesterol in Cells Via Sputtered Silver MALDI

NASA Astrophysics Data System (ADS)

Xu, Libin; Kliman, Michal; Forsythe, Jay G.; Korade, Zeljka; Hmelo, Anthony B.; Porter, Ned A.; McLean, John A.

2015-06-01

Profiling and imaging of cholesterol and its precursors by mass spectrometry (MS) are important in a number of cholesterol biosynthesis disorders, such as in Smith-Lemli-Opitz syndrome (SLOS), where 7-dehydrocholesterol (7-DHC) is accumulated in affected individuals. SLOS is caused by defects in the enzyme that reduces 7-DHC to cholesterol. However, analysis of sterols is challenging because these hydrophobic olefins are difficult to ionize for MS detection. We report here sputtered silver matrix-assisted laser desorption/ionization (MALDI)-ion mobility-MS (IM-MS) analysis of cholesterol and 7-DHC. In comparison with liquid-based AgNO3 and colloidal Ag nanoparticle (AgNP), sputtered silver NP (10-25 nm) provided the lowest limits-of-detection based on the silver coordinated [cholesterol + Ag]+ and [7-DHC + Ag]+ signals while minimizing dehydrogenation products ([M + Ag-2H]+). When analyzing human fibroblasts that were directly grown on poly-L-lysine-coated ITO glass plates with this technique, in situ, the 7-DHC/cholesterol ratios for both control and SLOS human fibroblasts are readily obtained. The m/z of 491 (specific for [7-DHC + 107Ag]+) and 495 (specific for [cholesterol + 109Ag]+) were subsequently imaged using MALDI-IM-MS. MS images were co-registered with optical images of the cells for metabolic ratio determination. From these comparisons, ratios of 7-DHC/cholesterol for SLOS human fibroblasts are distinctly higher than in control human fibroblasts. Thus, this strategy demonstrates the utility for diagnosing/assaying the severity of cholesterol biosynthesis disorders in vitro.

Confocal Raman imaging and chemometrics applied to solve forensic document examination involving crossed lines and obliteration cases by a depth profiling study.

PubMed

Borba, Flávia de Souza Lins; Jawhari, Tariq; Saldanha Honorato, Ricardo; de Juan, Anna

2017-03-27

This article describes a non-destructive analytical method developed to solve forensic document examination problems involving crossed lines and obliteration. Different strategies combining confocal Raman imaging and multivariate curve resolution-alternating least squares (MCR-ALS) are presented. Multilayer images were acquired at subsequent depth layers into the samples. It is the first time that MCR-ALS is applied to multilayer images for forensic purposes. In this context, this method provides a single set of pure spectral ink signatures and related distribution maps for all layers examined from the sole information in the raw measurement. Four cases were investigated, namely, two concerning crossed lines with different degrees of ink similarity and two related to obliteration, where previous or no knowledge about the identity of the obliterated ink was available. In the crossing line scenario, MCR-ALS analysis revealed the ink nature and the chronological order in which strokes were drawn. For obliteration cases, results making active use of information about the identity of the obliterated ink in the chemometric analysis were of similar quality as those where the identity of the obliterated ink was unknown. In all obliteration scenarios, the identity of inks and the obliterated text were satisfactorily recovered. The analytical methodology proposed is of general use for analytical forensic document examination problems, and considers different degrees of complexity and prior available information. Besides, the strategies of data analysis proposed can be applicable to any other kind of problem in which multilayer Raman images from multicomponent systems have to be interpreted.

Analysis and classification of optical tomographic images of rheumatoid fingers with ANOVA and discriminate analysis

NASA Astrophysics Data System (ADS)

Montejo, Ludguier D.; Kim, Hyun K.; Häme, Yrjö; Jia, Jingfei; Montejo, Julio D.; Netz, Uwe J.; Blaschke, Sabine; Zwaka, Paul; Müeller, Gerhard A.; Beuthan, Jürgen; Hielscher, Andreas H.

2011-03-01

We present a study on the effectiveness of computer-aided diagnosis (CAD) of rheumatoid arthritis (RA) from frequency-domain diffuse optical tomographic (FDOT) images. FDOT is used to obtain the distribution of tissue optical properties. Subsequently, the non-parametric Kruskal-Wallis ANOVA test is employed to verify statistically significant differences between the optical parameters of patients affected by RA and healthy volunteers. Furthermore, quadratic discriminate analysis (QDA) of the absorption (μa) and scattering (μa or μ's) distributions is used to classify subjects as affected or not affected by RA. We evaluate the classification efficiency by determining the sensitivity (Se), specificity (Sp), and the Youden index (Y). We find that combining features extracted from μa and μa or μ's images allows for more accurate classification than when μa or μa or μ's features are considered individually on their own. Combining μa and μa or μ's features yields values of up to Y = 0.75 (Se = 0.84 and Sp = 0.91). The best results when μa or μ's features are considered individually are Y = 0.65 (Se = 0.85 and Sp = 0.80) and Y = 0.70 (Se = 0.80 and Sp = 0.90), respectively.

Technical Advance: Live-imaging analysis of human dendritic cell migrating behavior under the influence of immune-stimulating reagents in an organotypic model of lung

PubMed Central

Nguyen Hoang, Anh Thu; Chen, Puran; Björnfot, Sofia; Högstrand, Kari; Lock, John G.; Grandien, Alf; Coles, Mark; Svensson, Mattias

2014-01-01

This manuscript describes technical advances allowing manipulation and quantitative analyses of human DC migratory behavior in lung epithelial tissue. DCs are hematopoietic cells essential for the maintenance of tissue homeostasis and the induction of tissue-specific immune responses. Important functions include cytokine production and migration in response to infection for the induction of proper immune responses. To design appropriate strategies to exploit human DC functional properties in lung tissue for the purpose of clinical evaluation, e.g., candidate vaccination and immunotherapy strategies, we have developed a live-imaging assay based on our previously described organotypic model of the human lung. This assay allows provocations and subsequent quantitative investigations of DC functional properties under conditions mimicking morphological and functional features of the in vivo parental tissue. We present protocols to set up and prepare tissue models for 4D (x, y, z, time) fluorescence-imaging analysis that allow spatial and temporal studies of human DCs in live epithelial tissue, followed by flow cytometry analysis of DCs retrieved from digested tissue models. This model system can be useful for elucidating incompletely defined pathways controlling DC functional responses to infection and inflammation in lung epithelial tissue, as well as the efficacy of locally administered candidate interventions. PMID:24899587

Automatic detection of the macula in retinal fundus images using seeded mode tracking approach.

PubMed

Wong, Damon W K; Liu, Jiang; Tan, Ngan-Meng; Yin, Fengshou; Cheng, Xiangang; Cheng, Ching-Yu; Cheung, Gemmy C M; Wong, Tien Yin

2012-01-01

The macula is the part of the eye responsible for central high acuity vision. Detection of the macula is an important task in retinal image processing as a landmark for subsequent disease assessment, such as for age-related macula degeneration. In this paper, we have presented an approach to automatically determine the macula centre in retinal fundus images. First contextual information on the image is combined with a statistical model to obtain an approximate macula region of interest localization. Subsequently, we propose the use of a seeded mode tracking technique to locate the macula centre. The proposed approach is tested on a large dataset composed of 482 normal images and 162 glaucoma images from the ORIGA database and an additional 96 AMD images. The results show a ROI detection of 97.5%, and 90.5% correct detection of the macula within 1/3DD from a manual reference, which outperforms other current methods. The results are promising for the use of the proposed approach to locate the macula for the detection of macula diseases from retinal images.

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2004-01-01

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

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

PubMed

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

2015-05-08

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

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

PubMed Central

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

2015-01-01

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

Image-based spectroscopy for environmental monitoring

NASA Astrophysics Data System (ADS)

Bachmakov, Eduard; Molina, Carolyn; Wynne, Rosalind

2014-03-01

An image-processing algorithm for use with a nano-featured spectrometer chemical agent detection configuration is presented. The spectrometer chip acquired from Nano-Optic DevicesTM can reduce the size of the spectrometer down to a coin. The nanospectrometer chip was aligned with a 635nm laser source, objective lenses, and a CCD camera. The images from a nanospectrometer chip were collected and compared to reference spectra. Random background noise contributions were isolated and removed from the diffraction pattern image analysis via a threshold filter. Results are provided for the image-based detection of the diffraction pattern produced by the nanospectrometer. The featured PCF spectrometer has the potential to measure optical absorption spectra in order to detect trace amounts of contaminants. MATLAB tools allow for implementation of intelligent, automatic detection of the relevant sub-patterns in the diffraction patterns and subsequent extraction of the parameters using region-detection algorithms such as the generalized Hough transform, which detects specific shapes within the image. This transform is a method for detecting curves by exploiting the duality between points on a curve and parameters of that curve. By employing this imageprocessing technique, future sensor systems will benefit from new applications such as unsupervised environmental monitoring of air or water quality.

Power spectrum weighted edge analysis for straight edge detection in images

NASA Astrophysics Data System (ADS)

Karvir, Hrishikesh V.; Skipper, Julie A.

2007-04-01

Most man-made objects provide characteristic straight line edges and, therefore, edge extraction is a commonly used target detection tool. However, noisy images often yield broken edges that lead to missed detections, and extraneous edges that may contribute to false target detections. We present a sliding-block approach for target detection using weighted power spectral analysis. In general, straight line edges appearing at a given frequency are represented as a peak in the Fourier domain at a radius corresponding to that frequency, and a direction corresponding to the orientation of the edges in the spatial domain. Knowing the edge width and spacing between the edges, a band-pass filter is designed to extract the Fourier peaks corresponding to the target edges and suppress image noise. These peaks are then detected by amplitude thresholding. The frequency band width and the subsequent spatial filter mask size are variable parameters to facilitate detection of target objects of different sizes under known imaging geometries. Many military objects, such as trucks, tanks and missile launchers, produce definite signatures with parallel lines and the algorithm proves to be ideal for detecting such objects. Moreover, shadow-casting objects generally provide sharp edges and are readily detected. The block operation procedure offers advantages of significant reduction in noise influence, improved edge detection, faster processing speed and versatility to detect diverse objects of different sizes in the image. With Scud missile launcher replicas as target objects, the method has been successfully tested on terrain board test images under different backgrounds, illumination and imaging geometries with cameras of differing spatial resolution and bit-depth.

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.

Survey of contemporary trends in color image segmentation

NASA Astrophysics Data System (ADS)

Vantaram, Sreenath Rao; Saber, Eli

2012-10-01

In recent years, the acquisition of image and video information for processing, analysis, understanding, and exploitation of the underlying content in various applications, ranging from remote sensing to biomedical imaging, has grown at an unprecedented rate. Analysis by human observers is quite laborious, tiresome, and time consuming, if not infeasible, given the large and continuously rising volume of data. Hence the need for systems capable of automatically and effectively analyzing the aforementioned imagery for a variety of uses that span the spectrum from homeland security to elderly care. In order to achieve the above, tools such as image segmentation provide the appropriate foundation for expediting and improving the effectiveness of subsequent high-level tasks by providing a condensed and pertinent representation of image information. We provide a comprehensive survey of color image segmentation strategies adopted over the last decade, though notable contributions in the gray scale domain will also be discussed. Our taxonomy of segmentation techniques is sampled from a wide spectrum of spatially blind (or feature-based) approaches such as clustering and histogram thresholding as well as spatially guided (or spatial domain-based) methods such as region growing/splitting/merging, energy-driven parametric/geometric active contours, supervised/unsupervised graph cuts, and watersheds, to name a few. In addition, qualitative and quantitative results of prominent algorithms on several images from the Berkeley segmentation dataset are shown in order to furnish a fair indication of the current quality of the state of the art. Finally, we provide a brief discussion on our current perspective of the field as well as its associated future trends.

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images.

PubMed

Korbar, Bruno; Olofson, Andrea M; Miraflor, Allen P; Nicka, Catherine M; Suriawinata, Matthew A; Torresani, Lorenzo; Suriawinata, Arief A; Hassanpour, Saeed

2017-01-01

Histopathological characterization of colorectal polyps is critical for determining the risk of colorectal cancer and future rates of surveillance for patients. However, this characterization is a challenging task and suffers from significant inter- and intra-observer variability. We built an automatic image analysis method that can accurately classify different types of colorectal polyps on whole-slide images to help pathologists with this characterization and diagnosis. Our method is based on deep-learning techniques, which rely on numerous levels of abstraction for data representation and have shown state-of-the-art results for various image analysis tasks. Our method covers five common types of polyps (i.e., hyperplastic, sessile serrated, traditional serrated, tubular, and tubulovillous/villous) that are included in the US Multisociety Task Force guidelines for colorectal cancer risk assessment and surveillance. We developed multiple deep-learning approaches by leveraging a dataset of 2074 crop images, which were annotated by multiple domain expert pathologists as reference standards. We evaluated our method on an independent test set of 239 whole-slide images and measured standard machine-learning evaluation metrics of accuracy, precision, recall, and F1 score and their 95% confidence intervals. Our evaluation shows that our method with residual network architecture achieves the best performance for classification of colorectal polyps on whole-slide images (overall accuracy: 93.0%, 95% confidence interval: 89.0%-95.9%). Our method can reduce the cognitive burden on pathologists and improve their efficacy in histopathological characterization of colorectal polyps and in subsequent risk assessment and follow-up recommendations.

Semi-quantitative methods yield greater inter- and intraobserver agreement than subjective methods for interpreting 99m technetium-hydroxymethylene-diphosphonate uptake in equine thoracic processi spinosi.

PubMed

van Zadelhoff, Claudia; Ehrle, Anna; Merle, Roswitha; Jahn, Werner; Lischer, Christoph

2018-05-09

Scintigraphy is a standard diagnostic method for evaluating horses with back pain due to suspected thoracic processus spinosus pathology. Lesion detection is based on subjective or semi-quantitative assessments of increased uptake. This retrospective, analytical study is aimed to compare semi-quantitative and subjective methods in the evaluation of scintigraphic images of the processi spinosi in the equine thoracic spine. Scintigraphic images of 20 Warmblood horses, presented for assessment of orthopedic conditions between 2014 and 2016, were included in the study. Randomized, blinded image evaluation was performed by 11 veterinarians using subjective and semi-quantitative methods. Subjective grading was performed for the analysis of red-green-blue and grayscale scintigraphic images, which were presented in full-size or as masked images. For the semi-quantitative assessment, observers placed regions of interest over each processus spinosus. The uptake ratio of each processus spinosus in comparison to a reference region of interest was determined. Subsequently, a modified semi-quantitative calculation was developed whereby only the highest counts-per-pixel for a specified number of pixels was processed. Inter- and intraobserver agreement was calculated using intraclass correlation coefficients. Inter- and intraobserver intraclass correlation coefficients were 41.65% and 71.39%, respectively, for the subjective image assessment. Additionally, a correlation between intraobserver agreement, experience, and grayscale images was identified. The inter- and intraobserver agreement was significantly increased when using semi-quantitative analysis (97.35% and 98.36%, respectively) or the modified semi-quantitative calculation (98.61% and 98.82%, respectively). The proposed modified semi-quantitative technique showed a higher inter- and intraobserver agreement when compared to other methods, which makes it a useful tool for the analysis of scintigraphic images. The association of the findings from this study with clinical and radiological examinations requires further investigation. © 2018 American College of Veterinary Radiology.

Association between pathology and texture features of multi parametric MRI of the prostate

NASA Astrophysics Data System (ADS)

Kuess, Peter; Andrzejewski, Piotr; Nilsson, David; Georg, Petra; Knoth, Johannes; Susani, Martin; Trygg, Johan; Helbich, Thomas H.; Polanec, Stephan H.; Georg, Dietmar; Nyholm, Tufve

2017-10-01

The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.

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

Zawisza, I; Yan, H; Yin, F

Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogatemore » signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction algorithm is effective in estimating surrogate motion multiple-steps in advance. Relative-weighting method shows better prediction accuracy than equal-weighting method. More parameters of this algorithm are under investigation.« less

Atom Probe Analysis of Ex Situ Gas-Charged Stable Hydrides.

PubMed

Haley, Daniel; Bagot, Paul A J; Moody, Michael P

2017-04-01

In this work, we report on the atom probe tomography analysis of two metallic hydrides formed by pressurized charging using an ex situ hydrogen charging cell, in the pressure range of 200-500 kPa (2-5 bar). Specifically we report on the deuterium charging of Pd/Rh and V systems. Using this ex situ system, we demonstrate the successful loading and subsequent atom probe analysis of deuterium within a Pd/Rh alloy, and demonstrate that deuterium is likely present within the oxide-metal interface of a native oxide formed on vanadium. Through these experiments, we demonstrate the feasibility of ex situ hydrogen analysis for hydrides via atom probe tomography, and thus a practical route to three-dimensional imaging of hydrogen in hydrides at the atomic scale.

Quantitative analysis on collagen of dermatofibrosarcoma protuberans skin by second harmonic generation microscopy.

PubMed

Wu, Shulian; Huang, Yudian; Li, Hui; Wang, Yunxia; Zhang, Xiaoman

2015-01-01

Dermatofibrosarcoma protuberans (DFSP) is a skin cancer usually mistaken as other benign tumors. Abnormal DFSP resection results in tumor recurrence. Quantitative characterization of collagen alteration on the skin tumor is essential for developing a diagnostic technique. In this study, second harmonic generation (SHG) microscopy was performed to obtain images of the human DFSP skin and normal skin. Subsequently, structure and texture analysis methods were applied to determine the differences in skin texture characteristics between the two skin types, and the link between collagen alteration and tumor was established. Results suggest that combining SHG microscopy and texture analysis methods is a feasible and effective method to describe the characteristics of skin tumor like DFSP. © Wiley Periodicals, Inc.

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.

Improved and Robust Detection of Cell Nuclei from Four Dimensional Fluorescence Images

PubMed Central

Bashar, Md. Khayrul; Yamagata, Kazuo; Kobayashi, Tetsuya J.

2014-01-01

Segmentation-free direct methods are quite efficient for automated nuclei extraction from high dimensional images. A few such methods do exist but most of them do not ensure algorithmic robustness to parameter and noise variations. In this research, we propose a method based on multiscale adaptive filtering for efficient and robust detection of nuclei centroids from four dimensional (4D) fluorescence images. A temporal feedback mechanism is employed between the enhancement and the initial detection steps of a typical direct method. We estimate the minimum and maximum nuclei diameters from the previous frame and feed back them as filter lengths for multiscale enhancement of the current frame. A radial intensity-gradient function is optimized at positions of initial centroids to estimate all nuclei diameters. This procedure continues for processing subsequent images in the sequence. Above mechanism thus ensures proper enhancement by automated estimation of major parameters. This brings robustness and safeguards the system against additive noises and effects from wrong parameters. Later, the method and its single-scale variant are simplified for further reduction of parameters. The proposed method is then extended for nuclei volume segmentation. The same optimization technique is applied to final centroid positions of the enhanced image and the estimated diameters are projected onto the binary candidate regions to segment nuclei volumes.Our method is finally integrated with a simple sequential tracking approach to establish nuclear trajectories in the 4D space. Experimental evaluations with five image-sequences (each having 271 3D sequential images) corresponding to five different mouse embryos show promising performances of our methods in terms of nuclear detection, segmentation, and tracking. A detail analysis with a sub-sequence of 101 3D images from an embryo reveals that the proposed method can improve the nuclei detection accuracy by 9 over the previous methods, which used inappropriate large valued parameters. Results also confirm that the proposed method and its variants achieve high detection accuracies ( 98 mean F-measure) irrespective of the large variations of filter parameters and noise levels. PMID:25020042

SDL: Saliency-Based Dictionary Learning Framework for Image Similarity.

PubMed

Sarkar, Rituparna; Acton, Scott T

2018-02-01

In image classification, obtaining adequate data to learn a robust classifier has often proven to be difficult in several scenarios. Classification of histological tissue images for health care analysis is a notable application in this context due to the necessity of surgery, biopsy or autopsy. To adequately exploit limited training data in classification, we propose a saliency guided dictionary learning method and subsequently an image similarity technique for histo-pathological image classification. Salient object detection from images aids in the identification of discriminative image features. We leverage the saliency values for the local image regions to learn a dictionary and respective sparse codes for an image, such that the more salient features are reconstructed with smaller error. The dictionary learned from an image gives a compact representation of the image itself and is capable of representing images with similar content, with comparable sparse codes. We employ this idea to design a similarity measure between a pair of images, where local image features of one image, are encoded with the dictionary learned from the other and vice versa. To effectively utilize the learned dictionary, we take into account the contribution of each dictionary atom in the sparse codes to generate a global image representation for image comparison. The efficacy of the proposed method was evaluated using three tissue data sets that consist of mammalian kidney, lung and spleen tissue, breast cancer, and colon cancer tissue images. From the experiments, we observe that our methods outperform the state of the art with an increase of 14.2% in the average classification accuracy over all data sets.

Multimodality and nanoparticles in medical imaging

PubMed Central

Huang, Wen-Yen; Davis, Jason J.

2015-01-01

A number of medical imaging techniques are used heavily in the provision of spatially resolved information on disease and physiological status and accordingly play a critical role in clinical diagnostics and subsequent treatment. Though, for most imaging modes, contrast is potentially enhanced through the use of contrast agents or improved hardware or imaging protocols, no single methodology provides, in isolation, a detailed mapping of anatomy, disease markers or physiological status. In recent years, the concept of complementing the strengths of one imaging modality with those of another has come to the fore and been further bolstered by the development of fused instruments such as PET/CT and PET/MRI stations. Coupled with the continual development in imaging hardware has been a surge in reports of contrast agents bearing multiple functionality, potentially providing not only a powerful and highly sensitised means of co-localising physiological/disease status and anatomy, but also the tracking and delineation of multiple markers and indeed subsequent or simultaneous highly localized therapy (“theragnostics”). PMID:21409202

Diagnosis of vulnerable atherosclerotic plaques by time-resolved fluorescence spectroscopy and ultrasound imaging.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Beseth, B; Dorafshar, A H; Reil, T; Baker, D; Freischlag, J; Shung, K K; Sun, L; Marcu, L

2006-01-01

In this study, time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) and ultrasonography were applied to detect vulnerable (high-risk) atherosclerotic plaque. A total of 813 TR-LIFS measurements were taken from carotid plaques of 65 patients, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified by histopathology as thin, fibrotic, calcified, low-inflamed, inflamed and necrotic lesions. Spectral and time-resolved parameters (normalized intensity values and Laguerre expansion coefficients) were extracted from the TR-LIFS data. Feature selection for classification was performed by either analysis of variance (ANOVA) or principal component analysis (PCA). A stepwise linear discriminant analysis algorithm was developed for detecting inflamed and necrotic lesion, representing the most vulnerable plaques. These vulnerable plaques were detected with high sensitivity (>80%) and specificity (>90%). Ultrasound (US) imaging was obtained in 4 carotid plaques in addition to TR-LIFS examination. Preliminary results indicate that US provides important structural information of the plaques that could be combined with the compositional information obtained by TR-LIFS, to obtain a more accurate diagnosis of vulnerable atherosclerotic plaque.

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation.

PubMed

Kang, Sung-Won; Lee, Woo-Jin; Choi, Soon-Chul; Lee, Sam-Sun; Heo, Min-Suk; Huh, Kyung-Hoe; Kim, Tae-Il; Yi, Won-Jin

2015-03-01

We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method.

Multiparametric Analysis of the Tumor Microenvironment: Hypoxia Markers and Beyond.

PubMed

Mayer, Arnulf; Vaupel, Peter

2017-01-01

We have established a novel in situ protein analysis pipeline, which is built upon highly sensitive, multichannel immunofluorescent staining of paraffin sections of human and xenografted tumor tissue. Specimens are digitized using slide scanners equipped with suitable light sources and fluorescence filter combinations. Resulting digital images are subsequently subjected to quantitative image analysis using a primarily object-based approach, which comprises segmentation of single cells or higher-order structures (e.g., blood vessels), cell shape approximation, measurement of signal intensities in individual fluorescent channels and correlation of these data with positional information for each object. Our approach could be particularly useful for the study of the hypoxic tumor microenvironment as it can be utilized to systematically explore the influence of spatial factors on cell phenotypes, e.g., the distance of a given cell type from the nearest blood vessel on the cellular expression of hypoxia-associated biomarkers and other proteins reflecting their specific state of activation or function. In this report, we outline the basic methodology and provide an outlook on possible use cases.

Quantitative histogram analysis of images

NASA Astrophysics Data System (ADS)

Holub, Oliver; Ferreira, Sérgio T.

2006-11-01

A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for loading of an image No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No of lines in distributed program, including test data, etc.:138 946 No. of bytes in distributed program, including test data, etc.:15 166 675 Distribution format: tar.gz Nature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user. Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels. Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis) Typical running time: Seconds (depending on image size and processor speed) Unusual features of the program: None

Fully-automated, high-throughput micro-computed tomography analysis of body composition enables therapeutic efficacy monitoring in preclinical models.

PubMed

Wyatt, S K; Barck, K H; Kates, L; Zavala-Solorio, J; Ross, J; Kolumam, G; Sonoda, J; Carano, R A D

2015-11-01

The ability to non-invasively measure body composition in mouse models of obesity and obesity-related disorders is essential for elucidating mechanisms of metabolic regulation and monitoring the effects of novel treatments. These studies aimed to develop a fully automated, high-throughput micro-computed tomography (micro-CT)-based image analysis technique for longitudinal quantitation of adipose, non-adipose and lean tissue as well as bone and demonstrate utility for assessing the effects of two distinct treatments. An initial validation study was performed in diet-induced obesity (DIO) and control mice on a vivaCT 75 micro-CT system. Subsequently, four groups of DIO mice were imaged pre- and post-treatment with an experimental agonistic antibody specific for anti-fibroblast growth factor receptor 1 (anti-FGFR1, R1MAb1), control immunoglobulin G antibody, a known anorectic antiobesity drug (rimonabant, SR141716), or solvent control. The body composition analysis technique was then ported to a faster micro-CT system (CT120) to markedly increase throughput as well as to evaluate the use of micro-CT image intensity for hepatic lipid content in DIO and control mice. Ex vivo chemical analysis and colorimetric analysis of the liver triglycerides were performed as the standard metrics for correlation with body composition and hepatic lipid status, respectively. Micro-CT-based body composition measures correlate with ex vivo chemical analysis metrics and enable distinction between DIO and control mice. R1MAb1 and rimonabant have differing effects on body composition as assessed by micro-CT. High-throughput body composition imaging is possible using a modified CT120 system. Micro-CT also provides a non-invasive assessment of hepatic lipid content. This work describes, validates and demonstrates utility of a fully automated image analysis technique to quantify in vivo micro-CT-derived measures of adipose, non-adipose and lean tissue, as well as bone. These body composition metrics highly correlate with standard ex vivo chemical analysis and enable longitudinal evaluation of body composition and therapeutic efficacy monitoring.

