Web tools for effective retrieval, visualization, and evaluation of cardiology medical images and records

NASA Astrophysics Data System (ADS)

Masseroli, Marco; Pinciroli, Francesco

2000-12-01

To provide easy retrieval, integration and evaluation of multimodal cardiology images and data in a web browser environment, distributed application technologies and java programming were used to implement a client-server architecture based on software agents. The server side manages secure connections and queries to heterogeneous remote databases and file systems containing patient personal and clinical data. The client side is a Java applet running in a web browser and providing a friendly medical user interface to perform queries on patient and medical test dat and integrate and visualize properly the various query results. A set of tools based on Java Advanced Imaging API enables to process and analyze the retrieved cardiology images, and quantify their features in different regions of interest. The platform-independence Java technology makes the developed prototype easy to be managed in a centralized form and provided in each site where an intranet or internet connection can be located. Giving the healthcare providers effective tools for querying, visualizing and evaluating comprehensively cardiology medical images and records in all locations where they can need them- i.e. emergency, operating theaters, ward, or even outpatient clinics- the developed prototype represents an important aid in providing more efficient diagnoses and medical treatments.

Retrieving high-resolution images over the Internet from an anatomical image database

NASA Astrophysics Data System (ADS)

Strupp-Adams, Annette; Henderson, Earl

1999-12-01

The Visible Human Data set is an important contribution to the national collection of anatomical images. To enhance the availability of these images, the National Library of Medicine has supported the design and development of a prototype object-oriented image database which imports, stores, and distributes high resolution anatomical images in both pixel and voxel formats. One of the key database modules is its client-server Internet interface. This Web interface provides a query engine with retrieval access to high-resolution anatomical images that range in size from 100KB for browser viewable rendered images, to 1GB for anatomical structures in voxel file formats. The Web query and retrieval client-server system is composed of applet GUIs, servlets, and RMI application modules which communicate with each other to allow users to query for specific anatomical structures, and retrieve image data as well as associated anatomical images from the database. Selected images can be downloaded individually as single files via HTTP or downloaded in batch-mode over the Internet to the user's machine through an applet that uses Netscape's Object Signing mechanism. The image database uses ObjectDesign's object-oriented DBMS, ObjectStore that has a Java interface. The query and retrieval systems has been tested with a Java-CDE window system, and on the x86 architecture using Windows NT 4.0. This paper describes the Java applet client search engine that queries the database; the Java client module that enables users to view anatomical images online; the Java application server interface to the database which organizes data returned to the user, and its distribution engine that allow users to download image files individually and/or in batch-mode.

A hierarchical SVG image abstraction layer for medical imaging

NASA Astrophysics Data System (ADS)

Kim, Edward; Huang, Xiaolei; Tan, Gang; Long, L. Rodney; Antani, Sameer

2010-03-01

As medical imaging rapidly expands, there is an increasing need to structure and organize image data for efficient analysis, storage and retrieval. In response, a large fraction of research in the areas of content-based image retrieval (CBIR) and picture archiving and communication systems (PACS) has focused on structuring information to bridge the "semantic gap", a disparity between machine and human image understanding. An additional consideration in medical images is the organization and integration of clinical diagnostic information. As a step towards bridging the semantic gap, we design and implement a hierarchical image abstraction layer using an XML based language, Scalable Vector Graphics (SVG). Our method encodes features from the raw image and clinical information into an extensible "layer" that can be stored in a SVG document and efficiently searched. Any feature extracted from the raw image including, color, texture, orientation, size, neighbor information, etc., can be combined in our abstraction with high level descriptions or classifications. And our representation can natively characterize an image in a hierarchical tree structure to support multiple levels of segmentation. Furthermore, being a world wide web consortium (W3C) standard, SVG is able to be displayed by most web browsers, interacted with by ECMAScript (standardized scripting language, e.g. JavaScript, JScript), and indexed and retrieved by XML databases and XQuery. Using these open source technologies enables straightforward integration into existing systems. From our results, we show that the flexibility and extensibility of our abstraction facilitates effective storage and retrieval of medical images.

A mathematical model of neuro-fuzzy approximation in image classification

NASA Astrophysics Data System (ADS)

Gopalan, Sasi; Pinto, Linu; Sheela, C.; Arun Kumar M., N.

2016-06-01

Image digitization and explosion of World Wide Web has made traditional search for image, an inefficient method for retrieval of required grassland image data from large database. For a given input query image Content-Based Image Retrieval (CBIR) system retrieves the similar images from a large database. Advances in technology has increased the use of grassland image data in diverse areas such has agriculture, art galleries, education, industry etc. In all the above mentioned diverse areas it is necessary to retrieve grassland image data efficiently from a large database to perform an assigned task and to make a suitable decision. A CBIR system based on grassland image properties and it uses the aid of a feed-forward back propagation neural network for an effective image retrieval is proposed in this paper. Fuzzy Memberships plays an important role in the input space of the proposed system which leads to a combined neural fuzzy approximation in image classification. The CBIR system with mathematical model in the proposed work gives more clarity about fuzzy-neuro approximation and the convergence of the image features in a grassland image.

Indexing the medical open access literature for textual and content-based visual retrieval.

PubMed

Eggel, Ivan; Müller, Henning

2010-01-01

Over the past few years an increasing amount of scientific journals have been created in an open access format. Particularly in the medical field the number of openly accessible journals is enormous making a wide body of knowledge available for analysis and retrieval. Part of the trend towards open access publications can be linked to funding bodies such as the NIH¹ (National Institutes of Health) and the Swiss National Science Foundation (SNF²) requiring funded projects to make all articles of funded research available publicly. This article describes an approach to make part of the knowledge of open access journals available for retrieval including the textual information but also the images contained in the articles. For this goal all articles of 24 journals related to medical informatics and medical imaging were crawled from the web pages of BioMed Central. Text and images of the PDF (Portable Document Format) files were indexed separately and a web-based retrieval interface allows for searching via keyword queries or by visual similarity queries. Starting point for a visual similarity query can be an image on the local hard disk that is uploaded or any image found via the textual search. Search for similar documents is also possible.

Architecture for biomedical multimedia information delivery on the World Wide Web

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Goh, Gin-Hua; Neve, Leif; Thoma, George R.

1997-10-01

Research engineers at the National Library of Medicine are building a prototype system for the delivery of multimedia biomedical information on the World Wide Web. This paper discuses the architecture and design considerations for the system, which will be used initially to make images and text from the third National Health and Nutrition Examination Survey (NHANES) publicly available. We categorized our analysis as follows: (1) fundamental software tools: we analyzed trade-offs among use of conventional HTML/CGI, X Window Broadway, and Java; (2) image delivery: we examined the use of unconventional TCP transmission methods; (3) database manager and database design: we discuss the capabilities and planned use of the Informix object-relational database manager and the planned schema for the HNANES database; (4) storage requirements for our Sun server; (5) user interface considerations; (6) the compatibility of the system with other standard research and analysis tools; (7) image display: we discuss considerations for consistent image display for end users. Finally, we discuss the scalability of the system in terms of incorporating larger or more databases of similar data, and the extendibility of the system for supporting content-based retrieval of biomedical images. The system prototype is called the Web-based Medical Information Retrieval System. An early version was built as a Java applet and tested on Unix, PC, and Macintosh platforms. This prototype used the MiniSQL database manager to do text queries on a small database of records of participants in the second NHANES survey. The full records and associated x-ray images were retrievable and displayable on a standard Web browser. A second version has now been built, also a Java applet, using the MySQL database manager.

J-Plus Web Portal

NASA Astrophysics Data System (ADS)

Civera Lorenzo, Tamara

2017-10-01

Brief presentation about the J-PLUS EDR data access web portal (http://archive.cefca.es/catalogues/jplus-edr) where the different services available to retrieve images and catalogues data have been presented.J-PLUS Early Data Release (EDR) archive includes two types of data: images and dual and single catalogue data which include parameters measured from images. J-PLUS web portal offers catalogue data and images through several different online data access tools or services each suited to a particular need. The different services offered are: Coverage map Sky navigator Object visualization Image search Cone search Object list search Virtual observatory services: Simple Cone Search Simple Image Access Protocol Simple Spectral Access Protocol Table Access Protocol

A medical ontology for intelligent web-based skin lesions image retrieval.

PubMed

Maragoudakis, Manolis; Maglogiannis, Ilias

2011-06-01

Researchers have applied increasing efforts towards providing formal computational frameworks to consolidate the plethora of concepts and relations used in the medical domain. In the domain of skin related diseases, the variability of semantic features contained within digital skin images is a major barrier to the medical understanding of the symptoms and development of early skin cancers. The desideratum of making these standards machine-readable has led to their formalization in ontologies. In this work, in an attempt to enhance an existing Core Ontology for skin lesion images, hand-coded from image features, high quality images were analyzed by an autonomous ontology creation engine. We show that by exploiting agglomerative clustering methods with distance criteria upon the existing ontological structure, the original domain model could be enhanced with new instances, attributes and even relations, thus allowing for better classification and retrieval of skin lesion categories from the web.

4D reconstruction of the past: the image retrieval and 3D model construction pipeline

NASA Astrophysics Data System (ADS)

Hadjiprocopis, Andreas; Ioannides, Marinos; Wenzel, Konrad; Rothermel, Mathias; Johnsons, Paul S.; Fritsch, Dieter; Doulamis, Anastasios; Protopapadakis, Eftychios; Kyriakaki, Georgia; Makantasis, Kostas; Weinlinger, Guenther; Klein, Michael; Fellner, Dieter; Stork, Andre; Santos, Pedro

2014-08-01

One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.

Developing a comprehensive system for content-based retrieval of image and text data from a national survey

NASA Astrophysics Data System (ADS)

Antani, Sameer K.; Natarajan, Mukil; Long, Jonathan L.; Long, L. Rodney; Thoma, George R.

2005-04-01

The article describes the status of our ongoing R&D at the U.S. National Library of Medicine (NLM) towards the development of an advanced multimedia database biomedical information system that supports content-based image retrieval (CBIR). NLM maintains a collection of 17,000 digitized spinal X-rays along with text survey data from the Second National Health and Nutritional Examination Survey (NHANES II). These data serve as a rich data source for epidemiologists and researchers of osteoarthritis and musculoskeletal diseases. It is currently possible to access these through text keyword queries using our Web-based Medical Information Retrieval System (WebMIRS). CBIR methods developed specifically for biomedical images could offer direct visual searching of these images by means of example image or user sketch. We are building a system which supports hybrid queries that have text and image-content components. R&D goals include developing algorithms for robust image segmentation for localizing and identifying relevant anatomy, labeling the segmented anatomy based on its pathology, developing suitable indexing and similarity matching methods for images and image features, and associating the survey text information for query and retrieval along with the image data. Some highlights of the system developed in MATLAB and Java are: use of a networked or local centralized database for text and image data; flexibility to incorporate new research work; provides a means to control access to system components under development; and use of XML for structured reporting. The article details the design, features, and algorithms in this third revision of this prototype system, CBIR3.

Space Images for NASA JPL Android Version

NASA Technical Reports Server (NTRS)

Nelson, Jon D.; Gutheinz, Sandy C.; Strom, Joshua R.; Arca, Jeremy M.; Perez, Martin; Boggs, Karen; Stanboli, Alice

2013-01-01

This software addresses the demand for easily accessible NASA JPL images and videos by providing a user friendly and simple graphical user interface that can be run via the Android platform from any location where Internet connection is available. This app is complementary to the iPhone version of the application. A backend infrastructure stores, tracks, and retrieves space images from the JPL Photojournal and Institutional Communications Web server, and catalogs the information into a streamlined rating infrastructure. This system consists of four distinguishing components: image repository, database, server-side logic, and Android mobile application. The image repository contains images from various JPL flight projects. The database stores the image information as well as the user rating. The server-side logic retrieves the image information from the database and categorizes each image for display. The Android mobile application is an interfacing delivery system that retrieves the image information from the server for each Android mobile device user. Also created is a reporting and tracking system for charting and monitoring usage. Unlike other Android mobile image applications, this system uses the latest emerging technologies to produce image listings based directly on user input. This allows for countless combinations of images returned. The backend infrastructure uses industry-standard coding and database methods, enabling future software improvement and technology updates. The flexibility of the system design framework permits multiple levels of display possibilities and provides integration capabilities. Unique features of the software include image/video retrieval from a selected set of categories, image Web links that can be shared among e-mail users, sharing to Facebook/Twitter, marking as user's favorites, and image metadata searchable for instant results.

Design, Development and Testing of Web Services for Multi-Sensor Snow Cover Mapping

NASA Astrophysics Data System (ADS)

Kadlec, Jiri

This dissertation presents the design, development and validation of new data integration methods for mapping the extent of snow cover based on open access ground station measurements, remote sensing images, volunteer observer snow reports, and cross country ski track recordings from location-enabled mobile devices. The first step of the data integration procedure includes data discovery, data retrieval, and data quality control of snow observations at ground stations. The WaterML R package developed in this work enables hydrologists to retrieve and analyze data from multiple organizations that are listed in the Consortium of Universities for the Advancement of Hydrologic Sciences Inc (CUAHSI) Water Data Center catalog directly within the R statistical software environment. Using the WaterML R package is demonstrated by running an energy balance snowpack model in R with data inputs from CUAHSI, and by automating uploads of real time sensor observations to CUAHSI HydroServer. The second step of the procedure requires efficient access to multi-temporal remote sensing snow images. The Snow Inspector web application developed in this research enables the users to retrieve a time series of fractional snow cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) for any point on Earth. The time series retrieval method is based on automated data extraction from tile images provided by a Web Map Tile Service (WMTS). The average required time for retrieving 100 days of data using this technique is 5.4 seconds, which is significantly faster than other methods that require the download of large satellite image files. The presented data extraction technique and space-time visualization user interface can be used as a model for working with other multi-temporal hydrologic or climate data WMTS services. The third, final step of the data integration procedure is generating continuous daily snow cover maps. A custom inverse distance weighting method has been developed to combine volunteer snow reports, cross-country ski track reports and station measurements to fill cloud gaps in the MODIS snow cover product. The method is demonstrated by producing a continuous daily time step snow presence probability map dataset for the Czech Republic region. The ability of the presented methodology to reconstruct MODIS snow cover under cloud is validated by simulating cloud cover datasets and comparing estimated snow cover to actual MODIS snow cover. The percent correctly classified indicator showed accuracy between 80 and 90% using this method. Using crowdsourcing data (volunteer snow reports and ski tracks) improves the map accuracy by 0.7--1.2%. The output snow probability map data sets are published online using web applications and web services. Keywords: crowdsourcing, image analysis, interpolation, MODIS, R statistical software, snow cover, snowpack probability, Tethys platform, time series, WaterML, web services, winter sports.

An Image Retrieval and Processing Expert System for the World Wide Web

NASA Technical Reports Server (NTRS)

Rodriguez, Ricardo; Rondon, Angelica; Bruno, Maria I.; Vasquez, Ramon

1998-01-01

This paper presents a system that is being developed in the Laboratory of Applied Remote Sensing and Image Processing at the University of P.R. at Mayaguez. It describes the components that constitute its architecture. The main elements are: a Data Warehouse, an Image Processing Engine, and an Expert System. Together, they provide a complete solution to researchers from different fields that make use of images in their investigations. Also, since it is available to the World Wide Web, it provides remote access and processing of images.

Space Images for NASA/JPL

NASA Technical Reports Server (NTRS)

Boggs, Karen; Gutheinz, Sandy C.; Watanabe, Susan M.; Oks, Boris; Arca, Jeremy M.; Stanboli, Alice; Peez, Martin; Whatmore, Rebecca; Kang, Minliang; Espinoza, Luis A.

2010-01-01

Space Images for NASA/JPL is an Apple iPhone application that allows the general public to access featured images from the Jet Propulsion Laboratory (JPL). A back-end infrastructure stores, tracks, and retrieves space images from the JPL Photojournal Web server, and catalogs the information into a streamlined rating infrastructure.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

PubMed

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm

PubMed Central

Song, Wei; Mei, Haibin

2017-01-01

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient. PMID:28737699

Performance analysis of algorithms for retrieval of magnetic resonance images for interactive teleradiology

NASA Astrophysics Data System (ADS)

Atkins, M. Stella; Hwang, Robert; Tang, Simon

2001-05-01

We have implemented a prototype system consisting of a Java- based image viewer and a web server extension component for transmitting Magnetic Resonance Images (MRI) to an image viewer, to test the performance of different image retrieval techniques. We used full-resolution images, and images compressed/decompressed using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm. We examined the SPIHT decompression algorithm using both non- progressive and progressive transmission, focusing on the running times of the algorithm, client memory usage and garbage collection. We also compared the Java implementation with a native C++ implementation of the non- progressive SPIHT decompression variant. Our performance measurements showed that for uncompressed image retrieval using a 10Mbps Ethernet, a film of 16 MR images can be retrieved and displayed almost within interactive times. The native C++ code implementation of the client-side decoder is twice as fast as the Java decoder. If the network bandwidth is low, the high communication time for retrieving uncompressed images may be reduced by use of SPIHT-compressed images, although the image quality is then degraded. To provide diagnostic quality images, we also investigated the retrieval of up to 3 images on a MR film at full-resolution, using progressive SPIHT decompression. The Java-based implementation of progressive decompression performed badly, mainly due to the memory requirements for maintaining the image states, and the high cost of execution of the Java garbage collector. Hence, in systems where the bandwidth is high, such as found in a hospital intranet, SPIHT image compression does not provide advantages for image retrieval performance.

An Online Image Analysis Tool for Science Education

ERIC Educational Resources Information Center

Raeside, L.; Busschots, B.; Waddington, S.; Keating, J. G.

2008-01-01

This paper describes an online image analysis tool developed as part of an iterative, user-centered development of an online Virtual Learning Environment (VLE) called the Education through Virtual Experience (EVE) Portal. The VLE provides a Web portal through which schoolchildren and their teachers create scientific proposals, retrieve images and…

Content-based image retrieval on mobile devices

NASA Astrophysics Data System (ADS)

Ahmad, Iftikhar; Abdullah, Shafaq; Kiranyaz, Serkan; Gabbouj, Moncef

2005-03-01

Content-based image retrieval area possesses a tremendous potential for exploration and utilization equally for researchers and people in industry due to its promising results. Expeditious retrieval of desired images requires indexing of the content in large-scale databases along with extraction of low-level features based on the content of these images. With the recent advances in wireless communication technology and availability of multimedia capable phones it has become vital to enable query operation in image databases and retrieve results based on the image content. In this paper we present a content-based image retrieval system for mobile platforms, providing the capability of content-based query to any mobile device that supports Java platform. The system consists of light-weight client application running on a Java enabled device and a server containing a servlet running inside a Java enabled web server. The server responds to image query using efficient native code from selected image database. The client application, running on a mobile phone, is able to initiate a query request, which is handled by a servlet in the server for finding closest match to the queried image. The retrieved results are transmitted over mobile network and images are displayed on the mobile phone. We conclude that such system serves as a basis of content-based information retrieval on wireless devices and needs to cope up with factors such as constraints on hand-held devices and reduced network bandwidth available in mobile environments.

