Penetration depth measurement of near-infrared hyperspectral imaging light for milk powder

USDA-ARS?s Scientific Manuscript database

The increasingly common application of near-infrared (NIR) hyperspectral imaging technique to the analysis of food powders has led to the need for optical characterization of samples. This study was aimed at exploring the feasibility of quantifying penetration depth of NIR hyperspectral imaging ligh...

Retinal imaging analysis based on vessel detection.

PubMed

Jamal, Arshad; Hazim Alkawaz, Mohammed; Rehman, Amjad; Saba, Tanzila

2017-07-01

With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art. © 2017 Wiley Periodicals, Inc.

An advanced software suite for the processing and analysis of silicon luminescence images

NASA Astrophysics Data System (ADS)

Payne, D. N. R.; Vargas, C.; Hameiri, Z.; Wenham, S. R.; Bagnall, D. M.

2017-06-01

Luminescence imaging is a versatile characterisation technique used for a broad range of research and industrial applications, particularly for the field of photovoltaics where photoluminescence and electroluminescence imaging is routinely carried out for materials analysis and quality control. Luminescence imaging can reveal a wealth of material information, as detailed in extensive literature, yet these techniques are often only used qualitatively instead of being utilised to their full potential. Part of the reason for this is the time and effort required for image processing and analysis in order to convert image data to more meaningful results. In this work, a custom built, Matlab based software suite is presented which aims to dramatically simplify luminescence image processing and analysis. The suite includes four individual programs which can be used in isolation or in conjunction to achieve a broad array of functionality, including but not limited to, point spread function determination and deconvolution, automated sample extraction, image alignment and comparison, minority carrier lifetime calibration and iron impurity concentration mapping.

Sensor, signal, and image informatics - state of the art and current topics.

PubMed

Lehmann, T M; Aach, T; Witte, H

2006-01-01

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

Application of He ion microscopy for material analysis

NASA Astrophysics Data System (ADS)

Altmann, F.; Simon, M.; Klengel, R.

2009-05-01

Helium ion beam microscopy (HIM) is a new high resolution imaging technique. The use of Helium ions instead of electrons enables none destructive imaging combined with contrasts quite similar to that from Gallium ion beam imaging. The use of very low probe currents and the comfortable charge compensation using low energy electrons offer imaging of none conductive samples without conductive coating. An ongoing microelectronic sample with Gold/Aluminum interconnects and polymer electronic devices were chosen to evaluate HIM in comparison to scanning electron microscopy (SEM). The aim was to look for key applications of HIM in material analysis. Main focus was on complementary contrast mechanisms and imaging of none conductive samples.

An online database for plant image analysis software tools.

PubMed

Lobet, Guillaume; Draye, Xavier; Périlleux, Claire

2013-10-09

Recent years have seen an increase in methods for plant phenotyping using image analyses. These methods require new software solutions for data extraction and treatment. These solutions are instrumental in supporting various research pipelines, ranging from the localisation of cellular compounds to the quantification of tree canopies. However, due to the variety of existing tools and the lack of central repository, it is challenging for researchers to identify the software that is best suited for their research. We present an online, manually curated, database referencing more than 90 plant image analysis software solutions. The website, plant-image-analysis.org, presents each software in a uniform and concise manner enabling users to identify the available solutions for their experimental needs. The website also enables user feedback, evaluations and new software submissions. The plant-image-analysis.org database provides an overview of existing plant image analysis software. The aim of such a toolbox is to help users to find solutions, and to provide developers a way to exchange and communicate about their work.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

PubMed

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

The Image of Women in the National Education Text Books in Jordan

ERIC Educational Resources Information Center

Al-Khalidi, Nasiema Mustafa Sadeq

2016-01-01

The study aimed to identify the image of women and how it was dealt with in the National Education books in Jordan, where the content of the National Education books analyzed and for multiple age stages, also it addressed the content analysis of images, concepts and fees, activities and evaluation to identify the image of women in the family, at…

Dedicated computer system AOTK for image processing and analysis of horse navicular bone

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Fojud, A.; Koszela, K.; Mueller, W.; Górna, K.; Okoń, P.; Piekarska-Boniecka, H.

2017-07-01

The aim of the research was made the dedicated application AOTK (pol. Analiza Obrazu Trzeszczki Kopytowej) for image processing and analysis of horse navicular bone. The application was produced by using specialized software like Visual Studio 2013 and the .NET platform. To implement algorithms of image processing and analysis were used libraries of Aforge.NET. Implemented algorithms enabling accurate extraction of the characteristics of navicular bones and saving data to external files. Implemented in AOTK modules allowing the calculations of distance selected by user, preliminary assessment of conservation of structure of the examined objects. The application interface is designed in a way that ensures user the best possible view of the analyzed images.

Cnn Based Retinal Image Upscaling Using Zero Component Analysis

NASA Astrophysics Data System (ADS)

Nasonov, A.; Chesnakov, K.; Krylov, A.

2017-05-01

The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.

Evaluation of quantitative image analysis criteria for the high-resolution microendoscopic detection of neoplasia in Barrett's esophagus

NASA Astrophysics Data System (ADS)

Muldoon, Timothy J.; Thekkek, Nadhi; Roblyer, Darren; Maru, Dipen; Harpaz, Noam; Potack, Jonathan; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2010-03-01

Early detection of neoplasia in patients with Barrett's esophagus is essential to improve outcomes. The aim of this ex vivo study was to evaluate the ability of high-resolution microendoscopic imaging and quantitative image analysis to identify neoplastic lesions in patients with Barrett's esophagus. Nine patients with pathologically confirmed Barrett's esophagus underwent endoscopic examination with biopsies or endoscopic mucosal resection. Resected fresh tissue was imaged with fiber bundle microendoscopy; images were analyzed by visual interpretation or by quantitative image analysis to predict whether the imaged sites were non-neoplastic or neoplastic. The best performing pair of quantitative features were chosen based on their ability to correctly classify the data into the two groups. Predictions were compared to the gold standard of histopathology. Subjective analysis of the images by expert clinicians achieved average sensitivity and specificity of 87% and 61%, respectively. The best performing quantitative classification algorithm relied on two image textural features and achieved a sensitivity and specificity of 87% and 85%, respectively. This ex vivo pilot trial demonstrates that quantitative analysis of images obtained with a simple microendoscope system can distinguish neoplasia in Barrett's esophagus with good sensitivity and specificity when compared to histopathology and to subjective image interpretation.

Image pattern recognition supporting interactive analysis and graphical visualization

NASA Technical Reports Server (NTRS)

Coggins, James M.

1992-01-01

Image Pattern Recognition attempts to infer properties of the world from image data. Such capabilities are crucial for making measurements from satellite or telescope images related to Earth and space science problems. Such measurements can be the required product itself, or the measurements can be used as input to a computer graphics system for visualization purposes. At present, the field of image pattern recognition lacks a unified scientific structure for developing and evaluating image pattern recognition applications. The overall goal of this project is to begin developing such a structure. This report summarizes results of a 3-year research effort in image pattern recognition addressing the following three principal aims: (1) to create a software foundation for the research and identify image pattern recognition problems in Earth and space science; (2) to develop image measurement operations based on Artificial Visual Systems; and (3) to develop multiscale image descriptions for use in interactive image analysis.

Breast cancer histopathology image analysis: a review.

PubMed

Veta, Mitko; Pluim, Josien P W; van Diest, Paul J; Viergever, Max A

2014-05-01

This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.

Exploring the feasibility of iris recognition for visible spectrum iris images obtained using smartphone camera

NASA Astrophysics Data System (ADS)

Trokielewicz, Mateusz; Bartuzi, Ewelina; Michowska, Katarzyna; Andrzejewska, Antonina; Selegrat, Monika

2015-09-01

In the age of modern, hyperconnected society that increasingly relies on mobile devices and solutions, implementing a reliable and accurate biometric system employing iris recognition presents new challenges. Typical biometric systems employing iris analysis require expensive and complicated hardware. We therefore explore an alternative way using visible spectrum iris imaging. This paper aims at answering several questions related to applying iris biometrics for images obtained in the visible spectrum using smartphone camera. Can irides be successfully and effortlessly imaged using a smartphone's built-in camera? Can existing iris recognition methods perform well when presented with such images? The main advantage of using near-infrared (NIR) illumination in dedicated iris recognition cameras is good performance almost independent of the iris color and pigmentation. Are the images obtained from smartphone's camera of sufficient quality even for the dark irides? We present experiments incorporating simple image preprocessing to find the best visibility of iris texture, followed by a performance study to assess whether iris recognition methods originally aimed at NIR iris images perform well with visible light images. To our best knowledge this is the first comprehensive analysis of iris recognition performance using a database of high-quality images collected in visible light using the smartphones flashlight together with the application of commercial off-the-shelf (COTS) iris recognition methods.

Image acquisitions, processing and analysis in the process of obtaining characteristics of horse navicular bone

NASA Astrophysics Data System (ADS)

Zaborowicz, M.; Włodarek, J.; Przybylak, A.; Przybył, K.; Wojcieszak, D.; Czekała, W.; Ludwiczak, A.; Boniecki, P.; Koszela, K.; Przybył, J.; Skwarcz, J.

2015-07-01

The aim of this study was investigate the possibility of using methods of computer image analysis for the assessment and classification of morphological variability and the state of health of horse navicular bone. Assumption was that the classification based on information contained in the graphical form two-dimensional digital images of navicular bone and information of horse health. The first step in the research was define the classes of analyzed bones, and then using methods of computer image analysis for obtaining characteristics from these images. This characteristics were correlated with data concerning the animal, such as: side of hooves, number of navicular syndrome (scale 0-3), type, sex, age, weight, information about lace, information about heel. This paper shows the introduction to the study of use the neural image analysis in the diagnosis of navicular bone syndrome. Prepared method can provide an introduction to the study of non-invasive way to assess the condition of the horse navicular bone.

Landsat image and sample design for water reservoirs (Rapel dam Central Chile).

PubMed

Lavanderos, L; Pozo, M E; Pattillo, C; Miranda, H

1990-01-01

Spatial heterogeneity of the Rapel reservoir surface waters is analyzed through Landsat images. The image digital counts are used with the aim or developing an aprioristic quantitative sample design.Natural horizontal stratification of the Rapel Reservoir (Central Chile) is produced mainly by suspended solids. The spatial heterogeneity conditions of the reservoir for the Spring 86-Summer 87 period were determined by qualitative analysis and image processing of the MSS Landsat, bands 1 and 3. The space-time variations of the different observed strata obtained with multitemporal image analysis.A random stratified sample design (r.s.s.d) was developed, based on the digital counts statistical analysis. Strata population size as well as the average, variance and sampling size of the digital counts were obtained by the r.s.s.d method.Stratification determined by analysis of satellite images were later correlated with ground data. Though the stratification of the reservoir is constant over time, the shape and size of the strata varys.

A Comparative Evaluation of Mixed Dentition Analysis on Reliability of Cone Beam Computed Tomography Image Compared to Plaster Model.

PubMed

Gowd, Snigdha; Shankar, T; Dash, Samarendra; Sahoo, Nivedita; Chatterjee, Suravi; Mohanty, Pritam

2017-01-01

The aim of the study was to evaluate the reliability of cone beam computed tomography (CBCT) obtained image over plaster model for the assessment of mixed dentition analysis. Thirty CBCT-derived images and thirty plaster models were derived from the dental archives, and Moyer's and Tanaka-Johnston analyses were performed. The data obtained were interpreted and analyzed statistically using SPSS 10.0/PC (SPSS Inc., Chicago, IL, USA). Descriptive and analytical analysis along with Student's t -test was performed to qualitatively evaluate the data and P < 0.05 was considered statistically significant. Statistically, significant results were obtained on data comparison between CBCT-derived images and plaster model; the mean for Moyer's analysis in the left and right lower arch for CBCT and plaster model was 21.2 mm, 21.1 mm and 22.5 mm, 22.5 mm, respectively. CBCT-derived images were less reliable as compared to data obtained directly from plaster model for mixed dentition analysis.

Standardisation of DNA quantitation by image analysis: quality control of instrumentation.

PubMed

Puech, M; Giroud, F

1999-05-01

DNA image analysis is frequently performed in clinical practice as a prognostic tool and to improve diagnosis. The precision of prognosis and diagnosis depends on the accuracy of analysis and particularly on the quality of image analysis systems. It has been reported that image analysis systems used for DNA quantification differ widely in their characteristics (Thunissen et al.: Cytometry 27: 21-25, 1997). This induces inter-laboratory variations when the same sample is analysed in different laboratories. In microscopic image analysis, the principal instrumentation errors arise from the optical and electronic parts of systems. They bring about problems of instability, non-linearity, and shading and glare phenomena. The aim of this study is to establish tools and standardised quality control procedures for microscopic image analysis systems. Specific reference standard slides have been developed to control instability, non-linearity, shading and glare phenomena and segmentation efficiency. Some systems have been controlled with these tools and these quality control procedures. Interpretation criteria and accuracy limits of these quality control procedures are proposed according to the conclusions of a European project called PRESS project (Prototype Reference Standard Slide). Beyond these limits, tested image analysis systems are not qualified to realise precise DNA analysis. The different procedures presented in this work determine if an image analysis system is qualified to deliver sufficiently precise DNA measurements for cancer case analysis. If the controlled systems are beyond the defined limits, some recommendations are given to find a solution to the problem.

CLINICAL AUDIT OF IMAGE QUALITY IN RADIOLOGY USING VISUAL GRADING CHARACTERISTICS ANALYSIS.

PubMed

Tesselaar, Erik; Dahlström, Nils; Sandborg, Michael

2016-06-01

The aim of this work was to assess whether an audit of clinical image quality could be efficiently implemented within a limited time frame using visual grading characteristics (VGC) analysis. Lumbar spine radiography, bedside chest radiography and abdominal CT were selected. For each examination, images were acquired or reconstructed in two ways. Twenty images per examination were assessed by 40 radiology residents using visual grading of image criteria. The results were analysed using VGC. Inter-observer reliability was assessed. The results of the visual grading analysis were consistent with expected outcomes. The inter-observer reliability was moderate to good and correlated with perceived image quality (r(2) = 0.47). The median observation time per image or image series was within 2 min. These results suggest that the use of visual grading of image criteria to assess the quality of radiographs provides a rapid method for performing an image quality audit in a clinical environment. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Analysis of a New Variational Model to Restore Point-Like and Curve-Like Singularities in Imaging

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

Aubert, Gilles, E-mail: gaubert@unice.fr; Blanc-Feraud, Laure, E-mail: Laure.Blanc-Feraud@inria.fr; Graziani, Daniele, E-mail: Daniele.Graziani@inria.fr

2013-02-15

The paper is concerned with the analysis of a new variational model to restore point-like and curve-like singularities in biological images. To this aim we investigate the variational properties of a suitable energy which governs these pathologies. Finally in order to realize numerical experiments we minimize, in the discrete setting, a regularized version of this functional by fast descent gradient scheme.

The application of computer image analysis in life sciences and environmental engineering

NASA Astrophysics Data System (ADS)

Mazur, R.; Lewicki, A.; Przybył, K.; Zaborowicz, M.; Koszela, K.; Boniecki, P.; Mueller, W.; Raba, B.

2014-04-01

The main aim of the article was to present research on the application of computer image analysis in Life Science and Environmental Engineering. The authors used different methods of computer image analysis in developing of an innovative biotest in modern biomonitoring of water quality. Created tools were based on live organisms such as bioindicators Lemna minor L. and Hydra vulgaris Pallas as well as computer image analysis method in the assessment of negatives reactions during the exposition of the organisms to selected water toxicants. All of these methods belong to acute toxicity tests and are particularly essential in ecotoxicological assessment of water pollutants. Developed bioassays can be used not only in scientific research but are also applicable in environmental engineering and agriculture in the study of adverse effects on water quality of various compounds used in agriculture and industry.

Learning a cost function for microscope image segmentation.

PubMed

Nilufar, Sharmin; Perkins, Theodore J

2014-01-01

Quantitative analysis of microscopy images is increasingly important in clinical researchers' efforts to unravel the cellular and molecular determinants of disease, and for pathological analysis of tissue samples. Yet, manual segmentation and measurement of cells or other features in images remains the norm in many fields. We report on a new system that aims for robust and accurate semi-automated analysis of microscope images. A user interactively outlines one or more examples of a target object in a training image. We then learn a cost function for detecting more objects of the same type, either in the same or different images. The cost function is incorporated into an active contour model, which can efficiently determine optimal boundaries by dynamic programming. We validate our approach and compare it to some standard alternatives on three different types of microscopic images: light microscopy of blood cells, light microscopy of muscle tissue sections, and electron microscopy cross-sections of axons and their myelin sheaths.

Applications of independent component analysis in SAR images

NASA Astrophysics Data System (ADS)

Huang, Shiqi; Cai, Xinhua; Hui, Weihua; Xu, Ping

2009-07-01

The detection of faint, small and hidden targets in synthetic aperture radar (SAR) image is still an issue for automatic target recognition (ATR) system. How to effectively separate these targets from the complex background is the aim of this paper. Independent component analysis (ICA) theory can enhance SAR image targets and improve signal clutter ratio (SCR), which benefits to detect and recognize faint targets. Therefore, this paper proposes a new SAR image target detection algorithm based on ICA. In experimental process, the fast ICA (FICA) algorithm is utilized. Finally, some real SAR image data is used to test the method. The experimental results verify that the algorithm is feasible, and it can improve the SCR of SAR image and increase the detection rate for the faint small targets.

BATSE imaging survey of the Galactic plane

NASA Technical Reports Server (NTRS)

Grindlay, J. E.; Barret, D.; Bloser, P. F.; Zhang, S. N.; Robinson, C.; Harmon, B. A.

1997-01-01

The burst and transient source experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO) provides all sky monitoring capability, occultation analysis and occultation imaging which enables new and fainter sources to be searched for in relatively crowded fields. The occultation imaging technique is used in combination with an automated BATSE image scanner, allowing an analysis of large data sets of occultation images for detections of candidate sources and for the construction of source catalogs and data bases. This automated image scanner system is being tested on archival data in order to optimize the search and detection thresholds. The image search system, its calibration results and preliminary survey results on archival data are reported on. The aim of the survey is to identify a complete sample of black hole candidates in the galaxy and constrain the number of black hole systems and neutron star systems.

Fractal-Based Image Analysis In Radiological Applications

NASA Astrophysics Data System (ADS)

Dellepiane, S.; Serpico, S. B.; Vernazza, G.; Viviani, R.

1987-10-01

We present some preliminary results of a study aimed to assess the actual effectiveness of fractal theory and to define its limitations in the area of medical image analysis for texture description, in particular, in radiological applications. A general analysis to select appropriate parameters (mask size, tolerance on fractal dimension estimation, etc.) has been performed on synthetically generated images of known fractal dimensions. Moreover, we analyzed some radiological images of human organs in which pathological areas can be observed. Input images were subdivided into blocks of 6x6 pixels; then, for each block, the fractal dimension was computed in order to create fractal images whose intensity was related to the D value, i.e., texture behaviour. Results revealed that the fractal images could point out the differences between normal and pathological tissues. By applying histogram-splitting segmentation to the fractal images, pathological areas were isolated. Two different techniques (i.e., the method developed by Pentland and the "blanket" method) were employed to obtain fractal dimension values, and the results were compared; in both cases, the appropriateness of the fractal description of the original images was verified.

Investigation into How 8th Grade Students Define Fractals

ERIC Educational Resources Information Center

Karakus, Fatih

2015-01-01

The analysis of 8th grade students' concept definitions and concept images can provide information about their mental schema of fractals. There is limited research on students' understanding and definitions of fractals. Therefore, this study aimed to investigate the elementary students' definitions of fractals based on concept image and concept…

Towards a framework for agent-based image analysis of remote-sensing data

PubMed Central

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-01-01

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA). PMID:27721916

Towards a framework for agent-based image analysis of remote-sensing data.

PubMed

Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

2015-04-03

Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects' properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

Towards adaptive, streaming analysis of x-ray tomography data

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

Thomas, Mathew; Kleese van Dam, Kerstin; Marshall, Matthew J.

2015-03-04

Temporal and spatial resolution of chemical imaging methodologies such as x-ray tomography are rapidly increasing, leading to more complex experimental procedures and fast growing data volumes. Automated analysis pipelines and big data analytics are becoming essential to effectively evaluate the results of such experiments. Offering those data techniques in an adaptive, streaming environment can further substantially improve the scientific discovery process, by enabling experimental control and steering based on the evaluation of emerging phenomena as they are observed by the experiment. Pacific Northwest National Laboratory (PNNL)’ Chemical Imaging Initiative (CII - http://imaging.pnnl.gov/ ) has worked since 2011 towards developing amore » framework that allows users to rapidly compose and customize high throughput experimental analysis pipelines for multiple instrument types. The framework, named ‘Rapid Experimental Analysis’ (REXAN) Framework [1], is based on the idea of reusable component libraries and utilizes the PNNL developed collaborative data management and analysis environment ‘Velo’, to provide a user friendly analysis and data management environment for experimental facilities. This article will, discuss the capabilities established for X-Ray tomography, discuss lessons learned, and provide an overview of our more recent work in the Analysis in Motion Initiative (AIM - http://aim.pnnl.gov/ ) at PNNL to provide REXAN capabilities in a streaming environment.« less

Ripening of salami: assessment of colour and aspect evolution using image analysis and multivariate image analysis.

PubMed

Fongaro, Lorenzo; Alamprese, Cristina; Casiraghi, Ernestina

2015-03-01

During ripening of salami, colour changes occur due to oxidation phenomena involving myoglobin. Moreover, shrinkage due to dehydration results in aspect modifications, mainly ascribable to fat aggregation. The aim of this work was the application of image analysis (IA) and multivariate image analysis (MIA) techniques to the study of colour and aspect changes occurring in salami during ripening. IA results showed that red, green, blue, and intensity parameters decreased due to the development of a global darker colour, while Heterogeneity increased due to fat aggregation. By applying MIA, different salami slice areas corresponding to fat and three different degrees of oxidised meat were identified and quantified. It was thus possible to study the trend of these different areas as a function of ripening, making objective an evaluation usually performed by subjective visual inspection. Copyright © 2014 Elsevier Ltd. All rights reserved.

BaTMAn: Bayesian Technique for Multi-image Analysis

NASA Astrophysics Data System (ADS)

Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

2016-12-01

Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

MicroCT parameters for multimaterial elements assessment

NASA Astrophysics Data System (ADS)

de Araújo, Olga M. O.; Silva Bastos, Jaqueline; Machado, Alessandra S.; dos Santos, Thaís M. P.; Ferreira, Cintia G.; Rosifini Alves Claro, Ana Paula; Lopes, Ricardo T.

2018-03-01

Microtomography is a non-destructive testing technique for quantitative and qualitative analysis. The investigation of multimaterial elements with great difference of density can result in artifacts that degrade image quality depending on combination of additional filter. The aim of this study is the selection of parameters most appropriate for analysis of bone tissue with metallic implant. The results show the simulation with MCNPX code for the distribution of energy without additional filter, with use of aluminum, copper and brass filters and their respective reconstructed images showing the importance of the choice of these parameters in image acquisition process on computed microtomography.

GENOMIC DIVERSITY AND THE MICROENVIRONMENT AS DRIVERS OF PROGRESSION IN DCIS

DTIC Science & Technology

2017-10-01

stains, including quantitative analysis, 7) Identification of upstaged DCIS cases for the radiology aim, 8) Development of image analysis methods for...goals of the project? Aim 1. Determine whether genetic diversity of DCIS is greater in DCIS with adjacent invasive disease compared to DCIS without... compared to DCIS without IDC. Since genomics is not the sole driver of tumor behavior, we will phenotypically characterize DCIS and its

Qualitative and quantitative interpretation of SEM image using digital image processing.

PubMed

Saladra, Dawid; Kopernik, Magdalena

2016-10-01

The aim of the this study is improvement of qualitative and quantitative analysis of scanning electron microscope micrographs by development of computer program, which enables automatic crack analysis of scanning electron microscopy (SEM) micrographs. Micromechanical tests of pneumatic ventricular assist devices result in a large number of micrographs. Therefore, the analysis must be automatic. Tests for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates (Bionate II) are performed. These tests include microshear, microtension and fatigue analysis. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope images was achieved by a set of computational tools that includes binarization, simplified expanding, expanding, simple image statistic thresholding, the filters Laplacian 1, and Laplacian 2, Otsu and reverse binarization. Several modifications of the known image processing techniques and combinations of the selected image processing techniques were applied. The introduced quantitative analysis of digital scanning electron microscope images enables computation of stereological parameters such as area, crack angle, crack length, and total crack length per unit area. This study also compares the functionality of the developed computer program of digital image processing with existing applications. The described pre- and postprocessing may be helpful in scanning electron microscopy and transmission electron microscopy surface investigations. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Model-based quantification of image quality

NASA Technical Reports Server (NTRS)

Hazra, Rajeeb; Miller, Keith W.; Park, Stephen K.

1989-01-01

In 1982, Park and Schowengerdt published an end-to-end analysis of a digital imaging system quantifying three principal degradation components: (1) image blur - blurring caused by the acquisition system, (2) aliasing - caused by insufficient sampling, and (3) reconstruction blur - blurring caused by the imperfect interpolative reconstruction. This analysis, which measures degradation as the square of the radiometric error, includes the sample-scene phase as an explicit random parameter and characterizes the image degradation caused by imperfect acquisition and reconstruction together with the effects of undersampling and random sample-scene phases. In a recent paper Mitchell and Netravelli displayed the visual effects of the above mentioned degradations and presented subjective analysis about their relative importance in determining image quality. The primary aim of the research is to use the analysis of Park and Schowengerdt to correlate their mathematical criteria for measuring image degradations with subjective visual criteria. Insight gained from this research can be exploited in the end-to-end design of optical systems, so that system parameters (transfer functions of the acquisition and display systems) can be designed relative to each other, to obtain the best possible results using quantitative measurements.

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.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

The analysis of optical-electro collimated light tube measurement system

NASA Astrophysics Data System (ADS)

Li, Zhenhui; Jiang, Tao; Cao, Guohua; Wang, Yanfei

2005-12-01

A new type of collimated light tube (CLT) is mentioned in this paper. The analysis and structure of CLT are described detail. The reticle and discrimination board are replaced by a optical-electro graphics generator, or DLP-Digital Light Processor. DLP gives all kinds of graphics controlled by computer, the lighting surface lies on the focus of the CLT. The rays of light pass through the CLT, and the tested products, the image of aim is received by variant focus objective CCD camera, the image can be processed by computer, then, some basic optical parameters will be obtained, such as optical aberration, image slope, etc. At the same time, motorized translation stage carry the DLP moving to simulate the limited distance. The grating ruler records the displacement of the DLP. The key technique is optical-electro auto-focus, the best imaging quality can be gotten by moving 6-D motorized positioning stage. Some principal questions can be solved in this device, for example, the aim generating, the structure of receiving system and optical matching.

Design and validation of Segment--freely available software for cardiovascular image analysis.

PubMed

Heiberg, Einar; Sjögren, Jane; Ugander, Martin; Carlsson, Marcus; Engblom, Henrik; Arheden, Håkan

2010-01-11

Commercially available software for cardiovascular image analysis often has limited functionality and frequently lacks the careful validation that is required for clinical studies. We have already implemented a cardiovascular image analysis software package and released it as freeware for the research community. However, it was distributed as a stand-alone application and other researchers could not extend it by writing their own custom image analysis algorithms. We believe that the work required to make a clinically applicable prototype can be reduced by making the software extensible, so that researchers can develop their own modules or improvements. Such an initiative might then serve as a bridge between image analysis research and cardiovascular research. The aim of this article is therefore to present the design and validation of a cardiovascular image analysis software package (Segment) and to announce its release in a source code format. Segment can be used for image analysis in magnetic resonance imaging (MRI), computed tomography (CT), single photon emission computed tomography (SPECT) and positron emission tomography (PET). Some of its main features include loading of DICOM images from all major scanner vendors, simultaneous display of multiple image stacks and plane intersections, automated segmentation of the left ventricle, quantification of MRI flow, tools for manual and general object segmentation, quantitative regional wall motion analysis, myocardial viability analysis and image fusion tools. Here we present an overview of the validation results and validation procedures for the functionality of the software. We describe a technique to ensure continued accuracy and validity of the software by implementing and using a test script that tests the functionality of the software and validates the output. The software has been made freely available for research purposes in a source code format on the project home page http://segment.heiberg.se. Segment is a well-validated comprehensive software package for cardiovascular image analysis. It is freely available for research purposes provided that relevant original research publications related to the software are cited.

A software tool for automatic classification and segmentation of 2D/3D medical images

NASA Astrophysics Data System (ADS)

Strzelecki, Michal; Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur

2013-02-01

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided.

Novel imaging closed loop control strategy for heliostats

NASA Astrophysics Data System (ADS)

Bern, Gregor; Schöttl, Peter; Heimsath, Anna; Nitz, Peter

2017-06-01

Central Receiver Systems use up to thousands of heliostats to concentrate solar radiation. The precise control of heliostat aiming points is crucial not only for efficiency but also for reliable plant operation. Besides the calibration of open loop control systems, closed loop tracking strategies are developed to address a precise and efficient aiming strategy. The need for cost reductions in the heliostat field intensifies the motivation for economic closed loop control systems. This work introduces an approach for a closed loop heliostat tracking strategy using image analysis and signal modulation. The approach aims at the extraction of heliostat focal spot position within the receiver domain by means of a centralized remote vision system decoupled from the rough conditions close to the focal area. Taking an image sequence of the receiver while modulating a signal on different heliostats, their aiming points are retrieved. The work describes the methodology and shows first results from simulations and practical tests performed in small scale, motivating further investigation and deployment.

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.

Pilot Study of an Open-source Image Analysis Software for Automated Screening of Conventional Cervical Smears.

PubMed

Sanyal, Parikshit; Ganguli, Prosenjit; Barui, Sanghita; Deb, Prabal

2018-01-01

The Pap stained cervical smear is a screening tool for cervical cancer. Commercial systems are used for automated screening of liquid based cervical smears. However, there is no image analysis software used for conventional cervical smears. The aim of this study was to develop and test the diagnostic accuracy of a software for analysis of conventional smears. The software was developed using Python programming language and open source libraries. It was standardized with images from Bethesda Interobserver Reproducibility Project. One hundred and thirty images from smears which were reported Negative for Intraepithelial Lesion or Malignancy (NILM), and 45 images where some abnormality has been reported, were collected from the archives of the hospital. The software was then tested on the images. The software was able to segregate images based on overall nuclear: cytoplasmic ratio, coefficient of variation (CV) in nuclear size, nuclear membrane irregularity, and clustering. 68.88% of abnormal images were flagged by the software, as well as 19.23% of NILM images. The major difficulties faced were segmentation of overlapping cell clusters and separation of neutrophils. The software shows potential as a screening tool for conventional cervical smears; however, further refinement in technique is required.

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.

Facial fluid synthesis for assessment of acne vulgaris using luminescent visualization system through optical imaging and integration of fluorescent imaging system

NASA Astrophysics Data System (ADS)

Balbin, Jessie R.; Dela Cruz, Jennifer C.; Camba, Clarisse O.; Gozo, Angelo D.; Jimenez, Sheena Mariz B.; Tribiana, Aivje C.

2017-06-01

Acne vulgaris, commonly called as acne, is a skin problem that occurs when oil and dead skin cells clog up in a person's pores. This is because hormones change which makes the skin oilier. The problem is people really do not know the real assessment of sensitivity of their skin in terms of fluid development on their faces that tends to develop acne vulgaris, thus having more complications. This research aims to assess Acne Vulgaris using luminescent visualization system through optical imaging and integration of image processing algorithms. Specifically, this research aims to design a prototype for facial fluid analysis using luminescent visualization system through optical imaging and integration of fluorescent imaging system, and to classify different facial fluids present in each person. Throughout the process, some structures and layers of the face will be excluded, leaving only a mapped facial structure with acne regions. Facial fluid regions are distinguished from the acne region as they are characterized differently.

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

PubMed

Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

2017-01-01

Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.

Comparison of histomorphometrical data obtained with two different image analysis methods.

PubMed

Ballerini, Lucia; Franke-Stenport, Victoria; Borgefors, Gunilla; Johansson, Carina B

2007-08-01

A common way to determine tissue acceptance of biomaterials is to perform histomorphometrical analysis on histologically stained sections from retrieved samples with surrounding tissue, using various methods. The "time and money consuming" methods and techniques used are often "in house standards". We address light microscopic investigations of bone tissue reactions on un-decalcified cut and ground sections of threaded implants. In order to screen sections and generate results faster, the aim of this pilot project was to compare results generated with the in-house standard visual image analysis tool (i.e., quantifications and judgements done by the naked eye) with a custom made automatic image analysis program. The histomorphometrical bone area measurements revealed no significant differences between the methods but the results of the bony contacts varied significantly. The raw results were in relative agreement, i.e., the values from the two methods were proportional to each other: low bony contact values in the visual method corresponded to low values with the automatic method. With similar resolution images and further improvements of the automatic method this difference should become insignificant. A great advantage using the new automatic image analysis method is that it is time saving--analysis time can be significantly reduced.

Syntactic methods of shape feature description and its application in analysis of medical images

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Tadeusiewicz, Ryszard

2000-02-01

The paper presents specialist algorithms of morphologic analysis of shapes of selected organs of abdominal cavity proposed in order to diagnose disease symptoms occurring in the main pancreatic ducts and upper segments of ureters. Analysis of the correct morphology of these structures has been conducted with the use of syntactic methods of pattern recognition. Its main objective is computer-aided support to early diagnosis of neoplastic lesions and pancreatitis based on images taken in the course of examination with the endoscopic retrograde cholangiopancreatography (ERCP) method and a diagnosis of morphological lesions in ureter based on kidney radiogram analysis. In the analysis of ERCP images, the main objective is to recognize morphological lesions in pancreas ducts characteristic for carcinoma and chronic pancreatitis. In the case of kidney radiogram analysis the aim is to diagnose local irregularity of ureter lumen. Diagnosing the above mentioned lesion has been conducted with the use of syntactic methods of pattern recognition, in particular the languages of shape features description and context-free attributed grammars. These methods allow to recognize and describe in a very efficient way the aforementioned lesions on images obtained as a result of initial image processing into diagrams of widths of the examined structures.

[Advances in automatic detection technology for images of thin blood film of malaria parasite].

PubMed

Juan-Sheng, Zhang; Di-Qiang, Zhang; Wei, Wang; Xiao-Guang, Wei; Zeng-Guo, Wang

2017-05-05

This paper reviews the computer vision and image analysis studies aiming at automated diagnosis or screening of malaria in microscope images of thin blood film smears. On the basis of introducing the background and significance of automatic detection technology, the existing detection technologies are summarized and divided into several steps, including image acquisition, pre-processing, morphological analysis, segmentation, count, and pattern classification components. Then, the principles and implementation methods of each step are given in detail. In addition, the promotion and application in automatic detection technology of thick blood film smears are put forwarded as questions worthy of study, and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

Towards a computer-aided diagnosis system for vocal cord diseases.

PubMed

Verikas, A; Gelzinis, A; Bacauskiene, M; Uloza, V

2006-01-01

The objective of this work is to investigate a possibility of creating a computer-aided decision support system for an automated analysis of vocal cord images aiming to categorize diseases of vocal cords. The problem is treated as a pattern recognition task. To obtain a concise and informative representation of a vocal cord image, colour, texture, and geometrical features are used. The representation is further analyzed by a pattern classifier categorizing the image into healthy, diffuse, and nodular classes. The approach developed was tested on 785 vocal cord images collected at the Department of Otolaryngology, Kaunas University of Medicine, Lithuania. A correct classification rate of over 87% was obtained when categorizing a set of unseen images into the aforementioned three classes. Bearing in mind the high similarity of the decision classes, the results obtained are rather encouraging and the developed tools could be very helpful for assuring objective analysis of the images of laryngeal diseases.

Spatiotemporal Analysis of High-Speed Videolaryngoscopic Imaging of Organic Pathologies in Males

ERIC Educational Resources Information Center

Bohr, Christopher; Kräck, Angelika; Dubrovskiy Denis; Eysholdt, Ulrich; Svec, Jan; Psychogios, Georgios; Ziethe, Anke; Döllinger, Michael

2014-01-01

Purpose: The aim of this study was to identify parameters that would differentiate healthy from pathological organic-based vocal fold vibrations to emphasize clinical usefulness of high-speed imaging. Method: Fifty-five men (M age = 36 years, SD = 20 years) were examined and separated into 4 groups: 1 healthy (26 individuals) and 3 pathological…

Gifted Students' Metaphor Images about Mathematics

ERIC Educational Resources Information Center

Arikan, Elif Esra; Unal, Hasan

2015-01-01

The aim of this study is to investigate the metaphors images of gifted students about mathematics. The sample of the study consists of 82 gifted students, which are 2, 3, 4, 5, 6, 7 graders, from Istanbul. Data were collected by asking students to complete the sentence: "Mathematics is as …, because…". In the study content analysis was…

The Wide-Field Imaging Interferometry Testbed (WIIT): Recent Progress and Results

NASA Technical Reports Server (NTRS)

Rinehart, Stephen A.; Frey, Bradley J.; Leisawitz, David T.; Lyon, Richard G.; Maher, Stephen F.; Martino, Anthony J.

2008-01-01

Continued research with the Wide-Field Imaging Interferometry Testbed (WIIT) has achieved several important milestones. We have moved WIIT into the Advanced Interferometry and Metrology (AIM) Laboratory at Goddard, and have characterized the testbed in this well-controlled environment. The system is now completely automated and we are in the process of acquiring large data sets for analysis. In this paper, we discuss these new developments and outline our future research directions. The WIIT testbed, combined with new data analysis techniques and algorithms, provides a demonstration of the technique of wide-field interferometric imaging, a powerful tool for future space-borne interferometers.

Improving lip wrinkles: lipstick-related image analysis.

PubMed

Ryu, Jong-Seong; Park, Sun-Gyoo; Kwak, Taek-Jong; Chang, Min-Youl; Park, Moon-Eok; Choi, Khee-Hwan; Sung, Kyung-Hye; Shin, Hyun-Jong; Lee, Cheon-Koo; Kang, Yun-Seok; Yoon, Moung-Seok; Rang, Moon-Jeong; Kim, Seong-Jin

2005-08-01

The appearance of lip wrinkles is problematic if it is adversely influenced by lipstick make-up causing incomplete color tone, spread phenomenon and pigment remnants. It is mandatory to develop an objective assessment method for lip wrinkle status by which the potential of wrinkle-improving products to lips can be screened. The present study is aimed at finding out the useful parameters from the image analysis of lip wrinkles that is affected by lipstick application. The digital photograph image of lips before and after lipstick application was assessed from 20 female volunteers. Color tone was measured by Hue, Saturation and Intensity parameters, and time-related pigment spread was calculated by the area over vermilion border by image-analysis software (Image-Pro). The efficacy of wrinkle-improving lipstick containing asiaticoside was evaluated from 50 women by using subjective and objective methods including image analysis in a double-blind placebo-controlled fashion. The color tone and spread phenomenon after lipstick make-up were remarkably affected by lip wrinkles. The level of standard deviation by saturation value of image-analysis software was revealed as a good parameter for lip wrinkles. By using the lipstick containing asiaticoside for 8 weeks, the change of visual grading scores and replica analysis indicated the wrinkle-improving effect. As the depth and number of wrinkles were reduced, the lipstick make-up appearance by image analysis also improved significantly. The lip wrinkle pattern together with lipstick make-up can be evaluated by the image-analysis system in addition to traditional assessment methods. Thus, this evaluation system is expected to test the efficacy of wrinkle-reducing lipstick that was not described in previous dermatologic clinical studies.

Comparison of binary mask defect printability analysis using virtual stepper system and aerial image microscope system

NASA Astrophysics Data System (ADS)

Phan, Khoi A.; Spence, Chris A.; Dakshina-Murthy, S.; Bala, Vidya; Williams, Alvina M.; Strener, Steve; Eandi, Richard D.; Li, Junling; Karklin, Linard

1999-12-01

As advanced process technologies in the wafer fabs push the patterning processes toward lower k1 factor for sub-wavelength resolution printing, reticles are required to use optical proximity correction (OPC) and phase-shifted mask (PSM) for resolution enhancement. For OPC/PSM mask technology, defect printability is one of the major concerns. Current reticle inspection tools available on the market sometimes are not capable of consistently differentiating between an OPC feature and a true random defect. Due to the process complexity and high cost associated with the making of OPC/PSM reticles, it is important for both mask shops and lithography engineers to understand the impact of different defect types and sizes to the printability. Aerial Image Measurement System (AIMS) has been used in the mask shops for a number of years for reticle applications such as aerial image simulation and transmission measurement of repaired defects. The Virtual Stepper System (VSS) provides an alternative method to do defect printability simulation and analysis using reticle images captured by an optical inspection or review system. In this paper, pre- programmed defects and repairs from a Defect Sensitivity Monitor (DSM) reticle with 200 nm minimum features (at 1x) will be studied for printability. The simulated resist lines by AIMS and VSS are both compared to SEM images of resist wafers qualitatively and quantitatively using CD verification.Process window comparison between unrepaired and repaired defects for both good and bad repair cases will be shown. The effect of mask repairs to resist pattern images for the binary mask case will be discussed. AIMS simulation was done at the International Sematech, Virtual stepper simulation at Zygo and resist wafers were processed at AMD-Submicron Development Center using a DUV lithographic process for 0.18 micrometer Logic process technology.

Repeatability of diagnostic ultrasonography in the assessment of the equine superficial digital flexor tendon.

PubMed

Pickersgill, C H; Marr, C M; Reid, S W

2001-01-01

A quantitative investigation of the variation that can occur during the course of ultrasonography of the equine superficial digital flexor tendons (SDFT) was undertaken. The aim of this investigation was to use an objective measure, namely the measurement of CSA, to quantify the variability occurring during the course of the ultrasonographic assessment of the equine SDFT. The effects of 3 variables on the CSA measurements were determined. 1) Image acquisition operator (IAc): two different operators undertaking the ultrasonographic examination; 2) image analysis operator (IAn): two different operators undertaking the calculation of CSA values from previously stored images; and 3) analytical equipment (used during CSA measurement) (IEq): the use of 2 different sets of equipment during calculation of CSA values. Tendon cross-sectional area (CSA) measurements were used as the comparative variable of 3 potential sources: interoperator, during image acquisition; interoperator, during CSA measurement; and intraoperator, when using different analytical equipment. Two operators obtained transverse ultrasonographic images from the forelimb SDFTs of 16 National Hunt (NH) Thoroughbred (TB) racehorses, each undertaking analysis of their own and the other operator's images. One operator undertook analysis of their images using 2 sets of equipment. There was no statistically significant difference in the results obtained when different operators undertook image acquisition (P>0.05). At all but the most distal level, there was no significant difference when different equipment was used during analysis (P>0.05). A significant difference (P<0.01) was reported when different operators undertook image analysis, one operator consistently returning larger measurements. Different operators undertaking different stages of an examination can result in significant variability. To reduce confounding during ultrasonographic investigations involving multiple persons, one operator should undertake image analysis, although different operators may undertake image acquisition.

The performance of magnetic resonance imaging in the detection of triangular fibrocartilage complex injury: a meta-analysis.

PubMed

Wang, Z X; Chen, S L; Wang, Q Q; Liu, B; Zhu, J; Shen, J

2015-06-01

The aim of this study was to evaluate the accuracy of magnetic resonance imaging in the detection of triangular fibrocartilage complex injury through a meta-analysis. A comprehensive literature search was conducted before 1 April 2014. All studies comparing magnetic resonance imaging results with arthroscopy or open surgery findings were reviewed, and 25 studies that satisfied the eligibility criteria were included. Data were pooled to yield pooled sensitivity and specificity, which were respectively 0.83 and 0.82. In detection of central and peripheral tears, magnetic resonance imaging had respectively a pooled sensitivity of 0.90 and 0.88 and a pooled specificity of 0.97 and 0.97. Six high-quality studies using Ringler's recommended magnetic resonance imaging parameters were selected for analysis to determine whether optimal imaging protocols yielded better results. The pooled sensitivity and specificity of these six studies were 0.92 and 0.82, respectively. The overall accuracy of magnetic resonance imaging was acceptable. For peripheral tears, the pooled data showed a relatively high accuracy. Magnetic resonance imaging with appropriate parameters are an ideal method for diagnosing different types of triangular fibrocartilage complex tears. © The Author(s) 2015.

Quantification of differences between nailfold capillaroscopy images with a scleroderma pattern and normal pattern using measures of geometric and algorithmic complexity.

PubMed

Urwin, Samuel George; Griffiths, Bridget; Allen, John

2017-02-01

This study aimed to quantify and investigate differences in the geometric and algorithmic complexity of the microvasculature in nailfold capillaroscopy (NFC) images displaying a scleroderma pattern and those displaying a 'normal' pattern. 11 NFC images were qualitatively classified by a capillary specialist as indicative of 'clear microangiopathy' (CM), i.e. a scleroderma pattern, and 11 as 'not clear microangiopathy' (NCM), i.e. a 'normal' pattern. Pre-processing was performed, and fractal dimension (FD) and Kolmogorov complexity (KC) were calculated following image binarisation. FD and KC were compared between groups, and a k-means cluster analysis (n  =  2) on all images was performed, without prior knowledge of the group assigned to them (i.e. CM or NCM), using FD and KC as inputs. CM images had significantly reduced FD and KC compared to NCM images, and the cluster analysis displayed promising results that the quantitative classification of images into CM and NCM groups is possible using the mathematical measures of FD and KC. The analysis techniques used show promise for quantitative microvascular investigation in patients with systemic sclerosis.

Dental computed tomographic imaging as age estimation: morphological analysis of the third molar of a group of Turkish population.

PubMed

Cantekin, Kenan; Sekerci, Ahmet Ercan; Buyuk, Suleyman Kutalmis

2013-12-01

Computed tomography (CT) is capable of providing accurate and measurable 3-dimensional images of the third molar. The aims of this study were to analyze the development of the mandibular third molar and its relation to chronological age and to create new reference data for a group of Turkish participants aged 9 to 25 years on the basis of cone-beam CT images. All data were obtained from the patients' records including medical, social, and dental anamnesis and cone-beam CT images of 752 patients. Linear regression analysis was performed to obtain regression formulas for dental age calculation with chronological age and to determine the coefficient of determination (r) for each sex. Statistical analysis showed a strong correlation between age and third-molar development for the males (r2 = 0.80) and the females (r2 = 0.78). Computed tomographic images are clinically useful for accurate and reliable estimation of dental ages of children and youth.

The Relationship Between Body Image and Sexual Function in Middle-Aged Women.

PubMed

Afshari, Poorandokht; Houshyar, Zeinab; Javadifar, Nahid; Pourmotahari, Fatemeh; Jorfi, Maryam

2016-11-01

An individual's social and marital function, interpersonal relationships, and quality of life may, sometimes be affected by negative body image. This study is aimed at determining the relationship between body image and sexual function in middle-aged women. In this cross-sectional study, 437 middle-aged women, who were referred to various public healthcare centers in Ahvaz, Iran during 2014-2015, were selected. The Female Sexual Function Index (FSFI) and Body Shape Questionnaire (BSQ) were used for data collection. Chi-square, one-way analysis of variance, Spearman's correlation test, and logistic regression analysis were performed for statistical analysis. Approximately 58% of the participants expressed satisfaction with their body image, 35% were mildly dissatisfied, and 7% were moderately dissatisfied with their body image. Body image had a significant negative relationship with sexual satisfaction and sexual function (p=0.005). Furthermore, there was a significant relationship between body image and sexual desire (p=0.022), pain (p=0.001), sexual arousal (p<0.0005), sexual orgasm (p=0.001), and sexual satisfaction (p<0.0005). As the results indicated, body image is an important aspect of sexual health. In this study, women with a positive body image had higher sexual function valuation, compared to women with a negative body image. Also, body shape satisfaction was a predictor of sexual function.

Guided filter and principal component analysis hybrid method for hyperspectral pansharpening

NASA Astrophysics Data System (ADS)

Qu, Jiahui; Li, Yunsong; Dong, Wenqian

2018-01-01

Hyperspectral (HS) pansharpening aims to generate a fused HS image with high spectral and spatial resolution through integrating an HS image with a panchromatic (PAN) image. A guided filter (GF) and principal component analysis (PCA) hybrid HS pansharpening method is proposed. First, the HS image is interpolated and the PCA transformation is performed on the interpolated HS image. The first principal component (PC1) channel concentrates on the spatial information of the HS image. Different from the traditional PCA method, the proposed method sharpens the PAN image and utilizes the GF to obtain the spatial information difference between the HS image and the enhanced PAN image. Then, in order to reduce spectral and spatial distortion, an appropriate tradeoff parameter is defined and the spatial information difference is injected into the PC1 channel through multiplying by this tradeoff parameter. Once the new PC1 channel is obtained, the fused image is finally generated by the inverse PCA transformation. Experiments performed on both synthetic and real datasets show that the proposed method outperforms other several state-of-the-art HS pansharpening methods in both subjective and objective evaluations.

A new method of cardiographic image segmentation based on grammar

NASA Astrophysics Data System (ADS)

Hamdi, Salah; Ben Abdallah, Asma; Bedoui, Mohamed H.; Alimi, Adel M.

2011-10-01

The measurement of the most common ultrasound parameters, such as aortic area, mitral area and left ventricle (LV) volume, requires the delineation of the organ in order to estimate the area. In terms of medical image processing this translates into the need to segment the image and define the contours as accurately as possible. The aim of this work is to segment an image and make an automated area estimation based on grammar. The entity "language" will be projected to the entity "image" to perform structural analysis and parsing of the image. We will show how the idea of segmentation and grammar-based area estimation is applied to real problems of cardio-graphic image processing.

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

PubMed

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

2017-01-01

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

IQM: An Extensible and Portable Open Source Application for Image and Signal Analysis in Java

PubMed Central

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM’s image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis. PMID:25612319

IQM: an extensible and portable open source application for image and signal analysis in Java.

PubMed

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Applications of High-speed motion analysis system on Solid Rocket Motor (SRM)

NASA Astrophysics Data System (ADS)

Liu, Yang; He, Guo-qiang; Li, Jiang; Liu, Pei-jin; Chen, Jian

2007-01-01

High-speed motion analysis system could record images up to 12,000fps and analyzed with the image processing system. The system stored data and images directly in electronic memory convenient for managing and analyzing. The high-speed motion analysis system and the X-ray radiography system were established the high-speed real-time X-ray radiography system, which could diagnose and measure the dynamic and high-speed process in opaque. The image processing software was developed for improve quality of the original image for acquiring more precise information. The typical applications of high-speed motion analysis system on solid rocket motor (SRM) were introduced in the paper. The research of anomalous combustion of solid propellant grain with defects, real-time measurement experiment of insulator eroding, explosion incision process of motor, structure and wave character of plume during the process of ignition and flameout, measurement of end burning of solid propellant, measurement of flame front and compatibility between airplane and missile during the missile launching were carried out using high-speed motion analysis system. The significative results were achieved through the research. Aim at application of high-speed motion analysis system on solid rocket motor, the key problem, such as motor vibrancy, electrical source instability, geometry aberrance, and yawp disturbance, which damaged the image quality, was solved. The image processing software was developed which improved the capability of measuring the characteristic of image. The experimental results showed that the system was a powerful facility to study instantaneous and high-speed process in solid rocket motor. With the development of the image processing technique, the capability of high-speed motion analysis system was enhanced.

Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing.

PubMed

Mari, João Fernando; Saito, José Hiroki; Neves, Amanda Ferreira; Lotufo, Celina Monteiro da Cruz; Destro-Filho, João-Batista; Nicoletti, Maria do Carmo

2015-12-01

Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy. The neurons are segmented from the fluorescence channel images using a combination of segmentation by thresholding, watershed transform, and object classification. The positioning of microelectrodes is obtained from the transmitted light channel images using the circular Hough transform. The proposed method was applied to images of dissociated culture of rat dorsal root ganglion (DRG) neuronal cells. The morphological and topological quantitative analysis carried out produced information regarding the state of culture, such as population count, neuron-to-neuron and neuron-to-microelectrode distances, soma morphologies, neuron sizes, neuron and microelectrode spatial distributions. Most of the analysis of microscopy images taken from neuronal cultures on MEA only consider simple qualitative analysis. Also, the proposed framework aims to standardize the image processing and to compute quantitative useful measures for integrated image-signal studies and further computational simulations. As results show, the implemented microelectrode identification method is robust and so are the implemented neuron segmentation and classification one (with a correct segmentation rate up to 84%). The quantitative information retrieved by the method is highly relevant to assist the integrated signal-image study of recorded electrophysiological signals as well as the physical aspects of the neuron culture on MEA. Although the experiments deal with DRG cell images, cortical and hippocampal cell images could also be processed with small adjustments in the image processing parameter estimation.

Automatically assisting human memory: a SenseCam browser.

PubMed

Doherty, Aiden R; Moulin, Chris J A; Smeaton, Alan F

2011-10-01

SenseCams have many potential applications as tools for lifelogging, including the possibility of use as a memory rehabilitation tool. Given that a SenseCam can log hundreds of thousands of images per year, it is critical that these be presented to the viewer in a manner that supports the aims of memory rehabilitation. In this article we report a software browser constructed with the aim of using the characteristics of memory to organise SenseCam images into a form that makes the wealth of information stored on SenseCam more accessible. To enable a large amount of visual information to be easily and quickly assimilated by a user, we apply a series of automatic content analysis techniques to structure the images into "events", suggest their relative importance, and select representative images for each. This minimises effort when browsing and searching. We provide anecdotes on use of such a system and emphasise the need for SenseCam images to be meaningfully sorted using such a browser.

3-D characterization of weathered building limestones by high resolution synchrotron X-ray microtomography.

PubMed

Rozenbaum, O

2011-04-15

Understanding the weathering processes of building stones and more generally of their transfer properties requires detailed knowledge of the porosity characteristics. This study aims at analyzing three-dimensional images obtained by X-ray microtomography of building stones. In order to validate these new results a weathered limestone previously characterised (Rozenbaum et al., 2007) by two-dimensional image analysis was selected. The 3-D images were analysed by a set of mathematical tools that enable the description of the pore and solid phase distribution. Results show that 3-D image analysis is a powerful technique to characterise the morphological, structural and topological differences due to weathering. The paper also discusses criteria for mathematically determining whether a stone is weathered or not. Copyright © 2011 Elsevier B.V. All rights reserved.

Blind source separation of ex-vivo aorta tissue multispectral images

PubMed Central

Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

2015-01-01

Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method’s performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue. PMID:26137366

Semi-simultaneous application of neutron and X-ray radiography in revealing the defects in an Al casting.

PubMed

Balaskó, M; Korösi, F; Szalay, Zs

2004-10-01

A semi-simultaneous application of neutron and X-ray radiography (NR, XR) respectively, was applied to an Al casting. The experiments were performed at the 10MW VVR-SM research reactor in Budapest (Hungary). The aim was to reveal, identify and parameterize the hidden defects in the Al casting. The joint application of NR and XR revealed hidden defects located in the Al casting. Image analysis of the NR and XR images unveiled a cone-like dimensionality of the defects. The spectral density analysis of the images showed a distinctly different character for the hidden defect region of Al casting in comparison with that of the defect-free one.

Tug-of-war lacunarity—A novel approach for estimating lacunarity

NASA Astrophysics Data System (ADS)

Reiss, Martin A.; Lemmerer, Birgit; Hanslmeier, Arnold; Ahammer, Helmut

2016-11-01

Modern instrumentation provides us with massive repositories of digital images that will likely only increase in the future. Therefore, it has become increasingly important to automatize the analysis of digital images, e.g., with methods from pattern recognition. These methods aim to quantify the visual appearance of captured textures with quantitative measures. As such, lacunarity is a useful multi-scale measure of texture's heterogeneity but demands high computational efforts. Here we investigate a novel approach based on the tug-of-war algorithm, which estimates lacunarity in a single pass over the image. We computed lacunarity for theoretical and real world sample images, and found that the investigated approach is able to estimate lacunarity with low uncertainties. We conclude that the proposed method combines low computational efforts with high accuracy, and that its application may have utility in the analysis of high-resolution images.

Characterisation of human non-proliferative diabetic retinopathy using the fractal analysis

PubMed Central

Ţălu, Ştefan; Călugăru, Dan Mihai; Lupaşcu, Carmen Alina

2015-01-01

AIM To investigate and quantify changes in the branching patterns of the retina vascular network in diabetes using the fractal analysis method. METHODS This was a clinic-based prospective study of 172 participants managed at the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and December 2013. A set of 172 segmented and skeletonized human retinal images, corresponding to both normal (24 images) and pathological (148 images) states of the retina were examined. An automatic unsupervised method for retinal vessel segmentation was applied before fractal analysis. The fractal analyses of the retinal digital images were performed using the fractal analysis software ImageJ. Statistical analyses were performed for these groups using Microsoft Office Excel 2003 and GraphPad InStat software. RESULTS It was found that subtle changes in the vascular network geometry of the human retina are influenced by diabetic retinopathy (DR) and can be estimated using the fractal geometry. The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values of mild non-proliferative DR (NPDR) images (segmented and skeletonized versions). The average of fractal dimensions D for the normal images (segmented and skeletonized versions) is higher than the corresponding values of moderate NPDR images (segmented and skeletonized versions). The lowest values were found for the corresponding values of severe NPDR images (segmented and skeletonized versions). CONCLUSION The fractal analysis of fundus photographs may be used for a more complete undeTrstanding of the early and basic pathophysiological mechanisms of diabetes. The architecture of the retinal microvasculature in diabetes can be quantitative quantified by means of the fractal dimension. Microvascular abnormalities on retinal imaging may elucidate early mechanistic pathways for microvascular complications and distinguish patients with DR from healthy individuals. PMID:26309878

Multispectral UV imaging for fast and non-destructive quality control of chemical and physical tablet attributes.

PubMed

Klukkert, Marten; Wu, Jian X; Rantanen, Jukka; Carstensen, Jens M; Rades, Thomas; Leopold, Claudia S

2016-07-30

Monitoring of tablet quality attributes in direct vicinity of the production process requires analytical techniques that allow fast, non-destructive, and accurate tablet characterization. The overall objective of this study was to investigate the applicability of multispectral UV imaging as a reliable, rapid technique for estimation of the tablet API content and tablet hardness, as well as determination of tablet intactness and the tablet surface density profile. One of the aims was to establish an image analysis approach based on multivariate image analysis and pattern recognition to evaluate the potential of UV imaging for automatized quality control of tablets with respect to their intactness and surface density profile. Various tablets of different composition and different quality regarding their API content, radial tensile strength, intactness, and surface density profile were prepared using an eccentric as well as a rotary tablet press at compression pressures from 20MPa up to 410MPa. It was found, that UV imaging can provide both, relevant information on chemical and physical tablet attributes. The tablet API content and radial tensile strength could be estimated by UV imaging combined with partial least squares analysis. Furthermore, an image analysis routine was developed and successfully applied to the UV images that provided qualitative information on physical tablet surface properties such as intactness and surface density profiles, as well as quantitative information on variations in the surface density. In conclusion, this study demonstrates that UV imaging combined with image analysis is an effective and non-destructive method to determine chemical and physical quality attributes of tablets and is a promising approach for (near) real-time monitoring of the tablet compaction process and formulation optimization purposes. Copyright © 2015 Elsevier B.V. All rights reserved.

Neural correlates of monocular and binocular depth cues based on natural images: a LORETA analysis.