[Diagnostic imaging of changes of the canine intervertebral disc].

PubMed

Harder, Lisa K

2016-10-12

Intervertebral disc degeneration can cause intervertebral disc herniation. Diagnostic imaging, including radiography, computed tomography and magnetic resonance imaging, is the most important tool in diagnosis. Firstly, an overview of macroscopic and biochemical physiology and pathology of the intervertebral disc will be given. Subsequently, the physics of diagnostic imaging and the appearance of intervertebral disc degeneration and displacement in several imaging methods are described.

Using Digital Radiography To Image Liquid Nitrogen in Voids

NASA Technical Reports Server (NTRS)

Cox, Dwight; Blevins, Elana

2007-01-01

Digital radiography by use of (1) a field-portable x-ray tube that emits low-energy x rays and (2) an electronic imaging x-ray detector has been found to be an effective technique for detecting liquid nitrogen inside voids in thermal-insulation panels. The technique was conceived as a means of investigating cryopumping (including cryoingestion) as a potential cause of loss of thermal insulation foam from space-shuttle external fuel tanks. The technique could just as well be used to investigate cryopumping and cryoingestion in other settings. In images formed by use of low-energy x-rays, one can clearly distinguish between voids filled with liquid nitrogen and those filled with gaseous nitrogen or other gases. Conventional film radiography is of some value, but yields only non-real-time still images that do not show time dependences of levels of liquids in voids. In contrast, the present digital radiographic technique yields a succession of images in real time at a rate of about 10 frames per second. The digitized images can be saved for subsequent analysis to extract data on time dependencies of levels of liquids and, hence, of flow paths and rates of filling and draining. The succession of images also amounts to a real-time motion picture that can be used as a guide to adjustment of test conditions.

Imaging human brain cyto- and myelo-architecture with quantitative OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Boas, David A.; Wang, Hui; Konukoglu, Ender; Fischl, Bruce; Sakadzic, Sava; Magnain, Caroline V.

2017-02-01

No current imaging technology allows us to directly and without significant distortion visualize the microscopic and defining anatomical features of the human brain. Ex vivo histological techniques can yield exquisite planar images, but the cutting, mounting and staining that are required components of this type of imaging induce distortions that are different for each slice, introducing cross-slice differences that prohibit true 3D analysis. We are overcoming this issue by utilizing Optical Coherence Tomography (OCT) with the goal to image whole human brain cytoarchitectural and laminar properties with potentially 3.5 µm resolution in block-face without the need for exogenous staining. From the intrinsic scattering contrast of the brain tissue, OCT gives us images that are comparable to Nissl stains, but without the distortions introduced in standard histology as the OCT images are acquired from the block face prior to slicing and thus without the need for subsequent staining and mounting. We have shown that laminar and cytoarchitectural properties of the brain can be characterized with OCT just as well as with Nissl staining. We will present our recent advances to improve the axial resolution while maintaining contrast; improvements afforded by speckle reduction procedures; and efforts to obtain quantitative maps of the optical scattering coefficient, an intrinsic property of the tissue.

Neuroinflammation and its relationship to changes in brain volume and white matter lesions in multiple sclerosis.

PubMed

Datta, Gourab; Colasanti, Alessandro; Rabiner, Eugenii A; Gunn, Roger N; Malik, Omar; Ciccarelli, Olga; Nicholas, Richard; Van Vlierberghe, Eline; Van Hecke, Wim; Searle, Graham; Santos-Ribeiro, Andre; Matthews, Paul M

2017-11-01

Brain magnetic resonance imaging is an important tool in the diagnosis and monitoring of multiple sclerosis patients. However, magnetic resonance imaging alone provides limited information for predicting an individual patient's disability progression. In part, this is because magnetic resonance imaging lacks sensitivity and specificity for detecting chronic diffuse and multi-focal inflammation mediated by activated microglia/macrophages. The aim of this study was to test for an association between 18 kDa translocator protein brain positron emission tomography signal, which arises largely from microglial activation, and measures of subsequent disease progression in multiple sclerosis patients. Twenty-one patients with multiple sclerosis (seven with secondary progressive disease and 14 with a relapsing remitting disease course) underwent T1- and T2-weighted and magnetization transfer magnetic resonance imaging at baseline and after 1 year. Positron emission tomography scanning with the translocator protein radioligand 11C-PBR28 was performed at baseline. Brain tissue and lesion volumes were segmented from the T1- and T2-weighted magnetic resonance imaging and relative 11C-PBR28 uptake in the normal-appearing white matter was estimated as a distribution volume ratio with respect to a caudate pseudo-reference region. Normal-appearing white matter distribution volume ratio at baseline was correlated with enlarging T2-hyperintense lesion volumes over the subsequent year (ρ = 0.59, P = 0.01). A post hoc analysis showed that this association reflected behaviour in the subgroup of relapsing remitting patients (ρ = 0.74, P = 0.008). By contrast, in the subgroup of secondary progressive patients, microglial activation at baseline was correlated with later progression of brain atrophy (ρ = 0.86, P = 0.04). A regression model including the baseline normal-appearing white matter distribution volume ratio, T2 lesion volume and normal-appearing white matter magnetization transfer ratio for all of the patients combined explained over 90% of the variance in enlarging lesion volume over the subsequent 1 year. Glial activation in white matter assessed by translocator protein PET significantly improves predictions of white matter lesion enlargement in relapsing remitting patients and is associated with greater brain atrophy in secondary progressive disease over a period of short term follow-up. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

High Frequency of Neuroimaging Abnormalities Among Pediatric Patients With Sepsis Who Undergo Neuroimaging.

PubMed

Sandquist, Mary K; Clee, Mark S; Patel, Smruti K; Howard, Kelli A; Yunger, Toni; Nagaraj, Usha D; Jones, Blaise V; Fei, Lin; Vadivelu, Sudhakar; Wong, Hector R

2017-07-01

This study was intended to describe and correlate the neuroimaging findings in pediatric patients after sepsis. Retrospective chart review. Single tertiary care PICU. Patients admitted to Cincinnati Children's Hospital Medical Center with a discharge diagnosis of sepsis or septic shock between 2004 and 2013 were crossmatched with patients who underwent neuroimaging during the same time period. All neuroimaging studies that occurred during or subsequent to a septic event were reviewed, and all new imaging findings were recorded and classified. As many patients experienced multiple septic events and/or had multiple neuroimaging studies after sepsis, our statistical analysis utilized the most recent or "final" imaging study available for each patient so that only brain imaging findings that persisted were included. A total of 389 children with sepsis and 1,705 concurrent or subsequent neuroimaging studies were included in the study. Median age at first septic event was 3.4 years (interquartile range, 0.7-11.5). Median time from first sepsis event to final neuroimaging was 157 days (interquartile range, 10-1,054). The most common indications for final imaging were follow-up (21%), altered mental status (18%), and fever/concern for infection (15%). Sixty-three percentage (n = 243) of final imaging studies demonstrated abnormal findings, the most common of which were volume loss (39%) and MRI signal and/or CT attenuation abnormalities (21%). On multivariable logistic regression, highest Pediatric Risk of Mortality score and presence of oncologic diagnosis/organ transplantation were independently associated with any abnormal final neuroimaging study findings (odds ratio, 1.032; p = 0.048 and odds ratio, 1.632; p = 0.041), although early timing of neuroimaging demonstrated a negative association (odds ratio, 0.606; p = 0.039). The most common abnormal finding of volume loss was independently associated with highest Pediatric Risk of Mortality score (odds ratio, 1.037; p = 0.016) and oncologic diagnosis/organ transplantation (odds ratio, 2.207; p = 0.001) and was negatively associated with early timing of neuroimaging (odds ratio, 0.575; p = 0.037). The majority of pediatric patients with sepsis and concurrent or subsequent neuroimaging have abnormal neuroimaging findings. The implications of this high incidence for long-term neurologic outcomes and follow-up require further exploration.

Imaging of Endogenous Metabolites of Plant Leaves by Mass Spectrometry Based on Laser Activated Electron Tunneling.

PubMed

Huang, Lulu; Tang, Xuemei; Zhang, Wenyang; Jiang, Ruowei; Chen, Disong; Zhang, Juan; Zhong, Hongying

2016-04-07

A new mass spectrometric imaging approach based on laser activated electron tunneling (LAET) was described and applied to analysis of endogenous metabolites of plant leaves. LAET is an electron-directed soft ionization technique. Compressed thin films of semiconductor nanoparticles of bismuth cobalt zinc oxide were placed on the sample plate for proof-of-principle demonstration because they can not only absorb ultraviolet laser but also have high electron mobility. Upon laser irradiation, electrons are excited from valence bands to conduction bands. With appropriate kinetic energies, photoexcited electrons can tunnel away from the barrier and eventually be captured by charge deficient atoms present in neutral molecules. Resultant unpaired electron subsequently initiates specific chemical bond cleavage and generates ions that can be detected in negative ion mode of the mass spectrometer. LAET avoids the co-crystallization process of routinely used organic matrix materials with analyzes in MALDI (matrix assisted-laser desorption ionization) analysis. Thus uneven distribution of crystals with different sizes and shapes as well as background peaks in the low mass range resulting from matrix molecules is eliminated. Advantages of LAET imaging technique include not only improved spatial resolution but also photoelectron capture dissociation which produces predictable fragment ions.

A novel procedure for examining pre-lexical phonetic-level analysis

NASA Astrophysics Data System (ADS)

Bashford, James A.; Warren, Richard M.; Lenz, Peter W.

2005-09-01

A recorded word repeated over and over is heard to undergo a series of illusory changes (verbal transformations) to other syllables and words in the listener's lexicon. When a second image of the same repeating word is added through dichotic presentation (with an interaural delay preventing fusion), the two distinct lateralized images of the word undergo independent illusory transformations at the same rate observed for a single image [Lenz et al., J. Acoust. Soc. Am. 107, 2857 (2000)]. However, when the contralateral word differs by even one phoneme, transformation rate decreases dramatically [Bashford et al., J. Acoust. Soc. Am. 110, 2658 (2001)]. This suppression of transformations did not occur when a nonspeech competitor was employed. The present study found that dichotic suppression of transformation rate also is independent of the top-down influence of a verbal competitor's word frequency, neighborhood density, and lexicality. However, suppression did increase with the extent of feature mismatch at a given phoneme position (e.g., transformations for ``dark'' were suppressed more by contralateral ``hark'' than by ``bark''). These and additional findings indicate that dichotic verbal transformations can provide experimental access to a pre-lexical phonetic analysis normally obscured by subsequent processing. [Work supported by NIH.

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.

Investigation of a novel approach to scoring Giemsa-stained malaria-infected thin blood films.

PubMed

Proudfoot, Owen; Drew, Nathan; Scholzen, Anja; Xiang, Sue; Plebanski, Magdalena

2008-04-21

Daily assessment of the percentage of erythrocytes that are infected ('percent-parasitaemia') across a time-course is a necessary step in many experimental studies of malaria, but represents a time-consuming and unpopular task among researchers. The most common method is extensive microscopic examination of Giemsa-stained thin blood-films. This study explored a method for the assessment of percent-parasitaemia that does not require extended periods of microscopy and results in a descriptive and permanent record of parasitaemia data that is highly amenable to subsequent 'data-mining'. Digital photography was utilized in conjunction with a basic purpose-written computer programme to test the viability of the concept. Partial automation of the determination of percent parasitaemia was then explored, resulting in the successful customization of commercially available broad-spectrum image analysis software towards this aim. Lastly, automated discrimination between infected and uninfected RBCs based on analysis of digital parameters of individual cell images was explored in an effort to completely automate the calculation of an accurate percent-parasitaemia.

Automated Tracking of Cell Migration with Rapid Data Analysis.

PubMed

DuChez, Brian J

2017-09-01

Cell migration is essential for many biological processes including development, wound healing, and metastasis. However, studying cell migration often requires the time-consuming and labor-intensive task of manually tracking cells. To accelerate the task of obtaining coordinate positions of migrating cells, we have developed a graphical user interface (GUI) capable of automating the tracking of fluorescently labeled nuclei. This GUI provides an intuitive user interface that makes automated tracking accessible to researchers with no image-processing experience or familiarity with particle-tracking approaches. Using this GUI, users can interactively determine a minimum of four parameters to identify fluorescently labeled cells and automate acquisition of cell trajectories. Additional features allow for batch processing of numerous time-lapse images, curation of unwanted tracks, and subsequent statistical analysis of tracked cells. Statistical outputs allow users to evaluate migratory phenotypes, including cell speed, distance, displacement, and persistence, as well as measures of directional movement, such as forward migration index (FMI) and angular displacement. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Region based feature extraction from non-cooperative iris images using triplet half-band filter bank

NASA Astrophysics Data System (ADS)

Barpanda, Soubhagya Sankar; Majhi, Banshidhar; Sa, Pankaj Kumar

2015-09-01

In this paper, we have proposed energy based features using a multi-resolution analysis (MRA) on iris template. The MRA is based on our suggested triplet half-band filter bank (THFB). The THFB derivation process is discussed in detail. The iris template is divided into six equispaced sub-templates and two level decomposition has been made to each sub-template using THFB except second one. The reason for discarding the second template is due to the fact that it mostly contains the noise due to eyelids, eyelashes, and occlusion due to segmentation failure. Subsequently, energy features are derived from the decomposed coefficients of each sub-template. The proposed feature has been experimented on standard databases like CASIAv3, UBIRISv1, and IITD and mostly on iris images which encounter a segmentation failure. Comparative analysis has been done with existing features based on Gabor transform, Fourier transform, and CDF 9/7 filter bank. The proposed scheme shows superior performance with respect to FAR, GAR and AUC.

Autonomous Onboard Science Data Analysis for Comet Missions

NASA Technical Reports Server (NTRS)

Thompson, David R.; Tran, Daniel Q.; McLaren, David; Chien, Steve A.; Bergman, Larry; Castano, Rebecca; Doyle, Richard; Estlin, Tara; Lenda, Matthew

2012-01-01

Coming years will bring several comet rendezvous missions. The Rosetta spacecraft arrives at Comet 67P/Churyumov-Gerasimenko in 2014. Subsequent rendezvous might include a mission such as the proposed Comet Hopper with multiple surface landings, as well as Comet Nucleus Sample Return (CNSR) and Coma Rendezvous and Sample Return (CRSR). These encounters will begin to shed light on a population that, despite several previous flybys, remains mysterious and poorly understood. Scientists still have little direct knowledge of interactions between the nucleus and coma, their variation across different comets or their evolution over time. Activity may change on short timescales so it is challenging to characterize with scripted data acquisition. Here we investigate automatic onboard image analysis that could act faster than round-trip light time to capture unexpected outbursts and plume activity. We describe one edge-based method for detect comet nuclei and plumes, and test the approach on an existing catalog of comet images. Finally, we quantify benefits to specific measurement objectives by simulating a basic plume monitoring campaign.

Imaging and Analysis of Void-defects in Solder Joints Formed in Reduced Gravity using High-Resolution Computed Tomography

NASA Technical Reports Server (NTRS)

Easton, John W.; Struk, Peter M.; Rotella, Anthony

2008-01-01

As a part of efforts to develop an electronics repair capability for long duration space missions, techniques and materials for soldering components on a circuit board in reduced gravity must be developed. This paper presents results from testing solder joint formation in low gravity on a NASA Reduced Gravity Research Aircraft. The results presented include joints formed using eutectic tin-lead solder and one of the following fluxes: (1) a no-clean flux core, (2) a rosin flux core, and (3) a solid solder wire with external liquid no-clean flux. The solder joints are analyzed with a computed tomography (CT) technique which imaged the interior of the entire solder joint. This replaced an earlier technique that required the solder joint to be destructively ground down revealing a single plane which was subsequently analyzed. The CT analysis technique is described and results presented with implications for future testing as well as implications for the overall electronics repair effort discussed.

Analysis of biological time-lapse microscopic experiment from the point of view of the information theory.

PubMed

Štys, Dalibor; Urban, Jan; Vaněk, Jan; Císař, Petr

2011-06-01

We report objective analysis of information in the microscopic image of the cell monolayer. The process of transfer of information about the cell by the microscope is analyzed in terms of the classical Shannon information transfer scheme. The information source is the biological object, the information transfer channel is the whole microscope including the camera chip. The destination is the model of biological system. The information contribution is analyzed as information carried by a point to overall information in the image. Subsequently we obtain information reflection of the biological object. This is transformed in the biological model which, in information terminology, is the destination. This, we propose, should be constructed as state transitions in individual cells modulated by information bonds between the cells. We show examples of detected cell states in multidimensional state space. This space is reflected as colour channel intensity phenomenological state space. We have also observed information bonds and show examples of them.

Analysis of biological time-lapse microscopic experiment from the point of view of the information theory.

PubMed

Stys, Dalibor; Urban, Jan; Vanek, Jan; Císar, Petr

2010-07-01

We report objective analysis of information in the microscopic image of the cell monolayer. The process of transfer of information about the cell by the microscope is analyzed in terms of the classical Shannon information transfer scheme. The information source is the biological object, the information transfer channel is the whole microscope including the camera chip. The destination is the model of biological system. The information contribution is analyzed as information carried by a point to overall information in the image. Subsequently we obtain information reflection of the biological object. This is transformed in the biological model which, in information terminology, is the destination. This, we propose, should be constructed as state transitions in individual cells modulated by information bonds between the cells. We show examples of detected cell states in multidimensional state space reflected in space an colour channel intensity phenomenological state space. We have also observed information bonds and show examples of them. Copyright 2010 Elsevier Ltd. All rights reserved.

Biodistribution and predictive value of 18F-fluorocyclophosphamide in mice bearing human breast cancer xenografts.

PubMed

Kesner, Amanda L; Hsueh, Wei-Ann; Htet, Nwe Linn; Pio, Betty S; Czernin, Johannes; Pegram, Mark D; Phelps, Michael E; Silverman, Daniel H S

2007-12-01

In mice bearing human breast cancer xenografts, we examined the biodistribution of (18)F-fluorocyclophosphamide ((18)F-F-CP) to evaluate its potential as a noninvasive prognostic tool for predicting the resistance of tumors to cyclophosphamide therapy. (18)F-F-CP was synthesized as we recently described, and PET data were acquired after administration of (18)F-F-CP in mice bearing human breast cancer xenografts (MCF-7 cells). Tracer biodistribution in reconstructed images was quantified by region-of-interest analysis. Distribution was also assessed by harvesting dissected organs, tumors, and blood, determining (18)F content in each tissue with a gamma-well counter. The mice were subsequently treated with cyclophosphamide, and tumor size was monitored for at least 3 wk after chemotherapy administration. The distribution of harvested activity correlated strongly with distribution observed in PET images. Target organs were related to routes of metabolism and excretion. (18)F-F-CP uptake was highest in kidneys, lowest in brain, and intermediate in tumors, as determined by both image-based and tissue-based measurements. (18)F-F-CP uptake was not inhibited by coadministration of an approximately x700 concentration of unlabeled cyclophosphamide. PET measures of (18)F-F-CP uptake in tumor predicted the magnitude of the response to subsequent administration of cyclophosphamide. Noninvasive assessment of (18)F-F-CP uptake using PET may potentially be helpful for predicting the response of breast tumors to cyclophosphamide before therapy begins.

Fabrication of a chirped artificial compound eye for endoscopic imaging fiber bundle by dose-modulated laser lithography and subsequent thermal reflow

NASA Astrophysics Data System (ADS)

Deng, Shengfeng; Lyu, Jinke; Sun, Hongda; Cui, Xiaobin; Wang, Tun; Lu, Miao

2015-03-01

A chirped artificial compound eye on a curved surface was fabricated using an optical resin and then mounted on the end of an endoscopic imaging fiber bundle. The focal length of each lenslet on the curved surface was variable to realize a flat focal plane, which matched the planar end surface of the fiber bundle. The variation of the focal length was obtained by using a photoresist mold formed by dose-modulated laser lithography and subsequent thermal reflow. The imaging performance of the fiber bundle was characterized by coupling with a coaxial light microscope, and the result demonstrated a larger field of view and better imaging quality than that of an artificial compound eye with a uniform focal length. Accordingly, this technology has potential application in stereoscopic endoscopy.

Advanced Test Reactor National Scientific User Facility (ATR NSUF) Monthly Report December 2014

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

Renae Soelberg

2014-12-01

• PNNL has completed sectioning of the U.C. Berkeley hydride fuel rodlet 1 (highest burn-up) and is currently polishing samples in preparation for optical metallography. • A disk was successfully sectioned from rodlet 1 at the location of the internal thermocouple tip as desired. The transition from annular pellet to solid pellet is verified by the eutectic-filled inner cavity located on the back face of this disk (top left) and the solid front face (bottom left). Preliminary low-resolution images indicate interesting sample characteristics in the eutectic surrounding the rodlet at the location of the outer thermocouple tip (right). This samplemore » has been potted and is currently being polished for high-resolution optical microscopy and subsequent SEM analysis. (See images.)« less

Antero-posterior (AP) pelvis x-ray imaging on a trolley: Impact of trolley design, mattress design and radiographer practice on image quality and radiation dose.

PubMed

Tugwell, J R; England, A; Hogg, P

2017-08-01

Physical and technical differences exist between imaging on an x-ray tabletop and imaging on a trolley. This study evaluates how trolley imaging impacts image quality and radiation dose for an antero-posterior (AP) pelvis projection whilst subsequently exploring means of optimising this imaging examination. An anthropomorphic pelvis phantom was imaged on a commercially available trolley under various conditions. Variables explored included two mattresses, two image receptor holder positions, three source to image distances (SIDs) and four mAs values. Image quality was evaluated using relative visual grading analysis with the reference image acquired on the x-ray tabletop. Contrast to noise ratio (CNR) was calculated. Effective dose was established using Monte Carlo simulation. Optimisation scores were derived as a figure of merit by dividing effective dose with visual image quality scores. Visual image quality reduced significantly (p < 0.05) whilst effective dose increased significantly (p < 0.05) for images acquired on the trolley using identical acquisition parameters to the reference image. The trolley image with the highest optimisation score was acquired using 130 cm SID, 20 mAs, the standard mattress and platform not elevated. A difference of 12.8 mm was found between the image with the lowest and highest magnification factor (18%). The acquisition parameters used for AP pelvis on the x-ray tabletop are not transferable to trolley imaging and should be modified accordingly to compensate for the differences that exist. Exposure charts should be developed for trolley imaging to ensure optimal image quality at lowest possible dose. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Visual Search with Image Modification in Age-Related Macular Degeneration

PubMed Central

Wiecek, Emily; Jackson, Mary Lou; Dakin, Steven C.; Bex, Peter

2012-01-01

Purpose. AMD results in loss of central vision and a dependence on low-resolution peripheral vision. While many image enhancement techniques have been proposed, there is a lack of quantitative comparison of the effectiveness of enhancement. We developed a natural visual search task that uses patients' eye movements as a quantitative and functional measure of the efficacy of image modification. Methods. Eye movements of 17 patients (mean age = 77 years) with AMD were recorded while they searched for target objects in natural images. Eight different image modification methods were implemented and included manipulations of local image or edge contrast, color, and crowding. In a subsequent task, patients ranked their preference of the image modifications. Results. Within individual participants, there was no significant difference in search duration or accuracy across eight different image manipulations. When data were collapsed across all image modifications, a multivariate model identified six significant predictors for normalized search duration including scotoma size and acuity, as well as interactions among scotoma size, age, acuity, and contrast (P < 0.05). Additionally, an analysis of image statistics showed no correlation with search performance across all image modifications. Rank ordering of enhancement methods based on participants' preference revealed a trend that participants preferred the least modified images (P < 0.05). Conclusions. There was no quantitative effect of image modification on search performance. A better understanding of low- and high-level components of visual search in natural scenes is necessary to improve future attempts at image enhancement for low vision patients. Different search tasks may require alternative image modifications to improve patient functioning and performance. PMID:22930725

Automatic initialization and quality control of large-scale cardiac MRI segmentations.

PubMed

Albà, Xènia; Lekadir, Karim; Pereañez, Marco; Medrano-Gracia, Pau; Young, Alistair A; Frangi, Alejandro F

2018-01-01

Continuous advances in imaging technologies enable ever more comprehensive phenotyping of human anatomy and physiology. Concomitant reduction of imaging costs has resulted in widespread use of imaging in large clinical trials and population imaging studies. Magnetic Resonance Imaging (MRI), in particular, offers one-stop-shop multidimensional biomarkers of cardiovascular physiology and pathology. A wide range of analysis methods offer sophisticated cardiac image assessment and quantification for clinical and research studies. However, most methods have only been evaluated on relatively small databases often not accessible for open and fair benchmarking. Consequently, published performance indices are not directly comparable across studies and their translation and scalability to large clinical trials or population imaging cohorts is uncertain. Most existing techniques still rely on considerable manual intervention for the initialization and quality control of the segmentation process, becoming prohibitive when dealing with thousands of images. The contributions of this paper are three-fold. First, we propose a fully automatic method for initializing cardiac MRI segmentation, by using image features and random forests regression to predict an initial position of the heart and key anatomical landmarks in an MRI volume. In processing a full imaging database, the technique predicts the optimal corrective displacements and positions in relation to the initial rough intersections of the long and short axis images. Second, we introduce for the first time a quality control measure capable of identifying incorrect cardiac segmentations with no visual assessment. The method uses statistical, pattern and fractal descriptors in a random forest classifier to detect failures to be corrected or removed from subsequent statistical analysis. Finally, we validate these new techniques within a full pipeline for cardiac segmentation applicable to large-scale cardiac MRI databases. The results obtained based on over 1200 cases from the Cardiac Atlas Project show the promise of fully automatic initialization and quality control for population studies. Copyright © 2017 Elsevier B.V. All rights reserved.