Keynote Talk: Mining the Web 2.0 for Improved Image Search

NASA Astrophysics Data System (ADS)

Baeza-Yates, Ricardo

There are several semantic sources that can be found in the Web that are either explicit, e.g. Wikipedia, or implicit, e.g. derived from Web usage data. Most of them are related to user generated content (UGC) or what is called today the Web 2.0. In this talk we show how to use these sources of evidence in Flickr, such as tags, visual annotations or clicks, which represent the the wisdom of crowds behind UGC, to improve image search. These results are the work of the multimedia retrieval team at Yahoo! Research Barcelona and they are already being used in Yahoo! image search. This work is part of a larger effort to produce a virtuous data feedback circuit based on the right combination many different technologies to leverage the Web itself.

Content-based image retrieval with ontological ranking

NASA Astrophysics Data System (ADS)

Tsai, Shen-Fu; Tsai, Min-Hsuan; Huang, Thomas S.

2010-02-01

Images are a much more powerful medium of expression than text, as the adage says: "One picture is worth a thousand words." It is because compared with text consisting of an array of words, an image has more degrees of freedom and therefore a more complicated structure. However, the less limited structure of images presents researchers in the computer vision community a tough task of teaching machines to understand and organize images, especially when a limit number of learning examples and background knowledge are given. The advance of internet and web technology in the past decade has changed the way human gain knowledge. People, hence, can exchange knowledge with others by discussing and contributing information on the web. As a result, the web pages in the internet have become a living and growing source of information. One is therefore tempted to wonder whether machines can learn from the web knowledge base as well. Indeed, it is possible to make computer learn from the internet and provide human with more meaningful knowledge. In this work, we explore this novel possibility on image understanding applied to semantic image search. We exploit web resources to obtain links from images to keywords and a semantic ontology constituting human's general knowledge. The former maps visual content to related text in contrast to the traditional way of associating images with surrounding text; the latter provides relations between concepts for machines to understand to what extent and in what sense an image is close to the image search query. With the aid of these two tools, the resulting image search system is thus content-based and moreover, organized. The returned images are ranked and organized such that semantically similar images are grouped together and given a rank based on the semantic closeness to the input query. The novelty of the system is twofold: first, images are retrieved not only based on text cues but their actual contents as well; second, the grouping is different from pure visual similarity clustering. More specifically, the inferred concepts of each image in the group are examined in the context of a huge concept ontology to determine their true relations with what people have in mind when doing image search.

Improving healthcare services using web based platform for management of medical case studies.

PubMed

Ogescu, Cristina; Plaisanu, Claudiu; Udrescu, Florian; Dumitru, Silviu

2008-01-01

The paper presents a web based platform for management of medical cases, support for healthcare specialists in taking the best clinical decision. Research has been oriented mostly on multimedia data management, classification algorithms for querying, retrieving and processing different medical data types (text and images). The medical case studies can be accessed by healthcare specialists and by students as anonymous case studies providing trust and confidentiality in Internet virtual environment. The MIDAS platform develops an intelligent framework to manage sets of medical data (text, static or dynamic images), in order to optimize the diagnosis and the decision process, which will reduce the medical errors and will increase the quality of medical act. MIDAS is an integrated project working on medical information retrieval from heterogeneous, distributed medical multimedia database.

Storing and Viewing Electronic Documents.

ERIC Educational Resources Information Center

Falk, Howard

1999-01-01

Discusses the conversion of fragile library materials to computer storage and retrieval to extend the life of the items and to improve accessibility through the World Wide Web. Highlights include entering the images, including scanning; optical character recognition; full text and manual indexing; and available document- and image-management…

Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

NASA Astrophysics Data System (ADS)

Chen, Yi-Chen; Lin, Chao-Hung

2016-06-01

With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.

Distributing medical images with internet technologies: a DICOM web server and a DICOM java viewer.

PubMed

Fernàndez-Bayó, J; Barbero, O; Rubies, C; Sentís, M; Donoso, L

2000-01-01

With the advent of filmless radiology, it becomes important to be able to distribute radiologic images digitally throughout an entire hospital. A new approach based on World Wide Web technologies was developed to accomplish this objective. This approach involves a Web server that allows the query and retrieval of images stored in a Digital Imaging and Communications in Medicine (DICOM) archive. The images can be viewed inside a Web browser with use of a small Java program known as the DICOM Java Viewer, which is executed inside the browser. The system offers several advantages over more traditional picture archiving and communication systems (PACS): It is easy to install and maintain, is platform independent, allows images to be manipulated and displayed efficiently, and is easy to integrate with existing systems that are already making use of Web technologies. The system is user-friendly and can easily be used from outside the hospital if a security policy is in place. The simplicity and flexibility of Internet technologies makes them highly preferable to the more complex PACS workstations. The system works well, especially with magnetic resonance and computed tomographic images, and can help improve and simplify interdepartmental relationships in a filmless hospital environment.

Enhanced reproducibility of SADI web service workflows with Galaxy and Docker.

PubMed

Aranguren, Mikel Egaña; Wilkinson, Mark D

2015-01-01

Semantic Web technologies have been widely applied in the life sciences, for example by data providers such as OpenLifeData and through web services frameworks such as SADI. The recently reported OpenLifeData2SADI project offers access to the vast OpenLifeData data store through SADI services. This article describes how to merge data retrieved from OpenLifeData2SADI with other SADI services using the Galaxy bioinformatics analysis platform, thus making this semantic data more amenable to complex analyses. This is demonstrated using a working example, which is made distributable and reproducible through a Docker image that includes SADI tools, along with the data and workflows that constitute the demonstration. The combination of Galaxy and Docker offers a solution for faithfully reproducing and sharing complex data retrieval and analysis workflows based on the SADI Semantic web service design patterns.

Rotation invariant fast features for large-scale recognition

NASA Astrophysics Data System (ADS)

Takacs, Gabriel; Chandrasekhar, Vijay; Tsai, Sam; Chen, David; Grzeszczuk, Radek; Girod, Bernd

2012-10-01

We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation- Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15× faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.2 Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

LandEx - Fast, FOSS-Based Application for Query and Retrieval of Land Cover Patterns

NASA Astrophysics Data System (ADS)

Netzel, P.; Stepinski, T.

2012-12-01

The amount of satellite-based spatial data is continuously increasing making a development of efficient data search tools a priority. The bulk of existing research on searching satellite-gathered data concentrates on images and is based on the concept of Content-Based Image Retrieval (CBIR); however, available solutions are not efficient and robust enough to be put to use as deployable web-based search tools. Here we report on development of a practical, deployable tool that searches classified, rather than raw image. LandEx (Landscape Explorer) is a GeoWeb-based tool for Content-Based Pattern Retrieval (CBPR) contained within the National Land Cover Dataset 2006 (NLCD2006). The USGS-developed NLCD2006 is derived from Landsat multispectral images; it covers the entire conterminous U.S. with the resolution of 30 meters/pixel and it depicts 16 land cover classes. The size of NLCD2006 is about 10 Gpixels (161,000 x 100,000 pixels). LandEx is a multi-tier GeoWeb application based on Open Source Software. Main components are: GeoExt/OpenLayers (user interface), GeoServer (OGC WMS, WCS and WPS server), and GRASS (calculation engine). LandEx performs search using query-by-example approach: user selects a reference scene (exhibiting a chosen pattern of land cover classes) and the tool produces, in real time, a map indicating a degree of similarity between the reference pattern and all local patterns across the U.S. Scene pattern is encapsulated by a 2D histogram of classes and sizes of single-class clumps. Pattern similarity is based on the notion of mutual information. The resultant similarity map can be viewed and navigated in a web browser, or it can download as a GeoTiff file for more in-depth analysis. The LandEx is available at http://sil.uc.edu

Content-based image retrieval in medical applications for picture archiving and communication systems

NASA Astrophysics Data System (ADS)

Lehmann, Thomas M.; Guld, Mark O.; Thies, Christian; Fischer, Benedikt; Keysers, Daniel; Kohnen, Michael; Schubert, Henning; Wein, Berthold B.

2003-05-01

Picture archiving and communication systems (PACS) aim to efficiently provide the radiologists with all images in a suitable quality for diagnosis. Modern standards for digital imaging and communication in medicine (DICOM) comprise alphanumerical descriptions of study, patient, and technical parameters. Currently, this is the only information used to select relevant images within PACS. Since textual descriptions insufficiently describe the great variety of details in medical images, content-based image retrieval (CBIR) is expected to have a strong impact when integrated into PACS. However, existing CBIR approaches usually are limited to a distinct modality, organ, or diagnostic study. In this state-of-the-art report, we present first results implementing a general approach to content-based image retrieval in medical applications (IRMA) and discuss its integration into PACS environments. Usually, a PACS consists of a DICOM image server and several DICOM-compliant workstations, which are used by radiologists for reading the images and reporting the findings. Basic IRMA components are the relational database, the scheduler, and the web server, which all may be installed on the DICOM image server, and the IRMA daemons running on distributed machines, e.g., the radiologists" workstations. These workstations can also host the web-based front-ends of IRMA applications. Integrating CBIR and PACS, a special focus is put on (a) location and access transparency for data, methods, and experiments, (b) replication transparency for methods in development, (c) concurrency transparency for job processing and feature extraction, (d) system transparency at method implementation time, and (e) job distribution transparency when issuing a query. Transparent integration will have a certain impact on diagnostic quality supporting both evidence-based medicine and case-based reasoning.

The comparative effectiveness of conventional and digital image libraries.

PubMed

McColl, R I; Johnson, A

2001-03-01

Before introducing a hospital-wide image database to improve access, navigation and retrieval speed, a comparative study between a conventional slide library and a matching image database was undertaken to assess its relative benefits. Paired time trials and personal questionnaires revealed faster retrieval rates, higher image quality, and easier viewing for the pilot digital image database. Analysis of confidentiality, copyright and data protection exposed similar issues for both systems, thus concluding that the digital image database is a more effective library system. The authors suggest that in the future, medical images will be stored on large, professionally administered, centrally located file servers, allowing specialist image libraries to be tailored locally for individual users. The further integration of the database with web technology will enable cheap and efficient remote access for a wide range of users.

Simultenious binary hash and features learning for image retrieval

NASA Astrophysics Data System (ADS)

Frantc, V. A.; Makov, S. V.; Voronin, V. V.; Marchuk, V. I.; Semenishchev, E. A.; Egiazarian, K. O.; Agaian, S.

2016-05-01

Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo-collection management systems, web-scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image-retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel-based image representation to hash-value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine-tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data- dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state-of-the-art methods.

Image Re-Ranking Based on Topic Diversity.

PubMed

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

A Multimodal Search Engine for Medical Imaging Studies.

PubMed

Pinho, Eduardo; Godinho, Tiago; Valente, Frederico; Costa, Carlos

2017-02-01

The use of digital medical imaging systems in healthcare institutions has increased significantly, and the large amounts of data in these systems have led to the conception of powerful support tools: recent studies on content-based image retrieval (CBIR) and multimodal information retrieval in the field hold great potential in decision support, as well as for addressing multiple challenges in healthcare systems, such as computer-aided diagnosis (CAD). However, the subject is still under heavy research, and very few solutions have become part of Picture Archiving and Communication Systems (PACS) in hospitals and clinics. This paper proposes an extensible platform for multimodal medical image retrieval, integrated in an open-source PACS software with profile-based CBIR capabilities. In this article, we detail a technical approach to the problem by describing its main architecture and each sub-component, as well as the available web interfaces and the multimodal query techniques applied. Finally, we assess our implementation of the engine with computational performance benchmarks.

Multimedia explorer: image database, image proxy-server and search-engine.

PubMed Central

Frankewitsch, T.; Prokosch, U.

1999-01-01

Multimedia plays a major role in medicine. Databases containing images, movies or other types of multimedia objects are increasing in number, especially on the WWW. However, no good retrieval mechanism or search engine currently exists to efficiently track down such multimedia sources in the vast of information provided by the WWW. Secondly, the tools for searching databases are usually not adapted to the properties of images. HTML pages do not allow complex searches. Therefore establishing a more comfortable retrieval involves the use of a higher programming level like JAVA. With this platform independent language it is possible to create extensions to commonly used web browsers. These applets offer a graphical user interface for high level navigation. We implemented a database using JAVA objects as the primary storage container which are then stored by a JAVA controlled ORACLE8 database. Navigation depends on a structured vocabulary enhanced by a semantic network. With this approach multimedia objects can be encapsulated within a logical module for quick data retrieval. PMID:10566463

Multimedia explorer: image database, image proxy-server and search-engine.

PubMed

Frankewitsch, T; Prokosch, U

1999-01-01

Multimedia plays a major role in medicine. Databases containing images, movies or other types of multimedia objects are increasing in number, especially on the WWW. However, no good retrieval mechanism or search engine currently exists to efficiently track down such multimedia sources in the vast of information provided by the WWW. Secondly, the tools for searching databases are usually not adapted to the properties of images. HTML pages do not allow complex searches. Therefore establishing a more comfortable retrieval involves the use of a higher programming level like JAVA. With this platform independent language it is possible to create extensions to commonly used web browsers. These applets offer a graphical user interface for high level navigation. We implemented a database using JAVA objects as the primary storage container which are then stored by a JAVA controlled ORACLE8 database. Navigation depends on a structured vocabulary enhanced by a semantic network. With this approach multimedia objects can be encapsulated within a logical module for quick data retrieval.

Indexing and Retrieval for the Web.

ERIC Educational Resources Information Center

Rasmussen, Edie M.

2003-01-01

Explores current research on indexing and ranking as retrieval functions of search engines on the Web. Highlights include measuring search engine stability; evaluation of Web indexing and retrieval; Web crawlers; hyperlinks for indexing and ranking; ranking for metasearch; document structure; citation indexing; relevance; query evaluation;…

Arachne—A web-based event viewer for MINERνA

NASA Astrophysics Data System (ADS)

Tagg, N.; Brangham, J.; Chvojka, J.; Clairemont, M.; Day, M.; Eberly, B.; Felix, J.; Fields, L.; Gago, A. M.; Gran, R.; Harris, D. A.; Kordosky, M.; Lee, H.; Maggi, G.; Maher, E.; Mann, W. A.; Marshall, C. M.; McFarland, K. S.; McGowan, A. M.; Mislivec, A.; Mousseau, J.; Osmanov, B.; Osta, J.; Paolone, V.; Perdue, G.; Ransome, R. D.; Ray, H.; Schellman, H.; Schmitz, D. W.; Simon, C.; Solano Salinas, C. J.; Tice, B. G.; Walding, J.; Walton, T.; Wolcott, J.; Zhang, D.; Ziemer, B. P.; MinerνA Collaboration

2012-06-01

Neutrino interaction events in the MINERνA detector are visually represented with a web-based tool called Arachne. Data are retrieved from a central server via AJAX, and client-side JavaScript draws images into the user's browser window using the draft HTML 5 standard. These technologies allow neutrino interactions to be viewed by anyone with a web browser, allowing for easy hand-scanning of particle interactions. Arachne has been used in MINERνA to evaluate neutrino data in a prototype detector, to tune reconstruction algorithms, and for public outreach and education.

Arachne - A web-based event viewer for MINERvA

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

Tagg, N.; /Otterbein Coll.; Brangham, J.

2011-11-01

Neutrino interaction events in the MINERvA detector are visually represented with a web-based tool called Arachne. Data are retrieved from a central server via AJAX, and client-side JavaScript draws images into the user's browser window using the draft HTML 5 standard. These technologies allow neutrino interactions to be viewed by anyone with a web browser, allowing for easy hand-scanning of particle interactions. Arachne has been used in MINERvA to evaluate neutrino data in a prototype detector, to tune reconstruction algorithms, and for public outreach and education.

ChRIS--A web-based neuroimaging and informatics system for collecting, organizing, processing, visualizing and sharing of medical data.

PubMed

Pienaar, Rudolph; Rannou, Nicolas; Bernal, Jorge; Hahn, Daniel; Grant, P Ellen

2015-01-01

The utility of web browsers for general purpose computing, long anticipated, is only now coming into fruition. In this paper we present a web-based medical image data and information management software platform called ChRIS ([Boston] Children's Research Integration System). ChRIS' deep functionality allows for easy retrieval of medical image data from resources typically found in hospitals, organizes and presents information in a modern feed-like interface, provides access to a growing library of plugins that process these data - typically on a connected High Performance Compute Cluster, allows for easy data sharing between users and instances of ChRIS and provides powerful 3D visualization and real time collaboration.

Creating a classification of image types in the medical literature for visual categorization

NASA Astrophysics Data System (ADS)

Müller, Henning; Kalpathy-Cramer, Jayashree; Demner-Fushman, Dina; Antani, Sameer

2012-02-01

Content-based image retrieval (CBIR) from specialized collections has often been proposed for use in such areas as diagnostic aid, clinical decision support, and teaching. The visual retrieval from broad image collections such as teaching files, the medical literature or web images, by contrast, has not yet reached a high maturity level compared to textual information retrieval. Visual image classification into a relatively small number of classes (20-100) on the other hand, has shown to deliver good results in several benchmarks. It is, however, currently underused as a basic technology for retrieval tasks, for example, to limit the search space. Most classification schemes for medical images are focused on specific areas and consider mainly the medical image types (modalities), imaged anatomy, and view, and merge them into a single descriptor or classification hierarchy. Furthermore, they often ignore other important image types such as biological images, statistical figures, flowcharts, and diagrams that frequently occur in the biomedical literature. Most of the current classifications have also been created for radiology images, which are not the only types to be taken into account. With Open Access becoming increasingly widespread particularly in medicine, images from the biomedical literature are more easily available for use. Visual information from these images and knowledge that an image is of a specific type or medical modality could enrich retrieval. This enrichment is hampered by the lack of a commonly agreed image classification scheme. This paper presents a hierarchy for classification of biomedical illustrations with the goal of using it for visual classification and thus as a basis for retrieval. The proposed hierarchy is based on relevant parts of existing terminologies, such as the IRMA-code (Image Retrieval in Medical Applications), ad hoc classifications and hierarchies used in imageCLEF (Image retrieval task at the Cross-Language Evaluation Forum) and NLM's (National Library of Medicine) OpenI. Furtheron, mappings to NLM's MeSH (Medical Subject Headings), RSNA's RadLex (Radiological Society of North America, Radiology Lexicon), and the IRMA code are also attempted for relevant image types. Advantages derived from such hierarchical classification for medical image retrieval are being evaluated through benchmarks such as imageCLEF, and R&D systems such as NLM's OpenI. The goal is to extend this hierarchy progressively and (through adding image types occurring in the biomedical literature) to have a terminology for visual image classification based on image types distinguishable by visual means and occurring in the medical open access literature.

Social Image Tag Ranking by Two-View Learning

NASA Astrophysics Data System (ADS)

Zhuang, Jinfeng; Hoi, Steven C. H.

Tags play a central role in text-based social image retrieval and browsing. However, the tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In order to solve this problem, researchers have proposed techniques to rank the annotated tags of a social image according to their relevance to the visual content of the image. In this paper, we aim to overcome the challenge of social image tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the conventional learning approaches that usually assumes some parametric models, our method is completely data-driven and makes no assumption about the underlying models, making the proposed solution practically more effective. We formulate our method as an optimization task and present an efficient algorithm to solve it. To evaluate the efficacy of our method, we conducted an extensive set of experiments by applying our technique to both text-based social image retrieval and automatic image annotation tasks. Our empirical results showed that the proposed method can be more effective than the conventional approaches.