PubMed

Fischmeister, Florian Ph S; Bauer, Herbert

2006-10-01

Functional imaging studies investigating perception of depth rely solely on one type of depth cue based on non-natural stimulus material. To overcome these limitations and to provide a more realistic and complete set of depth cues natural stereoscopic images were used in this study. Using slow cortical potentials and source localization we aimed to identify the neural correlates of monocular and binocular depth cues. This study confirms and extends functional imaging studies, showing that natural images provide a good, reliable, and more realistic alternative to artificial stimuli, and demonstrates the possibility to separate the processing of different depth cues.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

PubMed

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

2018-05-02

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.

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.

Research of flaw image collecting and processing technology based on multi-baseline stereo imaging

NASA Astrophysics Data System (ADS)

Yao, Yong; Zhao, Jiguang; Pang, Xiaoyan

2008-03-01

Aiming at the practical situations such as accurate optimal design, complex algorithms and precise technical demands of gun bore flaw image collecting, the design frame of a 3-D image collecting and processing system based on multi-baseline stereo imaging was presented in this paper. This system mainly including computer, electrical control box, stepping motor and CCD camera and it can realize function of image collection, stereo matching, 3-D information reconstruction and after-treatments etc. Proved by theoretical analysis and experiment results, images collected by this system were precise and it can slake efficiently the uncertainty problem produced by universally veins or repeated veins. In the same time, this system has faster measure speed and upper measure precision.

Volumetric image interpretation in radiology: scroll behavior and cognitive processes.

PubMed

den Boer, Larissa; van der Schaaf, Marieke F; Vincken, Koen L; Mol, Chris P; Stuijfzand, Bobby G; van der Gijp, Anouk

2018-05-16

The interpretation of medical images is a primary task for radiologists. Besides two-dimensional (2D) images, current imaging technologies allow for volumetric display of medical images. Whereas current radiology practice increasingly uses volumetric images, the majority of studies on medical image interpretation is conducted on 2D images. The current study aimed to gain deeper insight into the volumetric image interpretation process by examining this process in twenty radiology trainees who all completed four volumetric image cases. Two types of data were obtained concerning scroll behaviors and think-aloud data. Types of scroll behavior concerned oscillations, half runs, full runs, image manipulations, and interruptions. Think-aloud data were coded by a framework of knowledge and skills in radiology including three cognitive processes: perception, analysis, and synthesis. Relating scroll behavior to cognitive processes showed that oscillations and half runs coincided more often with analysis and synthesis than full runs, whereas full runs coincided more often with perception than oscillations and half runs. Interruptions were characterized by synthesis and image manipulations by perception. In addition, we investigated relations between cognitive processes and found an overall bottom-up way of reasoning with dynamic interactions between cognitive processes, especially between perception and analysis. In sum, our results highlight the dynamic interactions between these processes and the grounding of cognitive processes in scroll behavior. It suggests, that the types of scroll behavior are relevant to describe how radiologists interact with and manipulate volumetric images.

Towards an Analysis of Visual Images in School Science Textbooks and Press Articles about Science and Technology

NASA Astrophysics Data System (ADS)

Dimopoulos, Kostas; Koulaidis, Vasilis; Sklaveniti, Spyridoula

2003-04-01

This paper aims at presenting the application of a grid for the analysis of the pedagogic functions of visual images included in school science textbooks and daily press articles about science and technology. The analysis is made using the dimensions of content specialisation (classification) and social-pedagogic relationships (framing) promoted by the images as well as the elaboration and abstraction of the corresponding visual code (formality), thus combining pedagogical and socio-semiotic perspectives. The grid is applied to the analysis of 2819 visual images collected from school science textbooks and another 1630 visual images additionally collected from the press. The results show that the science textbooks in comparison to the press material: a) use ten times more images, b) use more images so as to familiarise their readers with the specialised techno-scientific content and codes, and c) tend to create a sense of higher empowerment for their readers by using the visual mode. Furthermore, as the educational level of the school science textbooks (i.e., from primary to lower secondary level) rises, the content specialisation projected by the visual images and the elaboration and abstraction of the corresponding visual code also increases. The above results have implications for the terms and conditions for the effective exploitation of visual material as the educational level rises as well as for the effective incorporation of visual images from press material into science classes.

Image Quality Analysis of Various Gastrointestinal Endoscopes: Why Image Quality Is a Prerequisite for Proper Diagnostic and Therapeutic Endoscopy

PubMed Central

Ko, Weon Jin; An, Pyeong; Ko, Kwang Hyun; Hahm, Ki Baik; Hong, Sung Pyo

2015-01-01

Arising from human curiosity in terms of the desire to look within the human body, endoscopy has undergone significant advances in modern medicine. Direct visualization of the gastrointestinal (GI) tract by traditional endoscopy was first introduced over 50 years ago, after which fairly rapid advancement from rigid esophagogastric scopes to flexible scopes and high definition videoscopes has occurred. In an effort towards early detection of precancerous lesions in the GI tract, several high-technology imaging scopes have been developed, including narrow band imaging, autofocus imaging, magnified endoscopy, and confocal microendoscopy. However, these modern developments have resulted in fundamental imaging technology being skewed towards red-green-blue and this technology has obscured the advantages of other endoscope techniques. In this review article, we have described the importance of image quality analysis using a survey to consider the diversity of endoscope system selection in order to better achieve diagnostic and therapeutic goals. The ultimate aims can be achieved through the adoption of modern endoscopy systems that obtain high image quality. PMID:26473119

Medical image analysis with artificial neural networks.

PubMed

Jiang, J; Trundle, P; Ren, J

2010-12-01

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. Copyright © 2010 Elsevier Ltd. All rights reserved.

Texture analysis of high-resolution FLAIR images for TLE

NASA Astrophysics Data System (ADS)

Jafari-Khouzani, Kourosh; Soltanian-Zadeh, Hamid; Elisevich, Kost

2005-04-01

This paper presents a study of the texture information of high-resolution FLAIR images of the brain with the aim of determining the abnormality and consequently the candidacy of the hippocampus for temporal lobe epilepsy (TLE) surgery. Intensity and volume features of the hippocampus from FLAIR images of the brain have been previously shown to be useful in detecting the abnormal hippocampus in TLE. However, the small size of the hippocampus may limit the texture information. High-resolution FLAIR images show more details of the abnormal intensity variations of the hippocampi and therefore are more suitable for texture analysis. We study and compare the low and high-resolution FLAIR images of six epileptic patients. The hippocampi are segmented manually by an expert from T1-weighted MR images. Then the segmented regions are mapped on the corresponding FLAIR images for texture analysis. The 2-D wavelet transforms of the hippocampi are employed for feature extraction. We compare the ability of the texture features from regular and high-resolution FLAIR images to distinguish normal and abnormal hippocampi. Intracranial EEG results as well as surgery outcome are used as gold standard. The results show that the intensity variations of the hippocampus are related to the abnormalities in the TLE.

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

Automatic comic page image understanding based on edge segment analysis

NASA Astrophysics Data System (ADS)

Liu, Dong; Wang, Yongtao; Tang, Zhi; Li, Luyuan; Gao, Liangcai

2013-12-01

Comic page image understanding aims to analyse the layout of the comic page images by detecting the storyboards and identifying the reading order automatically. It is the key technique to produce the digital comic documents suitable for reading on mobile devices. In this paper, we propose a novel comic page image understanding method based on edge segment analysis. First, we propose an efficient edge point chaining method to extract Canny edge segments (i.e., contiguous chains of Canny edge points) from the input comic page image; second, we propose a top-down scheme to detect line segments within each obtained edge segment; third, we develop a novel method to detect the storyboards by selecting the border lines and further identify the reading order of these storyboards. The proposed method is performed on a data set consisting of 2000 comic page images from ten printed comic series. The experimental results demonstrate that the proposed method achieves satisfactory results on different comics and outperforms the existing methods.

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

NASA Astrophysics Data System (ADS)

Boutet de Monvel, J.

2007-09-01

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

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

Neuroimaging in aphasia treatment research: Consensus and practical guidelines for data analysis

PubMed Central

Meinzer, Marcus; Beeson, Pélagie M.; Cappa, Stefano; Crinion, Jenny; Kiran, Swathi; Saur, Dorothee; Parrish, Todd; Crosson, Bruce; Thompson, Cynthia K.

2012-01-01

Functional magnetic resonance imaging is the most widely used imaging technique to study treatment-induced recovery in post-stroke aphasia. The longitudinal design of such studies adds to the challenges researchers face when studying patient populations with brain damage in cross-sectional settings. The present review focuses on issues specifically relevant to neuroimaging data analysis in aphasia treatment research identified in discussions among international researchers at the Neuroimaging in Aphasia Treatment Research Workshop held at Northwestern University (Evanston, Illinois, USA). In particular, we aim to provide the reader with a critical review of unique problems related to the pre-processing, statistical modeling and interpretation of such data sets. Despite the fact that data analysis procedures critically depend on specific design features of a given study, we aim to discuss and communicate a basic set of practical guidelines that should be applicable to a wide range of studies and useful as a reference for researchers pursuing this line of research. PMID:22387474

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.

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

PubMed Central

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo

2016-01-01

Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

PubMed

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

2016-12-01

Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

NASA Astrophysics Data System (ADS)

Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

Multimodal image analysis of clinical influences on preterm brain development

PubMed Central

Ball, Gareth; Aljabar, Paul; Nongena, Phumza; Kennea, Nigel; Gonzalez‐Cinca, Nuria; Falconer, Shona; Chew, Andrew T.M.; Harper, Nicholas; Wurie, Julia; Rutherford, Mary A.; Edwards, A. David

2017-01-01

Objective Premature birth is associated with numerous complex abnormalities of white and gray matter and a high incidence of long‐term neurocognitive impairment. An integrated understanding of these abnormalities and their association with clinical events is lacking. The aim of this study was to identify specific patterns of abnormal cerebral development and their antenatal and postnatal antecedents. Methods In a prospective cohort of 449 infants (226 male), we performed a multivariate and data‐driven analysis combining multiple imaging modalities. Using canonical correlation analysis, we sought separable multimodal imaging markers associated with specific clinical and environmental factors and correlated to neurodevelopmental outcome at 2 years. Results We found five independent patterns of neuroanatomical variation that related to clinical factors including age, prematurity, sex, intrauterine complications, and postnatal adversity. We also confirmed the association between imaging markers of neuroanatomical abnormality and poor cognitive and motor outcomes at 2 years. Interpretation This data‐driven approach defined novel and clinically relevant imaging markers of cerebral maldevelopment, which offer new insights into the nature of preterm brain injury. Ann Neurol 2017;82:233–246 PMID:28719076

Bone texture analysis on dental radiographic images: results with several angulated radiographs on the same region of interest

NASA Astrophysics Data System (ADS)

Amouriq, Yves; Guedon, Jeanpierre; Normand, Nicolas; Arlicot, Aurore; Benhdech, Yassine; Weiss, Pierre

2011-03-01

Bone microarchitecture is the predictor of bone quality or bone disease. It can only be measured on a bone biopsy, which is invasive and not available for all clinical situations. Texture analysis on radiographs is a common way to investigate bone microarchitecture. But relationship between three-dimension histomorphometric parameters and two-dimension texture parameters is not always well known, with poor results. The aim of this study is to performed angulated radiographs of the same region of interest and see if a better relationship between texture analysis on several radiographs and histomorphometric parameters can be developed. Computed radiography images of dog (Beagle) mandible section in molar regions were compared with high-resolution micro-CT (Computed-Tomograph) volumes. Four radiographs with 27° angle (up, down, left, right, using Rinn ring and customized arm positioning system) were performed from initial radiograph position. Bone texture parameters were calculated on all images. Texture parameters were also computed from new images obtained by difference between angulated images. Results of fractal values in different trabecular areas give some caracterisation of bone microarchitecture.

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology

PubMed Central

Di Ruberto, Cecilia; Kocher, Michel

2018-01-01

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images. PMID:29419781

Image analysis of pubic bone for age estimation in a computed tomography sample.

PubMed

López-Alcaraz, Manuel; González, Pedro Manuel Garamendi; Aguilera, Inmaculada Alemán; López, Miguel Botella

2015-03-01

Radiology has demonstrated great utility for age estimation, but most of the studies are based on metrical and morphological methods in order to perform an identification profile. A simple image analysis-based method is presented, aimed to correlate the bony tissue ultrastructure with several variables obtained from the grey-level histogram (GLH) of computed tomography (CT) sagittal sections of the pubic symphysis surface and the pubic body, and relating them with age. The CT sample consisted of 169 hospital Digital Imaging and Communications in Medicine (DICOM) archives of known sex and age. The calculated multiple regression models showed a maximum R (2) of 0.533 for females and 0.726 for males, with a high intra- and inter-observer agreement. The method suggested is considered not only useful for performing an identification profile during virtopsy, but also for application in further studies in order to attach a quantitative correlation for tissue ultrastructure characteristics, without complex and expensive methods beyond image analysis.

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology.

PubMed

Loddo, Andrea; Di Ruberto, Cecilia; Kocher, Michel

2018-02-08

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images.

In Situ Characterization of Boehmite Particles in Water Using Liquid SEM

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

Yao, Juan; Arey, Bruce W.; Yang, Li

In situ imaging and elemental analysis of boehmite (AlOOH) particles in water is realized using the System for Analysis at the Liquid Vacuum Interface (SALVI) and Scanning Electron Microscopy (SEM). This paper describes the method and key steps in integrating the vacuum compatible SAVLI to SEM and obtaining secondary electron (SE) images of particles in liquid in high vacuum. Energy dispersive x-ray spectroscopy (EDX) is used to obtain elemental analysis of particles in liquid. A synthesized AlOOH particle is used as a model in the liquid SEM illustration. Our results demonstrate that particles can be imaged in the SE modemore » with good resolution. The AlOOH EDX spectrum shows significant signal from the Al compared with deionized water and the empty channel control. In situ liquid SEM is a powerful technique to study particles in liquid with many exciting applications. This procedure aims to provide technical details in how to conduct liquid SEM imaging and EDX analysis using SALVI and reduce potential pitfalls using this approach for other researchers.« less

A survey of MRI-based medical image analysis for brain tumor studies

NASA Astrophysics Data System (ADS)

Bauer, Stefan; Wiest, Roland; Nolte, Lutz-P.; Reyes, Mauricio

2013-07-01

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

Hybrid SPECT/CT imaging in neurology.

PubMed

Ciarmiello, Andrea; Giovannini, Elisabetta; Meniconi, Martina; Cuccurullo, Vincenzo; Gaeta, Maria Chiara

2014-01-01

In recent years, the SPECT/CT hybrid modality has led to a rapid development of imaging techniques in nuclear medicine, opening new perspectives for imaging staff and patients as well. However, while, the clinical role of positron emission tomography-computed tomography (PET-CT) is well consolidated, the diffusion and the consequent value of single-photon emission tomography-computed tomography (SPECT-CT) has yet to be weighed, Hence, there is a need for a careful analysis, comparing the "potential" benefits of the hybrid modality with the "established" ones of the standalone machine. The aim of this article is to analyze the impact of this hybrid tool on the diagnosis of diseases of the central nervous system, comparing strengths and weaknesses of both modalities through the use of SWOT analysis.

Estimating weak ratiometric signals in imaging data. II. Meta-analysis with multiple, dual-channel datasets.

PubMed

Sornborger, Andrew; Broder, Josef; Majumder, Anirban; Srinivasamoorthy, Ganesh; Porter, Erika; Reagin, Sean S; Keith, Charles; Lauderdale, James D

2008-09-01

Ratiometric fluorescent indicators are used for making quantitative measurements of a variety of physiological variables. Their utility is often limited by noise. This is the second in a series of papers describing statistical methods for denoising ratiometric data with the aim of obtaining improved quantitative estimates of variables of interest. Here, we outline a statistical optimization method that is designed for the analysis of ratiometric imaging data in which multiple measurements have been taken of systems responding to the same stimulation protocol. This method takes advantage of correlated information across multiple datasets for objectively detecting and estimating ratiometric signals. We demonstrate our method by showing results of its application on multiple, ratiometric calcium imaging experiments.

Texture classification of lung computed tomography images

NASA Astrophysics Data System (ADS)

Pheng, Hang See; Shamsuddin, Siti M.

2013-03-01

Current development of algorithms in computer-aided diagnosis (CAD) scheme is growing rapidly to assist the radiologist in medical image interpretation. Texture analysis of computed tomography (CT) scans is one of important preliminary stage in the computerized detection system and classification for lung cancer. Among different types of images features analysis, Haralick texture with variety of statistical measures has been used widely in image texture description. The extraction of texture feature values is essential to be used by a CAD especially in classification of the normal and abnormal tissue on the cross sectional CT images. This paper aims to compare experimental results using texture extraction and different machine leaning methods in the classification normal and abnormal tissues through lung CT images. The machine learning methods involve in this assessment are Artificial Immune Recognition System (AIRS), Naive Bayes, Decision Tree (J48) and Backpropagation Neural Network. AIRS is found to provide high accuracy (99.2%) and sensitivity (98.0%) in the assessment. For experiments and testing purpose, publicly available datasets in the Reference Image Database to Evaluate Therapy Response (RIDER) are used as study cases.

Research on vehicle detection based on background feature analysis in SAR images

NASA Astrophysics Data System (ADS)

Zhang, Bochuan; Tang, Bo; Zhang, Cong; Hu, Ruiguang; Yun, Hongquan; Xiao, Liping

2017-10-01

Aiming at vehicle detection on the ground through low resolution SAR images, a method is proposed for determining the region of the vehicles first and then detecting the target in the specific region. The experimental results show that this method not only reduces the target detection area, but also reduces the influence of terrain clutter on the detection, which greatly improves the reliability of the target detection.

Use of Fouler Transforms to define landscape scales of analysis for disturbances: A case study of thinned and unthinned forest stands

Treesearch

J. E. Lundquist; R. A. Sommerfeld

2002-01-01

Various disturbances such as disease and management practices cause canopy gaps that change patterns of forest stand structure. This study examined the usefulness of digital image analysis using aerial photos, Fourier Tranforms, and cluster analysis to investigate how different spatial statistics are affected by spatial scale. The specific aims were to: 1) evaluate how...

Effects of 99mTc-TRODAT-1 drug template on image quantitative analysis

PubMed Central

Yang, Bang-Hung; Chou, Yuan-Hwa; Wang, Shyh-Jen; Chen, Jyh-Cheng

2018-01-01

99mTc-TRODAT-1 is a type of drug that can bind to dopamine transporters in living organisms and is often used in SPCT imaging for observation of changes in the activity uptake of dopamine in the striatum. Therefore, it is currently widely used in studies on clinical diagnosis of Parkinson’s disease (PD) and movement-related disorders. In conventional 99mTc-TRODAT-1 SPECT image evaluation, visual inspection or manual selection of ROI for semiquantitative analysis is mainly used to observe and evaluate the degree of striatal defects. However, these methods are dependent on the subjective opinions of observers, which lead to human errors, have shortcomings such as long duration, increased effort, and have low reproducibility. To solve this problem, this study aimed to establish an automatic semiquantitative analytical method for 99mTc-TRODAT-1. This method combines three drug templates (one built-in SPECT template in SPM software and two self-generated MRI-based and HMPAO-based TRODAT-1 templates) for the semiquantitative analysis of the striatal phantom and clinical images. At the same time, the results of automatic analysis of the three templates were compared with results from a conventional manual analysis for examining the feasibility of automatic analysis and the effects of drug templates on automatic semiquantitative analysis results. After comparison, it was found that the MRI-based TRODAT-1 template generated from MRI images is the most suitable template for 99mTc-TRODAT-1 automatic semiquantitative analysis. PMID:29543874

Computer vision for microscopy diagnosis of malaria.

PubMed

Tek, F Boray; Dempster, Andrew G; Kale, Izzet

2009-07-13

This paper reviews computer vision and image analysis studies aiming at automated diagnosis or screening of malaria infection in microscope images of thin blood film smears. Existing works interpret the diagnosis problem differently or propose partial solutions to the problem. A critique of these works is furnished. In addition, a general pattern recognition framework to perform diagnosis, which includes image acquisition, pre-processing, segmentation, and pattern classification components, is described. The open problems are addressed and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

A tertiary hospital audit of the use of medical imaging in the 24 h preceding death.

PubMed

Liu, D; Weil, J; Boughey, M; Sutherland, T

2016-02-01

This study aims to investigate the number, modality and indication for imaging studies performed on acute hospital inpatients in the 24 h prior to death. Data were obtained from retrospective analysis of deceased patients from a university affiliated tertiary hospital over a 2-year period and it was found that around one in five inpatients received medical imaging in the last 24 h of their life (364 of 1855, 19.6%). © 2016 Royal Australasian College of Physicians.

Cardiac imaging: working towards fully-automated machine analysis & interpretation.

PubMed

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-03-01

Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered: This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary: Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation.

CellStress - open source image analysis program for single-cell analysis

NASA Astrophysics Data System (ADS)

Smedh, Maria; Beck, Caroline; Sott, Kristin; Goksör, Mattias

2010-08-01

This work describes our image-analysis software, CellStress, which has been developed in Matlab and is issued under a GPL license. CellStress was developed in order to analyze migration of fluorescent proteins inside single cells during changing environmental conditions. CellStress can also be used to score information regarding protein aggregation in single cells over time, which is especially useful when monitoring cell signaling pathways involved in e.g. Alzheimer's or Huntington's disease. Parallel single-cell analysis of large numbers of cells is an important part of the research conducted in systems biology and quantitative biology in order to mathematically describe cellular processes. To quantify properties for single cells, large amounts of data acquired during extended time periods are needed. Manual analyses of such data involve huge efforts and could also include a bias, which complicates the use and comparison of data for further simulations or modeling. Therefore, it is necessary to have an automated and unbiased image analysis procedure, which is the aim of CellStress. CellStress utilizes cell contours detected by CellStat (developed at Fraunhofer-Chalmers Centre), which identifies cell boundaries using bright field images, and thus reduces the fluorescent labeling needed.

A Framework of Hyperspectral Image Compression using Neural Networks

DOE PAGES

Masalmah, Yahya M.; Martínez Nieves, Christian; Rivera Soto, Rafael; ...

2015-01-01

Hyperspectral image analysis has gained great attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows usmore » to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. Lastly, this paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.« less

In utero eyeball development study by magnetic resonance imaging.

PubMed

Brémond-Gignac, D S; Benali, K; Deplus, S; Cussenot, O; Ferkdadji, L; Elmaleh, M; Lassau, J P

1997-01-01

The aim of this study was to measure fetal ocular development and to determine a growth curve by means of measurements in utero. Fetal ocular development was recorded by analysis of the results of magnetic resonance imaging (MRI). An anatomic study allowed definition of the best contrasted MRI sequences for calculation of the ocular surface. Biometric analysis of the values of the ocular surface in the neuro-ocular plane in 35 fetuses allowed establishment of a linear model of ocular growth curve in utero. Evaluation of ocular development may allow the detection and confirmation of malformational ocular anomalies such as microphthalmia.

Effect of Patient Set-up and Respiration motion on Defining Biological Targets for Image-Guided Targeted Radiotherapy

NASA Astrophysics Data System (ADS)

McCall, Keisha C.

Identification and monitoring of sub-tumor targets will be a critical step for optimal design and evaluation of cancer therapies in general and biologically targeted radiotherapy (dose-painting) in particular. Quantitative PET imaging may be an important tool for these applications. Currently radiotherapy planning accounts for tumor motion by applying geometric margins. These margins create a motion envelope to encompass the most probable positions of the tumor, while also maintaining the appropriate tumor control and normal tissue complication probabilities. This motion envelope is effective for uniform dose prescriptions where the therapeutic dose is conformed to the external margins of the tumor. However, much research is needed to establish the equivalent margins for non-uniform fields, where multiple biological targets are present and each target is prescribed its own dose level. Additionally, the size of the biological targets and close proximity make it impractical to apply planning margins on the sub-tumor level. Also, the extent of high dose regions must be limited to avoid excessive dose to the surrounding tissue. As such, this research project is an investigation of the uncertainty within quantitative PET images of moving and displaced dose-painting targets, and an investigation of the residual errors that remain after motion management. This included characterization of the changes in PET voxel-values as objects are moved relative to the discrete sampling interval of PET imaging systems (SPECIFIC AIM 1). Additionally, the repeatability of PET distributions and the delineating dose-painting targets were measured (SPECIFIC AIM 2). The effect of imaging uncertainty on the dose distributions designed using these images (SPECIFIC AIM 3) has also been investigated. This project also included analysis of methods to minimize motion during PET imaging and reduce the dosimetric impact of motion/position-induced imaging uncertainty (SPECIFIC AIM 4).

Evaluation of Lip Prints on Different Supports Using a Batch Image Processing Algorithm and Image Superimposition.

PubMed

Herrera, Lara Maria; Fernandes, Clemente Maia da Silva; Serra, Mônica da Costa

2018-01-01

This study aimed to develop and to assess an algorithm to facilitate lip print visualization, and to digitally analyze lip prints on different supports, by superimposition. It also aimed to classify lip prints according to sex. A batch image processing algorithm was developed, which facilitated the identification and extraction of information about lip grooves. However, it performed better for lip print images with a uniform background. Paper and glass slab allowed more correct identifications than glass and the both sides of compact disks. There was no significant difference between the type of support and the amount of matching structures located in the middle area of the lower lip. There was no evidence of association between types of lip grooves and sex. Lip groove patterns of type III and type I were the most common for both sexes. The development of systems for lip print analysis is necessary, mainly concerning digital methods. © 2017 American Academy of Forensic Sciences.

Evaluation of the influence of acquisition parameters of microtomography in image quality applied by carbonate rocks

NASA Astrophysics Data System (ADS)

Santos, T. M. P.; Machado, A. S.; Araújo, O. M. O.; Ferreira, C. G.; Lopes, R. T.

2018-03-01

X-ray computed microtomography is a powerful nondestructive technique for 2D and 3D structure analysis. However, parameters used in acquisition promote directs influence in qualitative and quantitative results in characterization of samples, due image resolution. The aim of this study is value the influence of theses parameters in results through of tests changing these parameters in different situations and system characterization. Results demonstrate those pixel size and detector matrixes are the main parameters that influence in resolution and image quality. Microtomography was considered an excellent technique for characterization using the best image resolution possible.

Development of methods for analysis of knee articular cartilage degeneration by magnetic resonance imaging data

NASA Astrophysics Data System (ADS)

Suponenkovs, Artjoms; Glazs, Aleksandrs; Platkajis, Ardis

2017-03-01

The aim of this paper is to describe the new methods for analyzing knee articular cartilage degeneration. The most important aspects regarding research about magnetic resonance imaging, knee joint anatomy, stages of knee osteoarthritis, medical image segmentation and relaxation times calculation. This paper proposes new methods for relaxation times calculation and medical image segmentation. The experimental part describes the most important aspect regarding analysing of articular cartilage relaxation times changing. This part contains experimental results, which show the codependence between relaxation times and organic structure. These experimental results and proposed methods can be helpful for early osteoarthritis diagnostics.

Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

NASA Astrophysics Data System (ADS)

Karaca, Yeliz; Cattani, Carlo

Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

A Model-Based Approach for Microvasculature Structure Distortion Correction in Two-Photon Fluorescence Microscopy Images

PubMed Central

Dao, Lam; Glancy, Brian; Lucotte, Bertrand; Chang, Lin-Ching; Balaban, Robert S; Hsu, Li-Yueh

2015-01-01

SUMMARY This paper investigates a post-processing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modeling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to sub volumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images. PMID:26224257

Quantication and analysis of respiratory motion from 4D MRI

NASA Astrophysics Data System (ADS)

Aizzuddin Abd Rahni, Ashrani; Lewis, Emma; Wells, Kevin

2014-11-01

It is well known that respiratory motion affects image acquisition and also external beam radiotherapy (EBRT) treatment planning and delivery. However often the existing approaches for respiratory motion management are based on a generic view of respiratory motion such as the general movement of organ, tissue or fiducials. This paper thus aims to present a more in depth analysis of respiratory motion based on 4D MRI for further integration into motion correction in image acquisition or image based EBRT. Internal and external motion was first analysed separately, on a per-organ basis for internal motion. Principal component analysis (PCA) was then performed on the internal and external motion vectors separately and the relationship between the two PCA spaces was analysed. The motion extracted from 4D MRI on general was found to be consistent with what has been reported in literature.

#LancerHealth: Using Twitter and Instagram as a tool in a campus wide health promotion initiative.

PubMed

Santarossa, Sara; Woodruff, Sarah J

2018-02-05

The present study aimed to explore using popular technology that people already have/use as a health promotion tool, in a campus wide social media health promotion initiative, entitled #LancerHealth . During a two-week period the university community was asked to share photos on Twitter and Instagram of What does being healthy on campus look like to you ?, while tagging the image with #LancerHealth . All publically tagged media was collected using the Netlytic software and analysed. Text analysis (N=234 records, Twitter; N=141 records, Instagram) revealed that the majority of the conversation was positive and focused on health and the university. Social network analysis, based on five network properties, showed a small network with little interaction. Lastly, photo coding analysis (N=71 unique image) indicated that the majority of the shared images were of physical activity (52%) and on campus (80%). Further research into this area is warranted.

Heterogeneity, histological features and DNA ploidy in oral carcinoma by image-based analysis.

PubMed

Diwakar, N; Sperandio, M; Sherriff, M; Brown, A; Odell, E W

2005-04-01

Oral squamous carcinomas appear heterogeneous on DNA ploidy analysis. However, this may be partly a result of sample dilution or the detection limit of techniques. The aim of this study was to determine whether oral squamous carcinomas are heterogeneous for ploidy status using image-based ploidy analysis and to determine whether ploidy status correlates with histological parameters. Multiple samples from 42 oral squamous carcinomas were analysed for DNA ploidy using an image-based system and scored for histological parameters. 22 were uniformly aneuploid, 1 uniformly tetraploid and 3 uniformly diploid. 16 appeared heterogeneous but only 8 appeared to be genuinely heterogeneous when minor ploidy histogram peaks were taken into account. Ploidy was closely related to nuclear pleomorphism but not differentiation. Sample variation, detection limits and diagnostic criteria account for much of the ploidy heterogeneity observed. Confident diagnosis of diploid status in an oral squamous cell carcinoma requires a minimum of 5 samples.

Image analysis for microelectronic retinal prosthesis.

PubMed

Hallum, L E; Cloherty, S L; Lovell, N H

2008-01-01

By way of extracellular, stimulating electrodes, a microelectronic retinal prosthesis aims to render discrete, luminous spots-so-called phosphenes-in the visual field, thereby providing a phosphene image (PI) as a rudimentary remediation of profound blindness. As part thereof, a digital camera, or some other photosensitive array, captures frames, frames are analyzed, and phosphenes are actuated accordingly by way of modulated charge injections. Here, we present a method that allows the assessment of image analysis schemes for integration with a prosthetic device, that is, the means of converting the captured image (high resolution) to modulated charge injections (low resolution). We use the mutual-information function to quantify the amount of information conveyed to the PI observer (device implantee), while accounting for the statistics of visual stimuli. We demonstrate an effective scheme involving overlapping, Gaussian kernels, and discuss extensions of the method to account for shortterm visual memory in observers, and their perceptual errors of omission and commission.

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.

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Mapping urban impervious surface using object-based image analysis with WorldView-3 satellite imagery

NASA Astrophysics Data System (ADS)

Iabchoon, Sanwit; Wongsai, Sangdao; Chankon, Kanoksuk

2017-10-01

Land use and land cover (LULC) data are important to monitor and assess environmental change. LULC classification using satellite images is a method widely used on a global and local scale. Especially, urban areas that have various LULC types are important components of the urban landscape and ecosystem. This study aims to classify urban LULC using WorldView-3 (WV-3) very high-spatial resolution satellite imagery and the object-based image analysis method. A decision rules set was applied to classify the WV-3 images in Kathu subdistrict, Phuket province, Thailand. The main steps were as follows: (1) the image was ortho-rectified with ground control points and using the digital elevation model, (2) multiscale image segmentation was applied to divide the image pixel level into image object level, (3) development of the decision ruleset for LULC classification using spectral bands, spectral indices, spatial and contextual information, and (4) accuracy assessment was computed using testing data, which sampled by statistical random sampling. The results show that seven LULC classes (water, vegetation, open space, road, residential, building, and bare soil) were successfully classified with overall classification accuracy of 94.14% and a kappa coefficient of 92.91%.

Galaxy evolution in the densest environments: HST imaging

NASA Astrophysics Data System (ADS)

Jorgensen, Inger

2013-10-01

We propose to process in a consistent fashion all available HST/ACS and WFC3 imaging of seven rich clusters of galaxies at z=1.2-1.6. The clusters are part of our larger project aimed at constraining models for galaxy evolution in dense environments from observations of stellar populations in rich z=1.2-2 galaxy clusters. The main objective is to establish the star formation {SF} history and structural evolution over this epoch during which large changes in SF rates and galaxy structure are expected to take place in cluster galaxies.The observational data required to meet our main objective are deep HST imaging and high S/N spectroscopy of individual cluster members. The HST imaging already exists for the seven rich clusters at z=1.2-1.6 included in this archive proposal. However, the data have not been consistently processed to derive colors, magnitudes, sizes and morphological parameters for all potential cluster members bright enough to be suitable for spectroscopic observations with 8-m class telescopes. We propose to carry out this processing and make all derived parameters publicly available. We will use the parameters derived from the HST imaging to {1} study the structural evolution of the galaxies, {2} select clusters and galaxies for spectroscopic observations, and {3} use the photometry and spectroscopy together for a unified analysis aimed at the SF history and structural changes. The analysis will also utilize data from the Gemini/HST Cluster Galaxy Project, which covers rich clusters at z=0.2-1.0 and for which we have similar HST imaging and high S/N spectroscopy available.

Cardiac Magnetic Resonance and Computed Tomography in Hypertrophic Cardiomyopathy: an Update

PubMed Central

de Oliveira, Diogo Costa Leandro; Assunção, Fernanda Boldrini; dos Santos, Alair Agusto Sarmet Moreira Damas; Nacif, Marcelo Souto

2016-01-01

Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiovascular disease and represents the main cause of sudden death in young patients. Cardiac magnetic resonance (CMR) and cardiac computed tomography (CCT) are noninvasive imaging methods with high sensitivity and specificity, useful for the establishment of diagnosis and prognosis of HCM, and for the screening of patients with subclinical phenotypes. The improvement of image analysis by CMR and CCT offers the potential to promote interventions aiming at stopping the natural course of the disease. This study aims to describe the role of RCM and CCT in the diagnosis and prognosis of HCM, and how these methods can be used in the management of these patients. PMID:27305111

Correcting the planar perspective projection in geometric structures applied to forensic facial analysis.

PubMed

Baldasso, Rosane Pérez; Tinoco, Rachel Lima Ribeiro; Vieira, Cristina Saft Matos; Fernandes, Mário Marques; Oliveira, Rogério Nogueira

2016-10-01

The process of forensic facial analysis may be founded on several scientific techniques and imaging modalities, such as digital signal processing, photogrammetry and craniofacial anthropometry. However, one of the main limitations in this analysis is the comparison of images acquired with different angles of incidence. The present study aimed to explore a potential approach for the correction of the planar perspective projection (PPP) in geometric structures traced from the human face. A technique for the correction of the PPP was calibrated within photographs of two geometric structures obtained with angles of incidence distorted in 80°, 60° and 45°. The technique was performed using ImageJ ® 1.46r (National Institutes of Health, Bethesda, Maryland). The corrected images were compared with photographs of the same object obtained in 90° (reference). In a second step, the technique was validated in a digital human face created using MakeHuman ® 1.0.2 (Free Software Foundation, Massachusetts, EUA) and Blender ® 2.75 (Blender ® Foundation, Amsterdam, Nederland) software packages. The images registered with angular distortion presented a gradual decrease in height when compared to the reference. The digital technique for the correction of the PPP is a valuable tool for forensic applications using photographic imaging modalities, such as forensic facial analysis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A comparison of 3D poly(ε-caprolactone) tissue engineering scaffolds produced with conventional and additive manufacturing techniques by means of quantitative analysis of SR μ-CT images

NASA Astrophysics Data System (ADS)

Brun, F.; Intranuovo, F.; Mohammadi, S.; Domingos, M.; Favia, P.; Tromba, G.

2013-07-01

The technique used to produce a 3D tissue engineering (TE) scaffold is of fundamental importance in order to guarantee its proper morphological characteristics. An accurate assessment of the resulting structural properties is therefore crucial in order to evaluate the effectiveness of the produced scaffold. Synchrotron radiation (SR) computed microtomography (μ-CT) combined with further image analysis seems to be one of the most effective techniques to this aim. However, a quantitative assessment of the morphological parameters directly from the reconstructed images is a non trivial task. This study considers two different poly(ε-caprolactone) (PCL) scaffolds fabricated with a conventional technique (Solvent Casting Particulate Leaching, SCPL) and an additive manufacturing (AM) technique (BioCell Printing), respectively. With the first technique it is possible to produce scaffolds with random, non-regular, rounded pore geometry. The AM technique instead is able to produce scaffolds with square-shaped interconnected pores of regular dimension. Therefore, the final morphology of the AM scaffolds can be predicted and the resulting model can be used for the validation of the applied imaging and image analysis protocols. It is here reported a SR μ-CT image analysis approach that is able to effectively and accurately reveal the differences in the pore- and throat-size distributions as well as connectivity of both AM and SCPL scaffolds.

Novel quantitative analysis of autofluorescence images for oral cancer screening.

PubMed

Huang, Tze-Ta; Huang, Jehn-Shyun; Wang, Yen-Yun; Chen, Ken-Chung; Wong, Tung-Yiu; Chen, Yi-Chun; Wu, Che-Wei; Chan, Leong-Perng; Lin, Yi-Chu; Kao, Yu-Hsun; Nioka, Shoko; Yuan, Shyng-Shiou F; Chung, Pau-Choo

2017-05-01

VELscope® was developed to inspect oral mucosa autofluorescence. However, its accuracy is heavily dependent on the examining physician's experience. This study was aimed toward the development of a novel quantitative analysis of autofluorescence images for oral cancer screening. Patients with either oral cancer or precancerous lesions and a control group with normal oral mucosa were enrolled in this study. White light images and VELscope® autofluorescence images of the lesions were taken with a digital camera. The lesion in the image was chosen as the region of interest (ROI). The average intensity and heterogeneity of the ROI were calculated. A quadratic discriminant analysis (QDA) was utilized to compute boundaries based on sensitivity and specificity. 47 oral cancer lesions, 54 precancerous lesions, and 39 normal oral mucosae controls were analyzed. A boundary of specificity of 0.923 and a sensitivity of 0.979 between the oral cancer lesions and normal oral mucosae were validated. The oral cancer and precancerous lesions could also be differentiated from normal oral mucosae with a specificity of 0.923 and a sensitivity of 0.970. The novel quantitative analysis of the intensity and heterogeneity of VELscope® autofluorescence images used in this study in combination with a QDA classifier can be used to differentiate oral cancer and precancerous lesions from normal oral mucosae. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genomic Diversity and the Microenvironment as Drivers of Progression in DCIS

DTIC Science & Technology

2016-10-01

been acquiring new skills in medical image analysis and learning about the complexities of breast cancer diagnosis. How were the results...database and medical record searching at Duke, 2) Development of methods for isolating DNA from archival DCIS lesions, 3) Deep and comprehensive...on the Aim 3 results to the SPIE Medical Imaging Conference to be held in February 2017. If accepted, those will each be published in the form of a

Body Image Issues In Lithuanian Magazines Aimed For Children And Adolescents In Relation To Body Mass Index And Body Size Perception Of 16-19 Y. Old Girls During The Last 15 Years.

PubMed

Tutkuviene, Janina; Misiute, Agne; Strupaite, Ieva; Paulikaite, Gintare; Pavlovskaja, Erika

2017-03-01

Mass media plays an important role in forming body image and makes the significant impact on body size perception in children and adolescents. The aim of present study was to reveal trends in depiction of body image cues in Lithuanian magazines aimed for children and adolescents in relation to changes of real body mass index (BMI) and body size perception of 16-19 y. old girls in the year 2000 and the 2015. Three popular journals published both in the year 2000 and the 2015, were chosen for in-depth analysis of their contents (the periodicity of different topics was counted and compared). Attention given to a healthy body image has increased and the promotion of especially skinny females’ body has decreased during the last 15 years from the dominant type in the year 2000 to depiction of slightly thin or normal body build in the 2015. However, the real BMI of 16-19 y. old Lithuanian girls has significantly increased during the 2000-2015 period (from 20.09 till 21.32 kg/m²; p<0,001). Despite this fact, the older adolescent girls were more satisfied with their own body size and shape in the year 2015 than in the 2000. The present study showed that changing depictions of body image issues in mass media (magazines aimed for adolescent girls) were in parallel with the proper self-esteem of body size in adolescent girls.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method

NASA Astrophysics Data System (ADS)

Irshad, Humayun; Oh, Eun-Yeong; Schmolze, Daniel; Quintana, Liza M.; Collins, Laura; Tamimi, Rulla M.; Beck, Andrew H.

2017-02-01

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

A novel technique to measure intensity fluctuations in EUV images and to detect coronal sound waves nearby active regions

NASA Astrophysics Data System (ADS)

Stenborg, G.; Marsch, E.; Vourlidas, A.; Howard, R.; Baldwin, K.

2011-02-01

Context. In the past years, evidence for the existence of outward-moving (Doppler blue-shifted) plasma and slow-mode magneto-acoustic propagating waves in various magnetic field structures (loops in particular) in the solar corona has been found in ultraviolet images and spectra. Yet their origin and possible connection to and importance for the mass and energy supply to the corona and solar wind is still unclear. There has been increasing interest in this problem thanks to the high-resolution observations available from the extreme ultraviolet (EUV) imagers on the Solar TErrestrial RElationships Observatory (STEREO) and the EUV spectrometer on the Hinode mission. Aims: Flows and waves exist in the corona, and their signatures appear in EUV imaging observations but are extremely difficult to analyse quantitatively because of their weak intensity. Hence, such information is currently available mostly from spectroscopic observations that are restricted in their spatial and temporal coverage. To understand the nature and origin of these fluctuations, imaging observations are essential. Here, we present measurements of the speed of intensity fluctuations observed along apparently open field lines with the Extreme UltraViolet Imagers (EUVI) onboard the STEREO mission. One aim of our paper is to demonstrate that we can make reliable kinematic measurements from these EUV images, thereby complementing and extending the spectroscopic measurements and opening up the full corona for such an analysis. Another aim is to examine the assumptions that lead to flow versus wave interpretation for these fluctuations. Methods: We have developed a novel image-processing method by fusing well established techniques for the kinematic analysis of coronal mass ejections (CME) with standard wavelet analysis. The power of our method lies with its ability to recover weak intensity fluctuations along individual magnetic structures at any orientation , anywhere within the full solar disk , and using standard synoptic observing sequences (cadence <3 min) without the need for special observation plans. Results: Using information from both EUVI imagers, we obtained wave phase speeds with values on the order of 60-90 km s-1, compatible with those obtained by other previous measurements. Moreover, we studied the periodicity of the observed fluctuations and established a predominance of a 16-min period, and other periods that seem to be multiples of an underlying 8-min period. Conclusions: The validation of our analysis technique opens up new possibilities for the study of coronal flows and waves, by extending it to the full disk and to a larger number of coronal structures than has been possible previously. It opens up a new scientific capability for the EUV observations from the recently launched Solar Dynamics Observatory. Here we clearly establish the ubiquitous existence of sound waves which continuously propagate along apparently open magnetic field lines. Movies 1 and 2 (Figs. 12 and 13) are only available in electronic form at http://www.aanda.org

Determination of renewable energy yield from mixed waste material from the use of novel image analysis methods.

PubMed

Wagland, S T; Dudley, R; Naftaly, M; Longhurst, P J

2013-11-01

Two novel techniques are presented in this study which together aim to provide a system able to determine the renewable energy potential of mixed waste materials. An image analysis tool was applied to two waste samples prepared using known quantities of source-segregated recyclable materials. The technique was used to determine the composition of the wastes, where through the use of waste component properties the biogenic content of the samples was calculated. The percentage renewable energy determined by image analysis for each sample was accurate to within 5% of the actual values calculated. Microwave-based multiple-point imaging (AutoHarvest) was used to demonstrate the ability of such a technique to determine the moisture content of mixed samples. This proof-of-concept experiment was shown to produce moisture measurement accurate to within 10%. Overall, the image analysis tool was able to determine the renewable energy potential of the mixed samples, and the AutoHarvest should enable the net calorific value calculations through the provision of moisture content measurements. The proposed system is suitable for combustion facilities, and enables the operator to understand the renewable energy potential of the waste prior to combustion. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-12-01

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

Limited diagnostic value of Dual-Time-Point (18)F-FDG PET/CT imaging for classifying solitary pulmonary nodules in granuloma-endemic regions both at visual and quantitative analyses.

PubMed

Chen, Song; Li, Xuena; Chen, Meijie; Yin, Yafu; Li, Na; Li, Yaming

2016-10-01

This study is aimed to compare the diagnostic power of using quantitative analysis or visual analysis with single time point imaging (STPI) PET/CT and dual time point imaging (DTPI) PET/CT for the classification of solitary pulmonary nodules (SPN) lesions in granuloma-endemic regions. SPN patients who received early and delayed (18)F-FDG PET/CT at 60min and 180min post-injection were retrospectively reviewed. Diagnoses are confirmed by pathological results or follow-ups. Three quantitative metrics, early SUVmax, delayed SUVmax and retention index(the percentage changes between the early SUVmax and delayed SUVmax), were measured for each lesion. Three 5-point scale score was given by blinded interpretations performed by physicians based on STPI PET/CT images, DTPI PET/CT images and CT images, respectively. ROC analysis was performed on three quantitative metrics and three visual interpretation scores. One-hundred-forty-nine patients were retrospectively included. The areas under curve (AUC) of the ROC curves of early SUVmax, delayed SUVmax, RI, STPI PET/CT score, DTPI PET/CT score and CT score are 0.73, 0.74, 0.61, 0.77 0.75 and 0.76, respectively. There were no significant differences between the AUCs in visual interpretation of STPI PET/CT images and DTPI PET/CT images, nor in early SUVmax and delayed SUVmax. The differences of sensitivity, specificity and accuracy between STPI PET/CT and DTPI PET/CT were not significantly different in either quantitative analysis or visual interpretation. In granuloma-endemic regions, DTPI PET/CT did not offer significant improvement over STPI PET/CT in differentiating malignant SPNs in both quantitative analysis and visual interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

Imaging and the completion of the omics paradigm in breast cancer.

PubMed

Leithner, D; Horvat, J V; Ochoa-Albiztegui, R E; Thakur, S; Wengert, G; Morris, E A; Helbich, T H; Pinker, K

2018-06-08

Within the field of oncology, "omics" strategies-genomics, transcriptomics, proteomics, metabolomics-have many potential applications and may significantly improve our understanding of the underlying processes of cancer development and progression. Omics strategies aim to develop meaningful imaging biomarkers for breast cancer (BC) by rapid assessment of large datasets with different biological information. In BC the paradigm of omics technologies has always favored the integration of multiple layers of omics data to achieve a complete portrait of BC. Advances in medical imaging technologies, image analysis, and the development of high-throughput methods that can extract and correlate multiple imaging parameters with "omics" data have ushered in a new direction in medical research. Radiogenomics is a novel omics strategy that aims to correlate imaging characteristics (i. e., the imaging phenotype) with underlying gene expression patterns, gene mutations, and other genome-related characteristics. Radiogenomics not only represents the evolution in the radiology-pathology correlation from the anatomical-histological level to the molecular level, but it is also a pivotal step in the omics paradigm in BC in order to fully characterize BC. Armed with modern analytical software tools, radiogenomics leads to new discoveries of quantitative and qualitative imaging biomarkers that offer hitherto unprecedented insights into the complex tumor biology and facilitate a deeper understanding of cancer development and progression. The field of radiogenomics in breast cancer is rapidly evolving, and results from previous studies are encouraging. It can be expected that radiogenomics will play an important role in the future and has the potential to revolutionize the diagnosis, treatment, and prognosis of BC patients. This article aims to give an overview of breast radiogenomics, its current role, future applications, and challenges.

Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

PubMed

Zhang, Jiachao; Hirakawa, Keigo

2017-04-01

This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

Methodological challenges of optical tweezers-based X-ray fluorescence imaging of biological model organisms at synchrotron facilities.

PubMed

Vergucht, Eva; Brans, Toon; Beunis, Filip; Garrevoet, Jan; Bauters, Stephen; De Rijcke, Maarten; Deruytter, David; Janssen, Colin; Riekel, Christian; Burghammer, Manfred; Vincze, Laszlo

2015-07-01

Recently, a radically new synchrotron radiation-based elemental imaging approach for the analysis of biological model organisms and single cells in their natural in vivo state was introduced. The methodology combines optical tweezers (OT) technology for non-contact laser-based sample manipulation with synchrotron radiation confocal X-ray fluorescence (XRF) microimaging for the first time at ESRF-ID13. The optical manipulation possibilities and limitations of biological model organisms, the OT setup developments for XRF imaging and the confocal XRF-related challenges are reported. In general, the applicability of the OT-based setup is extended with the aim of introducing the OT XRF methodology in all research fields where highly sensitive in vivo multi-elemental analysis is of relevance at the (sub)micrometre spatial resolution level.

Ring Image Analyzer

NASA Technical Reports Server (NTRS)

Strekalov, Dmitry V.

2012-01-01

Ring Image Analyzer software analyzes images to recognize elliptical patterns. It determines the ellipse parameters (axes ratio, centroid coordinate, tilt angle). The program attempts to recognize elliptical fringes (e.g., Newton Rings) on a photograph and determine their centroid position, the short-to-long-axis ratio, and the angle of rotation of the long axis relative to the horizontal direction on the photograph. These capabilities are important in interferometric imaging and control of surfaces. In particular, this program has been developed and applied for determining the rim shape of precision-machined optical whispering gallery mode resonators. The program relies on a unique image recognition algorithm aimed at recognizing elliptical shapes, but can be easily adapted to other geometric shapes. It is robust against non-elliptical details of the image and against noise. Interferometric analysis of precision-machined surfaces remains an important technological instrument in hardware development and quality analysis. This software automates and increases the accuracy of this technique. The software has been developed for the needs of an R&TD-funded project and has become an important asset for the future research proposal to NASA as well as other agencies.

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

PubMed

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

2004-01-01

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

Automatic analysis for neuron by confocal laser scanning microscope

NASA Astrophysics Data System (ADS)

Satou, Kouhei; Aoki, Yoshimitsu; Mataga, Nobuko; Hensh, Takao K.; Taki, Katuhiko

2005-12-01

The aim of this study is to develop a system that recognizes both the macro- and microscopic configurations of nerve cells and automatically performs the necessary 3-D measurements and functional classification of spines. The acquisition of 3-D images of cranial nerves has been enabled by the use of a confocal laser scanning microscope, although the highly accurate 3-D measurements of the microscopic structures of cranial nerves and their classification based on their configurations have not yet been accomplished. In this study, in order to obtain highly accurate measurements of the microscopic structures of cranial nerves, existing positions of spines were predicted by the 2-D image processing of tomographic images. Next, based on the positions that were predicted on the 2-D images, the positions and configurations of the spines were determined more accurately by 3-D image processing of the volume data. We report the successful construction of an automatic analysis system that uses a coarse-to-fine technique to analyze the microscopic structures of cranial nerves with high speed and accuracy by combining 2-D and 3-D image analyses.

T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model.

PubMed

Whittaker, Heather T; Zhu, Shenghua; Di Curzio, Domenico L; Buist, Richard; Li, Xin-Min; Noy, Suzanna; Wiseman, Frances K; Thiessen, Jonathan D; Martin, Melanie

2018-07-01

Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T 1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T 1 -weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD. Copyright © 2018. Published by Elsevier Inc.

An Image Encryption Algorithm Based on Information Hiding

NASA Astrophysics Data System (ADS)

Ge, Xin; Lu, Bin; Liu, Fenlin; Gong, Daofu

Aiming at resolving the conflict between security and efficiency in the design of chaotic image encryption algorithms, an image encryption algorithm based on information hiding is proposed based on the “one-time pad” idea. A random parameter is introduced to ensure a different keystream for each encryption, which has the characteristics of “one-time pad”, improving the security of the algorithm rapidly without significant increase in algorithm complexity. The random parameter is embedded into the ciphered image with information hiding technology, which avoids negotiation for its transport and makes the application of the algorithm easier. Algorithm analysis and experiments show that the algorithm is secure against chosen plaintext attack, differential attack and divide-and-conquer attack, and has good statistical properties in ciphered images.

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

PubMed

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

2014-02-01

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

Radar signal analysis of ballistic missile with micro-motion based on time-frequency distribution

NASA Astrophysics Data System (ADS)

Wang, Jianming; Liu, Lihua; Yu, Hua

2015-12-01

The micro-motion of ballistic missile targets induces micro-Doppler modulation on the radar return signal, which is a unique feature for the warhead discrimination during flight. In order to extract the micro-Doppler feature of ballistic missile targets, time-frequency analysis is employed to process the micro-Doppler modulated time-varying radar signal. The images of time-frequency distribution (TFD) reveal the micro-Doppler modulation characteristic very well. However, there are many existing time-frequency analysis methods to generate the time-frequency distribution images, including the short-time Fourier transform (STFT), Wigner distribution (WD) and Cohen class distribution, etc. Under the background of ballistic missile defence, the paper aims at working out an effective time-frequency analysis method for ballistic missile warhead discrimination from the decoys.

A learning tool for optical and microwave satellite image processing and analysis

NASA Astrophysics Data System (ADS)

Dashondhi, Gaurav K.; Mohanty, Jyotirmoy; Eeti, Laxmi N.; Bhattacharya, Avik; De, Shaunak; Buddhiraju, Krishna M.

2016-04-01

This paper presents a self-learning tool, which contains a number of virtual experiments for processing and analysis of Optical/Infrared and Synthetic Aperture Radar (SAR) images. The tool is named Virtual Satellite Image Processing and Analysis Lab (v-SIPLAB) Experiments that are included in Learning Tool are related to: Optical/Infrared - Image and Edge enhancement, smoothing, PCT, vegetation indices, Mathematical Morphology, Accuracy Assessment, Supervised/Unsupervised classification etc.; Basic SAR - Parameter extraction and range spectrum estimation, Range compression, Doppler centroid estimation, Azimuth reference function generation and compression, Multilooking, image enhancement, texture analysis, edge and detection. etc.; SAR Interferometry - BaseLine Calculation, Extraction of single look SAR images, Registration, Resampling, and Interferogram generation; SAR Polarimetry - Conversion of AirSAR or Radarsat data to S2/C3/T3 matrix, Speckle Filtering, Power/Intensity image generation, Decomposition of S2/C3/T3, Classification of S2/C3/T3 using Wishart Classifier [3]. A professional quality polarimetric SAR software can be found at [8], a part of whose functionality can be found in our system. The learning tool also contains other modules, besides executable software experiments, such as aim, theory, procedure, interpretation, quizzes, link to additional reading material and user feedback. Students can have understanding of Optical and SAR remotely sensed images through discussion of basic principles and supported by structured procedure for running and interpreting the experiments. Quizzes for self-assessment and a provision for online feedback are also being provided to make this Learning tool self-contained. One can download results after performing experiments.

Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography

NASA Astrophysics Data System (ADS)

Liu, Shengnan; Eggermont, Jeroen; Wolterbeek, Ron; Broersen, Alexander; Busk, Carol A. G. R.; Precht, Helle; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

2016-12-01

Intravascular optical coherence tomography (IVOCT) is an imaging technique that is used to analyze the underlying cause of cardiovascular disease. Because a catheter is used during imaging, the intensities can be affected by the catheter position. This work aims to analyze the effect of the catheter position on IVOCT image intensities and to propose a compensation method to minimize this effect in order to improve the visualization and the automatic analysis of IVOCT images. The effect of catheter position is modeled with respect to the distance between the catheter and the arterial wall (distance-dependent factor) and the incident angle onto the arterial wall (angle-dependent factor). A light transmission model incorporating both factors is introduced. On the basis of this model, the interaction effect of both factors is estimated with a hierarchical multivariant linear regression model. Statistical analysis shows that IVOCT intensities are significantly affected by both factors with p<0.001, as either aspect increases the intensity decreases. This effect differs for different pullbacks. The regression results were used to compensate for this effect. Experiments show that the proposed compensation method can improve the performance of the automatic bioresorbable vascular scaffold strut detection.

Instant electronic imaging systems are superior to Polaroid at detecting sight-threatening diabetic retinopathy.

PubMed

Ryder, R E; Kong, N; Bates, A S; Sim, J; Welch, J; Kritzinger, E E

1998-03-01

Polaroid photography in diabetic retinopathy screening allows instant image availability to enhance the results of ophthalmoscopy. Retinal cameras are now being developed which use video/digital imaging techniques to produce an instant enlarged retinal image on a computer monitor screen. We aimed to compare one such electronic imaging system, attached to a Canon CR5 45NM, with standard Polaroid retinal photography. Two hundred and thirteen eyes from 107 diabetic patients were photographed through dilated pupils by both systems in random order and the images were analysed blind. Diabetic retinopathy was present in 58 eyes of which 55/58 (95%) were detected on the electronic image and only 49/58 (84%) on the Polaroid. Of 34 eyes requiring ophthalmologist referral according to standard European criteria, 34/34 (100%) were detected on the electronic image and only 24/34 (71%) on the Polaroid. Side by side comparisons showed electronic imaging to be superior to Polaroid at lesion detection. Using linear analogue scales, the patients assessed the electronic imaging photographic flash as less uncomfortable than the Polaroid equivalent (p < 0.0001). Other advantages of electronic imaging include: ready storage of the images with other patient clinical data on the diabetes computerized register/database; potential for image enhancement and analysis using image analysis software and electronic transfer of images to ophthalmologist or general practitioner. Electronic imaging systems represent a potential major advance for the improvement of diabetic retinopathy screening.

Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions.

PubMed

Choi, Hongyoon

2018-04-01

Recent advances in deep learning have impacted various scientific and industrial fields. Due to the rapid application of deep learning in biomedical data, molecular imaging has also started to adopt this technique. In this regard, it is expected that deep learning will potentially affect the roles of molecular imaging experts as well as clinical decision making. This review firstly offers a basic overview of deep learning particularly for image data analysis to give knowledge to nuclear medicine physicians and researchers. Because of the unique characteristics and distinctive aims of various types of molecular imaging, deep learning applications can be different from other fields. In this context, the review deals with current perspectives of deep learning in molecular imaging particularly in terms of development of biomarkers. Finally, future challenges of deep learning application for molecular imaging and future roles of experts in molecular imaging will be discussed.

Predictive images of postoperative levator resection outcome using image processing software.

PubMed

Mawatari, Yuki; Fukushima, Mikiko

2016-01-01

This study aims to evaluate the efficacy of processed images to predict postoperative appearance following levator resection. Analysis involved 109 eyes from 65 patients with blepharoptosis who underwent advancement of levator aponeurosis and Müller's muscle complex (levator resection). Predictive images were prepared from preoperative photographs using the image processing software (Adobe Photoshop ® ). Images of selected eyes were digitally enlarged in an appropriate manner and shown to patients prior to surgery. Approximately 1 month postoperatively, we surveyed our patients using questionnaires. Fifty-six patients (89.2%) were satisfied with their postoperative appearances, and 55 patients (84.8%) positively responded to the usefulness of processed images to predict postoperative appearance. Showing processed images that predict postoperative appearance to patients prior to blepharoptosis surgery can be useful for those patients concerned with their postoperative appearance. This approach may serve as a useful tool to simulate blepharoptosis surgery.