TU-H-206-01: An Automated Approach for Identifying Geometric Distortions in Gamma Cameras

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

Mann, S; Nelson, J; Samei, E

2016-06-15

Purpose: To develop a clinically-deployable, automated process for detecting artifacts in routine nuclear medicine (NM) quality assurance (QA) bar phantom images. Methods: An artifact detection algorithm was created to analyze bar phantom images as part of an ongoing QA program. A low noise, high resolution reference image was acquired from an x-ray of the bar phantom with a Philips Digital Diagnost system utilizing image stitching. NM bar images, acquired for 5 million counts over a 512×512 matrix, were registered to the template image by maximizing mutual information (MI). The MI index was used as an initial test for artifacts; lowmore » values indicate an overall presence of distortions regardless of their spatial location. Images with low MI scores were further analyzed for bar linearity, periodicity, alignment, and compression to locate differences with respect to the template. Findings from each test were spatially correlated and locations failing multiple tests were flagged as potential artifacts requiring additional visual analysis. The algorithm was initially deployed for GE Discovery 670 and Infinia Hawkeye gamma cameras. Results: The algorithm successfully identified clinically relevant artifacts from both systems previously unnoticed by technologists performing the QA. Average MI indices for artifact-free images are 0.55. Images with MI indices < 0.50 have shown 100% sensitivity and specificity for artifact detection when compared with a thorough visual analysis. Correlation of geometric tests confirms the ability to spatially locate the most likely image regions containing an artifact regardless of initial phantom orientation. Conclusion: The algorithm shows the potential to detect gamma camera artifacts that may be missed by routine technologist inspections. Detection and subsequent correction of artifacts ensures maximum image quality and may help to identify failing hardware before it impacts clinical workflow. Going forward, the algorithm is being deployed to monitor data from all gamma cameras within our health system.« less

Single Particle Analysis by Combined Chemical Imaging to Study Episodic Air Pollution Events in Vienna

NASA Astrophysics Data System (ADS)

Ofner, Johannes; Eitenberger, Elisabeth; Friedbacher, Gernot; Brenner, Florian; Hutter, Herbert; Schauer, Gerhard; Kistler, Magdalena; Greilinger, Marion; Lohninger, Hans; Lendl, Bernhard; Kasper-Giebl, Anne

2017-04-01

The aerosol composition of a city like Vienna is characterized by a complex interaction of local emissions and atmospheric input on a regional and continental scale. The identification of major aerosol constituents for basic source appointment and air quality issues needs a high analytical effort. Exceptional episodic air pollution events strongly change the typical aerosol composition of a city like Vienna on a time-scale of few hours to several days. Analyzing the chemistry of particulate matter from these events is often hampered by the sampling time and related sample amount necessary to apply the full range of bulk analytical methods needed for chemical characterization. Additionally, morphological and single particle features are hardly accessible. Chemical Imaging evolved to a powerful tool for image-based chemical analysis of complex samples. As a complementary technique to bulk analytical methods, chemical imaging can address a new access to study air pollution events by obtaining major aerosol constituents with single particle features at high temporal resolutions and small sample volumes. The analysis of the chemical imaging datasets is assisted by multivariate statistics with the benefit of image-based chemical structure determination for direct aerosol source appointment. A novel approach in chemical imaging is combined chemical imaging or so-called multisensor hyperspectral imaging, involving elemental imaging (electron microscopy-based energy dispersive X-ray imaging), vibrational imaging (Raman micro-spectroscopy) and mass spectrometric imaging (Time-of-Flight Secondary Ion Mass Spectrometry) with subsequent combined multivariate analytics. Combined chemical imaging of precipitated aerosol particles will be demonstrated by the following examples of air pollution events in Vienna: Exceptional episodic events like the transformation of Saharan dust by the impact of the city of Vienna will be discussed and compared to samples obtained at a high alpine background site (Sonnblick Observatory, Saharan Dust Event from April 2016). Further, chemical imaging of biological aerosol constituents of an autumnal pollen breakout in Vienna, with background samples from nearby locations from November 2016 will demonstrate the advantages of the chemical imaging approach. Additionally, the chemical fingerprint of an exceptional air pollution event from a local emission source, caused by the pull down process of a building in Vienna will unravel the needs for multisensor imaging, especially the combinational access. Obtained chemical images will be correlated to bulk analytical results. Benefits of the overall methodical access by combining bulk analytics and combined chemical imaging of exceptional episodic air pollution events will be discussed.

Hand gesture recognition by analysis of codons

NASA Astrophysics Data System (ADS)

Ramachandra, Poornima; Shrikhande, Neelima

2007-09-01

The problem of recognizing gestures from images using computers can be approached by closely understanding how the human brain tackles it. A full fledged gesture recognition system will substitute mouse and keyboards completely. Humans can recognize most gestures by looking at the characteristic external shape or the silhouette of the fingers. Many previous techniques to recognize gestures dealt with motion and geometric features of hands. In this thesis gestures are recognized by the Codon-list pattern extracted from the object contour. All edges of an image are described in terms of sequence of Codons. The Codons are defined in terms of the relationship between maxima, minima and zeros of curvature encountered as one traverses the boundary of the object. We have concentrated on a catalog of 24 gesture images from the American Sign Language alphabet (Letter J and Z are ignored as they are represented using motion) [2]. The query image given as an input to the system is analyzed and tested against the Codon-lists, which are shape descriptors for external parts of a hand gesture. We have used the Weighted Frequency Indexing Transform (WFIT) approach which is used in DNA sequence matching for matching the Codon-lists. The matching algorithm consists of two steps: 1) the query sequences are converted to short sequences and are assigned weights and, 2) all the sequences of query gestures are pruned into match and mismatch subsequences by the frequency indexing tree based on the weights of the subsequences. The Codon sequences with the most weight are used to determine the most precise match. Once a match is found, the identified gesture and corresponding interpretation are shown as output.

ANALYSIS AND MODELING OF TWO FLARE LOOPS OBSERVED BY AIA AND EIS

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

Li, Y.; Ding, M. D.; Qiu, J.

2012-10-10

We analyze and model an M1.0 flare observed by SDO/AIA and Hinode/EIS to investigate how flare loops are heated and evolve subsequently. The flare is composed of two distinctive loop systems observed in extreme ultraviolet (EUV) images. The UV 1600 A emission at the feet of these loops exhibits a rapid rise, followed by enhanced emission in different EUV channels observed by the Atmospheric Imaging Assembly (AIA) and the EUV Imaging Spectrometer (EIS). Such behavior is indicative of impulsive energy deposit and the subsequent response in overlying coronal loops that evolve through different temperatures. Using the method we recently developed,more » we infer empirical heating functions from the rapid rise of the UV light curves for the two loop systems, respectively, treating them as two big loops with cross-sectional area of 5'' by 5'', and compute the plasma evolution in the loops using the EBTEL model. We compute the synthetic EUV light curves, which, with the limitation of the model, reasonably agree with observed light curves obtained in multiple AIA channels and EIS lines: they show the same evolution trend and their magnitudes are comparable by within a factor of two. Furthermore, we also compare the computed mean enthalpy flow velocity with the Doppler shift measurements by EIS during the decay phase of the two loops. Our results suggest that the two different loops with different heating functions as inferred from their footpoint UV emission, combined with their different lengths as measured from imaging observations, give rise to different coronal plasma evolution patterns captured both in the model and in observations.« less

Automatic three-dimensional registration of intravascular optical coherence tomography images

NASA Astrophysics Data System (ADS)

Ughi, Giovanni J.; Adriaenssens, Tom; Larsson, Matilda; Dubois, Christophe; Sinnaeve, Peter R.; Coosemans, Mark; Desmet, Walter; D'hooge, Jan

2012-02-01

Intravascular optical coherence tomography (IV-OCT) is a catheter-based high-resolution imaging technique able to visualize the inner wall of the coronary arteries and implanted devices in vivo with an axial resolution below 20 μm. IV-OCT is being used in several clinical trials aiming to quantify the vessel response to stent implantation over time. However, stent analysis is currently performed manually and corresponding images taken at different time points are matched through a very labor-intensive and subjective procedure. We present an automated method for the spatial registration of IV-OCT datasets. Stent struts are segmented through consecutive images and three-dimensional models of the stents are created for both datasets to be registered. The two models are initially roughly registered through an automatic initialization procedure and an iterative closest point algorithm is subsequently applied for a more precise registration. To correct for nonuniform rotational distortions (NURDs) and other potential acquisition artifacts, the registration is consecutively refined on a local level. The algorithm was first validated by using an in vitro experimental setup based on a polyvinyl-alcohol gel tubular phantom. Subsequently, an in vivo validation was obtained by exploiting stable vessel landmarks. The mean registration error in vitro was quantified to be 0.14 mm in the longitudinal axis and 7.3-deg mean rotation error. In vivo validation resulted in 0.23 mm in the longitudinal axis and 10.1-deg rotation error. These results indicate that the proposed methodology can be used for automatic registration of in vivo IV-OCT datasets. Such a tool will be indispensable for larger studies on vessel healing pathophysiology and reaction to stent implantation. As such, it will be valuable in testing the performance of new generations of intracoronary devices and new therapeutic drugs.

Computerized image analysis of cell-cell interactions in human renal tissue by using multi-channel immunoflourescent confocal microscopy

NASA Astrophysics Data System (ADS)

Peng, Yahui; Jiang, Yulei; Liarski, Vladimir M.; Kaverina, Natalya; Clark, Marcus R.; Giger, Maryellen L.

2012-03-01

Analysis of interactions between B and T cells in tubulointerstitial inflammation is important for understanding human lupus nephritis. We developed a computer technique to perform this analysis, and compared it with manual analysis. Multi-channel immunoflourescent-microscopy images were acquired from 207 regions of interest in 40 renal tissue sections of 19 patients diagnosed with lupus nephritis. Fresh-frozen renal tissue sections were stained with combinations of immunoflourescent antibodies to membrane proteins and counter-stained with a cell nuclear marker. Manual delineation of the antibodies was considered as the reference standard. We first segmented cell nuclei and cell membrane markers, and then determined corresponding cell types based on the distances between cell nuclei and specific cell-membrane marker combinations. Subsequently, the distribution of the shortest distance from T cell nuclei to B cell nuclei was obtained and used as a surrogate indicator of cell-cell interactions. The computer and manual analyses results were concordant. The average absolute difference was 1.1+/-1.2% between the computer and manual analysis results in the number of cell-cell distances of 3 μm or less as a percentage of the total number of cell-cell distances. Our computerized analysis of cell-cell distances could be used as a surrogate for quantifying cell-cell interactions as either an automated and quantitative analysis or for independent confirmation of manual analysis.

Pseudo colour visualization of fused multispectral laser scattering images for optical diagnosis of rheumatoid arthritis

NASA Astrophysics Data System (ADS)

Zabarylo, U.; Minet, O.

2010-01-01

Investigations on the application of optical procedures for the diagnosis of rheumatism using scattered light images are only at the beginning both in terms of new image-processing methods and subsequent clinical application. For semi-automatic diagnosis using laser light, the multispectral scattered light images are registered and overlapped to pseudo-coloured images, which depict diagnostically essential contents by visually highlighting pathological changes.

Multi-voxel patterns of visual category representation during episodic encoding are predictive of subsequent memory

PubMed Central

Kuhl, Brice A.; Rissman, Jesse; Wagner, Anthony D.

2012-01-01

Successful encoding of episodic memories is thought to depend on contributions from prefrontal and temporal lobe structures. Neural processes that contribute to successful encoding have been extensively explored through univariate analyses of neuroimaging data that compare mean activity levels elicited during the encoding of events that are subsequently remembered vs. those subsequently forgotten. Here, we applied pattern classification to fMRI data to assess the degree to which distributed patterns of activity within prefrontal and temporal lobe structures elicited during the encoding of word-image pairs were diagnostic of the visual category (Face or Scene) of the encoded image. We then assessed whether representation of category information was predictive of subsequent memory. Classification analyses indicated that temporal lobe structures contained information robustly diagnostic of visual category. Information in prefrontal cortex was less diagnostic of visual category, but was nonetheless associated with highly reliable classifier-based evidence for category representation. Critically, trials associated with greater classifier-based estimates of category representation in temporal and prefrontal regions were associated with a higher probability of subsequent remembering. Finally, consideration of trial-by-trial variance in classifier-based measures of category representation revealed positive correlations between prefrontal and temporal lobe representations, with the strength of these correlations varying as a function of the category of image being encoded. Together, these results indicate that multi-voxel representations of encoded information can provide unique insights into how visual experiences are transformed into episodic memories. PMID:21925190

Automatic Coregistration and orthorectification (ACRO) and subsequent mosaicing of NASA high-resolution imagery over the Mars MC11 quadrangle, using HRSC as a baseline

NASA Astrophysics Data System (ADS)

Sidiropoulos, Panagiotis; Muller, Jan-Peter; Watson, Gillian; Michael, Gregory; Walter, Sebastian

2018-02-01

This work presents the coregistered, orthorectified and mosaiced high-resolution products of the MC11 quadrangle of Mars, which have been processed using novel, fully automatic, techniques. We discuss the development of a pipeline that achieves fully automatic and parameter independent geometric alignment of high-resolution planetary images, starting from raw input images in NASA PDS format and following all required steps to produce a coregistered geotiff image, a corresponding footprint and useful metadata. Additionally, we describe the development of a radiometric calibration technique that post-processes coregistered images to make them radiometrically consistent. Finally, we present a batch-mode application of the developed techniques over the MC11 quadrangle to validate their potential, as well as to generate end products, which are released to the planetary science community, thus assisting in the analysis of Mars static and dynamic features. This case study is a step towards the full automation of signal processing tasks that are essential to increase the usability of planetary data, but currently, require the extensive use of human resources.

Atomic structure of a metal-supported two-dimensional germania film

NASA Astrophysics Data System (ADS)

Lewandowski, Adrián Leandro; Schlexer, Philomena; Büchner, Christin; Davis, Earl M.; Burrall, Hannah; Burson, Kristen M.; Schneider, Wolf-Dieter; Heyde, Markus; Pacchioni, Gianfranco; Freund, Hans-Joachim

2018-03-01

The growth and microscopic characterization of two-dimensional germania films is presented. Germanium oxide monolayer films were grown on Ru(0001) by physical vapor deposition and subsequent annealing in oxygen. We obtain a comprehensive image of the germania film structure by combining intensity-voltage low-energy electron diffraction (I/V-LEED) and ab initio density functional theory (DFT) analysis with atomic-resolution scanning tunneling microscopy (STM) imaging. For benchmarking purposes, the bare Ru(0001) substrate and the (2 ×2 )3 O covered Ru(0001) were analyzed with I/V-LEED with respect to previous reports. STM topographic images of the germania film reveal a hexagonal network where the oxygen and germanium atom positions appear in different imaging contrasts. For quantitative LEED, the best agreement has been achieved with DFT structures where the germanium atoms are located preferentially on the top and fcc hollow sites of the Ru(0001) substrate. Moreover, in these atomically flat germania films, local site geometries, i.e., tetrahedral building blocks, ring structures, and domain boundaries, have been identified, indicating possible pathways towards two-dimensional amorphous networks.

Working to make an image: an analysis of three Philip Morris corporate image media campaigns

PubMed Central

Szczypka, Glen; Wakefield, Melanie A; Emery, Sherry; Terry‐McElrath, Yvonne M; Flay, Brian R; Chaloupka, Frank J

2007-01-01

Objective To describe the nature and timing of, and population exposure to, Philip Morris USA's three explicit corporate image television advertising campaigns and explore the motivations behind each campaign. Methods : Analysis of television ratings from the largest 75 media markets in the United States, which measure the reach and frequency of population exposure to advertising; copies of all televised commercials produced by Philip Morris; and tobacco industry documents, which provide insights into the specific goals of each campaign. Findings Household exposure to the “Working to Make a Difference: the People of Philip Morris” averaged 5.37 ads/month for 27 months from 1999–2001; the “Tobacco Settlement” campaign averaged 10.05 ads/month for three months in 2000; and “PMUSA” averaged 3.11 ads/month for the last six months in 2003. The percentage of advertising exposure that was purchased in news programming in order to reach opinion leaders increased over the three campaigns from 20%, 39% and 60%, respectively. These public relations campaigns were designed to counter negative images, increase brand recognition, and improve the financial viability of the company. Conclusions Only one early media campaign focused on issues other than tobacco, whereas subsequent campaigns have been specifically concerned with tobacco issues, and more targeted to opinion leaders. The size and timing of the advertising buys appeared to be strategically crafted to maximise advertising exposure for these population subgroups during critical threats to Philip Morris's public image. PMID:17897994

A Multi Directional Perfect Reconstruction Filter Bank Designed with 2-D Eigenfilter Approach: Application to Ultrasound Speckle Reduction.

PubMed

Nagare, Mukund B; Patil, Bhushan D; Holambe, Raghunath S

2017-02-01

B-Mode ultrasound images are degraded by inherent noise called Speckle, which creates a considerable impact on image quality. This noise reduces the accuracy of image analysis and interpretation. Therefore, reduction of speckle noise is an essential task which improves the accuracy of the clinical diagnostics. In this paper, a Multi-directional perfect-reconstruction (PR) filter bank is proposed based on 2-D eigenfilter approach. The proposed method used for the design of two-dimensional (2-D) two-channel linear-phase FIR perfect-reconstruction filter bank. In this method, the fan shaped, diamond shaped and checkerboard shaped filters are designed. The quadratic measure of the error function between the passband and stopband of the filter has been used an objective function. First, the low-pass analysis filter is designed and then the PR condition has been expressed as a set of linear constraints on the corresponding synthesis low-pass filter. Subsequently, the corresponding synthesis filter is designed using the eigenfilter design method with linear constraints. The newly designed 2-D filters are used in translation invariant pyramidal directional filter bank (TIPDFB) for reduction of speckle noise in ultrasound images. The proposed 2-D filters give better symmetry, regularity and frequency selectivity of the filters in comparison to existing design methods. The proposed method is validated on synthetic and real ultrasound data which ensures improvement in the quality of ultrasound images and efficiently suppresses the speckle noise compared to existing methods.

Working to make an image: an analysis of three Philip Morris corporate image media campaigns.

PubMed

Szczypka, Glen; Wakefield, Melanie A; Emery, Sherry; Terry-McElrath, Yvonne M; Flay, Brian R; Chaloupka, Frank J

2007-10-01

To describe the nature and timing of, and population exposure to, Philip Morris USA's three explicit corporate image television advertising campaigns and explore the motivations behind each campaign. Analysis of television ratings from the largest 75 media markets in the United States, which measure the reach and frequency of population exposure to advertising; copies of all televised commercials produced by Philip Morris; and tobacco industry documents, which provide insights into the specific goals of each campaign. Household exposure to the "Working to Make a Difference: the People of Philip Morris" averaged 5.37 ads/month for 27 months from 1999-2001; the "Tobacco Settlement" campaign averaged 10.05 ads/month for three months in 2000; and "PMUSA" averaged 3.11 ads/month for the last six months in 2003. The percentage of advertising exposure that was purchased in news programming in order to reach opinion leaders increased over the three campaigns from 20%, 39% and 60%, respectively. These public relations campaigns were designed to counter negative images, increase brand recognition, and improve the financial viability of the company. Only one early media campaign focused on issues other than tobacco, whereas subsequent campaigns have been specifically concerned with tobacco issues, and more targeted to opinion leaders. The size and timing of the advertising buys appeared to be strategically crafted to maximise advertising exposure for these population subgroups during critical threats to Philip Morris's public image.

Hyperspectral imaging of cuttlefish camouflage indicates good color match in the eyes of fish predators.

PubMed

Chiao, Chuan-Chin; Wickiser, J Kenneth; Allen, Justine J; Genter, Brock; Hanlon, Roger T

2011-05-31

Camouflage is a widespread phenomenon throughout nature and an important antipredator tactic in natural selection. Many visual predators have keen color perception, and thus camouflage patterns should provide some degree of color matching in addition to other visual factors such as pattern, contrast, and texture. Quantifying camouflage effectiveness in the eyes of the predator is a challenge from the perspectives of both biology and optical imaging technology. Here we take advantage of hyperspectral imaging (HSI), which records full-spectrum light data, to simultaneously visualize color match and pattern match in the spectral and the spatial domains, respectively. Cuttlefish can dynamically camouflage themselves on any natural substrate and, despite their colorblindness, produce body patterns that appear to have high-fidelity color matches to the substrate when viewed directly by humans or with RGB images. Live camouflaged cuttlefish on natural backgrounds were imaged using HSI, and subsequent spectral analysis revealed that most reflectance spectra of individual cuttlefish and substrates were similar, rendering the color match possible. Modeling color vision of potential di- and trichromatic fish predators of cuttlefish corroborated the spectral match analysis and demonstrated that camouflaged cuttlefish show good color match as well as pattern match in the eyes of fish predators. These findings (i) indicate the strong potential of HSI technology to enhance studies of biological coloration and (ii) provide supporting evidence that cuttlefish can produce color-coordinated camouflage on natural substrates despite lacking color vision.

Differentiation of pre-ablation and post-ablation late gadolinium-enhanced cardiac MRI scans of longstanding persistent atrial fibrillation patients

NASA Astrophysics Data System (ADS)

Yang, Guang; Zhuang, Xiahai; Khan, Habib; Haldar, Shouvik; Nyktari, Eva; Li, Lei; Ye, Xujiong; Slabaugh, Greg; Wong, Tom; Mohiaddin, Raad; Keegan, Jennifer; Firmin, David

2017-03-01

Late Gadolinium-Enhanced Cardiac MRI (LGE CMRI) is an emerging non-invasive technique to image and quantify preablation native and post-ablation atrial scarring. Previous studies have reported that enhanced image intensities of the atrial scarring in the LGE CMRI inversely correlate with the left atrial endocardial voltage invasively obtained by electro-anatomical mapping. However, the reported reproducibility of using LGE CMRI to identify and quantify atrial scarring is variable. This may be due to two reasons: first, delineation of the left atrium (LA) and pulmonary veins (PVs) anatomy generally relies on manual operation that is highly subjective, and this could substantially affect the subsequent atrial scarring segmentation; second, simple intensity based image features may not be good enough to detect subtle changes in atrial scarring. In this study, we hypothesized that texture analysis can provide reliable image features for the LGE CMRI images subject to accurate and objective delineation of the heart anatomy based on a fully-automated whole heart segmentation (WHS) method. We tested the extracted texture features to differentiate between pre-ablation and post-ablation LGE CMRI studies in longstanding persistent atrial fibrillation patients. These patients often have extensive native scarring and differentiation from post-ablation scarring can be difficult. Quantification results showed that our method is capable of solving this classification task, and we can envisage further deployment of this texture analysis based method for other clinical problems using LGE CMRI.

ImagePAD, a novel counting application for the Apple iPad, used to quantify axons in the mouse optic nerve.

PubMed

Templeton, Justin P; Struebing, Felix L; Lemmon, Andrew; Geisert, Eldon E

2014-11-01

The present article introduces a new and easy to use counting application for the Apple iPad. The application "ImagePAD" takes advantage of the advanced user interface features offered by the Apple iOS platform, simplifying the rather tedious task of quantifying features in anatomical studies. For example, the image under analysis can be easily panned and zoomed using iOS-supported multi-touch gestures without losing the spatial context of the counting task, which is extremely important for ensuring count accuracy. This application allows one to quantify up to 5 different types of objects in a single field and output the data in a tab-delimited format for subsequent analysis. We describe two examples of the use of the application: quantifying axons in the optic nerve of the C57BL/6J mouse and determining the percentage of cells labeled with NeuN or ChAT in the retinal ganglion cell layer. For the optic nerve, contiguous images at 60× magnification were taken and transferred onto an Apple iPad. Axons were counted by tapping on the touch-sensitive screen using ImagePAD. Nine optic nerves were sampled and the number of axons in the nerves ranged from 38,872 axons to 50,196 axons with an average of 44,846 axons per nerve (SD = 3980 axons). Copyright © 2014 Elsevier Ltd. All rights reserved.

Corrosion consequences of microfouling in water reclamation systems

NASA Technical Reports Server (NTRS)

Ford, Tim; Mitchell, Ralph

1991-01-01

This paper examines the potential fouling and corrosion problems associated with microbial film formation throughout the water reclamation system (WRS) designed for the Space Station Freedom. It is shown that the use of advanced metal sputtering techiques combined with image analysis and FTIR spectroscopy will present realistic solutions for investigating the formation and function of biofilm on different alloys, the subsequent corrosion, and the efficiency of different treatments. These techniques, used in combination with electrochemical measurements of corrosion, will provide a powerful approach to examinations of materials considered for use in the WRS.

Satellite applications to a coastal inlet study, Clearwater Beach, Florida

NASA Technical Reports Server (NTRS)

Wang, Y. H.; Smutz, M.; Ruth, B. E.; Brooks, H. K.

1977-01-01

Two sets of LANDSAT magnetic tapes were obtained and displayed on the screen of an IMAGE 100 computer. Spectral analysis was performed to produce various signatures, their extent and location. Subsequent ground truth observations and measurements were gathered by means of hydrographic surveys and low-altitude aerial photography for interpretation and calibration of the LANDSAT data. Finally, a coastal engineering assessment based on the LANDSAT data was made. Recommendations to the City of Clearwater regarding the navigational channel alignment and dredging practice are presented in the light of the inlet stability.

Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); Elliott, James R. (Inventor); Stoakley, Diane M. (Inventor); Chu, Sang-Hyon (Inventor); King, Glen C. (Inventor); Kim, Jae-Woo (Inventor); Choi, Sang Hyouk (Inventor); Lillehei, Peter T. (Inventor)

2011-01-01

A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).

The causes of hypopituitarism in the absence of abnormal pituitary imaging.