Storage and retrieval of digital images in dermatology.

PubMed

Bittorf, A; Krejci-Papa, N C; Diepgen, T L

1995-11-01

Differential diagnosis in dermatology relies on the interpretation of visual information in the form of clinical and histopathological images. Up until now, reference images have had to be retrieved from textbooks and/or appropriate journals. To overcome inherent limitations of those storage media with respect to the number of images stored, display, and search parameters available, we designed a computer-based database of digitized dermatologic images. Images were taken from the photo archive of the Dermatological Clinic of the University of Erlangen. A database was designed using the Entity-Relationship approach. It was implemented on a PC-Windows platform using MS Access* and MS Visual Basic®. As WWW-server a Sparc 10 workstation was used with the CERN Hypertext-Transfer-Protocol-Daemon (httpd) 3.0 pre 6 software running. For compressed storage on a hard drive, a quality factor of 60 allowed on-screen differential diagnosis and corresponded to a compression factor of 1:35 for clinical images and 1:40 for histopathological images. Hierarchical keys of clinical or histopathological criteria permitted multi-criteria searches. A script using the Common Gateway Interface (CGI) enabled remote search and image retrieval via the World-Wide-Web (W3). A dermatologic image database, featurig clinical and histopathological images was constructed which allows for multi-parameter searches and world-wide remote access.

The semantic web and computer vision: old AI meets new AI

NASA Astrophysics Data System (ADS)

Mundy, J. L.; Dong, Y.; Gilliam, A.; Wagner, R.

2018-04-01

There has been vast process in linking semantic information across the billions of web pages through the use of ontologies encoded in the Web Ontology Language (OWL) based on the Resource Description Framework (RDF). A prime example is the Wikipedia where the knowledge contained in its more than four million pages is encoded in an ontological database called DBPedia http://wiki.dbpedia.org/. Web-based query tools can retrieve semantic information from DBPedia encoded in interlinked ontologies that can be accessed using natural language. This paper will show how this vast context can be used to automate the process of querying images and other geospatial data in support of report changes in structures and activities. Computer vision algorithms are selected and provided with context based on natural language requests for monitoring and analysis. The resulting reports provide semantically linked observations from images and 3D surface models.

Distributed nuclear medicine applications using World Wide Web and Java technology.

PubMed

Knoll, P; Höll, K; Mirzaei, S; Koriska, K; Köhn, H

2000-01-01

At present, medical applications applying World Wide Web (WWW) technology are mainly used to view static images and to retrieve some information. The Java platform is a relative new way of computing, especially designed for network computing and distributed applications which enables interactive connection between user and information via the WWW. The Java 2 Software Development Kit (SDK) including Java2D API, Java Remote Method Invocation (RMI) technology, Object Serialization and the Java Advanced Imaging (JAI) extension was used to achieve a robust, platform independent and network centric solution. Medical image processing software based on this technology is presented and adequate performance capability of Java is demonstrated by an iterative reconstruction algorithm for single photon emission computerized tomography (SPECT).

Towards building high performance medical image management system for clinical trials

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel

2011-03-01

Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving images from a centralized image repository to workstations to markup and annotate images. In such environment, it is critical to provide a high performance image management system that supports efficient concurrent image retrievals in a distributed environment. There are several major challenges: high throughput of large scale image data over the Internet from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our experiments show promising results of our methods, and our work provides a guideline for building enterprise level high performance medical image management systems.

U.S. Geological Survey and Microsoft Cooperative Research and Development Agreement: Geospatial Data Browsing and Retrieval Site on the World Wide Web

USGS Publications Warehouse

,

1999-01-01

In May 1997, the U.S. Geological Survey (USGS) and the Microsoft Corporation of Redmond, Wash., entered into a cooperative research and development agreement (CRADA) to make vast amounts of geospatial data available to the general public through the Internet. The CRADA is a 36-month joint effort to develop a general, public-oriented browsing and retrieval site for geospatial data on the Internet. Specifically, Microsoft plans to (1) modify a large volume of USGS geospatial data so the images can be displayed quickly and easily over the Internet, (2) implement an easy-to-use interface for low-speed connections, and (3) develop an Internet Web site capable of servicing millions of users per day.

U.S. Geological Survey and Microsoft Cooperative Research and Development Agreement: Geospatial Data Browsing and Retrieval Site on the World Wide Web

USGS Publications Warehouse

,

1998-01-01

In May 1997, the U.S. Geological Survey (USGS) and the Microsoft Corporation of Redmond, Wash., entered into a cooperative research and development agreement (CRADA) to make vast amounts of geospatial data available to the general public through the Internet. The CRADA is a 36-month joint effort to develop a general, public-oriented browsing and retrieval site for geospatial data on the Internet. Specifically, Microsoft plans to (1) modify a large volume of USGS geospatial data so the images can be displayed quickly and easily over the Internet, (2) implement an easy-to-use interface for low-speed connections, and (3) develop an Internet Web site capable of servicing millions of users per day.

Java-based browsing, visualization and processing of heterogeneous medical data from remote repositories.

PubMed

Masseroli, M; Bonacina, S; Pinciroli, F

2004-01-01

The actual development of distributed information technologies and Java programming enables employing them also in the medical arena to support the retrieval, integration and evaluation of heterogeneous data and multimodal images in a web browser environment. With this aim, we used them to implement a client-server architecture based on software agents. The client side is a Java applet running in a web browser and providing a friendly medical user interface to browse and visualize different patient and medical test data, integrating them properly. The server side manages secure connections and queries to heterogeneous remote databases and file systems containing patient personal and clinical data. Based on the Java Advanced Imaging API, processing and analysis tools were developed to support the evaluation of remotely retrieved bioimages through the quantification of their features in different regions of interest. The Java platform-independence allows the centralized management of the implemented prototype and its deployment to each site where an intranet or internet connection is available. Giving healthcare providers effective support for comprehensively browsing, visualizing and evaluating medical images and records located in different remote repositories, the developed prototype can represent an important aid in providing more efficient diagnoses and medical treatments.

BIRD: Bio-Image Referral Database. Design and implementation of a new web based and patient multimedia data focused system for effective medical diagnosis and therapy.

PubMed

Pinciroli, Francesco; Masseroli, Marco; Acerbo, Livio A; Bonacina, Stefano; Ferrari, Roberto; Marchente, Mario

2004-01-01

This paper presents a low cost software platform prototype supporting health care personnel in retrieving patient referral multimedia data. These information are centralized in a server machine and structured by using a flexible eXtensible Markup Language (XML) Bio-Image Referral Database (BIRD). Data are distributed on demand to requesting client in an Intranet network and transformed via eXtensible Stylesheet Language (XSL) to be visualized in an uniform way on market browsers. The core server operation software has been developed in PHP Hypertext Preprocessor scripting language, which is very versatile and useful for crafting a dynamic Web environment.

A cloud-based multimodality case file for mobile devices.

PubMed

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

The peer review system (PRS) for quality assurance and treatment improvement in radiation therapy

NASA Astrophysics Data System (ADS)

Le, Anh H. T.; Kapoor, Rishabh; Palta, Jatinder R.

2012-02-01

Peer reviews are needed across all disciplines of medicine to address complex medical challenges in disease care, medical safety, insurance coverage handling, and public safety. Radiation therapy utilizes technologically advanced imaging for treatment planning, often with excellent efficacy. Since planning data requirements are substantial, patients are at risk for repeat diagnostic procedures or suboptimal therapeutic intervention due to a lack of knowledge regarding previous treatments. The Peer Review System (PRS) will make this critical radiation therapy information readily available on demand via Web technology. The PRS system has been developed with current Web technology, .NET framework, and in-house DICOM library. With the advantages of Web server-client architecture, including IIS web server, SOAP Web Services and Silverlight for the client side, the patient data can be visualized through web browser and distributed across multiple locations by the local area network and Internet. This PRS will significantly improve the quality, safety, and accessibility, of treatment plans in cancer therapy. Furthermore, the secure Web-based PRS with DICOM-RT compliance will provide flexible utilities for organization, sorting, and retrieval of imaging studies and treatment plans to optimize the patient treatment and ultimately improve patient safety and treatment quality.

WE-E-BRB-11: Riview a Web-Based Viewer for Radiotherapy.

PubMed

Apte, A; Wang, Y; Deasy, J

2012-06-01

Collaborations involving radiotherapy data collection, such as the recently proposed international radiogenomics consortium, require robust, web-based tools to facilitate reviewing treatment planning information. We present the architecture and prototype characteristics for a web-based radiotherapy viewer. The web-based environment developed in this work consists of the following components: 1) Import of DICOM/RTOG data: CERR was leveraged to import DICOM/RTOG data and to convert to database friendly RT objects. 2) Extraction and Storage of RT objects: The scan and dose distributions were stored as .png files per slice and view plane. The file locations were written to the MySQL database. Structure contours and DVH curves were written to the database as numeric data. 3) Web interfaces to query, retrieve and visualize the RT objects: The Web application was developed using HTML 5 and Ruby on Rails (RoR) technology following the MVC philosophy. The open source ImageMagick library was utilized to overlay scan, dose and structures. The application allows users to (i) QA the treatment plans associated with a study, (ii) Query and Retrieve patients matching anonymized ID and study, (iii) Review up to 4 plans simultaneously in 4 window panes (iv) Plot DVH curves for the selected structures and dose distributions. A subset of data for lung cancer patients was used to prototype the system. Five user accounts were created to have access to this study. The scans, doses, structures and DVHs for 10 patients were made available via the web application. A web-based system to facilitate QA, and support Query, Retrieve and the Visualization of RT data was prototyped. The RIVIEW system was developed using open source and free technology like MySQL and RoR. We plan to extend the RIVIEW system further to be useful in clinical trial data collection, outcomes research, cohort plan review and evaluation. © 2012 American Association of Physicists in Medicine.

A Holistic, Similarity-Based Approach for Personalized Ranking in Web Databases

ERIC Educational Resources Information Center

Telang, Aditya

2011-01-01

With the advent of the Web, the notion of "information retrieval" has acquired a completely new connotation and currently encompasses several disciplines ranging from traditional forms of text and data retrieval in unstructured and structured repositories to retrieval of static and dynamic information from the contents of the surface and deep Web.…

TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury

NASA Astrophysics Data System (ADS)

Li, Shimiao; Gong, Tianxia; Wang, Jie; Liu, Ruizhe; Tan, Chew Lim; Leong, Tze Yun; Pang, Boon Chuan; Lim, C. C. Tchoyoson; Lee, Cheng Kiang; Tian, Qi; Zhang, Zhuo

2010-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction. However, current hospital database system does not provide an efficient and intuitive tool for doctors to search out cases relevant to the current study case. In this paper, we present the TBIdoc system: a content-based image retrieval (CBIR) system which works on the TBI CT images. In this web-based system, user can query by uploading CT image slices from one study, retrieval result is a list of TBI cases ranked according to their 3D visual similarity to the query case. Specifically, cases of TBI CT images often present diffuse or focal lesions. In TBIdoc system, these pathological image features are represented as bin-based binary feature vectors. We use the Jaccard-Needham measure as the similarity measurement. Based on these, we propose a 3D similarity measure for computing the similarity score between two series of CT slices. nDCG is used to evaluate the system performance, which shows the system produces satisfactory retrieval results. The system is expected to improve the current hospital data management in TBI and to give better support for the clinical decision-making process. It may also contribute to the computer-aided education in TBI.

Medical Images Remote Consultation

NASA Astrophysics Data System (ADS)

Ferraris, Maurizio; Frixione, Paolo; Squarcia, Sandro

Teleconsultation of digital images among different medical centers is now a reality. The problem to be solved is how to interconnect all the clinical diagnostic devices in a hospital in order to allow physicians and health physicists, working in different places, to discuss on interesting clinical cases visualizing the same diagnostic images at the same time. Applying World Wide Web technologies, the proposed system can be easily used by people with no specific computer knowledge providing a verbose help to guide the user through the right steps of execution. Diagnostic images are retrieved from a relational database or from a standard DICOM-PACS through the DICOM-WWW gateway allowing connection of the usual Web browsers to DICOM applications via the HTTP protocol. The system, which is proposed for radiotherapy implementation, where radiographies play a fundamental role, can be easily converted to different field of medical applications where a remote access to secure data are compulsory.

Introduction to the JASIST Special Topic Issue on Web Retrieval and Mining: A Machine Learning Perspective.

ERIC Educational Resources Information Center

Chen, Hsinchun

2003-01-01

Discusses information retrieval techniques used on the World Wide Web. Topics include machine learning in information extraction; relevance feedback; information filtering and recommendation; text classification and text clustering; Web mining, based on data mining techniques; hyperlink structure; and Web size. (LRW)

Finding Information on the World Wide Web: The Retrieval Effectiveness of Search Engines.

ERIC Educational Resources Information Center

Pathak, Praveen; Gordon, Michael

1999-01-01

Describes a study that examined the effectiveness of eight search engines for the World Wide Web. Calculated traditional information-retrieval measures of recall and precision at varying numbers of retrieved documents to use as the bases for statistical comparisons of retrieval effectiveness. Also examined the overlap between search engines.…

Optimality of the basic colour categories for classification

PubMed Central

Griffin, Lewis D

2005-01-01

Categorization of colour has been widely studied as a window into human language and cognition, and quite separately has been used pragmatically in image-database retrieval systems. This suggests the hypothesis that the best category system for pragmatic purposes coincides with human categories (i.e. the basic colours). We have tested this hypothesis by assessing the performance of different category systems in a machine-vision task. The task was the identification of the odd-one-out from triples of images obtained using a web-based image-search service. In each triple, two of the images had been retrieved using the same search term, the other a different term. The terms were simple concrete nouns. The results were as follows: (i) the odd-one-out task can be performed better than chance using colour alone; (ii) basic colour categorization performs better than random systems of categories; (iii) a category system that performs better than the basic colours could not be found; and (iv) it is not just the general layout of the basic colours that is important, but also the detail. We conclude that (i) the results support the plausibility of an explanation for the basic colours as a result of a pressure-to-optimality and (ii) the basic colours are good categories for machine vision image-retrieval systems. PMID:16849219

Evaluation of web-based annotation of ophthalmic images for multicentric clinical trials.

PubMed

Chalam, K V; Jain, P; Shah, V A; Shah, Gaurav Y

2006-06-01

An Internet browser-based annotation system can be used to identify and describe features in digitalized retinal images, in multicentric clinical trials, in real time. In this web-based annotation system, the user employs a mouse to draw and create annotations on a transparent layer, that encapsulates the observations and interpretations of a specific image. Multiple annotation layers may be overlaid on a single image. These layers may correspond to annotations by different users on the same image or annotations of a temporal sequence of images of a disease process, over a period of time. In addition, geometrical properties of annotated figures may be computed and measured. The annotations are stored in a central repository database on a server, which can be retrieved by multiple users in real time. This system facilitates objective evaluation of digital images and comparison of double-blind readings of digital photographs, with an identifiable audit trail. Annotation of ophthalmic images allowed clinically feasible and useful interpretation to track properties of an area of fundus pathology. This provided an objective method to monitor properties of pathologies over time, an essential component of multicentric clinical trials. The annotation system also allowed users to view stereoscopic images that are stereo pairs. This web-based annotation system is useful and valuable in monitoring patient care, in multicentric clinical trials, telemedicine, teaching and routine clinical settings.

Multimedia data repository for the World Wide Web

NASA Astrophysics Data System (ADS)

Chen, Ken; Lu, Dajin; Xu, Duanyi

1998-08-01

This paper introduces the design and implementation of a Multimedia Data Repository served as a multimedia information system, which provides users a Web accessible, platform independent interface to query, browse, and retrieve multimedia data such as images, graphics, audio, video from a large multimedia data repository. By integrating the multimedia DBMS, in which the textual information and samples of the multimedia data is organized and stored, and Web server together into the Microsoft ActiveX Server Framework, users can access the DBMS and query the information by simply using a Web browser at the client-side. The original multimedia data can then be located and transmitted through the Internet from the tertiary storage device, a 400 CDROM optical jukebox at the server-side, to the client-side for further use.

Wireless remote control of clinical image workflow: using a PDA for off-site distribution and disaster recovery.

PubMed

Documet, Jorge; Liu, Brent J; Documet, Luis; Huang, H K

2006-07-01

This paper describes a picture archiving and communication system (PACS) tool based on Web technology that remotely manages medical images between a PACS archive and remote destinations. Successfully implemented in a clinical environment and also demonstrated for the past 3 years at the conferences of various organizations, including the Radiological Society of North America, this tool provides a very practical and simple way to manage a PACS, including off-site image distribution and disaster recovery. The application is robust and flexible and can be used on a standard PC workstation or a Tablet PC, but more important, it can be used with a personal digital assistant (PDA). With a PDA, the Web application becomes a powerful wireless and mobile image management tool. The application's quick and easy-to-use features allow users to perform Digital Imaging and Communications in Medicine (DICOM) queries and retrievals with a single interface, without having to worry about the underlying configuration of DICOM nodes. In addition, this frees up dedicated PACS workstations to perform their specialized roles within the PACS workflow. This tool has been used at Saint John's Health Center in Santa Monica, California, for 2 years. The average number of queries per month is 2,021, with 816 C-MOVE retrieve requests. Clinical staff members can use PDAs to manage image workflow and PACS examination distribution conveniently for off-site consultations by referring physicians and radiologists and for disaster recovery. This solution also improves radiologists' effectiveness and efficiency in health care delivery both within radiology departments and for off-site clinical coverage.

Web information retrieval based on ontology

NASA Astrophysics Data System (ADS)

Zhang, Jian

2013-03-01

The purpose of the Information Retrieval (IR) is to find a set of documents that are relevant for a specific information need of a user. Traditional Information Retrieval model commonly used in commercial search engine is based on keyword indexing system and Boolean logic queries. One big drawback of traditional information retrieval is that they typically retrieve information without an explicitly defined domain of interest to the users so that a lot of no relevance information returns to users, which burden the user to pick up useful answer from these no relevance results. In order to tackle this issue, many semantic web information retrieval models have been proposed recently. The main advantage of Semantic Web is to enhance search mechanisms with the use of Ontology's mechanisms. In this paper, we present our approach to personalize web search engine based on ontology. In addition, key techniques are also discussed in our paper. Compared to previous research, our works concentrate on the semantic similarity and the whole process including query submission and information annotation.

A neotropical Miocene pollen database employing image-based search and semantic modeling.

PubMed

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W; Jaramillo, Carlos; Shyu, Chi-Ren

2014-08-01

Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.