Predictive images of postoperative levator resection outcome using image processing software

PubMed Central

Mawatari, Yuki; Fukushima, Mikiko

2016-01-01

Purpose This study aims to evaluate the efficacy of processed images to predict postoperative appearance following levator resection. Methods Analysis involved 109 eyes from 65 patients with blepharoptosis who underwent advancement of levator aponeurosis and Müller’s muscle complex (levator resection). Predictive images were prepared from preoperative photographs using the image processing software (Adobe Photoshop®). Images of selected eyes were digitally enlarged in an appropriate manner and shown to patients prior to surgery. Results Approximately 1 month postoperatively, we surveyed our patients using questionnaires. Fifty-six patients (89.2%) were satisfied with their postoperative appearances, and 55 patients (84.8%) positively responded to the usefulness of processed images to predict postoperative appearance. Conclusion Showing processed images that predict postoperative appearance to patients prior to blepharoptosis surgery can be useful for those patients concerned with their postoperative appearance. This approach may serve as a useful tool to simulate blepharoptosis surgery. PMID:27757008

A Survey of FDG- and Amyloid-PET Imaging in Dementia and GRADE Analysis

PubMed Central

Daniela, Perani; Orazio, Schillaci; Alessandro, Padovani; Mariano, Nobili Flavio; Leonardo, Iaccarino; Pasquale Anthony, Della Rosa; Giovanni, Frisoni; Carlo, Caltagirone

2014-01-01

PET based tools can improve the early diagnosis of Alzheimer's disease (AD) and differential diagnosis of dementia. The importance of identifying individuals at risk of developing dementia among people with subjective cognitive complaints or mild cognitive impairment has clinical, social, and therapeutic implications. Within the two major classes of AD biomarkers currently identified, that is, markers of pathology and neurodegeneration, amyloid- and FDG-PET imaging represent decisive tools for their measurement. As a consequence, the PET tools have been recognized to be of crucial value in the recent guidelines for the early diagnosis of AD and other dementia conditions. The references based recommendations, however, include large PET imaging literature based on visual methods that greatly reduces sensitivity and specificity and lacks a clear cut-off between normal and pathological findings. PET imaging can be assessed using parametric or voxel-wise analyses by comparing the subject's scan with a normative data set, significantly increasing the diagnostic accuracy. This paper is a survey of the relevant literature on FDG and amyloid-PET imaging aimed at providing the value of quantification for the early and differential diagnosis of AD. This allowed a meta-analysis and GRADE analysis revealing high values for PET imaging that might be useful in considering recommendations. PMID:24772437

Health-Related Messages about Physical Activity Promotion: An Analysis of Photographs on Social Networking Sites of Universities

ERIC Educational Resources Information Center

Martínez-Bello, Vladimir E.; Martínez-Rojas, Ángela; Molina-García, Javier

2017-01-01

The main aim of this study was to examine how different physical activity domains are represented on the official social media sites of Spanish universities, through a content analysis of the photographs. Our results show that the representation of different physical activity domains is not balanced. While the analysed images do promote a message…

A Content Analysis Comparing Gender Images in Network Television Commercials Aired in Daytime, Evening, and Weekend Telecasts.

ERIC Educational Resources Information Center

Craig, R. Stephen

A content analysis comparing gender portrayals in 2,209 network television commercials was conducted. Many earlier studies treated television advertising's portrayal of men as unproblematic and excluded ads aimed specifically at men from the study sample. To address this shortcoming, the sample was chosen from three different day parts: (1)…

In Situ Characterization of Boehmite Particles in Water Using Liquid SEM.

PubMed

Yao, Juan; Arey, Bruce W; Yang, Li; Zhang, Fei; Komorek, Rachel; Chun, Jaehun; Yu, Xiao-Ying

2017-09-27

In situ imaging and elemental analysis of boehmite (AlOOH) particles in water is realized using the System for Analysis at the Liquid Vacuum Interface (SALVI) and Scanning Electron Microscopy (SEM). This paper describes the method and key steps in integrating the vacuum compatible SAVLI to SEM and obtaining secondary electron (SE) images of particles in liquid in high vacuum. Energy dispersive x-ray spectroscopy (EDX) is used to obtain elemental analysis of particles in liquid and control samples including deionized (DI) water only and an empty channel as well. Synthesized boehmite (AlOOH) particles suspended in liquid are used as a model in the liquid SEM illustration. The results demonstrate that the particles can be imaged in the SE mode with good resolution (i.e., 400 nm). The AlOOH EDX spectrum shows significant signal from the aluminum (Al) when compared with the DI water and the empty channel control. In situ liquid SEM is a powerful technique to study particles in liquid with many exciting applications. This procedure aims to provide technical know-how in order to conduct liquid SEM imaging and EDX analysis using SALVI and to reduce potential pitfalls when using this approach.

Measurement of stain on extracted teeth using spectrophotometry and digital image analysis.

PubMed

Lath, D L; Smith, R N; Guan, Y H; Karmo, M; Brook, A H

2007-08-01

The aim of this study was to assess the reliability and validate a customized image analysis system, designed for use within clinical trials of general dental hygiene and whitening products, for the measurement of stain levels on extracted teeth and to compare it with reflectance spectrophotometry. Twenty non-carious extracted teeth were soaked in an artificial saliva, brushed for 1 min using an electric toothbrush and a standard toothpaste, bleached using a 5.3% hydrogen peroxide solution and cycled for 6 h daily through a tea solution. CIE L* values were obtained after each treatment step using the customized image analysis system and a reflectance spectrophotometer. A statistical analysis was carried out in SPSS. Fleiss' coefficient of reliability for intra-operator repeatability of the image analysis system and spectrophotometry was 0.996 and 0.946 respectively. CIE L* values were consistently higher using the image analysis compared with spectrophotometry, and t-tests for each treatment step showed significant differences (P < 0.05) for the two methods. Limits of agreement between the methods were -27.95 to +2.07, with a 95% confidence of the difference calculated as -14.26 to -11.84. The combined results for all treatment steps showed a significant difference between the methods for the CIE L* values (P < 0.05). The image analysis system has proven to be a reliable method for assessment of changes in stain level on extracted teeth. The method has been validated against reflectance spectrophotometry. This method may be used for pilot in vitro studies/trials of oral hygiene and whitening products, before expensive in vivo tests are carried out.

Automated aerial image based CD metrology initiated by pattern marking with photomask layout data

NASA Astrophysics Data System (ADS)

Davis, Grant; Choi, Sun Young; Jung, Eui Hee; Seyfarth, Arne; van Doornmalen, Hans; Poortinga, Eric

2007-05-01

The photomask is a critical element in the lithographic image transfer process from the drawn layout to the final structures on the wafer. The non-linearity of the imaging process and the related MEEF impose a tight control requirement on the photomask critical dimensions. Critical dimensions can be measured in aerial images with hardware emulation. This is a more recent complement to the standard scanning electron microscope measurement of wafers and photomasks. Aerial image measurement includes non-linear, 3-dimensional, and materials effects on imaging that cannot be observed directly by SEM measurement of the mask. Aerial image measurement excludes the processing effects of printing and etching on the wafer. This presents a unique contribution to the difficult process control and modeling tasks in mask making. In the past, aerial image measurements have been used mainly to characterize the printability of mask repair sites. Development of photomask CD characterization with the AIMS TM tool was motivated by the benefit of MEEF sensitivity and the shorter feedback loop compared to wafer exposures. This paper describes a new application that includes: an improved interface for the selection of meaningful locations using the photomask and design layout data with the Calibre TM Metrology Interface, an automated recipe generation process, an automated measurement process, and automated analysis and result reporting on a Carl Zeiss AIMS TM system.

Invariant approach to the character classification

NASA Astrophysics Data System (ADS)

Šariri, Kristina; Demoli, Nazif

2008-04-01

Image moments analysis is a very useful tool which allows image description invariant to translation and rotation, scale change and some types of image distortions. The aim of this work was development of simple method for fast and reliable classification of characters by using Hu's and affine moment invariants. Measure of Eucleidean distance was used as a discrimination feature with statistical parameters estimated. The method was tested in classification of Times New Roman font letters as well as sets of the handwritten characters. It is shown that using all Hu's and three affine invariants as discrimination set improves recognition rate by 30%.

Quantitative high-speed laryngoscopic analysis of vocal fold vibration in fatigued voice of young karaoke singers.

PubMed

Yiu, Edwin M-L; Wang, Gaowu; Lo, Andy C Y; Chan, Karen M-K; Ma, Estella P-M; Kong, Jiangping; Barrett, Elizabeth Ann

2013-11-01

The present study aimed to determine whether there were physiological differences in the vocal fold vibration between nonfatigued and fatigued voices using high-speed laryngoscopic imaging and quantitative analysis. Twenty participants aged from 18 to 23 years (mean, 21.2 years; standard deviation, 1.3 years) with normal voice were recruited to participate in an extended singing task. Vocal fatigue was induced using a singing task. High-speed laryngoscopic image recordings of /i/ phonation were taken before and after the singing task. The laryngoscopic images were semiautomatically analyzed with the quantitative high-speed video processing program to extract indices related to the anteroposterior dimension (length), transverse dimension (width), and the speed of opening and closing. Significant reduction in the glottal length-to-width ratio index was found after vocal fatigue. Physiologically, this indicated either a significantly shorter (anteroposteriorly) or a wider (transversely) glottis after vocal fatigue. The high-speed imaging technique using quantitative analysis has the potential for early identification of vocally fatigued voice. Copyright © 2013 The Voice Foundation. All rights reserved.

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

Cardiac imaging: working towards fully-automated machine analysis & interpretation

PubMed Central

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-01-01

Introduction Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation. PMID:28277804

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

PubMed

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

2017-02-01

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

Are power calculations useful? A multicentre neuroimaging study

PubMed Central

Suckling, John; Henty, Julian; Ecker, Christine; Deoni, Sean C; Lombardo, Michael V; Baron-Cohen, Simon; Jezzard, Peter; Barnes, Anna; Chakrabarti, Bhismadev; Ooi, Cinly; Lai, Meng-Chuan; Williams, Steven C; Murphy, Declan GM; Bullmore, Edward

2014-01-01

There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources. PMID:24644267

MicroCT analysis of a retrieved root restored with a bonded fiber-reinforced composite dowel: a pilot study.

PubMed

Lorenzoni, Fabio Cesar; Bonfante, Estevam A; Bonfante, Gerson; Martins, Leandro M; Witek, Lukasz; Silva, Nelson R F A

2013-08-01

This evaluation aimed to (1) validate micro-computed tomography (microCT) findings using scanning electron microscopy (SEM) imaging, and (2) quantify the volume of voids and the bonded surface area resulting from fiber-reinforced composite (FRC) dowel cementation technique using microCT scanning technology/3D reconstructing software. A fiberglass dowel was cemented in a condemned maxillary lateral incisor prior to its extraction. A microCT scan was performed of the extracted tooth creating a large volume of data in DICOM format. This set of images was imported to image-processing software to inspect the internal architecture of structures. The outer surface and the spatial relationship of dentin, FRC dowel, cement layer, and voids were reconstructed. Three-dimensional spatial architecture of structures and volumetric analysis revealed that 9.89% of the resin cement was composed of voids and that the bonded area between root dentin and cement was 60.63% larger than that between cement and FRC dowel. SEM imaging demonstrated the presence of voids similarly observed using microCT technology (aim 1). MicroCT technology was able to nondestructively measure the volume of voids within the cement layer and the bonded surface area at the root/cement/FRC interfaces (aim 2). The interfaces at the root dentin/cement/dowel represent a timely and relevant topic where several efforts have been conducted in the past few years to understand their inherent features. MicroCT technology combined with 3D reconstruction allows for not only inspecting the internal arrangement rendered by fiberglass adhesively bonded to root dentin, but also estimating the volume of voids and contacted bond area between the dentin and cement layer. © 2013 by the American College of Prosthodontists.

Mining textural knowledge in biological images: Applications, methods and trends.

PubMed

Di Cataldo, Santa; Ficarra, Elisa

2017-01-01

Texture analysis is a major task in many areas of computer vision and pattern recognition, including biological imaging. Indeed, visual textures can be exploited to distinguish specific tissues or cells in a biological sample, to highlight chemical reactions between molecules, as well as to detect subcellular patterns that can be evidence of certain pathologies. This makes automated texture analysis fundamental in many applications of biomedicine, such as the accurate detection and grading of multiple types of cancer, the differential diagnosis of autoimmune diseases, or the study of physiological processes. Due to their specific characteristics and challenges, the design of texture analysis systems for biological images has attracted ever-growing attention in the last few years. In this paper, we perform a critical review of this important topic. First, we provide a general definition of texture analysis and discuss its role in the context of bioimaging, with examples of applications from the recent literature. Then, we review the main approaches to automated texture analysis, with special attention to the methods of feature extraction and encoding that can be successfully applied to microscopy images of cells or tissues. Our aim is to provide an overview of the state of the art, as well as a glimpse into the latest and future trends of research in this area.

Whole-tumor histogram analysis of the cerebral blood volume map: tumor volume defined by 11C-methionine positron emission tomography image improves the diagnostic accuracy of cerebral glioma grading.

PubMed

Wu, Rongli; Watanabe, Yoshiyuki; Arisawa, Atsuko; Takahashi, Hiroto; Tanaka, Hisashi; Fujimoto, Yasunori; Watabe, Tadashi; Isohashi, Kayako; Hatazawa, Jun; Tomiyama, Noriyuki

2017-10-01

This study aimed to compare the tumor volume definition using conventional magnetic resonance (MR) and 11C-methionine positron emission tomography (MET/PET) images in the differentiation of the pre-operative glioma grade by using whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) maps. Thirty-four patients with histopathologically proven primary brain low-grade gliomas (n = 15) and high-grade gliomas (n = 19) underwent pre-operative or pre-biopsy MET/PET, fluid-attenuated inversion recovery, dynamic susceptibility contrast perfusion-weighted magnetic resonance imaging, and contrast-enhanced T1-weighted at 3.0 T. The histogram distribution derived from the nCBV maps was obtained by co-registering the whole tumor volume delineated on conventional MR or MET/PET images, and eight histogram parameters were assessed. The mean nCBV value had the highest AUC value (0.906) based on MET/PET images. Diagnostic accuracy significantly improved when the tumor volume was measured from MET/PET images compared with conventional MR images for the parameters of mean, 50th, and 75th percentile nCBV value (p = 0.0246, 0.0223, and 0.0150, respectively). Whole-tumor histogram analysis of CBV map provides more valuable histogram parameters and increases diagnostic accuracy in the differentiation of pre-operative cerebral gliomas when the tumor volume is derived from MET/PET images.

Digital image analysis of Ki67 in hot spots is superior to both manual Ki67 and mitotic counts in breast cancer.

PubMed

Stålhammar, Gustav; Robertson, Stephanie; Wedlund, Lena; Lippert, Michael; Rantalainen, Mattias; Bergh, Jonas; Hartman, Johan

2018-05-01

During pathological examination of breast tumours, proliferative activity is routinely evaluated by a count of mitoses. Adding immunohistochemical stains of Ki67 provides extra prognostic and predictive information. However, the currently used methods for these evaluations suffer from imperfect reproducibility. It is still unclear whether analysis of Ki67 should be performed in hot spots, in the tumour periphery, or as an average of the whole tumour section. The aim of this study was to compare the clinical relevance of mitoses, Ki67 and phosphohistone H3 in two cohorts of primary breast cancer specimens (total n = 294). Both manual and digital image analysis scores were evaluated for sensitivity and specificity for luminal B versus A subtype as defined by PAM50 gene expression assays, for high versus low transcriptomic grade, for axillary lymph node status, and for prognostic value in terms of prediction of overall and relapse-free survival. Digital image analysis of Ki67 outperformed the other markers, especially in hot spots. Tumours with high Ki67 expression and high numbers of phosphohistone H3-positive cells had significantly increased hazard ratios for all-cause mortality within 10 years from diagnosis. Replacing manual mitotic counts with digital image analysis of Ki67 in hot spots increased the differences in overall survival between the highest and lowest histological grades, and added significant prognostic information. Digital image analysis of Ki67 in hot spots is the marker of choice for routine analysis of proliferation in breast cancer. © 2017 John Wiley & Sons Ltd.

Molecular Imaging and Therapy of Prostate Cancer

DTIC Science & Technology

2015-10-01

arsenic-based, IGF1R-targeted radiopharmaceuticals can allow for PET imaging, IRT, and monitoring the therapeutic response of PCa. Specific Aims: Aim 1: To...models with PET imaging. Aim 3: To monitor the efficacy of 76As-based IRT of PCa with multimodality imaging.

Augmented Reality Image Guidance in Minimally Invasive Prostatectomy

NASA Astrophysics Data System (ADS)

Cohen, Daniel; Mayer, Erik; Chen, Dongbin; Anstee, Ann; Vale, Justin; Yang, Guang-Zhong; Darzi, Ara; Edwards, Philip'eddie'

This paper presents our work aimed at providing augmented reality (AR) guidance of robot-assisted laparoscopic surgery (RALP) using the da Vinci system. There is a good clinical case for guidance due to the significant rate of complications and steep learning curve for this procedure. Patients who were due to undergo robotic prostatectomy for organ-confined prostate cancer underwent preoperative 3T MRI scans of the pelvis. These were segmented and reconstructed to form 3D images of pelvic anatomy. The reconstructed image was successfully overlaid onto screenshots of the recorded surgery post-procedure. Surgeons who perform minimally-invasive prostatectomy took part in a user-needs analysis to determine the potential benefits of an image guidance system after viewing the overlaid images. All surgeons stated that the development would be useful at key stages of the surgery and could help to improve the learning curve of the procedure and improve functional and oncological outcomes. Establishing the clinical need in this way is a vital early step in development of an AR guidance system. We have also identified relevant anatomy from preoperative MRI. Further work will be aimed at automated registration to account for tissue deformation during the procedure, using a combination of transrectal ultrasound and stereoendoscopic video.

Study of the urban evolution of Brasilia with the use of LANDSAT data

NASA Technical Reports Server (NTRS)

Deoliveira, M. D. N. (Principal Investigator); Foresti, C.; Niero, M.; Parreiras, E. M. D. F.

1984-01-01

The urban growth of Brasilia within the last ten years is analyzed with special emphasis on the utilization of remote sensing orbital data and automatic image processing. The urban spatial structure and the monitoring of its temporal changes were focused in a whole and dynamic way by the utilization of MSS-LANDSAT images for June 1973, 1978 and 1983. In order to aid data interpretation, a registration algorithm implemented at the Interactive Multispectral Image Analysis System (IMAGE-100) was utilized aiming at the overlap of multitemporal images. The utilization of suitable digital filters, combined with the images overlap, allowed a rapid identification of areas of possible urban growth and oriented the field work. The results obtained permitted an evaluation of the urban growth of Brasilia, taking as reference the proposed stated for the construction of the city.

Analysis of intensity variability in multislice and cone beam computed tomography.

PubMed

Nackaerts, Olivia; Maes, Frederik; Yan, Hua; Couto Souza, Paulo; Pauwels, Ruben; Jacobs, Reinhilde

2011-08-01

The aim of this study was to evaluate the variability of intensity values in cone beam computed tomography (CBCT) imaging compared with multislice computed tomography Hounsfield units (MSCT HU) in order to assess the reliability of density assessments using CBCT images. A quality control phantom was scanned with an MSCT scanner and five CBCT scanners. In one CBCT scanner, the phantom was scanned repeatedly in the same and in different positions. Images were analyzed using registration to a mathematical model. MSCT images were used as a reference. Density profiles of MSCT showed stable HU values, whereas in CBCT imaging the intensity values were variable over the profile. Repositioning of the phantom resulted in large fluctuations in intensity values. The use of intensity values in CBCT images is not reliable, because the values are influenced by device, imaging parameters and positioning. © 2011 John Wiley & Sons A/S.

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

PubMed Central

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

2010-01-01

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

Green light may improve diagnostic accuracy of nailfold capillaroscopy with a simple digital videomicroscope.

PubMed

Weekenstroo, Harm H A; Cornelissen, Bart M W; Bernelot Moens, Hein J

2015-06-01

Nailfold capillaroscopy is a non-invasive and safe technique for the analysis of microangiopathologies. Imaging quality of widely used simple videomicroscopes is poor. The use of green illumination instead of the commonly used white light may improve contrast. The aim of the study was to compare the effect of green illumination with white illumination, regarding capillary density, the number of microangiopathologies, and sensitivity and specificity for systemic sclerosis. Five rheumatologists have evaluated 80 images; 40 images acquired with green light, and 40 images acquired with white light. A larger number of microangiopathologies were found in images acquired with green light than in images acquired with white light. This results in slightly higher sensitivity with green light in comparison with white light, without reducing the specificity. These findings suggest that green instead of white illumination may facilitate evaluation of capillaroscopic images obtained with a low-cost digital videomicroscope.

Experiment and application of soft x-ray grazing incidence optical scattering phenomena

NASA Astrophysics Data System (ADS)

Chen, Shuyan; Li, Cheng; Zhang, Yang; Su, Liping; Geng, Tao; Li, Kun

2017-08-01

For short wavelength imaging systems，surface scattering effects is one of important factors degrading imaging performance. Study of non-intuitive surface scatter effects resulting from practical optical fabrication tolerances is a necessary work for optical performance evaluation of high resolution short wavelength imaging systems. In this paper, Soft X-ray optical scattering distribution is measured by a soft X-ray reflectometer installed by my lab, for different sample mirrors、wavelength and grazing angle. Then aim at space solar telescope, combining these scattered light distributions, and surface scattering numerical model of grazing incidence imaging system, PSF and encircled energy of optical system of space solar telescope are computed. We can conclude that surface scattering severely degrade imaging performance of grazing incidence systems through analysis and computation.

Evaluation of the 3D spatial distribution of the Calcium/Phosphorus ratio in bone using computed-tomography dual-energy analysis.

PubMed

Hadjipanteli, A; Kourkoumelis, N; Fromme, P; Huang, J; Speller, R D

2016-01-01

The Calcium/Phosphorus (Ca/P) ratio was shown to vary between healthy bones and bones with osteoporotic symptoms. The relation of the Ca/P ratio to bone quality remains under investigation. To study this relation and determine if the ratio can be used to predict bone fractures, a non-invasive 3D imaging technique is required. The first aim of this study was to test the effectiveness of a computed-tomography dual-energy analysis (CT-DEA) technique developed to assess the Ca/P ratio in bone apatite (collagen-free bone) in identifying differences between healthy and inflammation-mediated osteoporotic (IMO) bones. The second aim was to extend the above technique for its application to a more complex structure, intact bone, that could potentially lead to clinical use. For the first aim, healthy and IMO rabbit cortical bone apatite samples were assessed. For the second aim, some changes were made to the technique, which was applied to healthy and IMO intact bone samples. Statistically significant differences between healthy and IMO bone apatite were found for the bulk Ca/P ratio, low Ca/P ratio proportion and interconnected low Ca/P ratio proportion. For the intact bone samples, the bulk Ca/P ratio was found to be significantly different between healthy and IMO. Results show that the CT-DEA technique can be used to identify differences in the Ca/P ratio between healthy and osteoporotic, in both bone apatite and intact bone. With quantitative imaging becoming an increasingly important advancement in medical imaging, CT-DEA for bone decomposition could potentially have several applications. Copyright © 2015. Published by Elsevier Ltd.

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

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

Li, R; Aguilera, T; Shultz, D

2014-06-15

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayesmore » (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in identifying patients who might benefit from adjuvant therapy.« less

Molecular imaging assessment of periodontitis lesions in an experimental mouse model.

PubMed

Ideguchi, Hidetaka; Yamashiro, Keisuke; Yamamoto, Tadashi; Shimoe, Masayuki; Hongo, Shoichi; Kochi, Shinsuke; Yoshihara-Hirata, Chiaki; Aoyagi, Hiroaki; Kawamura, Mari; Takashiba, Shogo

2018-06-06

We aimed to evaluate molecular imaging as a novel diagnostic tool for mice periodontitis model induced by ligature and Porphyromonas gingivalis (Pg) inoculation. Twelve female mice were assigned to the following groups: no treatment as control group (n = 4); periodontitis group induced by ligature and Pg as Pg group (n = 4); and Pg group treated with glycyrrhizinic acid (GA) as Pg + GA group (n = 4). All mice were administered a myeloperoxidase (MPO) activity-specific luminescent probe and observed using a charge-coupled device camera on day 14. Image analysis on all mice was conducted using software to determine the signal intensity of inflammation. Additionally, histological and radiographic evaluation for periodontal inflammation and bone resorption at the site of periodontitis, and quantitative enzyme-linked immunosorbent assay (ELISA) were conducted on three mice for each group. Each experiment was performed three times. Levels of serum IgG antibody against P. gingivalis were significantly higher in the Pg than in the Pg + GA group. Histological analyses indicated that the number of osteoclasts and neutrophils were significantly lower in the Pg + GA than in the Pg group. Micro-CT image analysis indicated no difference in bone resorption between the Pg and Pg + GA groups. The signal intensity of MPO activity was detected on the complete craniofacial image; moreover, strong signal intensity was localized specifically at the periodontitis site in the ex vivo palate, with group-wise differences. Molecular imaging analysis based on MPO activity showed high sensitivity of detection of periodontal inflammation in mice. Molecular imaging analysis based on MPO activity has potential as a diagnostic tool for periodontitis.

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas.

PubMed

Kinoshita, Manabu; Sakai, Mio; Arita, Hideyuki; Shofuda, Tomoko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki; Nakanishi, Katsuyuki; Kanemura, Yonehiro

2016-01-01

Reports have suggested that tumor textures presented on T2-weighted images correlate with the genetic status of glioma. Therefore, development of an image analyzing framework that is capable of objective and high throughput image texture analysis for large scale image data collection is needed. The current study aimed to address the development of such a framework by introducing two novel parameters for image textures on T2-weighted images, i.e., Shannon entropy and Prewitt filtering. Twenty-two WHO grade 2 and 28 grade 3 glioma patients were collected whose pre-surgical MRI and IDH1 mutation status were available. Heterogeneous lesions showed statistically higher Shannon entropy than homogenous lesions (p = 0.006) and ROC curve analysis proved that Shannon entropy on T2WI was a reliable indicator for discrimination of homogenous and heterogeneous lesions (p = 0.015, AUC = 0.73). Lesions with well-defined borders exhibited statistically higher Edge mean and Edge median values using Prewitt filtering than those with vague lesion borders (p = 0.0003 and p = 0.0005 respectively). ROC curve analysis also proved that both Edge mean and median values were promising indicators for discrimination of lesions with vague and well defined borders and both Edge mean and median values performed in a comparable manner (p = 0.0002, AUC = 0.81 and p < 0.0001, AUC = 0.83, respectively). Finally, IDH1 wild type gliomas showed statistically lower Shannon entropy on T2WI than IDH1 mutated gliomas (p = 0.007) but no difference was observed between IDH1 wild type and mutated gliomas in Edge median values using Prewitt filtering. The current study introduced two image metrics that reflect lesion texture described on T2WI. These two metrics were validated by readings of a neuro-radiologist who was blinded to the results. This observation will facilitate further use of this technique in future large scale image analysis of glioma.

IJ-OpenCV: Combining ImageJ and OpenCV for processing images in biomedicine.

PubMed

Domínguez, César; Heras, Jónathan; Pascual, Vico

2017-05-01

The effective processing of biomedical images usually requires the interoperability of diverse software tools that have different aims but are complementary. The goal of this work is to develop a bridge to connect two of those tools: ImageJ, a program for image analysis in life sciences, and OpenCV, a computer vision and machine learning library. Based on a thorough analysis of ImageJ and OpenCV, we detected the features of these systems that could be enhanced, and developed a library to combine both tools, taking advantage of the strengths of each system. The library was implemented on top of the SciJava converter framework. We also provide a methodology to use this library. We have developed the publicly available library IJ-OpenCV that can be employed to create applications combining features from both ImageJ and OpenCV. From the perspective of ImageJ developers, they can use IJ-OpenCV to easily create plugins that use any functionality provided by the OpenCV library and explore different alternatives. From the perspective of OpenCV developers, this library provides a link to the ImageJ graphical user interface and all its features to handle regions of interest. The IJ-OpenCV library bridges the gap between ImageJ and OpenCV, allowing the connection and the cooperation of these two systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization of propagation-based x-ray phase-contrast tomography for breast cancer imaging

NASA Astrophysics Data System (ADS)

Baran, P.; Pacile, S.; Nesterets, Y. I.; Mayo, S. C.; Dullin, C.; Dreossi, D.; Arfelli, F.; Thompson, D.; Lockie, D.; McCormack, M.; Taba, S. T.; Brun, F.; Pinamonti, M.; Nickson, C.; Hall, C.; Dimmock, M.; Zanconati, F.; Cholewa, M.; Quiney, H.; Brennan, P. C.; Tromba, G.; Gureyev, T. E.

2017-03-01

The aim of this study was to optimise the experimental protocol and data analysis for in-vivo breast cancer x-ray imaging. Results are presented of the experiment at the SYRMEP beamline of Elettra Synchrotron using the propagation-based phase-contrast mammographic tomography method, which incorporates not only absorption, but also x-ray phase information. In this study the images of breast tissue samples, of a size corresponding to a full human breast, with radiologically acceptable x-ray doses were obtained, and the degree of improvement of the image quality (from the diagnostic point of view) achievable using propagation-based phase-contrast image acquisition protocols with proper incorporation of x-ray phase retrieval into the reconstruction pipeline was investigated. Parameters such as the x-ray energy, sample-to-detector distance and data processing methods were tested, evaluated and optimized with respect to the estimated diagnostic value using a mastectomy sample with a malignant lesion. The results of quantitative evaluation of images were obtained by means of radiological assessment carried out by 13 experienced specialists. A comparative analysis was performed between the x-ray and the histological images of the specimen. The results of the analysis indicate that, within the investigated range of parameters, both the objective image quality characteristics and the subjective radiological scores of propagation-based phase-contrast images of breast tissues monotonically increase with the strength of phase contrast which in turn is directly proportional to the product of the radiation wavelength and the sample-to-detector distance. The outcomes of this study serve to define the practical imaging conditions and the CT reconstruction procedures appropriate for low-dose phase-contrast mammographic imaging of live patients at specially designed synchrotron beamlines.

Simultaneous Assessment of Myocardial Perfusion, Wall Motion, and Deformation during Myocardial Contrast Echocardiography: A Feasibility Study.

PubMed

Zoppellaro, Giacomo; Venneri, Lucia; Khattar, Rajdeep S; Li, Wei; Senior, Roxy

2016-06-01

Ultrasound contrast agents may be used for the assessment of regional wall motion and myocardial perfusion, but are generally considered not suitable for deformation analysis. The aim of our study was to assess the feasibility of deformation imaging on contrast-enhanced images using a novel methodology. We prospectively enrolled 40 patients who underwent stress echocardiography with continuous intravenous infusion of SonoVue for the assessment of myocardial perfusion imaging with flash replenishment technique. We compared longitudinal strain (Lε) values, assessed with a vendor-independent software (2D CPA), on 68 resting contrast-enhanced and 68 resting noncontrast recordings. Strain analysis on contrast recordings was evaluated in the first cardiac cycles after the flash. Tracking of contrast images was deemed feasible in all subjects and in all views. Contrast administration improved image quality and increased the number of segments used for deformation analysis. Lε of noncontrast and contrast-enhanced images were statistically different (-18.8 ± 4.5% and -22.8 ± 5.4%, respectively; P < 0.001), but their correlation was good (ICC 0.65, 95%CI 0.42-0.78). Patients with resting wall-motion abnormalities showed lower Lε values on contrast recordings (-18.6 ± 6.0% vs. -24.2 ± 5.5%, respectively; P < 0.01). Intra-operator and inter-operator reproducibility was good for both noncontrast and contrast images with no statistical differences. Our study shows that deformation analysis on postflash contrast-enhanced images is feasible and reproducible. Therefore, it would be possible to perform a simultaneous evaluation of wall-motion abnormalities, volumes, ejection fraction, perfusion defects, and cardiac deformation on the same contrast recording. © 2016, Wiley Periodicals, Inc.

Evaluation of photoshop based image analysis in cytologic diagnosis of pleural fluid in comparison with conventional modalities.

PubMed

Jafarian, Amir Hossein; Tasbandi, Aida; Mohamadian Roshan, Nema

2018-04-19

The aim of this study is to investigate and compare the results of digital image analysis in pleural effusion cytology samples with conventional modalities. In this cross-sectional study, 53 pleural fluid cytology smears from Qaem hospital pathology department, located in Mashhad, Iran were investigated. Prior to digital analysis, all specimens were evaluated by two pathologists and categorized into three groups as: benign, suspicious, and malignant. Using an Olympus microscope and Olympus DP3 digital camera, digital images from cytology slides were captured. Appropriate images (n = 130) were separately imported to Adobe Photoshop CS5 and parameters including area and perimeter, circularity, Gray Value mean, integrated density, and nucleus to cytoplasm area ratio were analyzed. Gray Value mean, nucleus to cytoplasm area ratio, and circularity showed the best sensitivity and specificity rates as well as significant differences between all groups. Also, nucleus area and perimeter showed a significant relation between suspicious and malignant groups with benign group. Whereas, there was no such difference between suspicious and malignant groups. We concluded that digital image analysis is welcomed in the field of research on pleural fluid smears as it can provide quantitative data to apply various comparisons and reduce interobserver variation which could assist pathologists to achieve a more accurate diagnosis. © 2018 Wiley Periodicals, Inc.

Analysis of full disc Ca II K spectroheliograms. I. Photometric calibration and centre-to-limb variation compensation

NASA Astrophysics Data System (ADS)

Chatzistergos, Theodosios; Ermolli, Ilaria; Solanki, Sami K.; Krivova, Natalie A.

2018-01-01

Context. Historical Ca II K spectroheliograms (SHG) are unique in representing long-term variations of the solar chromospheric magnetic field. They usually suffer from numerous problems and lack photometric calibration. Thus accurate processing of these data is required to get meaningful results from their analysis. Aims: In this paper we aim at developing an automatic processing and photometric calibration method that provides precise and consistent results when applied to historical SHG. Methods: The proposed method is based on the assumption that the centre-to-limb variation of the intensity in quiet Sun regions does not vary with time. We tested the accuracy of the proposed method on various sets of synthetic images that mimic problems encountered in historical observations. We also tested our approach on a large sample of images randomly extracted from seven different SHG archives. Results: The tests carried out on the synthetic data show that the maximum relative errors of the method are generally <6.5%, while the average error is <1%, even if rather poor quality observations are considered. In the absence of strong artefacts the method returns images that differ from the ideal ones by <2% in any pixel. The method gives consistent values for both plage and network areas. We also show that our method returns consistent results for images from different SHG archives. Conclusions: Our tests show that the proposed method is more accurate than other methods presented in the literature. Our method can also be applied to process images from photographic archives of solar observations at other wavelengths than Ca II K.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis.

PubMed

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-08-08

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis

PubMed Central

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-01-01

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases. PMID:28786947

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.

Is 'virtual histology' the next step after the 'virtual autopsy'? Magnetic resonance microscopy in forensic medicine.

PubMed

Thali, M J; Dirnhofer, R; Becker, R; Oliver, W; Potter, K

2004-10-01

The study aimed to validate magnetic resonance microscopy (MRM) studies of forensic tissue specimens (skin samples with electric injury patterns) against the results from routine histology. Computed tomography and magnetic resonance imaging are fast becoming important tools in clinical and forensic pathology. This study is the first forensic application of MRM to the analysis of electric injury patterns in human skin. Three-dimensional high-resolution MRM images of fixed skin specimens provided a complete 3D view of the damaged tissues at the site of an electric injury as well as in neighboring tissues, consistent with histologic findings. The image intensity of the dermal layer in T2-weighted MRM images was reduced in the central zone due to carbonization or coagulation necrosis and increased in the intermediate zone because of dermal edema. A subjacent blood vessel with an intravascular occlusion supports the hypothesis that current traveled through the vascular system before arcing to ground. High-resolution imaging offers a noninvasive alternative to conventional histology in forensic wound analysis and can be used to perform 3D virtual histology.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

PubMed Central

Belgiu, Mariana; Drǎguţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules. PMID:24623959

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Belgiu, Mariana; ǎguţ, Lucian, , Dr; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Microtomography evaluation of dental tissue wear surface induced by in vitro simulated chewing cycles on human and composite teeth.

PubMed

Bedini, Rossella; Pecci, Raffaella; Notarangelo, Gianluca; Zuppante, Francesca; Persico, Salvatore; Di Carlo, Fabio

2012-01-01

In this study a 3D microtomography display of tooth surfaces after in vitro dental wear tests has been obtained. Natural teeth have been compared with prosthetic teeth, manufactured by three different polyceramic composite materials. The prosthetic dental element samples, similar to molars, have been placed in opposition to human teeth extracted by paradontology diseases. After microtomography analysis, samples have been subjected to in vitro fatigue test cycles by servo-hydraulic mechanical testing machine. After the fatigue test, each sample has been subjected again to microtomography analysis to obtain volumetric value changes and dental wear surface images. Wear surface images were obtained by 3D reconstruction software and volumetric value changes were measured by CT analyser software. The aim of this work has been to show the potential of microtomography technique to display very clear and reliable wear surface images. Microtomography analysis methods to evaluate volumetric value changes have been used to quantify dental tissue and composite material wear.

Imaging Practice Patterns: Referral Network Analysis of a Single State of Origination.

PubMed

Grayson, James; Basciano, Peter; Rawson, James V; Klein, Kandace

2015-12-01

The aim of this study was to examine the referral pattern of imaging studies requested in a single state compared with the potential location of interpretation. Analysis of Medicare patients in a DocGraph data set was performed to identify sequential different physician services claims for the same patient for which the second claim was for services provided by a radiologist. In the 2011 Medicare population, radiology referrals from physicians practicing in Georgia resulted in 76.5% of radiology interpretations by radiologists inside the state of Georgia. The states bordering Georgia accounted for 11.6% of interpretations in the Georgia market. The remaining interpretations were distributed throughout the remainder of the country. A significant proportion of routine imaging interpretation occurs outside the state in which an examination is performed. Additional studies are needed to identify complex drivers of imaging referral patterns, such as patient geographic location and demographics, radiologist workforce distribution, contractual obligations, and social relationships. Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Adipose Tissue Quantification by Imaging Methods: A Proposed Classification

PubMed Central

Shen, Wei; Wang, ZiMian; Punyanita, Mark; Lei, Jianbo; Sinav, Ahmet; Kral, John G.; Imielinska, Celina; Ross, Robert; Heymsfield, Steven B.

2007-01-01

Recent advances in imaging techniques and understanding of differences in the molecular biology of adipose tissue has rendered classical anatomy obsolete, requiring a new classification of the topography of adipose tissue. Adipose tissue is one of the largest body compartments, yet a classification that defines specific adipose tissue depots based on their anatomic location and related functions is lacking. The absence of an accepted taxonomy poses problems for investigators studying adipose tissue topography and its functional correlates. The aim of this review was to critically examine the literature on imaging of whole body and regional adipose tissue and to create the first systematic classification of adipose tissue topography. Adipose tissue terminology was examined in over 100 original publications. Our analysis revealed inconsistencies in the use of specific definitions, especially for the compartment termed “visceral” adipose tissue. This analysis leads us to propose an updated classification of total body and regional adipose tissue, providing a well-defined basis for correlating imaging studies of specific adipose tissue depots with molecular processes. PMID:12529479

Infrared spectroscopy and spectroscopic imaging in forensic science.

PubMed

Ewing, Andrew V; Kazarian, Sergei G

2017-01-16

Infrared spectroscopy and spectroscopic imaging, are robust, label free and inherently non-destructive methods with a high chemical specificity and sensitivity that are frequently employed in forensic science research and practices. This review aims to discuss the applications and recent developments of these methodologies in this field. Furthermore, the use of recently emerged Fourier transform infrared (FT-IR) spectroscopic imaging in transmission, external reflection and Attenuated Total Reflection (ATR) modes are summarised with relevance and potential for forensic science applications. This spectroscopic imaging approach provides the opportunity to obtain the chemical composition of fingermarks and information about possible contaminants deposited at a crime scene. Research that demonstrates the great potential of these techniques for analysis of fingerprint residues, explosive materials and counterfeit drugs will be reviewed. The implications of this research for the examination of different materials are considered, along with an outlook of possible future research avenues for the application of vibrational spectroscopic methods to the analysis of forensic samples.

Post Hoc Analysis of Passive Cavitation Imaging for Classification of Histotripsy-Induced Liquefaction in Vitro.

PubMed

Bader, Kenneth B; Haworth, Kevin J; Maxwell, Adam D; Holland, Christy K

2018-01-01

Histotripsy utilizes focused ultrasound to generate bubble clouds for transcutaneous tissue liquefaction. Bubble activity maps are under development to provide image guidance and monitor treatment progress. The aim of this paper was to investigate the feasibility of using plane wave B-mode and passive cavitation images to be used as binary classifiers of histotripsy-induced liquefaction. Prostate tissue phantoms were exposed to histotripsy pulses over a range of pulse durations (5- ) and peak negative pressures (12-23 MPa). Acoustic emissions were recorded during the insonation and beamformed to form passive cavitation images. Plane wave B-mode images were acquired following the insonation to detect the hyperechoic bubble cloud. Phantom samples were sectioned and stained to delineate the liquefaction zone. Correlation between passive cavitation and plane wave B-mode images and the liquefaction zone was assessed using receiver operating characteristic (ROC) curve analysis. Liquefaction of the phantom was observed for all the insonation conditions. The area under the ROC (0.94 versus 0.82), accuracy (0.90 versus 0.83), and sensitivity (0.81 versus 0.49) was greater for passive cavitation images relative to B-mode images ( ) along the azimuth of the liquefaction zone. The specificity was greater than 0.9 for both imaging modalities. These results demonstrate a stronger correlation between histotripsy-induced liquefaction and passive cavitation imaging compared with the plane wave B-mode imaging, albeit with limited passive cavitation image range resolution.

Using the Image Analysis Method for Describing Soil Detachment by a Single Water Drop Impact

PubMed Central

Ryżak, Magdalena; Bieganowski, Andrzej

2012-01-01

The aim of the present work was to develop a method based on image analysis for describing soil detachment caused by the impact of a single water drop. The method consisted of recording tracks made by splashed particles on blotting paper under an optical microscope. The analysis facilitated division of the recorded particle tracks on the paper into drops, “comets” and single particles. Additionally, the following relationships were determined: (i) the distances of splash; (ii) the surface areas of splash tracks into relation to distance; (iii) the surface areas of the solid phase transported over a given distance; and (iv) the ratio of the solid phase to the splash track area in relation to distance. Furthermore, the proposed method allowed estimation of the weight of soil transported by a single water drop splash in relation to the distance of the water drop impact. It was concluded that the method of image analysis of splashed particles facilitated analysing the results at very low water drop energy and generated by single water drops.

GEOBIA For Land Use Mapping Using Worldview2 Image In Bengkak Village Coastal, Banyuwangi Regency, East Java

NASA Astrophysics Data System (ADS)

Alrassi, Fitzastri; Salim, Emil; Nina, Anastasia; Alwi, Luthfi; Danoedoro, Projo; Kamal, Muhammad

2016-11-01

The east coast of Banyuwangi regency has a diverse variety of land use such as ponds, mangroves, agricultural fields and settlements. WorldView-2 is a multispectral image with high spatial resolution that can display detailed information of land use. Geographic Object Based Image Analysis (GEOBIA) classification technique uses object segments as the smallest unit of analysis. The segmentation and classification process is not only based on spectral value of the image but also considering other elements of the image interpretation. This gives GEOBIA an opportunities and challenges in the mapping and monitoring of land use. This research aims to assess the GEOBIA classification method for generating the classification of land use in coastal areas of Banyuwangi. The result of this study is land use classification map produced by GEOBIA classification. We verified the accuracy of the resulted land use map by comparing the map with result from visual interpretation of the image that have been validated through field surveys. Variation of land use in most of the east coast of Banyuwangi regency is dominated by mangrove, agricultural fields, mixed farms, settlements and ponds.

The robot's eyes - Stereo vision system for automated scene analysis

NASA Technical Reports Server (NTRS)

Williams, D. S.

1977-01-01

Attention is given to the robot stereo vision system which maintains the image produced by solid-state detector television cameras in a dynamic random access memory called RAPID. The imaging hardware consists of sensors (two solid-state image arrays using a charge injection technique), a video-rate analog-to-digital converter, the RAPID memory, and various types of computer-controlled displays, and preprocessing equipment (for reflexive actions, processing aids, and object detection). The software is aimed at locating objects and transversibility. An object-tracking algorithm is discussed and it is noted that tracking speed is in the 50-75 pixels/s range.

Accuracy of fluorodeoxyglucose-PET imaging for differentiating benign from malignant pleural effusions: a meta-analysis.

PubMed

Porcel, José M; Hernández, Paula; Martínez-Alonso, Montserrat; Bielsa, Silvia; Salud, Antonieta

2015-02-01

The role of fluorodeoxyglucose (FDG)-PET imaging for diagnosing malignant pleural effusions is not well defined. The aim of this study was to summarize the evidence for its use in ruling in or out the malignant origin of a pleural effusion or thickening. A meta-analysis was conducted of diagnostic accuracy studies published in the Cochrane Library, PubMed, and Embase (inception to June 2013) without language restrictions. Two investigators selected studies that had evaluated the performance of FDG-PET imaging in patients with pleural effusions or thickening, using pleural cytopathology or histopathology as the reference standard for malignancy. Subgroup analyses were conducted according to FDG-PET imaging interpretation (qualitative or semiquantitative), PET imaging equipment (PET vs integrated PET-CT imaging), and/or target population (known lung cancer or malignant pleural mesothelioma). Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. We used a bivariate random-effects model for the analysis and pooling of diagnostic performance measures across studies. Fourteen non-high risk of bias studies, comprising 407 patients with malignant and 232 with benign pleural conditions, met the inclusion criteria. Semiquantitative PET imaging readings had a significantly lower sensitivity for diagnosing malignant effusions than visual assessments (82% vs 91%; P = .026). The pooled test characteristics of integrated PET-CT imaging systems using semiquantitative interpretations for identifying malignant effusions were: sensitivity, 81%; specificity, 74%; positive likelihood ratio (LR), 3.22; negative LR, 0.26; and area under the curve, 0.838. Resultant data were heterogeneous, and spectrum bias should be considered when appraising FDG-PET imaging operating characteristics. The moderate accuracy of PET-CT imaging using semiquantitative readings precludes its routine recommendation for discriminating malignant from benign pleural effusions.

A voxel based comparative analysis using magnetization transfer imaging and T1-weighted magnetic resonance imaging in progressive supranuclear palsy

PubMed Central

Sandhya, Mangalore; Saini, Jitender; Pasha, Shaik Afsar; Yadav, Ravi; Pal, Pramod Kumar

2014-01-01

Aims: In progressive supranuclear palsy (PSP) tissue damage occurs in specific cortical and subcortical regions. Voxel based analysis using T1-weighted images depict quantitative gray matter (GM) atrophy changes. Magnetization transfer (MT) imaging depicts qualitative changes in the brain parenchyma. The purpose of our study was to investigate whether MT imaging could indicate abnormalities in PSP. Settings and Design: A total of 10 patients with PSP (9 men and 1 woman) and 8 controls (5 men and 3 women) were studied with T1-weighted magnetic resonance imaging (MRI) and 3DMT imaging. Voxel based analysis of T1-weighted MRI was performed to investigate brain atrophy while MT was used to study qualitative abnormalities in the brain tissue. We used SPM8 to investigate group differences (with two sample t-test) using the GM and white matter (WM) segmented data. Results: T1-weighted imaging and MT are equally sensitive to detect changes in GM and WM in PSP. Magnetization transfer ratio images and magnetization-prepared rapid acquisition of gradient echo revealed extensive bilateral volume and qualitative changes in the orbitofrontal, prefrontal cortex and limbic lobe and sub cortical GM. The prefrontal structures involved were the rectal gyrus, medial, inferior frontal gyrus (IFG) and middle frontal gyrus (MFG). The anterior cingulate, cingulate gyrus and lingual gyrus of limbic lobe and subcortical structures such as caudate, thalamus, insula and claustrum were also involved. Cerebellar involvement mainly of anterior lobe was also noted. Conclusions: The findings suggest that voxel based MT imaging permits a whole brain unbiased investigation of central nervous system structural integrity in PSP. PMID:25024571

Hemorrhage detection in MRI brain images using images features

NASA Astrophysics Data System (ADS)

Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

2013-11-01

The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

An Exploratory Study of Residents' Perception of Place Image: The Case of Kavala.

PubMed

Stylidis, Dimitrios; Sit, Jason; Biran, Avital

2016-05-01

Studies on place image have predominantly focused on the tourists' destination image and have given limited attention to other stakeholders' perspectives. This study aims to address this gap by focusing on the notion of residents' place image, whereby it reviews existing literature on residents' place image in terms of whether common attributes can be identified, and examines the role of community-focused attributes in its measurement. Data collected from a sample of 481 Kavala residents (Greece) were subjected to exploratory and confirmatory factor analysis. The study reveals that the existing measurement tools have typically emphasized destination-focused attributes and neglected community-focused attributes. This study contributes to the residents' place image research by proposing a more holistic measurement, which consisted of four dimensions: physical appearance, community services, social environment, and entertainment opportunities. The study also offers practical insights for developing and promoting a tourist place while simultaneously enhancing its residents' quality of life.

Application of LANDSAT data to the study of urban development in Brasilia

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Deoliveira, M. D. L. N.; Foresti, C.; Niero, M.; Parreira, E. M. D. M. F.

1984-01-01

The urban growth of Brasilia within the last ten years is analyzed with special emphasis on the utilization of remote sensing orbital data and automatic image processing. The urban spatial structure and the monitoring of its temporal changes were examined in a whole and dynamic way by the utilization of MSS-LANDSAT images for June (1973, 1978 and 1983). In order to aid data interpretation, a registration algorithm implemented in the Interactive Multispectral Image Analysis System (IMAGE-100) was utilized aiming at the overlap of multitemporal images. The utilization of suitable digital filters, combined with the images overlap, allowed a rapid identification of areas of possible urban growth and oriented the field work. The results obtained in this work permitted an evaluation of the urban growth of Brasilia, taking as reference the proposal stated for the construction of the city in the Pilot Plan elaborated by Lucio Costa.

Eyeing the Sky's Water Vapor

NASA Technical Reports Server (NTRS)

2008-01-01

This image, and many like it, are one way NASA's Phoenix Mars Lander is measuring trace amounts of water vapor in the atmosphere over far-northern Mars. Phoenix's Surface Stereo Imager (SSI) uses solar filters, or filters designed to image the sun, to make these images. The camera is aimed at the sky for long exposures.

SSI took this image as a test on June 9, 2008, which was the Phoenix mission's 15th Martian day, or sol, since landing, at 5:20 p.m. local solar time. The camera was pointed about 38 degrees above the horizon. The white dots in the sky are detector dark current that will be removed during image processing and analysis.

The Phoenix Mission is led by the University of Arizona, Tucson, on behalf of NASA. Project management of the mission is by NASA's Jet Propulsion Laboratory, Pasadena, Calif. Spacecraft development is by Lockheed Martin Space

An Exploratory Study of Residents’ Perception of Place Image

PubMed Central

Stylidis, Dimitrios; Sit, Jason; Biran, Avital

2014-01-01

Studies on place image have predominantly focused on the tourists’ destination image and have given limited attention to other stakeholders’ perspectives. This study aims to address this gap by focusing on the notion of residents’ place image, whereby it reviews existing literature on residents’ place image in terms of whether common attributes can be identified, and examines the role of community-focused attributes in its measurement. Data collected from a sample of 481 Kavala residents (Greece) were subjected to exploratory and confirmatory factor analysis. The study reveals that the existing measurement tools have typically emphasized destination-focused attributes and neglected community-focused attributes. This study contributes to the residents’ place image research by proposing a more holistic measurement, which consisted of four dimensions: physical appearance, community services, social environment, and entertainment opportunities. The study also offers practical insights for developing and promoting a tourist place while simultaneously enhancing its residents’ quality of life. PMID:29708109

Principal Component Analysis in the Spectral Analysis of the Dynamic Laser Speckle Patterns

NASA Astrophysics Data System (ADS)

Ribeiro, K. M.; Braga, R. A., Jr.; Horgan, G. W.; Ferreira, D. D.; Safadi, T.

2014-02-01

Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle. Usually, these patterns of optical interference evolving in time are analyzed by graphical or numerical methods, and the analysis in frequency domain has also been an option, however involving large computational requirements which demands new approaches to filter the images in time. Principal component analysis (PCA) works with the statistical decorrelation of data and it can be used as a data filtering. In this context, the present work evaluated the PCA technique to filter in time the data from the biospeckle images aiming the reduction of time computer consuming and improving the robustness of the filtering. It was used 64 images of biospeckle in time observed in a maize seed. The images were arranged in a data matrix and statistically uncorrelated by PCA technique, and the reconstructed signals were analyzed using the routine graphical and numerical methods to analyze the biospeckle. Results showed the potential of the PCA tool in filtering the dynamic laser speckle data, with the definition of markers of principal components related to the biological phenomena and with the advantage of fast computational processing.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images.

PubMed

Mraity, Hussien A A B; England, Andrew; Cassidy, Simon; Eachus, Peter; Dominguez, Alejandro; Hogg, Peter

2016-01-01

The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images

PubMed Central

England, Andrew; Cassidy, Simon; Eachus, Peter; Dominguez, Alejandro; Hogg, Peter

2016-01-01

Objective: The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. Methods: Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. Results: A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). Conclusion: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. Advances in knowledge: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality. PMID:26943836

Generalized Scalar-on-Image Regression Models via Total Variation.

PubMed

Wang, Xiao; Zhu, Hongtu

2017-01-01

The use of imaging markers to predict clinical outcomes can have a great impact in public health. The aim of this paper is to develop a class of generalized scalar-on-image regression models via total variation (GSIRM-TV), in the sense of generalized linear models, for scalar response and imaging predictor with the presence of scalar covariates. A key novelty of GSIRM-TV is that it is assumed that the slope function (or image) of GSIRM-TV belongs to the space of bounded total variation in order to explicitly account for the piecewise smooth nature of most imaging data. We develop an efficient penalized total variation optimization to estimate the unknown slope function and other parameters. We also establish nonasymptotic error bounds on the excess risk. These bounds are explicitly specified in terms of sample size, image size, and image smoothness. Our simulations demonstrate a superior performance of GSIRM-TV against many existing approaches. We apply GSIRM-TV to the analysis of hippocampus data obtained from the Alzheimers Disease Neuroimaging Initiative (ADNI) dataset.

The diagnostic value of narrow-band imaging for early and invasive lung cancer: a meta-analysis.

PubMed

Zhu, Juanjuan; Li, Wei; Zhou, Jihong; Chen, Yuqing; Zhao, Chenling; Zhang, Ting; Peng, Wenjia; Wang, Xiaojing

2017-07-01

This study aimed to compare the ability of narrow-band imaging to detect early and invasive lung cancer with that of conventional pathological analysis and white-light bronchoscopy. We searched the PubMed, EMBASE, Sinomed, and China National Knowledge Infrastructure databases for relevant studies. Meta-disc software was used to perform data analysis, meta-regression analysis, sensitivity analysis, and heterogeneity testing, and STATA software was used to determine if publication bias was present, as well as to calculate the relative risks for the sensitivity and specificity of narrow-band imaging vs those of white-light bronchoscopy for the detection of early and invasive lung cancer. A random-effects model was used to assess the diagnostic efficacy of the above modalities in cases in which a high degree of between-study heterogeneity was noted with respect to their diagnostic efficacies. The database search identified six studies including 578 patients. The pooled sensitivity and specificity of narrow-band imaging were 86% (95% confidence interval: 83-88%) and 81% (95% confidence interval: 77-84%), respectively, and the pooled sensitivity and specificity of white-light bronchoscopy were 70% (95% confidence interval: 66-74%) and 66% (95% confidence interval: 62-70%), respectively. The pooled relative risks for the sensitivity and specificity of narrow-band imaging vs the sensitivity and specificity of white-light bronchoscopy for the detection of early and invasive lung cancer were 1.33 (95% confidence interval: 1.07-1.67) and 1.09 (95% confidence interval: 0.84-1.42), respectively, and sensitivity analysis showed that narrow-band imaging exhibited good diagnostic efficacy with respect to detecting early and invasive lung cancer and that the results of the study were stable. Narrow-band imaging was superior to white light bronchoscopy with respect to detecting early and invasive lung cancer; however, the specificities of the two modalities did not differ significantly.

Comparison of Cornea Module and DermaInspect for noninvasive imaging of ocular surface pathologies

NASA Astrophysics Data System (ADS)

Steven, Philipp; Müller, Maya; Koop, Norbert; Rose, Christian; Hüttmann, Gereon

2009-11-01

Minimally invasive imaging of ocular surface pathologies aims at securing clinical diagnosis without actual tissue probing. For this matter, confocal microscopy (Cornea Module) is in daily use in ophthalmic practice. Multiphoton microscopy is a new optical technique that enables high-resolution imaging and functional analysis of living tissues based on tissue autofluorescence. This study was set up to compare the potential of a multiphoton microscope (DermaInspect) to the Cornea Module. Ocular surface pathologies such as pterygia, papillomae, and nevi were investigated in vivo using the Cornea Module and imaged immediately after excision by DermaInspect. Two excitation wavelengths, fluorescence lifetime imaging and second-harmonic generation (SHG), were used to discriminate different tissue structures. Images were compared with the histopathological assessment of the samples. At wavelengths of 730 nm, multiphoton microscopy exclusively revealed cellular structures. Collagen fibrils were specifically demonstrated by second-harmonic generation. Measurements of fluorescent lifetimes enabled the highly specific detection of goblet cells, erythrocytes, and nevus-cell clusters. At the settings used, DermaInspect reaches higher resolutions than the Cornea Module and obtains additional structural information. The parallel detection of multiphoton excited autofluorescence and confocal imaging could expand the possibilities of minimally invasive investigation of the ocular surface toward functional analysis at higher resolutions.

Influence of long-range Coulomb interaction in velocity map imaging.

PubMed

Barillot, T; Brédy, R; Celep, G; Cohen, S; Compagnon, I; Concina, B; Constant, E; Danakas, S; Kalaitzis, P; Karras, G; Lépine, F; Loriot, V; Marciniak, A; Predelus-Renois, G; Schindler, B; Bordas, C

2017-07-07

The standard velocity-map imaging (VMI) analysis relies on the simple approximation that the residual Coulomb field experienced by the photoelectron ejected from a neutral or ion system may be neglected. Under this almost universal approximation, the photoelectrons follow ballistic (parabolic) trajectories in the externally applied electric field, and the recorded image may be considered as a 2D projection of the initial photoelectron velocity distribution. There are, however, several circumstances where this approximation is not justified and the influence of long-range forces must absolutely be taken into account for the interpretation and analysis of the recorded images. The aim of this paper is to illustrate this influence by discussing two different situations involving isolated atoms or molecules where the analysis of experimental images cannot be performed without considering long-range Coulomb interactions. The first situation occurs when slow (meV) photoelectrons are photoionized from a neutral system and strongly interact with the attractive Coulomb potential of the residual ion. The result of this interaction is the formation of a more complex structure in the image, as well as the appearance of an intense glory at the center of the image. The second situation, observed also at low energy, occurs in the photodetachment from a multiply charged anion and it is characterized by the presence of a long-range repulsive potential. Then, while the standard VMI approximation is still valid, the very specific features exhibited by the recorded images can be explained only by taking into consideration tunnel detachment through the repulsive Coulomb barrier.