PubMed

Wilson, V; Mallipedhi, A; Stephens, J W; Redfern, R M; Price, D E

2014-01-01

Hypopituitarism in the absence of a history of pituitary pathology or abnormal pituitary imaging is rare. To identify the cause of hypopituitarism in individuals in whom pituitary imaging was normal. Retrospective analysis of electronic patient record. A review of the pituitary function in the 506 patients on the Morriston Hospital pituitary database revealed 230 had some degree of hypopituitarism and of these, 21 (9%) had normal pituitary imaging. Of this group, six patients had a past medical history of subarachnoid haemorrhage, head injury or meningitis, and mainly suffered from a deficiency of antidiuretic hormone. One patient had a stroke resulting in multiple anterior hormone deficiencies and six individuals had idiopathic cranial diabetes insipidus (DI). Subsequent investigations of the remaining eight patients with normal pituitary imaging revealed that two had neurosarcoidosis both of whom had panhypopituitarism. Four patients had haemochromatosis which resulted in gonadotropin deficiency in two, DI in one and panhypopituitarism in the other. There were two individuals with confirmed hypopituitarism and multiple hormone deficiencies in which no cause could be identified. These results show that hypopituitarism in the absence of pituitary pathology or an identifiable cause is rare. In patients with multiple anterior pituitary hormone deficiencies haemochromatosis and sarcoidosis should be considered.

Glaucoma risk index: automated glaucoma detection from color fundus images.

PubMed

Bock, Rüdiger; Meier, Jörg; Nyúl, László G; Hornegger, Joachim; Michelson, Georg

2010-06-01

Glaucoma as a neurodegeneration of the optic nerve is one of the most common causes of blindness. Because revitalization of the degenerated nerve fibers of the optic nerve is impossible early detection of the disease is essential. This can be supported by a robust and automated mass-screening. We propose a novel automated glaucoma detection system that operates on inexpensive to acquire and widely used digital color fundus images. After a glaucoma specific preprocessing, different generic feature types are compressed by an appearance-based dimension reduction technique. Subsequently, a probabilistic two-stage classification scheme combines these features types to extract the novel Glaucoma Risk Index (GRI) that shows a reasonable glaucoma detection performance. On a sample set of 575 fundus images a classification accuracy of 80% has been achieved in a 5-fold cross-validation setup. The GRI gains a competitive area under ROC (AUC) of 88% compared to the established topography-based glaucoma probability score of scanning laser tomography with AUC of 87%. The proposed color fundus image-based GRI achieves a competitive and reliable detection performance on a low-priced modality by the statistical analysis of entire images of the optic nerve head. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Computer-assisted analysis of the vascular endothelial cell motile response to injury.

PubMed

Askey, D B; Herman, I M

1988-12-01

We have developed an automated, user-friendly method to track vascular endothelial cell migration in vitro using an IBM PC/XT with MS DOS. Analog phase-contrast images of the bovine aortic endothelial cells are converted into digital images (8 bit, 250 x 240 pixel resolution) using a Tecmar Video VanGogh A/D board. Digitized images are stored at selected time points following mechanical injury in vitro. FORTRAN and assembly language subroutines have been implemented to automatically detect the wound edge and the edge of each cell nucleus in the phase-contrast, light-microscope field. Detection of the wound edge is accomplished by intensity thresholding following noise reduction in the image and subsequent sampling of the wound. After the range of wound intensities is determined, the entire image is sampled and a histogram of intensities is formed. The histogram peak corresponding to the wound intensities is subtracted, leaving a histogram peak that gives the range of intensities corresponding to the cell nuclei. Rates of cell migration, as well as cellular trajectories and cell surface areas, can be automatically quantitated and analyzed. This inexpensive, automated cell-tracking system should be widely applicable in a variety of cell biologic applications.

Light Sheet Tomography (LST) for in situ imaging of plant roots.

PubMed

Yang, Zhengyi; Downie, Helen; Rozbicki, Emil; Dupuy, Lionel X; MacDonald, Michael P

2013-07-15

The production of crops capable of efficient nutrient use is essential for addressing the problem of global food security. The ability of a plant's root system to interact with the soil micro-environment determines how effectively it can extract water and nutrients. In order to assess this ability and develop the fast and cost effective phenotyping techniques which are needed to establish efficient root systems, in situ imaging in soil is required. To date this has not been possible due to the high density of scatterers and absorbers in soil or because other growth substrates do not sufficiently model the heterogeneity of a soil's microenvironment. We present here a new form of light sheet imaging with novel transparent soil containing refractive index matched particles. This imaging method does not rely on fluorescence, but relies solely on scattering from root material. We term this form of imaging Light Sheet Tomography (LST). We have tested LST on a range of materials and plant roots in transparent soil and gel. Due to the low density of root structures, i.e. relatively large spaces between adjacent roots, long-term monitoring of lettuce root development in situ with subsequent quantitative analysis was achieved.

Accelerating cine-MR Imaging in Mouse Hearts Using Compressed Sensing

PubMed Central

Wech, Tobias; Lemke, Angela; Medway, Debra; Stork, Lee-Anne; Lygate, Craig A; Neubauer, Stefan; Köstler, Herbert; Schneider, Jürgen E

2011-01-01

Purpose To combine global cardiac function imaging with compressed sensing (CS) in order to reduce scan time and to validate this technique in normal mouse hearts and in a murine model of chronic myocardial infarction. Materials and Methods To determine the maximally achievable acceleration factor, fully acquired cine data, obtained in sham and chronically infarcted (MI) mouse hearts were 2–4-fold undersampled retrospectively, followed by CS reconstruction and blinded image segmentation. Subsequently, dedicated CS sampling schemes were implemented at a preclinical 9.4 T magnetic resonance imaging (MRI) system, and 2- and 3-fold undersampled cine data were acquired in normal mouse hearts with high temporal and spatial resolution. Results The retrospective analysis demonstrated that an undersampling factor of three is feasible without impairing accuracy of cardiac functional parameters. Dedicated CS sampling schemes applied prospectively to normal mouse hearts yielded comparable left-ventricular functional parameters, and intra- and interobserver variability between fully and 3-fold undersampled data. Conclusion This study introduces and validates an alternative means to speed up experimental cine-MRI without the need for expensive hardware. J. Magn. Reson. Imaging 2011. © 2011 Wiley Periodicals, Inc. PMID:21932360

Automated 100-Position Specimen Loader and Image Acquisition System for Transmission Electron Microscopy

PubMed Central

Lefman, Jonathan; Morrison, Robert; Subramaniam, Sriram

2007-01-01

We report the development of a novel, multi-specimen imaging system for high-throughput transmission electron microscopy. Our cartridge-based loading system, called the “Gatling”, permits the sequential examination of as many as 100 specimens in the microscope for room temperature electron microscopy using mechanisms for rapid and automated specimen exchange. The software for the operation of the Gatling and automated data acquisition has been implemented in an updated version of our in-house program AutoEM. In the current implementation of the system, the time required to deliver 95 specimens into the microscope and collect overview images from each is about 13 hours. Regions of interest are identified from a low magnification atlas generation from each specimen and an unlimited number of higher magnifications images can be subsequently acquired from these regions using fully automated data acquisition procedures that can be controlled from a remote interface. We anticipate that the availability of the Gatling will greatly accelerate the speed of data acquisition for a variety of applications in biology, materials science and nanotechnology that require rapid screening and image analysis of multiple specimens. PMID:17240161

Optimization of Sample Preparation and Instrumental Parameters for the Rapid Analysis of Drugs of Abuse in Hair samples by MALDI-MS/MS Imaging

NASA Astrophysics Data System (ADS)

Flinders, Bryn; Beasley, Emma; Verlaan, Ricky M.; Cuypers, Eva; Francese, Simona; Bassindale, Tom; Clench, Malcolm R.; Heeren, Ron M. A.

2017-08-01

Matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) has been employed to rapidly screen longitudinally sectioned drug user hair samples for cocaine and its metabolites using continuous raster imaging. Optimization of the spatial resolution and raster speed were performed on intact cocaine contaminated hair samples. The optimized settings (100 × 150 μm at 0.24 mm/s) were subsequently used to examine longitudinally sectioned drug user hair samples. The MALDI-MS/MS images showed the distribution of the most abundant cocaine product ion at m/z 182. Using the optimized settings, multiple hair samples obtained from two users were analyzed in approximately 3 h: six times faster than the standard spot-to-spot acquisition method. Quantitation was achieved using longitudinally sectioned control hair samples sprayed with a cocaine dilution series. A multiple reaction monitoring (MRM) experiment was also performed using the `dynamic pixel' imaging method to screen for cocaine and a range of its metabolites, in order to differentiate between contaminated hairs and drug users. Cocaine, benzoylecgonine, and cocaethylene were detectable, in agreement with analyses carried out using the standard LC-MS/MS method. [Figure not available: see fulltext.

Context-based automated defect classification system using multiple morphological masks

DOEpatents

Gleason, Shaun S.; Hunt, Martin A.; Sari-Sarraf, Hamed

2002-01-01

Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact. At the heart of the system is a knowledge database that stores and distributes historical semiconductor wafer and defect data to guide the feature extraction and classification processes. In summary, this invention takes as its input a set of images containing semiconductor defect information, and generates as its output a classification for the defect that describes not only the defect itself, but also the location of that defect with respect to the semiconductor process layers.

Temporal assessment of radiomic features on clinical mammography in a high-risk population

NASA Astrophysics Data System (ADS)

Mendel, Kayla R.; Li, Hui; Lan, Li; Chan, Chun-Wai; King, Lauren M.; Tayob, Nabihah; Whitman, Gary; El-Zein, Randa; Bedrosian, Isabelle; Giger, Maryellen L.

2018-02-01

Extraction of high-dimensional quantitative data from medical images has become necessary in disease risk assessment, diagnostics and prognostics. Radiomic workflows for mammography typically involve a single medical image for each patient although medical images may exist for multiple imaging exams, especially in screening protocols. Our study takes advantage of the availability of mammograms acquired over multiple years for the prediction of cancer onset. This study included 841 images from 328 patients who developed subsequent mammographic abnormalities, which were confirmed as either cancer (n=173) or non-cancer (n=155) through diagnostic core needle biopsy. Quantitative radiomic analysis was conducted on antecedent FFDMs acquired a year or more prior to diagnostic biopsy. Analysis was limited to the breast contralateral to that in which the abnormality arose. Novel metrics were used to identify robust radiomic features. The most robust features were evaluated in the task of predicting future malignancies on a subset of 72 subjects (23 cancer cases and 49 non-cancer controls) with mammograms over multiple years. Using linear discriminant analysis, the robust radiomic features were merged into predictive signatures by: (i) using features from only the most recent contralateral mammogram, (ii) change in feature values between mammograms, and (iii) ratio of feature values over time, yielding AUCs of 0.57 (SE=0.07), 0.63 (SE=0.06), and 0.66 (SE=0.06), respectively. The AUCs for temporal radiomics (ratio) statistically differed from chance, suggesting that changes in radiomics over time may be critical for risk assessment. Overall, we found that our two-stage process of robustness assessment followed by performance evaluation served well in our investigation on the role of temporal radiomics in risk assessment.

Strain analysis in CRT candidates using the novel segment length in cine (SLICE) post-processing technique on standard CMR cine images.

PubMed

Zweerink, Alwin; Allaart, Cornelis P; Kuijer, Joost P A; Wu, LiNa; Beek, Aernout M; van de Ven, Peter M; Meine, Mathias; Croisille, Pierre; Clarysse, Patrick; van Rossum, Albert C; Nijveldt, Robin

2017-12-01

Although myocardial strain analysis is a potential tool to improve patient selection for cardiac resynchronization therapy (CRT), there is currently no validated clinical approach to derive segmental strains. We evaluated the novel segment length in cine (SLICE) technique to derive segmental strains from standard cardiovascular MR (CMR) cine images in CRT candidates. Twenty-seven patients with left bundle branch block underwent CMR examination including cine imaging and myocardial tagging (CMR-TAG). SLICE was performed by measuring segment length between anatomical landmarks throughout all phases on short-axis cines. This measure of frame-to-frame segment length change was compared to CMR-TAG circumferential strain measurements. Subsequently, conventional markers of CRT response were calculated. Segmental strains showed good to excellent agreement between SLICE and CMR-TAG (septum strain, intraclass correlation coefficient (ICC) 0.76; lateral wall strain, ICC 0.66). Conventional markers of CRT response also showed close agreement between both methods (ICC 0.61-0.78). Reproducibility of SLICE was excellent for intra-observer testing (all ICC ≥0.76) and good for interobserver testing (all ICC ≥0.61). The novel SLICE post-processing technique on standard CMR cine images offers both accurate and robust segmental strain measures compared to the 'gold standard' CMR-TAG technique, and has the advantage of being widely available. • Myocardial strain analysis could potentially improve patient selection for CRT. • Currently a well validated clinical approach to derive segmental strains is lacking. • The novel SLICE technique derives segmental strains from standard CMR cine images. • SLICE-derived strain markers of CRT response showed close agreement with CMR-TAG. • Future studies will focus on the prognostic value of SLICE in CRT candidates.

Use of high-resolution satellite images for detection of geological structures related to Central Andes geothermal field, Chile.

NASA Astrophysics Data System (ADS)

Benavides-Rivas, C. L.; Soto-Pinto, C. A.; Arellano-Baeza, A. A.

2014-12-01

Central valley and the border with Argentina in the center, and in the fault system Liquiñe-Ofqui in the South of the country. High resolution images from the LANDSAT 8 satellite have been used to delineate the geological structures related to the potential geothermal reservoirs located at the northern end of the Southern Volcanic Zone of Chile. It was done by applying the lineament extraction technique, using the ADALGEO software, developed by [Soto et al., 2013]. These structures have been compared with the distribution of main geological structures obtained in the field. It was found that the lineament density increases in the areas of the major heat flux indicating that the lineament analysis could be a power tool for the detection of faults and joint zones associated to the geothermal fields. A lineament is generally defined as a straight or slightly curved feature in the landscape visible satellite image as an aligned sequence of pixel intensity contrast compared to the background. The system features extracted from satellite images is not identical to the geological lineaments that are generally determined by ground surveys, however, generally reflects the structure of faults and fractures in the crust. A temporal sequence of eight Landsat multispectral images of Central Andes geothermal field, located in VI region de Chile, was used to study changes in the configuration of the lineaments during 2011. The presence of minerals with silicification, epidotization, and albitization, which are typical for geothrmal reservoirs, was also identified, using their spectral characteristics, and subsequently corroborated in the field. Both lineament analysis and spectral analysis gave similar location of the reservoir, which increases reliability of the results.

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography.

PubMed

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-09-01

Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography leading to underestimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multiresolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low-resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model, which may introduce artifacts in regions where no significant correlation exists between anatomical and functional details. A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present, the new model outperformed the 2D global approach, avoiding artifacts and significantly improving quality of the corrected images and their quantitative accuracy. A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multiresolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information.

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography

PubMed Central

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E.; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-01-01

Purpose Partial volume effects (PVE) are consequences of the limited spatial resolution in emission tomography leading to under-estimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multi-resolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model which may introduce artefacts in regions where no significant correlation exists between anatomical and functional details. Methods A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Results Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present the new model outperformed the 2D global approach, avoiding artefacts and significantly improving quality of the corrected images and their quantitative accuracy. Conclusions A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multi-resolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information. PMID:21978037

Effects of agmatine on blood-brain barrier stabilization assessed by permeability MRI in a rat model of transient cerebral ischemia.

PubMed

Ahn, S S; Kim, S H; Lee, J E; Ahn, K J; Kim, D J; Choi, H S; Kim, J; Shin, N-Y; Lee, S-K

2015-02-01

BBB disruption after acute ischemic stroke and subsequent permeability increase may be enhanced by reperfusion. Agmatine has been reported to attenuate BBB disruption. Our aim was to evaluate the effects of agmatine on BBB stabilization in a rat model of transient cerebral ischemia by using permeability dynamic contrast-enhanced MR imaging at early stages and subsequently to demonstrate the feasibility of dynamic contrast-enhanced MR imaging for the investigation of new therapies. Thirty-four male Sprague-Dawley rats were subjected to transient MCA occlusion for 90 minutes. Immediately after reperfusion, agmatine (100 mg/kg) or normal saline was injected intraperitoneally into the agmatine-treated group (n = 17) or the control group, respectively. MR imaging was performed after reperfusion. For quantitative analysis, regions of interest were defined within the infarct area, and values for volume transfer constant, rate transfer coefficient, volume fraction of extravascular extracellular space, and volume fraction of blood plasma were obtained. Infarct volume, infarct growth, quantitative imaging parameters, and numbers of factor VIII-positive cells after immunohistochemical staining were compared between control and agmatine-treated groups. Among the permeability parameters, volume transfer constant and volume fraction of extravascular extracellular space were significantly lower in the agmatine-treated group compared with the control group (0.05 ± 0.02 minutes(-1) versus 0.08 ± 0.03 minute(-1), P = .012, for volume transfer constant and 0.12 ± 0.06 versus 0.22 ± 0.15, P = .02 for volume fraction of extravascular extracellular space). Other permeability parameters were not significantly different between the groups. The number of factor VIII-positive cells was less in the agmatine-treated group than in the control group (3-fold versus 4-fold, P = .037). In ischemic stroke, agmatine protects the BBB, which can be monitored in vivo by quantification of permeability by using dynamic contrast-enhanced MR imaging. Therefore, dynamic contrast-enhanced MR imaging may serve as a potential imaging biomarker for assessing the BBB stabilization properties of pharmacologic agents. © 2015 by American Journal of Neuroradiology.

Boundary acquisition for setup of numerical simulation

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

Diegert, C.

1997-12-31

The author presents a work flow diagram that includes a path that begins with taking experimental measurements, and ends with obtaining insight from results produced by numerical simulation. Two examples illustrate this path: (1) Three-dimensional imaging measurement at micron scale, using X-ray tomography, provides information on the boundaries of irregularly-shaped alumina oxide particles held in an epoxy matrix. A subsequent numerical simulation predicts the electrical field concentrations that would occur in the observed particle configurations. (2) Three-dimensional imaging measurement at meter scale, again using X-ray tomography, provides information on the boundaries fossilized bone fragments in a Parasaurolophus crest recently discoveredmore » in New Mexico. A subsequent numerical simulation predicts acoustic response of the elaborate internal structure of nasal passageways defined by the fossil record. The author must both add value, and must change the format of the three-dimensional imaging measurements before the define the geometric boundary initial conditions for the automatic mesh generation, and subsequent numerical simulation. The author applies a variety of filters and statistical classification algorithms to estimate the extents of the structures relevant to the subsequent numerical simulation, and capture these extents as faceted geometries. The author will describe the particular combination of manual and automatic methods used in the above two examples.« less

Correlative imaging across microscopy platforms using the fast and accurate relocation of microscopic experimental regions (FARMER) method

NASA Astrophysics Data System (ADS)

Huynh, Toan; Daddysman, Matthew K.; Bao, Ying; Selewa, Alan; Kuznetsov, Andrey; Philipson, Louis H.; Scherer, Norbert F.

2017-05-01

Imaging specific regions of interest (ROIs) of nanomaterials or biological samples with different imaging modalities (e.g., light and electron microscopy) or at subsequent time points (e.g., before and after off-microscope procedures) requires relocating the ROIs. Unfortunately, relocation is typically difficult and very time consuming to achieve. Previously developed techniques involve the fabrication of arrays of features, the procedures for which are complex, and the added features can interfere with imaging the ROIs. We report the Fast and Accurate Relocation of Microscopic Experimental Regions (FARMER) method, which only requires determining the coordinates of 3 (or more) conspicuous reference points (REFs) and employs an algorithm based on geometric operators to relocate ROIs in subsequent imaging sessions. The 3 REFs can be quickly added to various regions of a sample using simple tools (e.g., permanent markers or conductive pens) and do not interfere with the ROIs. The coordinates of the REFs and the ROIs are obtained in the first imaging session (on a particular microscope platform) using an accurate and precise encoded motorized stage. In subsequent imaging sessions, the FARMER algorithm finds the new coordinates of the ROIs (on the same or different platforms), using the coordinates of the manually located REFs and the previously recorded coordinates. FARMER is convenient, fast (3-15 min/session, at least 10-fold faster than manual searches), accurate (4.4 μm average error on a microscope with a 100x objective), and precise (almost all errors are <8 μm), even with deliberate rotating and tilting of the sample well beyond normal repositioning accuracy. We demonstrate this versatility by imaging and re-imaging a diverse set of samples and imaging methods: live mammalian cells at different time points; fixed bacterial cells on two microscopes with different imaging modalities; and nanostructures on optical and electron microscopes. FARMER can be readily adapted to any imaging system with an encoded motorized stage and can facilitate multi-session and multi-platform imaging experiments in biology, materials science, photonics, and nanoscience.

A Novel Murine Model for Localized Radiation Necrosis and its Characterization Using Advanced Magnetic Resonance Imaging

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

Jost, Sarah C.; Hope, Andrew; Kiehl, Erich

Purpose: To develop a murine model of radiation necrosis using fractionated, subtotal cranial irradiation; and to investigate the imaging signature of radiation-induced tissue damage using advanced magnetic resonance imaging techniques. Methods and Materials: Twenty-four mice each received 60 Gy of hemispheric (left) irradiation in 10 equal fractions. Magnetic resonance images at 4.7 T were subsequently collected using T1-, T2-, and diffusion sequences at selected time points after irradiation. After imaging, animals were killed and their brains fixed for correlative histologic analysis. Results: Contrast-enhanced T1- and T2-weighted magnetic resonance images at months 2, 3, and 4 showed changes consistent with progressivemore » radiation necrosis. Quantitatively, mean diffusivity was significantly higher (mean = 0.86, 1.13, and 1.24 {mu}m{sup 2}/ms at 2, 3, and 4 months, respectively) in radiated brain, compared with contralateral untreated brain tissue (mean = 0.78, 0.82, and 0.83 {mu}m{sup 2}/ms) (p < 0.0001). Histology reflected changes typically seen in radiation necrosis. Conclusions: This murine model of radiation necrosis will facilitate investigation of imaging biomarkers that distinguish between radiation necrosis and tumor recurrence. In addition, this preclinical study supports clinical data suggesting that diffusion-weighted imaging may be helpful in answering this diagnostic question in clinical settings.« less

Measurement of glucose concentration by image processing of thin film slides

NASA Astrophysics Data System (ADS)

Piramanayagam, Sankaranaryanan; Saber, Eli; Heavner, David

2012-02-01

Measurement of glucose concentration is important for diagnosis and treatment of diabetes mellitus and other medical conditions. This paper describes a novel image-processing based approach for measuring glucose concentration. A fluid drop (patient sample) is placed on a thin film slide. Glucose, present in the sample, reacts with reagents on the slide to produce a color dye. The color intensity of the dye formed varies with glucose at different concentration levels. Current methods use spectrophotometry to determine the glucose level of the sample. Our proposed algorithm uses an image of the slide, captured at a specific wavelength, to automatically determine glucose concentration. The algorithm consists of two phases: training and testing. Training datasets consist of images at different concentration levels. The dye-occupied image region is first segmented using a Hough based technique and then an intensity based feature is calculated from the segmented region. Subsequently, a mathematical model that describes a relationship between the generated feature values and the given concentrations is obtained. During testing, the dye region of a test slide image is segmented followed by feature extraction. These two initial steps are similar to those done in training. However, in the final step, the algorithm uses the model (feature vs. concentration) obtained from the training and feature generated from test image to predict the unknown concentration. The performance of the image-based analysis was compared with that of a standard glucose analyzer.

Open framework for management and processing of multi-modality and multidimensional imaging data for analysis and modelling muscular function

NASA Astrophysics Data System (ADS)

García Juan, David; Delattre, Bénédicte M. A.; Trombella, Sara; Lynch, Sean; Becker, Matthias; Choi, Hon Fai; Ratib, Osman

2014-03-01

Musculoskeletal disorders (MSD) are becoming a big healthcare economical burden in developed countries with aging population. Classical methods like biopsy or EMG used in clinical practice for muscle assessment are invasive and not accurately sufficient for measurement of impairments of muscular performance. Non-invasive imaging techniques can nowadays provide effective alternatives for static and dynamic assessment of muscle function. In this paper we present work aimed toward the development of a generic data structure for handling n-dimensional metabolic and anatomical data acquired from hybrid PET/MR scanners. Special static and dynamic protocols were developed for assessment of physical and functional images of individual muscles of the lower limb. In an initial stage of the project a manual segmentation of selected muscles was performed on high-resolution 3D static images and subsequently interpolated to full dynamic set of contours from selected 2D dynamic images across different levels of the leg. This results in a full set of 4D data of lower limb muscles at rest and during exercise. These data can further be extended to a 5D data by adding metabolic data obtained from PET images. Our data structure and corresponding image processing extension allows for better evaluation of large volumes of multidimensional imaging data that are acquired and processed to generate dynamic models of the moving lower limb and its muscular function.

Lightning-channel morphology by return-stroke radiation field waveforms

NASA Technical Reports Server (NTRS)

Willett, J. C.; Le Vine, D. M.; Idone, V. P.

1995-01-01

Simultaneous video and wideband electric field recordings of 32 cloud-to-ground lightning flashes in Florida were analyzed to show the formation of new channels to ground can be detected by examination of the return-stroke radiation fields alone. The return-stroke E and dE/dt waveforms were subjectively classified according to their fine structure. Then the video images were examined field by field to identify each waveform with a visible channel to ground. Fifty-five correlated waveforms and channel images were obtained. Of these, all 34 first-stroke waveforms (multiple jagged E peaks, noisy dE/dt), 8 of which were not radiated by the chronologically first stroke in the flash, came from new channels to ground (not previously seen on video). All 18 subsequent-stroke waveforms (smoothly rounded E and quiet dE/dt after initial peak) were radiated by old channels (illuminated by a previous stroke). Two double-ground waveforms (two distinct first-return-stroke pulses separated by tens of microseconds or less) coincided with video fields showing two new channels. One `anomalous-stroke' waveform (beginning like a first stroke and ending like a subsequent) was produced by a new channel segment to ground branching off an old channel. This waveform classification depends on the presence or absence of high-frequency fine structure. Fourier analysis shows that first-stroke waveforms contain about 18 dB more spectral power in the frequency interval from 500 kHz to at least 7 MHz than subsequent-stroke waveforms for at least 13 microseconds after the main peak.