Information Retrieval System for Japanese Standard Disease-Code Master Using XML Web Service

PubMed Central

Hatano, Kenji; Ohe, Kazuhiko

2003-01-01

Information retrieval system of Japanese Standard Disease-Code Master Using XML Web Service is developed. XML Web Service is a new distributed processing system by standard internet technologies. With seamless remote method invocation of XML Web Service, users are able to get the latest disease code master information from their rich desktop applications or internet web sites, which refer to this service. PMID:14728364

MetaSEEk: a content-based metasearch engine for images

NASA Astrophysics Data System (ADS)

Beigi, Mandis; Benitez, Ana B.; Chang, Shih-Fu

1997-12-01

Search engines are the most powerful resources for finding information on the rapidly expanding World Wide Web (WWW). Finding the desired search engines and learning how to use them, however, can be very time consuming. The integration of such search tools enables the users to access information across the world in a transparent and efficient manner. These systems are called meta-search engines. The recent emergence of visual information retrieval (VIR) search engines on the web is leading to the same efficiency problem. This paper describes and evaluates MetaSEEk, a content-based meta-search engine used for finding images on the Web based on their visual information. MetaSEEk is designed to intelligently select and interface with multiple on-line image search engines by ranking their performance for different classes of user queries. User feedback is also integrated in the ranking refinement. We compare MetaSEEk with a base line version of meta-search engine, which does not use the past performance of the different search engines in recommending target search engines for future queries.

Remote Sensing Information Gateway: A free application and web service for fast, convenient, interoperable access to large repositories of atmospheric data

NASA Astrophysics Data System (ADS)

Plessel, T.; Szykman, J.; Freeman, M.

2012-12-01

EPA's Remote Sensing Information Gateway (RSIG) is a widely used free applet and web service for quickly and easily retrieving, visualizing and saving user-specified subsets of atmospheric data - by variable, geographic domain and time range. Petabytes of available data include thousands of variables from a set of NASA and NOAA satellites, aircraft, ground stations and EPA air-quality models. The RSIG applet is used by atmospheric researchers and uses the rsigserver web service to obtain data and images. The rsigserver web service is compliant with the Open Geospatial Consortium Web Coverage Service (OGC-WCS) standard to facilitate data discovery and interoperability. Since rsigserver is publicly accessible, it can be (and is) used by other applications. This presentation describes the architecture and technical implementation details of this successful system with an emphasis on achieving convenience, high-performance, data integrity and security.

Web information retrieval for health professionals.

PubMed

Ting, S L; See-To, Eric W K; Tse, Y K

2013-06-01

This paper presents a Web Information Retrieval System (WebIRS), which is designed to assist the healthcare professionals to obtain up-to-date medical knowledge and information via the World Wide Web (WWW). The system leverages the document classification and text summarization techniques to deliver the highly correlated medical information to the physicians. The system architecture of the proposed WebIRS is first discussed, and then a case study on an application of the proposed system in a Hong Kong medical organization is presented to illustrate the adoption process and a questionnaire is administrated to collect feedback on the operation and performance of WebIRS in comparison with conventional information retrieval in the WWW. A prototype system has been constructed and implemented on a trial basis in a medical organization. It has proven to be of benefit to healthcare professionals through its automatic functions in classification and summarizing the medical information that the physicians needed and interested. The results of the case study show that with the use of the proposed WebIRS, significant reduction of searching time and effort, with retrieval of highly relevant materials can be attained.

Exploring access to scientific literature using content-based image retrieval

NASA Astrophysics Data System (ADS)

Deserno, Thomas M.; Antani, Sameer; Long, Rodney

2007-03-01

The number of articles published in the scientific medical literature is continuously increasing, and Web access to the journals is becoming common. Databases such as SPIE Digital Library, IEEE Xplore, indices such as PubMed, and search engines such as Google provide the user with sophisticated full-text search capabilities. However, information in images and graphs within these articles is entirely disregarded. In this paper, we quantify the potential impact of using content-based image retrieval (CBIR) to access this non-text data. Based on the Journal Citations Report (JCR), the journal Radiology was selected for this study. In 2005, 734 articles were published electronically in this journal. This included 2,587 figures, which yields a rate of 3.52 figures per article. Furthermore, 56.4% of these figures are composed of several individual panels, i.e. the figure combines different images and/or graphs. According to the Image Cross-Language Evaluation Forum (ImageCLEF), the error rate of automatic identification of medical images is about 15%. Therefore, it is expected that, by applying ImageCLEF-like techniques, already 95.5% of articles could be retrieved by means of CBIR. The challenge for CBIR in scientific literature, however, is the use of local texture properties to analyze individual image panels in composite illustrations. Using local features for content-based image representation, 8.81 images per article are available, and the predicted correctness rate may increase to 98.3%. From this study, we conclude that CBIR may have a high impact in medical literature research and suggest that additional research in this area is warranted.

yourSky: Custom Sky-Image Mosaics via the Internet

NASA Technical Reports Server (NTRS)

Jacob, Joseph

2003-01-01

yourSky (http://yourSky.jpl.nasa.gov) is a computer program that supplies custom astronomical image mosaics of sky regions specified by requesters using client computers connected to the Internet. [yourSky is an upgraded version of the software reported in Software for Generating Mosaics of Astronomical Images (NPO-21121), NASA Tech Briefs, Vol. 25, No. 4 (April 2001), page 16a.] A requester no longer has to engage in the tedious process of determining what subset of images is needed, nor even to know how the images are indexed in image archives. Instead, in response to a requester s specification of the size and location of the sky area, (and optionally of the desired set and type of data, resolution, coordinate system, projection, and image format), yourSky automatically retrieves the component image data from archives totaling tens of terabytes stored on computer tape and disk drives at multiple sites and assembles the component images into a mosaic image by use of a high-performance parallel code. yourSky runs on the server computer where the mosaics are assembled. Because yourSky includes a Web-interface component, no special client software is needed: ordinary Web browser software is sufficient.

Handwritten-word spotting using biologically inspired features.

PubMed

van der Zant, Tijn; Schomaker, Lambert; Haak, Koen

2008-11-01

For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language and collection. We propose a biologically inspired whole-word recognition method which is used to incrementally elicit word labels in a live, web-based annotation system, named Monk. Since human labor should be minimized given the massive amount of image data, it becomes important to rely on robust perceptual mechanisms in the machine. Recent computational models of the neuro-physiology of vision are applied to isolated word classification. A primate cortex-like mechanism allows to classify text-images that have a low frequency of occurrence. Typically these images are the most difficult to retrieve and often contain named entities and are regarded as the most important to people. Usually standard pattern-recognition technology cannot deal with these text-images if there are not enough labeled instances. The results of this retrieval system are compared to normalized word-image matching and appear to be very promising.

Engineering a Multi-Purpose Test Collection for Web Retrieval Experiments.

ERIC Educational Resources Information Center

Bailey, Peter; Craswell, Nick; Hawking, David

2003-01-01

Describes a test collection that was developed as a multi-purpose testbed for experiments on the Web in distributed information retrieval, hyperlink algorithms, and conventional ad hoc retrieval. Discusses inter-server connectivity, integrity of server holdings, inclusion of documents related to a wide spread of likely queries, and distribution of…

Towards an Intelligent Possibilistic Web Information Retrieval Using Multiagent System

ERIC Educational Resources Information Center

Elayeb, Bilel; Evrard, Fabrice; Zaghdoud, Montaceur; Ahmed, Mohamed Ben

2009-01-01

Purpose: The purpose of this paper is to make a scientific contribution to web information retrieval (IR). Design/methodology/approach: A multiagent system for web IR is proposed based on new technologies: Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). This system is based on a possibilistic qualitative approach which extends the…

Millennial Undergraduate Research Strategies in Web and Library Information Retrieval Systems

ERIC Educational Resources Information Center

Porter, Brandi

2011-01-01

This article summarizes the author's dissertation regarding search strategies of millennial undergraduate students in Web and library online information retrieval systems. Millennials bring a unique set of search characteristics and strategies to their research since they have never known a world without the Web. Through the use of search engines,…

Storage and distribution of pathology digital images using integrated web-based viewing systems.

PubMed

Marchevsky, Alberto M; Dulbandzhyan, Ronda; Seely, Kevin; Carey, Steve; Duncan, Raymond G

2002-05-01

Health care providers have expressed increasing interest in incorporating digital images of gross pathology specimens and photomicrographs in routine pathology reports. To describe the multiple technical and logistical challenges involved in the integration of the various components needed for the development of a system for integrated Web-based viewing, storage, and distribution of digital images in a large health system. An Oracle version 8.1.6 database was developed to store, index, and deploy pathology digital photographs via our Intranet. The database allows for retrieval of images by patient demographics or by SNOMED code information. The Intranet of a large health system accessible from multiple computers located within the medical center and at distant private physician offices. The images can be viewed using any of the workstations of the health system that have authorized access to our Intranet, using a standard browser or a browser configured with an external viewer or inexpensive plug-in software, such as Prizm 2.0. The images can be printed on paper or transferred to film using a digital film recorder. Digital images can also be displayed at pathology conferences by using wireless local area network (LAN) and secure remote technologies. The standardization of technologies and the adoption of a Web interface for all our computer systems allows us to distribute digital images from a pathology database to a potentially large group of users distributed in multiple locations throughout a large medical center.

A neotropical Miocene pollen database employing image-based search and semantic modeling1

PubMed Central

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W.; Jaramillo, Carlos; Shyu, Chi-Ren

2014-01-01

• Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. PMID:25202648

Comparison of quality of internet pages on human papillomavirus immunization in Italian and in English.

PubMed

Tozzi, Alberto Eugenio; Buonuomo, Paola Sabrina; Ciofi degli Atti, Marta Luisa; Carloni, Emanuela; Meloni, Marco; Gamba, Fiorenza

2010-01-01

Information available on the Internet about immunizations may influence parents' perception about human papillomavirus (HPV) immunization and their attitude toward vaccinating their daughters. We hypothesized that the quality of information on HPV available on the Internet may vary with language and with the level of knowledge of parents. To this end we compared the quality of a sample of Web pages in Italian with a sample of Web pages in English. Five reviewers assessed the quality of Web pages retrieved with popular search engines using criteria adapted from the Good Information Practice Essential Criteria for Vaccine Safety Web Sites recommended by the World Health Organization. Quality of Web pages was assessed in the domains of accessibility, credibility, content, and design. Scores in these domains were compared through nonparametric statistical tests. We retrieved and reviewed 74 Web sites in Italian and 117 in English. Most retrieved Web pages (33.5%) were from private agencies. Median scores were higher in Web pages in English compared with those in Italian in the domain of accessibility (p < .01), credibility (p < .01), and content (p < .01). The highest credibility and content scores were those of Web pages from governmental agencies or universities. Accessibility scores were positively associated with content scores (p < .01) and with credibility scores (p < .01). A total of 16.2% of Web pages in Italian opposed HPV immunization compared with 6.0% of those in English (p < .05). Quality of information and number of Web pages opposing HPV immunization may vary with the Web site language. High-quality Web pages on HPV, especially from public health agencies and universities, should be easily accessible and retrievable with common Web search engines. Copyright 2010 Society for Adolescent Medicine. Published by Elsevier Inc. All rights reserved.

VizieR Online Data Catalog: UV and IR properties for galaxies (Mao+, 2014)

NASA Astrophysics Data System (ADS)

Mao, Y.-W.; Kong, X.; Lin, L.

2017-03-01

Broadband FUV and NUV imaging data were obtained from GALEX observations and downloaded from the Multimission Archive at Space Telescope Science Institute (MAST) Web site (http://galex.stsci.edu/); 8um (dust-only) and 24um images were observed by the Spitzer Space Telescope (Spitzer) and retrieved from the SINGS data distribution service (http://irsa.ipac.caltech.edu/data/SPITZER/SINGS/). Hα narrowband imaging data are also employed in this work. The Hα narrowband image for NGC 3031 was observed by the 60/90 cm Schmidt telescope at Xing-Long station of the National Astronomical Observatories of China with the filter of transmission profile FWHM~120Å. (2 data files).

How To Succeed in Promoting Your Web Site: The Impact of Search Engine Registration on Retrieval of a World Wide Web Site.

ERIC Educational Resources Information Center

Tunender, Heather; Ervin, Jane

1998-01-01

Character strings were planted in a World Wide Web site (Project Whistlestop) to test indexing and retrieval rates of five Web search tools (Lycos, infoseek, AltaVista, Yahoo, Excite). It was found that search tools indexed few of the planted character strings, none indexed the META descriptor tag, and only Excite indexed into the 3rd-4th site…

Design of a web portal for interdisciplinary image retrieval from multiple online image resources.

PubMed

Kammerer, F J; Frankewitsch, T; Prokosch, H-U

2009-01-01

Images play an important role in medicine. Finding the desired images within the multitude of online image databases is a time-consuming and frustrating process. Existing websites do not meet all the requirements for an ideal learning environment for medical students. This work intends to establish a new web portal providing a centralized access point to a selected number of online image databases. A back-end system locates images on given websites and extracts relevant metadata. The images are indexed using UMLS and the MetaMap system provided by the US National Library of Medicine. Specially developed functions allow to create individual navigation structures. The front-end system suits the specific needs of medical students. A navigation structure consisting of several medical fields, university curricula and the ICD-10 was created. The images may be accessed via the given navigation structure or using different search functions. Cross-references are provided by the semantic relations of the UMLS. Over 25,000 images were identified and indexed. A pilot evaluation among medical students showed good first results concerning the acceptance of the developed navigation structures and search features. The integration of the images from different sources into the UMLS semantic network offers a quick and an easy-to-use learning environment.

Wormhole: A Powerful Data Mashup

NASA Technical Reports Server (NTRS)

Widen, David

2011-01-01

The mobile platform is quickly becoming the standard way that users interact with online resources. The iOS operating system allows iPhone and iPad users to seamlessly access highly interactive web applications that until recently were only available via a desktop or laptop. Wormhole is an AJAX application implemented as a smart web widget that allows users to easily supplement web pages with data directly from the Instrument Operations Subsystems division (IOS) at JPL. It creates an interactive mashup using a website's core content enhanced by dynamically retrieved image and metadata supplied by IOS using the webification API. Currently, this technology is limited in scope to NASA data; however, it can easily be augmented to serve many other needs. This web widget can be delivered in various ways, including as a bookmarklet. The underlying technology that powers Wormhole also has applications to other divisions while they are running current missions.

Network and User-Perceived Performance of Web Page Retrievals

NASA Technical Reports Server (NTRS)

Kruse, Hans; Allman, Mark; Mallasch, Paul

1998-01-01

The development of the HTTP protocol has been driven by the need to improve the network performance of the protocol by allowing the efficient retrieval of multiple parts of a web page without the need for multiple simultaneous TCP connections between a client and a server. We suggest that the retrieval of multiple page elements sequentially over a single TCP connection may result in a degradation of the perceived performance experienced by the user. We attempt to quantify this perceived degradation through the use of a model which combines a web retrieval simulation and an analytical model of TCP operation. Starting with the current HTTP/l.1 specification, we first suggest a client@side heuristic to improve the perceived transfer performance. We show that the perceived speed of the page retrieval can be increased without sacrificing data transfer efficiency. We then propose a new client/server extension to the HTTP/l.1 protocol to allow for the interleaving of page element retrievals. We finally address the issue of the display of advertisements on web pages, and in particular suggest a number of mechanisms which can make efficient use of IP multicast to send advertisements to a number of clients within the same network.

Information Retrieval for Education: Making Search Engines Language Aware

ERIC Educational Resources Information Center

Ott, Niels; Meurers, Detmar

2010-01-01

Search engines have been a major factor in making the web the successful and widely used information source it is today. Generally speaking, they make it possible to retrieve web pages on a topic specified by the keywords entered by the user. Yet web searching currently does not take into account which of the search results are comprehensible for…

Automated MeSH indexing of the World-Wide Web.

PubMed Central

Fowler, J.; Kouramajian, V.; Maram, S.; Devadhar, V.

1995-01-01

To facilitate networked discovery and information retrieval in the biomedical domain, we have designed a system for automatic assignment of Medical Subject Headings to documents retrieved from the World-Wide Web. Our prototype implementations show significant promise. We describe our methods and discuss the further development of a completely automated indexing tool called the "Web-MeSH Medibot." PMID:8563421

Deep learning application: rubbish classification with aid of an android device

NASA Astrophysics Data System (ADS)

Liu, Sijiang; Jiang, Bo; Zhan, Jie

2017-06-01

Deep learning is a very hot topic currently in pattern recognition and artificial intelligence researches. Aiming at the practical problem that people usually don't know correct classifications some rubbish should belong to, based on the powerful image classification ability of the deep learning method, we have designed a prototype system to help users to classify kinds of rubbish. Firstly the CaffeNet Model was adopted for our classification network training on the ImageNet dataset, and the trained network was deployed on a web server. Secondly an android app was developed for users to capture images of unclassified rubbish, upload images to the web server for analyzing backstage and retrieve the feedback, so that users can obtain the classification guide by an android device conveniently. Tests on our prototype system of rubbish classification show that: an image of one single type of rubbish with origin shape can be better used to judge its classification, while an image containing kinds of rubbish or rubbish with changed shape may fail to help users to decide rubbish's classification. However, the system still shows promising auxiliary function for rubbish classification if the network training strategy can be optimized further.

CD-based image archival and management on a hybrid radiology intranet.

PubMed

Cox, R D; Henri, C J; Bret, P M

1997-08-01

This article describes the design and implementation of a low-cost image archival and management solution on a radiology network consisting of UNIX, IBM personal computer-compatible (IBM, Purchase, NY) and Macintosh (Apple Computer, Cupertino, CA) workstations. The picture archiving and communications system (PACS) is modular, scaleable and conforms to the Digital Imaging and Communications in Medicine (DICOM) 3.0 standard for image transfer, storage and retrieval. Image data is made available on soft-copy reporting workstations by a work-flow management scheme and on desktop computers through a World Wide Web (WWW) interface. Data archival is based on recordable compact disc (CD) technology and is automated. The project has allowed the radiology department to eliminate the use of film in magnetic resonance (MR) imaging, computed tomography (CT) and ultrasonography.

Mining and integration of pathway diagrams from imaging data.

PubMed

Kozhenkov, Sergey; Baitaluk, Michael

2012-03-01

Pathway diagrams from PubMed and World Wide Web (WWW) contain valuable highly curated information difficult to reach without tools specifically designed and customized for the biological semantics and high-content density of the images. There is currently no search engine or tool that can analyze pathway images, extract their pathway components (molecules, genes, proteins, organelles, cells, organs, etc.) and indicate their relationships. Here, we describe a resource of pathway diagrams retrieved from article and web-page images through optical character recognition, in conjunction with data mining and data integration methods. The recognized pathways are integrated into the BiologicalNetworks research environment linking them to a wealth of data available in the BiologicalNetworks' knowledgebase, which integrates data from >100 public data sources and the biomedical literature. Multiple search and analytical tools are available that allow the recognized cellular pathways, molecular networks and cell/tissue/organ diagrams to be studied in the context of integrated knowledge, experimental data and the literature. BiologicalNetworks software and the pathway repository are freely available at www.biologicalnetworks.org. Supplementary data are available at Bioinformatics online.

In-house access to PACS images and related data through World Wide Web

NASA Astrophysics Data System (ADS)

Mascarini, Christian; Ratib, Osman M.; Trayser, Gerhard; Ligier, Yves; Appel, R. D.

1996-05-01

The development of a hospital wide PACS is in progress at the University Hospital of Geneva and several archive modules are operational since 1992. This PACS is intended for wide distribution of images to clinical wards. As the PACS project and the number of archived images grow rapidly in the hospital, it was necessary to provide an easy, more widely accessible and convenient access to the PACS database for the clinicians in the different wards and clinical units of the hospital. An innovative solution has been developed using tools such as Netscape navigator and NCSA World Wide Web server as an alternative to conventional database query and retrieval software. These tools present the advantages of providing an user interface which is the same independently of the platform being used (Mac, Windows, UNIX, ...), and an easy integration of different types of documents (text, images, ...). A strict access control has been added to this interface. It allows user identification and access rights checking, as defined by the in-house hospital information system, before allowing the navigation through patient data records.