Morphological image analysis for classification of gastrointestinal tissues using optical coherence tomography

NASA Astrophysics Data System (ADS)

Garcia-Allende, P. Beatriz; Amygdalos, Iakovos; Dhanapala, Hiruni; Goldin, Robert D.; Hanna, George B.; Elson, Daniel S.

2012-01-01

Computer-aided diagnosis of ophthalmic diseases using optical coherence tomography (OCT) relies on the extraction of thickness and size measures from the OCT images, but such defined layers are usually not observed in emerging OCT applications aimed at "optical biopsy" such as pulmonology or gastroenterology. Mathematical methods such as Principal Component Analysis (PCA) or textural analyses including both spatial textural analysis derived from the two-dimensional discrete Fourier transform (DFT) and statistical texture analysis obtained independently from center-symmetric auto-correlation (CSAC) and spatial grey-level dependency matrices (SGLDM), as well as, quantitative measurements of the attenuation coefficient have been previously proposed to overcome this problem. We recently proposed an alternative approach consisting of a region segmentation according to the intensity variation along the vertical axis and a pure statistical technology for feature quantification. OCT images were first segmented in the axial direction in an automated manner according to intensity. Afterwards, a morphological analysis of the segmented OCT images was employed for quantifying the features that served for tissue classification. In this study, a PCA processing of the extracted features is accomplished to combine their discriminative power in a lower number of dimensions. Ready discrimination of gastrointestinal surgical specimens is attained demonstrating that the approach further surpasses the algorithms previously reported and is feasible for tissue classification in the clinical setting.

Bio-metals imaging and speciation in cells using proton and synchrotron radiation X-ray microspectroscopy

PubMed Central

Ortega, Richard; Devès, Guillaume; Carmona, Asunción

2009-01-01

The direct detection of biologically relevant metals in single cells and of their speciation is a challenging task that requires sophisticated analytical developments. The aim of this article is to present the recent achievements in the field of cellular chemical element imaging, and direct speciation analysis, using proton and synchrotron radiation X-ray micro- and nano-analysis. The recent improvements in focusing optics for MeV-accelerated particles and keV X-rays allow application to chemical element analysis in subcellular compartments. The imaging and quantification of trace elements in single cells can be obtained using particle-induced X-ray emission (PIXE). The combination of PIXE with backscattering spectrometry and scanning transmission ion microscopy provides a high accuracy in elemental quantification of cellular organelles. On the other hand, synchrotron radiation X-ray fluorescence provides chemical element imaging with less than 100 nm spatial resolution. Moreover, synchrotron radiation offers the unique capability of spatially resolved chemical speciation using micro-X-ray absorption spectroscopy. The potential of these methods in biomedical investigations will be illustrated with examples of application in the fields of cellular toxicology, and pharmacology, bio-metals and metal-based nano-particles. PMID:19605403

Marginal Fisher analysis and its variants for human gait recognition and content- based image retrieval.

PubMed

Xu, Dong; Yan, Shuicheng; Tao, Dacheng; Lin, Stephen; Zhang, Hong-Jiang

2007-11-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for human gait recognition and content-based image retrieval (CBIR). In this paper, we present extensions of our recently proposed marginal Fisher analysis (MFA) to address these problems. For human gait recognition, we first present a direct application of MFA, then inspired by recent advances in matrix and tensor-based dimensionality reduction algorithms, we present matrix-based MFA for directly handling 2-D input in the form of gray-level averaged images. For CBIR, we deal with the relevance feedback problem by extending MFA to marginal biased analysis, in which within-class compactness is characterized only by the distances between each positive sample and its neighboring positive samples. In addition, we present a new technique to acquire a direct optimal solution for MFA without resorting to objective function modification as done in many previous algorithms. We conduct comprehensive experiments on the USF HumanID gait database and the Corel image retrieval database. Experimental results demonstrate that MFA and its extensions outperform related algorithms in both applications.

Age estimation using exfoliative cytology and radiovisiography: A comparative study

PubMed Central

Nallamala, Shilpa; Guttikonda, Venkateswara Rao; Manchikatla, Praveen Kumar; Taneeru, Sravya

2017-01-01

Introduction: Age estimation is one of the essential factors in establishing the identity of an individual. Among various methods, exfoliative cytology (EC) is a unique, noninvasive technique, involving simple, and pain-free collection of intact cells from the oral cavity for microscopic examination. Objective: The study was undertaken with an aim to estimate the age of an individual from the average cell size of their buccal smears calculated using image analysis morphometric software and the pulp–tooth area ratio in mandibular canine of the same individual using radiovisiography (RVG). Materials and Methods: Buccal smears were collected from 100 apparently healthy individuals. After fixation in 95% alcohol, the smears were stained using Papanicolaou stain. The average cell size was measured using image analysis software (Image-Pro Insight 8.0). The RVG images of mandibular canines were obtained, pulp and tooth areas were traced using AutoCAD 2010 software, and area ratio was calculated. The estimated age was then calculated using regression analysis. Results: The paired t-test between chronological age and estimated age by cell size and pulp–tooth area ratio was statistically nonsignificant (P > 0.05). Conclusion: In the present study, age estimated by pulp–tooth area ratio and EC yielded good results. PMID:29657491

Age estimation using exfoliative cytology and radiovisiography: A comparative study.

PubMed

Nallamala, Shilpa; Guttikonda, Venkateswara Rao; Manchikatla, Praveen Kumar; Taneeru, Sravya

2017-01-01

Age estimation is one of the essential factors in establishing the identity of an individual. Among various methods, exfoliative cytology (EC) is a unique, noninvasive technique, involving simple, and pain-free collection of intact cells from the oral cavity for microscopic examination. The study was undertaken with an aim to estimate the age of an individual from the average cell size of their buccal smears calculated using image analysis morphometric software and the pulp-tooth area ratio in mandibular canine of the same individual using radiovisiography (RVG). Buccal smears were collected from 100 apparently healthy individuals. After fixation in 95% alcohol, the smears were stained using Papanicolaou stain. The average cell size was measured using image analysis software (Image-Pro Insight 8.0). The RVG images of mandibular canines were obtained, pulp and tooth areas were traced using AutoCAD 2010 software, and area ratio was calculated. The estimated age was then calculated using regression analysis. The paired t -test between chronological age and estimated age by cell size and pulp-tooth area ratio was statistically nonsignificant ( P > 0.05). In the present study, age estimated by pulp-tooth area ratio and EC yielded good results.

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

A New Dusts Sensor for Cultural Heritage Applications Based on Image Processing

PubMed Central

Proietti, Andrea; Leccese, Fabio; Caciotta, Maurizio; Morresi, Fabio; Santamaria, Ulderico; Malomo, Carmela

2014-01-01

In this paper, we propose a new sensor for the detection and analysis of dusts (seen as powders and fibers) in indoor environments, especially designed for applications in the field of Cultural Heritage or in other contexts where the presence of dust requires special care (surgery, clean rooms, etc.). The presented system relies on image processing techniques (enhancement, noise reduction, segmentation, metrics analysis) and it allows obtaining both qualitative and quantitative information on the accumulation of dust. This information aims to identify the geometric and topological features of the elements of the deposit. The curators can use this information in order to design suitable prevention and maintenance actions for objects and environments. The sensor consists of simple and relatively cheap tools, based on a high-resolution image acquisition system, a preprocessing software to improve the captured image and an analysis algorithm for the feature extraction and the classification of the elements of the dust deposit. We carried out some tests in order to validate the system operation. These tests were performed within the Sistine Chapel in the Vatican Museums, showing the good performance of the proposed sensor in terms of execution time and classification accuracy. PMID:24901977

Quantitative image analysis for evaluating the coating thickness and pore distribution in coated small particles.

PubMed

Laksmana, F L; Van Vliet, L J; Hartman Kok, P J A; Vromans, H; Frijlink, H W; Van der Voort Maarschalk, K

2009-04-01

This study aims to develop a characterization method for coating structure based on image analysis, which is particularly promising for the rational design of coated particles in the pharmaceutical industry. The method applies the MATLAB image processing toolbox to images of coated particles taken with Confocal Laser Scanning Microscopy (CSLM). The coating thicknesses have been determined along the particle perimeter, from which a statistical analysis could be performed to obtain relevant thickness properties, e.g. the minimum coating thickness and the span of the thickness distribution. The characterization of the pore structure involved a proper segmentation of pores from the coating and a granulometry operation. The presented method facilitates the quantification of porosity, thickness and pore size distribution of a coating. These parameters are considered the important coating properties, which are critical to coating functionality. Additionally, the effect of the coating process variations on coating quality can straight-forwardly be assessed. Enabling a good characterization of the coating qualities, the presented method can be used as a fast and effective tool to predict coating functionality. This approach also enables the influence of different process conditions on coating properties to be effectively monitored, which latterly leads to process tailoring.

Detection of explosives on the surface of banknotes by Raman hyperspectral imaging and independent component analysis.

PubMed

Almeida, Mariana R; Correa, Deleon N; Zacca, Jorge J; Logrado, Lucio Paulo Lima; Poppi, Ronei J

2015-02-20

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50 μg cm(-2). Copyright © 2014 Elsevier B.V. All rights reserved.

In Silico Neuro-Oncology: Brownian Motion-Based Mathematical Treatment as a Potential Platform for Modeling the Infiltration of Glioma Cells into Normal Brain Tissue.

PubMed

Antonopoulos, Markos; Stamatakos, Georgios

2015-01-01

Intensive glioma tumor infiltration into the surrounding normal brain tissues is one of the most critical causes of glioma treatment failure. To quantitatively understand and mathematically simulate this phenomenon, several diffusion-based mathematical models have appeared in the literature. The majority of them ignore the anisotropic character of diffusion of glioma cells since availability of pertinent truly exploitable tomographic imaging data is limited. Aiming at enriching the anisotropy-enhanced glioma model weaponry so as to increase the potential of exploiting available tomographic imaging data, we propose a Brownian motion-based mathematical analysis that could serve as the basis for a simulation model estimating the infiltration of glioblastoma cells into the surrounding brain tissue. The analysis is based on clinical observations and exploits diffusion tensor imaging (DTI) data. Numerical simulations and suggestions for further elaboration are provided.

Disability in physical education textbooks: an analysis of image content.

PubMed

Táboas-Pais, María Inés; Rey-Cao, Ana

2012-10-01

The aim of this paper is to show how images of disability are portrayed in physical education textbooks for secondary schools in Spain. The sample was composed of 3,316 images published in 36 textbooks by 10 publishing houses. A content analysis was carried out using a coding scheme based on categories employed in other similar studies and adapted to the requirements of this study with additional categories. The variables were camera angle, gender, type of physical activity, field of practice, space, and level. Univariate and bivariate descriptive analyses were also carried out. The Pearson chi-square statistic was used to identify associations between the variables. Results showed a noticeable imbalance between people with disabilities and people without disabilities, and women with disabilities were less frequently represented than men with disabilities. People with disabilities were depicted as participating in a very limited variety of segregated, competitive, and elite sports activities.

IRIS: a novel spectral imaging system for the analysis of cultural heritage objects

NASA Astrophysics Data System (ADS)

Papadakis, V. M.; Orphanos, Y.; Kogou, S.; Melessanaki, K.; Pouli, P.; Fotakis, C.

2011-06-01

A new portable spectral imaging system is herein presented capable of acquiring images of high resolution (2MPixels) ranging from 380 nm up to 950 nm. The system consists of a digital color CCD camera, 15 interference filters covering all the sensitivity range of the detector and a robust filter changing system. The acquisition software has been developed in "LabView" programming language allowing easy handling and modification by end-users. The system has been tested and evaluated on a series of objects of Cultural Heritage (CH) value including paintings, encrusted stonework, ceramics etc. This paper aims to present the system, as well as, its application and advantages in the analysis of artworks with emphasis on the detailed compositional and structural information of layered surfaces based on reflection & fluorescence spectroscopy. Specific examples will be presented and discussed on the basis of system improvements.

A new method for computer-assisted detection, definition and differentiation of the urinary calculi.

PubMed

Yildirim, Duzgun; Ozturk, Ovunc; Tutar, Onur; Nurili, Fuad; Bozkurt, Halil; Kayadibi, Huseyin; Karaarslan, Ercan; Bakan, Selim

2014-09-01

Urinary stones are common and can be diagnosed with computed tomography (CT) easily. In this study, we aimed to specify the opacity characteristics of various types of calcified foci that develop through the urinary system by using an image analysis program. With this method, we try to differentiate the calculi from the non-calculous opacities and also we aimed to present how to identify the characteristic features of renal and ureteral calcules. We obtained the CT studies of the subjects (n = 48, mean age = 41 years) by using a dual source CT imaging system. We grouped the calculi detected in the dual-energy CT sections as renal (n = 40) or ureteric (n = 45) based on their locations. Other radio-opaque structures that were identified outside but within close proximity of the urinary tract were recorded as calculi "mimickers". We used ImageJ program for morphological analysis. All the acquired data were analyzed statistically. According to thorough morphological parameters, there were statistically significant differences in the angle and Feret angle values between calculi and mimickers (p < 0.001). Multivariate logistical regression analysis showed that Minor Axis and Feret angle parameters can be used to distinguish between ureteric (p = 0.003) and kidney (p = 0.001) stones. Computer-based morphologic parameters can be used simply to differentiate between calcular and noncalcular densities on CT and also between renal and ureteric stones.

Managing and Querying Image Annotation and Markup in XML.

PubMed

Wang, Fusheng; Pan, Tony; Sharma, Ashish; Saltz, Joel

2010-01-01

Proprietary approaches for representing annotations and image markup are serious barriers for researchers to share image data and knowledge. The Annotation and Image Markup (AIM) project is developing a standard based information model for image annotation and markup in health care and clinical trial environments. The complex hierarchical structures of AIM data model pose new challenges for managing such data in terms of performance and support of complex queries. In this paper, we present our work on managing AIM data through a native XML approach, and supporting complex image and annotation queries through native extension of XQuery language. Through integration with xService, AIM databases can now be conveniently shared through caGrid.

Managing and Querying Image Annotation and Markup in XML

PubMed Central

Wang, Fusheng; Pan, Tony; Sharma, Ashish; Saltz, Joel

2010-01-01

Proprietary approaches for representing annotations and image markup are serious barriers for researchers to share image data and knowledge. The Annotation and Image Markup (AIM) project is developing a standard based information model for image annotation and markup in health care and clinical trial environments. The complex hierarchical structures of AIM data model pose new challenges for managing such data in terms of performance and support of complex queries. In this paper, we present our work on managing AIM data through a native XML approach, and supporting complex image and annotation queries through native extension of XQuery language. Through integration with xService, AIM databases can now be conveniently shared through caGrid. PMID:21218167

Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry.

PubMed

Oetjen, Janina; Veselkov, Kirill; Watrous, Jeramie; McKenzie, James S; Becker, Michael; Hauberg-Lotte, Lena; Kobarg, Jan Hendrik; Strittmatter, Nicole; Mróz, Anna K; Hoffmann, Franziska; Trede, Dennis; Palmer, Andrew; Schiffler, Stefan; Steinhorst, Klaus; Aichler, Michaela; Goldin, Robert; Guntinas-Lichius, Orlando; von Eggeling, Ferdinand; Thiele, Herbert; Maedler, Kathrin; Walch, Axel; Maass, Peter; Dorrestein, Pieter C; Takats, Zoltan; Alexandrov, Theodore

2015-01-01

Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms. High-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma. With the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.

Navy Tactical Applications Guide. Volume 7. Southern Hemisphere Weather Analysis and Forecast Applications

DTIC Science & Technology

1989-10-01

R2). The 500-mb analysis (Fig. IB-22a) during the winter season. Several important differ - has been reanalyzed to fit the satellite image data. ences...EARI AIM 21 JV! so% +20 7 +818 +765 16 SURFACE 86072012Z One Ica us Figure IB-27a. FNOC Surface Analysis . 1200 GMT 20 July 19...and the high and is also shown by the 0000 GMT surface is not a result of the blocking pattern. The axis of the high analysis . The cloud vortex

Magnetic particle imaging for in vivo blood flow velocity measurements in mice

NASA Astrophysics Data System (ADS)

Kaul, Michael G.; Salamon, Johannes; Knopp, Tobias; Ittrich, Harald; Adam, Gerhard; Weller, Horst; Jung, Caroline

2018-03-01

Magnetic particle imaging (MPI) is a new imaging technology. It is a potential candidate to be used for angiographic purposes, to study perfusion and cell migration. The aim of this work was to measure velocities of the flowing blood in the inferior vena cava of mice, using MPI, and to evaluate it in comparison with magnetic resonance imaging (MRI). A phantom mimicking the flow within the inferior vena cava with velocities of up to 21 cm s‑1 was used for the evaluation of the applied analysis techniques. Time–density and distance–density analyses for bolus tracking were performed to calculate flow velocities. These findings were compared with the calibrated velocities set by a flow pump, and it can be concluded that velocities of up to 21 cm s‑1 can be measured by MPI. A time–density analysis using an arrival time estimation algorithm showed the best agreement with the preset velocities. In vivo measurements were performed in healthy FVB mice (n  =  10). MRI experiments were performed using phase contrast (PC) for velocity mapping. For MPI measurements, a standardized injection of a superparamagnetic iron oxide tracer was applied. In vivo MPI data were evaluated by a time–density analysis and compared to PC MRI. A Bland–Altman analysis revealed good agreement between the in vivo velocities acquired by MRI of 4.0  ±  1.5 cm s‑1 and those measured by MPI of 4.8  ±  1.1 cm s‑1. Magnetic particle imaging is a new tool with which to measure and quantify flow velocities. It is fast, radiation-free, and produces 3D images. It therefore offers the potential for vascular imaging.

SEM AutoAnalysis: enhancing photomask and NIL defect disposition and review

NASA Astrophysics Data System (ADS)

Schulz, Kristian; Egodage, Kokila; Tabbone, Gilles; Ehrlich, Christian; Garetto, Anthony

2017-06-01

For defect disposition and repair verification regarding printability, AIMS™ is the state of the art measurement tool in industry. With its unique capability of capturing aerial images of photomasks it is the one method that comes closest to emulating the printing behaviour of a scanner. However for nanoimprint lithography (NIL) templates aerial images cannot be applied to evaluate the success of a repair process. Hence, for NIL defect dispositioning scanning, electron microscopy (SEM) imaging is the method of choice. In addition, it has been a standard imaging method for further root cause analysis of defects and defect review on optical photomasks which enables 2D or even 3D mask profiling at high resolutions. In recent years a trend observed in mask shops has been the automation of processes that traditionally were driven by operators. This of course has brought many advantages one of which is freeing cost intensive labour from conducting repetitive and tedious work. Furthermore, it reduces variability in processes due to different operator skill and experience levels which at the end contributes to eliminating the human factor. Taking these factors into consideration, one of the software based solutions available under the FAVOR® brand to support customer needs is the aerial image evaluation software, AIMS™ AutoAnalysis (AAA). It provides fully automated analysis of AIMS™ images and runs in parallel to measurements. This is enabled by its direct connection and communication with the AIMS™tools. As one of many positive outcomes, generating automated result reports is facilitated, standardizing the mask manufacturing workflow. Today, AAA has been successfully introduced into production at multiple customers and is supporting the workflow as described above. These trends indeed have triggered the demand for similar automation with respect to SEM measurements leading to the development of SEM AutoAnalysis (SAA). It aims towards a fully automated SEM image evaluation process utilizing a completely different algorithm due to the different nature of SEM images and aerial images. Both AAA and SAA are the building blocks towards an image evaluation suite in the mask shop industry.

Continuous monitoring of arthritis in animal models using optical imaging modalities

NASA Astrophysics Data System (ADS)

Son, Taeyoon; Yoon, Hyung-Ju; Lee, Saseong; Jang, Won Seuk; Jung, Byungjo; Kim, Wan-Uk

2014-10-01

Given the several difficulties associated with histology, including difficulty in continuous monitoring, this study aimed to investigate the feasibility of optical imaging modalities-cross-polarization color (CPC) imaging, erythema index (EI) imaging, and laser speckle contrast (LSC) imaging-for continuous evaluation and monitoring of arthritis in animal models. C57BL/6 mice, used for the evaluation of arthritis, were divided into three groups: arthritic mice group (AMG), positive control mice group (PCMG), and negative control mice group (NCMG). Complete Freund's adjuvant, mineral oil, and saline were injected into the footpad for AMG, PCMG, and NCMG, respectively. LSC and CPC images were acquired from 0 through 144 h after injection for all groups. EI images were calculated from CPC images. Variations in feet area, EI, and speckle index for each mice group over time were calculated for quantitative evaluation of arthritis. Histological examinations were performed, and the results were found to be consistent with those from optical imaging analysis. Thus, optical imaging modalities may be successfully applied for continuous evaluation and monitoring of arthritis in animal models.

Quality Control of Structural MRI Images Applied Using FreeSurfer—A Hands-On Workflow to Rate Motion Artifacts

PubMed Central

Backhausen, Lea L.; Herting, Megan M.; Buse, Judith; Roessner, Veit; Smolka, Michael N.; Vetter, Nora C.

2016-01-01

In structural magnetic resonance imaging motion artifacts are common, especially when not scanning healthy young adults. It has been shown that motion affects the analysis with automated image-processing techniques (e.g., FreeSurfer). This can bias results. Several developmental and adult studies have found reduced volume and thickness of gray matter due to motion artifacts. Thus, quality control is necessary in order to ensure an acceptable level of quality and to define exclusion criteria of images (i.e., determine participants with most severe artifacts). However, information about the quality control workflow and image exclusion procedure is largely lacking in the current literature and the existing rating systems differ. Here, we propose a stringent workflow of quality control steps during and after acquisition of T1-weighted images, which enables researchers dealing with populations that are typically affected by motion artifacts to enhance data quality and maximize sample sizes. As an underlying aim we established a thorough quality control rating system for T1-weighted images and applied it to the analysis of developmental clinical data using the automated processing pipeline FreeSurfer. This hands-on workflow and quality control rating system will aid researchers in minimizing motion artifacts in the final data set, and therefore enhance the quality of structural magnetic resonance imaging studies. PMID:27999528

Incidental findings found in “healthy” volunteers during imaging performed for research: current legal and ethical implications

PubMed Central

Booth, T C; Jackson, A; Wardlaw, J M; Taylor, S A; Waldman, A D

2010-01-01

Incidental findings found in “healthy” volunteers during research imaging are common and have important implications for study design and performance, particularly in the areas of informed consent, subjects' rights, clinical image analysis and disclosure. In this study, we aimed to determine current practice and regulations concerning information that should be given to research subjects when obtaining consent, reporting of research images, who should be informed about any incidental findings and the method of disclosure. We reviewed all UK, European and international humanitarian, legal and ethical agencies' guidance. We found that the guidance on what constitutes incidental pathology, how to recognise it and what to do about it is inconsistent between agencies, difficult to find and less complete in the UK than elsewhere. Where given, guidance states that volunteers should be informed during the consent process about how research images will be managed, whether a mechanism exists for identifying incidental findings, arrangements for their disclosure, the potential benefit or harm and therapeutic options. The effects of incidentally discovered pathology on the individual can be complex and far-reaching. Radiologist involvement in analysis of research images varies widely; many incidental findings might therefore go unrecognised. In conclusion, guidance on the management of research imaging is inconsistent, limited and does not address the interests of volunteers. Improved standards to guide management of research images and incidental findings are urgently required. PMID:20335427

Bi-temporal analysis of landscape changes in the easternmost mediterranean deltas using binary and classified change information.

PubMed

Alphan, Hakan

2013-03-01

The aim of this study is (1) to quantify landscape changes in the easternmost Mediterranean deltas using bi-temporal binary change detection approach and (2) to analyze relationships between conservation/management designations and various categories of change that indicate type, degree and severity of human impact. For this purpose, image differencing and ratioing were applied to Landsat TM images of 1984 and 2006. A total of 136 candidate change images including normalized difference vegetation index (NDVI) and principal component analysis (PCA) difference images were tested to understand performance of bi-temporal pre-classification analysis procedures in the Mediterranean delta ecosystems. Results showed that visible image algebra provided high accuracies than did NDVI and PCA differencing. On the other hand, Band 5 differencing had one of the lowest change detection performances. Seven superclasses of change were identified using from/to change categories between the earlier and later dates. These classes were used to understand spatial character of anthropogenic impacts in the study area and derive qualitative and quantitative change information within and outside of the conservation/management areas. Change analysis indicated that natural site and wildlife reserve designations fell short of protecting sand dunes from agricultural expansion in the west. East of the study area, however, was exposed to least human impact owing to the fact that nature conservation status kept human interference at a minimum. Implications of these changes were discussed and solutions were proposed to deal with management problems leading to environmental change.

Representations of Codeine Misuse on Instagram: Content Analysis

PubMed Central

Cherian, Roy; Westbrook, Marisa; Ramo, Danielle

2018-01-01

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

Radiation dose reduction in abdominal computed tomography during the late hepatic arterial phase using a model-based iterative reconstruction algorithm: how low can we go?

PubMed

Husarik, Daniela B; Marin, Daniele; Samei, Ehsan; Richard, Samuel; Chen, Baiyu; Jaffe, Tracy A; Bashir, Mustafa R; Nelson, Rendon C

2012-08-01

The aim of this study was to compare the image quality of abdominal computed tomography scans in an anthropomorphic phantom acquired at different radiation dose levels where each raw data set is reconstructed with both a standard convolution filtered back projection (FBP) and a full model-based iterative reconstruction (MBIR) algorithm. An anthropomorphic phantom in 3 sizes was used with a custom-built liver insert simulating late hepatic arterial enhancement and containing hypervascular liver lesions of various sizes. Imaging was performed on a 64-section multidetector-row computed tomography scanner (Discovery CT750 HD; GE Healthcare, Waukesha, WI) at 3 different tube voltages for each patient size and 5 incrementally decreasing tube current-time products for each tube voltage. Quantitative analysis consisted of contrast-to-noise ratio calculations and image noise assessment. Qualitative image analysis was performed by 3 independent radiologists rating subjective image quality and lesion conspicuity. Contrast-to-noise ratio was significantly higher and mean image noise was significantly lower on MBIR images than on FBP images in all patient sizes, at all tube voltage settings, and all radiation dose levels (P < 0.05). Overall image quality and lesion conspicuity were rated higher for MBIR images compared with FBP images at all radiation dose levels. Image quality and lesion conspicuity on 25% to 50% dose MBIR images were rated equal to full-dose FBP images. This phantom study suggests that depending on patient size, clinically acceptable image quality of the liver in the late hepatic arterial phase can be achieved with MBIR at approximately 50% lower radiation dose compared with FBP.

Neurosensoric disturbances after surgical removal of the mandibular third molar based on either panoramic imaging or cone beam CT scanning: A randomized controlled trial (RCT)

PubMed Central

Vaeth, Michael; Wenzel, Ann

2016-01-01

Objective: Pre-surgical CBCT has been suggested before removal of the mandibular third molar. Currently, the standard-of-care is two-dimensional (2D) panoramic imaging. The aim of this randomized controlled trial was to analyse possible differences in neurosensoric disturbances of the inferior alveolar nerve between patients undergoing either panoramic imaging or CBCT before surgical removal of the mandibular third molar. Furthermore, the aim was to perform a sensitivity analysis to assess the statistical significance of different assumptions related to sample size calculations. Methods: 230 patients were randomized to a scan group and a non-scan group. All patients were referred from practicing dentists in the Copenhagen area. Inclusion criteria were overlap of the root complex and the mandibular canal on a 2D radiographic image. Central allocation of the randomization code and double blind settings were established. The surgical removal was performed in a specialized surgical practice geographically and personally separated from the study practice. Registration of neurosensoric anomalies was performed with a Semmes–Weinstein test and a visual analogue scale questionnaire pre- and post-surgically. Results: In the scan group (n = 114), 21 episodes of neurosensoric disturbances were registered and in the non-scan group (n = 116), 13 episodes of neurosensoric disturbances were registered. There was no statistically significant difference between the two groups (p = 0.14). Performing a sensitivity analysis confirmed that CBCT was not superior to panoramic imaging in avoiding neurosensoric disturbances. Conclusions: The use of CBCT before removal of the mandibular third molar does not seem to reduce the number of neurosensoric disturbances. PMID:26648386

Neurosensoric disturbances after surgical removal of the mandibular third molar based on either panoramic imaging or cone beam CT scanning: A randomized controlled trial (RCT).

PubMed

Petersen, Lars B; Vaeth, Michael; Wenzel, Ann

2016-01-01

Pre-surgical CBCT has been suggested before removal of the mandibular third molar. Currently, the standard-of-care is two-dimensional (2D) panoramic imaging. The aim of this randomized controlled trial was to analyse possible differences in neurosensoric disturbances of the inferior alveolar nerve between patients undergoing either panoramic imaging or CBCT before surgical removal of the mandibular third molar. Furthermore, the aim was to perform a sensitivity analysis to assess the statistical significance of different assumptions related to sample size calculations. 230 patients were randomized to a scan group and a non-scan group. All patients were referred from practicing dentists in the Copenhagen area. Inclusion criteria were overlap of the root complex and the mandibular canal on a 2D radiographic image. Central allocation of the randomization code and double blind settings were established. The surgical removal was performed in a specialized surgical practice geographically and personally separated from the study practice. Registration of neurosensoric anomalies was performed with a Semmes-Weinstein test and a visual analogue scale questionnaire pre- and post-surgically. In the scan group (n = 114), 21 episodes of neurosensoric disturbances were registered and in the non-scan group (n = 116), 13 episodes of neurosensoric disturbances were registered. There was no statistically significant difference between the two groups (p = 0.14). Performing a sensitivity analysis confirmed that CBCT was not superior to panoramic imaging in avoiding neurosensoric disturbances. The use of CBCT before removal of the mandibular third molar does not seem to reduce the number of neurosensoric disturbances.

Advanced pushbroom hyperspectral LWIR imagers

NASA Astrophysics Data System (ADS)

Holma, Hannu; Hyvärinen, Timo; Lehtomaa, Jarmo; Karjalainen, Harri; Jaskari, Risto

2009-05-01

Performance studies and instrument designs for hyperspectral pushbroom imagers in thermal wavelength region are introduced. The studies involve imaging systems based on both MCT and microbolometer detector. All the systems employ pushbroom imaging spectrograph with transmission grating and on-axis optics. The aim of the work was to design high performance instruments with good image quality and compact size for various application requirements. A big challenge in realizing these goals without considerable cooling of the whole instrument is to control the instrument radiation from all the surfaces of the instrument itself. This challenge is even bigger in hyperspectral instruments, where the optical power from the target is spread spectrally over tens of pixels, but the instrument radiation is not dispersed. Without any suppression, the instrument radiation can overwhelm the radiation from the target by 1000 times. In the first imager design, BMC-technique (background monitoring on-chip), background suppression and temperature stabilization have been combined with cryo-cooled MCT-detector. The performance of a very compact hyperspectral imager with 84 spectral bands and 384 spatial samples has been studied and NESR of 18 mW/(m2srμm) at 10 μm wavelength for 300 K target has been achieved. This leads to SNR of 580. These results are based on a simulation model. The second version of the imager with an uncooled microbolometer detector and optics in ambient temperature aims at imaging targets at higher temperatures or with illumination. Heater rods with ellipsoidal reflectors can be used to illuminate the swath line of the hyperspectral imager on a target or sample, like drill core in mineralogical analysis. Performance characteristics for microbolometer version have been experimentally verified.

Accuracy of MRI for the diagnosis of metastatic cervical lymphadenopathy in patients with thyroid cancer.

PubMed

Chen, Qinghua; Raghavan, Prashant; Mukherjee, Sugoto; Jameson, Mark J; Patrie, James; Xin, Wenjun; Xian, Junfang; Wang, Zhenchang; Levine, Paul A; Wintermark, Max

2015-10-01

The aim of this study was to systematically compare a comprehensive array of magnetic resonance (MR) imaging features in terms of their sensitivity and specificity to diagnose cervical lymph node metastases in patients with thyroid cancer. The study included 41 patients with thyroid malignancy who underwent surgical excision of cervical lymph nodes and had preoperative MR imaging ≤4weeks prior to surgery. Three head and neck neuroradiologists independently evaluated all the MR images. Using the pathology results as reference, the sensitivity, specificity and interobserver agreement of each MR imaging characteristic were calculated. On multivariate analysis, no single imaging feature was significantly correlated with metastasis. In general, imaging features demonstrated high specificity, but poor sensitivity and moderate interobserver agreement at best. Commonly used MR imaging features have limited sensitivity at correctly identifying cervical lymph node metastases in patients with thyroid cancer. A negative neck MR scan should not dissuade a surgeon from performing a neck dissection in patients with thyroid carcinomas.

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.

Observing vegetation phenology through social media.

PubMed

Silva, Sam J; Barbieri, Lindsay K; Thomer, Andrea K

2018-01-01

The widespread use of social media has created a valuable but underused source of data for the environmental sciences. We demonstrate the potential for images posted to the website Twitter to capture variability in vegetation phenology across United States National Parks. We process a subset of images posted to Twitter within eight U.S. National Parks, with the aim of understanding the amount of green vegetation in each image. Analysis of the relative greenness of the images show statistically significant seasonal cycles across most National Parks at the 95% confidence level, consistent with springtime green-up and fall senescence. Additionally, these social media-derived greenness indices correlate with monthly mean satellite NDVI (r = 0.62), reinforcing the potential value these data could provide in constraining models and observing regions with limited high quality scientific monitoring.

Deep into the Brain: Artificial Intelligence in Stroke Imaging

PubMed Central

Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

2017-01-01

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives. PMID:29037014

Image encryption algorithm based on multiple mixed hash functions and cyclic shift

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Zhu, Xiaoqiang; Wu, Xiangjun; Zhang, Yingqian

2018-08-01

This paper proposes a new one-time pad scheme for chaotic image encryption that is based on the multiple mixed hash functions and the cyclic-shift function. The initial value is generated using both information of the plaintext image and the chaotic sequences, which are calculated from the SHA1 and MD5 hash algorithms. The scrambling sequences are generated by the nonlinear equations and logistic map. This paper aims to improve the deficiencies of traditional Baptista algorithms and its improved algorithms. We employ the cyclic-shift function and piece-wise linear chaotic maps (PWLCM), which give each shift number the characteristics of chaos, to diffuse the image. Experimental results and security analysis show that the new scheme has better security and can resist common attacks.

Deep into the Brain: Artificial Intelligence in Stroke Imaging.

PubMed

Lee, Eun-Jae; Kim, Yong-Hwan; Kim, Namkug; Kang, Dong-Wha

2017-09-01

Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.

Views of Nature and the Human-Nature Relations: An Analysis of the Visual Syntax of Pictures about the Environment in Greek Primary School Textbooks--Diachronic Considerations

ERIC Educational Resources Information Center

Lemoni, Rea; Lefkaditou, Ageliki; Stamou, Anastasia G.; Schizas, Dimitrios; Stamou, George P.

2013-01-01

This paper explores the function of the visual syntax of images in Greek primary school textbooks. By using a model for the formal analysis of the visual material, which will allow us to disclose the mechanisms through which meanings are manifested, our aim is to investigate the discursive transition relating to the view of nature and the…

Quantification of protein expression in cells and cellular subcompartments on immunohistochemical sections using a computer supported image analysis system.

PubMed

Braun, Martin; Kirsten, Robert; Rupp, Niels J; Moch, Holger; Fend, Falko; Wernert, Nicolas; Kristiansen, Glen; Perner, Sven

2013-05-01

Quantification of protein expression based on immunohistochemistry (IHC) is an important step for translational research and clinical routine. Several manual ('eyeballing') scoring systems are used in order to semi-quantify protein expression based on chromogenic intensities and distribution patterns. However, manual scoring systems are time-consuming and subject to significant intra- and interobserver variability. The aim of our study was to explore, whether new image analysis software proves to be sufficient as an alternative tool to quantify protein expression. For IHC experiments, one nucleus specific marker (i.e., ERG antibody), one cytoplasmic specific marker (i.e., SLC45A3 antibody), and one marker expressed in both compartments (i.e., TMPRSS2 antibody) were chosen. Stainings were applied on TMAs, containing tumor material of 630 prostate cancer patients. A pathologist visually quantified all IHC stainings in a blinded manner, applying a four-step scoring system. For digital quantification, image analysis software (Tissue Studio v.2.1, Definiens AG, Munich, Germany) was applied to obtain a continuous spectrum of average staining intensity. For each of the three antibodies we found a strong correlation of the manual protein expression score and the score of the image analysis software. Spearman's rank correlation coefficient was 0.94, 0.92, and 0.90 for ERG, SLC45A3, and TMPRSS2, respectively (p⟨0.01). Our data suggest that the image analysis software Tissue Studio is a powerful tool for quantification of protein expression in IHC stainings. Further, since the digital analysis is precise and reproducible, computer supported protein quantification might help to overcome intra- and interobserver variability and increase objectivity of IHC based protein assessment.

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

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

Cui, Y; Shirato, H; Song, J

2015-06-15

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

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.

Polarization-singular processing of biological layers laser images to diagnose and classify their optical properties

NASA Astrophysics Data System (ADS)

Ushenko, Yu. O.; Telenga, O. Y.

2011-09-01

Presented in this work are the results of investigation aimed at analysis of coordinate distributions for azimuths and ellipticity of polarization (polarization maps) in blood plasma layers laser images of three groups of patients: healthy (group 1), with dysplasia (group 2) and cancer of cervix uteri (group 3). To characterize polarization maps for all groups of samples, the authors have offered to use three groups of parameters: statistical moments of the first to the fourth orders, autocorrelation functions, logarithmic dependences for power spectra related to distributions of azimuths and ellipticity of polarization inherent to blood plasma laser images. Ascertained are the criteria for diagnostics and differentiation of cervix uteri pathological changes.

Analysis of elements in a minimal amount of temporomandibular joint fluid on fluid-attenuated inversion recovery magnetic resonance images.

PubMed

Hanyuda, Hitoshi; Otonari-Yamamoto, Mika; Imoto, Kenichi; Sakamoto, Junichiro; Kodama, Sayaka; Kamio, Takashi; Sano, Tsukasa

2013-01-01

The aim of this study was to elucidate possible elements in minimal amounts of fluid (MF) in the temporomandibular joint by analyzing signal intensities in T2-weighted and fluid-attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. Fifteen joints (15 patients) with MF were subjected to MR imaging to obtain T2-weighted and FLAIR images. Regions of interest were placed on MF, cerebrospinal fluid (CSF), and gray matter (GM), and their signal intensities were measured on both images. The signal intensity ratio (SIR) obtained by the signal intensity of GM between MF and CSF was compared in T2-weighted and FLAIR images. The average SIR of MF was lower than that of CSF on T2-weighted images, whereas it was higher on FLAIR images. The average suppression ratio of the signal intensity was lower for MF (24.1%) than for CSF (71.4%). MF may contain elements such as protein that are capable of inducing a shortened T1 relaxation time on MR images. Copyright © 2013 Elsevier Inc. All rights reserved.

Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

PubMed

Reena Benjamin, J; Jayasree, T

2018-02-01

In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

Performance analysis of sliding window filtering of two dimensional signals based on stream data processing systems

NASA Astrophysics Data System (ADS)

Kazanskiy, Nikolay; Protsenko, Vladimir; Serafimovich, Pavel

2016-03-01

This research article contains an experiment with implementation of image filtering task in Apache Storm and IBM InfoSphere Streams stream data processing systems. The aim of presented research is to show that new technologies could be effectively used for sliding window filtering of image sequences. The analysis of execution was focused on two parameters: throughput and memory consumption. Profiling was performed on CentOS operating systems running on two virtual machines for each system. The experiment results showed that IBM InfoSphere Streams has about 1.5 to 13.5 times lower memory footprint than Apache Storm, but could be about 2.0 to 2.5 slower on a real hardware.

Trends in radiology and experimental research.

PubMed

Sardanelli, Francesco

2017-01-01

European Radiology Experimental , the new journal launched by the European Society of Radiology, is placed in the context of three general and seven radiology-specific trends. After describing the impact of population aging, personalized/precision medicine, and information technology development, the article considers the following trends: the tension between subspecialties and the unity of the discipline; attention to patient safety; the challenge of reproducibility for quantitative imaging; standardized and structured reporting; search for higher levels of evidence in radiology (from diagnostic performance to patient outcome); the increasing relevance of interventional radiology; and continuous technological evolution. The new journal will publish not only studies on phantoms, cells, or animal models but also those describing development steps of imaging biomarkers or those exploring secondary end-points of large clinical trials. Moreover, consideration will be given to studies regarding: computer modelling and computer aided detection and diagnosis; contrast materials, tracers, and theranostics; advanced image analysis; optical, molecular, hybrid and fusion imaging; radiomics and radiogenomics; three-dimensional printing, information technology, image reconstruction and post-processing, big data analysis, teleradiology, clinical decision support systems; radiobiology; radioprotection; and physics in radiology. The journal aims to establish a forum for basic science, computer and information technology, radiology, and other medical subspecialties.

The Diagnostic Efficacy of Cone-beam Computed Tomography in Endodontics: A Systematic Review and Analysis by a Hierarchical Model of Efficacy.

PubMed

Rosen, Eyal; Taschieri, Silvio; Del Fabbro, Massimo; Beitlitum, Ilan; Tsesis, Igor

2015-07-01

The aim of this study was to evaluate the diagnostic efficacy of cone-beam computed tomographic (CBCT) imaging in endodontics based on a systematic search and analysis of the literature using an efficacy model. A systematic search of the literature was performed to identify studies evaluating the use of CBCT imaging in endodontics. The identified studies were subjected to strict inclusion criteria followed by an analysis using a hierarchical model of efficacy (model) designed for appraisal of the literature on the levels of efficacy of a diagnostic imaging modality. Initially, 485 possible relevant articles were identified. After title and abstract screening and a full-text evaluation, 58 articles (12%) that met the inclusion criteria were analyzed and allocated to levels of efficacy. Most eligible articles (n = 52, 90%) evaluated technical characteristics or the accuracy of CBCT imaging, which was defined in this model as low levels of efficacy. Only 6 articles (10%) proclaimed to evaluate the efficacy of CBCT imaging to support the practitioner's decision making; treatment planning; and, ultimately, the treatment outcome, which was defined as higher levels of efficacy. The expected ultimate benefit of CBCT imaging to the endodontic patient as evaluated by its level of diagnostic efficacy is unclear and is mainly limited to its technical and diagnostic accuracy efficacies. Even for these low levels of efficacy, current knowledge is limited. Therefore, a cautious and rational approach is advised when considering CBCT imaging for endodontic purposes. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

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

Drawing Desire: Male Youth and Homoerotic Fan Art

ERIC Educational Resources Information Center

Dennis, Jeffery P.

2010-01-01

Although Western mass media aimed at juvenile audiences aggressively eliminates any references to same-sex desire and behavior, it inspires a tremendous amount of homoerotic fan art. To determine how same-sex potential is portrayed in juvenile fan art, a content analysis was conducted of 872 male homoerotic images by 442 juvenile male and female…

Peripheral Quantitative CT (pQCT) Using a Dedicated Extremity Cone-Beam CT Scanner

PubMed Central

Muhit, A. A.; Arora, S.; Ogawa, M.; Ding, Y.; Zbijewski, W.; Stayman, J. W.; Thawait, G.; Packard, N.; Senn, R.; Yang, D.; Yorkston, J.; Bingham, C.O.; Means, K.; Carrino, J. A.; Siewerdsen, J. H.

2014-01-01

Purpose We describe the initial assessment of the peripheral quantitative CT (pQCT) imaging capabilities of a cone-beam CT (CBCT) scanner dedicated to musculoskeletal extremity imaging. The aim is to accurately measure and quantify bone and joint morphology using information automatically acquired with each CBCT scan, thereby reducing the need for a separate pQCT exam. Methods A prototype CBCT scanner providing isotropic, sub-millimeter spatial resolution and soft-tissue contrast resolution comparable or superior to standard multi-detector CT (MDCT) has been developed for extremity imaging, including the capability for weight-bearing exams and multi-mode (radiography, fluoroscopy, and volumetric) imaging. Assessment of pQCT performance included measurement of bone mineral density (BMD), morphometric parameters of subchondral bone architecture, and joint space analysis. Measurements employed phantoms, cadavers, and patients from an ongoing pilot study imaged with the CBCT prototype (at various acquisition, calibration, and reconstruction techniques) in comparison to MDCT (using pQCT protocols for analysis of BMD) and micro-CT (for analysis of subchondral morphometry). Results The CBCT extremity scanner yielded BMD measurement within ±2–3% error in both phantom studies and cadaver extremity specimens. Subchondral bone architecture (bone volume fraction, trabecular thickness, degree of anisotropy, and structure model index) exhibited good correlation with gold standard micro-CT (error ~5%), surpassing the conventional limitations of spatial resolution in clinical MDCT scanners. Joint space analysis demonstrated the potential for sensitive 3D joint space mapping beyond that of qualitative radiographic scores in application to non-weight-bearing versus weight-bearing lower extremities and assessment of phalangeal joint space integrity in the upper extremities. Conclusion The CBCT extremity scanner demonstrated promising initial results in accurate pQCT analysis from images acquired with each CBCT scan. Future studies will include improved x-ray scatter correction and image reconstruction techniques to further improve accuracy and to correlate pQCT metrics with known pathology. PMID:25076823

DrishtiCare: a telescreening platform for diabetic retinopathy powered with fundus image analysis.

PubMed

Joshi, Gopal Datt; Sivaswamy, Jayanthi

2011-01-01

Diabetic retinopathy is the leading cause of blindness in urban populations. Early diagnosis through regular screening and timely treatment has been shown to prevent visual loss and blindness. It is very difficult to cater to this vast set of diabetes patients, primarily because of high costs in reaching out to patients and a scarcity of skilled personnel. Telescreening offers a cost-effective solution to reach out to patients but is still inadequate due to an insufficient number of experts who serve the diabetes population. Developments toward fundus image analysis have shown promise in addressing the scarcity of skilled personnel for large-scale screening. This article aims at addressing the underlying issues in traditional telescreening to develop a solution that leverages the developments carried out in fundus image analysis. We propose a novel Web-based telescreening solution (called DrishtiCare) integrating various value-added fundus image analysis components. A Web-based platform on the software as a service (SaaS) delivery model is chosen to make the service cost-effective, easy to use, and scalable. A server-based prescreening system is employed to scrutinize the fundus images of patients and to refer them to the experts. An automatic quality assessment module ensures transfer of fundus images that meet grading standards. An easy-to-use interface, enabled with new visualization features, is designed for case examination by experts. Three local primary eye hospitals have participated and used DrishtiCare's telescreening service. A preliminary evaluation of the proposed platform is performed on a set of 119 patients, of which 23% are identified with the sight-threatening retinopathy. Currently, evaluation at a larger scale is under process, and a total of 450 patients have been enrolled. The proposed approach provides an innovative way of integrating automated fundus image analysis in the telescreening framework to address well-known challenges in large-scale disease screening. It offers a low-cost, effective, and easily adoptable screening solution to primary care providers. © 2010 Diabetes Technology Society.

Textural analysis of optical coherence tomography skin images: quantitative differentiation between healthy and cancerous tissues

NASA Astrophysics Data System (ADS)

Adabi, Saba; Conforto, Silvia; Hosseinzadeh, Matin; Noe, Shahryar; Daveluy, Steven; Mehregan, Darius; Nasiriavanaki, Mohammadreza

2017-02-01

Optical Coherence Tomography (OCT) offers real-time high-resolution three-dimensional images of tissue microstructures. In this study, we used OCT skin images acquired from ten volunteers, neither of whom had any skin conditions addressing the features of their anatomic location. OCT segmented images are analyzed based on their optical properties (attenuation coefficient) and textural image features e.g., contrast, correlation, homogeneity, energy, entropy, etc. Utilizing the information and referring to their clinical insight, we aim to make a comprehensive computational model for the healthy skin. The derived parameters represent the OCT microstructural morphology and might provide biological information for generating an atlas of normal skin from different anatomic sites of human skin and may allow for identification of cell microstructural changes in cancer patients. We then compared the parameters of healthy samples with those of abnormal skin and classified them using a linear Support Vector Machines (SVM) with 82% accuracy.

Land Cover Analysis by Using Pixel-Based and Object-Based Image Classification Method in Bogor

NASA Astrophysics Data System (ADS)

Amalisana, Birohmatin; Rokhmatullah; Hernina, Revi

2017-12-01

The advantage of image classification is to provide earth’s surface information like landcover and time-series changes. Nowadays, pixel-based image classification technique is commonly performed with variety of algorithm such as minimum distance, parallelepiped, maximum likelihood, mahalanobis distance. On the other hand, landcover classification can also be acquired by using object-based image classification technique. In addition, object-based classification uses image segmentation from parameter such as scale, form, colour, smoothness and compactness. This research is aimed to compare the result of landcover classification and its change detection between parallelepiped pixel-based and object-based classification method. Location of this research is Bogor with 20 years range of observation from 1996 until 2016. This region is famous as urban areas which continuously change due to its rapid development, so that time-series landcover information of this region will be interesting.

The visual communication in the optonometric scales.

PubMed

Dantas, Rosane Arruda; Pagliuca, Lorita Marlena Freitag

2006-01-01

Communication through vision involves visual apprenticeship that demands ocular integrity, which results in the importance of the evaluation of visual acuity. The scale of images, formed by optotypes, is a method for the verification of visual acuity in kindergarten children. To identify the optotype the child needs to know the image in analysis. Given the importance of visual communication during the process of construction of the scale of images, one presents a bibliographic, analytical study aiming at thinking about the principles for the construction of those tables. One considers the draw inserted as an optotype as a non-verbal symbolic expression of the body and/or of the environment constructed based on the caption of experiences by the individual. One contests the indiscriminate use of images, for one understands that there must be previous knowledge. Despite the subjectivity of the optotypes, the scales continue valid if one adapts images to those of the universe of the children to be examined.

Heuristic Enhancement of Magneto-Optical Images for NDE

NASA Astrophysics Data System (ADS)

Cacciola, Matteo; Megali, Giuseppe; Pellicanò, Diego; Calcagno, Salvatore; Versaci, Mario; Morabito, FrancescoCarlo

2010-12-01

The quality of measurements in nondestructive testing and evaluation plays a key role in assessing the reliability of different inspection techniques. Each different technique, like the magneto-optic imaging here treated, is affected by some special types of noise which are related to the specific device used for their acquisition. Therefore, the design of even more accurate image processing is often required by relevant applications, for instance, in implementing integrated solutions for flaw detection and characterization. The aim of this paper is to propose a preprocessing procedure based on independent component analysis (ICA) to ease the detection of rivets and/or flaws in the specimens under test. A comparison of the proposed approach with some other advanced image processing methodologies used for denoising magneto-optic images (MOIs) is carried out, in order to show advantages and weakness of ICA in improving the accuracy and performance of the rivets/flaw detection.

Chapter 14: Electron Microscopy on Thin Films for Solar Cells

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

Romero, Manuel; Abou-Ras, Daniel; Nichterwitz, Melanie

2016-07-22

This chapter overviews the various techniques applied in scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and highlights their possibilities and also limitations. It gives the various imaging and analysis techniques applied on a scanning electron microscope. The chapter shows that imaging is divided into that making use of secondary electrons (SEs) and of backscattered electrons (BSEs), resulting in different contrasts in the images and thus providing information on compositions, microstructures, and surface potentials. Whenever aiming for imaging and analyses at scales of down to the angstroms range, TEM and its related techniques are appropriate tools. In many cases,more » also SEM techniques provide the access to various material properties of the individual layers, not requiring specimen preparation as time consuming as TEM techniques. Finally, the chapter dedicates to cross-sectional specimen preparation for electron microscopy. The preparation decides indeed on the quality of imaging and analyses.« less

A picture tells a thousand words: A content analysis of concussion-related images online.

PubMed

Ahmed, Osman H; Lee, Hopin; Struik, Laura L

2016-09-01

Recently image-sharing social media platforms have become a popular medium for sharing health-related images and associated information. However within the field of sports medicine, and more specifically sports related concussion, the content of images and meta-data shared through these popular platforms have not been investigated. The aim of this study was to analyse the content of concussion-related images and its accompanying meta-data on image-sharing social media platforms. We retrieved 300 images from Pinterest, Instagram and Flickr by using a standardised search strategy. All images were screened and duplicate images were removed. We excluded images if they were: non-static images; illustrations; animations; or screenshots. The content and characteristics of each image was evaluated using a customised coding scheme to determine major content themes, and images were referenced to the current international concussion management guidelines. From 300 potentially relevant images, 176 images were included for analysis; 70 from Pinterest, 63 from Flickr, and 43 from Instagram. Most images were of another person or a scene (64%), with the primary content depicting injured individuals (39%). The primary purposes of the images were to share a concussion-related incident (33%) and to dispense education (19%). For those images where it could be evaluated, the majority (91%) were found to reflect the Sports Concussion Assessment Tool 3 (SCAT3) guidelines. The ability to rapidly disseminate rich information though photos, images, and infographics to a wide-reaching audience suggests that image-sharing social media platforms could be used as an effective communication tool for sports concussion. Public health strategies could direct educative content to targeted populations via the use of image-sharing platforms. Further research is required to understand how image-sharing platforms can be used to effectively relay evidence-based information to patients and sports medicine clinicians. Copyright © 2016 Elsevier Ltd. All rights reserved.

Digital image processing techniques for the analysis of fuel sprays global pattern

NASA Astrophysics Data System (ADS)

Zakaria, Rami; Bryanston-Cross, Peter; Timmerman, Brenda

2017-12-01

We studied the fuel atomization process of two fuel injectors to be fitted in a new small rotary engine design. The aim was to improve the efficiency of the engine by optimizing the fuel injection system. Fuel sprays were visualised by an optical diagnostic system. Images of fuel sprays were produced under various testing conditions, by changing the line pressure, nozzle size, injection frequency, etc. The atomisers were a high-frequency microfluidic dispensing system and a standard low flow-rate fuel injector. A series of image processing procedures were developed in order to acquire information from the laser-scattering images. This paper presents the macroscopic characterisation of Jet fuel (JP8) sprays. We observed the droplet density distribution, tip velocity, and spray-cone angle against line-pressure and nozzle-size. The analysis was performed for low line-pressure (up to 10 bar) and short injection period (1-2 ms). Local velocity components were measured by applying particle image velocimetry (PIV) on double-exposure images. The discharge velocity was lower in the micro dispensing nozzle sprays and the tip penetration slowed down at higher rates compared to the gasoline injector. The PIV test confirmed that the gasoline injector produced sprays with higher velocity elements at the centre and the tip regions.

Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

PubMed

Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

2017-08-01

The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

Effects of alopecia on body image and quality of life of Turkish cancer women with or without headscarf.

PubMed

Erol, Ozgul; Can, Gulbeyaz; Aydıner, Adnan

2012-10-01

The aim of this study was to find out the effects of chemotherapy-related alopecia on body image and quality of life of Turkish women who have cancer with or without headscarves and factors affecting them. This descriptive study was conducted with 204 women who received chemotherapy at the Istanbul University Institute of Oncology, Turkey. The Patient Description Form, Body Image Scale and Nightingale Symptom Assessment Scale were used in data collection. Statistical analyses were performed using descriptive statistics and non-parametric tests. Logistic regression analysis was done to predict the factors affecting body image and quality of life of the patients. No difference was found between women wearing headscarves and those who did not in respect of their body image. However, women who wore headscarves who had no alopecia felt less dissatisfied with their scars, and women not wearing headscarves who had no alopecia have been feeling less self-conscious, less dissatisfied with their appearance. There was difference in terms of quality of life: women wearing headscarves had worse physical, psychological and general well-being than others. Although there were many important factors, multivariate analysis showed that for body image, having alopecia and wearing headscarves; and for quality of life, having alopecia were the variables that had considerable effects.

Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies.

PubMed

Fornasaro, Stefano; Vicario, Annalisa; De Leo, Luigina; Bonifacio, Alois; Not, Tarcisio; Sergo, Valter

2018-05-14

Raman hyperspectral imaging is an emerging practice in biological and biomedical research for label free analysis of tissues and cells. Using this method, both spatial distribution and spectral information of analyzed samples can be obtained. The current study reports the first Raman microspectroscopic characterisation of colon tissues from patients with Coeliac Disease (CD). The aim was to assess if Raman imaging coupled with hyperspectral multivariate image analysis is capable of detecting the alterations in the biochemical composition of intestinal tissues associated with CD. The analytical approach was based on a multi-step methodology: duodenal biopsies from healthy and coeliac patients were measured and processed with Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). Based on the distribution maps and the pure spectra of the image constituents obtained from MCR-ALS, interesting biochemical differences between healthy and coeliac patients has been derived. Noticeably, a reduced distribution of complex lipids in the pericryptic space, and a different distribution and abundance of proteins rich in beta-sheet structures was found in CD patients. The output of the MCR-ALS analysis was then used as a starting point for two clustering algorithms (k-means clustering and hierarchical clustering methods). Both methods converged with similar results providing precise segmentation over multiple Raman images of studied tissues.

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

PubMed Central

Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano

2008-01-01

Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177

Pharyngeal airway changes following maxillary expansion or protraction: A meta-analysis.

PubMed

Lee, W-C; Tu, Y-K; Huang, C-S; Chen, R; Fu, M-W; Fu, E

2018-02-01

The aim of this meta-analysis was to investigate the changes in airway dimensions after rapid maxillary expansion (RME) and facemask (FM) protraction. Using PubMed, Medline, ScienceDirect and Web of Science, only controlled clinical trials, published up to November 2016, with RME and/or FM as keywords that had ≥6 months follow-up period were included in this meta-analysis. The changes in pharyngeal airway dimension in both two-dimensional and three-dimensional images were included in the analysis. Nine studies met the criteria. There are statically significant changes in upper airway and nasal passage airway in the intervention groups as compared to the control groups, assessed in two-dimensional and three-dimensional images. However , in the lower airway and the airway below the palatal plane, no statistically significant changes are seen in 2D and 3D images. RME/FM treatments might increase the upper airway space in children and young adolescents. However, more RCTs and long-term cohort studies are needed to further clarify the effects on pharyngeal airway changes. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Evaluation of agave fiber delignification by means of microscopy techniques and image analysis.

PubMed

Hernández-Hernández, Hilda M; Chanona-Pérez, Jorge J; Calderón-Domínguez, Georgina; Perea-Flores, María J; Mendoza-Pérez, Jorge A; Vega, Alberto; Ligero, Pablo; Palacios-González, Eduardo; Farrera-Rebollo, Reynold R

2014-10-01

Recently, the use of different types of natural fibers to produce paper and textiles from agave plants has been proposed. Agave atrovirens can be a good source of cellulose and lignin; nevertheless, the microstructural changes that happen during delignification have scarcely been studied. The aim of this work was to study the microstructural changes that occur during the delignification of agave fibers by means of microscopy techniques and image analysis. The fibers of A. atrovirens were obtained from leaves using convective drying, milling, and sieving. Fibers were processed using the Acetosolv pulping method at different concentrations of acetic acid; increasing acid concentration promoted higher levels of delignification, structural damage, and the breakdown of fiber clumps. Delignification followed by spectrometric analysis and microstructural studies were carried out by light, confocal laser scanning and scanning electron microscopy and showed that the delignification process follows three stages: initial, bulk, and residual. Microscopy techniques and image analysis were efficient tools for microstructural characterization during delignification of agave fibers, allowing quantitative evaluation of the process and the development of linear prediction models. The data obtained integrated numerical and microstructural information that could be valuable for the study of pulping of lignocellulosic materials.