Role of biofilm roughness and hydrodynamic conditions in Legionella pneumophila adhesion to and detachment from simulated drinking water biofilms.

PubMed

Shen, Yun; Monroy, Guillermo L; Derlon, Nicolas; Janjaroen, Dao; Huang, Conghui; Morgenroth, Eberhard; Boppart, Stephen A; Ashbolt, Nicholas J; Liu, Wen-Tso; Nguyen, Thanh H

2015-04-07

Biofilms in drinking water distribution systems (DWDS) could exacerbate the persistence and associated risks of pathogenic Legionella pneumophila (L. pneumophila), thus raising human health concerns. However, mechanisms controlling adhesion and subsequent detachment of L. pneumophila associated with biofilms remain unclear. We determined the connection between L. pneumophila adhesion and subsequent detachment with biofilm physical structure characterization using optical coherence tomography (OCT) imaging technique. Analysis of the OCT images of multispecies biofilms grown under low nutrient condition up to 34 weeks revealed the lack of biofilm deformation even when these biofilms were exposed to flow velocity of 0.7 m/s, typical flow for DWDS. L. pneumophila adhesion on these biofilm under low flow velocity (0.007 m/s) positively correlated with biofilm roughness due to enlarged biofilm surface area and local flow conditions created by roughness asperities. The preadhered L. pneumophila on selected rough and smooth biofilms were found to detach when these biofilms were subjected to higher flow velocity. At the flow velocity of 0.1 and 0.3 m/s, the ratio of detached cell from the smooth biofilm surface was from 1.3 to 1.4 times higher than that from the rough biofilm surface, presumably because of the low shear stress zones near roughness asperities. This study determined that physical structure and local hydrodynamics control L. pneumophila adhesion to and detachment from simulated drinking water biofilm, thus it is the first step toward reducing the risk of L. pneumophila exposure and subsequent infections.

Identification of nodal tissue in the living heart using rapid scanning fiber-optics confocal microscopy and extracellular fluorophores.

PubMed

Huang, Chao; Kaza, Aditya K; Hitchcock, Robert W; Sachse, Frank B

2013-09-01

Risks associated with pediatric reconstructive heart surgery include injury of the sinoatrial node (SAN) and atrioventricular node (AVN), requiring cardiac rhythm management using implantable pacemakers. These injuries are the result of difficulties in identifying nodal tissues intraoperatively. Here we describe an approach based on confocal microscopy and extracellular fluorophores to quantify tissue microstructure and identify nodal tissue. Using conventional 3-dimensional confocal microscopy we investigated the microstructural arrangement of SAN, AVN, and atrial working myocardium (AWM) in fixed rat heart. AWM exhibited a regular striated arrangement of the extracellular space. In contrast, SAN and AVN had an irregular, reticulated arrangement. AWM, SAN, and AVN tissues were beneath a thin surface layer of tissue that did not obstruct confocal microscopic imaging. Subsequently, we imaged tissues in living rat hearts with real-time fiber-optics confocal microscopy. Fiber-optics confocal microscopy images resembled images acquired with conventional confocal microscopy. We investigated spatial regularity of tissue microstructure from Fourier analysis and second-order image moments. Fourier analysis of fiber-optics confocal microscopy images showed that the spatial regularity of AWM was greater than that of nodal tissues (37.5 ± 5.0% versus 24.3 ± 3.9% for SAN and 23.8 ± 3.7% for AVN; P<0.05). Similar differences of spatial regularities were revealed from second-order image moments (50.0 ± 7.3% for AWM versus 29.3 ± 6.7% for SAN and 27.3 ± 5.5% for AVN; P<0.05). The study demonstrates feasibility of identifying nodal tissue in living heart using extracellular fluorophores and fiber-optics confocal microscopy. Application of the approach in pediatric reconstructive heart surgery may reduce risks of injuring nodal tissues.

Multi-scale Gaussian representation and outline-learning based cell image segmentation.

PubMed

Farhan, Muhammad; Ruusuvuori, Pekka; Emmenlauer, Mario; Rämö, Pauli; Dehio, Christoph; Yli-Harja, Olli

2013-01-01

High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks.

Multi-scale Gaussian representation and outline-learning based cell image segmentation

PubMed Central

2013-01-01

Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

A comparison of diagnostic imaging ordering patterns between advanced practice clinicians and primary care physicians following office-based evaluation and management visits.

PubMed

Hughes, Danny R; Jiang, Miao; Duszak, Richard

2015-01-01

Little is known about the use of diagnostic testing, such as medical imaging, by advanced practice clinicians (APCs), specifically, nurse practitioners and physician assistants. To examine the use of diagnostic imaging ordered by APCs relative to that of primary care physicians (PCPs) following office-based encounters. Using 2010-2011 Medicare claims for a 5% sample of beneficiaries, we compared diagnostic imaging ordering between APC and PCP episodes of care, controlling for geographic variation, patient demographics, and Charlson Comorbidity Index scores. Provider specialty codes were used to identify PCPs and APCs (general practice, family practice, or internal medicine for PCP; nurse practitioner or physician assistant for APC). Episodes were constructed using evaluation and management (E&M) office visits without any claims 30 days prior to the index visit and (1) no claims at all within the subsequent 30 days; (2) no claims within the subsequent 30 days other than a single imaging event; or (3) claims for any nonimaging services in that subsequent 30-day period. The primary outcome was whether an imaging event followed a qualifying E&M visit. Advanced practice clinicians and PCPs ordered imaging in 2.8% and 1.9% episodes of care, respectively. In adjusted estimates and across all patient groups and imaging services, APCs were associated with more imaging than PCPs (odds ratio [OR], 1.34 [95% CI, 1.27-1.42]), ordering 0.3% more images per episode. Advanced practice clinicians were associated with increased radiography orders on both new (OR, 1.36 [95% CI, 1.13-1.66]) and established (OR, 1.33 [95% CI, 1.24-1.43]) patients, ordering 0.3% and 0.2% more images per episode of care, respectively. For advanced imaging, APCs were associated with increased imaging on established patients (OR, 1.28 [95% CI, 1.14-1.44]), ordering 0.1% more images, but were not significantly different from PCPs ordering imaging on new patients. Advanced practice clinicians are associated with more imaging services than PCPs for similar patients during E&M office visits. Expanding the use of APCs may alleviate PCP shortages. While increased use of imaging appears modest for individual patients, this increase may have ramifications on care and overall costs at the population level.

Rapid detection of bacterial contamination in cell or tissue cultures based on Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bolwien, Carsten; Sulz, Gerd; Becker, Sebastian; Thielecke, Hagen; Mertsching, Heike; Koch, Steffen

2008-02-01

Monitoring the sterility of cell or tissue cultures is an essential task, particularly in the fields of regenerative medicine and tissue engineering when implanting cells into the human body. We present a system based on a commercially available microscope equipped with a microfluidic cell that prepares the particles found in the solution for analysis, a Raman-spectrometer attachment optimized for non-destructive, rapid recording of Raman spectra, and a data acquisition and analysis tool for identification of the particles. In contrast to conventional sterility testing in which samples are incubated over weeks, our system is able to analyze milliliters of supernatant or cell suspension within hours by filtering relevant particles and placing them on a Raman-friendly substrate in the microfluidic cell. Identification of critical particles via microscopic imaging and subsequent image analysis is carried out before micro-Raman analysis of those particles is then carried out with an excitation wavelength of 785 nm. The potential of this setup is demonstrated by results of artificial contamination of samples with a pool of bacteria, fungi, and spores: single-channel spectra of the critical particles are automatically baseline-corrected without using background data and classified via hierarchical cluster analysis, showing great promise for accurate and rapid detection and identification of contaminants.

Computer-aided boundary delineation of agricultural lands

NASA Technical Reports Server (NTRS)

Cheng, Thomas D.; Angelici, Gary L.; Slye, Robert E.; Ma, Matt

1989-01-01

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were.

Spin echo SPI methods for quantitative analysis of fluids in porous media.

PubMed

Li, Linqing; Han, Hui; Balcom, Bruce J

2009-06-01

Fluid density imaging is highly desirable in a wide variety of porous media measurements. The SPRITE class of MRI methods has proven to be robust and general in their ability to generate density images in porous media, however the short encoding times required, with correspondingly high magnetic field gradient strengths and filter widths, and low flip angle RF pulses, yield sub-optimal S/N images, especially at low static field strength. This paper explores two implementations of pure phase encode spin echo 1D imaging, with application to a proposed new petroleum reservoir core analysis measurement. In the first implementation of the pulse sequence, we modify the spin echo single point imaging (SE-SPI) technique to acquire the k-space origin data point, with a near zero evolution time, from the free induction decay (FID) following a 90 degrees excitation pulse. Subsequent k-space data points are acquired by separately phase encoding individual echoes in a multi-echo acquisition. T(2) attenuation of the echo train yields an image convolution which causes blurring. The T(2) blur effect is moderate for porous media with T(2) lifetime distributions longer than 5 ms. As a robust, high S/N, and fast 1D imaging method, this method will be highly complementary to SPRITE techniques for the quantitative analysis of fluid content in porous media. In the second implementation of the SE-SPI pulse sequence, modification of the basic measurement permits fast determination of spatially resolved T(2) distributions in porous media through separately phase encoding each echo in a multi-echo CPMG pulse train. An individual T(2) weighted image may be acquired from each echo. The echo time (TE) of each T(2) weighted image may be reduced to 500 micros or less. These profiles can be fit to extract a T(2) distribution from each pixel employing a variety of standard inverse Laplace transform methods. Fluid content 1D images are produced as an essential by product of determining the spatially resolved T(2) distribution. These 1D images do not suffer from a T(2) related blurring. The above SE-SPI measurements are combined to generate 1D images of the local saturation and T(2) distribution as a function of saturation, upon centrifugation of petroleum reservoir core samples. The logarithm mean T(2) is observed to shift linearly with water saturation. This new reservoir core analysis measurement may provide a valuable calibration of the Coates equation for irreducible water saturation, which has been widely implemented in NMR well logging measurements.

Improving Landslide Susceptibility Modeling Using an Empirical Threshold Scheme for Excluding Landslide Deposition

NASA Astrophysics Data System (ADS)

Tsai, F.; Lai, J. S.; Chiang, S. H.

2015-12-01

Landslides are frequently triggered by typhoons and earthquakes in Taiwan, causing serious economic losses and human casualties. Remotely sensed images and geo-spatial data consisting of land-cover and environmental information have been widely used for producing landslide inventories and causative factors for slope stability analysis. Landslide susceptibility, on the other hand, can represent the spatial likelihood of landslide occurrence and is an important basis for landslide risk assessment. As multi-temporal satellite images become popular and affordable, they are commonly used to generate landslide inventories for subsequent analysis. However, it is usually difficult to distinguish different landslide sub-regions (scarp, debris flow, deposition etc.) directly from remote sensing imagery. Consequently, the extracted landslide extents using image-based visual interpretation and automatic detections may contain many depositions that may reduce the fidelity of the landslide susceptibility model. This study developed an empirical thresholding scheme based on terrain characteristics for eliminating depositions from detected landslide areas to improve landslide susceptibility modeling. In this study, Bayesian network classifier is utilized to build a landslide susceptibility model and to predict sequent rainfall-induced shallow landslides in the Shimen reservoir watershed located in northern Taiwan. Eleven causative factors are considered, including terrain slope, aspect, curvature, elevation, geology, land-use, NDVI, soil, distance to fault, river and road. Landslide areas detected using satellite images acquired before and after eight typhoons between 2004 to 2008 are collected as the main inventory for training and verification. In the analysis, previous landslide events are used as training data to predict the samples of the next event. The results are then compared with recorded landslide areas in the inventory to evaluate the accuracy. Experimental results demonstrate that the accuracies of landslide susceptibility analysis in all sequential predictions have been improved significantly after eliminating landslide depositions.

Nondestructive cryomicro-CT imaging enables structural and molecular analysis of human lung tissue.

PubMed

Vasilescu, Dragoş M; Phillion, André B; Tanabe, Naoya; Kinose, Daisuke; Paige, David F; Kantrowitz, Jacob J; Liu, Gang; Liu, Hanqiao; Fishbane, Nick; Verleden, Stijn E; Vanaudenaerde, Bart M; Lenburg, Marc; Stevenson, Christopher S; Spira, Avrum; Cooper, Joel D; Hackett, Tillie-Louise; Hogg, James C

2017-01-01

Micro-computed tomography (CT) enables three-dimensional (3D) imaging of complex soft tissue structures, but current protocols used to achieve this goal preclude cellular and molecular phenotyping of the tissue. Here we describe a radiolucent cryostage that permits micro-CT imaging of unfixed frozen human lung samples at an isotropic voxel size of (11 µm) 3 under conditions where the sample is maintained frozen at -30°C during imaging. The cryostage was tested for thermal stability to maintain samples frozen up to 8 h. This report describes the methods used to choose the materials required for cryostage construction and demonstrates that whole genome mRNA integrity and expression are not compromised by exposure to micro-CT radiation and that the tissue can be used for immunohistochemistry. The new cryostage provides a novel method enabling integration of 3D tissue structure with cellular and molecular analysis to facilitate the identification of molecular determinants of disease. The described micro-CT cryostage provides a novel way to study the three-dimensional lung structure preserved without the effects of fixatives while enabling subsequent studies of the cellular matrix composition and gene expression. This approach will, for the first time, enable researchers to study structural changes of lung tissues that occur with disease and correlate them with changes in gene or protein signatures. Copyright © 2017 the American Physiological Society.

Chapter 17: Bioimage Informatics for Systems Pharmacology

PubMed Central

Li, Fuhai; Yin, Zheng; Jin, Guangxu; Zhao, Hong; Wong, Stephen T. C.

2013-01-01

Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from conventional microscopy studies on a few cells, and could provide stronger statistical power for drawing experimental observations and conclusions. However, it is challenging to manually extract and quantify phenotypic changes from the large amounts of complex image data generated. Thus, bioimage informatics approaches are needed to rapidly and objectively quantify and analyze the image data. This paper provides an overview of the bioimage informatics challenges and approaches in image-based studies for drug and target discovery. The concepts and capabilities of image-based screening are first illustrated by a few practical examples investigating different kinds of phenotypic changes caEditorsused by drugs, compounds, or RNAi. The bioimage analysis approaches, including object detection, segmentation, and tracking, are then described. Subsequently, the quantitative features, phenotype identification, and multidimensional profile analysis for profiling the effects of drugs and targets are summarized. Moreover, a number of publicly available software packages for bioimage informatics are listed for further reference. It is expected that this review will help readers, including those without bioimage informatics expertise, understand the capabilities, approaches, and tools of bioimage informatics and apply them to advance their own studies. PMID:23633943

Object representations in ventral and dorsal visual streams: fMRI repetition effects depend on attention and part–whole configuration

PubMed Central

Thoma, Volker; Henson, Richard N.

2011-01-01

The effects of attention and object configuration on the neural responses to short-lag visual image repetition were investigated with fMRI. Attention to one of two object images in a prime display was cued spatially. The images were either intact or split vertically; a manipulation that negates the influence of view-based representations. A subsequent single intact probe image was named covertly. Behavioural priming observed as faster button presses was found for attended primes in both intact and split configurations, but only for uncued primes in the intact configuration. In a voxel-wise analysis, fMRI repetition suppression (RS) was observed in a left mid-fusiform region for attended primes, both intact and split, whilst a right intraparietal region showed repetition enhancement (RE) for intact primes, regardless of attention. In a factorial analysis across regions of interest (ROIs) defined from independent localiser contrasts, RS for attended objects in the ventral stream was significantly left-lateralised, whilst repetition effects in ventral and dorsal ROIs correlated with the amount of priming in specific conditions. These fMRI results extend hybrid theories of object recognition, implicating left ventral stream regions in analytic processing (requiring attention), consistent with prior hypotheses about hemispheric specialisation, and implicating dorsal stream regions in holistic processing (independent of attention). PMID:21554967

Image segmentation and registration for the analysis of joint motion from 3D MRI

NASA Astrophysics Data System (ADS)

Hu, Yangqiu; Haynor, David R.; Fassbind, Michael; Rohr, Eric; Ledoux, William

2006-03-01

We report an image segmentation and registration method for studying joint morphology and kinematics from in vivo MRI scans and its application to the analysis of ankle joint motion. Using an MR-compatible loading device, a foot was scanned in a single neutral and seven dynamic positions including maximal flexion, rotation and inversion/eversion. A segmentation method combining graph cuts and level sets was developed which allows a user to interactively delineate 14 bones in the neutral position volume in less than 30 minutes total, including less than 10 minutes of user interaction. In the subsequent registration step, a separate rigid body transformation for each bone is obtained by registering the neutral position dataset to each of the dynamic ones, which produces an accurate description of the motion between them. We have processed six datasets, including 3 normal and 3 pathological feet. For validation our results were compared with those obtained from 3DViewnix, a semi-automatic segmentation program, and achieved good agreement in volume overlap ratios (mean: 91.57%, standard deviation: 3.58%) for all bones. Our tool requires only 1/50 and 1/150 of the user interaction time required by 3DViewnix and NIH Image Plus, respectively, an improvement that has the potential to make joint motion analysis from MRI practical in research and clinical applications.

Technical advance: live-imaging analysis of human dendritic cell migrating behavior under the influence of immune-stimulating reagents in an organotypic model of lung.

PubMed

Nguyen Hoang, Anh Thu; Chen, Puran; Björnfot, Sofia; Högstrand, Kari; Lock, John G; Grandien, Alf; Coles, Mark; Svensson, Mattias

2014-09-01

This manuscript describes technical advances allowing manipulation and quantitative analyses of human DC migratory behavior in lung epithelial tissue. DCs are hematopoietic cells essential for the maintenance of tissue homeostasis and the induction of tissue-specific immune responses. Important functions include cytokine production and migration in response to infection for the induction of proper immune responses. To design appropriate strategies to exploit human DC functional properties in lung tissue for the purpose of clinical evaluation, e.g., candidate vaccination and immunotherapy strategies, we have developed a live-imaging assay based on our previously described organotypic model of the human lung. This assay allows provocations and subsequent quantitative investigations of DC functional properties under conditions mimicking morphological and functional features of the in vivo parental tissue. We present protocols to set up and prepare tissue models for 4D (x, y, z, time) fluorescence-imaging analysis that allow spatial and temporal studies of human DCs in live epithelial tissue, followed by flow cytometry analysis of DCs retrieved from digested tissue models. This model system can be useful for elucidating incompletely defined pathways controlling DC functional responses to infection and inflammation in lung epithelial tissue, as well as the efficacy of locally administered candidate interventions. © 2014 Society for Leukocyte Biology.

Application of Six Sigma methodology to a diagnostic imaging process.

PubMed

Taner, Mehmet Tolga; Sezen, Bulent; Atwat, Kamal M

2012-01-01

This paper aims to apply the Six Sigma methodology to improve workflow by eliminating the causes of failure in the medical imaging department of a private Turkish hospital. Implementation of the design, measure, analyse, improve and control (DMAIC) improvement cycle, workflow chart, fishbone diagrams and Pareto charts were employed, together with rigorous data collection in the department. The identification of root causes of repeat sessions and delays was followed by failure, mode and effect analysis, hazard analysis and decision tree analysis. The most frequent causes of failure were malfunction of the RIS/PACS system and improper positioning of patients. Subsequent to extensive training of professionals, the sigma level was increased from 3.5 to 4.2. The data were collected over only four months. Six Sigma's data measurement and process improvement methodology is the impetus for health care organisations to rethink their workflow and reduce malpractice. It involves measuring, recording and reporting data on a regular basis. This enables the administration to monitor workflow continuously. The improvements in the workflow under study, made by determining the failures and potential risks associated with radiologic care, will have a positive impact on society in terms of patient safety. Having eliminated repeat examinations, the risk of being exposed to more radiation was also minimised. This paper supports the need to apply Six Sigma and present an evaluation of the process in an imaging department.

Non-destructive evaluation of polymer coating structures on pharmaceutical pellets using full-field optical coherence tomography.

PubMed

Li, Chen; Zeitler, J Axel; Dong, Yue; Shen, Yao-Chun

2014-01-01

Full-field optical coherence tomography (FF-OCT) using a conventional light-emitting diode and a complementary metal-oxide semiconductor camera has been developed for characterising coatings on small pellet samples. A set of en-face images covering an area of 700 × 700 μm(2) was taken over a depth range of 166 μm. The three-dimensional structural information, such as the coating thickness and uniformity, was subsequently obtained by analysis of the recorded en-face images. Drug-loaded pharmaceutical sustained-release pellets with two coating layers and of a sub-millimetre diameter were studied to demonstrate the usefulness of the developed system. We have shown that both coatings can be clearly resolved and the thickness was determined to be 40 and 50 μm for the outer and inner coating layers, respectively. It was also found that the outer coating layer is relatively uniform, whereas the inner coating layer has many particle-like features. X-ray computed microtomography measurements carried out on the same pellet sample confirmed all these findings. The presented FF-OCT approach is inexpensive and has better spatial resolution compared with other non-destructive analysis techniques such as terahertz pulsed imaging, and is thus considered advantageous for the quantitative analysis of thin coatings on small pellet samples. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

One-stop-shop stroke imaging with functional CT.

PubMed

Tong, Elizabeth; Komlosi, Peter; Wintermark, Max

2015-12-01

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

Development of Software to Digitize Historic Hardcopy Seismograms from Nuclear Explosions

DTIC Science & Technology

2010-09-01

portion. As will be discussed below, this complicates the preparation of the image for subsequent digitization because background threshold values are...is the output image and  −1 < β ≤ 0 is a user selectable parameter. Global contrast enhancement uses a whitening transform to make a given image

fMRI evidence for areas that process surface gloss in the human visual cortex

PubMed Central

Sun, Hua-Chun; Ban, Hiroshi; Di Luca, Massimiliano; Welchman, Andrew E.

2015-01-01

Surface gloss is an important cue to the material properties of objects. Recent progress in the study of macaque’s brain has increased our understating of the areas involved in processing information about gloss, however the homologies with the human brain are not yet fully understood. Here we used human functional magnetic resonance imaging (fMRI) measurements to localize brain areas preferentially responding to glossy objects. We measured cortical activity for thirty-two rendered three-dimensional objects that had either Lambertian or specular surface properties. To control for differences in image structure, we overlaid a grid on the images and scrambled its cells. We found activations related to gloss in the posterior fusiform sulcus (pFs) and in area V3B/KO. Subsequent analysis with Granger causality mapping indicated that V3B/KO processes gloss information differently than pFs. Our results identify a small network of mid-level visual areas whose activity may be important in supporting the perception of surface gloss. PMID:25490434

Nanotechnology in Glycomics: Applications in Diagnostics, Therapy, Imaging, and Separation Processes

PubMed Central

Dosekova, Erika; Filip, Jaroslav; Bertok, Tomas; Both, Peter; Kasak, Peter; Tkac, Jan

2017-01-01

This review comprehensively covers the most recent achievements (from 2013) in the successful integration of nanomaterials in the field of glycomics. The first part of the paper addresses the beneficial properties of nanomaterials for the construction of biosensors, bioanalytical devices, and protocols for the detection of various analytes, including viruses and whole cells, together with their key characteristics. The second part of the review focuses on the application of nanomaterials integrated with glycans for various biomedical applications, that is, vaccines against viral and bacterial infections and cancer cells, as therapeutic agents, for in vivo imaging and nuclear magnetic resonance imaging, and for selective drug delivery. The final part of the review describes various ways in which glycan enrichment can be effectively done using nanomaterials, molecularly imprinted polymers with polymer thickness controlled at the nanoscale, with a subsequent analysis of glycans by mass spectrometry. A short section describing an active glycoprofiling by microengines (microrockets) is covered as well. PMID:27859448

Nanotechnology in Glycomics: Applications in Diagnostics, Therapy, Imaging, and Separation Processes.

PubMed

Dosekova, Erika; Filip, Jaroslav; Bertok, Tomas; Both, Peter; Kasak, Peter; Tkac, Jan

2017-05-01

This review comprehensively covers the most recent achievements (from 2013) in the successful integration of nanomaterials in the field of glycomics. The first part of the paper addresses the beneficial properties of nanomaterials for the construction of biosensors, bioanalytical devices, and protocols for the detection of various analytes, including viruses and whole cells, together with their key characteristics. The second part of the review focuses on the application of nanomaterials integrated with glycans for various biomedical applications, that is, vaccines against viral and bacterial infections and cancer cells, as therapeutic agents, for in vivo imaging and nuclear magnetic resonance imaging, and for selective drug delivery. The final part of the review describes various ways in which glycan enrichment can be effectively done using nanomaterials, molecularly imprinted polymers with polymer thickness controlled at the nanoscale, with a subsequent analysis of glycans by mass spectrometry. A short section describing an active glycoprofiling by microengines (microrockets) is covered as well. © 2016 Wiley Periodicals, Inc.

Multimodal evaluation of ultra-short laser pulses treatment for skin burn injuries.

PubMed

Santos, Moises Oliveira Dos; Latrive, Anne; De Castro, Pedro Arthur Augusto; De Rossi, Wagner; Zorn, Telma Maria Tenorio; Samad, Ricardo Elgul; Freitas, Anderson Zanardi; Cesar, Carlos Lenz; Junior, Nilson Dias Vieira; Zezell, Denise Maria

2017-03-01

Thousands of people die every year from burn injuries. The aim of this study is to evaluate the feasibility of high intensity femtosecond lasers as an auxiliary treatment of skin burns. We used an in vivo animal model and monitored the healing process using 4 different imaging modalities: histology, Optical Coherence Tomography (OCT), Second Harmonic Generation (SHG), and Fourier Transform Infrared (FTIR) spectroscopy. 3 dorsal areas of 20 anesthetized Wistar rats were burned by water vapor exposure and subsequently treated either by classical surgical debridement, by laser ablation, or left without treatment. Skin burn tissues were non-invasively characterized by OCT images and biopsied for further histopathology analysis, SHG imaging and FTIR spectroscopy at 3, 5, 7 and 14 days after burn. The laser protocol was found as efficient as the classical treatment for promoting the healing process. The study concludes to the validation of femtosecond ultra-short pulses laser treatment for skinburns, with the advantage of minimizing operatory trauma.