Line-based logo recognition through a web-camera

NASA Astrophysics Data System (ADS)

Chen, Xiaolu; Wang, Yangsheng; Feng, Xuetao

2007-11-01

Logo recognition has gained much development in the document retrieval and shape analysis domain. As human computer interaction becomes more and more popular, the logo recognition through a web-camera is a promising technology in view of application. But for practical application, the study of logo recognition in real scene is much more difficult than the work in clear scene. To cope with the need, we make some improvements on conventional method. First, moment information is used to calculate the test image's orientation angle, which is used to normalize the test image. Second, the main structure of the test image, which is represented by lines patterns, is acquired and modified Hausdorff distance is employed to match the image and each of the existing templates. The proposed method, which is invariant to scale and rotation, gives good result and can work at real-time. The main contribution of this paper is that some improvements are introduced into the exiting recognition framework which performs much better than the original one. Besides, we have built a highly successful logo recognition system using our improved method.

An architecture for diversity-aware search for medical web content.

PubMed

Denecke, K

2012-01-01

The Web provides a huge source of information, also on medical and health-related issues. In particular the content of medical social media data can be diverse due to the background of an author, the source or the topic. Diversity in this context means that a document covers different aspects of a topic or a topic is described in different ways. In this paper, we introduce an approach that allows to consider the diverse aspects of a search query when providing retrieval results to a user. We introduce a system architecture for a diversity-aware search engine that allows retrieving medical information from the web. The diversity of retrieval results is assessed by calculating diversity measures that rely upon semantic information derived from a mapping to concepts of a medical terminology. Considering these measures, the result set is diversified by ranking more diverse texts higher. The methods and system architecture are implemented in a retrieval engine for medical web content. The diversity measures reflect the diversity of aspects considered in a text and its type of information content. They are used for result presentation, filtering and ranking. In a user evaluation we assess the user satisfaction with an ordering of retrieval results that considers the diversity measures. It is shown through the evaluation that diversity-aware retrieval considering diversity measures in ranking could increase the user satisfaction with retrieval results.

Engineering Analysis Using a Web-based Protocol

NASA Technical Reports Server (NTRS)

Schoeffler, James D.; Claus, Russell W.

2002-01-01

This paper reviews the development of a web-based framework for engineering analysis. A one-dimensional, high-speed analysis code called LAPIN was used in this study, but the approach can be generalized to any engineering analysis tool. The web-based framework enables users to store, retrieve, and execute an engineering analysis from a standard web-browser. We review the encapsulation of the engineering data into the eXtensible Markup Language (XML) and various design considerations in the storage and retrieval of application data.

Secure Display of Space-Exploration Images

NASA Technical Reports Server (NTRS)

Cheng, Cecilia; Thornhill, Gillian; McAuley, Michael

2006-01-01

Java EDR Display Interface (JEDI) is software for either local display or secure Internet distribution, to authorized clients, of image data acquired from cameras aboard spacecraft engaged in exploration of remote planets. ( EDR signifies experimental data record, which, in effect, signifies image data.) Processed at NASA s Multimission Image Processing Laboratory (MIPL), the data can be from either near-realtime processing streams or stored files. JEDI uses the Java Advanced Imaging application program interface, plus input/output packages that are parts of the Video Image Communication and Retrieval software of the MIPL, to display images. JEDI can be run as either a standalone application program or within a Web browser as a servlet with an applet front end. In either operating mode, JEDI communicates using the HTTP(s) protocol(s). In the Web-browser case, the user must provide a password to gain access. For each user and/or image data type, there is a configuration file, called a "personality file," containing parameters that control the layout of the displays and the information to be included in them. Once JEDI has accepted the user s password, it processes the requested EDR (provided that user is authorized to receive the specific EDR) to create a display according to the user s personality file.

Beyond the electronic textbook model: software techniques to make on-line educational content dynamic.

PubMed

Frank, M S; Dreyer, K

2001-06-01

We describe a working software technology that enables educators to incorporate their expertise and teaching style into highly interactive and Socratic educational material for distribution on the world wide web. A graphically oriented interactive authoring system was developed to enable the computer novice to create and store within a database his or her domain expertise in the form of electronic knowledge. The authoring system supports and facilitates the input and integration of several types of content, including free-form, stylized text, miniature and full-sized images, audio, and interactive questions with immediate feedback. The system enables the choreography and sequencing of these entities for display within a web page as well as the sequencing of entire web pages within a case-based or thematic presentation. Images or segments of text can be hyperlinked with point-and-click to other entities such as adjunctive web pages, audio, or other images, cases, or electronic chapters. Miniature (thumbnail) images are automatically linked to their full-sized counterparts. The authoring system contains a graphically oriented word processor, an image editor, and capabilities to automatically invoke and use external image-editing software such as Photoshop. The system works in both local area network (LAN) and internet-centric environments. An internal metalanguage (invisible to the author but stored with the content) was invented to represent the choreographic directives that specify the interactive delivery of the content on the world wide web. A database schema was developed to objectify and store both this electronic knowledge and its associated choreographic metalanguage. A database engine was combined with page-rendering algorithms in order to retrieve content from the database and deliver it on the web in a Socratic style, assess the recipient's current fund of knowledge, and provide immediate feedback, thus stimulating in-person interaction with a human expert. This technology enables the educator to choreograph a stylized, interactive delivery of his or her message using multimedia components assembled in virtually any order, spanning any number of web pages for a given case or theme. An educator can thus exercise precise influence on specific learning objectives, embody his or her personal teaching style within the content, and ultimately enhance its educational impact. The described technology amplifies the efforts of the educator and provides a more dynamic and enriching learning environment for web-based education.

A novel architecture for information retrieval system based on semantic web

NASA Astrophysics Data System (ADS)

Zhang, Hui

2011-12-01

Nowadays, the web has enabled an explosive growth of information sharing (there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhead. The challenge that is now before us is not only to help people locating relevant information precisely but also to access and aggregate a variety of information from different resources automatically. Current web document are in human-oriented formats and they are suitable for the presentation, but machines cannot understand the meaning of document. To address this issue, Berners-Lee proposed a concept of semantic web. With semantic web technology, web information can be understood and processed by machine. It provides new possibilities for automatic web information processing. A main problem of semantic web information retrieval is that when these is not enough knowledge to such information retrieval system, the system will return to a large of no sense result to uses due to a huge amount of information results. In this paper, we present the architecture of information based on semantic web. In addiction, our systems employ the inference Engine to check whether the query should pose to Keyword-based Search Engine or should pose to the Semantic Search Engine.

Adopting and adapting a commercial view of web services for the Navy

NASA Astrophysics Data System (ADS)

Warner, Elizabeth; Ladner, Roy; Katikaneni, Uday; Petry, Fred

2005-05-01

Web Services are being adopted as the enabling technology to provide net-centric capabilities for many Department of Defense operations. The Navy Enterprise Portal, for example, is Web Services-based, and the Department of the Navy is promulgating guidance for developing Web Services. Web Services, however, only constitute a baseline specification that provides the foundation on which users, under current approaches, write specialized applications in order to retrieve data over the Internet. Application development may increase dramatically as the number of different available Web Services increases. Reasons for specialized application development include XML schema versioning differences, adoption/use of diverse business rules, security access issues, and time/parameter naming constraints, among others. We are currently developing for the US Navy a system which will improve delivery of timely and relevant meteorological and oceanographic (MetOc) data to the warfighter. Our objective is to develop an Advanced MetOc Broker (AMB) that leverages Web Services technology to identify, retrieve and integrate relevant MetOc data in an automated manner. The AMB will utilize a Mediator, which will be developed by applying ontological research and schema matching techniques to MetOc forms of data. The AMB, using the Mediator, will support a new, advanced approach to the use of Web Services; namely, the automated identification, retrieval and integration of MetOc data. Systems based on this approach will then not require extensive end-user application development for each Web Service from which data can be retrieved. Users anywhere on the globe will be able to receive timely environmental data that fits their particular needs.

The Comprehensive Microbial Resource.

PubMed

Peterson, J D; Umayam, L A; Dickinson, T; Hickey, E K; White, O

2001-01-01

One challenge presented by large-scale genome sequencing efforts is effective display of uniform information to the scientific community. The Comprehensive Microbial Resource (CMR) contains robust annotation of all complete microbial genomes and allows for a wide variety of data retrievals. The bacterial information has been placed on the Web at http://www.tigr.org/CMR for retrieval using standard web browsing technology. Retrievals can be based on protein properties such as molecular weight or hydrophobicity, GC-content, functional role assignments and taxonomy. The CMR also has special web-based tools to allow data mining using pre-run homology searches, whole genome dot-plots, batch downloading and traversal across genomes using a variety of datatypes.

The research and implementation of coalfield spontaneous combustion of carbon emission WebGIS based on Silverlight and ArcGIS server

NASA Astrophysics Data System (ADS)

Zhu, Z.; Bi, J.; Wang, X.; Zhu, W.

2014-02-01

As an important sub-topic of the natural process of carbon emission data public information platform construction, coalfield spontaneous combustion of carbon emission WebGIS system has become an important study object. In connection with data features of coalfield spontaneous combustion carbon emissions (i.e. a wide range of data, which is rich and complex) and the geospatial characteristics, data is divided into attribute data and spatial data. Based on full analysis of the data, completed the detailed design of the Oracle database and stored on the Oracle database. Through Silverlight rich client technology and the expansion of WCF services, achieved the attribute data of web dynamic query, retrieval, statistical, analysis and other functions. For spatial data, we take advantage of ArcGIS Server and Silverlight-based API to invoke GIS server background published map services, GP services, Image services and other services, implemented coalfield spontaneous combustion of remote sensing image data and web map data display, data analysis, thematic map production. The study found that the Silverlight technology, based on rich client and object-oriented framework for WCF service, can efficiently constructed a WebGIS system. And then, combined with ArcGIS Silverlight API to achieve interactive query attribute data and spatial data of coalfield spontaneous emmission, can greatly improve the performance of WebGIS system. At the same time, it provided a strong guarantee for the construction of public information on China's carbon emission data.

Optimising web site designs for people with learning disabilities

PubMed Central

Williams, Peter; Hennig, Christian

2015-01-01

Much relevant internet-mediated information is inaccessible to people with learning disabilities because of difficulties in navigating the web. This paper reports on the methods undertaken to determine how information can be optimally presented for this cohort. Qualitative work is outlined where attributes relating to site layout affecting usability were elicited. A study comparing web sites of different design layouts exhibiting these attributes is discussed, with the emphasis on methodology. Eight interfaces were compared using various combinations of menu position (vertical or horizontal), text size and the absence or presence of images to determine which attributes of a site have the greatest performance impact. Study participants were also asked for their preferences, via a ‘smiley-face’ rating scale and simple interviews. ‘Acquiescence bias’ was minimised by avoiding polar (‘yes/no’) interrogatives, achieved by asking participants to compare layouts (such as horizontal versus vertical menu), with reasons coaxed from those able to articulate them. Preferred designs were for large text and images. This was the reverse of those facilitating fastest retrieval times, a discrepancy due to preferences being judged on aesthetic considerations. Design recommendations that reconcile preference and performance findings are offered. These include using a horizontal menu, juxtaposing images and text, and reducing text from sentences to phrases, thus facilitating preferred large text without increasing task times. PMID:26097431

A semantically-aided architecture for a web-based monitoring system for carotid atherosclerosis.

PubMed

Kolias, Vassileios D; Stamou, Giorgos; Golemati, Spyretta; Stoitsis, Giannis; Gkekas, Christos D; Liapis, Christos D; Nikita, Konstantina S

2015-08-01

Carotid atherosclerosis is a multifactorial disease and its clinical diagnosis depends on the evaluation of heterogeneous clinical data, such as imaging exams, biochemical tests and the patient's clinical history. The lack of interoperability between Health Information Systems (HIS) does not allow the physicians to acquire all the necessary data for the diagnostic process. In this paper, a semantically-aided architecture is proposed for a web-based monitoring system for carotid atherosclerosis that is able to gather and unify heterogeneous data with the use of an ontology and to create a common interface for data access enhancing the interoperability of HIS. The architecture is based on an application ontology of carotid atherosclerosis that is used to (a) integrate heterogeneous data sources on the basis of semantic representation and ontological reasoning and (b) access the critical information using SPARQL query rewriting and ontology-based data access services. The architecture was tested over a carotid atherosclerosis dataset consisting of the imaging exams and the clinical profile of 233 patients, using a set of complex queries, constructed by the physicians. The proposed architecture was evaluated with respect to the complexity of the queries that the physicians could make and the retrieval speed. The proposed architecture gave promising results in terms of interoperability, data integration of heterogeneous sources with an ontological way and expanded capabilities of query and retrieval in HIS.

Into the Dark Domain: The UK Web Archive as a Source for the Contemporary History of Public Health

PubMed Central

Gorsky, Martin

2015-01-01

With the migration of the written record from paper to digital format, archivists and historians must urgently consider how web content should be conserved, retrieved and analysed. The British Library has recently acquired a large number of UK domain websites, captured 1996–2010, which is colloquially termed the Dark Domain Archive while technical issues surrounding user access are resolved. This article reports the results of an invited pilot project that explores methodological issues surrounding use of this archive. It asks how the relationship between UK public health and local government was represented on the web, drawing on the ‘declinist’ historiography to frame its questions. It points up some difficulties in developing an aggregate picture of web content due to duplication of sites. It also highlights their potential for thematic and discourse analysis, using both text and image, illustrated through an argument about the contradictory rationale for public health policy under New Labour. PMID:26217072

Sources and Resources Into the Dark Domain: The UK Web Archive as a Source for the Contemporary History of Public Health.

PubMed

Gorsky, Martin

2015-08-01

With the migration of the written record from paper to digital format, archivists and historians must urgently consider how web content should be conserved, retrieved and analysed. The British Library has recently acquired a large number of UK domain websites, captured 1996-2010, which is colloquially termed the Dark Domain Archive while technical issues surrounding user access are resolved. This article reports the results of an invited pilot project that explores methodological issues surrounding use of this archive. It asks how the relationship between UK public health and local government was represented on the web, drawing on the 'declinist' historiography to frame its questions. It points up some difficulties in developing an aggregate picture of web content due to duplication of sites. It also highlights their potential for thematic and discourse analysis, using both text and image, illustrated through an argument about the contradictory rationale for public health policy under New Labour.

The Comprehensive Microbial Resource

PubMed Central

Peterson, Jeremy D.; Umayam, Lowell A.; Dickinson, Tanja; Hickey, Erin K.; White, Owen

2001-01-01

One challenge presented by large-scale genome sequencing efforts is effective display of uniform information to the scientific community. The Comprehensive Microbial Resource (CMR) contains robust annotation of all complete microbial genomes and allows for a wide variety of data retrievals. The bacterial information has been placed on the Web at http://www.tigr.org/CMR for retrieval using standard web browsing technology. Retrievals can be based on protein properties such as molecular weight or hydrophobicity, GC-content, functional role assignments and taxonomy. The CMR also has special web-based tools to allow data mining using pre-run homology searches, whole genome dot-plots, batch downloading and traversal across genomes using a variety of datatypes. PMID:11125067

Virtual Global Magnetic Observatory - Concept and Implementation

NASA Astrophysics Data System (ADS)

Papitashvili, V.; Clauer, R.; Petrov, V.; Saxena, A.

2002-12-01

The existing World Data Centers (WDC) continue to serve excellently the worldwide scientific community in providing free access to a huge number of global geophysical databases. Various institutions at different geographic locations house these Centers, mainly organized by a scientific discipline. However, population of the Centers requires mandatory or voluntary submission of locally collected data. Recently many digital geomagnetic datasets have been placed on the World Wide Web and some of these sets have not been even submitted to any data center. This has created an urgent need for more sophisticated search engines capable of identifying geomagnetic data on the Web and then retrieving a certain amount of data for the scientific analysis. In this study, we formulate a concept of the virtual global magnetic observatory (VGMO) that currently uses a pre-set list of the Web-based geomagnetic data holders (including WDC) as retrieving a requested case-study interval. Saving the retrieved data locally over the multiple requests, a VGMO user begins to build his/her own data sub-center, which does not need to search the Web if the newly requested interval will be within a span of the earlier retrieved data. At the same time, this self-populated sub-center becomes available to other VGMO users down on the requests chain. Some aspects of the Web``crawling'' helping to identify the newly ``webbed'' digital geomagnetic data are also considered.

CERES Web Links

Atmospheric Science Data Center

2013-03-21

...   Web Links to Relevant CERES Information Relevant information about CERES, CERES references, ... Instrument Working Group Home Page Aerosol Retrieval Web Page  (Center for Satellite Applications and Research) ...

Information Retrieval Strategies of Millennial Undergraduate Students in Web and Library Database Searches

ERIC Educational Resources Information Center

Porter, Brandi

2009-01-01

Millennial students make up a large portion of undergraduate students attending colleges and universities, and they have a variety of online resources available to them to complete academically related information searches, primarily Web based and library-based online information retrieval systems. The content, ease of use, and required search…

Using the web to validate document recognition results: experiments with business cards

NASA Astrophysics Data System (ADS)

Oertel, Clemens; O'Shea, Shauna; Bodnar, Adam; Blostein, Dorothea

2004-12-01

The World Wide Web is a vast information resource which can be useful for validating the results produced by document recognizers. Three computational steps are involved, all of them challenging: (1) use the recognition results in a Web search to retrieve Web pages that contain information similar to that in the document, (2) identify the relevant portions of the retrieved Web pages, and (3) analyze these relevant portions to determine what corrections (if any) should be made to the recognition result. We have conducted exploratory implementations of steps (1) and (2) in the business-card domain: we use fields of the business card to retrieve Web pages and identify the most relevant portions of those Web pages. In some cases, this information appears suitable for correcting OCR errors in the business card fields. In other cases, the approach fails due to stale information: when business cards are several years old and the business-card holder has changed jobs, then websites (such as the home page or company website) no longer contain information matching that on the business card. Our exploratory results indicate that in some domains it may be possible to develop effective means of querying the Web with recognition results, and to use this information to correct the recognition results and/or detect that the information is stale.

Using the web to validate document recognition results: experiments with business cards

NASA Astrophysics Data System (ADS)

Oertel, Clemens; O'Shea, Shauna; Bodnar, Adam; Blostein, Dorothea

2005-01-01

The World Wide Web is a vast information resource which can be useful for validating the results produced by document recognizers. Three computational steps are involved, all of them challenging: (1) use the recognition results in a Web search to retrieve Web pages that contain information similar to that in the document, (2) identify the relevant portions of the retrieved Web pages, and (3) analyze these relevant portions to determine what corrections (if any) should be made to the recognition result. We have conducted exploratory implementations of steps (1) and (2) in the business-card domain: we use fields of the business card to retrieve Web pages and identify the most relevant portions of those Web pages. In some cases, this information appears suitable for correcting OCR errors in the business card fields. In other cases, the approach fails due to stale information: when business cards are several years old and the business-card holder has changed jobs, then websites (such as the home page or company website) no longer contain information matching that on the business card. Our exploratory results indicate that in some domains it may be possible to develop effective means of querying the Web with recognition results, and to use this information to correct the recognition results and/or detect that the information is stale.