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

Applicability of Cone Beam Computed Tomography to the Assessment of the Vocal Tract before and after Vocal Exercises in Normal Subjects.

PubMed

Garcia, Elisângela Zacanti; Yamashita, Hélio Kiitiro; Garcia, Davi Sousa; Padovani, Marina Martins Pereira; Azevedo, Renata Rangel; Chiari, Brasília Maria

2016-01-01

Cone beam computed tomography (CBCT), which represents an alternative to traditional computed tomography and magnetic resonance imaging, may be a useful instrument to study vocal tract physiology related to vocal exercises. This study aims to evaluate the applicability of CBCT to the assessment of variations in the vocal tract of healthy individuals before and after vocal exercises. Voice recordings and CBCT images before and after vocal exercises performed by 3 speech-language pathologists without vocal complaints were collected and compared. Each participant performed 1 type of exercise, i.e., Finnish resonance tube technique, prolonged consonant "b" technique, or chewing technique. The analysis consisted of an acoustic analysis and tomographic imaging. Modifications of the vocal tract settings following vocal exercises were properly detected by CBCT, and changes in the acoustic parameters were, for the most part, compatible with the variations detected in image measurements. CBCT was shown to be capable of properly assessing the changes in vocal tract settings promoted by vocal exercises. © 2017 S. Karger AG, Basel.

Clinical applications of textural analysis in non-small cell lung cancer.

PubMed

Phillips, Iain; Ajaz, Mazhar; Ezhil, Veni; Prakash, Vineet; Alobaidli, Sheaka; McQuaid, Sarah J; South, Christopher; Scuffham, James; Nisbet, Andrew; Evans, Philip

2018-01-01

Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed "radiomics" and includes semantic and agnostic approaches. Textural analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour. TA is an attractive tool as large existing image sets can be submitted to diverse techniques for data processing, presentation, interpretation and hypothesis testing with annotated clinical outcomes. There is a growing anthology of published data using different TA techniques to differentiate between benign and malignant lung nodules, differentiate tissue subtypes of lung cancer, prognosticate and predict outcome and treatment response, as well as predict treatment side effects and potentially aid radiotherapy planning. The aim of this systematic review is to summarize the current published data and understand the potential future role of TA in managing lung cancer.

A Meta-Analysis Examining the Influence of Pro-Eating Disorder Websites on Body Image and Eating Pathology.

PubMed

Rodgers, Rachel F; Lowy, Alice S; Halperin, Daniella M; Franko, Debra L

2016-01-01

Previous research has indicated that exposure to pro-eating disorder websites might increase eating pathology; however, the magnitude of this effect is unknown. This study aimed to conduct a systematic review and meta-analysis to examine the effect of exposure to pro-eating disorder websites on body image and eating pathology. Studies examining the relationship between exposure to pro-eating disorder websites and eating pathology-related outcomes were included. The systematic review identified nine studies. Findings revealed significant effect sizes of exposure to pro-eating disorder websites on body image dissatisfaction (five studies), d = .41, p = .003; dieting (six studies), d = .68, p < .001, and negative affect (three studies), d = 1.00, p < .001. No effect emerged for bulimic symptoms (four studies), d = .22, p = .73. Findings confirmed the effect of pro-eating disorder websites on body image and eating pathology, highlighting the need for enforceable regulation of these websites. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

Time Series Analysis OF SAR Image Fractal Maps: The Somma-Vesuvio Volcanic Complex Case Study

NASA Astrophysics Data System (ADS)

Pepe, Antonio; De Luca, Claudio; Di Martino, Gerardo; Iodice, Antonio; Manzo, Mariarosaria; Pepe, Susi; Riccio, Daniele; Ruello, Giuseppe; Sansosti, Eugenio; Zinno, Ivana

2016-04-01

The fractal dimension is a significant geophysical parameter describing natural surfaces representing the distribution of the roughness over different spatial scale; in case of volcanic structures, it has been related to the specific nature of materials and to the effects of active geodynamic processes. In this work, we present the analysis of the temporal behavior of the fractal dimension estimates generated from multi-pass SAR images relevant to the Somma-Vesuvio volcanic complex (South Italy). To this aim, we consider a Cosmo-SkyMed data-set of 42 stripmap images acquired from ascending orbits between October 2009 and December 2012. Starting from these images, we generate a three-dimensional stack composed by the corresponding fractal maps (ordered according to the acquisition dates), after a proper co-registration. The time-series of the pixel-by-pixel estimated fractal dimension values show that, over invariant natural areas, the fractal dimension values do not reveal significant changes; on the contrary, over urban areas, it correctly assumes values outside the natural surfaces fractality range and show strong fluctuations. As a final result of our analysis, we generate a fractal map that includes only the areas where the fractal dimension is considered reliable and stable (i.e., whose standard deviation computed over the time series is reasonably small). The so-obtained fractal dimension map is then used to identify areas that are homogeneous from a fractal viewpoint. Indeed, the analysis of this map reveals the presence of two distinctive landscape units corresponding to the Mt. Vesuvio and Gran Cono. The comparison with the (simplified) geological map clearly shows the presence in these two areas of volcanic products of different age. The presented fractal dimension map analysis demonstrates the ability to get a figure about the evolution degree of the monitored volcanic edifice and can be profitably extended in the future to other volcanic systems with very distinctive characteristics, with the aim to perform land classification, such as the identification of areas characterized by similar soil use, slopes and exposures.

Spectral imaging toolbox: segmentation, hyperstack reconstruction, and batch processing of spectral images for the determination of cell and model membrane lipid order.

PubMed

Aron, Miles; Browning, Richard; Carugo, Dario; Sezgin, Erdinc; Bernardino de la Serna, Jorge; Eggeling, Christian; Stride, Eleanor

2017-05-12

Spectral imaging with polarity-sensitive fluorescent probes enables the quantification of cell and model membrane physical properties, including local hydration, fluidity, and lateral lipid packing, usually characterized by the generalized polarization (GP) parameter. With the development of commercial microscopes equipped with spectral detectors, spectral imaging has become a convenient and powerful technique for measuring GP and other membrane properties. The existing tools for spectral image processing, however, are insufficient for processing the large data sets afforded by this technological advancement, and are unsuitable for processing images acquired with rapidly internalized fluorescent probes. Here we present a MATLAB spectral imaging toolbox with the aim of overcoming these limitations. In addition to common operations, such as the calculation of distributions of GP values, generation of pseudo-colored GP maps, and spectral analysis, a key highlight of this tool is reliable membrane segmentation for probes that are rapidly internalized. Furthermore, handling for hyperstacks, 3D reconstruction and batch processing facilitates analysis of data sets generated by time series, z-stack, and area scan microscope operations. Finally, the object size distribution is determined, which can provide insight into the mechanisms underlying changes in membrane properties and is desirable for e.g. studies involving model membranes and surfactant coated particles. Analysis is demonstrated for cell membranes, cell-derived vesicles, model membranes, and microbubbles with environmentally-sensitive probes Laurdan, carboxyl-modified Laurdan (C-Laurdan), Di-4-ANEPPDHQ, and Di-4-AN(F)EPPTEA (FE), for quantification of the local lateral density of lipids or lipid packing. The Spectral Imaging Toolbox is a powerful tool for the segmentation and processing of large spectral imaging datasets with a reliable method for membrane segmentation and no ability in programming required. The Spectral Imaging Toolbox can be downloaded from https://uk.mathworks.com/matlabcentral/fileexchange/62617-spectral-imaging-toolbox .

Effects of dose reduction on bone strength prediction using finite element analysis

NASA Astrophysics Data System (ADS)

Anitha, D.; Subburaj, Karupppasamy; Mei, Kai; Kopp, Felix K.; Foehr, Peter; Noel, Peter B.; Kirschke, Jan S.; Baum, Thomas

2016-12-01

This study aimed to evaluate the effect of dose reduction, by means of tube exposure reduction, on bone strength prediction from finite-element (FE) analysis. Fresh thoracic mid-vertebrae specimens (n = 11) were imaged, using multi-detector computed tomography (MDCT), at different intensities of X-ray tube exposures (80, 150, 220 and 500 mAs). Bone mineral density (BMD) was estimated from the mid-slice of each specimen from MDCT images. Differences in image quality and geometry of each specimen were measured. FE analysis was performed on all specimens to predict fracture load. Paired t-tests were used to compare the results obtained, using the highest CT dose (500 mAs) as reference. Dose reduction had no significant impact on FE-predicted fracture loads, with significant correlations obtained with reference to 500 mAs, for 80 mAs (R2  = 0.997, p < 0.001), 150 mAs (R2 = 0.998, p < 0.001) and 220 mAs (R2 = 0.987, p < 0.001). There were no significant differences in volume quantification between the different doses examined. CT imaging radiation dose could be reduced substantially to 64% with no impact on strength estimates obtained from FE analysis. Reduced CT dose will enable early diagnosis and advanced monitoring of osteoporosis and associated fracture risk.

Relationship between Body Image and Psychological Well-being in Patients with Morbid Obesity.

PubMed

Yazdani, Negar; Hosseini, Sayed Vahid; Amini, Masood; Sobhani, Zahra; Sharif, Farkhondeh; Khazraei, Hajar

2018-04-01

Morbid obesity is rising around the world. It can cause unpleasant appearance and body image. Most of the studies have aimed to evaluate the psychopathology of overweight and obesity and paying attention to mental well-being in morbid obese individuals is rare. Therefore, this study aimed to assess the relationship between body image and psychological well-being in morbid obese patients. This cross-sectional study, using simple random sampling method, was done on 124 morbid obese patients who referred to obesity clinic in Shiraz from 2016 to 2017. The data were collected by body image index and psychological well-being questionnaire. Results were analyzed using descriptive statistics, Pearson correlation coefficient test, ANOVA, and Regression analysis. The results showed a significant relationship between body image and psychological well-being (r=0.43) (P<0.001), and between the total score of the body image and all the subscales of psychological well-being except autonomy and purpose in life (P<0.05). There was also a significant relationship between the total score of psychological well-being and all the subscales of body image (P<0.05). However, there was no significant difference between the mean scores of the body image and those of psychological well-being in different categories of body mass index (BMI) (P>0.05). Final results indicated that body image defects caused by obesity could lie in negative psychological well-being in all aspects. This study can promote health clinicians' knowledge in supporting of mental status of obese individuals. It is suggested that preventing and supporting intervention should be performed as effective methods for encountering and coping with psychological effects of obesity.

An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

PubMed

Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

2017-08-01

Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

An analysis of absorbing image on the Indonesian text by using color matching

NASA Astrophysics Data System (ADS)

Hutagalung, G. A.; Tulus; Iryanto; Lubis, Y. F. A.; Khairani, M.; Suriati

2018-03-01

The insertion of messages in an image is performed by inserting per character message in some pixels. One way of inserting a message into an image is by inserting the ASCII decimal value of a character to the decimal value of the primary color of the image. Messages that use characters in letters, numbers or symbols, where the use of letters of each word is different in number and frequency of use, as well as the use of letters in various messages within each language. In Indonesian language, the use of the letter A to be the most widely used, and the use of other letters greatly affect the clarity of a message or text presented in the language. This study aims to determine the capacity to absorb the message in Indonesian language from an image and what are the things that affect the difference. The data used in this study consists of several images in JPG or JPEG format can be obtained from the image drawing software or hardware of the image makers at different image sizes. The results of testing on four samples of a color image have been obtained by using an image size of 1200 X 1920.

Photography of the histological and radiological analysis of the ligaments of the distal radioulnar joint.

PubMed

Clayton, Gemma

2013-06-01

This project was undertaken as part of the PhD research project of Paul Malone, Pricipal Investigator, Covance plc, Harrogate. Mr Malone approached the photography department for involvement in the study with the aim of settling the current debate on the anatomical and histological features of the distal radioulnar ligaments by capturing the anatomy photographically throughout the process of dissection via a microtome. The author was approached to lead on the photographic protocol as part of her post-graduate certificate training at Staffordshire University. High-resolution digital images of an entire human arm were required, the main area of interest being the distal radioulnar joint of the wrist. Images were to be taken at 40 μm intervals as the specimen was sliced. When microtomy was undertaken through the ligaments images were made at 20 μm intervals. A method of suspending a camera approximately 1 metre above the specimen was devised, together with the preparation for the capture, processing and storage of images. The resulting images were then to be subject to further analysis in the form of 3-Dimensional reconstruction, using computer modelling techniques and software. The possibility of merging the images with sequences obtained from both CT & MRI using image handling software is also an area of exploration, in collaboration with the University of Manchester's Visualisation Centre.

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

PubMed

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

2018-04-01

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

Thermal error analysis and compensation for digital image/volume correlation

NASA Astrophysics Data System (ADS)

Pan, Bing

2018-02-01

Digital image/volume correlation (DIC/DVC) rely on the digital images acquired by digital cameras and x-ray CT scanners to extract the motion and deformation of test samples. Regrettably, these imaging devices are unstable optical systems, whose imaging geometry may undergo unavoidable slight and continual changes due to self-heating effect or ambient temperature variations. Changes in imaging geometry lead to both shift and expansion in the recorded 2D or 3D images, and finally manifest as systematic displacement and strain errors in DIC/DVC measurements. Since measurement accuracy is always the most important requirement in various experimental mechanics applications, these thermal-induced errors (referred to as thermal errors) should be given serious consideration in order to achieve high accuracy, reproducible DIC/DVC measurements. In this work, theoretical analyses are first given to understand the origin of thermal errors. Then real experiments are conducted to quantify thermal errors. Three solutions are suggested to mitigate or correct thermal errors. Among these solutions, a reference sample compensation approach is highly recommended because of its easy implementation, high accuracy and in-situ error correction capability. Most of the work has appeared in our previously published papers, thus its originality is not claimed. Instead, this paper aims to give a comprehensive overview and more insights of our work on thermal error analysis and compensation for DIC/DVC measurements.

Intraoral radiographs texture analysis for dental implant planning.

PubMed

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

2016-11-01

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

The use of fingerprints available on the web in false identity documents: Analysis from a forensic intelligence perspective.

PubMed

Girelli, Carlos Magno Alves

2016-05-01

Fingerprints present in false identity documents were found on the web. In some cases, laterally reversed (mirrored) images of a same fingerprint were observed in different documents. In the present work, 100 fingerprints images downloaded from the web, as well as their reversals obtained by image editing, were compared between themselves and against the database of the Brazilian Federal Police AFIS, in order to better understand trends about this kind of forgery in Brazil. Some image editing effects were observed in the analyzed fingerprints: addition of artifacts (such as watermarks), image rotation, image stylization, lateral reversal and tonal reversal. Discussion about lateral reversals' detection is presented in this article, as well as suggestion to reduce errors due to missed HIT decisions between reversed fingerprints. The present work aims to highlight the importance of the fingerprints' analysis when performing document examination, especially when only copies of documents are available, something very common in Brazil. Besides the intrinsic features of the fingermarks considered in three levels of details by ACE-V methodology, some visual features of the fingerprints images can be helpful to identify sources of forgeries and modus operandi, such as: limits and image contours, fails in the friction ridges caused by excess or lack of inking and presence of watermarks and artifacts arising from the background. Based on the agreement of such features in fingerprints present in different identity documents and also on the analysis of the time and location where the documents were seized, it is possible to highlight potential links between apparently unconnected crimes. Therefore, fingerprints have potential to reduce linkage blindness and the present work suggests the analysis of fingerprints when profiling false identity documents, as well as the inclusion of fingerprints features in the profile of the documents. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

High-Content Microscopy Analysis of Subcellular Structures: Assay Development and Application to Focal Adhesion Quantification.

PubMed

Kroll, Torsten; Schmidt, David; Schwanitz, Georg; Ahmad, Mubashir; Hamann, Jana; Schlosser, Corinne; Lin, Yu-Chieh; Böhm, Konrad J; Tuckermann, Jan; Ploubidou, Aspasia

2016-07-01

High-content analysis (HCA) converts raw light microscopy images to quantitative data through the automated extraction, multiparametric analysis, and classification of the relevant information content. Combined with automated high-throughput image acquisition, HCA applied to the screening of chemicals or RNAi-reagents is termed high-content screening (HCS). Its power in quantifying cell phenotypes makes HCA applicable also to routine microscopy. However, developing effective HCA and bioinformatic analysis pipelines for acquisition of biologically meaningful data in HCS is challenging. Here, the step-by-step development of an HCA assay protocol and an HCS bioinformatics analysis pipeline are described. The protocol's power is demonstrated by application to focal adhesion (FA) detection, quantitative analysis of multiple FA features, and functional annotation of signaling pathways regulating FA size, using primary data of a published RNAi screen. The assay and the underlying strategy are aimed at researchers performing microscopy-based quantitative analysis of subcellular features, on a small scale or in large HCS experiments. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Second consensus on the assessment of sublingual microcirculation in critically ill patients: results from a task force of the European Society of Intensive Care Medicine.

PubMed

Ince, Can; Boerma, E Christiaan; Cecconi, Maurizio; De Backer, Daniel; Shapiro, Nathan I; Duranteau, Jacques; Pinsky, Michael R; Artigas, Antonio; Teboul, Jean-Louis; Reiss, Irwin K M; Aldecoa, Cesar; Hutchings, Sam D; Donati, Abele; Maggiorini, Marco; Taccone, Fabio S; Hernandez, Glenn; Payen, Didier; Tibboel, Dick; Martin, Daniel S; Zarbock, Alexander; Monnet, Xavier; Dubin, Arnaldo; Bakker, Jan; Vincent, Jean-Louis; Scheeren, Thomas W L

2018-03-01

Hand-held vital microscopes (HVMs) were introduced to observe sublingual microcirculatory alterations at the bedside in different shock states in critically ill patients. This consensus aims to provide clinicians with guidelines for practical use and interpretation of the sublingual microcirculation. Furthermore, it aims to promote the integration of routine application of HVM microcirculatory monitoring in conventional hemodynamic monitoring of systemic hemodynamic variables. In accordance with the Delphi method we organized three international expert meetings to discuss the various aspects of the technology, physiology, measurements, and clinical utility of HVM sublingual microcirculatory monitoring to formulate this consensus document. A task force from the Cardiovascular Dynamics Section of the European Society of Intensive Care Medicine (with endorsement of its Executive Committee) created this consensus as an update of a previous consensus in 2007. We classified consensus statements as definitions, requirements, and/or recommendations, with a minimum requirement of 80% agreement of all participants. In this consensus the nature of microcirculatory alterations is described. The nature of variables, which can be extracted from analysis of microcirculatory images, is presented and the needed dataset of variables to identify microcirculatory alterations is defined. Practical aspects of sublingual HVM measurements and the nature of artifacts are described. Eleven statements were formulated that pertained to image acquisitions and quality statements. Fourteen statements addressed the analysis of the images, and 13 statements are related to future developments. This consensus describes 25 statements regarding the acquisition and interpretation of microcirculatory images needed to guide the assessment of the microcirculation in critically ill patients.

Optical differentiation between malignant and benign lymphadenopathy by grey scale texture analysis of endobronchial ultrasound convex probe images.

PubMed

Nguyen, Phan; Bashirzadeh, Farzad; Hundloe, Justin; Salvado, Olivier; Dowson, Nicholas; Ware, Robert; Masters, Ian Brent; Bhatt, Manoj; Kumar, Aravind Ravi; Fielding, David

2012-03-01

Morphologic and sonographic features of endobronchial ultrasound (EBUS) convex probe images are helpful in predicting metastatic lymph nodes. Grey scale texture analysis is a well-established methodology that has been applied to ultrasound images in other fields of medicine. The aim of this study was to determine if this methodology could differentiate between benign and malignant lymphadenopathy of EBUS images. Lymph nodes from digital images of EBUS procedures were manually mapped to obtain a region of interest and were analyzed in a prediction set. The regions of interest were analyzed for the following grey scale texture features in MATLAB (version 7.8.0.347 [R2009a]): mean pixel value, difference between maximal and minimal pixel value, SEM pixel value, entropy, correlation, energy, and homogeneity. Significant grey scale texture features were used to assess a validation set compared with fluoro-D-glucose (FDG)-PET-CT scan findings where available. Fifty-two malignant nodes and 48 benign nodes were in the prediction set. Malignant nodes had a greater difference in the maximal and minimal pixel values, SEM pixel value, entropy, and correlation, and a lower energy (P < .0001 for all values). Fifty-one lymph nodes were in the validation set; 44 of 51 (86.3%) were classified correctly. Eighteen of these lymph nodes also had FDG-PET-CT scan assessment, which correctly classified 14 of 18 nodes (77.8%), compared with grey scale texture analysis, which correctly classified 16 of 18 nodes (88.9%). Grey scale texture analysis of EBUS convex probe images can be used to differentiate malignant and benign lymphadenopathy. Preliminary results are comparable to FDG-PET-CT scan.

The caBIG annotation and image Markup project.

PubMed

Channin, David S; Mongkolwat, Pattanasak; Kleper, Vladimir; Sepukar, Kastubh; Rubin, Daniel L

2010-04-01

Image annotation and markup are at the core of medical interpretation in both the clinical and the research setting. Digital medical images are managed with the DICOM standard format. While DICOM contains a large amount of meta-data about whom, where, and how the image was acquired, DICOM says little about the content or meaning of the pixel data. An image annotation is the explanatory or descriptive information about the pixel data of an image that is generated by a human or machine observer. An image markup is the graphical symbols placed over the image to depict an annotation. While DICOM is the standard for medical image acquisition, manipulation, transmission, storage, and display, there are no standards for image annotation and markup. Many systems expect annotation to be reported verbally, while markups are stored in graphical overlays or proprietary formats. This makes it difficult to extract and compute with both of them. The goal of the Annotation and Image Markup (AIM) project is to develop a mechanism, for modeling, capturing, and serializing image annotation and markup data that can be adopted as a standard by the medical imaging community. The AIM project produces both human- and machine-readable artifacts. This paper describes the AIM information model, schemas, software libraries, and tools so as to prepare researchers and developers for their use of AIM.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

Tradeoff between noise reduction and inartificial visualization in a model-based iterative reconstruction algorithm on coronary computed tomography angiography.

PubMed

Hirata, Kenichiro; Utsunomiya, Daisuke; Kidoh, Masafumi; Funama, Yoshinori; Oda, Seitaro; Yuki, Hideaki; Nagayama, Yasunori; Iyama, Yuji; Nakaura, Takeshi; Sakabe, Daisuke; Tsujita, Kenichi; Yamashita, Yasuyuki

2018-05-01

We aimed to evaluate the image quality performance of coronary CT angiography (CTA) under the different settings of forward-projected model-based iterative reconstruction solutions (FIRST).Thirty patients undergoing coronary CTA were included. Each image was reconstructed using filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR-3D), and 2 model-based iterative reconstructions including FIRST-body and FIRST-cardiac sharp (CS). CT number and noise were measured in the coronary vessels and plaque. Subjective image-quality scores were obtained for noise and structure visibility.In the objective image analysis, FIRST-body produced the significantly highest contrast-to-noise ratio. Regarding subjective image quality, FIRST-CS had the highest score for structure visibility, although the image noise score was inferior to that of FIRST-body.In conclusion, FIRST provides significant improvements in objective and subjective image quality compared with FBP and AIDR-3D. FIRST-body effectively reduces image noise, but the structure visibility with FIRST-CS was superior to FIRST-body.

Evaluation of three methods for retrospective correction of vignetting on medical microscopy images utilizing two open source software tools.

PubMed

Babaloukas, Georgios; Tentolouris, Nicholas; Liatis, Stavros; Sklavounou, Alexandra; Perrea, Despoina

2011-12-01

Correction of vignetting on images obtained by a digital camera mounted on a microscope is essential before applying image analysis. The aim of this study is to evaluate three methods for retrospective correction of vignetting on medical microscopy images and compare them with a prospective correction method. One digital image from four different tissues was used and a vignetting effect was applied on each of these images. The resulted vignetted image was replicated four times and in each replica a different method for vignetting correction was applied with fiji and gimp software tools. The highest peak signal-to-noise ratio from the comparison of each method to the original image was obtained from the prospective method in all tissues. The morphological filtering method provided the highest peak signal-to-noise ratio value amongst the retrospective methods. The prospective method is suggested as the method of choice for correction of vignetting and if it is not applicable, then the morphological filtering may be suggested as the retrospective alternative method. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.

Advanced Weapon System (AWS) Sensor Prediction Techniques Study. Volume II

DTIC Science & Technology

1981-09-01

models are suggested. TV. 1-1 ’ICourant Com’p’uter Sctence Report #9 December 1975 Scene Analysis: A Survey Carl Weiman Cou rant Institute of...some crucial differences. In the psycho- logical model of mechanical vision, the aim of scene analysis is to perceive and understand 2-0 images of 3-D...scenes. The meaning of this analogy can be clarified using a rudimentary informational model ; this yields a natural hierarchy from physical

Ischemic colitis in five points: an update 2013.

PubMed

Rania, Hefaiedh; Mériam, Sabbah; Rym, Ennaifer; Hyafa, Romdhane; Amine, Attaoui; Najet, Bel Hadj; Lassad, Gharbi; Mohamed, Taher Khalfallah

2014-05-01

Ischemic colitis is the most common form of intestinal ischemia. The presence of diarrhea and mild lower gastrointestinal bleeding should guide the diagnosis. Although many laboratory tests and radiographic images may suggest the diagnosis, colonic endoscopic with histological analysis of biopsies is the gold standard for identification of colonic ischemia. aim : The aim of this study was to resume in 5 points: the epidemiology, the clinical features, the diagnostic approach and the management of ischemic colitis in five points. methods: Review of literature. results: Incidence of ischemic colitis was between 3 and 10%. The clinical presentation is predominated by the non gangrenous form associating abdominal pain, tenderness, diarrhea and lower gastrointestinal bleeding. The most frequent causes are represented by systemic hypoperfusion. Laboratory tests can orientate the diagnosis but are unspecific. Radiographic images based on computed tomography or more recently magnetic resonance imaging may suggest the diagnosis, but the confirmation will be given by endoscopic visualization of colonic mucosa with histological analysis of biopsies. Conservative treatment is the most often sufficient to improve colonic lesions. Surgical treatment is reserved for perforations and strictures. The incidence of colonic ischemia is difficult to ascertain. The diagnosis is usually made by medical history, examination, and endoscopy which have become the diagnostic procedure of choice. A high index of suspicion and prompt management are essential for optimum outcomes in patients with colonic ischemia.

Investigating Gravity Waves in Polar Mesospheric Clouds Using Tomographic Reconstructions of AIM Satellite Imagery

NASA Astrophysics Data System (ADS)

Hart, V. P.; Taylor, M. J.; Doyle, T. E.; Zhao, Y.; Pautet, P.-D.; Carruth, B. L.; Rusch, D. W.; Russell, J. M.

2018-01-01

This research presents the first application of tomographic techniques for investigating gravity wave structures in polar mesospheric clouds (PMCs) imaged by the Cloud Imaging and Particle Size instrument on the NASA AIM satellite. Albedo data comprising consecutive PMC scenes were used to tomographically reconstruct a 3-D layer using the Partially Constrained Algebraic Reconstruction Technique algorithm and a previously developed "fanning" technique. For this pilot study, a large region (760 × 148 km) of the PMC layer (altitude 83 km) was sampled with a 2 km horizontal resolution, and an intensity weighted centroid technique was developed to create novel 2-D surface maps, characterizing the individual gravity waves as well as their altitude variability. Spectral analysis of seven selected wave events observed during the Northern Hemisphere 2007 PMC season exhibited dominant horizontal wavelengths of 60-90 km, consistent with previous studies. These tomographic analyses have enabled a broad range of new investigations. For example, a clear spatial anticorrelation was observed between the PMC albedo and wave-induced altitude changes, with higher-albedo structures aligning well with wave troughs, while low-intensity regions aligned with wave crests. This result appears to be consistent with current theories of PMC development in the mesopause region. This new tomographic imaging technique also provides valuable wave amplitude information enabling further mesospheric gravity wave investigations, including quantitative analysis of their hemispheric and interannual characteristics and variations.

How automated image analysis techniques help scientists in species identification and classification?

PubMed

Yousef Kalafi, Elham; Town, Christopher; Kaur Dhillon, Sarinder

2017-09-04

Identification of taxonomy at a specific level is time consuming and reliant upon expert ecologists. Hence the demand for automated species identification increased over the last two decades. Automation of data classification is primarily focussed on images, incorporating and analysing image data has recently become easier due to developments in computational technology. Research efforts in identification of species include specimens' image processing, extraction of identical features, followed by classifying them into correct categories. In this paper, we discuss recent automated species identification systems, categorizing and evaluating their methods. We reviewed and compared different methods in step by step scheme of automated identification and classification systems of species images. The selection of methods is influenced by many variables such as level of classification, number of training data and complexity of images. The aim of writing this paper is to provide researchers and scientists an extensive background study on work related to automated species identification, focusing on pattern recognition techniques in building such systems for biodiversity studies.

Biomedical imaging ontologies: A survey and proposal for future work

PubMed Central

Smith, Barry; Arabandi, Sivaram; Brochhausen, Mathias; Calhoun, Michael; Ciccarese, Paolo; Doyle, Scott; Gibaud, Bernard; Goldberg, Ilya; Kahn, Charles E.; Overton, James; Tomaszewski, John; Gurcan, Metin

2015-01-01

Background: Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical definitions thereby also supporting reasoning over the tagged data. Aim: This paper provides a survey of the biomedical imaging ontologies that have been developed thus far. It outlines the challenges, particularly faced by ontologies in the fields of histopathological imaging and image analysis, and suggests a strategy for addressing these challenges in the example domain of quantitative histopathology imaging. Results and Conclusions: The ultimate goal is to support the multiscale understanding of disease that comes from using interoperable ontologies to integrate imaging data with clinical and genomics data. PMID:26167381

Mixture of learners for cancer stem cell detection using CD13 and H and E stained images

NASA Astrophysics Data System (ADS)

Oǧuz, Oǧuzhan; Akbaş, Cem Emre; Mallah, Maen; Taşdemir, Kasım.; Akhan Güzelcan, Ece; Muenzenmayer, Christian; Wittenberg, Thomas; Üner, Ayşegül; Cetin, A. E.; ćetin Atalay, Rengül

2016-03-01

In this article, algorithms for cancer stem cell (CSC) detection in liver cancer tissue images are developed. Conventionally, a pathologist examines of cancer cell morphologies under microscope. Computer aided diagnosis systems (CAD) aims to help pathologists in this tedious and repetitive work. The first algorithm locates CSCs in CD13 stained liver tissue images. The method has also an online learning algorithm to improve the accuracy of detection. The second family of algorithms classify the cancer tissues stained with H and E which is clinically routine and cost effective than immunohistochemistry (IHC) procedure. The algorithms utilize 1D-SIFT and Eigen-analysis based feature sets as descriptors. Normal and cancerous tissues can be classified with 92.1% accuracy in H and E stained images. Classification accuracy of low and high-grade cancerous tissue images is 70.4%. Therefore, this study paves the way for diagnosing the cancerous tissue and grading the level of it using H and E stained microscopic tissue images.

Optical design of ultrashort throw liquid crystal on silicon projection system

NASA Astrophysics Data System (ADS)

Huang, Jiun-Woei

2017-05-01

An ultrashort throw liquid crystal on silicon (LCoS) projector for home cinema, virtual reality, and automobile heads-up display has been designed and fabricated. To achieve the best performance and highest-quality image, this study aimed to design wide-angle projection optics and optimize the illumination for LCoS. Based on the telecentric lens projection system and optimized Koehler illumination, the optical parameters were calculated. The projector's optical system consisted of a conic aspheric mirror and image optics using either symmetric double Gauss or a large-angle eyepiece to achieve a full projection angle larger than 155 deg. By applying Koehler illumination, image resolution was enhanced and the modulation transfer function of the image in high spatial frequency was increased to form a high-quality illuminated image. The partial coherence analysis verified that the design was capable of 2.5 lps/mm within a 2 m×1.5 m projected image. The throw ratio was less than 0.25 in HD format.

How scary! An analysis of visual communication concerning genetically modified organisms in Italy.

PubMed

Ventura, Vera; Frisio, Dario G; Ferrazzi, Giovanni; Siletti, Elena

2017-07-01

Several studies provide evidence of the role of written communication in influencing public perception towards genetically modified organisms, whereas visual communication has been sparsely investigated. This article aims to evaluate the exposure of the Italian population to scary genetically modified organism-related images. A set of 517 images collected through Google are classified considering fearful attributes, and an index that accounts for the scary impact of these images is built. Then, through an ordinary least-squares regression, we estimate the relationship between the Scary Impact Index and a set of variables that describes the context in which the images appear. The results reveal that the first (and most viewed) Google result images contain the most frightful contents. In addition, the agri-food sector in Italy is strongly oriented towards offering a negative representation of genetically modified organisms. Exposure to scary images could be a factor that affects the negative perception of genetically modified organisms in Italy.

Fourier Ptychographic Microscopy for Rapid, High-Resolution Imaging of Circulating Tumor Cells Enriched by Microfiltration.

PubMed

Williams, Anthony; Chung, Jaebum; Yang, Changhuei; Cote, Richard J

2017-01-01

Examining the hematogenous compartment for evidence of metastasis has increased significantly within the oncology research community in recent years, due to the development of technologies aimed at the enrichment of circulating tumor cells (CTCs), the subpopulation of primary tumor cells that gain access to the circulatory system and are responsible for colonization at distant sites. In contrast to other technologies, filtration-based CTC enrichment, which exploits differences in size between larger tumor cells and surrounding smaller, non-tumor blood cells, has the potential to improve CTC characterization through isolation of tumor cell populations with greater molecular heterogeneity. However, microscopic analysis of uneven filtration surfaces containing CTCs is laborious, time-consuming, and inconsistent, preventing widespread use of filtration-based enrichment technologies. Here, integrated with a microfiltration-based CTC and rare cell enrichment device we have previously described, we present a protocol for Fourier Ptychographic Microscopy (FPM), a method that, unlike many automated imaging platforms, produces high-speed, high-resolution images that can be digitally refocused, allowing users to observe objects of interest present on multiple focal planes within the same image frame. The development of a cost-effective and high-throughput CTC analysis system for filtration-based enrichment technologies could have profound clinical implications for improved CTC detection and analysis.

Structural Connectivity Changes Underlying Altered Working Memory Networks in Mild Cognitive Impairment: A Three-Way Image Fusion Analysis.

PubMed

Teipel, Stefan; Ehlers, Inga; Erbe, Anna; Holzmann, Carsten; Lau, Esther; Hauenstein, Karlheinz; Berger, Christoph

2015-01-01

Working memory impairment is among the earliest signs of cognitive decline in Alzheimer's disease (AD) and mild cognitive impairment (MCI). We aimed to study the functional and structural substrate of working memory impairment in early AD dementia and MCI. We studied a group of 12 MCI and AD subjects compared to 12 age- and gender-matched healthy elderly controls using diffusion tensor imaging (DTI), and functional magnetic resonance imaging (fMRI) during a 2-back versus 1-back letter recognition task. We performed a three-way image fusion analysis with joint independent component analysis of cortical activation during working memory, and DTI derived measures of fractional anisotropy (FA) and the mode of anisotropy. We found significant hypoactivation in posterior brain areas and relative hyperactivation in anterior brain areas during working memory in AD/MCI subjects compared to controls. Corresponding independent components from DTI data revealed reduced FA and reduced mode of anisotropy in intracortical projecting fiber tracts with posterior predominance and increased FA and increased mode along the corticospinal tract in AD/MCI compared to controls. Our findings suggest that impairments of structural fiber tract integrity accompany breakdown of posterior and relatively preserved anterior cortical activation during working memory performance in MCI/AD subjects. Copyright © 2014 by the American Society of Neuroimaging.

Accuracy of a remote quantitative image analysis in the whole slide images.

PubMed

Słodkowska, Janina; Markiewicz, Tomasz; Grala, Bartłomiej; Kozłowski, Wojciech; Papierz, Wielisław; Pleskacz, Katarzyna; Murawski, Piotr

2011-03-30

The rationale for choosing a remote quantitative method supporting a diagnostic decision requires some empirical studies and knowledge on scenarios including valid telepathology standards. The tumours of the central nervous system [CNS] are graded on the base of the morphological features and the Ki-67 labelling Index [Ki-67 LI]. Various methods have been applied for Ki-67 LI estimation. Recently we have introduced the Computerized Analysis of Medical Images [CAMI] software for an automated Ki-67 LI counting in the digital images. Aims of our study was to explore the accuracy and reliability of a remote assessment of Ki-67 LI with CAMI software applied to the whole slide images [WSI]. The WSI representing CNS tumours: 18 meningiomas and 10 oligodendrogliomas were stored on the server of the Warsaw University of Technology. The digital copies of entire glass slides were created automatically by the Aperio ScanScope CS with objective 20x or 40x. Aperio's Image Scope software provided functionality for a remote viewing of WSI. The Ki-67 LI assessment was carried on within 2 out of 20 selected fields of view (objective 40x) representing the highest labelling areas in each WSI. The Ki-67 LI counting was performed by 3 various methods: 1) the manual reading in the light microscope - LM, 2) the automated counting with CAMI software on the digital images - DI , and 3) the remote quantitation on the WSIs - as WSI method. The quality of WSIs and technical efficiency of the on-line system were analysed. The comparative statistical analysis was performed for the results obtained by 3 methods of Ki-67 LI counting. The preliminary analysis showed that in 18% of WSI the results of Ki-67 LI differed from those obtained in other 2 methods of counting when the quality of the glass slides was below the standard range. The results of our investigations indicate that the remote automated Ki-67 LI analysis performed with the CAMI algorithm on the whole slide images of meningiomas and oligodendrogliomas could be successfully used as an alternative method to the manual reading as well as to the digital images quantitation with CAMI software. According to our observation a need of a remote supervision/consultation and training for the effective use of remote quantitative analysis of WSI is necessary.

Support vector machine as a binary classifier for automated object detection in remotely sensed data

NASA Astrophysics Data System (ADS)

Wardaya, P. D.

2014-02-01

In the present paper, author proposes the application of Support Vector Machine (SVM) for the analysis of satellite imagery. One of the advantages of SVM is that, with limited training data, it may generate comparable or even better results than the other methods. The SVM algorithm is used for automated object detection and characterization. Specifically, the SVM is applied in its basic nature as a binary classifier where it classifies two classes namely, object and background. The algorithm aims at effectively detecting an object from its background with the minimum training data. The synthetic image containing noises is used for algorithm testing. Furthermore, it is implemented to perform remote sensing image analysis such as identification of Island vegetation, water body, and oil spill from the satellite imagery. It is indicated that SVM provides the fast and accurate analysis with the acceptable result.

Optimally weighted least-squares steganalysis

NASA Astrophysics Data System (ADS)

Ker, Andrew D.

2007-02-01

Quantitative steganalysis aims to estimate the amount of payload in a stego object, and such estimators seem to arise naturally in steganalysis of Least Significant Bit (LSB) replacement in digital images. However, as with all steganalysis, the estimators are subject to errors, and their magnitude seems heavily dependent on properties of the cover. In very recent work we have given the first derivation of estimation error, for a certain method of steganalysis (the Least-Squares variant of Sample Pairs Analysis) of LSB replacement steganography in digital images. In this paper we make use of our theoretical results to find an improved estimator and detector. We also extend the theoretical analysis to another (more accurate) steganalysis estimator (Triples Analysis) and hence derive an improved version of that estimator too. Experimental results show that the new steganalyzers have improved accuracy, particularly in the difficult case of never-compressed covers.

Collaborative real-time motion video analysis by human observer and image exploitation algorithms

NASA Astrophysics Data System (ADS)

Hild, Jutta; Krüger, Wolfgang; Brüstle, Stefan; Trantelle, Patrick; Unmüßig, Gabriel; Heinze, Norbert; Peinsipp-Byma, Elisabeth; Beyerer, Jürgen

2015-05-01

Motion video analysis is a challenging task, especially in real-time applications. In most safety and security critical applications, a human observer is an obligatory part of the overall analysis system. Over the last years, substantial progress has been made in the development of automated image exploitation algorithms. Hence, we investigate how the benefits of automated video analysis can be integrated suitably into the current video exploitation systems. In this paper, a system design is introduced which strives to combine both the qualities of the human observer's perception and the automated algorithms, thus aiming to improve the overall performance of a real-time video analysis system. The system design builds on prior work where we showed the benefits for the human observer by means of a user interface which utilizes the human visual focus of attention revealed by the eye gaze direction for interaction with the image exploitation system; eye tracker-based interaction allows much faster, more convenient, and equally precise moving target acquisition in video images than traditional computer mouse selection. The system design also builds on prior work we did on automated target detection, segmentation, and tracking algorithms. Beside the system design, a first pilot study is presented, where we investigated how the participants (all non-experts in video analysis) performed in initializing an object tracking subsystem by selecting a target for tracking. Preliminary results show that the gaze + key press technique is an effective, efficient, and easy to use interaction technique when performing selection operations on moving targets in videos in order to initialize an object tracking function.

Global analysis of gully composition using manual and automated exploration of CRISM imagery

NASA Astrophysics Data System (ADS)

Allender, Elyse; Stepinski, Tomasz F.

2018-03-01

Gully formations on Mars have been the focus of many morphological and mineralogical studies aimed at inferring the mechanisms of their formation and evolution. In this paper we have analyzed 354 globally distributed gully-bearing Full Resolution Targeted (FRT) Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) images. The primary goal of the analysis was to identify all spectrally distinct deposits in these images (if any) and to classify them into hydrated and non-hydrated categories using only CRISM summary parameters (Viviano-Beck et al., 2014). Such approach makes possible to analyze a very large set of all distinct deposits in 354 images. We found that 68% of these images lack any distinct deposits, 8% of images contain non-hydrated deposits which coincide with the gullies and 24% of images contain hydrated deposits which coincide with the gullies. These results are compared with the recent analysis of 110 CRISM images by Nuñez et al. (2016) who also found that most gullies coincide with indistinct deposits, but, contrary to our findings, they found a predominance of non-hydrated minerals among distinct deposits. We attribute this discrepancy in part to their smaller and geographically biased sample of images, and in part to differing protocols of categorizing images. The discrepancy between the two surveys is further increased if we count all deposits in FRT gully-bearing images, not just deposits directly coinciding with the gullies, obtaining 44% indistinct, 15% non-hydrated, and 41% hydrated images. The secondary goal of this study was to perform the same image survey using a recently developed automated method in order to assess its accuracy and thus its feasibility for performing future surveys. We found the overall accuracy of the auto-mapper to be 76.2% but its accuracy for discovering distinct deposits, and in particular, distinct hydrated deposits was lower. We attributed the deficiencies of the auto-mapper primarily to its sensitivity to presence of noise in images and especially to presence of speckle noise. It is however worth noting that qualitatively both manual and automatic surveys arrived at the same overall conclusion.

Body Image of Women Submitted to Breast Cancer Treatment

PubMed

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

2018-06-25

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

Comparative analysis of methods for extracting vessel network on breast MRI images

NASA Astrophysics Data System (ADS)

Gaizer, Bence T.; Vassiou, Katerina G.; Lavdas, Eleftherios; Arvanitis, Dimitrios L.; Fezoulidis, Ioannis V.; Glotsos, Dimitris T.

2017-11-01

Digital processing of MRI images aims to provide an automatized diagnostic evaluation of regular health screenings. Cancerous lesions are proven to cause an alteration in the vessel structure of the diseased organ. Currently there are several methods used for extraction of the vessel network in order to quantify its properties. In this work MRI images (Signa HDx 3.0T, GE Healthcare, courtesy of University Hospital of Larissa) of 30 female breasts were subjected to three different vessel extraction algorithms to determine the location of their vascular network. The first method is an experiment to build a graph over known points of the vessel network; the second algorithm aims to determine the direction and diameter of vessels at these points; the third approach is a seed growing algorithm, spreading selection to neighbors of the known vessel pixels. The possibilities shown by the different methods were analyzed, and quantitative measurements were performed. The data provided by these measurements showed no clear correlation with the presence or malignancy of tumors, based on the radiological diagnosis of skilled physicians.

A Novel Imaging Analysis Method for Capturing Pharyngeal Constriction During Swallowing.

PubMed

Schwertner, Ryan W; Garand, Kendrea L; Pearson, William G

2016-01-01

Videofluoroscopic imaging of swallowing known as the Modified Barium Study (MBS) is the standard of care for assessing swallowing difficulty. While the clinical purpose of this radiographic imaging is to primarily assess aspiration risk, valuable biomechanical data is embedded in these studies. Computational analysis of swallowing mechanics (CASM) is an established research methodology for assessing multiple interactions of swallowing mechanics based on coordinates mapping muscle function including hyolaryngeal movement, pharyngeal shortening, tongue base retraction, and extension of the head and neck, however coordinates characterizing pharyngeal constriction is undeveloped. The aim of this study was to establish a method for locating the superior and middle pharyngeal constrictors using hard landmarks as guides on MBS videofluoroscopic imaging, and to test the reliability of this new method. Twenty de-identified, normal, MBS videos were randomly selected from a database. Two raters annotated landmarks for the superior and middle pharyngeal constrictors frame-by-frame using a semi-automated MATLAB tracker tool at two time points. Intraclass correlation coefficients were used to assess test-retest reliability between two raters with an ICC = 0.99 or greater for all coordinates for the retest measurement. MorphoJ integrated software was used to perform a discriminate function analysis to visualize how all 12 coordinates interact with each other in normal swallowing. The addition of the superior and middle pharyngeal constrictor coordinates to CASM allows for a robust analysis of the multiple components of swallowing mechanics interacting with a wide range of variables in both patient specific and cohort studies derived from common use imaging data.

A Novel Imaging Analysis Method for Capturing Pharyngeal Constriction During Swallowing

PubMed Central

Schwertner, Ryan W.; Garand, Kendrea L.; Pearson, William G.

2016-01-01

Videofluoroscopic imaging of swallowing known as the Modified Barium Study (MBS) is the standard of care for assessing swallowing difficulty. While the clinical purpose of this radiographic imaging is to primarily assess aspiration risk, valuable biomechanical data is embedded in these studies. Computational analysis of swallowing mechanics (CASM) is an established research methodology for assessing multiple interactions of swallowing mechanics based on coordinates mapping muscle function including hyolaryngeal movement, pharyngeal shortening, tongue base retraction, and extension of the head and neck, however coordinates characterizing pharyngeal constriction is undeveloped. The aim of this study was to establish a method for locating the superior and middle pharyngeal constrictors using hard landmarks as guides on MBS videofluoroscopic imaging, and to test the reliability of this new method. Twenty de-identified, normal, MBS videos were randomly selected from a database. Two raters annotated landmarks for the superior and middle pharyngeal constrictors frame-by-frame using a semi-automated MATLAB tracker tool at two time points. Intraclass correlation coefficients were used to assess test-retest reliability between two raters with an ICC = 0.99 or greater for all coordinates for the retest measurement. MorphoJ integrated software was used to perform a discriminate function analysis to visualize how all 12 coordinates interact with each other in normal swallowing. The addition of the superior and middle pharyngeal constrictor coordinates to CASM allows for a robust analysis of the multiple components of swallowing mechanics interacting with a wide range of variables in both patient specific and cohort studies derived from common use imaging data. PMID:28239682

Representations of Codeine Misuse on Instagram: Content Analysis.

PubMed

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

2018-03-20

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

Stereoscopic Machine-Vision System Using Projected Circles

NASA Technical Reports Server (NTRS)

Mackey, Jeffrey R.

2010-01-01

A machine-vision system capable of detecting obstacles large enough to damage or trap a robotic vehicle is undergoing development. The system includes (1) a pattern generator that projects concentric circles of laser light forward onto the terrain, (2) a stereoscopic pair of cameras that are aimed forward to acquire images of the circles, (3) a frame grabber and digitizer for acquiring image data from the cameras, and (4) a single-board computer that processes the data. The system is being developed as a prototype of machine- vision systems to enable robotic vehicles ( rovers ) on remote planets to avoid craters, large rocks, and other terrain features that could capture or damage the vehicles. Potential terrestrial applications of systems like this one could include terrain mapping, collision avoidance, navigation of robotic vehicles, mining, and robotic rescue. This system is based partly on the same principles as those of a prior stereoscopic machine-vision system in which the cameras acquire images of a single stripe of laser light that is swept forward across the terrain. However, this system is designed to afford improvements over some of the undesirable features of the prior system, including the need for a pan-and-tilt mechanism to aim the laser to generate the swept stripe, ambiguities in interpretation of the single-stripe image, the time needed to sweep the stripe across the terrain and process the data from many images acquired during that time, and difficulty of calibration because of the narrowness of the stripe. In this system, the pattern generator does not contain any moving parts and need not be mounted on a pan-and-tilt mechanism: the pattern of concentric circles is projected steadily in the forward direction. The system calibrates itself by use of data acquired during projection of the concentric-circle pattern onto a known target representing flat ground. The calibration- target image data are stored in the computer memory for use as a template in processing terrain images. During operation on terrain, the images acquired by the left and right cameras are analyzed. The analysis includes (1) computation of the horizontal and vertical dimensions and the aspect ratios of rectangles that bound the circle images and (2) comparison of these aspect ratios with those of the template. Coordinates of distortions of the circles are used to identify and locate objects. If the analysis leads to identification of an object of significant size, then stereoscopicvision algorithms are used to estimate the distance to the object. The time taken in performing this analysis on a single pair of images acquired by the left and right cameras in this system is a fraction of the time taken in processing the many pairs of images acquired in a sweep of the laser stripe across the field of view in the prior system. The results of the analysis include data on sizes and shapes of, and distances and directions to, objects. Coordinates of objects are updated as the vehicle moves so that intelligent decisions regarding speed and direction can be made. The results of the analysis are utilized in a computational decision-making process that generates obstacle-avoidance data and feeds those data to the control system of the robotic vehicle.

Different Aspects of Secondary School Students' Mental Frameworks Related to Concept of Scientist

ERIC Educational Resources Information Center

Karaçam, Sedat

2015-01-01

The aim of this study is to examine secondary school students' images and conceptualisations about scientists by contextual data analysis, and to determine relationships between them. The respondents were 356 students attending 6th and 7th grades of secondary school in Duzce. Tests were conducted during 2013-2014 academic year. Students' images…

[2008 Shanghai Customer Satisfaction Survey report of after-sales service for medical imaging equipments].

PubMed

Li, Bin; Wang, Li-Jun; Zhang, Li-Fang; Qian, Jian-Guo; Zheng, Jia-Gang; Zhu, Gao-Jie; He, De-Hua; Xu, Zi-Tian

2009-07-01

To improve the after-sales service, a survey aimed at the after-serveis of 3 kinds of medical equipment is applied among 68 hospitals in Shanghai Area in 2008.The Stat. and analysis results are showed in the paper, which will certainly channel off suppliers to set up a harmonious market together.

The Representation of Islam in the Hungarian Geography Textbooks

ERIC Educational Resources Information Center

Császár, Zsuzsu M.; Vati, Tamás

2012-01-01

This research has been seeking an answer to the question about what kind of image of the Islam is conveyed by the most popular and densely used textbooks to students. In the course of analysis, primary and secondary schools textbooks were examined via quantitative and qualitative methods. The objective demonstration of the research results aims to…

The New Approach to Sport Medicine: 3-D Reconstruction

ERIC Educational Resources Information Center

Ince, Alparslan

2015-01-01

The aim of this study is to present a new approach to sport medicine. Comparative analysis of the Vertebrae Lumbales was done in sedentary group and Muay Thai athletes. It was done by acquiring three dimensional (3-D) data and models through photogrammetric methods from the Multi-detector Computerized Tomography (MDCT) images of the Vertebrae…

An Analysis of Conceptual Flow Patterns and Structures in the Physics Classroom

ERIC Educational Resources Information Center

Eshach, Haim

2010-01-01

The aim of the current research is to characterize the conceptual flow processes occurring in whole-class dialogic discussions with a high level of interanimation; in the present case, of a high-school class learning about image creation on plane mirrors. Using detailed chains of interaction and conceptual flow discourse maps--both developed for…

Follow-Up Imaging of Inflammatory Myofibroblastic Tumor of the Uterus and Its Spontaneous Regression

PubMed Central

Markovic Vasiljkovic, Biljana; Plesinac Karapandzic, Vesna; Pejcic, Tomislav; Djuric Stefanovic, Aleksandra; Milosevic, Zorica; Plesinac, Snezana

2016-01-01

Inflammatory myofibroblastic tumor (IMT) is an aggressive benign mass that may arise from various tissues and organs with a great variability of histological and clinical appearances. Due to variable and nonspecific imaging findings, diagnosis of IMT is not obtained before surgery. The aim of this paper is to present CT and MRI findings during four-year follow-up of complete, spontaneous regression of IMT of the uterus. The diagnosis was made by histology and immunohistochemistry analysis of the open excisional biopsy specimen. At that time, the organ of origin was not specified. After analysis of the follow-up imaging findings and the mode of tumor regression, the uterus was proclaimed as the probable site of origin. IMT of the uterus is extremely rare and has been reported in ten cases up to now. The gradual, complete regression of uterine IMT documented by CT and MRI may contribute to understanding of its nature. PMID:27110328

Neural image analysis in the process of quality assessment: domestic pig oocytes

NASA Astrophysics Data System (ADS)

Boniecki, P.; Przybył, J.; Kuzimska, T.; Mueller, W.; Raba, B.; Lewicki, A.; Przybył, K.; Zaborowicz, M.; Koszela, K.

2014-04-01

The questions related to quality classification of animal oocytes are explored by numerous scientific and research centres. This research is important, particularly in the context of improving the breeding value of farm animals. The methods leading to the stimulation of normal development of a larger number of fertilised animal oocytes in extracorporeal conditions are of special importance. Growing interest in the techniques of supported reproduction resulted in searching for new, increasingly effective methods for quality assessment of mammalian gametes and embryos. Progress in the production of in vitro animal embryos in fact depends on proper classification of obtained oocytes. The aim of this paper was the development of an original method for quality assessment of oocytes, performed on the basis of their graphical presentation in the form of microscopic digital images. The classification process was implemented on the basis of the information coded in the form of microphotographic pictures of the oocytes of domestic pig, using the modern methods of neural image analysis.

The use of paleo-imaging and microbiological testing in the analysis of antique cultural material: multislice tomography, and microbial analysis of the Trogir Cathedral cope hood depicting St. Martin and a beggar.

PubMed

Cavka, Mislav; Petaros, Anja; Kavur, Lovro; Skrlin, Jasenka; Mlinaric Missoni, Emilija; Jankovic, Ivor; Brkljacic, Boris

2013-01-01

Paleoradiology is the study of biological and other materials from archeological settings through the use of various medical imaging techniques. Although it is most often used in the scientific study of ancient human remains, it can also be used to study metals, ceramics, paper, and clothes. The aim of this study was to test two paleoimaging techniques (MSCT and mammography) in the analysis of an important Croatian liturgical vestment: the hood of a bishop's cope from St. Lawrence's Treasury in Trogir depicting St. Martin and a beggar. To ensure a safe environment for scientists participating in the analysis, a preliminary microbiological analysis was performed, which contributed to the database of microbiological flora found on Croatian archeological remains and relics studied to date. Due to a great amount of metal filaments, the paleoradiological analysis did not produce satisfactory results. However, a digitally enhanced image clearly showed fine metal embroidery of the hood that was not so easily perceived by naked eye. This article argues in favor of expanding paleoradiological studies on materials other than human remains and also of publishing unsatisfactory results, as important lessons for future development of techniques and methods to analyze ancient remains and seek answers about human historical and cultural heritage.

magHD: a new approach to multi-dimensional data storage, analysis, display and exploitation

NASA Astrophysics Data System (ADS)

Angleraud, Christophe

2014-06-01

The ever increasing amount of data and processing capabilities - following the well- known Moore's law - is challenging the way scientists and engineers are currently exploiting large datasets. The scientific visualization tools, although quite powerful, are often too generic and provide abstract views of phenomena, thus preventing cross disciplines fertilization. On the other end, Geographic information Systems allow nice and visually appealing maps to be built but they often get very confused as more layers are added. Moreover, the introduction of time as a fourth analysis dimension to allow analysis of time dependent phenomena such as meteorological or climate models, is encouraging real-time data exploration techniques that allow spatial-temporal points of interests to be detected by integration of moving images by the human brain. Magellium is involved in high performance image processing chains for satellite image processing as well as scientific signal analysis and geographic information management since its creation (2003). We believe that recent work on big data, GPU and peer-to-peer collaborative processing can open a new breakthrough in data analysis and display that will serve many new applications in collaborative scientific computing, environment mapping and understanding. The magHD (for Magellium Hyper-Dimension) project aims at developing software solutions that will bring highly interactive tools for complex datasets analysis and exploration commodity hardware, targeting small to medium scale clusters with expansion capabilities to large cloud based clusters.

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.

Use of the TM tasseled cap transform for interpretation of spectral contrasts in an urban scene

NASA Technical Reports Server (NTRS)

Goward, S. N.; Wharton, S. W.

1984-01-01

Investigations are being conducted with the objective to develop automated numerical image analysis procedures. In this context, an examination is performed of physically-based multispectral data transforms as a means to incorporate a priori knowledge of land radiance properties in the analysis process. A physically-based transform of TM observations was developed. This transform extends the Landsat MSS Tasseled Cap transform reported by Kauth and Thomas (1976) to TM data observations. The present study has the aim to examine the utility of the TM Tasseled Cap transform as applied to TM data from an urban landscape. The analysis conducted is based on 512 x 512 subset of the Washington, DC November 2, 1982 TM scene, centered on Springfield, VA. It appears that the TM tasseled cap transformation provides a good means to explain land physical attributes of the Washington scene. This result provides a suggestion regarding a direction by which a priori knowledge of landscape spectral patterns may be incorporated into numerical image analysis.

Adaptable pattern recognition system for discriminating Melanocytic Nevi from Malignant Melanomas using plain photography images from different image databases.

PubMed

Kostopoulos, Spiros A; Asvestas, Pantelis A; Kalatzis, Ioannis K; Sakellaropoulos, George C; Sakkis, Theofilos H; Cavouras, Dionisis A; Glotsos, Dimitris T

2017-09-01

The aim of this study was to propose features that evaluate pictorial differences between melanocytic nevus (mole) and melanoma lesions by computer-based analysis of plain photography images and to design a cross-platform, tunable, decision support system to discriminate with high accuracy moles from melanomas in different publicly available image databases. Digital plain photography images of verified mole and melanoma lesions were downloaded from (i) Edinburgh University Hospital, UK, (Dermofit, 330moles/70 melanomas, under signed agreement), from 5 different centers (Multicenter, 63moles/25 melanomas, publicly available), and from the Groningen University, Netherlands (Groningen, 100moles/70 melanomas, publicly available). Images were processed for outlining the lesion-border and isolating the lesion from the surrounding background. Fourteen features were generated from each lesion evaluating texture (4), structure (5), shape (4) and color (1). Features were subjected to statistical analysis for determining differences in pictorial properties between moles and melanomas. The Probabilistic Neural Network (PNN) classifier, the exhaustive search features selection, the leave-one-out (LOO), and the external cross-validation (ECV) methods were used to design the PR-system for discriminating between moles and melanomas. Statistical analysis revealed that melanomas as compared to moles were of lower intensity, of less homogenous surface, had more dark pixels with intensities spanning larger spectra of gray-values, contained more objects of different sizes and gray-levels, had more asymmetrical shapes and irregular outlines, had abrupt intensity transitions from lesion to background tissue, and had more distinct colors. The PR-system designed by the Dermofit images scored on the Dermofit images, using the ECV, 94.1%, 82.9%, 96.5% for overall accuracy, sensitivity, specificity, on the Multicenter Images 92.0%, 88%, 93.7% and on the Groningen Images 76.2%, 73.9%, 77.8% respectively. The PR-system as designed by the Dermofit image database could be fine-tuned to classify with good accuracy plain photography moles/melanomas images of other databases employing different image capturing equipment and protocols. Copyright © 2017 Elsevier B.V. All rights reserved.