Characterizing the response of a scintillator-based detector to single electrons.

PubMed

Sang, Xiahan; LeBeau, James M

2016-02-01

Here we report the response of a high angle annular dark field scintillator-based detector to single electrons. We demonstrate that care must be taken when determining the single electron intensity as significant discrepancies can occur when quantifying STEM images with different methods. To account for the detector response, we first image the detector using very low beam currents (∼8fA), and subsequently model the interval between consecutive single electrons events. We find that single electrons striking the detector present a wide distribution of intensities, which we show is not described by a simple function. Further, we present a method to accurately account for the electrons within the incident probe when conducting quantitative imaging. The role detector settings play on determining the single electron intensity is also explored. Finally, we extend our analysis to describe the response of the detector to multiple electron events within the dwell interval of each pixel. Copyright © 2015 Elsevier B.V. All rights reserved.

USGS remote sensing coordination for the 2010 Haiti earthquake

USGS Publications Warehouse

Duda, Kenneth A.; Jones, Brenda

2011-01-01

In response to the devastating 12 January 2010, earthquake in Haiti, the US Geological Survey (USGS) provided essential coordinating services for remote sensing activities. Communication was rapidly established between the widely distributed response teams and data providers to define imaging requirements and sensor tasking opportunities. Data acquired from a variety of sources were received and archived by the USGS, and these products were subsequently distributed using the Hazards Data Distribution System (HDDS) and other mechanisms. Within six weeks after the earthquake, over 600,000 files representing 54 terabytes of data were provided to the response community. The USGS directly supported a wide variety of groups in their use of these data to characterize post-earthquake conditions and to make comparisons with pre-event imagery. The rapid and continuing response achieved was enabled by existing imaging and ground systems, and skilled personnel adept in all aspects of satellite data acquisition, processing, distribution and analysis. The information derived from image interpretation assisted senior planners and on-site teams to direct assistance where it was most needed.

3D confocal Raman imaging of oil-rich emulsion from enzyme-assisted aqueous extraction of extruded soybean powder.

PubMed

Wu, Longkun; Wang, Limin; Qi, Baokun; Zhang, Xiaonan; Chen, Fusheng; Li, Yang; Sui, Xiaonan; Jiang, Lianzhou

2018-05-30

The understanding of the structure morphology of oil-rich emulsion from enzyme-assisted extraction processing (EAEP) was a critical step to break the oil-rich emulsion structure in order to recover oil. Albeit EAEP method has been applied as an alternative way to conventional solvent extraction method, the structure morphology of oil-rich emulsion was still unclear. The current study aimed to investigate the structure morphology of oil-rich emulsion from EAEP using 3D confocal Raman imaging technique. With increasing the enzymatic hydrolysis duration from 1 to 3 h, the stability of oil-rich emulsion was decreased as visualized in the 3D confocal Raman images that the protein and oil were mixed together. The subsequent Raman spectrum analysis further revealed that the decreased stability of oil-rich emulsion was due to the protein aggregations via SS bonds or protein-lipid interactions. The conformational transfer in protein indicated the formation of a compact structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Magnetic resonance imaging and image analysis for assessment of HPMC matrix tablets structural evolution in USP Apparatus 4.

PubMed

Kulinowski, Piotr; Dorożyński, Przemysław; Młynarczyk, Anna; Węglarz, Władysław P

2011-05-01

The purpose of the study was to present a methodology for the processing of Magnetic Resonance Imaging (MRI) data for the quantification of the dosage form matrix evolution during drug dissolution. The results of the study were verified by comparison with other approaches presented in literature. A commercially available, HPMC-based quetiapine fumarate tablet was studied with a 4.7T MR system. Imaging was performed inside an MRI probe-head coupled with a flow-through cell for 12 h in circulating water. The images were segmented into three regions using threshold-based segmentation algorithms due to trimodal structure of the image intensity histograms. Temporal evolution of dry glassy, swollen glassy and gel regions was monitored. The characteristic features were observed: initial high expansion rate of the swollen glassy and gel layers due to initial water uptake, dry glassy core disappearance and maximum area of swollen glassy region at 4 h, and subsequent gel layer thickness increase at the expense of swollen glassy layer. The temporal evolution of an HPMC-based tablet by means of noninvasive MRI integrated with USP Apparatus 4 was found to be consistent with both the theoretical model based on polymer disentanglement concentration and experimental VIS/FTIR studies.

A correlative approach for combining microCT, light and transmission electron microscopy in a single 3D scenario

PubMed Central

2013-01-01

Background In biomedical research, a huge variety of different techniques is currently available for the structural examination of small specimens, including conventional light microscopy (LM), transmission electron microscopy (TEM), confocal laser scanning microscopy (CLSM), microscopic X-ray computed tomography (microCT), and many others. Since every imaging method is physically limited by certain parameters, a correlative use of complementary methods often yields a significant broader range of information. Here we demonstrate the advantages of the correlative use of microCT, light microscopy, and transmission electron microscopy for the analysis of small biological samples. Results We used a small juvenile bivalve mollusc (Mytilus galloprovincialis, approximately 0.8 mm length) to demonstrate the workflow of a correlative examination by microCT, LM serial section analysis, and TEM-re-sectioning. Initially these three datasets were analyzed separately, and subsequently they were fused in one 3D scene. This workflow is very straightforward. The specimen was processed as usual for transmission electron microscopy including post-fixation in osmium tetroxide and embedding in epoxy resin. Subsequently it was imaged with microCT. Post-fixation in osmium tetroxide yielded sufficient X-ray contrast for microCT imaging, since the X-ray absorption of epoxy resin is low. Thereafter, the same specimen was serially sectioned for LM investigation. The serial section images were aligned and specific organ systems were reconstructed based on manual segmentation and surface rendering. According to the region of interest (ROI), specific LM sections were detached from the slides, re-mounted on resin blocks and re-sectioned (ultrathin) for TEM. For analysis, image data from the three different modalities was co-registered into a single 3D scene using the software AMIRA®. We were able to register both the LM section series volume and TEM slices neatly to the microCT dataset, with small geometric deviations occurring only in the peripheral areas of the specimen. Based on co-registered datasets the excretory organs, which were chosen as ROI for this study, could be investigated regarding both their ultrastructure as well as their position in the organism and their spatial relationship to adjacent tissues. We found structures typical for mollusc excretory systems, including ultrafiltration sites at the pericardial wall, and ducts leading from the pericardium towards the kidneys, which exhibit a typical basal infolding system. Conclusions The presented approach allows a comprehensive analysis and presentation of small objects regarding both the overall organization as well as cellular and subcellular details. Although our protocol involves a variety of different equipment and procedures, we maintain that it offers savings in both effort and cost. Co-registration of datasets from different imaging modalities can be accomplished with high-end desktop computers and offers new opportunities for understanding and communicating structural relationships within organisms and tissues. In general, the correlative use of different microscopic imaging techniques will continue to become more widespread in morphological and structural research in zoology. Classical TEM serial section investigations are extremely time consuming, and modern methods for 3D analysis of ultrastructure such as SBF-SEM and FIB-SEM are limited to very small volumes for examination. Thus the re-sectioning of LM sections is suitable for speeding up TEM examination substantially, while microCT could become a key-method for complementing ultrastructural examinations. PMID:23915384

Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Belkić, Dževad; Belkić, Karen

2018-01-01

This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

Extraction of latent images from printed media

NASA Astrophysics Data System (ADS)

Sergeyev, Vladislav; Fedoseev, Victor

2015-12-01

In this paper we propose an automatic technology for extraction of latent images from printed media such as documents, banknotes, financial securities, etc. This technology includes image processing by adaptively constructed Gabor filter bank for obtaining feature images, as well as subsequent stages of feature selection, grouping and multicomponent segmentation. The main advantage of the proposed technique is versatility: it allows to extract latent images made by different texture variations. Experimental results showing performance of the method over another known system for latent image extraction are given.

Poisson-event-based analysis of cell proliferation.

PubMed

Summers, Huw D; Wills, John W; Brown, M Rowan; Rees, Paul

2015-05-01

A protocol for the assessment of cell proliferation dynamics is presented. This is based on the measurement of cell division events and their subsequent analysis using Poisson probability statistics. Detailed analysis of proliferation dynamics in heterogeneous populations requires single cell resolution within a time series analysis and so is technically demanding to implement. Here, we show that by focusing on the events during which cells undergo division rather than directly on the cells themselves a simplified image acquisition and analysis protocol can be followed, which maintains single cell resolution and reports on the key metrics of cell proliferation. The technique is demonstrated using a microscope with 1.3 μm spatial resolution to track mitotic events within A549 and BEAS-2B cell lines, over a period of up to 48 h. Automated image processing of the bright field images using standard algorithms within the ImageJ software toolkit yielded 87% accurate recording of the manually identified, temporal, and spatial positions of the mitotic event series. Analysis of the statistics of the interevent times (i.e., times between observed mitoses in a field of view) showed that cell division conformed to a nonhomogeneous Poisson process in which the rate of occurrence of mitotic events, λ exponentially increased over time and provided values of the mean inter mitotic time of 21.1 ± 1.2 hours for the A549 cells and 25.0 ± 1.1 h for the BEAS-2B cells. Comparison of the mitotic event series for the BEAS-2B cell line to that predicted by random Poisson statistics indicated that temporal synchronisation of the cell division process was occurring within 70% of the population and that this could be increased to 85% through serum starvation of the cell culture. © 2015 International Society for Advancement of Cytometry.

Hierarchical storage of large volume of multidector CT data using distributed servers

NASA Astrophysics Data System (ADS)

Ratib, Osman; Rosset, Antoine; Heuberger, Joris; Bandon, David

2006-03-01

Multidector scanners and hybrid multimodality scanners have the ability to generate large number of high-resolution images resulting in very large data sets. In most cases, these datasets are generated for the sole purpose of generating secondary processed images and 3D rendered images as well as oblique and curved multiplanar reformatted images. It is therefore not essential to archive the original images after they have been processed. We have developed an architecture of distributed archive servers for temporary storage of large image datasets for 3D rendering and image processing without the need for long term storage in PACS archive. With the relatively low cost of storage devices it is possible to configure these servers to hold several months or even years of data, long enough for allowing subsequent re-processing if required by specific clinical situations. We tested the latest generation of RAID servers provided by Apple computers with a capacity of 5 TBytes. We implemented a peer-to-peer data access software based on our Open-Source image management software called OsiriX, allowing remote workstations to directly access DICOM image files located on the server through a new technology called "bonjour". This architecture offers a seamless integration of multiple servers and workstations without the need for central database or complex workflow management tools. It allows efficient access to image data from multiple workstation for image analysis and visualization without the need for image data transfer. It provides a convenient alternative to centralized PACS architecture while avoiding complex and time-consuming data transfer and storage.

The utilization of a non-invasive fluorescence imaging system to follow clinical dermatological MAL-PDT

NASA Astrophysics Data System (ADS)

Tyrrell, Jessica; Campbell, Sandra; Curnow, Alison

2009-06-01

This study employed a commercially available, non-invasive, fluorescence imaging system (Dyaderm, Biocam, Germany), to measure protoporphyrin IX (PpIX) concentration at several different stages during clinical dermatological methyl aminolevulinate photodynamic therapy (MAL-PDT). We validated the system prior to use to ensure that the PpIX changes witnessed were accurate and not due to environmental or user induced artifacts. The system was then employed to acquire color (morphological) and fluorescent (physiological) images simultaneously during dermatological PDT. Clinical data was collected from a range of licensed dermatological conditions (actinic keratosis, Bowen's disease and superficial basal cell carcinoma) during initial and subsequent PDT treatment cycles. The initial clinical data indicated that each type of licensed lesion considered responded in a similar manner following the application of Metvix (Galderma, U.K.) and the subsequent light irradiation (Aktilite, Galderma, U.K.). Images acquired three hours after Metvix application showed a significant increase in PpIX concentration within the lesion (P < 0.05), whilst PpIX levels in the surrounding normal tissue remained unaltered. After irradiation, the PpIX concentration was significantly decreased and returned to a level similar to the initial concentration originally observed. Lesions that received subsequent treatment cycles accumulated significantly less PpIX (P < 0.05) prior to irradiation.

The utility of magnetic resonance imaging in the diagnosis and management of pediatric benign ovarian lesions.

PubMed

Emil, Sherif; Youssef, Fouad; Arbash, Ghaidaa; Baird, Robert; Laberge, Jean-Martin; Puligandla, Pramod; Albuquerque, Pedro

2018-01-31

The utility of magnetic resonance imaging (MRI) in the diagnosis and management of pediatric ovarian lesions has not been well defined. A retrospective review of all girls who underwent MRI evaluation of ovarian masses during the period 2009-2015 was performed. The accuracy of MRI was evaluated by comparing results with surgical findings, pathology reports, and subsequent imaging. The influence of the MRI on the treatment plan was specifically explored. Eighteen girls, 12-17years of age, underwent 27 MRIs, subsequent to ultrasound identification of ovarian lesions. Of 9 neoplastic lesions diagnosed on MRI, 8 (89%) were confirmed by surgical and pathological findings. Of 18 functional lesions, 17 (94.4%) were confirmed pathologically or by resolution on subsequent imaging. Twenty MRI exams (74%) directly influenced the treatment plan, by leading to appropriate operative intervention in 9 and appropriate observation in 11. The extent of ovarian resection was guided by MRI findings in 8 of 9 (89%) neoplastic lesions. For characterizing lesions as neoplastic, the sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of MRI were 89%, 94%, 94%, 89%, and 93% respectively. MRI can differentiate functional from neoplastic pediatric ovarian masses, and guide ovarian resection in appropriate cases. II. Copyright © 2018. Published by Elsevier Inc.

A guide to analysis and reconstruction of serial block face scanning electron microscopy data

PubMed Central

TAGGART, M.; RIND, F.C.; WHITE, K.

2018-01-01

Summary Serial block face scanning electron microscopy (SBF‐SEM) is a relatively new technique that allows the acquisition of serially sectioned, imaged and digitally aligned ultrastructural data. There is a wealth of information that can be obtained from the resulting image stacks but this presents a new challenge for researchers – how to computationally analyse and make best use of the large datasets produced. One approach is to reconstruct structures and features of interest in 3D. However, the software programmes can appear overwhelming, time‐consuming and not intuitive for those new to image analysis. There are a limited number of published articles that provide sufficient detail on how to do this type of reconstruction. Therefore, the aim of this paper is to provide a detailed step‐by‐step protocol, accompanied by tutorial videos, for several types of analysis programmes that can be used on raw SBF‐SEM data, although there are more options available than can be covered here. To showcase the programmes, datasets of skeletal muscle from foetal and adult guinea pigs are initially used with procedures subsequently applied to guinea pig cardiac tissue and locust brain. The tissue is processed using the heavy metal protocol developed specifically for SBF‐SEM. Trimmed resin blocks are placed into a Zeiss Sigma SEM incorporating the Gatan 3View and the resulting image stacks are analysed in three different programmes, Fiji, Amira and MIB, using a range of tools available for segmentation. The results from the image analysis comparison show that the analysis tools are often more suited to a particular type of structure. For example, larger structures, such as nuclei and cells, can be segmented using interpolation, which speeds up analysis; single contrast structures, such as the nucleolus, can be segmented using the contrast‐based thresholding tools. Knowing the nature of the tissue and its specific structures (complexity, contrast, if there are distinct membranes, size) will help to determine the best method for reconstruction and thus maximize informative output from valuable tissue. PMID:29333754

A guide to analysis and reconstruction of serial block face scanning electron microscopy data.

PubMed

Cocks, E; Taggart, M; Rind, F C; White, K

2018-05-01

Serial block face scanning electron microscopy (SBF-SEM) is a relatively new technique that allows the acquisition of serially sectioned, imaged and digitally aligned ultrastructural data. There is a wealth of information that can be obtained from the resulting image stacks but this presents a new challenge for researchers - how to computationally analyse and make best use of the large datasets produced. One approach is to reconstruct structures and features of interest in 3D. However, the software programmes can appear overwhelming, time-consuming and not intuitive for those new to image analysis. There are a limited number of published articles that provide sufficient detail on how to do this type of reconstruction. Therefore, the aim of this paper is to provide a detailed step-by-step protocol, accompanied by tutorial videos, for several types of analysis programmes that can be used on raw SBF-SEM data, although there are more options available than can be covered here. To showcase the programmes, datasets of skeletal muscle from foetal and adult guinea pigs are initially used with procedures subsequently applied to guinea pig cardiac tissue and locust brain. The tissue is processed using the heavy metal protocol developed specifically for SBF-SEM. Trimmed resin blocks are placed into a Zeiss Sigma SEM incorporating the Gatan 3View and the resulting image stacks are analysed in three different programmes, Fiji, Amira and MIB, using a range of tools available for segmentation. The results from the image analysis comparison show that the analysis tools are often more suited to a particular type of structure. For example, larger structures, such as nuclei and cells, can be segmented using interpolation, which speeds up analysis; single contrast structures, such as the nucleolus, can be segmented using the contrast-based thresholding tools. Knowing the nature of the tissue and its specific structures (complexity, contrast, if there are distinct membranes, size) will help to determine the best method for reconstruction and thus maximize informative output from valuable tissue. © 2018 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

Computational analysis of Pelton bucket tip erosion using digital image processing

NASA Astrophysics Data System (ADS)

Shrestha, Bim Prasad; Gautam, Bijaya; Bajracharya, Tri Ratna

2008-03-01

Erosion of hydro turbine components through sand laden river is one of the biggest problems in Himalayas. Even with sediment trapping systems, complete removal of fine sediment from water is impossible and uneconomical; hence most of the turbine components in Himalayan Rivers are exposed to sand laden water and subject to erode. Pelton bucket which are being wildly used in different hydropower generation plant undergoes erosion on the continuous presence of sand particles in water. The subsequent erosion causes increase in splitter thickness, which is supposed to be theoretically zero. This increase in splitter thickness gives rise to back hitting of water followed by decrease in turbine efficiency. This paper describes the process of measurement of sharp edges like bucket tip using digital image processing. Image of each bucket is captured and allowed to run for 72 hours; sand concentration in water hitting the bucket is closely controlled and monitored. Later, the image of the test bucket is taken in the same condition. The process is repeated for 10 times. In this paper digital image processing which encompasses processes that performs image enhancement in both spatial and frequency domain. In addition, the processes that extract attributes from images, up to and including the measurement of splitter's tip. Processing of image has been done in MATLAB 6.5 platform. The result shows that quantitative measurement of edge erosion of sharp edges could accurately be detected and the erosion profile could be generated using image processing technique.

Revealing 3D Ultrastructure and Morphology of Stem Cell Spheroids by Electron Microscopy.

PubMed

Jaros, Josef; Petrov, Michal; Tesarova, Marketa; Hampl, Ales

2017-01-01

Cell culture methods have been developed in efforts to produce biologically relevant systems for developmental and disease modeling, and appropriate analytical tools are essential. Knowledge of ultrastructural characteristics represents the basis to reveal in situ the cellular morphology, cell-cell interactions, organelle distribution, niches in which cells reside, and many more. The traditional method for 3D visualization of ultrastructural components, serial sectioning using transmission electron microscopy (TEM), is very labor-intensive due to contentious TEM slice preparation and subsequent image processing of the whole collection. In this chapter, we present serial block-face scanning electron microscopy, together with complex methodology for spheroid formation, contrasting of cellular compartments, image processing, and 3D visualization. The described technique is effective for detailed morphological analysis of stem cell spheroids, organoids, as well as organotypic cell cultures.

Particle image and acoustic Doppler velocimetry analysis of a cross-flow turbine wake

NASA Astrophysics Data System (ADS)

Strom, Benjamin; Brunton, Steven; Polagye, Brian

2017-11-01

Cross-flow turbines have advantageous properties for converting kinetic energy in wind and water currents to rotational mechanical energy and subsequently electrical power. A thorough understanding of cross-flow turbine wakes aids understanding of rotor flow physics, assists geometric array design, and informs control strategies for individual turbines in arrays. In this work, the wake physics of a scale model cross-flow turbine are investigated experimentally. Three-component velocity measurements are taken downstream of a two-bladed turbine in a recirculating water channel. Time-resolved stereoscopic particle image and acoustic Doppler velocimetry are compared for planes normal to and distributed along the turbine rotational axis. Wake features are described using proper orthogonal decomposition, dynamic mode decomposition, and the finite-time Lyapunov exponent. Consequences for downstream turbine placement are discussed in conjunction with two-turbine array experiments.

Feature space analysis of MRI

NASA Astrophysics Data System (ADS)

Soltanian-Zadeh, Hamid; Windham, Joe P.; Peck, Donald J.

1997-04-01

This paper presents development and performance evaluation of an MRI feature space method. The method is useful for: identification of tissue types; segmentation of tissues; and quantitative measurements on tissues, to obtain information that can be used in decision making (diagnosis, treatment planning, and evaluation of treatment). The steps of the work accomplished are as follows: (1) Four T2-weighted and two T1-weighted images (before and after injection of Gadolinium) were acquired for ten tumor patients. (2) Images were analyed by two image analysts according to the following algorithm. The intracranial brain tissues were segmented from the scalp and background. The additive noise was suppressed using a multi-dimensional non-linear edge- preserving filter which preserves partial volume information on average. Image nonuniformities were corrected using a modified lowpass filtering approach. The resulting images were used to generate and visualize an optimal feature space. Cluster centers were identified on the feature space. Then images were segmented into normal tissues and different zones of the tumor. (3) Biopsy samples were extracted from each patient and were subsequently analyzed by the pathology laboratory. (4) Image analysis results were compared to each other and to the biopsy results. Pre- and post-surgery feature spaces were also compared. The proposed algorithm made it possible to visualize the MRI feature space and to segment the image. In all cases, the operators were able to find clusters for normal and abnormal tissues. Also, clusters for different zones of the tumor were found. Based on the clusters marked for each zone, the method successfully segmented the image into normal tissues (white matter, gray matter, and CSF) and different zones of the lesion (tumor, cyst, edema, radiation necrosis, necrotic core, and infiltrated tumor). The results agreed with those obtained from the biopsy samples. Comparison of pre- to post-surgery and radiation feature spaces confirmed that the tumor was not present in the second study but radiation necrosis was generated as a result of radiation.

Diagnostic PET Imaging of Mammary Microcalcifications Using 64Cu-DOTA-Alendronate in a Rat Model of Breast Cancer.

PubMed

Ahrens, Bradley J; Li, Lin; Ciminera, Alexandra K; Chea, Junie; Poku, Erasmus; Bading, James R; Weist, Michael R; Miller, Marcia M; Colcher, David M; Shively, John E

2017-09-01

The development of improved breast cancer screening methods is hindered by a lack of cancer-specific imaging agents and effective small-animal models to test them. The purpose of this study was to evaluate 64 Cu-DOTA-alendronate as a mammary microcalcification-targeting PET imaging agent, using an ideal rat model. Our long-term goal is to develop 64 Cu-DOTA-alendronate for the detection and noninvasive differentiation of malignant versus benign breast tumors with PET. Methods: DOTA-alendronate was synthesized, radiolabeled with 64 Cu, and administered to normal or tumor-bearing aged, female, retired breeder Sprague-Dawley rats for PET imaging. Mammary tissues were subsequently labeled and imaged with light, confocal, and electron microscopy to verify microcalcification targeting specificity of DOTA-alendronate and elucidate the histologic and ultrastructural characteristics of the microcalcifications in different mammary tumor types. Tumor uptake, biodistribution, and dosimetry studies were performed to evaluate the efficacy and safety of 64 Cu-DOTA-alendronate. Results: 64 Cu-DOTA-alendronate was radiolabeled with a 98% yield. PET imaging using aged, female, retired breeder rats showed specific binding of 64 Cu-DOTA-alendronate in mammary glands and mammary tumors. The highest uptake of 64 Cu-DOTA-alendronate was in malignant tumors and the lowest uptake in benign tumors and normal mammary tissue. Confocal analysis with carboxyfluorescein-alendronate confirmed the microcalcification binding specificity of alendronate derivatives. Biodistribution studies revealed tissue alendronate concentrations peaking within the first hour, then decreasing over the next 48 h. Our dosimetric analysis demonstrated a 64 Cu effective dose within the acceptable range for clinical PET imaging agents and the potential for translation into human patients. Conclusion: 64 Cu-DOTA-alendronate is a promising PET imaging agent for the sensitive and specific detection of mammary tumors as well as the differentiation of malignant versus benign tumors based on absolute labeling uptake. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Diagnostic Value of Software-Based Image Fusion of Computed Tomography and F18-FDG PET Scans in Patients with Malignant Lymphoma

PubMed Central

Henninger, B.; Putzer, D.; Kendler, D.; Uprimny, C.; Virgolini, I.; Gunsilius, E.; Bale, R.

2012-01-01

Aim. The purpose of this study was to evaluate the accuracy of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (FDG) positron emission tomography (PET), computed tomography (CT), and software-based image fusion of both modalities in the imaging of non-Hodgkin's lymphoma (NHL) and Hodgkin's disease (HD). Methods. 77 patients with NHL (n = 58) or HD (n = 19) underwent a FDG PET scan, a contrast-enhanced CT, and a subsequent digital image fusion during initial staging or followup. 109 examinations of each modality were evaluated and compared to each other. Conventional staging procedures, other imaging techniques, laboratory screening, and follow-up data constituted the reference standard for comparison with image fusion. Sensitivity and specificity were calculated for CT and PET separately. Results. Sensitivity and specificity for detecting malignant lymphoma were 90% and 76% for CT and 94% and 91% for PET, respectively. A lymph node region-based analysis (comprising 14 defined anatomical regions) revealed a sensitivity of 81% and a specificity of 97% for CT and 96% and 99% for FDG PET, respectively. Only three of 109 image fusion findings needed further evaluation (false positive). Conclusion. Digital fusion of PET and CT improves the accuracy of staging, restaging, and therapy monitoring in patients with malignant lymphoma and may reduce the need for invasive diagnostic procedures. PMID:22654631

Diffraction effects and inelastic electron transport in angle-resolved microscopic imaging applications.