Font adaptive word indexing of modern printed documents.

PubMed

Marinai, Simone; Marino, Emanuele; Soda, Giovanni

2006-08-01

We propose an approach for the word-level indexing of modern printed documents which are difficult to recognize using current OCR engines. By means of word-level indexing, it is possible to retrieve the position of words in a document, enabling queries involving proximity of terms. Web search engines implement this kind of indexing, allowing users to retrieve Web pages on the basis of their textual content. Nowadays, digital libraries hold collections of digitized documents that can be retrieved either by browsing the document images or relying on appropriate metadata assembled by domain experts. Word indexing tools would therefore increase the access to these collections. The proposed system is designed to index homogeneous document collections by automatically adapting to different languages and font styles without relying on OCR engines for character recognition. The approach is based on three main ideas: the use of Self Organizing Maps (SOM) to perform unsupervised character clustering, the definition of one suitable vector-based word representation whose size depends on the word aspect-ratio, and the run-time alignment of the query word with indexed words to deal with broken and touching characters. The most appropriate applications are for processing modern printed documents (17th to 19th centuries) where current OCR engines are less accurate. Our experimental analysis addresses six data sets containing documents ranging from books of the 17th century to contemporary journals.

[Development and evaluation of the medical imaging distribution system with dynamic web application and clustering technology].

PubMed

Yokohama, Noriya; Tsuchimoto, Tadashi; Oishi, Masamichi; Itou, Katsuya

2007-01-20

It has been noted that the downtime of medical informatics systems is often long. Many systems encounter downtimes of hours or even days, which can have a critical effect on daily operations. Such systems remain especially weak in the areas of database and medical imaging data. The scheme design shows the three-layer architecture of the system: application, database, and storage layers. The application layer uses the DICOM protocol (Digital Imaging and Communication in Medicine) and HTTP (Hyper Text Transport Protocol) with AJAX (Asynchronous JavaScript+XML). The database is designed to decentralize in parallel using cluster technology. Consequently, restoration of the database can be done not only with ease but also with improved retrieval speed. In the storage layer, a network RAID (Redundant Array of Independent Disks) system, it is possible to construct exabyte-scale parallel file systems that exploit storage spread. Development and evaluation of the test-bed has been successful in medical information data backup and recovery in a network environment. This paper presents a schematic design of the new medical informatics system that can be accommodated from a recovery and the dynamic Web application for medical imaging distribution using AJAX.

Information Retrieval in Telemedicine: a Comparative Study on Bibliographic Databases

PubMed Central

Ahmadi, Maryam; Sarabi, Roghayeh Ershad; Orak, Roohangiz Jamshidi; Bahaadinbeigy, Kambiz

2015-01-01

Background and Aims: The first step in each systematic review is selection of the most valid database that can provide the highest number of relevant references. This study was carried out to determine the most suitable database for information retrieval in telemedicine field. Methods: Cinhal, PubMed, Web of Science and Scopus databases were searched for telemedicine matched with Education, cost benefit and patient satisfaction. After analysis of the obtained results, the accuracy coefficient, sensitivity, uniqueness and overlap of databases were calculated. Results: The studied databases differed in the number of retrieved articles. PubMed was identified as the most suitable database for retrieving information on the selected topics with the accuracy and sensitivity ratios of 50.7% and 61.4% respectively. The uniqueness percent of retrieved articles ranged from 38% for Pubmed to 3.0% for Cinhal. The highest overlap rate (18.6%) was found between PubMed and Web of Science. Less than 1% of articles have been indexed in all searched databases. Conclusion: PubMed is suggested as the most suitable database for starting search in telemedicine and after PubMed, Scopus and Web of Science can retrieve about 90% of the relevant articles. PMID:26236086

Information Retrieval in Telemedicine: a Comparative Study on Bibliographic Databases.

PubMed

Ahmadi, Maryam; Sarabi, Roghayeh Ershad; Orak, Roohangiz Jamshidi; Bahaadinbeigy, Kambiz

2015-06-01

The first step in each systematic review is selection of the most valid database that can provide the highest number of relevant references. This study was carried out to determine the most suitable database for information retrieval in telemedicine field. Cinhal, PubMed, Web of Science and Scopus databases were searched for telemedicine matched with Education, cost benefit and patient satisfaction. After analysis of the obtained results, the accuracy coefficient, sensitivity, uniqueness and overlap of databases were calculated. The studied databases differed in the number of retrieved articles. PubMed was identified as the most suitable database for retrieving information on the selected topics with the accuracy and sensitivity ratios of 50.7% and 61.4% respectively. The uniqueness percent of retrieved articles ranged from 38% for Pubmed to 3.0% for Cinhal. The highest overlap rate (18.6%) was found between PubMed and Web of Science. Less than 1% of articles have been indexed in all searched databases. PubMed is suggested as the most suitable database for starting search in telemedicine and after PubMed, Scopus and Web of Science can retrieve about 90% of the relevant articles.

Programmatic access to data and information at the IRIS DMC via web services

NASA Astrophysics Data System (ADS)

Weertman, B. R.; Trabant, C.; Karstens, R.; Suleiman, Y. Y.; Ahern, T. K.; Casey, R.; Benson, R. B.

2011-12-01

The IRIS Data Management Center (DMC) has developed a suite of web services that provide access to the DMC's time series holdings, their related metadata and earthquake catalogs. In addition, services are available to perform simple, on-demand time series processing at the DMC prior to being shipped to the user. The primary goal is to provide programmatic access to data and processing services in a manner usable by and useful to the research community. The web services are relatively simple to understand and use and will form the foundation on which future DMC access tools will be built. Based on standard Web technologies they can be accessed programmatically with a wide range of programming languages (e.g. Perl, Python, Java), command line utilities such as wget and curl or with any web browser. We anticipate these services being used for everything from simple command line access, used in shell scripts and higher programming languages to being integrated within complex data processing software. In addition to improving access to our data by the seismological community the web services will also make our data more accessible to other disciplines. The web services available from the DMC include ws-bulkdataselect for the retrieval of large volumes of miniSEED data, ws-timeseries for the retrieval of individual segments of time series data in a variety of formats (miniSEED, SAC, ASCII, audio WAVE, and PNG plots) with optional signal processing, ws-station for station metadata in StationXML format, ws-resp for the retrieval of instrument response in RESP format, ws-sacpz for the retrieval of sensor response in the SAC poles and zeros convention and ws-event for the retrieval of earthquake catalogs. To make the services even easier to use, the DMC is developing a library that allows Java programmers to seamlessly retrieve and integrate DMC information into their own programs. The library will handle all aspects of dealing with the services and will parse the returned data. By using this library a developer will not need to learn the details of the service interfaces or understand the data formats returned. This library will be used to build the software bridge needed to request data and information from within MATLAB°. We also provide several client scripts written in Perl for the retrieval of waveform data, metadata and earthquake catalogs using command line programs. For more information on the DMC's web services please visit http://www.iris.edu/ws/

CliniWeb: managing clinical information on the World Wide Web.

PubMed

Hersh, W R; Brown, K E; Donohoe, L C; Campbell, E M; Horacek, A E

1996-01-01

The World Wide Web is a powerful new way to deliver on-line clinical information, but several problems limit its value to health care professionals: content is highly distributed and difficult to find, clinical information is not separated from non-clinical information, and the current Web technology is unable to support some advanced retrieval capabilities. A system called CliniWeb has been developed to address these problems. CliniWeb is an index to clinical information on the World Wide Web, providing a browsing and searching interface to clinical content at the level of the health care student or provider. Its database contains a list of clinical information resources on the Web that are indexed by terms from the Medical Subject Headings disease tree and retrieved with the assistance of SAPHIRE. Limitations of the processes used to build the database are discussed, together with directions for future research.

Automatic generation of Web mining environments

NASA Astrophysics Data System (ADS)

Cibelli, Maurizio; Costagliola, Gennaro

1999-02-01

The main problem related to the retrieval of information from the world wide web is the enormous number of unstructured documents and resources, i.e., the difficulty of locating and tracking appropriate sources. This paper presents a web mining environment (WME), which is capable of finding, extracting and structuring information related to a particular domain from web documents, using general purpose indices. The WME architecture includes a web engine filter (WEF), to sort and reduce the answer set returned by a web engine, a data source pre-processor (DSP), which processes html layout cues in order to collect and qualify page segments, and a heuristic-based information extraction system (HIES), to finally retrieve the required data. Furthermore, we present a web mining environment generator, WMEG, that allows naive users to generate a WME specific to a given domain by providing a set of specifications.

The Evolution of Web Searching.

ERIC Educational Resources Information Center

Green, David

2000-01-01

Explores the interrelation between Web publishing and information retrieval technologies and lists new approaches to Web indexing and searching. Highlights include Web directories; search engines; portalisation; Internet service providers; browser providers; meta search engines; popularity based analysis; natural language searching; links-based…

OpenMSI: A High-Performance Web-Based Platform for Mass Spectrometry Imaging

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

Rubel, Oliver; Greiner, Annette; Cholia, Shreyas

Mass spectrometry imaging (MSI) enables researchers to directly probe endogenous molecules directly within the architecture of the biological matrix. Unfortunately, efficient access, management, and analysis of the data generated by MSI approaches remain major challenges to this rapidly developing field. Despite the availability of numerous dedicated file formats and software packages, it is a widely held viewpoint that the biggest challenge is simply opening, sharing, and analyzing a file without loss of information. Here we present OpenMSI, a software framework and platform that addresses these challenges via an advanced, high-performance, extensible file format and Web API for remote data accessmore » (http://openmsi.nersc.gov). The OpenMSI file format supports storage of raw MSI data, metadata, and derived analyses in a single, self-describing format based on HDF5 and is supported by a large range of analysis software (e.g., Matlab and R) and programming languages (e.g., C++, Fortran, and Python). Careful optimization of the storage layout of MSI data sets using chunking, compression, and data replication accelerates common, selective data access operations while minimizing data storage requirements and are critical enablers of rapid data I/O. The OpenMSI file format has shown to provide >2000-fold improvement for image access operations, enabling spectrum and image retrieval in less than 0.3 s across the Internet even for 50 GB MSI data sets. To make remote high-performance compute resources accessible for analysis and to facilitate data sharing and collaboration, we describe an easy-to-use yet powerful Web API, enabling fast and convenient access to MSI data, metadata, and derived analysis results stored remotely to facilitate high-performance data analysis and enable implementation of Web based data sharing, visualization, and analysis.« less

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

PubMed

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Current Status and Future Plan of Arctic Sea Ice monitoring in South Korea

NASA Astrophysics Data System (ADS)

Shin, J.; Park, J.

2016-12-01

Arctic sea ice is one of the most important parameters in climate. For monitoring of sea ice changes, the National Meteorological Satellite Center (NMSC) of Korea Metrological Administration has developed the "Arctic sea ice monitoring system" to retrieve the sea ice extent and surface roughness using microwave sensor data, and statistical prediction model for Arctic sea ice extent. This system has been implemented to the web site for real-time public service. The sea ice information can be retrieved using the spaceborne microwave sensor-Special Sensor Microwave Imager/Sounder (SSMI/S). The sea ice information like sea ice extent, sea ice surface roughness, and predictive sea ice extent are produced weekly base since 2007. We also publish the "Analysis report of the Arctic sea ice" twice a year. We are trying to add more sea ice information into this system. Details of current status and future plan of Arctic sea ice monitoring and the methodology of the sea ice information retrievals will be presented in the meeting.

Web Mining: Machine Learning for Web Applications.

ERIC Educational Resources Information Center

Chen, Hsinchun; Chau, Michael

2004-01-01

Presents an overview of machine learning research and reviews methods used for evaluating machine learning systems. Ways that machine-learning algorithms were used in traditional information retrieval systems in the "pre-Web" era are described, and the field of Web mining and how machine learning has been used in different Web mining…

Network oriented radiological and medical archive

NASA Astrophysics Data System (ADS)

Ferraris, M.; Frixione, P.; Squarcia, S.

2001-10-01

In this paper the basic ideas of NORMA (Network Oriented Radiological and Medical Archive) are discussed. NORMA is an original project built by a team of physicists in collaboration with radiologists in order to select the best Treatment Planning in radiotherapy. It allows physicians and health physicists, working in different places, to discuss on interesting clinical cases visualizing the same diagnostic images, at the same time, and highlighting zones of interest (tumors and organs at risk). NORMA has a client/server architecture in order to be platform independent. Applying World Wide Web technologies, it can be easily used by people with no specific computer knowledge providing a verbose help to guide the user through the right steps of execution. The client side is an applet while the server side is a Java application. In order to optimize execution the project also includes a proprietary protocol, lying over TCP/IP suite, that organizes data exchanges and control messages. Diagnostic images are retrieved from a relational database or from a standard DICOM (Digital Images and COmmunications in Medicine) PACS through the DICOM-WWW gateway allowing connection of the usual Web browsers, used by the NORMA system, to DICOM applications via the HTTP protocol. Browser requests are sent to the gateway from the Web server through CGI (Common Gateway Interface). DICOM software translates the requests in DICOM messages and organizes the communication with the remote DICOM Application.

Overcoming Terminology Barrier Using Web Resources for Cross-Language Medical Information Retrieval

PubMed Central

Lu, Wen-Hsiang; Lin, Ray Shih-Jui; Chan, Yi-Che; Chen, Kuan-Hsi

2006-01-01

A number of authoritative medical websites, such as PubMed and MedlinePlus, provide consumers with the most up-to-date health information. However, non-English speakers often encounter not only language barriers (from other languages to English) but also terminology barriers (from laypersons’ terms to professional medical terms) when retrieving information from these websites. Our previous work addresses language barriers by developing a multilingual medical thesaurus, Chinese-English MeSH, while this study presents an approach to overcome terminology barriers based on Web resources. Two techniques were utilized in our approach: monolingual concept mapping using approximate string matching and crosslingual concept mapping using Web resources. The evaluation shows that our approach can significantly improve the performance on MeSH concept mapping and cross-language medical information retrieval. PMID:17238395

A multilingual assessment of melanoma information quality on the Internet.

PubMed

Bari, Lilla; Kemeny, Lajos; Bari, Ferenc

2014-06-01

This study aims to assess and compare melanoma information quality in Hungarian, Czech, and German languages on the Internet. We used country-specific Google search engines to retrieve the first 25 uniform resource locators (URLs) by searching the word "melanoma" in the given language. Using the automated toolbar of Health On the Net Foundation (HON), we assessed each Web site for HON certification based on the Health On the Net Foundation Code of Conduct (HONcode). Information quality was determined using a 35-point checklist created by Bichakjian et al. (J Clin Oncol 20:134-141, 2002), with the NCCN melanoma guideline as control. After excluding duplicate and link-only pages, a total of 24 Hungarian, 18 Czech, and 21 German melanoma Web sites were evaluated and rated. The amount of HON certified Web sites was the highest among the German Web pages (19%). One of the retrieved Hungarian and none of the Czech Web sites were HON certified. We found the highest number of Web sites containing comprehensive, correct melanoma information in German language, followed by Czech and Hungarian pages. Although the majority of the Web sites lacked data about incidence, risk factors, prevention, treatment, work-up, and follow-up, at least one comprehensive, high-quality Web site was found in each language. Several Web sites contained incorrect information in each language. While a small amount of comprehensive, quality melanoma-related Web sites was found, most of the retrieved Web content lacked basic disease information, such as risk factors, prevention, and treatment. A significant number of Web sites contained malinformation. In case of melanoma, primary and secondary preventions are of especially high importance; therefore, the improvement of disease information quality available on the Internet is necessary.

WEBCAP: Web Scheduler for Distance Learning Multimedia Documents with Web Workload Considerations

ERIC Educational Resources Information Center

Habib, Sami; Safar, Maytham

2008-01-01

In many web applications, such as the distance learning, the frequency of refreshing multimedia web documents places a heavy burden on the WWW resources. Moreover, the updated web documents may encounter inordinate delays, which make it difficult to retrieve web documents in time. Here, we present an Internet tool called WEBCAP that can schedule…

Automatic gang graffiti recognition and interpretation

NASA Astrophysics Data System (ADS)

Parra, Albert; Boutin, Mireille; Delp, Edward J.

2017-09-01

One of the roles of emergency first responders (e.g., police and fire departments) is to prevent and protect against events that can jeopardize the safety and well-being of a community. In the case of criminal gang activity, tools are needed for finding, documenting, and taking the necessary actions to mitigate the problem or issue. We describe an integrated mobile-based system capable of using location-based services, combined with image analysis, to track and analyze gang activity through the acquisition, indexing, and recognition of gang graffiti images. This approach uses image analysis methods for color recognition, image segmentation, and image retrieval and classification. A database of gang graffiti images is described that includes not only the images but also metadata related to the images, such as date and time, geoposition, gang, gang member, colors, and symbols. The user can then query the data in a useful manner. We have implemented these features both as applications for Android and iOS hand-held devices and as a web-based interface.

Informatics in radiology: RADTF: a semantic search-enabled, natural language processor-generated radiology teaching file.

PubMed

Do, Bao H; Wu, Andrew; Biswal, Sandip; Kamaya, Aya; Rubin, Daniel L

2010-11-01

Storing and retrieving radiology cases is an important activity for education and clinical research, but this process can be time-consuming. In the process of structuring reports and images into organized teaching files, incidental pathologic conditions not pertinent to the primary teaching point can be omitted, as when a user saves images of an aortic dissection case but disregards the incidental osteoid osteoma. An alternate strategy for identifying teaching cases is text search of reports in radiology information systems (RIS), but retrieved reports are unstructured, teaching-related content is not highlighted, and patient identifying information is not removed. Furthermore, searching unstructured reports requires sophisticated retrieval methods to achieve useful results. An open-source, RadLex(®)-compatible teaching file solution called RADTF, which uses natural language processing (NLP) methods to process radiology reports, was developed to create a searchable teaching resource from the RIS and the picture archiving and communication system (PACS). The NLP system extracts and de-identifies teaching-relevant statements from full reports to generate a stand-alone database, thus converting existing RIS archives into an on-demand source of teaching material. Using RADTF, the authors generated a semantic search-enabled, Web-based radiology archive containing over 700,000 cases with millions of images. RADTF combines a compact representation of the teaching-relevant content in radiology reports and a versatile search engine with the scale of the entire RIS-PACS collection of case material. ©RSNA, 2010

Promoting Your Web Site.