A New Effort for Atmospherical Forecast: Meteorological Image Processing Software (MIPS) for Astronomical Observations

NASA Astrophysics Data System (ADS)

Shameoni Niaei, M.; Kilic, Y.; Yildiran, B. E.; Yüzlükoglu, F.; Yesilyaprak, C.

2016-12-01

We have described a new software (MIPS) about the analysis and image processing of the meteorological satellite (Meteosat) data for an astronomical observatory. This software will be able to help to make some atmospherical forecast (cloud, humidity, rain) using meteosat data for robotic telescopes. MIPS uses a python library for Eumetsat data that aims to be completely open-source and licenced under GNU/General Public Licence (GPL). MIPS is a platform independent and uses h5py, numpy, and PIL with the general-purpose and high-level programming language Python and the QT framework.

Application of syntactic methods of pattern recognition for data mining and knowledge discovery in medicine

NASA Astrophysics Data System (ADS)

Ogiela, Marek R.; Tadeusiewicz, Ryszard

2000-04-01

This paper presents and discusses possibilities of application of selected algorithms belonging to the group of syntactic methods of patten recognition used to analyze and extract features of shapes and to diagnose morphological lesions seen on selected medical images. This method is particularly useful for specialist morphological analysis of shapes of selected organs of abdominal cavity conducted to diagnose disease symptoms occurring in the main pancreatic ducts, upper segments of ureters and renal pelvis. Analysis of the correct morphology of these organs is possible with the application of the sequential and tree method belonging to the group of syntactic methods of pattern recognition. The objective of this analysis is to support early diagnosis of disease lesions, mainly characteristic for carcinoma and pancreatitis, based on examinations of ERCP images and a diagnosis of morphological lesions in ureters as well as renal pelvis based on an analysis of urograms. In the analysis of ERCP images the main objective is to recognize morphological lesions in pancreas ducts characteristic for carcinoma and chronic pancreatitis, while in the case of kidney radiogram analysis the aim is to diagnose local irregularities of ureter lumen and to examine the morphology of renal pelvis and renal calyxes. Diagnosing the above mentioned lesion has been conducted with the use of syntactic methods of pattern recognition, in particular the languages of description of features of shapes and context-free sequential attributed grammars. These methods allow to recognize and describe in a very efficient way the aforementioned lesions on images obtained as a result of initial image processing of width diagrams of the examined structures. Additionally, in order to support the analysis of the correct structure of renal pelvis a method using the tree grammar for syntactic pattern recognition to define its correct morphological shapes has been presented.

Localized Energy-Based Normalization of Medical Images: Application to Chest Radiography.

PubMed

Philipsen, R H H M; Maduskar, P; Hogeweg, L; Melendez, J; Sánchez, C I; van Ginneken, B

2015-09-01

Automated quantitative analysis systems for medical images often lack the capability to successfully process images from multiple sources. Normalization of such images prior to further analysis is a possible solution to this limitation. This work presents a general method to normalize medical images and thoroughly investigates its effectiveness for chest radiography (CXR). The method starts with an energy decomposition of the image in different bands. Next, each band's localized energy is scaled to a reference value and the image is reconstructed. We investigate iterative and local application of this technique. The normalization is applied iteratively to the lung fields on six datasets from different sources, each comprising 50 normal CXRs and 50 abnormal CXRs. The method is evaluated in three supervised computer-aided detection tasks related to CXR analysis and compared to two reference normalization methods. In the first task, automatic lung segmentation, the average Jaccard overlap significantly increased from 0.72±0.30 and 0.87±0.11 for both reference methods to with normalization. The second experiment was aimed at segmentation of the clavicles. The reference methods had an average Jaccard index of 0.57±0.26 and 0.53±0.26; with normalization this significantly increased to . The third experiment was detection of tuberculosis related abnormalities in the lung fields. The average area under the Receiver Operating Curve increased significantly from 0.72±0.14 and 0.79±0.06 using the reference methods to with normalization. We conclude that the normalization can be successfully applied in chest radiography and makes supervised systems more generally applicable to data from different sources.

Characterizing pigments with hyperspectral imaging variable false-color composites

NASA Astrophysics Data System (ADS)

Hayem-Ghez, Anita; Ravaud, Elisabeth; Boust, Clotilde; Bastian, Gilles; Menu, Michel; Brodie-Linder, Nancy

2015-11-01

Hyperspectral imaging has been used for pigment characterization on paintings for the last 10 years. It is a noninvasive technique, which mixes the power of spectrophotometry and that of imaging technologies. We have access to a visible and near-infrared hyperspectral camera, ranging from 400 to 1000 nm in 80-160 spectral bands. In order to treat the large amount of data that this imaging technique generates, one can use statistical tools such as principal component analysis (PCA). To conduct the characterization of pigments, researchers mostly use PCA, convex geometry algorithms and the comparison of resulting clusters to database spectra with a specific tolerance (like the Spectral Angle Mapper tool on the dedicated software ENVI). Our approach originates from false-color photography and aims at providing a simple tool to identify pigments thanks to imaging spectroscopy. It can be considered as a quick first analysis to see the principal pigments of a painting, before using a more complete multivariate statistical tool. We study pigment spectra, for each kind of hue (blue, green, red and yellow) to identify the wavelength maximizing spectral differences. The case of red pigments is most interesting because our methodology can discriminate the red pigments very well—even red lakes, which are always difficult to identify. As for the yellow and blue categories, it represents a good progress of IRFC photography for pigment discrimination. We apply our methodology to study the pigments on a painting by Eustache Le Sueur, a French painter of the seventeenth century. We compare the results to other noninvasive analysis like X-ray fluorescence and optical microscopy. Finally, we draw conclusions about the advantages and limits of the variable false-color image method using hyperspectral imaging.

The detectability of brain metastases using contrast-enhanced spin-echo or gradient-echo images: a systematic review and meta-analysis.

PubMed

Suh, Chong Hyun; Jung, Seung Chai; Kim, Kyung Won; Pyo, Junhee

2016-09-01

This study aimed to compare the detectability of brain metastases using contrast-enhanced spin-echo (SE) and gradient-echo (GRE) T1-weighted images. The Ovid-MEDLINE and EMBASE databases were searched for studies on the detectability of brain metastases using contrast-enhanced SE or GRE images. The pooled proportions for the detectability of brain metastases were assessed using random-effects modeling. Heterogeneity among studies was determined using χ (2) statistics for the pooled estimates and the inconsistency index, I (2) . To overcome heterogeneity, subgroup analyses according to slice thickness and lesion size were performed. A total of eight eligible studies, which included a sample size of 252 patients and 1413 brain metastases, were included. The detectability of brain metastases using SE images (89.2 %) was higher than using GRE images (81.6 %; adjusted 84.0 %), but this difference was not statistically significant (p = 0.2385). In subgroup analysis of studies with 1-mm-thick slices and small metastases (<5 mm in diameter), 3-dimensional (3D) SE images demonstrated a higher detectability in comparison to 3D GRE images (93.7 % vs 73.1 % in 1-mm-thick slices; 89.5 % vs 59.4 % for small metastases) (p < 0.0001). Although both SE or GRE images are acceptable for detecting brain metastases, contrast-enhanced 3D SE images using 1-mm-thick slices are preferred for detecting brain metastases, especially small lesions (<5 mm in diameter).

Study of Lead as a Source X-ray Radiation Protection with an Analysis Grey Level Image

NASA Astrophysics Data System (ADS)

Susilo; Rahma, I. N.; Mosik; Masturi

2017-04-01

X-ray utilization in the medical field still has a potential danger for the human. This occurs when exposure to x-ray radiation received exceeds the dose limit value. It required a radiation shielding to prevent the hazard, and lead is one of the metals usually used as x-ray radiation shield. This work aims to determine the metallic lead properties to find out of the step wedge lead radiograph image. The instruments used are the plane x-ray, digital radiography system and personal computer installed by MATLAB, while the material is step wedge lead. The image of radiograph was analysed using GUI applications on MATLAB software to determine the values of grey level from the image and the optical density of the radiograph image. The results showed the greater optical density, the higher the image contrast, and the value of optical density in the image is inversely proportional to the voltage x-ray since the value of grey level at high voltage is smaller than that of at low voltage.

Analysis of the impact of digital watermarking on computer-aided diagnosis in medical imaging.

PubMed

Garcia-Hernandez, Jose Juan; Gomez-Flores, Wilfrido; Rubio-Loyola, Javier

2016-01-01

Medical images (MI) are relevant sources of information for detecting and diagnosing a large number of illnesses and abnormalities. Due to their importance, this study is focused on breast ultrasound (BUS), which is the main adjunct for mammography to detect common breast lesions among women worldwide. On the other hand, aiming to enhance data security, image fidelity, authenticity, and content verification in e-health environments, MI watermarking has been widely used, whose main goal is to embed patient meta-data into MI so that the resulting image keeps its original quality. In this sense, this paper deals with the comparison of two watermarking approaches, namely spread spectrum based on the discrete cosine transform (SS-DCT) and the high-capacity data-hiding (HCDH) algorithm, so that the watermarked BUS images are guaranteed to be adequate for a computer-aided diagnosis (CADx) system, whose two principal outcomes are lesion segmentation and classification. Experimental results show that HCDH algorithm is highly recommended for watermarking medical images, maintaining the image quality and without introducing distortion into the output of CADx. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nuclear imaging of the fuel assembly in ignition experimentsa)

NASA Astrophysics Data System (ADS)

Grim, G. P.; Guler, N.; Merrill, F. E.; Morgan, G. L.; Danly, C. R.; Volegov, P. L.; Wilde, C. H.; Wilson, D. C.; Clark, D. S.; Hinkel, D. E.; Jones, O. S.; Raman, K. S.; Izumi, N.; Fittinghoff, D. N.; Drury, O. B.; Alger, E. T.; Arnold, P. A.; Ashabranner, R. C.; Atherton, L. J.; Barrios, M. A.; Batha, S.; Bell, P. M.; Benedetti, L. R.; Berger, R. L.; Bernstein, L. A.; Berzins, L. V.; Betti, R.; Bhandarkar, S. D.; Bionta, R. M.; Bleuel, D. L.; Boehly, T. R.; Bond, E. J.; Bowers, M. W.; Bradley, D. K.; Brunton, G. K.; Buckles, R. A.; Burkhart, S. C.; Burr, R. F.; Caggiano, J. A.; Callahan, D. A.; Casey, D. T.; Castro, C.; Celliers, P. M.; Cerjan, C. J.; Chandler, G. A.; Choate, C.; Cohen, S. J.; Collins, G. W.; Cooper, G. W.; Cox, J. R.; Cradick, J. R.; Datte, P. S.; Dewald, E. L.; Di Nicola, P.; Di Nicola, J. M.; Divol, L.; Dixit, S. N.; Dylla-Spears, R.; Dzenitis, E. G.; Eckart, M. J.; Eder, D. C.; Edgell, D. H.; Edwards, M. J.; Eggert, J. H.; Ehrlich, R. B.; Erbert, G. V.; Fair, J.; Farley, D. R.; Felker, B.; Fortner, R. J.; Frenje, J. A.; Frieders, G.; Friedrich, S.; Gatu-Johnson, M.; Gibson, C. R.; Giraldez, E.; Glebov, V. Y.; Glenn, S. M.; Glenzer, S. H.; Gururangan, G.; Haan, S. W.; Hahn, K. D.; Hammel, B. A.; Hamza, A. V.; Hartouni, E. P.; Hatarik, R.; Hatchett, S. P.; Haynam, C.; Hermann, M. R.; Herrmann, H. W.; Hicks, D. G.; Holder, J. P.; Holunga, D. M.; Horner, J. B.; Hsing, W. W.; Huang, H.; Jackson, M. C.; Jancaitis, K. S.; Kalantar, D. H.; Kauffman, R. L.; Kauffman, M. I.; Khan, S. F.; Kilkenny, J. D.; Kimbrough, J. R.; Kirkwood, R.; Kline, J. L.; Knauer, J. P.; Knittel, K. M.; Koch, J. A.; Kohut, T. R.; Kozioziemski, B. J.; Krauter, K.; Krauter, G. W.; Kritcher, A. L.; Kroll, J.; Kyrala, G. A.; Fortune, K. N. La; LaCaille, G.; Lagin, L. J.; Land, T. A.; Landen, O. L.; Larson, D. W.; Latray, D. A.; Leeper, R. J.; Lewis, T. L.; LePape, S.; Lindl, J. D.; Lowe-Webb, R. R.; Ma, T.; MacGowan, B. J.; MacKinnon, A. J.; MacPhee, A. G.; Malone, R. M.; Malsbury, T. N.; Mapoles, E.; Marshall, C. D.; Mathisen, D. G.; McKenty, P.; McNaney, J. M.; Meezan, N. B.; Michel, P.; Milovich, J. L.; Moody, J. D.; Moore, A. S.; Moran, M. J.; Moreno, K.; Moses, E. I.; Munro, D. H.; Nathan, B. R.; Nelson, A. J.; Nikroo, A.; Olson, R. E.; Orth, C.; Pak, A. E.; Palma, E. S.; Parham, T. G.; Patel, P. K.; Patterson, R. W.; Petrasso, R. D.; Prasad, R.; Ralph, J. E.; Regan, S. P.; Rinderknecht, H.; Robey, H. F.; Ross, G. F.; Ruiz, C. L.; Séguin, F. H.; Salmonson, J. D.; Sangster, T. C.; Sater, J. D.; Saunders, R. L.; Schneider, M. B.; Schneider, D. H.; Shaw, M. J.; Simanovskaia, N.; Spears, B. K.; Springer, P. T.; Stoeckl, C.; Stoeffl, W.; Suter, L. J.; Thomas, C. A.; Tommasini, R.; Town, R. P.; Traille, A. J.; Wonterghem, B. Van; Wallace, R. J.; Weaver, S.; Weber, S. V.; Wegner, P. J.; Whitman, P. K.; Widmann, K.; Widmayer, C. C.; Wood, R. D.; Young, B. K.; Zacharias, R. A.; Zylstra, A.

2013-05-01

First results from the analysis of neutron image data collected on implosions of cryogenically layered deuterium-tritium capsules during the 2011-2012 National Ignition Campaign are reported. The data span a variety of experimental designs aimed at increasing the stagnation pressure of the central hotspot and areal density of the surrounding fuel assembly. Images of neutrons produced by deuterium-tritium fusion reactions in the hotspot are presented, as well as images of neutrons that scatter in the surrounding dense fuel assembly. The image data are compared with 1D and 2D model predictions, and consistency checked using other diagnostic data. The results indicate that the size of the fusing hotspot is consistent with the model predictions, as well as other imaging data, while the overall size of the fuel assembly, inferred from the scattered neutron images, is systematically smaller than models' prediction. Preliminary studies indicate these differences are consistent with a significant fraction (20%-25%) of the initial deuterium-tritium fuel mass outside the compact fuel assembly, due either to low mode mass asymmetry or high mode 3D mix effects at the ablator-ice interface.

Status of GDL - GNU Data Language

NASA Astrophysics Data System (ADS)

Coulais, A.; Schellens, M.; Gales, J.; Arabas, S.; Boquien, M.; Chanial, P.; Messmer, P.; Fillmore, D.; Poplawski, O.; Maret, S.; Marchal, G.; Galmiche, N.; Mermet, T.

2010-12-01

Gnu Data Language (GDL) is an open-source interpreted language aimed at numerical data analysis and visualisation. It is a free implementation of the Interactive Data Language (IDL) widely used in Astronomy. GDL has a full syntax compatibility with IDL, and includes a large set of library routines targeting advanced matrix manipulation, plotting, time-series and image analysis, mapping, and data input/output including numerous scientific data formats. We will present the current status of the project, the key accomplishments, and the weaknesses - areas where contributions are welcome!

Lightcurve Analysis for Minor Planets 1322 Coppernicus and 9148 Boriszaitsev

NASA Astrophysics Data System (ADS)

Noschese, Alfonso; Vecchione, Antonio; Ruocco, Nello; Izzo, Luca

2018-01-01

From 2017 March 16 to 2017 June 23, CCD images were taken with the aim to measure the rotation period of 1322 Coppernicus and 9148 Boriszaitsev. The data analysis gives a lightcurve with a rotation period of 8.125 ± 0.009 hours for Boriszaitsev, in agreement with other measurement recently published. On the contrary, the rotation period of 4.354 ± 0.005 measured for 1322 Coppernicus is rather different than the previous data collected in 1991 and 2006.

Imaging heterogeneity in the mitochondrial redox state of premalignant pancreas in the pancreas-specific PTEN-null transgenic mouse model

PubMed Central

2013-01-01

Background Metabolic alteration is one of the hallmarks of carcinogenesis. We aimed to identify certain metabolic biomarkers for the early detection of pancreatic cancer (PC) using the transgenic PTEN-null mouse model. Pancreas-specific deletion of PTEN in mouse caused progressive premalignant lesions such as highly proliferative ductal metaplasia. We imaged the mitochondrial redox state of the pancreases of the transgenic mice approximately eight months old using the redox scanner, i.e., the nicotinamide adenine dinucleotide/oxidized flavoproteins (NADH/Fp) fluorescence imager at low temperature. Two different approaches, the global averaging of the redox indices without considering tissue heterogeneity along tissue depth and the univariate analysis of multi-section data using tissue depth as a covariate were adopted for the statistical analysis of the multi-section imaging data. The standard deviations of the redox indices and the histogram analysis with Gaussian fit were used to determine the tissue heterogeneity. Results All methods show consistently that the PTEN deficient pancreases (Pdx1-Cre;PTENlox/lox) were significantly more heterogeneous in their mitochondrial redox state compared to the controls (PTENlox/lox). Statistical analysis taking into account the variations of the redox state with tissue depth further shows that PTEN deletion significantly shifted the pancreatic tissue to an overall more oxidized state. Oxidization of the PTEN-null group was not seen when the imaging data were analyzed by global averaging without considering the variation of the redox indices along tissue depth, indicating the importance of taking tissue heterogeneity into account for the statistical analysis of the multi-section imaging data. Conclusions This study reveals a possible link between the mitochondrial redox state alteration of the pancreas and its malignant transformation and may be further developed for establishing potential metabolic biomarkers for the early diagnosis of pancreatic cancer. PMID:24252270

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

A method to perform spinal motion analysis from functional X-ray images.

PubMed

Schulze, Martin; Trautwein, Frank; Vordemvenne, Thomas; Raschke, Michael; Heuer, Frank

2011-06-03

Identifying spinal instability is an important aim for proper surgical treatment. Analysis of functional X-ray images delivers measurements of the range of motion (RoM) and the center of rotation (CoR). In today's practice, CoR determination is often omitted, due to the lack of accurate methods. The aim of this work was to investigate the accuracy of a new analysis software (FXA™) based on an in vitro experiment. Six bovine spinal specimens (L3-4) were mounted in a robot (KR125, Kuka). CoRs were predefined by locking the robot actuator tool center point to the estimated position of the physiologic CoR and taking a baseline X-ray. Specimens were deflected to various RoM(preset) flexion/extension angles about the CoR(preset). Lateral functional radiographs were acquired and specimen movements were recorded using an optical motion tracking system (Optotrak Certus). RoM and CoR errors were calculated from presets for both methods. Prior to the experiment, the FXA™ software was verified with artificially generated images. For the artificial images, FXA™ yielded a mean RoM-error of 0.01 ± 0.03° (bias ± standard deviation). In the experiment, RoM-error of the FXA™-software (deviation from presets) was 0.04 ± 0.13°, and 0.10 ± 0.16° for the Optotrak, respectively. Both correlated with 0.998 (p < 0.001). For RoM < 1.0°, FXA™ determined CoR positions with a bias>20mm. This bias progressively decreased from RoM = 1° (bias = 6.0mm) to RoM = 9° (bias<1.5mm). Under the assumption that CoR location variances <5mm are clinically irrelevant on the lumbar spine, the FXA™ method can accurately determine CoRs for RoMs > 1°. Utilizing FXA™, polysegmental RoMs, CoRs and implant migration measurements could be performed in daily practice. Copyright © 2011 Elsevier Ltd. All rights reserved.

Study on super-resolution three-dimensional range-gated imaging technology

NASA Astrophysics Data System (ADS)

Guo, Huichao; Sun, Huayan; Wang, Shuai; Fan, Youchen; Li, Yuanmiao

2018-04-01

Range-gated three dimensional imaging technology is a hotspot in recent years, because of the advantages of high spatial resolution, high range accuracy, long range, and simultaneous reflection of target reflectivity information. Based on the study of the principle of intensity-related method, this paper has carried out theoretical analysis and experimental research. The experimental system adopts the high power pulsed semiconductor laser as light source, gated ICCD as the imaging device, can realize the imaging depth and distance flexible adjustment to achieve different work mode. The imaging experiment of small imaging depth is carried out aiming at building 500m away, and 26 group images were obtained with distance step 1.5m. In this paper, the calculation method of 3D point cloud based on triangle method is analyzed, and 15m depth slice of the target 3D point cloud are obtained by using two frame images, the distance precision is better than 0.5m. The influence of signal to noise ratio, illumination uniformity and image brightness on distance accuracy are analyzed. Based on the comparison with the time-slicing method, a method for improving the linearity of point cloud is proposed.

Local spatio-temporal analysis in vision systems

NASA Astrophysics Data System (ADS)

Geisler, Wilson S.; Bovik, Alan; Cormack, Lawrence; Ghosh, Joydeep; Gildeen, David

1994-07-01

The aims of this project are the following: (1) develop a physiologically and psychophysically based model of low-level human visual processing (a key component of which are local frequency coding mechanisms); (2) develop image models and image-processing methods based upon local frequency coding; (3) develop algorithms for performing certain complex visual tasks based upon local frequency representations, (4) develop models of human performance in certain complex tasks based upon our understanding of low-level processing; and (5) develop a computational testbed for implementing, evaluating and visualizing the proposed models and algorithms, using a massively parallel computer. Progress has been substantial on all aims. The highlights include the following: (1) completion of a number of psychophysical and physiological experiments revealing new, systematic and exciting properties of the primate (human and monkey) visual system; (2) further development of image models that can accurately represent the local frequency structure in complex images; (3) near completion in the construction of the Texas Active Vision Testbed; (4) development and testing of several new computer vision algorithms dealing with shape-from-texture, shape-from-stereo, and depth-from-focus; (5) implementation and evaluation of several new models of human visual performance; and (6) evaluation, purchase and installation of a MasPar parallel computer.

Utility of cytopathological specimens and an automated image analysis for the evaluation of HER2 status and intratumor heterogeneity in breast carcinoma.

PubMed

Arihiro, Koji; Oda, Miyo; Ogawa, Katsunari; Kaneko, Yoshie; Shimizu, Tomomi; Tanaka, Yuna; Marubashi, Yukari; Ishida, Katsunari; Takai, Chikako; Taoka, Chie; Kimura, Shuji; Shiroma, Noriyuki

2016-12-01

Although updated HER2 testing guidelines have been improved by a collaboration between the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAP) in 2013, HER2 evaluation is still problematic because of issues involving CEP17 polysomy, heterogeneity, and HER2 score 2+ cases. The aim of this retrospective study was to evaluate the relationship between HER2 gene heterogeneity, or so called CEP17 polysomy, using breast carcinoma cells sampled by scraping and the IHC score graded by automated image analysis using whole slide image. We randomly selected 23 breast carcinoma cases with a HER2 score 0, 24 cases with a HER2 score 1+, 24 cases with HER2 score 2+, and 23 cases with HER2 score 3+ from the records of patients with breast cancer at Hiroshima University Hospital. We compared the results of fluorescent in situ hybridization (FISH) using formalin-fixed, paraffin-embedded (FFPE) tissues and cytological samples and compared the HER2 score calculated using an automated image analysis using wholly scanned slide images and visual counting. We successfully performed the FISH assay in 78 of 94 cases (83%) using FFPE tissues and in all 94 (100%) cases using cytological samples. Frequency of both HER2 amplification and CEP17 polysomy was higher when cytological samples were used than when FFPE tissue was used. Frequency of HER2 heterogeneity using cytological samples was higher that than using FFPE tissue, except for the IHC score 3+ cases. When assessment of HER2 status based on FISH using FFPE tissue cannot be accomplished, FISH using cytological samples should be considered. When intensity of HER2 is heterogeneous in the tumor tissue, particularly in cases regarded as score 2+, they should be evaluated by automated image analysis using the whole slide image. Copyright © 2016 Elsevier GmbH. All rights reserved.

Interobserver variability of radiation therapists aligning to fiducial markers for prostate radiation therapy.

PubMed

Deegan, Timothy; Owen, Rebecca; Holt, Tanya; Roberts, Lisa; Biggs, Jennifer; McCarthy, Alicia; Parfitt, Matthew; Fielding, Andrew

2013-08-01

As the use of fiducial markers (FMs) for the localisation of the prostate during external beam radiation therapy (EBRT) has become part of routine practice, radiation therapists (RTs) have become increasingly responsible for online image interpretation. The aim of this investigation was to quantify the limits of agreement (LoA) between RTs when localising to FMs with orthogonal kilovoltage (kV) imaging. Six patients receiving prostate EBRT utilising FMs were included in this study. Treatment localisation was performed using kV imaging prior to each fraction. Online stereoscopic assessment of FMs, performed by the treating RTs, was compared with the offline assessment by three RTs. Observer agreement was determined by pairwise Bland-Altman analysis. Stereoscopic analysis of 225 image pairs was performed online at the time of treatment, and offline by three RT observers. Eighteen pairwise Bland-Altman analyses were completed to assess the level of agreement between observers. Localisation by RTs was found to be within clinically acceptable 95% LoAs. Small differences between RTs, in both the online and offline setting, were found to be within clinically acceptable limits. RTs were able to make consistent and reliable judgements when matching FMs on planar kV imaging. © 2013 The Authors. Journal of Medical Imaging and Radiation Oncology © 2013 The Royal Australian and New Zealand College of Radiologists.

Lesion registration for longitudinal disease tracking in an imaging informatics-based multiple sclerosis eFolder

NASA Astrophysics Data System (ADS)

Ma, Kevin; Liu, Joseph; Zhang, Xuejun; Lerner, Alex; Shiroishi, Mark; Amezcua, Lilyana; Liu, Brent

2016-03-01

We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results stored in DICOM-SR format. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system needs to quantify lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. In order to perform lesion registration, we have developed a brain warping and normalizing methodology using Statistical Parametric Mapping (SPM) MATLAB toolkit for brain MRI. Patients' brain MR images are processed via SPM's normalization processes, and the brain images are analyzed and warped according to the tissue probability map. Lesion identification and contouring are completed by neuroradiologists, and lesion volume quantification is completed by the eFolder's CAD program. Lesion comparison results in longitudinal studies show key growth and active regions. The results display successful lesion registration and tracking over a longitudinal study. Lesion change results are graphically represented in the web-based user interface, and users are able to correlate patient progress and changes in the MRI images. The completed lesion and disease tracking tool would enable the eFolder to provide complete patient profiles, improve the efficiency of patient care, and perform comprehensive data analysis through an integrated imaging informatics system.

Shadow detection and removal in RGB VHR images for land use unsupervised classification

NASA Astrophysics Data System (ADS)

Movia, A.; Beinat, A.; Crosilla, F.

2016-09-01

Nowadays, high resolution aerial images are widely available thanks to the diffusion of advanced technologies such as UAVs (Unmanned Aerial Vehicles) and new satellite missions. Although these developments offer new opportunities for accurate land use analysis and change detection, cloud and terrain shadows actually limit benefits and possibilities of modern sensors. Focusing on the problem of shadow detection and removal in VHR color images, the paper proposes new solutions and analyses how they can enhance common unsupervised classification procedures for identifying land use classes related to the CO2 absorption. To this aim, an improved fully automatic procedure has been developed for detecting image shadows using exclusively RGB color information, and avoiding user interaction. Results show a significant accuracy enhancement with respect to similar methods using RGB based indexes. Furthermore, novel solutions derived from Procrustes analysis have been applied to remove shadows and restore brightness in the images. In particular, two methods implementing the so called "anisotropic Procrustes" and the "not-centered oblique Procrustes" algorithms have been developed and compared with the linear correlation correction method based on the Cholesky decomposition. To assess how shadow removal can enhance unsupervised classifications, results obtained with classical methods such as k-means, maximum likelihood, and self-organizing maps, have been compared to each other and with a supervised clustering procedure.

An optical flow-based method for velocity field of fluid flow estimation

NASA Astrophysics Data System (ADS)

Głomb, Grzegorz; Świrniak, Grzegorz; Mroczka, Janusz

2017-06-01

The aim of this paper is to present a method for estimating flow-velocity vector fields using the Lucas-Kanade algorithm. The optical flow measurements are based on the Particle Image Velocimetry (PIV) technique, which is commonly used in fluid mechanics laboratories in both research institutes and industry. Common approaches for an optical characterization of velocity fields base on computation of partial derivatives of the image intensity using finite differences. Nevertheless, the accuracy of velocity field computations is low due to the fact that an exact estimation of spatial derivatives is very difficult in presence of rapid intensity changes in the PIV images, caused by particles having small diameters. The method discussed in this paper solves this problem by interpolating the PIV images using Gaussian radial basis functions. This provides a significant improvement in the accuracy of the velocity estimation but, more importantly, allows for the evaluation of the derivatives in intermediate points between pixels. Numerical analysis proves that the method is able to estimate even a separate vector for each particle with a 5× 5 px2 window, whereas a classical correlation-based method needs at least 4 particle images. With the use of a specialized multi-step hybrid approach to data analysis the method improves the estimation of the particle displacement far above 1 px.

A novel image processing technique for 3D volumetric analysis of severely resorbed alveolar sockets with CBCT.

PubMed

Manavella, Valeria; Romano, Federica; Garrone, Federica; Terzini, Mara; Bignardi, Cristina; Aimetti, Mario

2017-06-01

The aim of this study was to present and validate a novel procedure for the quantitative volumetric assessment of extraction sockets that combines cone-beam computed tomography (CBCT) and image processing techniques. The CBCT dataset of 9 severely resorbed extraction sockets was analyzed by means of two image processing software, Image J and Mimics, using manual and automated segmentation techniques. They were also applied on 5-mm spherical aluminum markers of known volume and on a polyvinyl chloride model of one alveolar socket scanned with Micro-CT to test the accuracy. Statistical differences in alveolar socket volume were found between the different methods of volumetric analysis (P<0.0001). The automated segmentation using Mimics was the most reliable and accurate method with a relative error of 1.5%, considerably smaller than the error of 7% and of 10% introduced by the manual method using Mimics and by the automated method using ImageJ. The currently proposed automated segmentation protocol for the three-dimensional rendering of alveolar sockets showed more accurate results, excellent inter-observer similarity and increased user friendliness. The clinical application of this method enables a three-dimensional evaluation of extraction socket healing after the reconstructive procedures and during the follow-up visits.

Application values of 99mTc-methoxyisobutylisonitrile imaging for differentiating benign and malignant thymic masses.

PubMed

Lu, Chenghui; Wang, Xufu; Liu, Bin; Liu, Xinfeng; Wang, Guoming; Zhang, Qin

2017-08-01

The aim of the present study was to investigate the application value of 99m Tc-methoxyisobutylisonitrile (MIBI) imaging to differentiate between benign and malignant thymic masses. A total of 32 patients with space-occupying mediastinal masses were enrolled and early and delayed-phase images were collected following injection with the imaging agent. The tumor to background ratio (T/N) values at the different phases were also recorded. The sensitivity of the qualitative analysis to distinguish between benign and malignant thymic masses was 95.24%, with specificity as 90.91%. The T/N values in the early and delayed phases were not significantly different in the group with benign thymic masses, but demonstrated statistical significant differences in the groups with low- and intermediate-grade malignant thymic masses. The T/N values at the above early and delayed phase were significantly different between the benign and low-grade malignancy groups, as well as between low- and moderate-grade malignancy groups. Those between the benign and moderate-grade malignancy groups demonstrated no significant difference. 99m Tc-MIBI imaging was able to differentiate between benign and malignant thymic masses, and the simultaneous semi-quantitative analysis of the T/N values of the tumors may be able to initially determine the degree of malignancy of thymoma.

Quantitative Time-Resolved Fluorescence Imaging of Androgen Receptor and Prostate-Specific Antigen in Prostate Tissue Sections.

PubMed

Krzyzanowska, Agnieszka; Lippolis, Giuseppe; Helczynski, Leszek; Anand, Aseem; Peltola, Mari; Pettersson, Kim; Lilja, Hans; Bjartell, Anders

2016-05-01

Androgen receptor (AR) and prostate-specific antigen (PSA) are expressed in the prostate and are involved in prostate cancer (PCa). The aim of this study was to develop reliable protocols for reproducible quantification of AR and PSA in benign and malignant prostate tissue using time-resolved fluorescence (TRF) imaging techniques. AR and PSA were detected with TRF in tissue microarrays from 91 PCa patients. p63/ alpha-methylacyl-CoA racemase (AMACR) staining on consecutive sections was used to categorize tissue areas as benign or cancerous. Automated image analysis was used to quantify staining intensity. AR intensity was significantly higher in AMACR+ and lower in AMACR- cancer areas as compared with benign epithelium. The PSA intensity was significantly lower in cancer areas, particularly in AMACR- glands. The AR/PSA ratio varied significantly in the AMACR+ tumor cells as compared with benign glands. There was a trend of more rapid disease progression in patients with higher AR/PSA ratios in the AMACR- areas. This study demonstrates the feasibility of developing reproducible protocols for TRF imaging and automated image analysis to study the expression of AR and PSA in benign and malignant prostate. It also highlighted the differences in AR and PSA protein expression within AMACR- and AMACR+ cancer regions. © 2016 The Histochemical Society.

Methods and potentials for using satellite image classification in school lessons

NASA Astrophysics Data System (ADS)

Voss, Kerstin; Goetzke, Roland; Hodam, Henryk

2011-11-01

The FIS project - FIS stands for Fernerkundung in Schulen (Remote Sensing in Schools) - aims at a better integration of the topic "satellite remote sensing" in school lessons. According to this, the overarching objective is to teach pupils basic knowledge and fields of application of remote sensing. Despite the growing significance of digital geomedia, the topic "remote sensing" is not broadly supported in schools. Often, the topic is reduced to a short reflection on satellite images and used only for additional illustration of issues relevant for the curriculum. Without addressing the issue of image data, this can hardly contribute to the improvement of the pupils' methodical competences. Because remote sensing covers more than simple, visual interpretation of satellite images, it is necessary to integrate remote sensing methods like preprocessing, classification and change detection. Dealing with these topics often fails because of confusing background information and the lack of easy-to-use software. Based on these insights, the FIS project created different simple analysis tools for remote sensing in school lessons, which enable teachers as well as pupils to be introduced to the topic in a structured way. This functionality as well as the fields of application of these analysis tools will be presented in detail with the help of three different classification tools for satellite image classification.

Changes in Structural Connectivity Following a Cognitive Intervention in Children With Traumatic Brain Injury.

PubMed

Yuan, Weihong; Treble-Barna, Amery; Sohlberg, McKay M; Harn, Beth; Wade, Shari L

2017-02-01

Structural connectivity analysis based on graph theory and diffusion tensor imaging tractography is a novel method that quantifies the topological characteristics in the brain network. This study aimed to examine structural connectivity changes following the Attention Intervention and Management (AIM) program designed to improve attention and executive function (EF) in children with traumatic brain injury (TBI). Seventeen children with complicated mild to severe TBI (13.66 ± 2.68 years; >12 months postinjury) completed magnetic resonance imaging (MRI) and neurobehavioral measures at time 1, 10 of whom completed AIM and assessment at time 2. Eleven matched healthy comparison (HC) children (13.37 ± 2.08 years) completed MRI and neurobehavioral assessment at both time points, but did not complete AIM. Network characteristics were analyzed to quantify the structural connectivity before and after the intervention. Mixed model analyses showed that small-worldness was significantly higher in the TBI group than the HC group at time 1, and both small-worldness and normalized clustering coefficient decreased significantly at time 2 in the TBI group whereas the HC group remained relatively unchanged. Reductions in mean local efficiency were significantly correlated with improvements in verbal inhibition and both parent- and child-reported EF. Increased normalized characteristic path length was significantly correlated with improved sustained attention. The results provide preliminary evidence suggesting that graph theoretical analysis may be a sensitive tool in pediatric TBI for detecting ( a) abnormalities of structural connectivity in brain network and ( b) structural neuroplasticity associated with neurobehavioral improvement following a short-term intervention for attention and EF.

The influence of the microscope lamp filament colour temperature on the process of digital images of histological slides acquisition standardization.

PubMed

Korzynska, Anna; Roszkowiak, Lukasz; Pijanowska, Dorota; Kozlowski, Wojciech; Markiewicz, Tomasz

2014-01-01

The aim of this study is to compare the digital images of the tissue biopsy captured with optical microscope using bright field technique under various light conditions. The range of colour's variation in immunohistochemically stained with 3,3'-Diaminobenzidine and Haematoxylin tissue samples is immense and coming from various sources. One of them is inadequate setting of camera's white balance to microscope's light colour temperature. Although this type of error can be easily handled during the stage of image acquisition, it can be eliminated with use of colour adjustment algorithms. The examination of the dependence of colour variation from microscope's light temperature and settings of the camera is done as an introductory research to the process of automatic colour standardization. Six fields of view with empty space among the tissue samples have been selected for analysis. Each field of view has been acquired 225 times with various microscope light temperature and camera white balance settings. The fourteen randomly chosen images have been corrected and compared, with the reference image, by the following methods: Mean Square Error, Structural SIMilarity and visual assessment of viewer. For two types of backgrounds and two types of objects, the statistical image descriptors: range, median, mean and its standard deviation of chromaticity on a and b channels from CIELab colour space, and luminance L, and local colour variability for objects' specific area have been calculated. The results have been averaged for 6 images acquired in the same light conditions and camera settings for each sample. The analysis of the results leads to the following conclusions: (1) the images collected with white balance setting adjusted to light colour temperature clusters in certain area of chromatic space, (2) the process of white balance correction for images collected with white balance camera settings not matched to the light temperature moves image descriptors into proper chromatic space but simultaneously the value of luminance changes. So the process of the image unification in a sense of colour fidelity can be solved in separate introductory stage before the automatic image analysis.

Onychomycosis diagnosis using fluorescence and infrared imaging systems

NASA Astrophysics Data System (ADS)

da Silva, Ana Paula; Fortunato, Thereza Cury; Stringasci, Mirian D.; Kurachi, Cristina; Bagnato, Vanderlei S.; Inada, Natalia M.

2015-06-01

Onychomycosis is a common disease of the nail plate, constituting approximately half of all cases of nail infection. Onychomycosis diagnosis is challenging because it is hard to distinguish from other diseases of the nail lamina such as psoriasis, lichen ruber or eczematous nails. The existing methods of diagnostics so far consist of clinical and laboratory analysis, such as: Direct Mycological examination and culture, PCR and histopathology with PAS staining. However, they all share certain disadvantages in terms of sensitivity and specificity, time delay, or cost. This study aimed to evaluate the use of infrared and fluorescence imaging as new non-invasive diagnostic tools in patients with suspected onychomycosis, and compare them with established techniques. For fluorescence analysis, a Clinical Evince (MM Optics®) was used, which consists of an optical assembly with UV LED light source wavelength 400 nm +/- 10 nm and the maximum light intensity: 40 mW/cm2 +/- 20%. For infrared analysis, a Fluke® Camera FKL model Ti400 was used. Patients with onychomycosis and control group were analyzed for comparison. The fluorescence images were processed using MATLAB® routines, and infrared images were analyzed using the SmartView® 3.6 software analysis provided by the company Fluke®. The results demonstrated that both infrared and fluorescence could be complementary to diagnose different types of onychomycosis lesions. The simplicity of operation, quick response and non-invasive assessment of the nail patients in real time, are important factors to be consider for an implementation.

Computer-aided diagnosis of colorectal polyp histology by using a real-time image recognition system and narrow-band imaging magnifying colonoscopy.

PubMed

Kominami, Yoko; Yoshida, Shigeto; Tanaka, Shinji; Sanomura, Yoji; Hirakawa, Tsubasa; Raytchev, Bisser; Tamaki, Toru; Koide, Tetsusi; Kaneda, Kazufumi; Chayama, Kazuaki

2016-03-01

It is necessary to establish cost-effective examinations and treatments for diminutive colorectal tumors that consider the treatment risk and surveillance interval after treatment. The Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) committee of the American Society for Gastrointestinal Endoscopy published a statement recommending the establishment of endoscopic techniques that practice the resect and discard strategy. The aims of this study were to evaluate whether our newly developed real-time image recognition system can predict histologic diagnoses of colorectal lesions depicted on narrow-band imaging and to satisfy some problems with the PIVI recommendations. We enrolled 41 patients who had undergone endoscopic resection of 118 colorectal lesions (45 nonneoplastic lesions and 73 neoplastic lesions). We compared the results of real-time image recognition system analysis with that of narrow-band imaging diagnosis and evaluated the correlation between image analysis and the pathological results. Concordance between the endoscopic diagnosis and diagnosis by a real-time image recognition system with a support vector machine output value was 97.5% (115/118). Accuracy between the histologic findings of diminutive colorectal lesions (polyps) and diagnosis by a real-time image recognition system with a support vector machine output value was 93.2% (sensitivity, 93.0%; specificity, 93.3%; positive predictive value (PPV), 93.0%; and negative predictive value, 93.3%). Although further investigation is necessary to establish our computer-aided diagnosis system, this real-time image recognition system may satisfy the PIVI recommendations and be useful for predicting the histology of colorectal tumors. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

A visual grading study for different administered activity levels in bone scintigraphy.

PubMed

Gustafsson, Agnetha; Karlsson, Henrik; Nilsson, Kerstin A; Geijer, Håkan; Olsson, Anna

2015-05-01

The aim of the study is to assess the administered activity levels versus visual-based image quality using visual grading regression (VGR) including an assessment of the newly stated image criteria for whole-body bone scintigraphy. A total of 90 patients was included and grouped in three levels of administered activity: 400, 500 and 600 MBq. Six clinical image criteria regarding image quality was formulated by experienced nuclear medicine physicians. Visual grading was performed in all images, where three physicians rated the fulfilment of the image criteria on a four-step ordinal scale. The results were analysed using VGR. A count analysis was also made where the total number of counts in both views was registered. The administered activity of 600 MBq gives significantly better image quality than 400 MBq in five of six criteria (P<0·05). Comparing the administered activity of 600 MBq to 500 MBq, four criteria of six show significantly better image quality (P<0·05). The administered activity of 500 MBq gives no significantly better image quality than 400 Mbq (P<0·05). The count analysis shows that none of the three levels of administrated activity fulfil the recommendations by the EANM. There was a significant improvement in perceived image quality using an activity level of 600 MBq compared to lower activity levels in whole-body bone scintigraphy for the gamma camera equipment end set-up used in this study. This type of visual-based grading study seems to be a valuable tool and easy to implement in the clinical environment. © 2014 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Comparison of anterior segment optical coherence tomography angiography and fluorescein angiography for iris vasculature analysis.

PubMed

Zett, Claudio; Stina, Deborah M Rosa; Kato, Renata Tiemi; Novais, Eduardo Amorim; Allemann, Norma

2018-04-01

The aim of this study is to perform imaging of irises of different colors using spectral domain anterior segment optical coherence tomography angiography (AS-OCTA) and iris fluorescein angiography (IFA) and compare their effectiveness in examining iris vasculature. This is a cross-sectional observational clinical study. Patients with no vascular iris alterations and different pigmentation levels were recruited. Participants were imaged using OCTA adapted with an anterior segment lens and IFA with a confocal scanning laser ophthalmoscope (cSLO) adapted with an anterior segment lens. AS-OCTA and IFA images were then compared. Two blinded readers classified iris pigmentation and compared the percentage of visible vessels between OCTA and IFA images. Twenty eyes of 10 patients with different degrees of iris pigmentation were imaged using AS-OCTA and IFA. Significantly more visible iris vessels were observed using OCTA than using FA (W = 5.22; p < 0.001). Iris pigmentation was negatively correlated to the percentage of visible vessels in both imaging methods (OCTA, rho = - 0.73, p < 0.001; IFA, rho = - 0.77, p < 0.001). Unlike FA, AS-OCTA could not detect leakage of dye, delay, or impregnation. Nystagmus and inadequate fixation along with motion artifacts resulted in lower quality images in AS-OCTA than in IFA. AS-OCTA is a new imaging modality which allows analysis of iris vasculature. In both AS-OCTA and IFA, iris pigmentation caused vasculature imaging blockage, but AS-OCTA provided more detailed iris vasculature images than IFA. Additional studies including different iris pathologies are needed to determine the most optimal scanning parameters in OCTA of the anterior segment.

Preclinical Imaging for the Study of Mouse Models of Thyroid Cancer

PubMed Central

Greco, Adelaide; Orlandella, Francesca Maria; Iervolino, Paola Lucia Chiara; Klain, Michele; Salvatore, Giuliana

2017-01-01

Thyroid cancer, which represents the most common tumors among endocrine malignancies, comprises a wide range of neoplasms with different clinical aggressiveness. One of the most important challenges in research is to identify mouse models that most closely resemble human pathology; other goals include finding a way to detect markers of disease that common to humans and mice and to identify the most appropriate and least invasive therapeutic strategies for specific tumor types. Preclinical thyroid imaging includes a wide range of techniques that allow for morphological and functional characterization of thyroid disease as well as targeting and in most cases, this imaging allows quantitative analysis of the molecular pattern of the thyroid cancer. The aim of this review paper is to provide an overview of all of the imaging techniques used to date both for diagnosis and theranostic purposes in mouse models of thyroid cancer. PMID:29258188

Representations in plastic surgery: the impact of self-image and self-confidence in the work environment.

PubMed

Foustanos, A; Pantazi, L; Zavrides, H

2007-01-01

This research was initiated by the authors' conviction that many people currently pay great attention to their personal appearance, which is directly linked to their self-confidence. The external image of individuals appears to have a decisive influence on their behavior and personal choices regarding both their personal and professional lives. Accordingly, it can be assumed that appearance influences professional choices and development. Moreover, individuals associate increased self-confidence with positive social images. Therefore, the main variables used in this study were self-image, self-confidence, and work environment. For the purpose of this study, the authors developed a questionnaire and distributed it to a sample of 100 women who had undergone aesthetic plastic surgery. The aim of the questionnaire was to discover the opinion of these women concerning the aforementioned assumptions. After the data processing and analysis, the authors concluded that the aforementioned variables are statistically significant and correlated.

Neural classifier in the estimation process of maturity of selected varieties of apples

NASA Astrophysics Data System (ADS)

Boniecki, P.; Piekarska-Boniecka, H.; Koszela, K.; Zaborowicz, M.; Przybył, K.; Wojcieszak, D.; Zbytek, Z.; Ludwiczak, A.; Przybylak, A.; Lewicki, A.

2015-07-01

This paper seeks to present methods of neural image analysis aimed at estimating the maturity state of selected varieties of apples which are popular in Poland. An identification of the degree of maturity of selected varieties of apples has been conducted on the basis of information encoded in graphical form, presented in the digital photos. The above process involves the application of the BBCH scale, used to determine the maturity of apples. The aforementioned scale is widely used in the EU and has been developed for many species of monocotyledonous plants and dicotyledonous plants. It is also worth noticing that the given scale enables detailed determinations of development stage of a given plant. The purpose of this work is to identify maturity level of selected varieties of apples, which is supported by the use of image analysis methods and classification techniques represented by artificial neural networks. The analysis of graphical representative features based on image analysis method enabled the assessment of the maturity of apples. For the utilitarian purpose the "JabVis 1.1" neural IT system was created, in accordance with requirements of the software engineering dedicated to support the decision-making processes occurring in broadly understood production process and processing of apples.

Hyperspectral imaging and multivariate analysis in the dried blood spots investigations

NASA Astrophysics Data System (ADS)

Majda, Alicja; Wietecha-Posłuszny, Renata; Mendys, Agata; Wójtowicz, Anna; Łydżba-Kopczyńska, Barbara

2018-04-01

The aim of this study was to apply a new methodology using the combination of the hyperspectral imaging and the dry blood spot (DBS) collecting. Application of the hyperspectral imaging is fast and non-destructive. DBS method offers the advantage also on the micro-invasive blood collecting and low volume of required sample. During experimental step, the reflected light was recorded by two hyperspectral systems. The collection of 776 spectral bands in the VIS-NIR range (400-1000 nm) and 256 spectral bands in the SWIR range (970-2500 nm) was applied. Pixel has the size of 8 × 8 and 30 × 30 µm for VIS-NIR and SWIR camera, respectively. The obtained data in the form of hyperspectral cubes were treated with chemometric methods, i.e., minimum noise fraction and principal component analysis. It has been shown that the application of these methods on this type of data, by analyzing the scatter plots, allows a rapid analysis of the homogeneity of DBS, and the selection of representative areas for further analysis. It also gives the possibility of tracking the dynamics of changes occurring in biological traces applied on the surface. For the analyzed 28 blood samples, described method allowed to distinguish those blood stains because of time of apply.

Clinical usefulness of magnifying endoscopy for non-ampullary duodenal tumors.

PubMed

Mizumoto, Takeshi; Sanomura, Yoji; Tanaka, Shinji; Kuroki, Kazutoshi; Kurihara, Mio; Yoshifuku, Yoshikazu; Oka, Shiro; Arihiro, Koji; Shimamoto, Fumio; Chayama, Kazuaki

2017-04-01

Study aims  This study aimed to investigate the clinical usefulness of magnifying endoscopy (ME) for non-ampullary duodenal tumors. Patients and methods  We enrolled 103 consecutive patients with non-ampullary duodenal tumors that were observed by ME with narrow-band imaging (ME-NBI) and had pit pattern analysis before endoscopic resection at Hiroshima University Hospital before December 2014. ME-NBI images were classified as Type B or Type C according to the Hiroshima classification, and pit patterns were classified as regular or irregular. We studied the clinicopathological features and diagnoses with ME-NBI and pit pattern analyses according to the Vienna classification (category 3: 73 patients; category 4: 30 patients). Results  Category 4 lesions were significantly larger than category 3 lesions. According to ME-NBI images, category 4 Type C lesions (83 %) were significantly more common than category 4 Type B lesions (17 %). According to pit pattern analyses, category 4 irregular lesions 4 (77 %) were significantly more common than category 4 regular lesions (23 %). The accuracies of using Type C ME-NBI images and irregular pit patterns to diagnose category 4 lesions were 87 % and 84 %, the sensitivities were 83 % and 77 %, and the specificities were 89 % and 88 %, respectively. There was no significant difference between ME-NBI and pit pattern analyses for diagnosing the histologic grade of non-ampullary duodenal tumors. Conclusion  Our study showed that ME-NBI and pit pattern analysis had equivalent abilities to determine the histologic grade of non-ampullary duodenal tumors. ME-NBI may be more useful because it is a simple, less time-consuming procedure.

Presence and Image of Women in the Information Media Aimed at Adolescents Aged 10 to 16.

ERIC Educational Resources Information Center

Dansereau, Stephanie; Maranda, Jeanne

An exploratory study identified the areas of information most commonly featured in the printed and electronic media designed specifically for adolescents aged 10-16 and also identified the presence and role of women in the information targeted to this age group. A content analysis was made of both French- and English-language television programs…

An Analysis of the Educational Value of Low-Fidelity Anatomy Models as External Representations

ERIC Educational Resources Information Center

Chan, Lap Ki; Cheng, Maurice M. W.

2011-01-01

Although high-fidelity digital models of human anatomy based on actual cross-sectional images of the human body have been developed, reports on the use of physical models in anatomy teaching continue to appear. This article aims to examine the common features shared by these physical models and analyze their educational value based on the…

Anthropomorphism--Matters or Not? On Agent Modality and Its Implications for Teaching English Idioms and Design Decisions

ERIC Educational Resources Information Center

Ahmadi, Alireza; Sahragard, Rahman; Babaie Shalmani, Hamed

2017-01-01

The present study aimed to examine whether agent-based instruction would privilege English as a Foreign Language (EFL) learners any better than mainstream approaches (e.g. analogical reasoning, guessing from context, image formation, semantic analysis, etc.) when it comes to the teaching of English idioms. It also sought to explore whether…

The Practice: An Analysis of the Factors Influencing the Training of Health Care Participants through Innovative Technology

ERIC Educational Resources Information Center

Gattoni, Ali; Tenzek, Kelly E.

2010-01-01

The aim of this paper is to develop a theoretical framework for understanding how new technologies become a part of culture and change our traditional images of health care and providers. Using the diffusion of innovations theory provides an understanding of how providers can adopt technology into practice. More specifically, this paper focuses on…

Characteristics of Vocal Fold Vibrations in Vocally Healthy Subjects: Analysis with Multi-Line Kymography

ERIC Educational Resources Information Center

Yamauchi, Akihito; Imagawa, Hiroshi; Sakakibara, Ken-Ichi; Yokonishi, Hisayuki; Nito, Takaharu; Yamasoba, Tatsuya; Tayama, Niro

2014-01-01

Purpose: In this study, the authors aimed to analyze longitudinal data from high-speed digital images in normative subjects using multi-line kymography. Method: Vocally healthy subjects were divided into young (9 men and 17 women; M[subscript age] = 27 years) and older groups (8 men and 12 women; M[subscript age] = 73 years). From high-speed…

Cross-cultural adaptation of the Female Genital Self-Image Scale (FGSIS) in Iranian female college students.

PubMed

Pakpour, Amir H; Zeidi, Isa Mohammadi; Ziaeiha, Masoumeh; Burri, Andrea

2014-01-01

The aim of the present study was to investigate the psychometric properties of a translated and culturally adapted Iranian version of the Female Genital Self-Image Scale (FGSIS-I) in a sample of college women. Further, the relationship between women's self-image, body appreciation, sexual functioning, and gynecological exam behavior was explored. A sample of 1,877 female students from five different universities across Qazvin and Tehran completed the Female Sexual Function Index (FSFI), the Body Appreciation Scale (BAS), the Rosenberg Self-Esteem Scale (RSES), the FGSIS-I, and a gynecological exam behavior questionnaire. Good to excellent internal consistency reliability, test-retest reliability, and convergent and construct validity were found. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) both provided a two-factor structure for the FGSIS-I. The validity of the FGSIS-I in predicting gynecological exam behavior of college women was tested using structural equation modeling (SEM). The final model accounted for 33% of the variance in gynecological exam behavior (p < 0.01). In conclusion, the FGSIS-I was found to be a highly valid and reliable instrument to assess female genital self-image in Iranian women.

Bone histomorphometry using free and commonly available software

PubMed Central

Egan, Kevin P.; Brennan, Tracy A.; Pignolo, Robert J.

2012-01-01

Aims Histomorphometric analysis is a widely used technique to assess changes in tissue structure and function. Commercially-available programs that measure histomorphometric parameters can be cost prohibitive. In this study, we compared an inexpensive method of histomorphometry to a current proprietary software program. Methods and results Image J and Adobe Photoshop® were used to measure static and kinetic bone histomorphometric parameters. Photomicrographs of Goldner’s Trichrome stained femurs were used to generate black and white image masks, representing bone and non-bone tissue, respectively, in Adobe Photoshop®. The masks were used to quantify histomorphometric parameters (bone volume, tissue volume, osteoid volume, mineralizing surface, and interlabel width) in Image J. The resultant values obtained using Image J and the proprietary software were compared and found to be statistically non-significant. Conclusions The wide ranging use of histomorphometric analysis for assessing the basic morphology of tissue components makes it important to have affordable and accurate measurement options that are available for a diverse range of applications. Here we have developed and validated an approach to histomorphometry using commonly and freely available software that is comparable to a much more costly, commercially-available software program. PMID:22882309

Distributed memory parallel Markov random fields using graph partitioning

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

Heinemann, C.; Perciano, T.; Ushizima, D.

Markov random fields (MRF) based algorithms have attracted a large amount of interest in image analysis due to their ability to exploit contextual information about data. Image data generated by experimental facilities, though, continues to grow larger and more complex, making it more difficult to analyze in a reasonable amount of time. Applying image processing algorithms to large datasets requires alternative approaches to circumvent performance problems. Aiming to provide scientists with a new tool to recover valuable information from such datasets, we developed a general purpose distributed memory parallel MRF-based image analysis framework (MPI-PMRF). MPI-PMRF overcomes performance and memory limitationsmore » by distributing data and computations across processors. The proposed approach was successfully tested with synthetic and experimental datasets. Additionally, the performance of the MPI-PMRF framework is analyzed through a detailed scalability study. We show that a performance increase is obtained while maintaining an accuracy of the segmentation results higher than 98%. The contributions of this paper are: (a) development of a distributed memory MRF framework; (b) measurement of the performance increase of the proposed approach; (c) verification of segmentation accuracy in both synthetic and experimental, real-world datasets« less

Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Zhao, Yan-Ru; Yu, Ke-Qiang; Li, Xiaoli; He, Yong

2016-12-01

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.

Deciphering protein signatures using color, morphological, and topological analysis of immunohistochemically stained human tissues

NASA Astrophysics Data System (ADS)

Zerhouni, Erwan; Prisacari, Bogdan; Zhong, Qing; Wild, Peter; Gabrani, Maria

2016-03-01

Images of tissue specimens enable evidence-based study of disease susceptibility and stratification. Moreover, staining technologies empower the evidencing of molecular expression patterns by multicolor visualization, thus enabling personalized disease treatment and prevention. However, translating molecular expression imaging into direct health benefits has been slow. Two major factors contribute to that. On the one hand, disease susceptibility and progression is a complex, multifactorial molecular process. Diseases, such as cancer, exhibit cellular heterogeneity, impeding the differentiation between diverse grades or types of cell formations. On the other hand, the relative quantification of the stained tissue selected features is ambiguous, tedious and time consuming, prone to clerical error, leading to intra- and inter-observer variability and low throughput. Image analysis of digital histopathology images is a fast-developing and exciting area of disease research that aims to address the above limitations. We have developed a computational framework that extracts unique signatures using color, morphological and topological information and allows the combination thereof. The integration of the above information enables diagnosis of disease with AUC as high as 0.97. Multiple staining show significant improvement with respect to most proteins, and an AUC as high as 0.99.

Least significant qubit algorithm for quantum images

NASA Astrophysics Data System (ADS)

Sang, Jianzhi; Wang, Shen; Li, Qiong

2016-11-01

To study the feasibility of the classical image least significant bit (LSB) information hiding algorithm on quantum computer, a least significant qubit (LSQb) information hiding algorithm of quantum image is proposed. In this paper, we focus on a novel quantum representation for color digital images (NCQI). Firstly, by designing the three qubits comparator and unitary operators, the reasonability and feasibility of LSQb based on NCQI are presented. Then, the concrete LSQb information hiding algorithm is proposed, which can realize the aim of embedding the secret qubits into the least significant qubits of RGB channels of quantum cover image. Quantum circuit of the LSQb information hiding algorithm is also illustrated. Furthermore, the secrets extracting algorithm and circuit are illustrated through utilizing control-swap gates. The two merits of our algorithm are: (1) it is absolutely blind and (2) when extracting secret binary qubits, it does not need any quantum measurement operation or any other help from classical computer. Finally, simulation and comparative analysis show the performance of our algorithm.