PubMed

Winkelmann, A; Nolze, G; Vespucci, S; Naresh-Kumar, G; Trager-Cowan, C; Vilalta-Clemente, A; Wilkinson, A J; Vos, M

2017-09-01

We analyse the signal formation process for scanning electron microscopic imaging applications on crystalline specimens. In accordance with previous investigations, we find nontrivial effects of incident beam diffraction on the backscattered electron distribution in energy and momentum. Specifically, incident beam diffraction causes angular changes of the backscattered electron distribution which we identify as the dominant mechanism underlying pseudocolour orientation imaging using multiple, angle-resolving detectors. Consequently, diffraction effects of the incident beam and their impact on the subsequent coherent and incoherent electron transport need to be taken into account for an in-depth theoretical modelling of the energy- and momentum distribution of electrons backscattered from crystalline sample regions. Our findings have implications for the level of theoretical detail that can be necessary for the interpretation of complex imaging modalities such as electron channelling contrast imaging (ECCI) of defects in crystals. If the solid angle of detection is limited to specific regions of the backscattered electron momentum distribution, the image contrast that is observed in ECCI and similar applications can be strongly affected by incident beam diffraction and topographic effects from the sample surface. As an application, we demonstrate characteristic changes in the resulting images if different properties of the backscattered electron distribution are used for the analysis of a GaN thin film sample containing dislocations. © 2017 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.

The Effects of Instrumentation on Urine Cytology and CK-20 Analysis for the Detection of Bladder Cancer.

PubMed

Wegelin, Olivier; Bartels, Diny W M; Tromp, Ellen; Kuypers, Karel C; van Melick, Harm H E

2015-10-01

To evaluate the effects of cystoscopy on urine cytology and additional cytokeratin-20 (CK-20) staining in patients presenting with gross hematuria. For 83 patients presenting with gross hematuria, spontaneous and instrumented paired urine samples were analyzed. Three patients were excluded. Spontaneous samples were collected within 1 hour before cystoscopy, and the instrumented samples were tapped through the cystoscope. Subsequently, patients underwent cystoscopic evaluation and imaging of the urinary tract. If tumor suspicious lesions were found on cystoscopy or imaging, subjects underwent transurethral resection or ureterorenoscopy. Two blinded uropathological reviewers (DB, KK) evaluated 160 urine samples. Reference standards were results of cystoscopy, imaging, or histopathology. Thirty-seven patients (46.3%) underwent transurethral resection or ureterorenoscopy procedures. In 30 patients (37.5%) tumor presence was confirmed by histopathology. The specificity of urine analysis was significantly higher for spontaneous samples than instrumented samples for both cytology alone (94% vs 72%, P = .01) and for cytology combined with CK-20 analysis (98% vs 84%, P = .02). The difference in sensitivity between spontaneous and instrumented samples was not significant for both cytology alone (40% vs 53%) and combined with CK-20 analysis (67% vs 67%). The addition of CK-20 analysis to cytology significantly increases test sensitivity in spontaneous urine cytology (67% vs 40%, P = .03). Instrumentation significantly decreases specificity of urine cytology. This may lead to unnecessary diagnostic procedures. Additional CK-20 staining in spontaneous urine cytology significantly increases sensitivity but did not improve the already high specificity. We suggest performing urine cytology and CK-20 analysis on spontaneously voided urine. Copyright © 2015 Elsevier Inc. All rights reserved.

Advanced Diagnostics for Reacting Flows

DTIC Science & Technology

2006-06-01

TECHNICAL DISCUSSION: 1. Infrared-PLIF Imaging Diagnostics using Vibrational Transitions IR-PLIF allows for imaging a group of molecular species important...excitation of IR-active vibrational modes with imaging of the subsequent vibrational fluorescence. Quantitative interpretation requires knowledge of...the vibrational energy transfer processes, and hence in recent years we have been developing models for infrared fluorescence. During the past year

Imaging in the assessment and management of athletic pubalgia.

PubMed

Robinson, Philip; Bhat, Vineet; English, Bryan

2011-02-01

This article reviews the clinical, anatomical, and biomechanical basis of pubalgia and relates it to the potential imaging findings and subsequent management. Although the magnetic resonance imaging features typically seen in symptomatic athletes are emphasized, this condition remains a complex clinical problem, and treatment addressing the functional rehabilitation of the entire region is highlighted. © Thieme Medical Publishers.

Modified Mean-Pyramid Coding Scheme

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Romer, Richard

1996-01-01

Modified mean-pyramid coding scheme requires transmission of slightly fewer data. Data-expansion factor reduced from 1/3 to 1/12. Schemes for progressive transmission of image data transmitted in sequence of frames in such way coarse version of image reconstructed after receipt of first frame and increasingly refined version of image reconstructed after receipt of each subsequent frame.

The Effect of Camera Angle and Image Size on Source Credibility and Interpersonal Attraction.

ERIC Educational Resources Information Center

McCain, Thomas A.; Wakshlag, Jacob J.

The purpose of this study was to examine the effects of two nonverbal visual variables (camera angle and image size) on variables developed in a nonmediated context (source credibility and interpersonal attraction). Camera angle and image size were manipulated in eight video taped television newscasts which were subsequently presented to eight…

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

PubMed

Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

2017-10-12

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

Volumetric quantification of bone-implant contact using micro-computed tomography analysis based on region-based segmentation

PubMed Central

Kang, Sung-Won; Lee, Woo-Jin; Choi, Soon-Chul; Lee, Sam-Sun; Heo, Min-Suk; Huh, Kyung-Hoe

2015-01-01

Purpose We have developed a new method of segmenting the areas of absorbable implants and bone using region-based segmentation of micro-computed tomography (micro-CT) images, which allowed us to quantify volumetric bone-implant contact (VBIC) and volumetric absorption (VA). Materials and Methods The simple threshold technique generally used in micro-CT analysis cannot be used to segment the areas of absorbable implants and bone. Instead, a region-based segmentation method, a region-labeling method, and subsequent morphological operations were successively applied to micro-CT images. The three-dimensional VBIC and VA of the absorbable implant were then calculated over the entire volume of the implant. Two-dimensional (2D) bone-implant contact (BIC) and bone area (BA) were also measured based on the conventional histomorphometric method. Results VA and VBIC increased significantly with as the healing period increased (p<0.05). VBIC values were significantly correlated with VA values (p<0.05) and with 2D BIC values (p<0.05). Conclusion It is possible to quantify VBIC and VA for absorbable implants using micro-CT analysis using a region-based segmentation method. PMID:25793178

Linear Stability Analysis of an Acoustically Vaporized Droplet

NASA Astrophysics Data System (ADS)

Siddiqui, Junaid; Qamar, Adnan; Samtaney, Ravi

2015-11-01

Acoustic droplet vaporization (ADV) is a phase transition phenomena of a superheat liquid (Dodecafluoropentane, C5F12) droplet to a gaseous bubble, instigated by a high-intensity acoustic pulse. This approach was first studied in imaging applications, and applicable in several therapeutic areas such as gas embolotherapy, thrombus dissolution, and drug delivery. High-speed imaging and theoretical modeling of ADV has elucidated several physical aspects, ranging from bubble nucleation to its subsequent growth. Surface instabilities are known to exist and considered responsible for evolving bubble shapes (non-spherical growth, bubble splitting and bubble droplet encapsulation). We present a linear stability analysis of the dynamically evolving interfaces of an acoustically vaporized micro-droplet (liquid A) in an infinite pool of a second liquid (liquid B). We propose a thermal ADV model for the base state. The linear analysis utilizes spherical harmonics (Ynm, of degree m and order n) and under various physical assumptions results in a time-dependent ODE of the perturbed interface amplitudes (one at the vapor/liquid A interface and the other at the liquid A/liquid B interface). The perturbation amplitudes are found to grow exponentially and do not depend on m. Supported by KAUST Baseline Research Funds.

Experimental saltwater intrusion in coastal aquifers using automated image analysis: Applications to homogeneous aquifers

NASA Astrophysics Data System (ADS)

Robinson, G.; Ahmed, Ashraf A.; Hamill, G. A.

2016-07-01

This paper presents the applications of a novel methodology to quantify saltwater intrusion parameters in laboratory-scale experiments. The methodology uses an automated image analysis procedure, minimising manual inputs and the subsequent systematic errors that can be introduced. This allowed the quantification of the width of the mixing zone which is difficult to measure in experimental methods that are based on visual observations. Glass beads of different grain sizes were tested for both steady-state and transient conditions. The transient results showed good correlation between experimental and numerical intrusion rates. The experimental intrusion rates revealed that the saltwater wedge reached a steady state condition sooner while receding than advancing. The hydrodynamics of the experimental mixing zone exhibited similar traits; a greater increase in the width of the mixing zone was observed in the receding saltwater wedge, which indicates faster fluid velocities and higher dispersion. The angle of intrusion analysis revealed the formation of a volume of diluted saltwater at the toe position when the saltwater wedge is prompted to recede. In addition, results of different physical repeats of the experiment produced an average coefficient of variation less than 0.18 of the measured toe length and width of the mixing zone.

An Automated Method for High-Throughput Screening of Arabidopsis Rosette Growth in Multi-Well Plates and Its Validation in Stress Conditions.

PubMed

De Diego, Nuria; Fürst, Tomáš; Humplík, Jan F; Ugena, Lydia; Podlešáková, Kateřina; Spíchal, Lukáš

2017-01-01

High-throughput plant phenotyping platforms provide new possibilities for automated, fast scoring of several plant growth and development traits, followed over time using non-invasive sensors. Using Arabidops is as a model offers important advantages for high-throughput screening with the opportunity to extrapolate the results obtained to other crops of commercial interest. In this study we describe the development of a highly reproducible high-throughput Arabidopsis in vitro bioassay established using our OloPhen platform, suitable for analysis of rosette growth in multi-well plates. This method was successfully validated on example of multivariate analysis of Arabidopsis rosette growth in different salt concentrations and the interaction with varying nutritional composition of the growth medium. Several traits such as changes in the rosette area, relative growth rate, survival rate and homogeneity of the population are scored using fully automated RGB imaging and subsequent image analysis. The assay can be used for fast screening of the biological activity of chemical libraries, phenotypes of transgenic or recombinant inbred lines, or to search for potential quantitative trait loci. It is especially valuable for selecting genotypes or growth conditions that improve plant stress tolerance.

MicroCT angiography detects vascular formation and regression in skin wound healing

PubMed Central

Urao, Norifumi; Okonkwo, Uzoagu A.; Fang, Milie M.; Zhuang, Zhen W.; Koh, Timothy J.; DiPietro, Luisa A.

2016-01-01

Properly regulated angiogenesis and arteriogenesis are essential for effective wound healing. Tissue injury induces robust new vessel formation and subsequent vessel maturation, which involves vessel regression and remodeling. Although formation of functional vasculature is essential for healing, alterations in vascular structure over the time course of skin wound healing are not well understood. Here, using high-resolution ex vivo X-ray micro-computed tomography (microCT), we describe the vascular network during healing of skin excisional wounds with highly detailed three-dimensional (3D) reconstructed images and associated quantitative analysis. We found that relative vessel volume, surface area and branching number are significantly decreased in wounds from day 7 to day 14 and 21. Segmentation and skeletonization analysis of selected branches from high-resolution images as small as 2.5 μm voxel size show that branching orders are decreased in the wound vessels during healing. In histological analysis, we found that the contrast agent fills mainly arterioles, but not small capillaries nor large veins. In summary, high-resolution microCT revealed dynamic alterations of vessel structures during wound healing. This technique may be useful as a key tool in the study of the formation and regression of wound vessels. PMID:27009591

C-IMAGE Teachers at Sea Maiden Voyages: Promoting Authentic Scientific Research in the Classroom

NASA Astrophysics Data System (ADS)

Hine, A. C.; Greely, T.; Lodge, A.

2012-12-01

The Center for Integrated Modeling & Analysis of Gulf Ecosystems (C-IMAGE) is one of eight consortia participating in the BP/Gulf of Mexico Research Initiative. C-IMAGE is a comprehensive research consortium of 13 national and international universities tasked with evaluating the environmental impacts of the 2010 Deepwater Horizon Oil Spill (DWH) on coastal ecosystems, the water column and the sea floor. The associated C-IMAGE research cruises provide a unique opportunity for Florida's K12 science educators to participate in the data collection and collaboration process alongside marine scientists as a member of the scientific crew. The mission of the C-IMAGE cruises is to help to answer several fundamental questions about the DWH event and subsequent impacts on the plankton population, reef and fish communities and the microbial communities. Deep sea sediment samples, plankton and fishes collected during these expeditions are the data sources. Sampling activities include the use of the SIPPER plankton sampler, multi-core sediment system and long line surveys to assess fish health. While at sea teachers participate in the at sea research and serve as the ship to shore communicator via social media (FB, Twitter, daily blogs) and LIVE video conferencing with formal and informal classrooms. Marine scientists, post-docs and graduate students participating in the C-IMAGE cruises collaborate with the teacher on board to communicate the science, technology and life at sea experiences to educational and general audiences. Upon return to shore, teachers will translate their At Sea learning experience to understandable inquiry-based lessons about the science and technology encompassing the northern Gulf of Mexico ecology, the DWH event and subsequent impacts. Lessons developed from the cruises will inform a future series of C-IMAGE Teacher Professional Developments during Phase 2 of Outreach activities. The results from three Gulf of Mexico expeditions (Aug-Nov) will be presented: related to teachers' working knowledge of research and sampling procedures as well as metrics for the potential value-added of social media as a mechanism for communicating research with formal and informal audiences. C-IMAGE teachers will engage in research with experts in biological and chemical modeling, marine resource assessment, sedimentary geochemistry and toxicology. This research is made possible by a grant from BP/The Gulf of Mexico Research Initiative. Contract #SA 12-10/GoMRI-007;

The Pixon Method for Data Compression Image Classification, and Image Reconstruction

NASA Technical Reports Server (NTRS)

Puetter, Richard; Yahil, Amos

2002-01-01

As initially proposed, this program had three goals: (1) continue to develop the highly successful Pixon method for image reconstruction and support other scientist in implementing this technique for their applications; (2) develop image compression techniques based on the Pixon method; and (3) develop artificial intelligence algorithms for image classification based on the Pixon approach for simplifying neural networks. Subsequent to proposal review the scope of the program was greatly reduced and it was decided to investigate the ability of the Pixon method to provide superior restorations of images compressed with standard image compression schemes, specifically JPEG-compressed images.

Comparison of magnetic resonance imaging and computed tomography in suspected lesions in the posterior cranial fossa.

PubMed Central

Teasdale, G. M.; Hadley, D. M.; Lawrence, A.; Bone, I.; Burton, H.; Grant, R.; Condon, B.; Macpherson, P.; Rowan, J.

1989-01-01

OBJECTIVE--To compare computed tomography and magnetic resonance imaging in investigating patients suspected of having a lesion in the posterior cranial fossa. DESIGN--Randomised allocation of newly referred patients to undergo either computed tomography or magnetic resonance imaging; the alternative investigation was performed subsequently only in response to a request from the referring doctor. SETTING--A regional neuroscience centre serving 2.7 million. PATIENTS--1020 Patients recruited between April 1986 and December 1987, all suspected by neurologists, neurosurgeons, or other specialists of having a lesion in the posterior fossa and referred for neuroradiology. The groups allocated to undergo computed tomography or magnetic resonance imaging were well matched in distributions of age, sex, specialty of referring doctor, investigation as an inpatient or an outpatient, suspected site of lesion, and presumed disease process; the referring doctor's confidence in the initial clinical diagnosis was also similar. INTERVENTIONS--After the patients had been imaged by either computed tomography or magnetic resonance (using a resistive magnet of 0.15 T) doctors were given the radiologist's report and a form asking if they considered that imaging with the alternative technique was necessary and, if so, why; it also asked for their current diagnoses and their confidence in them. MAIN OUTCOME MEASURES--Number of requests for the alternative method of investigation. Assessment of characteristics of patients for whom further imaging was requested and lesions that were suspected initially and how the results of the second imaging affected clinicians' and radiologists' opinions. RESULTS--Ninety three of the 501 patients who initially underwent computed tomography were referred subsequently for magnetic resonance imaging whereas only 28 of the 493 patients who initially underwent magnetic resonance imaging were referred subsequently for computed tomography. Over the study the number of patients referred for magnetic resonance imaging after computed tomography increased but requests for computed tomography after magnetic resonance imaging decreased. The reason that clinicians gave most commonly for requesting further imaging by magnetic resonance was that the results of the initial computed tomography failed to exclude their suspected diagnosis (64 patients). This was less common in patients investigated initially by magnetic resonance imaging (eight patients). Management of 28 patients (6%) imaged initially with computed tomography and 12 patients (2%) imaged initially with magnetic resonance was changed on the basis of the results of the alternative imaging. CONCLUSIONS--Magnetic resonance imaging provided doctors with the information required to manage patients suspected of having a lesion in the posterior fossa more commonly than computed tomography, but computed tomography alone was satisfactory in 80% of cases... PMID:2506965

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

NASA Astrophysics Data System (ADS)

Bhushan, A.; Sharker, M. H.; Karimi, H. A.

2015-07-01

In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

An integrated approach to characterization of fractured reservoirs

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

Datta-Gupta, A.; Majer, E.; Vasco, D.

1995-12-31

This paper summarizes an integrated hydrologic and seismic characterization of a fractured limestone formation at the Conoco Borehole Test Facility (CBTF) in Kay County, Oklahoma. Transient response from pressure interference tests were first inverted in order to identify location and orientation of dominant fractures at the CBTF. Subsequently, high resolution (1000 to 10000 Hz) cross-well and single-well seismic surveys were conducted to verify the preferential slow paths indicated by hydrologic analysis. Seismic surveys were conducted before and after an air injection in order to increase the visibility of the fracture zone to seismic imaging. Both Seismic and hydrologic analysis weremore » found to yield consistent results in detecting the location of a major fracture zone.« less

Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

PubMed

Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

2017-10-01

Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

Mapping Vesta Equatorial Quadrangle V-8EDL: Various Craters and Giant Grooves

NASA Astrophysics Data System (ADS)

Le Corre, L.; Nathues, A.; Reddy, V.; Buczkowski, D.; Denevi, B. W.; Gaffey, M.; Williams, D. A.; Garry, W. B.; Yingst, R.; Jaumann, R.; Pieters, C. M.; Russell, C. T.; Raymond, C. A.

2011-12-01

NASA's Dawn spacecraft arrived at the asteroid 4Vesta on July 15, 2011, and is now collecting imaging, spectroscopic, and elemental abundance data during its one-year orbital mission. As part of the geological analysis of the surface, a series of 15 quadrangle maps are being produced based on Framing Camera images (FC: spatial resolution: ~65 m/pixel) along with Visible & Infrared Spectrometer data (VIR: spatial resolution: ~180 m/pixel) obtained during the High-Altitude Mapping Orbit (HAMO). This poster presentation concentrates on our geologic analysis and mapping of quadrangle V-8EDL located between -22 and 22 degrees latitude and 144 and 216 degrees East longitude. This quadrangle is dominated by old craters (without any ejecta visible in the clear and color bands), but one small recent crater can be seen with bright ejecta blanket and rays. The latter has some small, dark units outside and inside the crater rim that could be indicative of impact melt. This quadrangle also contains a set of giant linear grooves running almost parallel to the equator that might have formed subsequent to a big impact. We will use FC mosaics with clear images and false color composites as well as VIR spectroscopy data in order to constrain the geology and identify the nature of each unit present in this quadrangle.

Magnetic Resonance Imaging (MRI) Analysis of Fibroid Location in Women Achieving Pregnancy After Uterine Artery Embolization

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

Walker, Woodruff J.; Bratby, Mark John

The purpose of this study was to evaluate the fibroid morphology in a cohort of women achieving pregnancy following treatment with uterine artery embolization (UAE) for symptomatic uterine fibroids. A retrospective review of magnetic resonance imaging (MRI) of the uterus was performed to assess pre-embolization fibroid morphology. Data were collected on fibroid size, type, and number and included analysis of follow-up imaging to assess response. There have been 67 pregnancies in 51 women, with 40 live births. Intramural fibroids were seen in 62.7% of the women (32/48). Of these the fibroids were multiple in 16. A further 12 women hadmore » submucosal fibroids, with equal numbers of types 1 and 2. Two of these women had coexistent intramural fibroids. In six women the fibroids could not be individually delineated and formed a complex mass. All subtypes of fibroid were represented in those subgroups of women achieving a live birth versus those who did not. These results demonstrate that the location of uterine fibroids did not adversely affect subsequent pregnancy in the patient population investigated. Although this is only a small qualitative study, it does suggest that all types of fibroids treated with UAE have the potential for future fertility.« less

GPR image analysis to locate water leaks from buried pipes by applying variance filters

NASA Astrophysics Data System (ADS)

Ocaña-Levario, Silvia J.; Carreño-Alvarado, Elizabeth P.; Ayala-Cabrera, David; Izquierdo, Joaquín

2018-05-01

Nowadays, there is growing interest in controlling and reducing the amount of water lost through leakage in water supply systems (WSSs). Leakage is, in fact, one of the biggest problems faced by the managers of these utilities. This work addresses the problem of leakage in WSSs by using GPR (Ground Penetrating Radar) as a non-destructive method. The main objective is to identify and extract features from GPR images such as leaks and components in a controlled laboratory condition by a methodology based on second order statistical parameters and, using the obtained features, to create 3D models that allows quick visualization of components and leaks in WSSs from GPR image analysis and subsequent interpretation. This methodology has been used before in other fields and provided promising results. The results obtained with the proposed methodology are presented, analyzed, interpreted and compared with the results obtained by using a well-established multi-agent based methodology. These results show that the variance filter is capable of highlighting the characteristics of components and anomalies, in an intuitive manner, which can be identified by non-highly qualified personnel, using the 3D models we develop. This research intends to pave the way towards future intelligent detection systems that enable the automatic detection of leaks in WSSs.

3D membrane segmentation and quantification of intact thick cells using cryo soft X-ray transmission microscopy: A pilot study

PubMed Central

Klementieva, Oxana; Werner, Stephan; Guttmann, Peter; Pratsch, Christoph; Cladera, Josep

2017-01-01

Structural analysis of biological membranes is important for understanding cell and sub-cellular organelle function as well as their interaction with the surrounding environment. Imaging of whole cells in three dimension at high spatial resolution remains a significant challenge, particularly for thick cells. Cryo-transmission soft X-ray microscopy (cryo-TXM) has recently gained popularity to image, in 3D, intact thick cells (∼10μm) with details of sub-cellular architecture and organization in near-native state. This paper reports a new tool to segment and quantify structural changes of biological membranes in 3D from cryo-TXM images by tracking an initial 2D contour along the third axis of the microscope, through a multi-scale ridge detection followed by an active contours-based model, with a subsequent refinement along the other two axes. A quantitative metric that assesses the grayscale profiles perpendicular to the membrane surfaces is introduced and shown to be linearly related to the membrane thickness. Our methodology has been validated on synthetic phantoms using realistic microscope properties and structure dimensions, as well as on real cryo-TXM data. Results demonstrate the validity of our algorithms for cryo-TXM data analysis. PMID:28376110

Potential costs of breast augmentation mammaplasty.

PubMed

Schmitt, William P; Eichhorn, Mitchell G; Ford, Ronald D

2016-01-01

Augmentation mammaplasty is one of the most common surgical procedures performed by plastic surgeons. The aim of this study was to estimate the cost of the initial procedure and its subsequent complications, as well as project the cost of Food and Drug Administration (FDA)-recommended surveillance imaging. The potential costs to the individual patient and society were calculated. Local plastic surgeons provided billing data for the initial primary silicone augmentation and reoperative procedures. Complication rates used for the cost analysis were obtained from the Allergen Core study on silicone implants. Imaging surveillance costs were considered in the estimations. The average baseline initial cost of silicone augmentation mammaplasty was calculated at $6335. The average total cost of primary breast augmentation over the first decade for an individual patient, including complications requiring reoperation and other ancillary costs, was calculated at $8226. Each decade thereafter cost an additional $1891. Costs may exceed $15,000 over an averaged lifetime, and the recommended implant surveillance could cost an additional $33,750. The potential cost of a breast augmentation, which includes the costs of complications and imaging, is significantly higher than the initial cost of the procedure. Level III, economic and decision analysis study. Copyright © 2015 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Quantification of synthesized hydration products using synchrotron microtomography and spectral analysis

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

Deboodt, Tyler; Ideker, Jason H.; Isgor, O. Burkan

2017-12-01

The use of x-ray computed tomography (CT) as a standalone method has primarily been used to characterize pore structure, cracking and mechanical damage in cementitious systems due to low contrast in the hydrated phases. These limitations have resulted in the inability to extract quantifiable information on such phases. The goal of this research was to address the limitations caused by low contrast and improving the ability to distinguish the four primary hydrated phases in portland cement; C-S-H, calcium hydroxide, monosulfate, and ettringite. X-ray CT on individual layers, binary mixtures of phases, and quaternary mixtures of phases to represent a hydratedmore » portland cement paste were imaged with synchrotron radiation. Known masses of each phase were converted to a volume and compared to the segmented image volumes. It was observed that adequate contrast in binary mixing of phases allowed for segmentation, and subsequent image analysis indicated quantifiable volumes could be extracted from the tomographic volume. However, low contrast was observed when C-S-H and monosulfate were paired together leading to difficulties segmenting in an unbiased manner. Quantification of phases in quaternary mixtures included larger errors than binary mixes due to histogram overlaps of monosulfate, C-S-H, and calcium hydroxide.« less

The direct analysis of drug distribution of rotigotine-loaded microspheres from tissue sections by LESA coupled with tandem mass spectrometry.