ERIC Educational Resources Information Center

Raeder, Aggi

1997-01-01

Discussion of ways to promote sites on the World Wide Web focuses on how search engines work and how they retrieve and identify sites. Appropriate Web links for submitting new sites and for Internet marketing are included. (LRW)

Image processing and applications based on visualizing navigation service

NASA Astrophysics Data System (ADS)

Hwang, Chyi-Wen

2015-07-01

When facing the "overabundant" of semantic web information, in this paper, the researcher proposes the hierarchical classification and visualizing RIA (Rich Internet Application) navigation system: Concept Map (CM) + Semantic Structure (SS) + the Knowledge on Demand (KOD) service. The aim of the Multimedia processing and empirical applications testing, was to investigating the utility and usability of this visualizing navigation strategy in web communication design, into whether it enables the user to retrieve and construct their personal knowledge or not. Furthermore, based on the segment markets theory in the Marketing model, to propose a User Interface (UI) classification strategy and formulate a set of hypermedia design principles for further UI strategy and e-learning resources in semantic web communication. These research findings: (1) Irrespective of whether the simple declarative knowledge or the complex declarative knowledge model is used, the "CM + SS + KOD navigation system" has a better cognition effect than the "Non CM + SS + KOD navigation system". However, for the" No web design experience user", the navigation system does not have an obvious cognition effect. (2) The essential of classification in semantic web communication design: Different groups of user have a diversity of preference needs and different cognitive styles in the CM + SS + KOD navigation system.

On Information Retrieval (IR) Systems: Revisiting Their Development, Evaluation Methodologies, and Assumptions (SIGs LAN, ED).

ERIC Educational Resources Information Center

Stirling, Keith

2000-01-01

Describes a session on information retrieval systems that planned to discuss relevance measures with Web-based information retrieval; retrieval system performance and evaluation; probabilistic independence of index terms; vector-based models; metalanguages and digital objects; how users assess the reliability, timeliness and bias of information;…

Opinions in Federated Search: University of Lugano at TREC 2014 Federated Web Search Track

DTIC Science & Technology

2014-11-01

Opinions in Federated Search : University of Lugano at TREC 2014 Federated Web Search Track Anastasia Giachanou 1 , Ilya Markov 2 and Fabio Crestani 1...ranking based on sentiment using the retrieval-interpolated diversification method. Keywords: federated search , resource selection, vertical selection...performance. Federated search , also known as Distributed Information Retrieval (DIR), o↵ers the means of simultaneously searching multiple information

Problems and challenges in patient information retrieval: a descriptive study.

PubMed Central

Kogan, S.; Zeng, Q.; Ash, N.; Greenes, R. A.

2001-01-01

Many patients now turn to the Web for health care information. However, a lack of domain knowledge and unfamiliarity with medical vocabulary and concepts restrict their ability to successfully obtain information they seek. The purpose of this descriptive study was to identify and classify the problems a patient encounters while performing information retrieval tasks on the Web, and the challenges it poses to informatics research. In this study, we observed patients performing various retrieval tasks, and measured the effectiveness of, satisfaction with, and usefulness of the results. Our study showed that patient information retrieval often failed to produce successful results due to a variety of problems. We propose a classification of patient IR problems based on our observations. PMID:11825205

A framework for biomedical figure segmentation towards image-based document retrieval

PubMed Central

2013-01-01

The figures included in many of the biomedical publications play an important role in understanding the biological experiments and facts described within. Recent studies have shown that it is possible to integrate the information that is extracted from figures in classical document classification and retrieval tasks in order to improve their accuracy. One important observation about the figures included in biomedical publications is that they are often composed of multiple subfigures or panels, each describing different methodologies or results. The use of these multimodal figures is a common practice in bioscience, as experimental results are graphically validated via multiple methodologies or procedures. Thus, for a better use of multimodal figures in document classification or retrieval tasks, as well as for providing the evidence source for derived assertions, it is important to automatically segment multimodal figures into subfigures and panels. This is a challenging task, however, as different panels can contain similar objects (i.e., barcharts and linecharts) with multiple layouts. Also, certain types of biomedical figures are text-heavy (e.g., DNA sequences and protein sequences images) and they differ from traditional images. As a result, classical image segmentation techniques based on low-level image features, such as edges or color, are not directly applicable to robustly partition multimodal figures into single modal panels. In this paper, we describe a robust solution for automatically identifying and segmenting unimodal panels from a multimodal figure. Our framework starts by robustly harvesting figure-caption pairs from biomedical articles. We base our approach on the observation that the document layout can be used to identify encoded figures and figure boundaries within PDF files. Taking into consideration the document layout allows us to correctly extract figures from the PDF document and associate their corresponding caption. We combine pixel-level representations of the extracted images with information gathered from their corresponding captions to estimate the number of panels in the figure. Thus, our approach simultaneously identifies the number of panels and the layout of figures. In order to evaluate the approach described here, we applied our system on documents containing protein-protein interactions (PPIs) and compared the results against a gold standard that was annotated by biologists. Experimental results showed that our automatic figure segmentation approach surpasses pure caption-based and image-based approaches, achieving a 96.64% accuracy. To allow for efficient retrieval of information, as well as to provide the basis for integration into document classification and retrieval systems among other, we further developed a web-based interface that lets users easily retrieve panels containing the terms specified in the user queries. PMID:24565394

Managing an Archive of Images

NASA Technical Reports Server (NTRS)

Andres, Vince; Walter, David; Hallal, Charles; Jones, Helene; Callac, Chris

2004-01-01

The SSC Multimedia Archive is an automated electronic system to manage images, acquired both by film and digital cameras, for the Public Affairs Office (PAO) at Stennis Space Center (SSC). Previously, the image archive was based on film photography and utilized a manual system that, by today s standards, had become inefficient and expensive. Now, the SSC Multimedia Archive, based on a server at SSC, contains both catalogs and images for pictures taken both digitally and with a traditional, film-based camera, along with metadata about each image. After a "shoot," a photographer downloads the images into the database. Members of the PAO can use a Web-based application to search, view and retrieve images, approve images for publication, and view and edit metadata associated with the images. Approved images are archived and cross-referenced with appropriate descriptions and information. Security is provided by allowing administrators to explicitly grant access privileges to personnel to only access components of the system that they need to (i.e., allow only photographers to upload images, only PAO designated employees may approve images).

[Study of sharing platform of web-based enhanced extracorporeal counterpulsation hemodynamic waveform data].

PubMed

Huang, Mingbo; Hu, Ding; Yu, Donglan; Zheng, Zhensheng; Wang, Kuijian

2011-12-01

Enhanced extracorporeal counterpulsation (EECP) information consists of both text and hemodynamic waveform data. At present EECP text information has been successfully managed through Web browser, while the management and sharing of hemodynamic waveform data through Internet has not been solved yet. In order to manage EECP information completely, based on the in-depth analysis of EECP hemodynamic waveform file of digital imaging and communications in medicine (DICOM) format and its disadvantages in Internet sharing, we proposed the use of the extensible markup language (XML), which is currently the Internet popular data exchange standard, as the storage specification for the sharing of EECP waveform data. Then we designed a web-based sharing system of EECP hemodynamic waveform data via ASP. NET 2.0 platform. Meanwhile, we specifically introduced the four main system function modules and their implement methods, including DICOM to XML conversion module, EECP waveform data management module, retrieval and display of EECP waveform module and the security mechanism of the system.

Improving life sciences information retrieval using semantic web technology.

PubMed

Quan, Dennis

2007-05-01

The ability to retrieve relevant information is at the heart of every aspect of research and development in the life sciences industry. Information is often distributed across multiple systems and recorded in a way that makes it difficult to piece together the complete picture. Differences in data formats, naming schemes and network protocols amongst information sources, both public and private, must be overcome, and user interfaces not only need to be able to tap into these diverse information sources but must also assist users in filtering out extraneous information and highlighting the key relationships hidden within an aggregated set of information. The Semantic Web community has made great strides in proposing solutions to these problems, and many efforts are underway to apply Semantic Web techniques to the problem of information retrieval in the life sciences space. This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.

The Protein Disease Database of human body fluids: II. Computer methods and data issues.

PubMed

Lemkin, P F; Orr, G A; Goldstein, M P; Creed, G J; Myrick, J E; Merril, C R

1995-01-01

The Protein Disease Database (PDD) is a relational database of proteins and diseases. With this database it is possible to screen for quantitative protein abnormalities associated with disease states. These quantitative relationships use data drawn from the peer-reviewed biomedical literature. Assays may also include those observed in high-resolution electrophoretic gels that offer the potential to quantitate many proteins in a single test as well as data gathered by enzymatic or immunologic assays. We are using the Internet World Wide Web (WWW) and the Web browser paradigm as an access method for wide distribution and querying of the Protein Disease Database. The WWW hypertext transfer protocol and its Common Gateway Interface make it possible to build powerful graphical user interfaces that can support easy-to-use data retrieval using query specification forms or images. The details of these interactions are totally transparent to the users of these forms. Using a client-server SQL relational database, user query access, initial data entry and database maintenance are all performed over the Internet with a Web browser. We discuss the underlying design issues, mapping mechanisms and assumptions that we used in constructing the system, data entry, access to the database server, security, and synthesis of derived two-dimensional gel image maps and hypertext documents resulting from SQL database searches.

IntegromeDB: an integrated system and biological search engine.

PubMed

Baitaluk, Michael; Kozhenkov, Sergey; Dubinina, Yulia; Ponomarenko, Julia

2012-01-19

With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback.

Skin image retrieval using Gabor wavelet texture feature.

PubMed

Ou, X; Pan, W; Zhang, X; Xiao, P

2016-12-01

Skin imaging plays a key role in many clinical studies. We have used many skin imaging techniques, including the recently developed capacitive contact skin imaging based on fingerprint sensors. The aim of this study was to develop an effective skin image retrieval technique using Gabor wavelet transform, which can be used on different types of skin images, but with a special focus on skin capacitive contact images. Content-based image retrieval (CBIR) is a useful technology to retrieve stored images from database by supplying query images. In a typical CBIR, images are retrieved based on colour, shape, texture, etc. In this study, texture feature is used for retrieving skin images, and Gabor wavelet transform is used for texture feature description and extraction. The results show that the Gabor wavelet texture features can work efficiently on different types of skin images. Although Gabor wavelet transform is slower compared with other image retrieval techniques, such as principal component analysis (PCA) and grey-level co-occurrence matrix (GLCM), Gabor wavelet transform is the best for retrieving skin capacitive contact images and facial images with different orientations. Gabor wavelet transform can also work well on facial images with different expressions and skin cancer/disease images. We have developed an effective skin image retrieval method based on Gabor wavelet transform, that it is useful for retrieving different types of images, namely digital colour face images, digital colour skin cancer and skin disease images, and particularly greyscale skin capacitive contact images. Gabor wavelet transform can also be potentially useful for face recognition (with different orientation and expressions) and skin cancer/disease diagnosis. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Validating a Geographical Image Retrieval System.

ERIC Educational Resources Information Center

Zhu, Bin; Chen, Hsinchun

2000-01-01

Summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. Describes an experiment to validate the performance of this image retrieval system against that of human subjects by examining similarity analysis…

BioModels.net Web Services, a free and integrated toolkit for computational modelling software.

PubMed

Li, Chen; Courtot, Mélanie; Le Novère, Nicolas; Laibe, Camille

2010-05-01

Exchanging and sharing scientific results are essential for researchers in the field of computational modelling. BioModels.net defines agreed-upon standards for model curation. A fundamental one, MIRIAM (Minimum Information Requested in the Annotation of Models), standardises the annotation and curation process of quantitative models in biology. To support this standard, MIRIAM Resources maintains a set of standard data types for annotating models, and provides services for manipulating these annotations. Furthermore, BioModels.net creates controlled vocabularies, such as SBO (Systems Biology Ontology) which strictly indexes, defines and links terms used in Systems Biology. Finally, BioModels Database provides a free, centralised, publicly accessible database for storing, searching and retrieving curated and annotated computational models. Each resource provides a web interface to submit, search, retrieve and display its data. In addition, the BioModels.net team provides a set of Web Services which allows the community to programmatically access the resources. A user is then able to perform remote queries, such as retrieving a model and resolving all its MIRIAM Annotations, as well as getting the details about the associated SBO terms. These web services use established standards. Communications rely on SOAP (Simple Object Access Protocol) messages and the available queries are described in a WSDL (Web Services Description Language) file. Several libraries are provided in order to simplify the development of client software. BioModels.net Web Services make one step further for the researchers to simulate and understand the entirety of a biological system, by allowing them to retrieve biological models in their own tool, combine queries in workflows and efficiently analyse models.

ACMES: fast multiple-genome searches for short repeat sequences with concurrent cross-species information retrieval

PubMed Central

Reneker, Jeff; Shyu, Chi-Ren; Zeng, Peiyu; Polacco, Joseph C.; Gassmann, Walter

2004-01-01

We have developed a web server for the life sciences community to use to search for short repeats of DNA sequence of length between 3 and 10 000 bases within multiple species. This search employs a unique and fast hash function approach. Our system also applies information retrieval algorithms to discover knowledge of cross-species conservation of repeat sequences. Furthermore, we have incorporated a part of the Gene Ontology database into our information retrieval algorithms to broaden the coverage of the search. Our web server and tutorial can be found at http://acmes.rnet.missouri.edu. PMID:15215469

An Efficient Approach for Web Indexing of Big Data through Hyperlinks in Web Crawling.

PubMed

Devi, R Suganya; Manjula, D; Siddharth, R K

2015-01-01

Web Crawling has acquired tremendous significance in recent times and it is aptly associated with the substantial development of the World Wide Web. Web Search Engines face new challenges due to the availability of vast amounts of web documents, thus making the retrieved results less applicable to the analysers. However, recently, Web Crawling solely focuses on obtaining the links of the corresponding documents. Today, there exist various algorithms and software which are used to crawl links from the web which has to be further processed for future use, thereby increasing the overload of the analyser. This paper concentrates on crawling the links and retrieving all information associated with them to facilitate easy processing for other uses. In this paper, firstly the links are crawled from the specified uniform resource locator (URL) using a modified version of Depth First Search Algorithm which allows for complete hierarchical scanning of corresponding web links. The links are then accessed via the source code and its metadata such as title, keywords, and description are extracted. This content is very essential for any type of analyser work to be carried on the Big Data obtained as a result of Web Crawling.

An Efficient Approach for Web Indexing of Big Data through Hyperlinks in Web Crawling

PubMed Central

Devi, R. Suganya; Manjula, D.; Siddharth, R. K.

2015-01-01

Web Crawling has acquired tremendous significance in recent times and it is aptly associated with the substantial development of the World Wide Web. Web Search Engines face new challenges due to the availability of vast amounts of web documents, thus making the retrieved results less applicable to the analysers. However, recently, Web Crawling solely focuses on obtaining the links of the corresponding documents. Today, there exist various algorithms and software which are used to crawl links from the web which has to be further processed for future use, thereby increasing the overload of the analyser. This paper concentrates on crawling the links and retrieving all information associated with them to facilitate easy processing for other uses. In this paper, firstly the links are crawled from the specified uniform resource locator (URL) using a modified version of Depth First Search Algorithm which allows for complete hierarchical scanning of corresponding web links. The links are then accessed via the source code and its metadata such as title, keywords, and description are extracted. This content is very essential for any type of analyser work to be carried on the Big Data obtained as a result of Web Crawling. PMID:26137592

Incorporating the APS Catalog of the POSS I and Image Archive in ADS

NASA Technical Reports Server (NTRS)

Humphreys, Roberta M.

1998-01-01

The primary purpose of this contract was to develop the software to both create and access an on-line database of images from digital scans of the Palomar Sky Survey. This required modifying our DBMS (called Star Base) to create an image database from the actual raw pixel data from the scans. The digitized images are processed into a set of coordinate-reference index and pixel files that are stored in run-length files, thus achieving an efficient lossless compression. For efficiency and ease of referencing, each digitized POSS I plate is then divided into 900 subplates. Our custom DBMS maps each query into the corresponding POSS plate(s) and subplate(s). All images from the appropriate subplates are retrieved from disk with byte-offsets taken from the index files. These are assembled on-the-fly into a GIF image file for browser display, and a FITS format image file for retrieval. The FITS images have a pixel size of 0.33 arcseconds. The FITS header contains astrometric and photometric information. This method keeps the disk requirements manageable while allowing for future improvements. When complete, the APS Image Database will contain over 130 Gb of data. A set of web pages query forms are available on-line, as well as an on-line tutorial and documentation. The database is distributed to the Internet by a high-speed SGI server and a high-bandwidth disk system. URL is http://aps.umn.edu/IDB/. The image database software is written in perl and C and has been compiled on SGI computers with MIX5.3. A copy of the written documentation is included and the software is on the accompanying exabyte tape.

Scaling Up High-Value Retrieval to Medium-Volume Data

NASA Astrophysics Data System (ADS)

Cunningham, Hamish; Hanbury, Allan; Rüger, Stefan

We summarise the scientific work presented at the first Information Retrieval Facility Conference [3] and argue that high-value retrieval with medium-volume data, exemplified by patent search, is a thriving topic in a multidisciplinary area that sits between Information Retrieval, Natural Language Processing and Semantic Web Technologies. We analyse the parameters that condition choices of retrieval technology for different sizes and values of document space, and we present the patent document space and some of its characteristics for retrieval work.

Finding Specification Pages from the Web

NASA Astrophysics Data System (ADS)

Yoshinaga, Naoki; Torisawa, Kentaro

This paper presents a method of finding a specification page on the Web for a given object (e.g., ``Ch. d'Yquem'') and its class label (e.g., ``wine''). A specification page for an object is a Web page which gives concise attribute-value information about the object (e.g., ``county''-``Sauternes'') in well formatted structures. A simple unsupervised method using layout and symbolic decoration cues was applied to a large number of the Web pages to acquire candidate attributes for each class (e.g., ``county'' for a class ``wine''). We then filter out irrelevant words from the putative attributes through an author-aware scoring function that we called site frequency. We used the acquired attributes to select a representative specification page for a given object from the Web pages retrieved by a normal search engine. Experimental results revealed that our system greatly outperformed the normal search engine in terms of this specification retrieval.

An integrated content and metadata based retrieval system for art.

PubMed

Lewis, Paul H; Martinez, Kirk; Abas, Fazly Salleh; Fauzi, Mohammad Faizal Ahmad; Chan, Stephen C Y; Addis, Matthew J; Boniface, Mike J; Grimwood, Paul; Stevenson, Alison; Lahanier, Christian; Stevenson, James

2004-03-01

A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.

IntegromeDB: an integrated system and biological search engine

PubMed Central

2012-01-01

Background With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Description Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. Conclusions The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback. PMID:22260095

A novel image retrieval algorithm based on PHOG and LSH

NASA Astrophysics Data System (ADS)

Wu, Hongliang; Wu, Weimin; Peng, Jiajin; Zhang, Junyuan

2017-08-01

PHOG can describe the local shape of the image and its relationship between the spaces. The using of PHOG algorithm to extract image features in image recognition and retrieval and other aspects have achieved good results. In recent years, locality sensitive hashing (LSH) algorithm has been superior to large-scale data in solving near-nearest neighbor problems compared with traditional algorithms. This paper presents a novel image retrieval algorithm based on PHOG and LSH. First, we use PHOG to extract the feature vector of the image, then use L different LSH hash table to reduce the dimension of PHOG texture to index values and map to different bucket, and finally extract the corresponding value of the image in the bucket for second image retrieval using Manhattan distance. This algorithm can adapt to the massive image retrieval, which ensures the high accuracy of the image retrieval and reduces the time complexity of the retrieval. This algorithm is of great significance.

WWW Entrez: A Hypertext Retrieval Tool for Molecular Biology.

ERIC Educational Resources Information Center

Epstein, Jonathan A.; Kans, Jonathan A.; Schuler, Gregory D.