An Optical Method for the In-Vivo Characterization of the Biomechanical Response of the Right Ventricle.

PubMed

Soltani, A; Lahti, J; Järvelä, K; Curtze, S; Laurikka, J; Hokka, M; Kuokkala, V-T

2018-05-01

The intraoperative in-vivo mechanical function of the left ventricle has been studied thoroughly using echocardiography in the past. However, due to technical and anatomical issues, the ultrasound technology cannot easily be focused on the right side of the heart during open-heart surgery, and the function of the right ventricle during the intervention remains largely unexplored. We used optical imaging and digital image correlation for the characterization of the right ventricle motion and deformation during open-heart surgery. This work is a pilot study focusing on one patient only with the aim of establishing the framework for long term research. These experiments show that optical imaging and the analysis of the images can be used to obtain similar parameters, and partly at higher accuracy, for describing the mechanical functioning of the heart as the ultrasound technology. This work describes the optical imaging based method to characterize the mechanical response of the heart in-vivo, and offers new insight into the mechanical function of the right ventricle.

Computational model of lightness perception in high dynamic range imaging

NASA Astrophysics Data System (ADS)

Krawczyk, Grzegorz; Myszkowski, Karol; Seidel, Hans-Peter

2006-02-01

An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

Cost-effectiveness modelling in diagnostic imaging: a stepwise approach.

PubMed

Sailer, Anna M; van Zwam, Wim H; Wildberger, Joachim E; Grutters, Janneke P C

2015-12-01

Diagnostic imaging (DI) is the fastest growing sector in medical expenditures and takes a central role in medical decision-making. The increasing number of various and new imaging technologies induces a growing demand for cost-effectiveness analysis (CEA) in imaging technology assessment. In this article we provide a comprehensive framework of direct and indirect effects that should be considered for CEA in DI, suitable for all imaging modalities. We describe and explain the methodology of decision analytic modelling in six steps aiming to transfer theory of CEA to clinical research by demonstrating key principles of CEA in a practical approach. We thereby provide radiologists with an introduction to the tools necessary to perform and interpret CEA as part of their research and clinical practice. • DI influences medical decision making, affecting both costs and health outcome. • This article provides a comprehensive framework for CEA in DI. • A six-step methodology for conducting and interpreting cost-effectiveness modelling is proposed.

Live dynamic imaging and analysis of developmental cardiac defects in mouse models with optical coherence tomography

NASA Astrophysics Data System (ADS)

Lopez, Andrew L.; Wang, Shang; Garcia, Monica; Valladolid, Christian; Larin, Kirill V.; Larina, Irina V.

2015-03-01

Understanding mouse embryonic development is an invaluable resource for our interpretation of normal human embryology and congenital defects. Our research focuses on developing methods for live imaging and dynamic characterization of early embryonic development in mouse models of human diseases. Using multidisciplinary methods: optical coherence tomography (OCT), live mouse embryo manipulations and static embryo culture, molecular biology, advanced image processing and computational modeling we aim to understand developmental processes. We have developed an OCT based approach to image live early mouse embryos (E8.5 - E9.5) cultured on an imaging stage and visualize developmental events with a spatial resolution of a few micrometers (less than the size of an individual cell) and a frame rate of up to hundreds of frames per second and reconstruct cardiodynamics in 4D (3D+time). We are now using these methods to study how specific embryonic lethal mutations affect cardiac morphology and function during early development.

An Overview of data science uses in bioimage informatics.

PubMed

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.

The Scientific Image in Behavior Analysis.

PubMed

Keenan, Mickey

2016-05-01

Throughout the history of science, the scientific image has played a significant role in communication. With recent developments in computing technology, there has been an increase in the kinds of opportunities now available for scientists to communicate in more sophisticated ways. Within behavior analysis, though, we are only just beginning to appreciate the importance of going beyond the printing press to elucidate basic principles of behavior. The aim of this manuscript is to stimulate appreciation of both the role of the scientific image and the opportunities provided by a quick response code (QR code) for enhancing the functionality of the printed page. I discuss the limitations of imagery in behavior analysis ("Introduction"), and I show examples of what can be done with animations and multimedia for teaching philosophical issues that arise when teaching about private events ("Private Events 1 and 2"). Animations are also useful for bypassing ethical issues when showing examples of challenging behavior ("Challenging Behavior"). Each of these topics can be accessed only by scanning the QR code provided. This contingency has been arranged to help the reader embrace this new technology. In so doing, I hope to show its potential for going beyond the limitations of the printing press.

Interpretative Guidelines and Possible Indications for Indocyanine Green Fluorescence Imaging in Robot-Assisted Sphincter-Saving Operations.

PubMed

Kim, Jin Cheon; Lee, Jong Lyul; Park, Seong Ho

2017-04-01

Since the introduction of indocyanine green angiography more than 25 years ago, few studies have presented interpretative guidelines for indocyanine green fluorescent imaging. We aimed to provide interpretative guidelines for indocyanine green fluorescent imaging through quantitative analysis and to suggest possible indications for indocyanine green fluorescent imaging during robot-assisted sphincter-saving operations. This is a retrospective observational study. This study was conducted at a single center. A cohort of 657 patients with rectal cancer who consecutively underwent curative robot-assisted sphincter-saving operations was enrolled between 2010 and 2016, including 310 patients with indocyanine green imaging (indocyanine green fluorescent imaging+ group) and 347 patients without indocyanine green imaging (indocyanine green fluorescent imaging- group). We tried to quantitatively define the indocyanine green fluorescent imaging findings based on perfusion (mesocolic and colic) time and perfusion intensity (5 grades) to provide probable indications. The anastomotic leakage rate was significantly lower in the indocyanine green fluorescent imaging+ group than in the indocyanine green fluorescent imaging- group (0.6% vs 5.2%) (OR, 0.123; 95% CI, 0.028-0.544; p = 0.006). Anastomotic stricture was closely correlated with anastomotic leakage (p = 0.002) and a short descending mesocolon (p = 0.003). Delayed perfusion (>60 s) and low perfusion intensity (1-2) were more frequently detected in patients with anastomotic stricture and marginal artery defects than in those without these factors (p ≤ 0.001). In addition, perfusion times greater than the mean were more frequently observed in patients aged >58 years, whereas low perfusion intensity was seen more in patients with short descending mesocolon and high ASA classes (≥3). The 300 patients in the indocyanine green fluorescent imaging- group underwent operations 3 years before indocyanine green fluorescent imaging. Quantitative analysis of indocyanine green fluorescent imaging may help prevent anastomotic complications during robot-assisted sphincter-saving operations, and may be of particular value in high-class ASA patients, older patients, and patients with a short descending mesocolon.

An automated form of video image analysis applied to classification of movement disorders.

PubMed

Chang, R; Guan, L; Burne, J A

Video image analysis is able to provide quantitative data on postural and movement abnormalities and thus has an important application in neurological diagnosis and management. The conventional techniques require patients to be videotaped while wearing markers in a highly structured laboratory environment. This restricts the utility of video in routine clinical practise. We have begun development of intelligent software which aims to provide a more flexible system able to quantify human posture and movement directly from whole-body images without markers and in an unstructured environment. The steps involved are to extract complete human profiles from video frames, to fit skeletal frameworks to the profiles and derive joint angles and swing distances. By this means a given posture is reduced to a set of basic parameters that can provide input to a neural network classifier. To test the system's performance we videotaped patients with dopa-responsive Parkinsonism and age-matched normals during several gait cycles, to yield 61 patient and 49 normal postures. These postures were reduced to their basic parameters and fed to the neural network classifier in various combinations. The optimal parameter sets (consisting of both swing distances and joint angles) yielded successful classification of normals and patients with an accuracy above 90%. This result demonstrated the feasibility of the approach. The technique has the potential to guide clinicians on the relative sensitivity of specific postural/gait features in diagnosis. Future studies will aim to improve the robustness of the system in providing accurate parameter estimates from subjects wearing a range of clothing, and to further improve discrimination by incorporating more stages of the gait cycle into the analysis.

A New Method for Non-destructive Measurement of Biomass, Growth Rates, Vertical Biomass Distribution and Dry Matter Content Based on Digital Image Analysis

PubMed Central

Tackenberg, Oliver

2007-01-01

Background and Aims Biomass is an important trait in functional ecology and growth analysis. The typical methods for measuring biomass are destructive. Thus, they do not allow the development of individual plants to be followed and they require many individuals to be cultivated for repeated measurements. Non-destructive methods do not have these limitations. Here, a non-destructive method based on digital image analysis is presented, addressing not only above-ground fresh biomass (FBM) and oven-dried biomass (DBM), but also vertical biomass distribution as well as dry matter content (DMC) and growth rates. Methods Scaled digital images of the plants silhouettes were taken for 582 individuals of 27 grass species (Poaceae). Above-ground biomass and DMC were measured using destructive methods. With image analysis software Zeiss KS 300, the projected area and the proportion of greenish pixels were calculated, and generalized linear models (GLMs) were developed with destructively measured parameters as dependent variables and parameters derived from image analysis as independent variables. A bootstrap analysis was performed to assess the number of individuals required for re-calibration of the models. Key Results The results of the developed models showed no systematic errors compared with traditionally measured values and explained most of their variance (R2 ≥ 0·85 for all models). The presented models can be directly applied to herbaceous grasses without further calibration. Applying the models to other growth forms might require a re-calibration which can be based on only 10–20 individuals for FBM or DMC and on 40–50 individuals for DBM. Conclusions The methods presented are time and cost effective compared with traditional methods, especially if development or growth rates are to be measured repeatedly. Hence, they offer an alternative way of determining biomass, especially as they are non-destructive and address not only FBM and DBM, but also vertical biomass distribution and DMC. PMID:17353204

Plasma cell quantification in bone marrow by computer-assisted image analysis.

PubMed

Went, P; Mayer, S; Oberholzer, M; Dirnhofer, S

2006-09-01

Minor and major criteria for the diagnosis of multiple meloma according to the definition of the WHO classification include different categories of the bone marrow plasma cell count: a shift from the 10-30% group to the > 30% group equals a shift from a minor to a major criterium, while the < 10% group does not contribute to the diagnosis. Plasma cell fraction in the bone marrow is therefore critical for the classification and optimal clinical management of patients with plasma cell dyscrasias. The aim of this study was (i) to establish a digital image analysis system able to quantify bone marrow plasma cells and (ii) to evaluate two quantification techniques in bone marrow trephines i.e. computer-assisted digital image analysis and conventional light-microscopic evaluation. The results were compared regarding inter-observer variation of the obtained results. Eighty-seven patients, 28 with multiple myeloma, 29 with monoclonal gammopathy of undetermined significance, and 30 with reactive plasmocytosis were included in the study. Plasma cells in H&E- and CD138-stained slides were quantified by two investigators using light-microscopic estimation and computer-assisted digital analysis. The sets of results were correlated with rank correlation coefficients. Patients were categorized according to WHO criteria addressing the plasma cell content of the bone marrow (group 1: 0-10%, group 2: 11-30%, group 3: > 30%), and the results compared by kappa statistics. The degree of agreement in CD138-stained slides was higher for results obtained using the computer-assisted image analysis system compared to light microscopic evaluation (corr.coeff. = 0.782), as was seen in the intra- (corr.coeff. = 0.960) and inter-individual results correlations (corr.coeff. = 0.899). Inter-observer agreement for categorized results (SM/PW: kappa 0.833) was in a high range. Computer-assisted image analysis demonstrated a higher reproducibility of bone marrow plasma cell quantification. This might be of critical importance for diagnosis, clinical management and prognostics when plasma cell numbers are low, which makes exact quantifications difficult.

Hydraulic separation of plastic wastes: Analysis of liquid-solid interaction.

PubMed

Moroni, Monica; Lupo, Emanuela; La Marca, Floriana

2017-08-01

The separation of plastic wastes in mechanical recycling plants is the process that ensures high-quality secondary raw materials. An innovative device employing a wet technology for particle separation is presented in this work. Due to the combination of the characteristic flow pattern developing within the apparatus and density, shape and size differences among two or more polymers, it allows their separation into two products, one collected within the instrument and the other one expelled through its outlet ducts. The kinematic investigation of the fluid flowing within the apparatus seeded with a passive tracer was conducted via image analysis for different hydraulic configurations. The two-dimensional turbulent kinetic energy results strictly connected to the apparatus separation efficacy. Image analysis was also employed to study the behaviour of mixtures of passive tracer and plastic particles with different physical characteristics in order to understand the coupling regime between fluid and solid phases. The two-dimensional turbulent kinetic energy analysis turned out to be fundamental to this aim. For the tested operating conditions, two-way coupling takes place, i.e., the fluid exerts an influence on the plastic particle and the opposite occurs too. Image analysis confirms the outcomes from the investigation of the two-phase flow via non-dimensional numbers (particle Reynolds number, Stokes number and solid phase volume fraction). Copyright © 2017 Elsevier Ltd. All rights reserved.

Dual-Energy CT: New Horizon in Medical Imaging

PubMed Central

Goo, Jin Mo

2017-01-01

Dual-energy CT has remained underutilized over the past decade probably due to a cumbersome workflow issue and current technical limitations. Clinical radiologists should be made aware of the potential clinical benefits of dual-energy CT over single-energy CT. To accomplish this aim, the basic principle, current acquisition methods with advantages and disadvantages, and various material-specific imaging methods as clinical applications of dual-energy CT should be addressed in detail. Current dual-energy CT acquisition methods include dual tubes with or without beam filtration, rapid voltage switching, dual-layer detector, split filter technique, and sequential scanning. Dual-energy material-specific imaging methods include virtual monoenergetic or monochromatic imaging, effective atomic number map, virtual non-contrast or unenhanced imaging, virtual non-calcium imaging, iodine map, inhaled xenon map, uric acid imaging, automatic bone removal, and lung vessels analysis. In this review, we focus on dual-energy CT imaging including related issues of radiation exposure to patients, scanning and post-processing options, and potential clinical benefits mainly to improve the understanding of clinical radiologists and thus, expand the clinical use of dual-energy CT; in addition, we briefly describe the current technical limitations of dual-energy CT and the current developments of photon-counting detector. PMID:28670151

Diaphragm breathing movement measurement using ultrasound and radiographic imaging: a concurrent validity.

PubMed

Noh, Dong K; Lee, Jae J; You, Joshua H

2014-01-01

Recent ultrasound imaging evidence asserts that the diaphragm is an important multifunctional muscle to control breathing as well as stabilize the core and posture in humans. However, the validity and accuracy of ultrasound for the measurement of dynamic diaphragm movements during breathing and functional core activities have not been determined. The specific aim of this study was to validate the accuracy of ultrasound imaging measurements of diaphragm movements by concurrently comparing these measurements to the gold standard of radiographic imaging measurements. A total of 14 asymptomatic adults (9 males, 5 females; mean age =28.4 ± 3.0 years) were recruited to participate in the study. Ultrasound and radiographic images were used concurrently to determine diaphragm movement (inspiration, expiration, and excursion) during tidal breathing. Pearson correlation analysis showed strong correlations, ranging from r=0.78 to r=0.83, between ultrasound and radiographic imaging measurements of the diaphragm during inhalation, exhalation, and excursion. These findings suggest that ultrasound imaging measurement is useful to accurately evaluate diaphragm movements during tidal breathing. Clinically, ultrasound imaging measurements can be used to diagnose and treat diaphragm movement impairments in individuals with neuromuscular disorders including spinal cord injuries, stroke, and multiple sclerosis.

Optimization of OSEM parameters in myocardial perfusion imaging reconstruction as a function of body mass index: a clinical approach*

PubMed Central

de Barros, Pietro Paolo; Metello, Luis F.; Camozzato, Tatiane Sabriela Cagol; Vieira, Domingos Manuel da Silva

2015-01-01

Objective The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients’ body mass index. Materials and Methods The present study included 28 adult patients submitted to myocardial perfusion imaging in a public hospital. The OSEM method was utilized in the images reconstruction with six different combinations of iterations and subsets numbers. The images were analyzed by nuclear cardiology specialists taking their diagnostic value into consideration and indicating the most appropriate images in terms of diagnostic quality. Results An overall scoring analysis demonstrated that the combination of four iterations and four subsets has generated the most appropriate images in terms of diagnostic quality for all the classes of body mass index; however, the role played by the combination of six iterations and four subsets is highlighted in relation to the higher body mass index classes. Conclusion The use of optimized parameters seems to play a relevant role in the generation of images with better diagnostic quality, ensuring the diagnosis and consequential appropriate and effective treatment for the patient. PMID:26543282

Development of an adaptive bilateral filter for evaluating color image difference

NASA Astrophysics Data System (ADS)

Wang, Zhaohui; Hardeberg, Jon Yngve

2012-04-01

Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

Autofluorescence endoscopy with "real-time" digital image processing in differential diagnostics of selected benign and malignant lesions in the oesophagus.

PubMed

Sieroń-Stołtny, Karolina; Kwiatek, Sebastian; Latos, Wojciech; Kawczyk-Krupka, Aleksandra; Cieślar, Grzegorz; Stanek, Agata; Ziaja, Damian; Bugaj, Andrzej M; Sieroń, Aleksander

2012-03-01

Oesophageal papilloma and Barrett's oesophagus are benign lesions known as risk factors of carcinoma in the oesophagus. Therefore, it is important to diagnose these early changes before neoplastic transformation. Autofluorescence endoscopy is a fast and non-invasive method of imaging of tissues based on the natural fluorescence of endogenous fluorophores. The aim of this study was to prove the diagnostic utility of autofluorescence endoscopy with digital image processing in histological diagnosis of endoscopic findings in the upper digestive tract, primarily in the imaging of oesophageal papilloma. During the retrospective analysis of about 200 endoscopic procedures in the upper digestive tract, 67 cases of benign, precancerous or cancerous changes were found. White light endoscopy (WLE) image, single-channel (red or green) autofluorescence images, as well as green and red fluorescence intensities in two modal fluorescence image and red-to-green (R/G) ratio (Numerical Colour Value, NCV) were correlated with histopathologic results. The NCV analysis in autofluorescence imaging (AFI) showed increased R/G ratio in cancerous changes in 96% vs. 85% in WLE. Simultaneous analysis with digital image processing allowed us to diagnose suspicious tissue as cancerous in all of cases. Barrett's metaplasia was confirmed in 90% vs. 79% (AFI vs. WLE), and 98% in imaging with digital image processing. In benign lesions, WLE allowed us to exclude tissue as malignant in 85%. Using autofluorescence endoscopy R/G ratio was increased in only 10% of benign changes causing the picture to be interpreted as suspicious, but when both methods were used together, 97.5% were cases excluded as malignancies. Mean R/G ratios were estimated to be 2.5 in cancers, 1.25 in Barrett's metaplasia and 0.75 in benign changes and were statistically significant (p=0.04). Autofluorescence imaging is a sensitive method to diagnose precancerous and cancerous early stages of the diseases located in oesophagus. Especially in two-modal imaging including white light endoscopy, autofluorescence imaging with digital image processing seems to be a useful modality of early diagnostics. Also in observation of papilloma changes, it facilitates differentiation between neoplastic and benign lesions and more accurate estimation of the risk of potential malignancy. Copyright © 2011 Elsevier B.V. All rights reserved.

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer.

PubMed

Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey

2017-04-12

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm². Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted.

Histogram Analysis of Diffusion Weighted Imaging at 3T is Useful for Prediction of Lymphatic Metastatic Spread, Proliferative Activity, and Cellularity in Thyroid Cancer

PubMed Central

Schob, Stefan; Meyer, Hans Jonas; Dieckow, Julia; Pervinder, Bhogal; Pazaitis, Nikolaos; Höhn, Anne Kathrin; Garnov, Nikita; Horvath-Rizea, Diana; Hoffmann, Karl-Titus; Surov, Alexey

2017-01-01

Pre-surgical diffusion weighted imaging (DWI) is increasingly important in the context of thyroid cancer for identification of the optimal treatment strategy. It has exemplarily been shown that DWI at 3T can distinguish undifferentiated from well-differentiated thyroid carcinoma, which has decisive implications for the magnitude of surgery. This study used DWI histogram analysis of whole tumor apparent diffusion coefficient (ADC) maps. The primary aim was to discriminate thyroid carcinomas which had already gained the capacity to metastasize lymphatically from those not yet being able to spread via the lymphatic system. The secondary aim was to reflect prognostically important tumor-biological features like cellularity and proliferative activity with ADC histogram analysis. Fifteen patients with follicular-cell derived thyroid cancer were enrolled. Lymph node status, extent of infiltration of surrounding tissue, and Ki-67 and p53 expression were assessed in these patients. DWI was obtained in a 3T system using b values of 0, 400, and 800 s/mm2. Whole tumor ADC volumes were analyzed using a histogram-based approach. Several ADC parameters showed significant correlations with immunohistopathological parameters. Most importantly, ADC histogram skewness and ADC histogram kurtosis were able to differentiate between nodal negative and nodal positive thyroid carcinoma. Conclusions: histogram analysis of whole ADC tumor volumes has the potential to provide valuable information on tumor biology in thyroid carcinoma. However, further studies are warranted. PMID:28417929

Evaluation of longitudinal tracking and data mining for an imaging informatics-based multiple sclerosis e-folder (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ma, Kevin C.; Forsyth, Sydney; Amezcua, Lilyana; Liu, Brent J.

2017-03-01

We have designed and developed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results to allow patient tracking. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and data analysis. The system quantifies lesion volumes, identify and register lesion locations to track shifts in volume and quantity of lesions in a longitudinal study. We aim to evaluate the two most important features of the system, data mining and longitudinal lesion tracking, to demonstrate the MS eFolder's capability in improving clinical workflow efficiency and outcome analysis for research. In order to evaluate data mining capabilities, we have collected radiological and neurological data from 72 patients, 36 Caucasian and 36 Hispanic matched by gender, disease duration, and age. Data analysis on those patients based on ethnicity is performed, and analysis results are displayed by the system's web-based user interface. The data mining module is able to successfully separate Hispanic and Caucasian patients and compare their disease profiles. For longitudinal lesion tracking, we have collected 4 longitudinal cases and simulated different lesion growths over the next year. As a result, the eFolder is able to detect changes in lesion volume and identifying lesions with the most changes. Data mining and lesion tracking evaluation results show high potential of eFolder's usefulness in patientcare and informatics research for multiple sclerosis.

Eating disorders and anabolic androgenic steroids in males - similarities and differences in self-image and psychiatric symptoms

PubMed Central

2013-01-01

Background Body dissatisfaction is common among both females and males. Dissatisfaction with the body is a risk factor both for onset of eating disorders and for abuse of anabolic androgenic steroids (AAS). Few studies have however investigated if there are other similarities in respect to self-image or psychiatric symptoms between clinical samples of eating disordered males and males in treatment for negative effects of AAS use. Aim The aim of this study was to compare two clinical samples, one of males with ED and one of males who used AAS, regarding self-image and psychiatric symptoms. Methods This study compared males with eating disorders (n = 13) and males who recently stopped AAS use (n = 29) on self-image and psychiatric symptoms, using The Structural Analysis of Social Behavior self-questionnaire and a shortened version of The Symptom Check List. Results The eating disorder group reported significantly lower scores for Self-emancipation and Active self-love and higher scores for Self-blame and Self-hate. Both groups reported serious psychiatric symptoms. The common denominator between groups was serious psychiatric symptomatology rather than negative self-image. Conclusions The negative self-image profile, especially self-hate, found among males with Eating Disorders may indicate that the studied groups differ in aetiology of the underlying problems. The serious psychiatric symptoms in both groups call staff to pay attention to any thoughts of suicide due to severe depressive symptoms where by specialized psychiatric treatment may be needed. PMID:23958408

Spherical Images for Cultural Heritage: Survey and Documentation with the Nikon KM360

NASA Astrophysics Data System (ADS)

Gottardi, C.; Guerra, F.

2018-05-01

The work presented here focuses on the analysis of the potential of spherical images acquired with specific cameras for documentation and three-dimensional reconstruction of Cultural Heritage. Nowadays, thanks to the introduction of cameras able to generate panoramic images automatically, without the requirement of a stitching software to join together different photos, spherical images allow the documentation of spaces in an extremely fast and efficient way. In this particular case, the Nikon Key Mission 360 spherical camera was tested on the Tolentini's cloister, which used to be part of the convent of the close church and now location of the Iuav University of Venice. The aim of the research is based on testing the acquisition of spherical images with the KM360 and comparing the obtained photogrammetric models with data acquired from a laser scanning survey in order to test the metric accuracy and the level of detail achievable with this particular camera. This work is part of a wider research project that the Photogrammetry Laboratory of the Iuav University of Venice has been dealing with in the last few months; the final aim of this research project will be not only the comparison between 3D models obtained from spherical images and laser scanning survey's techniques, but also the examination of their reliability and accuracy with respect to the previous methods of generating spherical panoramas. At the end of the research work, we would like to obtain an operational procedure for spherical cameras applied to metric survey and documentation of Cultural Heritage.

Application of photogrammetry for analysis of occlusal contacts.

PubMed

Shigeta, Yuko; Hirabayashi, Rio; Ikawa, Tomoko; Kihara, Takuya; Ando, Eriko; Hirai, Shinya; Fukushima, Shunji; Ogawa, Takumi

2013-04-01

The conventional 2D-analysis methods for occlusal contacts provided limited information on tooth morphology. This present study aims to detect 3D positional information of occlusal contacts from 2D-photos via photogrammetry. We propose an image processing solution for analysis of occlusal contacts and facets via the black silicone method and a photogrammetric technique. The occlusal facets were reconstructed from a 2D-photograph data-set of inter-occlusal records into a 3D image via photogrammetry. The configuration of the occlusal surface was reproduced with polygons. In addition, the textures of the occlusal contacts were mapped to each polygon. DIFFERENCE FROM CONVENTIONAL METHODS: Constructing occlusal facets with 3D polygons from 2D-photos with photogrammetry was a defining characteristic of this image processing technique. It allowed us to better observe findings of the black silicone method. Compared with conventional 3D analysis using a 3D scanner, our 3D models did not reproduce the detail of the anatomical configuration. However, by merging the findings of the inter-occlusal record, the deformation of mandible and the displacement of periodontal ligaments under occlusal force were reflected in our model. EFFECT OR PERFORMANCE: Through the use of polygons in the conversion of 2D images to 3D images, we were able to define the relation between the location and direction of the occlusal contacts and facets, which was difficult to detect via conventional methods. Through our method of making a 3D polygon model, the findings of inter-occlusal records which reflected the jaw/teeth behavior under occlusal force could be observed 3-dimensionally. Copyright © 2012 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Automated flow quantification in valvular heart disease based on backscattered Doppler power analysis: implementation on matrix-array ultrasound imaging systems.

PubMed

Buck, Thomas; Hwang, Shawn M; Plicht, Björn; Mucci, Ronald A; Hunold, Peter; Erbel, Raimund; Levine, Robert A

2008-06-01

Cardiac ultrasound imaging systems are limited in the noninvasive quantification of valvular regurgitation due to indirect measurements and inaccurate hemodynamic assumptions. We recently demonstrated that the principle of integration of backscattered acoustic Doppler power times velocity can be used for flow quantification in valvular regurgitation directly at the vena contracta of a regurgitant flow jet. We now aimed to accomplish implementation of automated Doppler power flow analysis software on a standard cardiac ultrasound system utilizing novel matrix-array transducer technology with detailed description of system requirements, components and software contributing to the system. This system based on a 3.5 MHz, matrix-array cardiac ultrasound scanner (Sonos 5500, Philips Medical Systems) was validated by means of comprehensive experimental signal generator trials, in vitro flow phantom trials and in vivo testing in 48 patients with mitral regurgitation of different severity and etiology using magnetic resonance imaging (MRI) for reference. All measurements displayed good correlation to the reference values, indicating successful implementation of automated Doppler power flow analysis on a matrix-array ultrasound imaging system. Systematic underestimation of effective regurgitant orifice areas >0.65 cm(2) and volumes >40 ml was found due to currently limited Doppler beam width that could be readily overcome by the use of new generation 2D matrix-array technology. Automated flow quantification in valvular heart disease based on backscattered Doppler power can be fully implemented on board a routinely used matrix-array ultrasound imaging systems. Such automated Doppler power flow analysis of valvular regurgitant flow directly, noninvasively, and user independent overcomes the practical limitations of current techniques.

Quantitative fibrosis parameters highly predict esophageal-gastro varices in primary biliary cirrhosis.

PubMed

Wu, Q-M; Zhao, X-Y; You, H

2016-01-01

Esophageal-gastro Varices (EGV) may develop in any histological stages of primary biliary cirrhosis (PBC). We aim to establish and validate quantitative fibrosis (qFibrosis) parameters in portal, septal and fibrillar areas as ideal predictors of EGV in PBC patients. PBC patients with liver biopsy, esophagogastroscopy and Second Harmonic Generation (SHG)/Two-photon Excited Fluorescence (TPEF) microscopy images were retrospectively enrolled in this study. qFibrosis parameters in portal, septal and fibrillar areas were acquired by computer-assisted SHG/TPEF imaging system. Independent predictor was identified using multivariate logistic regression analysis. PBC patients with liver biopsy, esophagogastroscopy and Second Harmonic Generation (SHG)/Two-photon Excited Fluorescence (TPEF) microscopy images were retrospectively enrolled in this study. qFibrosis parameters in portal, septal and fibrillar areas were acquired by computer-assisted SHG/TPEF imaging system. Independent predictor was identified using multivariate logistic regression analysis. Among the forty-nine PBC patients with qFibrosis images, twenty-nine PBC patients with both esophagogastroscopy data and qFibrosis data were selected out for EGV prognosis analysis and 44.8% (13/29) of them had EGV. The qFibrosis parameters of collagen percentage and number of crosslink in fibrillar area, short/long/thin strings number and length/width of the strings in septa area were associated with EGV (p < 0.05). Multivariate logistic analysis showed that the collagen percentage in fibrillar area ≥ 3.6% was an independent factor to predict EGV (odds ratio 6.9; 95% confidence interval 1.6-27.4). The area under receiver operating characteristic (ROC), diagnostic sensitivity and specificity was 0.9, 100% and 75% respectively. Collagen percentage in Collagen percentage in the fibrillar area as an independent predictor can highly predict EGV in PBC patients.

Structural differences in interictal migraine attack after epilepsy: A diffusion tensor imaging analysis.

PubMed

Huang, Qi; Lv, Xin; He, Yushuang; Wei, Xing; Ma, Meigang; Liao, Yuhan; Qin, Chao; Wu, Yuan

2017-12-01

Patients with epilepsy (PWE) are more likely to suffer from migraine attack, and aberrant white matter (WM) organization may be the mechanism underlying this phenomenon. This study aimed to use diffusion tensor imaging (DTI) technique to quantify WM structural differences in PWE with interictal migraine. Diffusion tensor imaging data were acquired in 13 PWE with migraine and 12 PWE without migraine. Diffusion metrics were analyzed using tract-atlas-based spatial statistics analysis. Atlas-based and tract-based spatial statistical analyses were conducted for robustness analysis. Correlation was explored between altered DTI metrics and clinical parameters. The main results are as follows: (i) Axonal damage plays a key role in PWE with interictal migraine. (ii) Significant diffusing alterations included higher fractional anisotropy (FA) in the fornix, higher mean diffusivity (MD) in the middle cerebellar peduncle (CP), left superior CP, and right uncinate fasciculus, and higher axial diffusivity (AD) in the middle CP and right medial lemniscus. (iii) Diffusion tensor imaging metrics has the tendency of correlation with seizure/migraine type and duration. Results indicate that characteristic structural impairments exist in PWE with interictal migraine. Epilepsy may contribute to migraine by altering WMs in the brain stem. White matter tracts in the fornix and right uncinate fasciculus also mediate migraine after epilepsy. This finding may improve our understanding of the pathological mechanisms underlying migraine attack after epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.

Magnetic resonance imaging of focal cortical dysplasia: Comparison of 3D and 2D fluid attenuated inversion recovery sequences at 3T.

PubMed

Tschampa, Henriette J; Urbach, Horst; Malter, Michael; Surges, Rainer; Greschus, Susanne; Gieseke, Jürgen

2015-10-01

Focal cortical dysplasia (FCD) is a frequent finding in drug resistant epilepsy. The aim of our study was to evaluate an isotropic high-resolution 3-dimensional Fluid-attenuated inversion recovery sequence (3D FLAIR) at 3T in comparison to standard 2D FLAIR in the diagnosis of FCD. In a prospective study, 19 epilepsy patients with the MR diagnosis of FCD were examined with a sagittal 3D FLAIR sequence with modulated refocusing flip angle (slice thickness 1.10mm) and a 2D FLAIR in the coronal (thk. 3mm) and axial planes (thk. 2mm). Manually placed regions of interest were used for quantitative analysis. Qualitative image analysis was performed by two neuroradiologists in consensus. Contrast between gray and white matter (p ≤ 0.02), the lesion (p ≤ 0.031) or hyperintense extension to the ventricle (p ≤ 0.021) and white matter was significantly higher in 2D than in 3D FLAIR sequences. In the visual analysis there was no difference between 2D and 3D sequences. Conventional 2D FLAIR sequences yield a higher image contrast compared to the employed 3D FLAIR sequence in patients with FCDs. Potential advantages of 3D imaging using surface rendering or automated techniques for lesion detection have to be further elucidated. Copyright © 2015 Elsevier B.V. All rights reserved.

A pigment analysis tool for hyperspectral images of cultural heritage artifacts

NASA Astrophysics Data System (ADS)

Bai, Di; Messinger, David W.; Howell, David

2017-05-01

The Gough Map, in the collection at the Bodleian Library, Oxford University, is one of the earliest surviving maps of Britain. Previous research deemed that it was likely created over the 15th century and afterwards it was extensively revised more than once. In 2015, the Gough Map was imaged using a hyperspectral imaging system at the Bodleian Library. The collection of the hyperspectral image (HSI) data was aimed at faded text enhancement for reading and pigment analysis for the material diversity of its composition and potentially the timeline of its creation. In this research, we introduce several methods to analyze the green pigments in the Gough Map, especially the number and spatial distribution of distinct green pigments. One approach, called the Gram Matrix, has been used to estimate the material diversity in a scene (i.e., endmember selection and dimensionality estimation). Here, we use the Gram Matrix technique to study the within-material differences of pigments in the Gough map with common visual color. We develop a pigment analysis tool that extracts visually common pixels, green pigments in this case, from the Gough Map and estimates its material diversity. It reveals that the Gough Map consists of at least six kinds of dominant green pigments. Both historical geographers and cartographic historians will benefit from this work to analyze the pigment diversity using HSI of cultural heritage artifacts.

Analysis of the Image of Scientists Portrayed in the Lebanese National Science Textbooks

NASA Astrophysics Data System (ADS)

Yacoubian, Hagop A.; Al-Khatib, Layan; Mardirossian, Taline

2017-07-01

This article presents an analysis of how scientists are portrayed in the Lebanese national science textbooks. The purpose of this study was twofold. First, to develop a comprehensive analytical framework that can serve as a tool to analyze the image of scientists portrayed in educational resources. Second, to analyze the image of scientists portrayed in the Lebanese national science textbooks that are used in Basic Education. An analytical framework, based on an extensive review of the relevant literature, was constructed that served as a tool for analyzing the textbooks. Based on evidence-based stereotypes, the framework focused on the individual and work-related characteristics of scientists. Fifteen science textbooks were analyzed using both quantitative and qualitative measures. Our analysis of the textbooks showed the presence of a number of stereotypical images. The scientists are predominantly white males of European descent. Non-Western scientists, including Lebanese and/or Arab scientists are mostly absent in the textbooks. In addition, the scientists are portrayed as rational individuals who work alone, who conduct experiments in their labs by following the scientific method, and by operating within Eurocentric paradigms. External factors do not influence their work. They are engaged in an enterprise which is objective, which aims for discovering the truth out there, and which involves dealing with direct evidence. Implications for science education are discussed.

Effect of formulation and baking conditions on the structure and development of non-enzymatic browning in biscuit models using images.

PubMed

Leiva-Valenzuela, Gabriel A; Quilaqueo, Marcela; Lagos, Daniela; Estay, Danilo; Pedreschi, Franco

2018-04-01

The aim of this research was to determine the effect of composition (dietary fiber = DF, fat = F, and gluten = G) and baking time on the target microstructural parameters that were observed using images of potato and wheat starch biscuits. Microstructures were studied Scanning Electron Microscope (SEM). Non-enzymatic browning (NEB) was assessed using color image analysis. Texture and moisture analysis was performed to have a better understanding of the baking process. Analysis of images revealed that the starch granules retained their native form at the end of baking, suggesting their in complete gelatinization. Granules size was similar at several different baking times, with an average equivalent diameter of 9 and 27 µm for wheat and potato starch, respectively. However, samples with different levels of DF and G increased circularity during baking to more than 30%, and also increasing hardness. NEB developed during baking, with the maximum increase observed between 13 and 19 min. This was reflected in decreased luminosity (L*) values due to a decrease in moisture levels. After 19 min, luminosity did not vary significantly. The ingredients that are used, as well as their quantities, can affect sample L* values. Therefore, choosing the correct ingredients and quantities can lead to different microstructures in the biscuits, with varying amounts of NEB products.

[Development of analysis software package for the two kinds of Japanese fluoro-d-glucose-positron emission tomography guideline].

PubMed

Matsumoto, Keiichi; Endo, Keigo

2013-06-01

Two kinds of Japanese guidelines for the data acquisition protocol of oncology fluoro-D-glucose-positron emission tomography (FDG-PET)/computed tomography (CT) scans were created by the joint task force of the Japanese Society of Nuclear Medicine Technology (JSNMT) and the Japanese Society of Nuclear Medicine (JSNM), and published in Kakuigaku-Gijutsu 27(5): 425-456, 2007 and 29(2): 195-235, 2009. These guidelines aim to standardize PET image quality among facilities and different PET/CT scanner models. The objective of this study was to develop a personal computer-based performance measurement and image quality processor for the two kinds of Japanese guidelines for oncology (18)F-FDG PET/CT scans. We call this software package the "PET quality control tool" (PETquact). Microsoft Corporation's Windows(™) is used as the operating system for PETquact, which requires 1070×720 image resolution and includes 12 different applications. The accuracy was examined for numerous applications of PETquact. For example, in the sensitivity application, the system sensitivity measurement results were equivalent when comparing two PET sinograms obtained from the PETquact and the report. PETquact is suited for analysis of the two kinds of Japanese guideline, and it shows excellent spec to performance measurements and image quality analysis. PETquact can be used at any facility if the software package is installed on a laptop computer.

“Fitspiration” on Social Media: A Content Analysis of Gendered Images

PubMed Central

Prichard, Ivanka; Lim, Megan Su Cheng

2017-01-01

Background “Fitspiration” (also known as “fitspo”) aims to inspire individuals to exercise and be healthy, but emerging research indicates exposure can negatively impact female body image. Fitspiration is frequently accessed on social media; however, it is currently unclear the degree to which messages about body image and exercise differ by gender of the subject. Objective The aim of our study was to conduct a content analysis to identify the characteristics of fitspiration content posted across social media and whether this differs according to subject gender. Methods Content tagged with #fitspo across Instagram, Facebook, Twitter, and Tumblr was extracted over a composite 30-minute period. All posts were analyzed by 2 independent coders according to a codebook. Results Of the 415/476 (87.2%) relevant posts extracted, most posts were on Instagram (360/415, 86.8%). Most posts (308/415, 74.2%) related thematically to exercise, and 81/415 (19.6%) related thematically to food. In total, 151 (36.4%) posts depicted only female subjects and 114/415 (27.5%) depicted only male subjects. Female subjects were typically thin but toned; male subjects were often muscular or hypermuscular. Within the images, female subjects were significantly more likely to be aged under 25 years (P<.001) than the male subjects, to have their full body visible (P=.001), and to have their buttocks emphasized (P<.001). Male subjects were more likely to have their face visible in the post (P=.005) than the female subjects. Female subjects were more likely to be sexualized than the male subjects (P=.002). Conclusions Female #fitspo subjects typically adhered to the thin or athletic ideal, and male subjects typically adhered to the muscular ideal. Future research and interventional efforts should consider the potential objectifying messages in fitspiration, as it relates to both female and male body image. PMID:28356239

"Fitspiration" on Social Media: A Content Analysis of Gendered Images.

PubMed

Carrotte, Elise Rose; Prichard, Ivanka; Lim, Megan Su Cheng

2017-03-29

"Fitspiration" (also known as "fitspo") aims to inspire individuals to exercise and be healthy, but emerging research indicates exposure can negatively impact female body image. Fitspiration is frequently accessed on social media; however, it is currently unclear the degree to which messages about body image and exercise differ by gender of the subject. The aim of our study was to conduct a content analysis to identify the characteristics of fitspiration content posted across social media and whether this differs according to subject gender. Content tagged with #fitspo across Instagram, Facebook, Twitter, and Tumblr was extracted over a composite 30-minute period. All posts were analyzed by 2 independent coders according to a codebook. Of the 415/476 (87.2%) relevant posts extracted, most posts were on Instagram (360/415, 86.8%). Most posts (308/415, 74.2%) related thematically to exercise, and 81/415 (19.6%) related thematically to food. In total, 151 (36.4%) posts depicted only female subjects and 114/415 (27.5%) depicted only male subjects. Female subjects were typically thin but toned; male subjects were often muscular or hypermuscular. Within the images, female subjects were significantly more likely to be aged under 25 years (P<.001) than the male subjects, to have their full body visible (P=.001), and to have their buttocks emphasized (P<.001). Male subjects were more likely to have their face visible in the post (P=.005) than the female subjects. Female subjects were more likely to be sexualized than the male subjects (P=.002). Female #fitspo subjects typically adhered to the thin or athletic ideal, and male subjects typically adhered to the muscular ideal. Future research and interventional efforts should consider the potential objectifying messages in fitspiration, as it relates to both female and male body image. ©Elise Rose Carrotte, Ivanka Prichard, Megan Su Cheng Lim. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 29.03.2017.

Bayesian spatial transformation models with applications in neuroimaging data

PubMed Central

Miranda, Michelle F.; Zhu, Hongtu; Ibrahim, Joseph G.

2013-01-01

Summary The aim of this paper is to develop a class of spatial transformation models (STM) to spatially model the varying association between imaging measures in a three-dimensional (3D) volume (or 2D surface) and a set of covariates. Our STMs include a varying Box-Cox transformation model for dealing with the issue of non-Gaussian distributed imaging data and a Gaussian Markov Random Field model for incorporating spatial smoothness of the imaging data. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. Simulations and real data analysis demonstrate that the STM significantly outperforms the voxel-wise linear model with Gaussian noise in recovering meaningful geometric patterns. Our STM is able to reveal important brain regions with morphological changes in children with attention deficit hyperactivity disorder. PMID:24128143

Radiometric and Geometric Accuracy Analysis of Rasat Pan Imagery

NASA Astrophysics Data System (ADS)

Kocaman, S.; Yalcin, I.; Guler, M.

2016-06-01

RASAT is the second Turkish Earth Observation satellite which was launched in 2011. It operates with pushbroom principle and acquires panchromatic and MS images with 7.5 m and 15 m resolutions, respectively. The swath width of the sensor is 30 km. The main aim of this study is to analyse the radiometric and geometric quality of RASAT images. A systematic validation approach for the RASAT imagery and its products is being applied. RASAT image pair acquired over Kesan city in Edirne province of Turkey are used for the investigations. The raw RASAT data (L0) are processed by Turkish Space Agency (TUBITAK-UZAY) to produce higher level image products. The image products include radiometrically processed (L1), georeferenced (L2) and orthorectified (L3) data, as well as pansharpened images. The image quality assessments include visual inspections, noise, MTF and histogram analyses. The geometric accuracy assessment results are only preliminary and the assessment is performed using the raw images. The geometric accuracy potential is investigated using 3D ground control points extracted from road intersections, which were measured manually in stereo from aerial images with 20 cm resolution and accuracy. The initial results of the study, which were performed using one RASAT panchromatic image pair, are presented in this paper.

Majolica imaging with THz waves: preliminary results

NASA Astrophysics Data System (ADS)

Catapano, Ilaria; Affinito, Antonio; Guerriero, Luigi; Bisceglia, Bruno; Soldovieri, Francesco

2016-05-01

Recent advancements performed in the development of stable and flexible devices working at TeraHertz (THz) frequencies have opened the way at considering this technology as a very interesting noninvasive diagnostic tool in cultural heritage. In this frame, the paper aims at assessing the ability of THz imaging to gather information about preservation state and constructive modalities of majolica artworks. In particular, THz surveys have been carried out on two majolica tiles dated back to the nineteenth century and realized as building cladding at Naples (Italy). The analysis has been performed by means of the Zomega fiber-coupled THz time-domain system. This analysis corroborates the ability of THz to reconstruct irregularities of majolica tile topography, to characterize pigment and glaze losses, and to detect and localize glaze and pigment layer as well as the glaze-clay body interface.

Automatic archaeological feature extraction from satellite VHR images

NASA Astrophysics Data System (ADS)

Jahjah, Munzer; Ulivieri, Carlo

2010-05-01

Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were applied to different archaeological sites in Turkmenistan (Nisa) and in Iraq (Babylon); a further change detection analysis was applied to the Babylon site using two HR images as a pre-post second gulf war. We had different results or outputs, taking into consideration the fact that the operative scale of sensed data determines the final result of the elaboration and the output of the information quality, because each of them was sensitive to specific shapes in each input image, we had mapped linear and nonlinear objects, updating archaeological cartography, automatic change detection analysis for the Babylon site. The discussion of these techniques has the objective to provide the archaeological team with new instruments for the orientation and the planning of a remote sensing application.

Imaging genetics approach to predict progression of Parkinson's diseases.

PubMed

Mansu Kim; Seong-Jin Son; Hyunjin Park

2017-07-01

Imaging genetics is a tool to extract genetic variants associated with both clinical phenotypes and imaging information. The approach can extract additional genetic variants compared to conventional approaches to better investigate various diseased conditions. Here, we applied imaging genetics to study Parkinson's disease (PD). We aimed to extract significant features derived from imaging genetics and neuroimaging. We built a regression model based on extracted significant features combining genetics and neuroimaging to better predict clinical scores of PD progression (i.e. MDS-UPDRS). Our model yielded high correlation (r = 0.697, p <; 0.001) and low root mean squared error (8.36) between predicted and actual MDS-UPDRS scores. Neuroimaging (from 123 I-Ioflupane SPECT) predictors of regression model were computed from independent component analysis approach. Genetic features were computed using image genetics approach based on identified neuroimaging features as intermediate phenotypes. Joint modeling of neuroimaging and genetics could provide complementary information and thus have the potential to provide further insight into the pathophysiology of PD. Our model included newly found neuroimaging features and genetic variants which need further investigation.

Can activity support influence image of a street?

NASA Astrophysics Data System (ADS)

Tamiami Fachrudin, Hilma

2018-03-01

Activity support may affect the formation of the image of a corridor and street. Form, place, and character of activity support in an area will have the function attraction and usefulness of its activities. The aim of this research is to analyze how the influence of activity support on the image of a street, in this case, Dr.Mansyur street which located in front of Universitas Sumatera Utara. Along the street, there are various activities that conducted from morning until evening. The method used is a quantitative method with observation and questionnaire techniques. A population of this study is visitors and students of architecture department from Universitas Sumatera Utara (USU) with sample number is 100 respondents for visitors and 100 respondents for students. Independent variables are activity support factors that consist of the type of activity, form, color, dimension, material, position and lighting. The dependent variable is imageability by [1]. Data were analyzed using logistic regression analysis. The results show that activity support influences image Dr. Mansyur street that has an image as a campus and culinary area and easy to identify.

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography

PubMed Central

Sidky, Emil Y.; Kraemer, David N.; Roth, Erin G.; Ullberg, Christer; Reiser, Ingrid S.; Pan, Xiaochuan

2014-01-01

Abstract. One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data. PMID:25685824

Analysis of iterative region-of-interest image reconstruction for x-ray computed tomography.

PubMed

Sidky, Emil Y; Kraemer, David N; Roth, Erin G; Ullberg, Christer; Reiser, Ingrid S; Pan, Xiaochuan

2014-10-03

One of the challenges for iterative image reconstruction (IIR) is that such algorithms solve an imaging model implicitly, requiring a complete representation of the scanned subject within the viewing domain of the scanner. This requirement can place a prohibitively high computational burden for IIR applied to x-ray computed tomography (CT), especially when high-resolution tomographic volumes are required. In this work, we aim to develop an IIR algorithm for direct region-of-interest (ROI) image reconstruction. The proposed class of IIR algorithms is based on an optimization problem that incorporates a data fidelity term, which compares a derivative of the estimated data with the available projection data. In order to characterize this optimization problem, we apply it to computer-simulated two-dimensional fan-beam CT data, using both ideal noiseless data and realistic data containing a level of noise comparable to that of the breast CT application. The proposed method is demonstrated for both complete field-of-view and ROI imaging. To demonstrate the potential utility of the proposed ROI imaging method, it is applied to actual CT scanner data.

Independent value of image fusion in unenhanced breast MRI using diffusion-weighted and morphological T2-weighted images for lesion characterization in patients with recently detected BI-RADS 4/5 x-ray mammography findings.

PubMed

Bickelhaupt, Sebastian; Tesdorff, Jana; Laun, Frederik Bernd; Kuder, Tristan Anselm; Lederer, Wolfgang; Teiner, Susanne; Maier-Hein, Klaus; Daniel, Heidi; Stieber, Anne; Delorme, Stefan; Schlemmer, Heinz-Peter

2017-02-01

The aim of this study was to evaluate the accuracy and applicability of solitarily reading fused image series of T2-weighted and high-b-value diffusion-weighted sequences for lesion characterization as compared to sequential or combined image analysis of these unenhanced sequences and to contrast- enhanced breast MRI. This IRB-approved study included 50 female participants with suspicious breast lesions detected in screening X-ray mammograms, all of which provided written informed consent. Prior to biopsy, all women underwent MRI including diffusion-weighted imaging (DWIBS, b = 1500s/mm 2 ). Images were analyzed as follows: prospective image fusion of DWIBS and T2-weighted images (FU), side-by-side analysis of DWIBS and T2-weighted series (CO), combination of the first two methods (CO+FU), and full contrast-enhanced diagnostic protocol (FDP). Diagnostic indices, confidence, and image quality of the protocols were compared by two blinded readers. Reading the CO+FU (accuracy 0.92; NPV 96.1 %; PPV 87.6 %) and the CO series (0.90; 96.1 %; 83.7 %) provided a diagnostic performance similar to the FDP (0.95; 96.1 %; 91.3 %; p > 0.05). FU reading alone significantly reduced the diagnostic accuracy (0.82; 93.3 %; 73.4 %; p = 0.023). MR evaluation of suspicious BI-RADS 4 and 5 lesions detected on mammography by using a non-contrast-enhanced T2-weighted and DWIBS sequence protocol is most accurate if MR images were read using the CO+FU protocol. • Unenhanced breast MRI with additional DWIBS/T2w-image fusion allows reliable lesion characterization. • Abbreviated reading of fused DWIBS/T2w-images alone decreases diagnostic confidence and accuracy. • Reading fused DWIBS/T2w-images as the sole diagnostic method should be avoided.

First analysis of solar structures in 1.21 mm full-disc ALMA image of the Sun

NASA Astrophysics Data System (ADS)

Brajša, R.; Sudar, D.; Benz, A. O.; Skokić, I.; Bárta, M.; Pontieu, B. De; Kim, S.; Kobelski, A.; Kuhar, M.; Shimojo, M.; Wedemeyer, S.; White, S.; Yagoubov, P.; Yan, Y.

2018-05-01

Context. Various solar features can be seen in emission or absorption on maps of the Sun in the millimetre and submillimetre wavelength range. The recently installed Atacama Large Millimetre/submillimetre Array (ALMA) is capable of observing the Sun in that wavelength range with an unprecedented spatial, temporal and spectral resolution. To interpret solar observations with ALMA, the first important step is to compare solar ALMA maps with simultaneous images of the Sun recorded in other spectral ranges. Aims: The first aim of the present work is to identify different structures in the solar atmosphere seen in the optical, infrared, and EUV parts of the spectrum (quiet Sun, active regions, prominences on the disc, magnetic inversion lines, coronal holes and coronal bright points) in a full-disc solar ALMA image. The second aim is to measure the intensities (brightness temperatures) of those structures and to compare them with the corresponding quiet Sun level. Methods: A full-disc solar image at 1.21 mm obtained on December 18, 2015, during a CSV-EOC campaign with ALMA is calibrated and compared with full-disc solar images from the same day in Hα line, in He I 1083 nm line core, and with various SDO images (AIA at 170 nm, 30.4 nm, 21.1 nm, 19.3 nm, and 17.1 nm and HMI magnetogram). The brightness temperatures of various structures are determined by averaging over corresponding regions of interest in the calibrated ALMA image. Results: Positions of the quiet Sun, active regions, prominences on the disc, magnetic inversion lines, coronal holes and coronal bright points are identified in the ALMA image. At the wavelength of 1.21 mm, active regions appear as bright areas (but sunspots are dark), while prominences on the disc and coronal holes are not discernible from the quiet Sun background, despite having slightly less intensity than surrounding quiet Sun regions. Magnetic inversion lines appear as large, elongated dark structures and coronal bright points correspond to ALMA bright points. Conclusions: These observational results are in general agreement with sparse earlier measurements at similar wavelengths. The identification of coronal bright points represents the most important new result. By comparing ALMA and other maps, it was found that the ALMA image was oriented properly and that the procedure of overlaying the ALMA image with other images is accurate at the 5 arcsec level. The potential of ALMA for physics of the solar chromosphere is emphasised.

[Professional divers: analysis of critical issues and proposal of a health protocol for work fitness].

PubMed

Pedata, Paola; Corvino, Anna Rita; Napolitano, Raffaele Carmine; Garzillo, Elpidio Maria; Furfaro, Ciro; Lamberti, Monica

2016-01-20

From many years now, thanks to the development of modern diving techniques, there has been a rapid spread of diving activities everywhere. In fact, divers are ever more numerous both among the Armed Forces and civilians who dive for work, like fishing, biological research and archeology. The aim of the study was to propose a health protocol for work fitness of professional divers keeping in mind the peculiar work activity, existing Italian legislation that is almost out of date and the technical and scientific evolution in this occupational field. We performed an analysis of the most frequently occurring diseases among professional divers and of the clinical investigation and imaging techniques used for work fitness assessment of professional divers. From analysis of the health protocol recommended by D.M. 13 January 1979 (Ministerial Decree), that is most used by occupational health physician, several critical issues emerged. Very often the clinical investigation and imaging techniques still used are almost obsolete, ignoring the execution of simple and inexpensive investigations that are more useful for work fitness assessment. Considering the out-dated legislation concerning diving disciplines, it is necessary to draw up a common health protocol that takes into account clinical and scientific knowledge and skills acquired in this area. This protocol's aim is to propose a useful tool for occupational health physicians who work in this sector.

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.

Crowdsourcing as a novel technique for retinal fundus photography classification: analysis of images in the EPIC Norfolk cohort on behalf of the UK Biobank Eye and Vision Consortium.

PubMed

Mitry, Danny; Peto, Tunde; Hayat, Shabina; Morgan, James E; Khaw, Kay-Tee; Foster, Paul J

2013-01-01

Crowdsourcing is the process of outsourcing numerous tasks to many untrained individuals. Our aim was to assess the performance and repeatability of crowdsourcing for the classification of retinal fundus photography. One hundred retinal fundus photograph images with pre-determined disease criteria were selected by experts from a large cohort study. After reading brief instructions and an example classification, we requested that knowledge workers (KWs) from a crowdsourcing platform classified each image as normal or abnormal with grades of severity. Each image was classified 20 times by different KWs. Four study designs were examined to assess the effect of varying incentive and KW experience in classification accuracy. All study designs were conducted twice to examine repeatability. Performance was assessed by comparing the sensitivity, specificity and area under the receiver operating characteristic curve (AUC). Without restriction on eligible participants, two thousand classifications of 100 images were received in under 24 hours at minimal cost. In trial 1 all study designs had an AUC (95%CI) of 0.701(0.680-0.721) or greater for classification of normal/abnormal. In trial 1, the highest AUC (95%CI) for normal/abnormal classification was 0.757 (0.738-0.776) for KWs with moderate experience. Comparable results were observed in trial 2. In trial 1, between 64-86% of any abnormal image was correctly classified by over half of all KWs. In trial 2, this ranged between 74-97%. Sensitivity was ≥ 96% for normal versus severely abnormal detections across all trials. Sensitivity for normal versus mildly abnormal varied between 61-79% across trials. With minimal training, crowdsourcing represents an accurate, rapid and cost-effective method of retinal image analysis which demonstrates good repeatability. Larger studies with more comprehensive participant training are needed to explore the utility of this compelling technique in large scale medical image analysis.

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.

A game-based platform for crowd-sourcing biomedical image diagnosis and standardized remote training and education of diagnosticians

NASA Astrophysics Data System (ADS)

Feng, Steve; Woo, Minjae; Chandramouli, Krithika; Ozcan, Aydogan

2015-03-01

Over the past decade, crowd-sourcing complex image analysis tasks to a human crowd has emerged as an alternative to energy-inefficient and difficult-to-implement computational approaches. Following this trend, we have developed a mathematical framework for statistically combining human crowd-sourcing of biomedical image analysis and diagnosis through games. Using a web-based smart game (BioGames), we demonstrated this platform's effectiveness for telediagnosis of malaria from microscopic images of individual red blood cells (RBCs). After public release in early 2012 (http://biogames.ee.ucla.edu), more than 3000 gamers (experts and non-experts) used this BioGames platform to diagnose over 2800 distinct RBC images, marking them as positive (infected) or negative (non-infected). Furthermore, we asked expert diagnosticians to tag the same set of cells with labels of positive, negative, or questionable (insufficient information for a reliable diagnosis) and statistically combined their decisions to generate a gold standard malaria image library. Our framework utilized minimally trained gamers' diagnoses to generate a set of statistical labels with an accuracy that is within 98% of our gold standard image library, demonstrating the "wisdom of the crowd". Using the same image library, we have recently launched a web-based malaria training and educational game allowing diagnosticians to compare their performance with their peers. After diagnosing a set of ~500 cells per game, diagnosticians can compare their quantified scores against a leaderboard and view their misdiagnosed cells. Using this platform, we aim to expand our gold standard library with new RBC images and provide a quantified digital tool for measuring and improving diagnostician training globally.

Development and implementation of an EPID-based method for localizing isocenter.

PubMed

Hyer, Daniel E; Mart, Christopher J; Nixon, Earl

2012-11-08

The aim of this study was to develop a phantom and analysis software that could be used to quickly and accurately determine the location of radiation isocenter to an accuracy of less than 1 mm using the EPID (Electronic Portal Imaging Device). The proposed solution uses a collimator setting of 10 × 10 cm2 to acquire EPID images of a new phantom constructed from LEGO blocks. Images from a number of gantry and collimator angles are analyzed by automated analysis software to determine the position of the jaws and center of the phantom in each image. The distance between a chosen jaw and the phantom center is then compared to the same distance measured after a 180° collimator rotation to determine if the phantom is centered in the dimension being investigated. Repeated tests show that the system is reproducibly independent of the imaging session, and calculated offsets of the phantom from radiation isocenter are a function of phantom setup only. Accuracy of the algorithm's calculated offsets were verified by imaging the LEGO phantom before and after applying the calculated offset. These measurements show that the offsets are predicted with an accuracy of approximately 0.3 mm, which is on the order of the detector's pitch. Comparison with a star-shot analysis yielded agreement of isocenter location within 0.5 mm. Additionally, the phantom and software are completely independent of linac vendor, and this study presents results from two linac manufacturers. A Varian Optical Guidance Platform (OGP) calibration array was also integrated into the phantom to allow calibration of the OGP while the phantom is positioned at radiation isocenter to reduce setup uncertainty in the calibration. This solution offers a quick, objective method to perform isocenter localization as well as laser alignment and OGP calibration on a monthly basis.