PubMed

Xu, Li-Xiao; Wang, Tian-Tian; Geng, Yin-Yin; Wang, Wen-Yan; Li, Yin; Duan, Xiao-Kun; Xu, Bin; Liu, Charles C; Liu, Wan-Hui

2017-09-01

The direct analysis of drug distribution of rotigotine-loaded microspheres (RoMS) from tissue sections by liquid extraction surface analysis (LESA) coupled with tandem mass spectrometry (MS/MS) was demonstrated. The RoMS distribution in rat tissues assessed by the ambient LESA-MS/MS approach without extensive or tedious sample pretreatment was compared with that obtained by a conventional liquid chromatography tandem mass spectrometry (LC-MS/MS) method in which organ excision and subsequent solvent extraction were commonly employed before analysis. Results obtained from the two were well correlated for a majority of the organs, such as muscle, liver, stomach, and hippocampus. The distribution of RoMS in the brain, however, was found to be mainly focused in the hippocampus and striatum regions as shown by the LESA-imaged profiles. The LESA approach we developed is sensitive enough, with an estimated LLOQ at 0.05 ng/mL of rotigotine in brain tissue, and information-rich with minimal sample preparation, suitable, and promising in assisting the development of new drug delivery systems for controlled drug release and protection. Graphical abstract Workflow for the LESA-MS/MS imaging of brain tissue section after intramuscular RoMS administration.

Single-Cell in Situ RNA Analysis With Switchable Fluorescent Oligonucleotides.

PubMed

Xiao, Lu; Guo, Jia

2018-01-01

Comprehensive RNA analyses in individual cells in their native spatial contexts promise to transform our understanding of normal physiology and disease pathogenesis. Here we report a single-cell in situ RNA analysis approach using switchable fluorescent oligonucleotides (SFO). In this method, transcripts are first hybridized by pre-decoding oligonucleotides. These oligonucleotides subsequently recruit SFO to stain their corresponding RNA targets. After fluorescence imaging, all the SFO in the whole specimen are simultaneously removed by DNA strand displacement reactions. Through continuous cycles of target staining, fluorescence imaging, and SFO removal, a large number of different transcripts can be identified by unique fluorophore sequences and visualized at the optical resolution. To demonstrate the feasibility of this approach, we show that the hybridized SFO can be efficiently stripped by strand displacement reactions within 30 min. We also demonstrate that this SFO removal process maintains the integrity of the RNA targets and the pre-decoding oligonucleotides, and keeps them hybridized. Applying this approach, we show that transcripts can be restained in at least eight hybridization cycles with high analysis accuracy, which theoretically would enable the whole transcriptome to be quantified at the single molecule sensitivity in individual cells. This in situ RNA analysis technology will have wide applications in systems biology, molecular diagnosis, and targeted therapies.

Value of diffusion-weighted MR imaging in the diagnosis of lymph node metastases in patients with cholangiocarcinoma.

PubMed

Holzapfel, Konstantin; Gaa, Jochen; Schubert, Elaine C; Eiber, Matthias; Kleeff, Joerg; Rummeny, Ernst J; Loos, Martin

2016-10-01

To evaluate diffusion-weighted MR imaging (DWI) in the diagnosis of lymph node metastases in patients with cholangiocarcinoma. In 24 patients with cholangiocarcinoma, MR imaging of the upper abdomen was performed prior to surgery at 1.5 T using a respiratory-triggered single-shot echo-planar imaging (SSEPI) sequence (b values: 50, 300, and 600 s/mm(2)). ADC (apparent diffusion coefficient) values and diameters of regional lymph nodes (LN) were determined. Subsequently, in all patients, surgical exploration and/or resection of the primary tumor and regional LN dissection were performed. Imaging results were correlated with results of histopathologic analysis. ADC values and diameters of benign and malignant LN were compared using the Mann-Whitney U test. In addition, a ROC (receiver operating characteristic curve) analysis was performed. The mean ADC value (×10(-3) mm(2)/s) of metastatic LN (1.21 ± 0.15) was significantly lower than that of benign LN (1.62 ± 0.33, p < 0.001) while there was no significant difference in the mean diameter of malignant (16.8 ± 5.4 mm) and benign LN (14.1 ± 4.0 mm; p = 0.09). Using an ADC value of 1.25 × 10(-3) mm(2)/s as threshold, 91.4% of LN were correctly classified as benign or malignant with a sensitivity/specificity of 83.3%/92.8% and a positive/negative predictive value of 66.7%/96.7%. The area under the ROC curve was 0.93. DWI using a respiratory-triggered SSEPI sequence, according to our preliminary experience, is a promising imaging modality in the differentiation of benign and malignant LN in patients with cholangiocarcinoma.

Extreme Tele-Echocardiography: Methodology for Remote Guidance of In-Flight Echocardiography Aboard the International Space Station

NASA Technical Reports Server (NTRS)

Martin, David S.; Borowski, Allan; Bungo, Michael W.; Gladding, Patrick; Greenberg, Neil; Hamilton, Doug; Levine, Benjamin D.; Lee, Stuart M.; Norwood, Kelly; Platts, Steven H.;

A Fast, Automatic Segmentation Algorithm for Locating and Delineating Touching Cell Boundaries in Imaged Histopathology

PubMed Central

Qi, Xin; Xing, Fuyong; Foran, David J.; Yang, Lin

2013-01-01

Summary Background Automated analysis of imaged histopathology specimens could potentially provide support for improved reliability in detection and classification in a range of investigative and clinical cancer applications. Automated segmentation of cells in the digitized tissue microarray (TMA) is often the prerequisite for quantitative analysis. However overlapping cells usually bring significant challenges for traditional segmentation algorithms. Objectives In this paper, we propose a novel, automatic algorithm to separate overlapping cells in stained histology specimens acquired using bright-field RGB imaging. Methods It starts by systematically identifying salient regions of interest throughout the image based upon their underlying visual content. The segmentation algorithm subsequently performs a quick, voting based seed detection. Finally, the contour of each cell is obtained using a repulsive level set deformable model using the seeds generated in the previous step. We compared the experimental results with the most current literature, and the pixel wise accuracy between human experts' annotation and those generated using the automatic segmentation algorithm. Results The method is tested with 100 image patches which contain more than 1000 overlapping cells. The overall precision and recall of the developed algorithm is 90% and 78%, respectively. We also implement the algorithm on GPU. The parallel implementation is 22 times faster than its C/C++ sequential implementation. Conclusion The proposed overlapping cell segmentation algorithm can accurately detect the center of each overlapping cell and effectively separate each of the overlapping cells. GPU is proven to be an efficient parallel platform for overlapping cell segmentation. PMID:22526139

Improved estimation of parametric images of cerebral glucose metabolic rate from dynamic FDG-PET using volume-wise principle component analysis

NASA Astrophysics Data System (ADS)

Dai, Xiaoqian; Tian, Jie; Chen, Zhe

2010-03-01

Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.

Development of image processing method to detect noise in geostationary imagery

NASA Astrophysics Data System (ADS)

Khlopenkov, Konstantin V.; Doelling, David R.

2016-10-01

The Clouds and the Earth's Radiant Energy System (CERES) has incorporated imagery from 16 individual geostationary (GEO) satellites across five contiguous domains since March 2000. In order to derive broadband fluxes uniform across satellite platforms it is important to ensure a good quality of the input raw count data. GEO data obtained by older GOES imagers (such as MTSAT-1, Meteosat-5, Meteosat-7, GMS-5, and GOES-9) are known to frequently contain various types of noise caused by transmission errors, sync errors, stray light contamination, and others. This work presents an image processing methodology designed to detect most kinds of noise and corrupt data in all bands of raw imagery from modern and historic GEO satellites. The algorithm is based on a set of different approaches to detect abnormal image patterns, including inter-line and inter-pixel differences within a scanline, correlation between scanlines, analysis of spatial variance, and also a 2D Fourier analysis of the image spatial frequencies. In spite of computational complexity, the described method is highly optimized for performance to facilitate volume processing of multi-year data and runs in fully automated mode. Reliability of this noise detection technique has been assessed by human supervision for each GEO dataset obtained during selected time periods in 2005 and 2006. This assessment has demonstrated the overall detection accuracy of over 99.5% and the false alarm rate of under 0.3%. The described noise detection routine is currently used in volume processing of historical GEO imagery for subsequent production of global gridded data products and for cross-platform calibration.

Propagation of registration uncertainty during multi-fraction cervical cancer brachytherapy

NASA Astrophysics Data System (ADS)

Amir-Khalili, A.; Hamarneh, G.; Zakariaee, R.; Spadinger, I.; Abugharbieh, R.

2017-10-01

Multi-fraction cervical cancer brachytherapy is a form of image-guided radiotherapy that heavily relies on 3D imaging during treatment planning, delivery, and quality control. In this context, deformable image registration can increase the accuracy of dosimetric evaluations, provided that one can account for the uncertainties associated with the registration process. To enable such capability, we propose a mathematical framework that first estimates the registration uncertainty and subsequently propagates the effects of the computed uncertainties from the registration stage through to the visualizations, organ segmentations, and dosimetric evaluations. To ensure the practicality of our proposed framework in real world image-guided radiotherapy contexts, we implemented our technique via a computationally efficient and generalizable algorithm that is compatible with existing deformable image registration software. In our clinical context of fractionated cervical cancer brachytherapy, we perform a retrospective analysis on 37 patients and present evidence that our proposed methodology for computing and propagating registration uncertainties may be beneficial during therapy planning and quality control. Specifically, we quantify and visualize the influence of registration uncertainty on dosimetric analysis during the computation of the total accumulated radiation dose on the bladder wall. We further show how registration uncertainty may be leveraged into enhanced visualizations that depict the quality of the registration and highlight potential deviations from the treatment plan prior to the delivery of radiation treatment. Finally, we show that we can improve the transfer of delineated volumetric organ segmentation labels from one fraction to the next by encoding the computed registration uncertainties into the segmentation labels.

An optical systems analysis approach to image resampling

NASA Technical Reports Server (NTRS)

Lyon, Richard G.

1997-01-01

All types of image registration require some type of resampling, either during the registration or as a final step in the registration process. Thus the image(s) must be regridded into a spatially uniform, or angularly uniform, coordinate system with some pre-defined resolution. Frequently the ending resolution is not the resolution at which the data was observed with. The registration algorithm designer and end product user are presented with a multitude of possible resampling methods each of which modify the spatial frequency content of the data in some way. The purpose of this paper is threefold: (1) to show how an imaging system modifies the scene from an end to end optical systems analysis approach, (2) to develop a generalized resampling model, and (3) empirically apply the model to simulated radiometric scene data and tabulate the results. A Hanning windowed sinc interpolator method will be developed based upon the optical characterization of the system. It will be discussed in terms of the effects and limitations of sampling, aliasing, spectral leakage, and computational complexity. Simulated radiometric scene data will be used to demonstrate each of the algorithms. A high resolution scene will be "grown" using a fractal growth algorithm based on mid-point recursion techniques. The result scene data will be convolved with a point spread function representing the optical response. The resultant scene will be convolved with the detection systems response and subsampled to the desired resolution. The resultant data product will be subsequently resampled to the correct grid using the Hanning windowed sinc interpolator and the results and errors tabulated and discussed.

Spatially resolved D-T(2) correlation NMR of porous media.

PubMed

Zhang, Yan; Blümich, Bernhard

2014-05-01

Within the past decade, 2D Laplace nuclear magnetic resonance (NMR) has been developed to analyze pore geometry and diffusion of fluids in porous media on the micrometer scale. Many objects like rocks and concrete are heterogeneous on the macroscopic scale, and an integral analysis of microscopic properties provides volume-averaged information. Magnetic resonance imaging (MRI) resolves this spatial average on the contrast scale set by the particular MRI technique. Desirable contrast parameters for studies of fluid transport in porous media derive from the pore-size distribution and the pore connectivity. These microscopic parameters are accessed by 1D and 2D Laplace NMR techniques. It is therefore desirable to combine MRI and 2D Laplace NMR to image functional information on fluid transport in porous media. Because 2D Laplace resolved MRI demands excessive measuring time, this study investigates the possibility to restrict the 2D Laplace analysis to the sum signals from low-resolution pixels, which correspond to pixels of similar amplitude in high-resolution images. In this exploratory study spatially resolved D-T2 correlation maps from glass beads and mortar are analyzed. Regions of similar contrast are first identified in high-resolution images to locate corresponding pixels in low-resolution images generated with D-T2 resolved MRI for subsequent pixel summation to improve the signal-to-noise ratio of contrast-specific D-T2 maps. This method is expected to contribute valuable information on correlated sample heterogeneity from the macroscopic and the microscopic scales in various types of porous materials including building materials and rock. Copyright © 2014 Elsevier Inc. All rights reserved.

Improved classification accuracy of powdery mildew infection levels of wine grapes by spatial-spectral analysis of hyperspectral images.

PubMed

Knauer, Uwe; Matros, Andrea; Petrovic, Tijana; Zanker, Timothy; Scott, Eileen S; Seiffert, Udo

2017-01-01

Hyperspectral imaging is an emerging means of assessing plant vitality, stress parameters, nutrition status, and diseases. Extraction of target values from the high-dimensional datasets either relies on pixel-wise processing of the full spectral information, appropriate selection of individual bands, or calculation of spectral indices. Limitations of such approaches are reduced classification accuracy, reduced robustness due to spatial variation of the spectral information across the surface of the objects measured as well as a loss of information intrinsic to band selection and use of spectral indices. In this paper we present an improved spatial-spectral segmentation approach for the analysis of hyperspectral imaging data and its application for the prediction of powdery mildew infection levels (disease severity) of intact Chardonnay grape bunches shortly before veraison. Instead of calculating texture features (spatial features) for the huge number of spectral bands independently, dimensionality reduction by means of Linear Discriminant Analysis (LDA) was applied first to derive a few descriptive image bands. Subsequent classification was based on modified Random Forest classifiers and selective extraction of texture parameters from the integral image representation of the image bands generated. Dimensionality reduction, integral images, and the selective feature extraction led to improved classification accuracies of up to [Formula: see text] for detached berries used as a reference sample (training dataset). Our approach was validated by predicting infection levels for a sample of 30 intact bunches. Classification accuracy improved with the number of decision trees of the Random Forest classifier. These results corresponded with qPCR results. An accuracy of 0.87 was achieved in classification of healthy, infected, and severely diseased bunches. However, discrimination between visually healthy and infected bunches proved to be challenging for a few samples, perhaps due to colonized berries or sparse mycelia hidden within the bunch or airborne conidia on the berries that were detected by qPCR. An advanced approach to hyperspectral image classification based on combined spatial and spectral image features, potentially applicable to many available hyperspectral sensor technologies, has been developed and validated to improve the detection of powdery mildew infection levels of Chardonnay grape bunches. The spatial-spectral approach improved especially the detection of light infection levels compared with pixel-wise spectral data analysis. This approach is expected to improve the speed and accuracy of disease detection once the thresholds for fungal biomass detected by hyperspectral imaging are established; it can also facilitate monitoring in plant phenotyping of grapevine and additional crops.

Autofluorescence imaging of basal cell carcinoma by smartphone RGB camera

NASA Astrophysics Data System (ADS)

Lihachev, Alexey; Derjabo, Alexander; Ferulova, Inesa; Lange, Marta; Lihacova, Ilze; Spigulis, Janis

2015-12-01

The feasibility of smartphones for in vivo skin autofluorescence imaging has been investigated. Filtered autofluorescence images from the same tissue area were periodically captured by a smartphone RGB camera with subsequent detection of fluorescence intensity decreasing at each image pixel for further imaging the planar distribution of those values. The proposed methodology was tested clinically with 13 basal cell carcinoma and 1 atypical nevus. Several clinical cases and potential future applications of the smartphone-based technique are discussed.

Autofluorescence imaging of basal cell carcinoma by smartphone RGB camera.

PubMed

Lihachev, Alexey; Derjabo, Alexander; Ferulova, Inesa; Lange, Marta; Lihacova, Ilze; Spigulis, Janis

2015-01-01

The feasibility of smartphones for in vivo skin autofluorescence imaging has been investigated. Filtered autofluorescence images from the same tissue area were periodically captured by a smartphone RGB camera with subsequent detection of fluorescence intensity decreasing at each image pixel for further imaging the planar distribution of those values. The proposed methodology was tested clinically with 13 basal cell carcinoma and 1 atypical nevus. Several clinical cases and potential future applications of the smartphone-based technique are discussed.

Three-dimensional imaging of the craniofacial complex.

PubMed

Nguyen, Can X.; Nissanov, Jonathan; Öztürk, Cengizhan; Nuveen, Michiel J.; Tuncay, Orhan C.

2000-02-01

Orthodontic treatment requires the rearrangement of craniofacial complex elements in three planes of space, but oddly the diagnosis is done with two-dimensional images. Here we report on a three-dimensional (3D) imaging system that employs the stereoimaging method of structured light to capture the facial image. The images can be subsequently integrated with 3D cephalometric tracings derived from lateral and PA films (www.clinorthodres.com/cor-c-070). The accuracy of the reconstruction obtained with this inexpensive system is about 400 µ.

Tools for automating the imaging of zebrafish larvae.

PubMed

Pulak, Rock

2016-03-01

The VAST BioImager system is a set of tools developed for zebrafish researchers who require the collection of images from a large number of 2-7 dpf zebrafish larvae. The VAST BioImager automates larval handling, positioning and orientation tasks. Color images at about 10 μm resolution are collected from the on-board camera of the system. If images of greater resolution and detail are required, this system is mounted on an upright microscope, such as a confocal or fluorescence microscope, to utilize their capabilities. The system loads a larvae, positions it in view of the camera, determines orientation using pattern recognition analysis, and then more precisely positions to user-defined orientation for optimal imaging of any desired tissue or organ system. Multiple images of the same larva can be collected. The specific part of each larva and the desired orientation and position is identified by the researcher and an experiment defining the settings and a series of steps can be saved and repeated for imaging of subsequent larvae. The system captures images, then ejects and loads another larva from either a bulk reservoir, a well of a 96 well plate using the LP Sampler, or individually targeted larvae from a Petri dish or other container using the VAST Pipettor. Alternative manual protocols for handling larvae for image collection are tedious and time consuming. The VAST BioImager automates these steps to allow for greater throughput of assays and screens requiring high-content image collection of zebrafish larvae such as might be used in drug discovery and toxicology studies. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

Hyperchromatic laser scanning cytometry

NASA Astrophysics Data System (ADS)

Tárnok, Attila; Mittag, Anja

2007-02-01

In the emerging fields of high-content and high-throughput single cell analysis for Systems Biology and Cytomics multi- and polychromatic analysis of biological specimens has become increasingly important. Combining different technologies and staining methods polychromatic analysis (i.e. using 8 or more fluorescent colors at a time) can be pushed forward to measure anything stainable in a cell, an approach termed hyperchromatic cytometry. For cytometric cell analysis microscope based Slide Based Cytometry (SBC) technologies are ideal as, unlike flow cytometry, they are non-consumptive, i.e. the analyzed sample is fixed on the slide. Based on the feature of relocation identical cells can be subsequently reanalyzed. In this manner data on the single cell level after manipulation steps can be collected. In this overview various components for hyperchromatic cytometry are demonstrated for a SBC instrument, the Laser Scanning Cytometer (Compucyte Corp., Cambridge, MA): 1) polychromatic cytometry, 2) iterative restaining (using the same fluorochrome for restaining and subsequent reanalysis), 3) differential photobleaching (differentiating fluorochromes by their different photostability), 4) photoactivation (activating fluorescent nanoparticles or photocaged dyes), and 5) photodestruction (destruction of FRET dyes). With the intelligent combination of several of these techniques hyperchromatic cytometry allows to quantify and analyze virtually all components of relevance on the identical cell. The combination of high-throughput and high-content SBC analysis with high-resolution confocal imaging allows clear verification of phenotypically distinct subpopulations of cells with structural information. The information gained per specimen is only limited by the number of available antibodies and by sterical hindrance.

Influence of Alkali Resistant (Ar) Fibreglass in Porcelain Clay for Manufacturing Vitrified Clay Pipes

NASA Astrophysics Data System (ADS)

Ikhmal Hanapi, Muhammad; Ahmad, Sufizar; Taib, Hariati; Ismail, Al Emran; Nasrull Abdol Rahman, Mohd; Salleh, Salihatun Md; Sadikin, Azmahani; Mahzan, Shahruddin

2017-10-01

The aim of this work is to determine the characteristics of porcelain ceramic with influence of milled Alkali Resistant (AR) fiberglass for manufacturing vitrified clay pipes. In this study, raw materials consist of porcelain clay and AR fiberglass were refined into powders less than 90μm. Subsequently, these samples were compacted into cylindrical pellet for chemical analysis using X-Ray Fluorescence (XRF). The ceramic sample was produced by mixing different weight percentage of AR glass to porcelain ceramic with 3 wt%, 6 wt%, 9 wt% and 12 wt%. Subsequently, the sample was compacted with 3 ton of pressure load and sintered at 900 °C, 1000 °C, 1100 °C and 1200 °C. The phase identification by using X-Ray Diffraction (XRD) and microstructural analysis were performed for the sintered sample. Chemical analysis revealed that the significant element for all raw material are SiO2, Al2O3, Na2O and K2O. Phase identification analysis shown that sample sintered at 1000 °C produces quartz (SiO2), berlinite (AlPO4), albite (NaAlSi3O8) and calcium-magnesium-aluminum-silicate (CaMgAlSiO). The formation of primary mullite was observed in sample sintered at 1100 °C. The image of microstructural morphology denoted that the formation of glassy phase with decreasing amount of void when sintering temperature and addition of AR glass were increased, which correspond well to phase identification analysis.

Simulation approach for the evaluation of tracking accuracy in radiotherapy: a preliminary study.

PubMed

Tanaka, Rie; Ichikawa, Katsuhiro; Mori, Shinichiro; Sanada, Sigeru

2013-01-01

Real-time tumor tracking in external radiotherapy can be achieved by diagnostic (kV) X-ray imaging with a dynamic flat-panel detector (FPD). It is important to keep the patient dose as low as possible while maintaining tracking accuracy. A simulation approach would be helpful to optimize the imaging conditions. This study was performed to develop a computer simulation platform based on a noise property of the imaging system for the evaluation of tracking accuracy at any noise level. Flat-field images were obtained using a direct-type dynamic FPD, and noise power spectrum (NPS) analysis was performed. The relationship between incident quantum number and pixel value was addressed, and a conversion function was created. The pixel values were converted into a map of quantum number using the conversion function, and the map was then input into the random number generator to simulate image noise. Simulation images were provided at different noise levels by changing the incident quantum numbers. Subsequently, an implanted marker was tracked automatically and the maximum tracking errors were calculated at different noise levels. The results indicated that the maximum tracking error increased with decreasing incident quantum number in flat-field images with an implanted marker. In addition, the range of errors increased with decreasing incident quantum number. The present method could be used to determine the relationship between image noise and tracking accuracy. The results indicated that the simulation approach would aid in determining exposure dose conditions according to the necessary tracking accuracy.

The x-ray light valve: a potentially low-cost, digital radiographic imaging system-concept and implementation considerations.

PubMed

Webster, Christie Ann; Koprinarov, Ivaylo; Germann, Stephen; Rowlands, J A

2008-03-01

New x-ray radiographic systems based on large-area flat-panel technology have revolutionized our capability to produce digital x-ray images. However, these imagers are extraordinarily expensive compared to the systems they are replacing. Hence, there is a need for a low-cost digital imaging system for general applications in radiology. A novel potentially low-cost radiographic imaging system based on established technologies is proposed-the X-Ray Light Valve (XLV). This is a potentially high-quality digital x-ray detector made of a photoconducting layer and a liquid-crystal cell, physically coupled in a sandwich structure. Upon exposure to x rays, charge is collected on the surface of the photoconductor. This causes a change in the optical properties of the liquid-crystal cell and a visible image is generated. Subsequently, it is digitized by a scanned optical imager. The image formation is based on controlled modulation of light from an external source. The operation and practical implementation of the XLV system are described. The potential performance of the complete system and issues related to sensitivity, spatial resolution, noise, and speed are discussed. The feasibility of clinical use of an XLV device based on amorphous selenium (a-Se) as the photoconductor and a reflective electrically controlled birefringence cell is analyzed. The results of our analysis indicate that the XLV can potentially be adapted to a wide variety of radiographic tasks.

Ambient Mass Spectrometry Imaging Using Direct Liquid Extraction Techniques

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

Laskin, Julia; Lanekoff, Ingela

2015-11-13

Mass spectrometry imaging (MSI) is a powerful analytical technique that enables label-free spatial localization and identification of molecules in complex samples.1-4 MSI applications range from forensics5 to clinical research6 and from understanding microbial communication7-8 to imaging biomolecules in tissues.1, 9-10 Recently, MSI protocols have been reviewed.11 Ambient ionization techniques enable direct analysis of complex samples under atmospheric pressure without special sample pretreatment.3, 12-16 In fact, in ambient ionization mass spectrometry, sample processing (e.g., extraction, dilution, preconcentration, or desorption) occurs during the analysis.17 This substantially speeds up analysis and eliminates any possible effects of sample preparation on the localization of moleculesmore » in the sample.3, 8, 12-14, 18-20 Venter and co-workers have classified ambient ionization techniques into three major categories based on the sample processing steps involved: 1) liquid extraction techniques, in which analyte molecules are removed from the sample and extracted into a solvent prior to ionization; 2) desorption techniques capable of generating free ions directly from substrates; and 3) desorption techniques that produce larger particles subsequently captured by an electrospray plume and ionized.17 This review focuses on localized analysis and ambient imaging of complex samples using a subset of ambient ionization methods broadly defined as “liquid extraction techniques” based on the classification introduced by Venter and co-workers.17 Specifically, we include techniques where analyte molecules are desorbed from solid or liquid samples using charged droplet bombardment, liquid extraction, physisorption, chemisorption, mechanical force, laser ablation, or laser capture microdissection. Analyte extraction is followed by soft ionization that generates ions corresponding to intact species. Some of the key advantages of liquid extraction techniques include the ease of operation, ability to analyze samples in their native environments, speed of analysis, and ability to tune the extraction solvent composition to a problem at hand. For example, solvent composition may be optimized for efficient extraction of different classes of analytes from the sample or for quantification or online derivatization through reactive analysis. In this review, we will: 1) introduce individual liquid extraction techniques capable of localized analysis and imaging, 2) describe approaches for quantitative MSI experiments free of matrix effects, 3) discuss advantages of reactive analysis for MSI experiments, and 4) highlight selected applications (published between 2012 and 2015) that focus on imaging and spatial profiling of molecules in complex biological and environmental samples.« less