Evaluation of random errors in Williams’ series coefficients obtained with digital image correlation

NASA Astrophysics Data System (ADS)

Lychak, Oleh V.; Holyns'kiy, Ivan S.

2016-03-01

The use of the Williams’ series parameters for fracture analysis requires valid information about their error values. The aim of this investigation is the development of the method for estimation of the standard deviation of random errors of the Williams’ series parameters, obtained from the measured components of the stress field. Also, the criteria for choosing the optimal number of terms in the truncated Williams’ series for derivation of their parameters with minimal errors is proposed. The method was used for the evaluation of the Williams’ parameters, obtained from the data, and measured by the digital image correlation technique for testing a three-point bending specimen.

Multimodal optical coherence tomography for in vivo imaging of brain tissue structure and microvascular network at glioblastoma

NASA Astrophysics Data System (ADS)

Yashin, Konstantin S.; Kiseleva, Elena B.; Gubarkova, Ekaterina V.; Matveev, Lev A.; Karabut, Maria M.; Elagin, Vadim V.; Sirotkina, Marina A.; Medyanik, Igor A.; Kravets, L. Y.; Gladkova, Natalia D.

2017-02-01

In the case of infiltrative brain tumors the surgeon faces difficulties in determining their boundaries to achieve total resection. The aim of the investigation was to evaluate the performance of multimodal OCT (MM OCT) for differential diagnostics of normal brain tissue and glioma using an experimental model of glioblastoma. The spectral domain OCT device that was used for the study provides simultaneously two modes: cross-polarization and microangiographic OCT. The comparative analysis of the both OCT modalities images from tumorous and normal brain tissue areas concurrently with histologic correlation shows certain difference between when accordingly to morphological and microvascular tissue features.

Stellar Clustering in the Dark Filament IRDC 321.706+0.066

NASA Astrophysics Data System (ADS)

Soto King, Piera

2017-06-01

We investigate the star formation process in the infrared dark cloud IRDC 321.706+0.066, where are located three infrared clusters recently discovered by Barbá et al. (2015) using images of the VISTA Variables in the Vía Láctea public survey: La Serena 210, 211 and 212. The aim is to characterize the stellar content of the three clusters and to investigate the star formation sequence in a filamentary dark cloud. We present a new photometric analysis of VVV images, and we use data from others surveys. We confirmed the presence of the three VVV clusters. And also, we propose a new cluster

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.

Precision disablement aiming system

DOEpatents

Monda, Mark J.; Hobart, Clinton G.; Gladwell, Thomas Scott

2016-02-16

A disrupter to a target may be precisely aimed by positioning a radiation source to direct radiation towards the target, and a detector is positioned to detect radiation that passes through the target. An aiming device is positioned between the radiation source and the target, wherein a mechanical feature of the aiming device is superimposed on the target in a captured radiographic image. The location of the aiming device in the radiographic image is used to aim a disrupter towards the target.

On-Line GIS Analysis and Image Processing for Geoportal Kielce/poland Development

NASA Astrophysics Data System (ADS)

Hejmanowska, B.; Głowienka, E.; Florek-Paszkowski, R.

2016-06-01

GIS databases are widely available on the Internet, but mainly for visualization with limited functionality; very simple queries are possible i.e. attribute query, coordinate readout, line and area measurements or pathfinder. A little more complex analysis (i.e. buffering or intersection) are rare offered. Paper aims at the concept of Geoportal functionality development in the field of GIS analysis. Multi-Criteria Evaluation (MCE) is planned to be implemented in web application. OGC Service is used for data acquisition from the server and results visualization. Advanced GIS analysis is planned in PostGIS and Python programming. In the paper an example of MCE analysis basing on Geoportal Kielce is presented. Other field where Geoportal can be developed is implementation of processing new available satellite images free of charge (Sentinel-2, Landsat 8, ASTER, WV-2). Now we are witnessing a revolution in access to the satellite imagery without charge. This should result in an increase of interest in the use of these data in various fields by a larger number of users, not necessarily specialists in remote sensing. Therefore, it seems reasonable to expand the functionality of Internet's tools for data processing by non-specialists, by automating data collection and prepared predefined analysis.

Evaluation of the Effectiveness of Simulation for M4 Marksmanship Training

DTIC Science & Technology

2014-02-01

DEMOGRAPHIC QUESTIONNAIRE ................................................. 34 APPENDIX C: ANALYSIS OF MARKSMANSHIP PERFORMANCE DATA TO IDENTIFY POTENTIAL...machine guns and anti- armour weapons. In these simulators, firers aim a modified weapon at a target image on a screen. When the firer pulls the trigger...investigate predictors of live-fire LF6 qualification. Specifically, we examined the utility of LF6 simulator scores and trainee demographic data as

Validation study of an interpolation method for calculating whole lung volumes and masses from reduced numbers of CT-images in ponies.

PubMed

Reich, H; Moens, Y; Braun, C; Kneissl, S; Noreikat, K; Reske, A

2014-12-01

Quantitative computer tomographic analysis (qCTA) is an accurate but time intensive method used to quantify volume, mass and aeration of the lungs. The aim of this study was to validate a time efficient interpolation technique for application of qCTA in ponies. Forty-one thoracic computer tomographic (CT) scans obtained from eight anaesthetised ponies positioned in dorsal recumbency were included. Total lung volume and mass and their distribution into four compartments (non-aerated, poorly aerated, normally aerated and hyperaerated; defined based on the attenuation in Hounsfield Units) were determined for the entire lung from all 5 mm thick CT-images, 59 (55-66) per animal. An interpolation technique validated for use in humans was then applied to calculate qCTA results for lung volumes and masses from only 10, 12, and 14 selected CT-images per scan. The time required for both procedures was recorded. Results were compared statistically using the Bland-Altman approach. The bias ± 2 SD for total lung volume calculated from interpolation of 10, 12, and 14 CT-images was -1.2 ± 5.8%, 0.1 ± 3.5%, and 0.0 ± 2.5%, respectively. The corresponding results for total lung mass were -1.1 ± 5.9%, 0.0 ± 3.5%, and 0.0 ± 3.0%. The average time for analysis of one thoracic CT-scan using the interpolation method was 1.5-2 h compared to 8 h for analysis of all images of one complete thoracic CT-scan. The calculation of pulmonary qCTA data by interpolation from 12 CT-images was applicable for equine lung CT-scans and reduced the time required for analysis by 75%. Copyright © 2014 Elsevier Ltd. All rights reserved.

Image-Based 3d Reconstruction and Analysis for Orthodontia

NASA Astrophysics Data System (ADS)

Knyaz, V. A.

2012-08-01

Among the main tasks of orthodontia are analysis of teeth arches and treatment planning for providing correct position for every tooth. The treatment plan is based on measurement of teeth parameters and designing perfect teeth arch curve which teeth are to create after treatment. The most common technique for teeth moving uses standard brackets which put on teeth and a wire of given shape which is clamped by these brackets for producing necessary forces to every tooth for moving it in given direction. The disadvantages of standard bracket technique are low accuracy of tooth dimensions measurements and problems with applying standard approach for wide variety of complex orthodontic cases. The image-based technique for orthodontic planning, treatment and documenting aimed at overcoming these disadvantages is proposed. The proposed approach provides performing accurate measurements of teeth parameters needed for adequate planning, designing correct teeth position and monitoring treatment process. The developed technique applies photogrammetric means for teeth arch 3D model generation, brackets position determination and teeth shifting analysis.

Reliability and validity of soft copy images based on flat-panel detector in pneumoconiosis classification: comparison with the analog radiographs.

PubMed

Lee, Won-Jeong; Choi, Byung-Soon

2013-06-01

The aim of this study was to evaluate the reliability and validity of soft copy images based on flat-panel detector of digital radiography (DR-FPD soft copy images) compared to analog radiographs (ARs) in pneumoconiosis classification and diagnosis. DR-FPD soft copy images and ARs from 349 subjects were independently read by four-experienced readers according to the International Labor Organization 2000 guidelines. DR-FPD soft copy images were used to obtain consensus reading (CR) by all readers as the gold standard. Reliability and validity were evaluated by a κ and receiver operating characteristic analysis, respectively. In small opacity, overall interreader agreement of DR-FPD soft copy images was significantly higher than that of ARs, but it was not significantly different in large opacity and costophrenic angle obliteration. In small opacity, agreement of DR-FPD soft copy images with CR was significantly higher than that of ARs with CR. It was also higher than that of ARs with CR in pleural plaque and thickening. Receiver operating characteristic areas were not different significantly between DR-FPD soft copy images and ARs. DR-FPD soft copy images showed accurate and reliable results in pneumoconiosis classification and diagnosis compared to ARs. Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.

A human visual based binarization technique for histological images

NASA Astrophysics Data System (ADS)

Shreyas, Kamath K. M.; Rajendran, Rahul; Panetta, Karen; Agaian, Sos

2017-05-01

In the field of vision-based systems for object detection and classification, thresholding is a key pre-processing step. Thresholding is a well-known technique for image segmentation. Segmentation of medical images, such as Computed Axial Tomography (CAT), Magnetic Resonance Imaging (MRI), X-Ray, Phase Contrast Microscopy, and Histological images, present problems like high variability in terms of the human anatomy and variation in modalities. Recent advances made in computer-aided diagnosis of histological images help facilitate detection and classification of diseases. Since most pathology diagnosis depends on the expertise and ability of the pathologist, there is clearly a need for an automated assessment system. Histological images are stained to a specific color to differentiate each component in the tissue. Segmentation and analysis of such images is problematic, as they present high variability in terms of color and cell clusters. This paper presents an adaptive thresholding technique that aims at segmenting cell structures from Haematoxylin and Eosin stained images. The thresholded result can further be used by pathologists to perform effective diagnosis. The effectiveness of the proposed method is analyzed by visually comparing the results to the state of art thresholding methods such as Otsu, Niblack, Sauvola, Bernsen, and Wolf. Computer simulations demonstrate the efficiency of the proposed method in segmenting critical information.

Imaging mass spectrometry in drug development and toxicology.

PubMed

Karlsson, Oskar; Hanrieder, Jörg

2017-06-01

During the last decades, imaging mass spectrometry has gained significant relevance in biomedical research. Recent advances in imaging mass spectrometry have paved the way for in situ studies on drug development, metabolism and toxicology. In contrast to whole-body autoradiography that images the localization of radiolabeled compounds, imaging mass spectrometry provides the possibility to simultaneously determine the discrete tissue distribution of the parent compound and its metabolites. In addition, imaging mass spectrometry features high molecular specificity and allows comprehensive, multiplexed detection and localization of hundreds of proteins, peptides and lipids directly in tissues. Toxicologists traditionally screen for adverse findings by histopathological examination. However, studies of the molecular and cellular processes underpinning toxicological and pathologic findings induced by candidate drugs or toxins are important to reach a mechanistic understanding and an effective risk assessment strategy. One of IMS strengths is the ability to directly overlay the molecular information from the mass spectrometric analysis with the tissue section and allow correlative comparisons of molecular and histologic information. Imaging mass spectrometry could therefore be a powerful tool for omics profiling of pharmacological/toxicological effects of drug candidates and toxicants in discrete tissue regions. The aim of the present review is to provide an overview of imaging mass spectrometry, with particular focus on MALDI imaging mass spectrometry, and its use in drug development and toxicology in general.

Automatic registration of multi-modal microscopy images for integrative analysis of prostate tissue sections.

PubMed

Lippolis, Giuseppe; Edsjö, Anders; Helczynski, Leszek; Bjartell, Anders; Overgaard, Niels Chr

2013-09-05

Prostate cancer is one of the leading causes of cancer related deaths. For diagnosis, predicting the outcome of the disease, and for assessing potential new biomarkers, pathologists and researchers routinely analyze histological samples. Morphological and molecular information may be integrated by aligning microscopic histological images in a multiplex fashion. This process is usually time-consuming and results in intra- and inter-user variability. The aim of this study is to investigate the feasibility of using modern image analysis methods for automated alignment of microscopic images from differently stained adjacent paraffin sections from prostatic tissue specimens. Tissue samples, obtained from biopsy or radical prostatectomy, were sectioned and stained with either hematoxylin & eosin (H&E), immunohistochemistry for p63 and AMACR or Time Resolved Fluorescence (TRF) for androgen receptor (AR). Image pairs were aligned allowing for translation, rotation and scaling. The registration was performed automatically by first detecting landmarks in both images, using the scale invariant image transform (SIFT), followed by the well-known RANSAC protocol for finding point correspondences and finally aligned by Procrustes fit. The Registration results were evaluated using both visual and quantitative criteria as defined in the text. Three experiments were carried out. First, images of consecutive tissue sections stained with H&E and p63/AMACR were successfully aligned in 85 of 88 cases (96.6%). The failures occurred in 3 out of 13 cores with highly aggressive cancer (Gleason score ≥ 8). Second, TRF and H&E image pairs were aligned correctly in 103 out of 106 cases (97%).The third experiment considered the alignment of image pairs with the same staining (H&E) coming from a stack of 4 sections. The success rate for alignment dropped from 93.8% in adjacent sections to 22% for sections furthest away. The proposed method is both reliable and fast and therefore well suited for automatic segmentation and analysis of specific areas of interest, combining morphological information with protein expression data from three consecutive tissue sections. Finally, the performance of the algorithm seems to be largely unaffected by the Gleason grade of the prostate tissue samples examined, at least up to Gleason score 7.

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.

Evaluation of the Effect of Light and Scanning Time Delay on The Image Quality of Intra Oral Photostimulable Phosphor Plates

PubMed Central

Eskandarloo, Amir; Yousefi, Arman; Soheili, Setareh; Ghazikhanloo, Karim; Amini, Payam; Mohammadpoor, Haniyeh

2017-01-01

Background: Nowadays, digital radiography is widely used in dental practice. One of the most common types is Photo Stimulated Phosphor Plate (PSP). Objective: The aims of this experimental study were to evaluate the impacts of different combinations of storage conditions and varying delays in reading of digital images captured using PSPs. Methods: Standardized images of a step wedges were obtained using PSPs from the Digora digital systems. Plates were exposed and immediately scanned to produce the baseline gold standard. The plates were re-exposed and stored in four different storage conditions: white light, yellow light, natural light environment and dark room, then scanned after 10 and 30 minutes and 4 and 8 hours. Objective analysis was conducted by density measurements and the data were analyzed statistically using GEE test. Subjective analysis was performed by two oral and maxillofacial radiologists and the results were analyzed using McNemar’s test. Results: The results from GEE analysis show that in the natural light environment, the densities in 10 minutes did not differ from the baseline. The mean densities decreased significantly during the time in all environments. The mean densities in step 2 for the dark room environment decreased with a slighter slope in comparison to yellow environment significantly. Conclusion: PSP images showed significant decrease in the density in plates scanned for 10 minutes or longer after exposure which may not be detected clinically. The yellow light environment had a different impact on the quality of PSP images. The spatial resolution did not change significantly with time. PMID:29430262

Evaluation of the Effect of Light and Scanning Time Delay on The Image Quality of Intra Oral Photostimulable Phosphor Plates.

PubMed

Eskandarloo, Amir; Yousefi, Arman; Soheili, Setareh; Ghazikhanloo, Karim; Amini, Payam; Mohammadpoor, Haniyeh

2017-01-01

Nowadays, digital radiography is widely used in dental practice. One of the most common types is Photo Stimulated Phosphor Plate (PSP). The aims of this experimental study were to evaluate the impacts of different combinations of storage conditions and varying delays in reading of digital images captured using PSPs. Standardized images of a step wedges were obtained using PSPs from the Digora digital systems. Plates were exposed and immediately scanned to produce the baseline gold standard. The plates were re-exposed and stored in four different storage conditions: white light, yellow light, natural light environment and dark room, then scanned after 10 and 30 minutes and 4 and 8 hours. Objective analysis was conducted by density measurements and the data were analyzed statistically using GEE test. Subjective analysis was performed by two oral and maxillofacial radiologists and the results were analyzed using McNemar's test. The results from GEE analysis show that in the natural light environment, the densities in 10 minutes did not differ from the baseline. The mean densities decreased significantly during the time in all environments. The mean densities in step 2 for the dark room environment decreased with a slighter slope in comparison to yellow environment significantly. PSP images showed significant decrease in the density in plates scanned for 10 minutes or longer after exposure which may not be detected clinically. The yellow light environment had a different impact on the quality of PSP images. The spatial resolution did not change significantly with time.

RecceMan: an interactive recognition assistance for image-based reconnaissance: synergistic effects of human perception and computational methods for object recognition, identification, and infrastructure analysis

NASA Astrophysics Data System (ADS)

El Bekri, Nadia; Angele, Susanne; Ruckhäberle, Martin; Peinsipp-Byma, Elisabeth; Haelke, Bruno

2015-10-01

This paper introduces an interactive recognition assistance system for imaging reconnaissance. This system supports aerial image analysts on missions during two main tasks: Object recognition and infrastructure analysis. Object recognition concentrates on the classification of one single object. Infrastructure analysis deals with the description of the components of an infrastructure and the recognition of the infrastructure type (e.g. military airfield). Based on satellite or aerial images, aerial image analysts are able to extract single object features and thereby recognize different object types. It is one of the most challenging tasks in the imaging reconnaissance. Currently, there are no high potential ATR (automatic target recognition) applications available, as consequence the human observer cannot be replaced entirely. State-of-the-art ATR applications cannot assume in equal measure human perception and interpretation. Why is this still such a critical issue? First, cluttered and noisy images make it difficult to automatically extract, classify and identify object types. Second, due to the changed warfare and the rise of asymmetric threats it is nearly impossible to create an underlying data set containing all features, objects or infrastructure types. Many other reasons like environmental parameters or aspect angles compound the application of ATR supplementary. Due to the lack of suitable ATR procedures, the human factor is still important and so far irreplaceable. In order to use the potential benefits of the human perception and computational methods in a synergistic way, both are unified in an interactive assistance system. RecceMan® (Reconnaissance Manual) offers two different modes for aerial image analysts on missions: the object recognition mode and the infrastructure analysis mode. The aim of the object recognition mode is to recognize a certain object type based on the object features that originated from the image signatures. The infrastructure analysis mode pursues the goal to analyze the function of the infrastructure. The image analyst extracts visually certain target object signatures, assigns them to corresponding object features and is finally able to recognize the object type. The system offers him the possibility to assign the image signatures to features given by sample images. The underlying data set contains a wide range of objects features and object types for different domains like ships or land vehicles. Each domain has its own feature tree developed by aerial image analyst experts. By selecting the corresponding features, the possible solution set of objects is automatically reduced and matches only the objects that contain the selected features. Moreover, we give an outlook of current research in the field of ground target analysis in which we deal with partly automated methods to extract image signatures and assign them to the corresponding features. This research includes methods for automatically determining the orientation of an object and geometric features like width and length of the object. This step enables to reduce automatically the possible object types offered to the image analyst by the interactive recognition assistance system.

Content-based quality evaluation of color images: overview and proposals

NASA Astrophysics Data System (ADS)

Tremeau, Alain; Richard, Noel; Colantoni, Philippe; Fernandez-Maloigne, Christine

2003-12-01

The automatic prediction of perceived quality from image data in general, and the assessment of particular image characteristics or attributes that may need improvement in particular, becomes an increasingly important part of intelligent imaging systems. The purpose of this paper is to propose to the color imaging community in general to develop a software package available on internet to help the user to select among all these approaches which is better appropriated to a given application. The ultimate goal of this project is to propose, next to implement, an open and unified color imaging system to set up a favourable context for the evaluation and analysis of color imaging processes. Many different methods for measuring the performance of a process have been proposed by different researchers. In this paper, we will discuss the advantages and shortcomings of most of main analysis criteria and performance measures currently used. The aim is not to establish a harsh competition between algorithms or processes, but rather to test and compare the efficiency of methodologies firstly to highlight strengths and weaknesses of a given algorithm or methodology on a given image type and secondly to have these results publicly available. This paper is focused on two important unsolved problems. Why it is so difficult to select a color space which gives better results than another one? Why it is so difficult to select an image quality metric which gives better results than another one, with respect to the judgment of the Human Visual System? Several methods used either in color imaging or in image quality will be thus discussed. Proposals for content-based image measures and means of developing a standard test suite for will be then presented. The above reference advocates for an evaluation protocol based on an automated procedure. This is the ultimate goal of our proposal.

ALOHA—Astronomical Light Optical Hybrid Analysis - From experimental demonstrations to a MIR instrument proposal

NASA Astrophysics Data System (ADS)

Lehmann, L.; Darré, P.; Szemendera, L.; Gomes, J. T.; Baudoin, R.; Ceus, D.; Brustlein, S.; Delage, L.; Grossard, L.; Reynaud, F.

2018-04-01

This paper gives an overview of the Astronomical Light Optical Hybrid Analysis (ALOHA) project dedicated to investigate a new method for high resolution imaging in mid infrared astronomy. This proposal aims to use a non-linear frequency conversion process to shift the thermal infrared radiation to a shorter wavelength domain compatible with proven technology such as guided optics and detectors. After a description of the principle, we summarise the evolution of our study from the high flux seminal experiments to the latest results in the photon counting regime.

Lp(a) (Lipoprotein(a)) Levels Predict Progression of Carotid Atherosclerosis in Subjects With Atherosclerotic Cardiovascular Disease on Intensive Lipid Therapy: An Analysis of the AIM-HIGH (Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides: Impact on Global Health Outcomes) Carotid Magnetic Resonance Imaging Substudy-Brief Report.

PubMed

Hippe, Daniel S; Phan, Binh An P; Sun, Jie; Isquith, Daniel A; O'Brien, Kevin D; Crouse, John R; Anderson, Todd; Huston, John; Marcovina, Santica M; Hatsukami, Thomas S; Yuan, Chun; Zhao, Xue-Qiao

2018-03-01

To assess whether Lp(a) (lipoprotein(a)) levels and other lipid levels were predictive of progression of atherosclerosis burden as assessed by carotid magnetic resonance imaging in subjects who have been treated with LDL-C (low-density lipoprotein cholesterol)-lowering therapy and participated in the AIM-HIGH trial (Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides: Impact on Global Health Outcomes). AIM-HIGH was a randomized, double-blind study of subjects with established vascular disease, elevated triglycerides, and low HDL-C (high-density lipoprotein cholesterol). One hundred fifty-two AIM-HIGH subjects underwent both baseline and 2-year follow-up carotid artery magnetic resonance imaging. Plaque burden was measured by the percent wall volume (%WV) of the carotid artery. Associations between annualized change in %WV with baseline and on-study (1 year) lipid variables were evaluated using multivariate linear regression and the Bonferroni correction to account for multiple comparisons. Average %WV at baseline was 41.6±6.8% and annualized change in %WV over 2 years ranged from -3.2% to 3.7% per year (mean: 0.2±1.1% per year; P =0.032). Increases in %WV were significantly associated with higher baseline Lp(a) (β=0.34 per 1-SD increase of Lp(a); 95% confidence interval, 0.15-0.52; P <0.001) after adjusting for clinical risk factors and other lipid levels. On-study Lp(a) had a similar positive association with %WV progression (β=0.33; 95% confidence interval, 0.15-0.52; P <0.001). Despite intensive lipid therapy, aimed at aggressively lowering LDL-C to <70 mg/dL, carotid atherosclerosis continued to progress as assessed by carotid magnetic resonance imaging and that elevated Lp(a) levels were independent predictors of increases in atherosclerosis burden. © 2018 American Heart Association, Inc.

Automated detection of diabetic retinopathy on digital fundus images.

PubMed

Sinthanayothin, C; Boyce, J F; Williamson, T H; Cook, H L; Mensah, E; Lal, S; Usher, D

2002-02-01

The aim was to develop an automated screening system to analyse digital colour retinal images for important features of non-proliferative diabetic retinopathy (NPDR). High performance pre-processing of the colour images was performed. Previously described automated image analysis systems were used to detect major landmarks of the retinal image (optic disc, blood vessels and fovea). Recursive region growing segmentation algorithms combined with the use of a new technique, termed a 'Moat Operator', were used to automatically detect features of NPDR. These features included haemorrhages and microaneurysms (HMA), which were treated as one group, and hard exudates as another group. Sensitivity and specificity data were calculated by comparison with an experienced fundoscopist. The algorithm for exudate recognition was applied to 30 retinal images of which 21 contained exudates and nine were without pathology. The sensitivity and specificity for exudate detection were 88.5% and 99.7%, respectively, when compared with the ophthalmologist. HMA were present in 14 retinal images. The algorithm achieved a sensitivity of 77.5% and specificity of 88.7% for detection of HMA. Fully automated computer algorithms were able to detect hard exudates and HMA. This paper presents encouraging results in automatic identification of important features of NPDR.

Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies.

PubMed

Koch, Lisa M; Rajchl, Martin; Bai, Wenjia; Baumgartner, Christian F; Tong, Tong; Passerat-Palmbach, Jonathan; Aljabar, Paul; Rueckert, Daniel

2017-08-22

Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets. However, the availability of fully annotated atlas images for training is limited due to the time required for the labelling task. Segmentation methods requiring only a proportion of each atlas image to be labelled could therefore reduce the workload on expert raters tasked with annotating atlas images. To address this issue, we first re-examine the labelling problem common in many existing approaches and formulate its solution in terms of a Markov Random Field energy minimisation problem on a graph connecting atlases and the target image. This provides a unifying framework for multi-atlas segmentation. We then show how modifications in the graph configuration of the proposed framework enable the use of partially annotated atlas images and investigate different partial annotation strategies. The proposed method was evaluated on two Magnetic Resonance Imaging (MRI) datasets for hippocampal and cardiac segmentation. Experiments were performed aimed at (1) recreating existing segmentation techniques with the proposed framework and (2) demonstrating the potential of employing sparsely annotated atlas data for multi-atlas segmentation.

Nuclear imaging of the fuel assembly in ignition experiments

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

Grim, G. P.; Guler, N.; Merrill, F. E.

First results from the analysis of neutron image data collected on implosions of cryogenically layered deuterium-tritium capsules during the 2011-2012 National Ignition Campaign are reported. The data span a variety of experimental designs aimed at increasing the stagnation pressure of the central hotspot and areal density of the surrounding fuel assembly. Images of neutrons produced by deuterium–tritium fusion reactions in the hotspot are presented, as well as images of neutrons that scatter in the surrounding dense fuel assembly. The image data are compared with 1D and 2D model predictions, and consistency checked using other diagnostic data. The results indicate thatmore » the size of the fusing hotspot is consistent with the model predictions, as well as other imaging data, while the overall size of the fuel assembly, inferred from the scattered neutron images, is systematically smaller than models’ prediction. Preliminary studies indicate these differences are consistent with a significant fraction (20%–25%) of the initial deuterium-tritium fuel mass outside the compact fuel assembly, due either to low mode mass asymmetry or high mode 3D mix effects at the ablator-ice interface.« less

Bioimage informatics approach to automated meibomian gland analysis in infrared images of meibography

PubMed Central

Celik, Turgay; Lee, Hwee Kuan; Petznick, Andrea; Tong, Louis

2013-01-01

Background Infrared (IR) meibography is an imaging technique to capture the Meibomian glands in the eyelids. These ocular surface structures are responsible for producing the lipid layer of the tear film which helps to reduce tear evaporation. In a normal healthy eye, the glands have similar morphological features in terms of spatial width, in-plane elongation, length. On the other hand, eyes with Meibomian gland dysfunction show visible structural irregularities that help in the diagnosis and prognosis of the disease. However, currently there is no universally accepted algorithm for detection of these image features which will be clinically useful. We aim to develop a method of automated gland segmentation which allows images to be classified. Methods A set of 131 meibography images were acquired from patients from the Singapore National Eye Center. We used a method of automated gland segmentation using Gabor wavelets. Features of the imaged glands including orientation, width, length and curvature were extracted and the IR images enhanced. The images were classified as ‘healthy’, ‘intermediate’ or ‘unhealthy’, through the use of a support vector machine classifier (SVM). Half the images were used for training the SVM and the other half for validation. Independently of this procedure, the meibographs were classified by an expert clinician into the same 3 grades. Results The algorithm correctly detected 94% and 98% of mid-line pixels of gland and inter-gland regions, respectively, on healthy images. On intermediate images, correct detection rates of 92% and 97% of mid-line pixels of gland and inter-gland regions were achieved respectively. The true positive rate of detecting healthy images was 86%, and for intermediate images, 74%. The corresponding false positive rates were 15% and 31% respectively. Using the SVM, the proposed method has 88% accuracy in classifying images into the 3 classes. The classification of images into healthy and unhealthy classes achieved a 100% accuracy, but 7/38 intermediate images were incorrectly classified. Conclusions This technique of image analysis in meibography can help clinicians to interpret the degree of gland destruction in patients with dry eye and meibomian gland dysfunction.

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

PubMed

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

2015-10-01

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

Magnetic resonance imaging reveals functional anatomy and biomechanics of a living dragon tree

PubMed Central

Hesse, Linnea; Masselter, Tom; Leupold, Jochen; Spengler, Nils; Speck, Thomas; Korvink, Jan Gerrit

2016-01-01

Magnetic resonance imaging (MRI) was used to gain in vivo insight into load-induced displacements of inner plant tissues making a non-invasive and non-destructive stress and strain analysis possible. The central aim of this study was the identification of a possible load-adapted orientation of the vascular bundles and their fibre caps as the mechanically relevant tissue in branch-stem-attachments of Dracaena marginata. The complex three-dimensional deformations that occur during mechanical loading can be analysed on the basis of quasi-three-dimensional data representations of the outer surface, the inner tissue arrangement (meristem and vascular system), and the course of single vascular bundles within the branch-stem-attachment region. In addition, deformations of vascular bundles could be quantified manually and by using digital image correlation software. This combination of qualitative and quantitative stress and strain analysis leads to an improved understanding of the functional morphology and biomechanics of D. marginata, a plant that is used as a model organism for optimizing branched technical fibre-reinforced lightweight trusses in order to increase their load bearing capacity. PMID:27604526

Biologically-inspired data decorrelation for hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Picon, Artzai; Ghita, Ovidiu; Rodriguez-Vaamonde, Sergio; Iriondo, Pedro Ma; Whelan, Paul F.

2011-12-01

Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

A Review of Mid-Infrared and Near-Infrared Imaging: Principles, Concepts and Applications in Plant Tissue Analysis.

PubMed

Türker-Kaya, Sevgi; Huck, Christian W

2017-01-20

Plant cells, tissues and organs are composed of various biomolecules arranged as structurally diverse units, which represent heterogeneity at microscopic levels. Molecular knowledge about those constituents with their localization in such complexity is very crucial for both basic and applied plant sciences. In this context, infrared imaging techniques have advantages over conventional methods to investigate heterogeneous plant structures in providing quantitative and qualitative analyses with spatial distribution of the components. Thus, particularly, with the use of proper analytical approaches and sampling methods, these technologies offer significant information for the studies on plant classification, physiology, ecology, genetics, pathology and other related disciplines. This review aims to present a general perspective about near-infrared and mid-infrared imaging/microspectroscopy in plant research. It is addressed to compare potentialities of these methodologies with their advantages and limitations. With regard to the organization of the document, the first section will introduce the respective underlying principles followed by instrumentation, sampling techniques, sample preparations, measurement, and an overview of spectral pre-processing and multivariate analysis. The last section will review selected applications in the literature.

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.

Neuroimaging of the Periaqueductal Gray: State of the Field

PubMed Central

Linnman, Clas; Moulton, Eric A.; Barmettler, Gabi; Becerra, Lino; Borsook, David

2011-01-01

This review and meta-analysis aims at summarizing and integrating the human neuroimaging studies that report periaqueductal gray (PAG) involvement; 250 original manuscripts on human neuroimaging of the PAG were identified. A narrative review and meta-analysis using activation likelihood estimates is included. Behaviors covered include pain and pain modulation, anxiety, bladder and bowel function and autonomic regulation. Methods include structural and functional magnetic resonance imaging, functional connectivity measures, diffusion weighted imaging and positron emission tomography. Human neuroimaging studies in healthy and clinical populations largely confirm the animal literature indicating that the PAG is involved in homeostatic regulation of salient functions such as pain, anxiety and autonomic function. Methodological concerns in the current literature, including resolution constraints, imaging artifacts and imprecise neuroanatomical labeling are discussed, and future directions are proposed. A general conclusion is that PAG neuroimaging is a field with enormous potential to translate animal data onto human behaviors, but with some growing pains that can and need to be addressed in order to add to our understanding of the neurobiology of this key region. PMID:22197740

Hyperspectral microscopy and cluster analysis for oral cancer diagnosis

NASA Astrophysics Data System (ADS)

Jarman, Anneliese; Manickavasagam, Arunthathi; Hosny, Neveen; Festy, Frederic

2017-02-01

Oral cancer incidences have been increasing in recent years and late detection often leads to poor prognosis. Raman spectroscopy has been identified has a valuable diagnostic tool for cancer but its time consuming nature has prevented its clinical use. For Raman to become a realistic aid to histopathology, a rapid pre-screening technique is required to find small regions of interest on tissue sections [1]. The aim of this work is to investigate the feasibility of hyperspectral imaging in the visible spectral range as a fast imaging technique before Raman is performed. We have built a hyperspectral microscope which captures 300 focused and intensity corrected images with wavelength ranging from 450- 750 nm in around 30 minutes with sub-micron spatial resolution and around 10 nm spectral resolution. Hyperstacks of known absorbing samples, including fluorescent dyes and dried blood droplets, show excellent results with spectrally accurate transmission spectra and concentration-dependent intensity variations. We successfully showed the presence of different components from a non-absorbent saliva droplet sample. Data analysis is the greatest hurdle to the interpretation of more complex data such as unstained tissue sections.

Automation of immunohistochemical evaluation in breast cancer using image analysis

PubMed Central

Prasad, Keerthana; Tiwari, Avani; Ilanthodi, Sandhya; Prabhu, Gopalakrishna; Pai, Muktha

2011-01-01

AIM: To automate breast cancer diagnosis and to study the inter-observer and intra-observer variations in the manual evaluations. METHODS: Breast tissue specimens from sixty cases were stained separately for estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2/neu). All cases were assessed by manual grading as well as image analysis. The manual grading was performed by an experienced expert pathologist. To study inter-observer and intra-observer variations, we obtained readings from another pathologist as the second observer from a different laboratory who has a little less experience than the first observer. We also took a second reading from the second observer to study intra-observer variations. Image analysis was carried out using in-house developed software (TissueQuant). A comparison of the results from image analysis and manual scoring of ER, PR and HER-2/neu was also carried out. RESULTS: The performance of the automated analysis in the case of ER, PR and HER-2/neu expressions was compared with the manual evaluations. The performance of the automated system was found to correlate well with the manual evaluations. The inter-observer variations were measured using Spearman correlation coefficient r and 95% confidence interval. In the case of ER expression, Spearman correlation r = 0.53, in the case of PR expression, r = 0.63, and in the case of HER-2/neu expression, r = 0.68. Similarly, intra-observer variations were also measured. In the case of ER, PR and HER-2/neu expressions, r = 0.46, 0.66 and 0.70, respectively. CONCLUSION: The automation of breast cancer diagnosis from immunohistochemically stained specimens is very useful for providing objective and repeatable evaluations. PMID:21611095

Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration

PubMed Central

Wardlaw, Joanna M; Smith, Eric E; Biessels, Geert J; Cordonnier, Charlotte; Fazekas, Franz; Frayne, Richard; Lindley, Richard I; O'Brien, John T; Barkhof, Frederik; Benavente, Oscar R; Black, Sandra E; Brayne, Carol; Breteler, Monique; Chabriat, Hugues; DeCarli, Charles; de Leeuw, Frank-Erik; Doubal, Fergus; Duering, Marco; Fox, Nick C; Greenberg, Steven; Hachinski, Vladimir; Kilimann, Ingo; Mok, Vincent; Oostenbrugge, Robert van; Pantoni, Leonardo; Speck, Oliver; Stephan, Blossom C M; Teipel, Stefan; Viswanathan, Anand; Werring, David; Chen, Christopher; Smith, Colin; van Buchem, Mark; Norrving, Bo; Gorelick, Philip B; Dichgans, Martin

2013-01-01

Summary Cerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE). PMID:23867200

Crowdsourcing as a screening tool to detect clinical features of glaucomatous optic neuropathy from digital photography.

PubMed

Mitry, Danny; Peto, Tunde; Hayat, Shabina; Blows, Peter; Morgan, James; Khaw, Kay-Tee; Foster, Paul J

2015-01-01

Crowdsourcing is the process of simplifying and outsourcing numerous tasks to many untrained individuals. Our aim was to assess the performance and repeatability of crowdsourcing in the classification of normal and glaucomatous discs from optic disc images. Optic disc images (N = 127) with pre-determined disease status were selected by consensus agreement from grading experts from a large cohort study. After reading brief illustrative instructions, we requested that knowledge workers (KWs) from a crowdsourcing platform (Amazon MTurk) classified each image as normal or abnormal. Each image was classified 20 times by different KWs. Two study designs were examined to assess the effect of varying KW experience and both study designs were conducted twice for consistency. Performance was assessed by comparing the sensitivity, specificity and area under the receiver operating characteristic curve (AUC). Overall, 2,540 classifications were received in under 24 hours at minimal cost. The sensitivity ranged between 83-88% across both trials and study designs, however the specificity was poor, ranging between 35-43%. In trial 1, the highest AUC (95%CI) was 0.64(0.62-0.66) and in trial 2 it was 0.63(0.61-0.65). There were no significant differences between study design or trials conducted. Crowdsourcing represents a cost-effective method of image analysis which demonstrates good repeatability and a high sensitivity. Optimisation of variables such as reward schemes, mode of image presentation, expanded response options and incorporation of training modules should be examined to determine their effect on the accuracy and reliability of this technique in retinal image analysis.

Discrimination of Benign and Neoplastic Mucosa with a High-Resolution Microendoscope (HRME) in Head and Neck Cancer

PubMed Central

Vila, Peter M.; Park, Chan W.; Pierce, Mark C.; Goldstein, Gregg H.; Levy, Lauren; Gurudutt, Vivek V.; Polydorides, Alexandras D.; Godbold, James H.; Teng, Marita S.; Genden, Eric M.; Miles, Brett A.; Anandasabapathy, Sharmila; Gillenwater, Ann M.; Richards-Kortum, Rebecca; Sikora, Andrew G.

2012-01-01

Background The efficacy of ablative surgery for head and neck squamous cell carcinoma (HNSCC) depends critically on obtaining negative margins. While intraoperative "frozen section" analysis of margins is a valuable adjunct, it is expensive, time-consuming, and highly dependent on pathologist expertise. Optical imaging has potential to improve the accuracy of margins by identifying cancerous tissue in real time. Our aim was to determine the accuracy and inter-rater reliability of head and neck cancer specialists using high-resolution microendoscopic (HRME) images to discriminate between cancerous and benign mucosa. Methods Thirty-eight patients diagnosed with HNSCC were enrolled in this single-center study. HRME was used to image each specimen after application of proflavine, with concurrent standard histopathologic analysis. Images were evaluated for quality control, and a training set containing representative images of benign and neoplastic tissue was assembled. After viewing training images, seven head and neck cancer specialists with no prior HRME experience reviewed 37 test images and were asked to classify each. Results The mean accuracy of all reviewers in correctly diagnosing neoplastic mucosa was 97 percent (95% Cl = 94–99%). The mean sensitivity and specificity were 98 percent (97–100%) and 92 percent (87–98%), respectively. The Fleiss kappa statistic for inter-rater reliability was 0.84 (0.77–0.91). Conclusions Medical professionals can be quickly trained to use HRME to discriminate between benign and neoplastic mucosa in the head and neck. With further development, the HRME shows promise as a method of real-time margin determination at the point of care. PMID:22492225

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.

Does thorax EIT image analysis depend on the image reconstruction method?

NASA Astrophysics Data System (ADS)

Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

2013-04-01

Different methods were proposed to analyze the resulting images of electrical impedance tomography (EIT) measurements during ventilation. The aim of our study was to examine if the analysis methods based on back-projection deliver the same results when applied on images based on other reconstruction algorithms. Seven mechanically ventilated patients with ARDS were examined by EIT. The thorax contours were determined from the routine CT images. EIT raw data was reconstructed offline with (1) filtered back-projection with circular forward model (BPC); (2) GREIT reconstruction method with circular forward model (GREITC) and (3) GREIT with individual thorax geometry (GREITT). Three parameters were calculated on the resulting images: linearity, global ventilation distribution and regional ventilation distribution. The results of linearity test are 5.03±2.45, 4.66±2.25 and 5.32±2.30 for BPC, GREITC and GREITT, respectively (median ±interquartile range). The differences among the three methods are not significant (p = 0.93, Kruskal-Wallis test). The proportions of ventilation in the right lung are 0.58±0.17, 0.59±0.20 and 0.59±0.25 for BPC, GREITC and GREITT, respectively (p = 0.98). The differences of the GI index based on different reconstruction methods (0.53±0.16, 0.51±0.25 and 0.54±0.16 for BPC, GREITC and GREITT, respectively) are also not significant (p = 0.93). We conclude that the parameters developed for images generated with GREITT are comparable with filtered back-projection and GREITC.

Image classification of human carcinoma cells using complex wavelet-based covariance descriptors.

PubMed

Keskin, Furkan; Suhre, Alexander; Kose, Kivanc; Ersahin, Tulin; Cetin, A Enis; Cetin-Atalay, Rengul

2013-01-01

Cancer cell lines are widely used for research purposes in laboratories all over the world. Computer-assisted classification of cancer cells can alleviate the burden of manual labeling and help cancer research. In this paper, we present a novel computerized method for cancer cell line image classification. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by subwindows which correspond to foreground pixels. For each subwindow, a covariance descriptor utilizing the dual-tree complex wavelet transform (DT-[Formula: see text]WT) coefficients and several morphological attributes are computed. Directionally selective DT-[Formula: see text]WT feature parameters are preferred primarily because of their ability to characterize edges at multiple orientations which is the characteristic feature of carcinoma cell line images. A Support Vector Machine (SVM) classifier with radial basis function (RBF) kernel is employed for final classification. Over a dataset of 840 images, we achieve an accuracy above 98%, which outperforms the classical covariance-based methods. The proposed system can be used as a reliable decision maker for laboratory studies. Our tool provides an automated, time- and cost-efficient analysis of cancer cell morphology to classify different cancer cell lines using image-processing techniques, which can be used as an alternative to the costly short tandem repeat (STR) analysis. The data set used in this manuscript is available as supplementary material through http://signal.ee.bilkent.edu.tr/cancerCellLineClassificationSampleImages.html.

Image Classification of Human Carcinoma Cells Using Complex Wavelet-Based Covariance Descriptors

PubMed Central

Keskin, Furkan; Suhre, Alexander; Kose, Kivanc; Ersahin, Tulin; Cetin, A. Enis; Cetin-Atalay, Rengul

2013-01-01

Cancer cell lines are widely used for research purposes in laboratories all over the world. Computer-assisted classification of cancer cells can alleviate the burden of manual labeling and help cancer research. In this paper, we present a novel computerized method for cancer cell line image classification. The aim is to automatically classify 14 different classes of cell lines including 7 classes of breast and 7 classes of liver cancer cells. Microscopic images containing irregular carcinoma cell patterns are represented by subwindows which correspond to foreground pixels. For each subwindow, a covariance descriptor utilizing the dual-tree complex wavelet transform (DT-WT) coefficients and several morphological attributes are computed. Directionally selective DT-WT feature parameters are preferred primarily because of their ability to characterize edges at multiple orientations which is the characteristic feature of carcinoma cell line images. A Support Vector Machine (SVM) classifier with radial basis function (RBF) kernel is employed for final classification. Over a dataset of 840 images, we achieve an accuracy above 98%, which outperforms the classical covariance-based methods. The proposed system can be used as a reliable decision maker for laboratory studies. Our tool provides an automated, time- and cost-efficient analysis of cancer cell morphology to classify different cancer cell lines using image-processing techniques, which can be used as an alternative to the costly short tandem repeat (STR) analysis. The data set used in this manuscript is available as supplementary material through http://signal.ee.bilkent.edu.tr/cancerCellLineClassificationSampleImages.html. PMID:23341908

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

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.

Iris Image Classification Based on Hierarchical Visual Codebook.

PubMed

Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

2014-06-01

Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

Measurement accuracy and perceived quality of imaging systems for the evaluation of periodontal structures.

PubMed

Baksi, B Güniz

2008-07-01

The aim of this study was to compare the subjective diagnostic quality of F-speed film images and original and enhanced storage phosphor plate (SPP) digital images for the visualization of periodontal ligament space (PLS) and periapical (PB) and alveolar crestal bone (CB) and to assess the accuracy of these image modalities for the measurement of alveolar bone levels. Standardized images of six dried mandibles were obtained with film and Digora SPPs. Six evaluators rated the visibility of anatomical structures using a three-point scale. Alveolar bone levels were measured from the coronal-most tip of the marginal bone to a reference point. Results were compared by using Friedman and Wilcoxon signed-ranks tests. The kappa (kappa) statistic was used to measure agreement among observers. The measurements were compared using repeated measures analysis of variance and Bonferroni tests (P = 0.05). A paired t test was used for comparison with true bone levels (P = 0.05). Enhanced SPP images were rated superior, followed by film and then the original SPP images, for the evaluation of anatomical structures. The value of kappa rose from fair to substantial after the enhancement of the SPP images. Film and enhanced SPP images provided alveolar bone lengths close to the true bone lengths. Enhancement of digital images provided better visibility and resulted in comparable accuracy to film images for the evaluation of periodontal structures.

X-ray dark-field radiography facilitates the diagnosis of pulmonary fibrosis in a mouse model.

PubMed

Hellbach, Katharina; Yaroshenko, Andre; Willer, Konstantin; Conlon, Thomas M; Braunagel, Margarita B; Auweter, Sigrid; Yildirim, Ali Ö; Eickelberg, Oliver; Pfeiffer, Franz; Reiser, Maximilian F; Meinel, Felix G

2017-03-23

The aim of this study was to evaluate whether diagnosing pulmonary fibrosis with projection radiography can be improved by using X-ray dark-field radiograms. Pulmonary X-ray transmission and dark-field images of C57Bl/6N mice, either treated with bleomycin to induce pulmonary fibrosis or PBS to serve as controls, were acquired with a prototype grating-based small-animal scanner. Two blinded readers, both experienced radiologists and familiar with dark-field imaging, had to assess dark-field and transmission images for the absence or presence of fibrosis. Furthermore readers were asked to grade their stage of diagnostic confidence. Histological evaluation of the lungs served as the standard of reference in this study. Both readers showed a notably higher diagnostic confidence when analyzing the dark-field radiographs (p < 0.001). Diagnostic accuracy improved significantly when evaluating the lungs in dark-field images alone (p = 0.02) or in combination with transmission images (p = 0.01) compared to sole analysis of absorption images. Interreader agreement improved from good when assessing only transmission images to excellent when analyzing dark-field images alone or in combination with transmission images. Adding dark-field images to conventional transmission images in a murine model of pulmonary fibrosis leads to an improved diagnosis of this disease on chest radiographs.

Breast-specific gamma camera imaging with 99mTc-MIBI has better diagnostic performance than magnetic resonance imaging in breast cancer patients: A meta-analysis.

PubMed

Zhang, Aimi; Li, Panli; Liu, Qiufang; Song, Shaoli

2017-01-01

This study aimed to evaluate the diagnostic role of breast-specific gamma camera imaging (BSGI) with technetium-99m-methoxy isobutyl isonitrile ( 99m Tc-MIBI) and magnetic resonance imaging (MRI) in patients with breast cancer through a meta-analysis. Three reviewers searched articles published in medical journals before June 2016 in MEDLINE, EMBASE and Springer Databases; the references listed in original articles were also retrieved. We used the quality assessment of diagnostic accuracy studies (QUADAS) tool to assess the quality of the included studies. Heterogeneity, pooled sensitivity and specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR) and summary receiver operating characteristic (SROC) curves were calculated by Meta-DiSc software to estimate the diagnostic performance of BSGI and MRI. Ten studies with 517 patients were included after meeting the inclusion criteria. We did a subgroup analysis of the same data type. The pooled sensitivities of BSGI and MRI were: 0.84 (95% CI, 0.79-0.88) and 0.89 (95% CI, 0.84-0.92) respectively, and the pooled specificities of BSGI and MRI were: 0.82 (95% CI, 0.74-0.88) and 0.39 (95% CI, 0.30-0.49) respectively. The areas under the SROC curve of BSGI and MRI were 0.93 and 0.72 respectively. The results of our meta-analysis indicated that compared with MRI, BSGI has similar sensitivity, higher specificity, better diagnostic performance, and can be widely used in clinical practice.

Skin cancer margin analysis within minutes with full-field OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Dalimier, Eugénie; Ogrich, Lauren; Morales, Diego; Cusack, Carrie Ann; Abdelmalek, Mark; Boccara, Claude; Durkin, John

2017-02-01

Non-melanoma skin cancer (NMSC) is the most common cancer. Treatment consists of surgical removal of the skin cancer. Traditional excision involves the removal of the visible skin cancer with a significant margin of normal skin. On cosmetically sensitive areas, Mohs micrographic tissue is the standard of care. Mohs uses intraoperative microscopic margin assessment which minimizes the surgical defect and can help reduce the recurrence rate by a factor of 3. The current Mohs technique relies on frozen section tissue slide preparation which significantly lengthens operative time and requires on-site trained histotechnicians. Full-Field Optical Coherence Tomography (FFOCT) is a novel optical imaging technique which provides a quick and efficient method to visualize cancerous areas in minutes, without any preparation or destruction of the tissue. This study aimed to evaluate the potential of FFOCT for the analysis of skin cancer margins during Mohs surgery. Over 150 images of Mohs specimens were acquired intraoperatively with FFOCT before frozen section analysis. The imaging procedure took less than 5 minutes for each specimen. No artifacts on histological preparation were found arising from FFOCT manipulation; however frozen section artifact was readily seen on FFOCT. An atlas was established with FFOCT images and corresponding histological slides to reveal FFOCT reading criteria of normal and cancerous structures. Blind analysis showed high concordance between FFOCT and histology. FFOCT can potentially reduce recurrence rates while maintaining short surgery times, optimize clinical workflow, and decrease healthcare costs. For the patient, this translates into smaller infection risk, decreased stress, and better comfort.

Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography: Unveiling the Invisible.

PubMed

Mannil, Manoj; von Spiczak, Jochen; Manka, Robert; Alkadhi, Hatem

2018-06-01

The aim of this study was to test whether texture analysis and machine learning enable the detection of myocardial infarction (MI) on non-contrast-enhanced low radiation dose cardiac computed tomography (CCT) images. In this institutional review board-approved retrospective study, we included non-contrast-enhanced electrocardiography-gated low radiation dose CCT image data (effective dose, 0.5 mSv) acquired for the purpose of calcium scoring of 27 patients with acute MI (9 female patients; mean age, 60 ± 12 years), 30 patients with chronic MI (8 female patients; mean age, 68 ± 13 years), and in 30 subjects (9 female patients; mean age, 44 ± 6 years) without cardiac abnormality, hereafter termed controls. Texture analysis of the left ventricle was performed using free-hand regions of interest, and texture features were classified twice (Model I: controls versus acute MI versus chronic MI; Model II: controls versus acute and chronic MI). For both classifications, 6 commonly used machine learning classifiers were used: decision tree C4.5 (J48), k-nearest neighbors, locally weighted learning, RandomForest, sequential minimal optimization, and an artificial neural network employing deep learning. In addition, 2 blinded, independent readers visually assessed noncontrast CCT images for the presence or absence of MI. In Model I, best classification results were obtained using the k-nearest neighbors classifier (sensitivity, 69%; specificity, 85%; false-positive rate, 0.15). In Model II, the best classification results were found with the locally weighted learning classification (sensitivity, 86%; specificity, 81%; false-positive rate, 0.19) with an area under the curve from receiver operating characteristics analysis of 0.78. In comparison, both readers were not able to identify MI in any of the noncontrast, low radiation dose CCT images. This study indicates the ability of texture analysis and machine learning in detecting MI on noncontrast low radiation dose CCT images being not visible for the radiologists' eye.

GPCALMA: A Tool For Mammography With A GRID-Connected Distributed Database

NASA Astrophysics Data System (ADS)

Bottigli, U.; Cerello, P.; Cheran, S.; Delogu, P.; Fantacci, M. E.; Fauci, F.; Golosio, B.; Lauria, A.; Lopez Torres, E.; Magro, R.; Masala, G. L.; Oliva, P.; Palmiero, R.; Raso, G.; Retico, A.; Stumbo, S.; Tangaro, S.

2003-09-01

The GPCALMA (Grid Platform for Computer Assisted Library for MAmmography) collaboration involves several departments of physics, INFN (National Institute of Nuclear Physics) sections, and italian hospitals. The aim of this collaboration is developing a tool that can help radiologists in early detection of breast cancer. GPCALMA has built a large distributed database of digitised mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) software which is integrated in a station that can also be used to acquire new images, as archive and to perform statistical analysis. The images (18×24 cm2, digitised by a CCD linear scanner with a 85 μm pitch and 4096 gray levels) are completely described: pathological ones have a consistent characterization with radiologist's diagnosis and histological data, non pathological ones correspond to patients with a follow up at least three years. The distributed database is realized throught the connection of all the hospitals and research centers in GRID tecnology. In each hospital local patients digital images are stored in the local database. Using GRID connection, GPCALMA will allow each node to work on distributed database data as well as local database data. Using its database the GPCALMA tools perform several analysis. A texture analysis, i.e. an automated classification on adipose, dense or glandular texture, can be provided by the system. GPCALMA software also allows classification of pathological features, in particular massive lesions (both opacities and spiculated lesions) analysis and microcalcification clusters analysis. The detection of pathological features is made using neural network software that provides a selection of areas showing a given "suspicion level" of lesion occurrence. The performance of the GPCALMA system will be presented in terms of the ROC (Receiver Operating Characteristic) curves. The results of GPCALMA system as "second reader" will also be presented.

Texture analysis of tissues in Gleason grading of prostate cancer

NASA Astrophysics Data System (ADS)

Alexandratou, Eleni; Yova, Dido; Gorpas, Dimitris; Maragos, Petros; Agrogiannis, George; Kavantzas, Nikolaos

2008-02-01

Prostate cancer is a common malignancy among maturing men and the second leading cause of cancer death in USA. Histopathological grading of prostate cancer is based on tissue structural abnormalities. Gleason grading system is the gold standard and is based on the organization features of prostatic glands. Although Gleason score has contributed on cancer prognosis and on treatment planning, its accuracy is about 58%, with this percentage to be lower in GG2, GG3 and GG5 grading. On the other hand it is strongly affected by "inter- and intra observer variations", making the whole process very subjective. Therefore, there is need for the development of grading tools based on imaging and computer vision techniques for a more accurate prostate cancer prognosis. The aim of this paper is the development of a novel method for objective grading of biopsy specimen in order to support histopathological prognosis of the tumor. This new method is based on texture analysis techniques, and particularly on Gray Level Co-occurrence Matrix (GLCM) that estimates image properties related to second order statistics. Histopathological images of prostate cancer, from Gleason grade2 to Gleason grade 5, were acquired and subjected to image texture analysis. Thirteen texture characteristics were calculated from this matrix as they were proposed by Haralick. Using stepwise variable selection, a subset of four characteristics were selected and used for the description and classification of each image field. The selected characteristics profile was used for grading the specimen with the multiparameter statistical method of multiple logistic discrimination analysis. The subset of these characteristics provided 87% correct grading of the specimens. The addition of any of the remaining characteristics did not improve significantly the diagnostic ability of the method. This study demonstrated that texture analysis techniques could provide valuable grading decision support to the pathologists, concerning prostate cancer prognosis.

Analysis of In-Situ Spectral Reflectance of Sago and Other Palms: Implications for Their Detection in Optical Satellite Images

NASA Astrophysics Data System (ADS)

Rendon Santillan, Jojene; Makinano-Santillan, Meriam

2018-04-01

We present a characterization, comparison and analysis of in-situ spectral reflectance of Sago and other palms (coconut, oil palm and nipa) to ascertain on which part of the electromagnetic spectrum these palms are distinguishable from each other. The analysis also aims to reveal information that will assist in selecting which band to use when mapping Sago palms using the images acquired by these sensors. The datasets used in the analysis consisted of averaged spectral reflectance curves of each palm species measured within the 345-1045 nm wavelength range using an Ocean Optics USB4000-VIS-NIR Miniature Fiber Optic Spectrometer. This in-situ reflectance data was also resampled to match the spectral response of the 4 bands of ALOS AVNIR-2, 3 bands of ASTER VNIR, 4 bands of Landsat 7 ETM+, 5 bands of Landsat 8, and 8 bands of Worldview-2 (WV2). Examination of the spectral reflectance curves showed that the near infra-red region, specifically at 770, 800 and 875 nm, provides the best wavelengths where Sago palms can be distinguished from other palms. The resampling of the in-situ reflectance spectra to match the spectral response of optical sensors made possible the analysis of the differences in reflectance values of Sago and other palms in different bands of the sensors. Overall, the knowledge learned from the analysis can be useful in the actual analysis of optical satellite images, specifically in determining which band to include or to exclude, or whether to use all bands of a sensor in discriminating and mapping Sago palms.

A Versatile Image Processor For Digital Diagnostic Imaging And Its Application In Computed Radiography

NASA Astrophysics Data System (ADS)

Blume, H.; Alexandru, R.; Applegate, R.; Giordano, T.; Kamiya, K.; Kresina, R.

1986-06-01

In a digital diagnostic imaging department, the majority of operations for handling and processing of images can be grouped into a small set of basic operations, such as image data buffering and storage, image processing and analysis, image display, image data transmission and image data compression. These operations occur in almost all nodes of the diagnostic imaging communications network of the department. An image processor architecture was developed in which each of these functions has been mapped into hardware and software modules. The modular approach has advantages in terms of economics, service, expandability and upgradeability. The architectural design is based on the principles of hierarchical functionality, distributed and parallel processing and aims at real time response. Parallel processing and real time response is facilitated in part by a dual bus system: a VME control bus and a high speed image data bus, consisting of 8 independent parallel 16-bit busses, capable of handling combined up to 144 MBytes/sec. The presented image processor is versatile enough to meet the video rate processing needs of digital subtraction angiography, the large pixel matrix processing requirements of static projection radiography, or the broad range of manipulation and display needs of a multi-modality diagnostic work station. Several hardware modules are described in detail. For illustrating the capabilities of the image processor, processed 2000 x 2000 pixel computed radiographs are shown and estimated computation times for executing the processing opera-tions are presented.

Image and Prestige Planning

ERIC Educational Resources Information Center

Ager, Dennis

2005-01-01

The aim of this paper is to clarify some notions about image and prestige planning. Starting from the Welsh example of language policy aiming to revitalise a language in danger of further decreasing in number of speakers and in centrality to Welsh life, definitions of four related terms are explored: image, status, prestige and identity. Paired…