This article describes the World Wide Web (WWW) Entrez server which is based upon the National Center for Biotechnology Information's (NCBI) Entrez retrieval database and software. Entrez is a molecular sequence retrieval system that contains an integrated view of portions of Medline and all publicly available nucleotide and protein databases,…

Applying Semantic Web technologies to improve the retrieval, credibility and use of health-related web resources.

PubMed

Mayer, Miguel A; Karampiperis, Pythagoras; Kukurikos, Antonis; Karkaletsis, Vangelis; Stamatakis, Kostas; Villarroel, Dagmar; Leis, Angela

2011-06-01

The number of health-related websites is increasing day-by-day; however, their quality is variable and difficult to assess. Various "trust marks" and filtering portals have been created in order to assist consumers in retrieving quality medical information. Consumers are using search engines as the main tool to get health information; however, the major problem is that the meaning of the web content is not machine-readable in the sense that computers cannot understand words and sentences as humans can. In addition, trust marks are invisible to search engines, thus limiting their usefulness in practice. During the last five years there have been different attempts to use Semantic Web tools to label health-related web resources to help internet users identify trustworthy resources. This paper discusses how Semantic Web technologies can be applied in practice to generate machine-readable labels and display their content, as well as to empower end-users by providing them with the infrastructure for expressing and sharing their opinions on the quality of health-related web resources.

PageRank without hyperlinks: Reranking with PubMed related article networks for biomedical text retrieval

PubMed Central

Lin, Jimmy

2008-01-01

Background Graph analysis algorithms such as PageRank and HITS have been successful in Web environments because they are able to extract important inter-document relationships from manually-created hyperlinks. We consider the application of these techniques to biomedical text retrieval. In the current PubMed® search interface, a MEDLINE® citation is connected to a number of related citations, which are in turn connected to other citations. Thus, a MEDLINE record represents a node in a vast content-similarity network. This article explores the hypothesis that these networks can be exploited for text retrieval, in the same manner as hyperlink graphs on the Web. Results We conducted a number of reranking experiments using the TREC 2005 genomics track test collection in which scores extracted from PageRank and HITS analysis were combined with scores returned by an off-the-shelf retrieval engine. Experiments demonstrate that incorporating PageRank scores yields significant improvements in terms of standard ranked-retrieval metrics. Conclusion The link structure of content-similarity networks can be exploited to improve the effectiveness of information retrieval systems. These results generalize the applicability of graph analysis algorithms to text retrieval in the biomedical domain. PMID:18538027

Document image retrieval through word shape coding.

PubMed

Lu, Shijian; Li, Linlin; Tan, Chew Lim

2008-11-01

This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.

WebGIVI: a web-based gene enrichment analysis and visualization tool.

PubMed

Sun, Liang; Zhu, Yongnan; Mahmood, A S M Ashique; Tudor, Catalina O; Ren, Jia; Vijay-Shanker, K; Chen, Jian; Schmidt, Carl J

2017-05-04

A major challenge of high throughput transcriptome studies is presenting the data to researchers in an interpretable format. In many cases, the outputs of such studies are gene lists which are then examined for enriched biological concepts. One approach to help the researcher interpret large gene datasets is to associate genes and informative terms (iTerm) that are obtained from the biomedical literature using the eGIFT text-mining system. However, examining large lists of iTerm and gene pairs is a daunting task. We have developed WebGIVI, an interactive web-based visualization tool ( http://raven.anr.udel.edu/webgivi/ ) to explore gene:iTerm pairs. WebGIVI was built via Cytoscape and Data Driven Document JavaScript libraries and can be used to relate genes to iTerms and then visualize gene and iTerm pairs. WebGIVI can accept a gene list that is used to retrieve the gene symbols and corresponding iTerm list. This list can be submitted to visualize the gene iTerm pairs using two distinct methods: a Concept Map or a Cytoscape Network Map. In addition, WebGIVI also supports uploading and visualization of any two-column tab separated data. WebGIVI provides an interactive and integrated network graph of gene and iTerms that allows filtering, sorting, and grouping, which can aid biologists in developing hypothesis based on the input gene lists. In addition, WebGIVI can visualize hundreds of nodes and generate a high-resolution image that is important for most of research publications. The source code can be freely downloaded at https://github.com/sunliang3361/WebGIVI . The WebGIVI tutorial is available at http://raven.anr.udel.edu/webgivi/tutorial.php .

An intelligent framework for medical image retrieval using MDCT and multi SVM.

PubMed

Balan, J A Alex Rajju; Rajan, S Edward

2014-01-01

Volumes of medical images are rapidly generated in medical field and to manage them effectively has become a great challenge. This paper studies the development of innovative medical image retrieval based on texture features and accuracy. The objective of the paper is to analyze the image retrieval based on diagnosis of healthcare management systems. This paper traces the development of innovative medical image retrieval to estimate both the image texture features and accuracy. The texture features of medical images are extracted using MDCT and multi SVM. Both the theoretical approach and the simulation results revealed interesting observations and they were corroborated using MDCT coefficients and SVM methodology. All attempts to extract the data about the image in response to the query has been computed successfully and perfect image retrieval performance has been obtained. Experimental results on a database of 100 trademark medical images show that an integrated texture feature representation results in 98% of the images being retrieved using MDCT and multi SVM. Thus we have studied a multiclassification technique based on SVM which is prior suitable for medical images. The results show the retrieval accuracy of 98%, 99% for different sets of medical images with respect to the class of image.

Wireless-PDA-controlled image workflow from PACS: the next trend in the health care enterprise?

NASA Astrophysics Data System (ADS)

Erberich, Stephan G.; Documet, Jorge; Zhou, Michael Z.; Cao, Fei; Liu, Brent J.; Mogel, Greg T.; Huang, H. K.

2003-05-01

Image workflow in today's Picture Archiving and Communication Systems (PACS) is controlled from fixed Display Workstations (DW) using proprietary control interfaces. A remote access to the Hospital Information System (HIS) and Radiology Information System (RIS) for urgent patient information retrieval does not exist or gradually become available. The lack for remote access and workflow control for HIS and RIS is especially true when it comes to medical images of a PACS on Department or Hospital level. As images become more complex and data sizes expand rapidly with new image techniques like functional MRI, Mammography or routine spiral CT to name a few, the access and manageability becomes an important issue. Long image downloads or incomplete work lists cannot be tolerated in a busy health care environment. In addition, the domain of the PACS is no longer limited to the imaging department and PACS is also being used in the ER and emergency care units. Thus a prompt and secure access and manageability not only by the radiologist, but also from the physician becomes crucial to optimally utilize the PACS in the health care enterprise of the new millennium. The purpose of this paper is to introduce a concept and its implementation of a remote access and workflow control of the PACS combining wireless, Internet and Internet2 technologies. A wireless device, the Personal Digital Assistant (PDA), is used to communicate to a PACS web server that acts as a gateway controlling the commands for which the user has access to the PACS server. The commands implemented for this test-bed are query/retrieve of the patient list and study list including modality, examination, series and image selection and pushing any list items to a selected DW on the PACS network.

Theoretical and Empirical Comparison of Big Data Image Processing with Apache Hadoop and Sun Grid Engine.

PubMed

Bao, Shunxing; Weitendorf, Frederick D; Plassard, Andrew J; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A

2017-02-11

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., "short" processing times and/or "large" datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply "large scale" processing transitions into "big data" and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and non-relevant for medical imaging.

Theoretical and empirical comparison of big data image processing with Apache Hadoop and Sun Grid Engine

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Weitendorf, Frederick D.; Plassard, Andrew J.; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A.

2017-03-01

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., "short" processing times and/or "large" datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply "large scale" processing transitions into "big data" and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and nonrelevant for medical imaging.

[Design and implementation of medical instrument standard information retrieval system based on APS.NET].

PubMed

Yu, Kaijun

2010-07-01

This paper Analys the design goals of Medical Instrumentation standard information retrieval system. Based on the B /S structure,we established a medical instrumentation standard retrieval system with ASP.NET C # programming language, IIS f Web server, SQL Server 2000 database, in the. NET environment. The paper also Introduces the system structure, retrieval system modules, system development environment and detailed design of the system.

Developing Design Criteria and Scale Up Methods for Water-Stable Metal-Organic Frameworks for Adsorption Applications

DTIC Science & Technology

2014-09-08

Figure 1.4: Number of publications containing the term “metal-organic frameworks” (Source: ISI Web of Science, retrieved April, 14 th , 2014) 8...1.4 Number of publications containing the term “metal-organic frameworks” (Source: ISI Web of Science, retrieved April, 14 th , 2014). 1.4...recorded with a PerkinElmer Spectrum One 10 in the range 400 – 4000 cm -1 . To record the IR spectrum, an IR beam is passed through the sample (in

SIRW: A web server for the Simple Indexing and Retrieval System that combines sequence motif searches with keyword searches.

PubMed

Ramu, Chenna

2003-07-01

SIRW (http://sirw.embl.de/) is a World Wide Web interface to the Simple Indexing and Retrieval System (SIR) that is capable of parsing and indexing various flat file databases. In addition it provides a framework for doing sequence analysis (e.g. motif pattern searches) for selected biological sequences through keyword search. SIRW is an ideal tool for the bioinformatics community for searching as well as analyzing biological sequences of interest.

What do patients know about their low back pain? An analysis of the quality of information available on the Internet.

PubMed

Galbusera, Fabio; Brayda-Bruno, Marco; Freutel, Maren; Seitz, Andreas; Steiner, Malte; Wehrle, Esther; Wilke, Hans-Joachim

2012-01-01

Previous surveys showed a poor quality of the web sites providing health information about low back pain. However, the rapid and continuous evolution of the Internet content may question the current validity of those investigations. The present study is aimed to quantitatively assess the quality of the Internet information about low back pain retrieved with the most commonly employed search engines. An Internet search with the keywords "low back pain" has been performed with Google, Yahoo!® and Bing™ in the English language. The top 30 hits obtained with each search engine were evaluated by five independent raters and averaged following criteria derived from previous works. All search results were categorized as declaring compliant to a quality standard for health information (e.g. HONCode) or not and based on the web site type (Institutional, Free informative, Commercial, News, Social Network, Unknown). The quality of the hits retrieved by the three search engines was extremely similar. The web sites had a clear purpose, were easy to navigate, and mostly lacked in validity and quality of the provided links. The conformity to a quality standard was correlated with a marked greater quality of the web sites in all respects. Institutional web sites had the best validity and ease of use. Free informative web sites had good quality but a markedly lower validity compared to Institutional websites. Commercial web sites provided more biased information. News web sites were well designed and easy to use, but lacked in validity. The average quality of the hits retrieved by the most commonly employed search engines could be defined as satisfactory and favorably comparable with previous investigations. Awareness of the user about checking the quality of the information remains of concern.

Structural and Multilingual Approaches to Subject Access on the Web.

ERIC Educational Resources Information Center

Chan, Lois Mai; Lin, Xia; Zeng, Marcia

This paper presents some of the efforts currently being made to develop mechanisms that can organize World Wide Web resources for efficient and effective retrieval, as well as programs that can accommodate multiple languages. Part 1 discusses structural approaches to organizing Web resources, including the use of hierarchical or…

A web-based approach for electrocardiogram monitoring in the home.

PubMed

Magrabi, F; Lovell, N H; Celler, B G

1999-05-01

A Web-based electrocardiogram (ECG) monitoring service in which a longitudinal clinical record is used for management of patients, is described. The Web application is used to collect clinical data from the patient's home. A database on the server acts as a central repository where this clinical information is stored. A Web browser provides access to the patient's records and ECG data. We discuss the technologies used to automate the retrieval and storage of clinical data from a patient database, and the recording and reviewing of clinical measurement data. On the client's Web browser, ActiveX controls embedded in the Web pages provide a link between the various components including the Web server, Web page, the specialised client side ECG review and acquisition software, and the local file system. The ActiveX controls also implement FTP functions to retrieve and submit clinical data to and from the server. An intelligent software agent on the server is activated whenever new ECG data is sent from the home. The agent compares historical data with newly acquired data. Using this method, an optimum patient care strategy can be evaluated, a summarised report along with reminders and suggestions for action is sent to the doctor and patient by email.

The National Institutes of Health Clinical Center Digital Imaging Network, Picture Archival and Communication System, and Radiology Information System.

PubMed

Goldszal, A F; Brown, G K; McDonald, H J; Vucich, J J; Staab, E V

2001-06-01

In this work, we describe the digital imaging network (DIN), picture archival and communication system (PACS), and radiology information system (RIS) currently being implemented at the Clinical Center, National Institutes of Health (NIH). These systems are presently in clinical operation. The DIN is a redundant meshed network designed to address gigabit density and expected high bandwidth requirements for image transfer and server aggregation. The PACS projected workload is 5.0 TB of new imaging data per year. Its architecture consists of a central, high-throughput Digital Imaging and Communications in Medicine (DICOM) data repository and distributed redundant array of inexpensive disks (RAID) servers employing fiber-channel technology for immediate delivery of imaging data. On demand distribution of images and reports to clinicians and researchers is accomplished via a clustered web server. The RIS follows a client-server model and provides tools to order exams, schedule resources, retrieve and review results, and generate management reports. The RIS-hospital information system (HIS) interfaces include admissions, discharges, and transfers (ATDs)/demographics, orders, appointment notifications, doctors update, and results.

An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses

DOE PAGES

Fischer, Curt R.; Ruebel, Oliver; Bowen, Benjamin P.

2015-09-11

Mass spectrometry imaging (MSI) is used in an increasing number of biological applications. Typical MSI datasets contain unique, high-resolution mass spectra from tens of thousands of spatial locations, resulting in raw data sizes of tens of gigabytes per sample. In this paper, we review technical progress that is enabling new biological applications and that is driving an increase in the complexity and size of MSI data. Handling such data often requires specialized computational infrastructure, software, and expertise. OpenMSI, our recently described platform, makes it easy to explore and share MSI datasets via the web – even when larger than 50more » GB. Here we describe the integration of OpenMSI with IPython notebooks for transparent, sharable, and replicable MSI research. An advantage of this approach is that users do not have to share raw data along with analyses; instead, data is retrieved via OpenMSI's web API. The IPython notebook interface provides a low-barrier entry point for data manipulation that is accessible for scientists without extensive computational training. Via these notebooks, analyses can be easily shared without requiring any data movement. We provide example notebooks for several common MSI analysis types including data normalization, plotting, clustering, and classification, and image registration.« less

An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses.

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

Fischer, CR; Ruebel, O; Bowen, BP

Mass spectrometry imaging (MSI) is used in an increasing number of biological applications. Typical MSI datasets contain unique, high-resolution mass spectra from tens of thousands of spatial locations, resulting in raw data sizes of tens of gigabytes per sample. In this paper, we review technical progress that is enabling new biological applications and that is driving an increase in the complexity and size of MSI data. Handling such data often requires specialized computational infrastructure, software, and expertise. OpenMSI, our recently described platform, makes it easy to explore and share MSI datasets via the web - even when larger than 50 GB.more » Here we describe the integration of OpenMSI with IPython notebooks for transparent, sharable, and replicable MSI research. An advantage of this approach is that users do not have to share raw data along with analyses; instead, data is retrieved via OpenMSI's web API. The IPython notebook interface provides a low-barrier entry point for data manipulation that is accessible for scientists without extensive computational training. Via these notebooks, analyses can be easily shared without requiring any data movement. We provide example notebooks for several common MSI analysis types including data normalization, plotting, clustering, and classification, and image registration.« less

An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses

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

Fischer, Curt R.; Ruebel, Oliver; Bowen, Benjamin P.

Mass spectrometry imaging (MSI) is used in an increasing number of biological applications. Typical MSI datasets contain unique, high-resolution mass spectra from tens of thousands of spatial locations, resulting in raw data sizes of tens of gigabytes per sample. In this paper, we review technical progress that is enabling new biological applications and that is driving an increase in the complexity and size of MSI data. Handling such data often requires specialized computational infrastructure, software, and expertise. OpenMSI, our recently described platform, makes it easy to explore and share MSI datasets via the web – even when larger than 50more » GB. Here we describe the integration of OpenMSI with IPython notebooks for transparent, sharable, and replicable MSI research. An advantage of this approach is that users do not have to share raw data along with analyses; instead, data is retrieved via OpenMSI's web API. The IPython notebook interface provides a low-barrier entry point for data manipulation that is accessible for scientists without extensive computational training. Via these notebooks, analyses can be easily shared without requiring any data movement. We provide example notebooks for several common MSI analysis types including data normalization, plotting, clustering, and classification, and image registration.« less

Implementing a distributed intranet-based information system.

PubMed

O'Kane, K C; McColligan, E E; Davis, G A

1996-11-01

The article discusses Internet and intranet technologies and describes how to install an intranet-based information system using the Merle language facility and other readily available components. Merle is a script language designed to support decentralized medical record information retrieval applications on the World Wide Web. The goal of this work is to provide a script language tool to facilitate construction of efficient, fully functional, multipoint medical record information systems that can be accessed anywhere by low-cost Web browsers to search, retrieve, and analyze patient information. The language allows legacy MUMPS applications to function in a Web environment and to make use of the Web graphical, sound, and video presentation services. It also permits downloading of script applets for execution on client browsers, and it can be used in standalone mode with the Unix, Windows 95, Windows NT, and OS/2 operating systems.

Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval.

PubMed

Wei, Xiu-Shen; Luo, Jian-Hao; Wu, Jianxin; Zhou, Zhi-Hua

2017-06-01

Deep convolutional neural network models pre-trained for the ImageNet classification task have been successfully adopted to tasks in other domains, such as texture description and object proposal generation, but these tasks require annotations for images in the new domain. In this paper, we focus on a novel and challenging task in the pure unsupervised setting: fine-grained image retrieval. Even with image labels, fine-grained images are difficult to classify, letting alone the unsupervised retrieval task. We propose the selective convolutional descriptor aggregation (SCDA) method. The SCDA first localizes the main object in fine-grained images, a step that discards the noisy background and keeps useful deep descriptors. The selected descriptors are then aggregated and the dimensionality is reduced into a short feature vector using the best practices we found. The SCDA is unsupervised, using no image label or bounding box annotation. Experiments on six fine-grained data sets confirm the effectiveness of the SCDA for fine-grained image retrieval. Besides, visualization of the SCDA features shows that they correspond to visual attributes (even subtle ones), which might explain SCDA's high-mean average precision in fine-grained retrieval. Moreover, on general image retrieval data sets, the SCDA achieves comparable retrieval results with the state-of-the-art general image retrieval approaches.

Planetary Data Systems (PDS) Imaging Node Atlas II

NASA Technical Reports Server (NTRS)

Stanboli, Alice; McAuley, James M.

2013-01-01

The Planetary Image Atlas (PIA) is a Rich Internet Application (RIA) that serves planetary imaging data to the science community and the general public. PIA also utilizes the USGS Unified Planetary Coordinate system (UPC) and the on-Mars map server. The Atlas was designed to provide the ability to search and filter through greater than 8 million planetary image files. This software is a three-tier Web application that contains a search engine backend (MySQL, JAVA), Web service interface (SOAP) between server and client, and a GWT Google Maps API client front end. This application allows for the search, retrieval, and download of planetary images and associated meta-data from the following missions: 2001 Mars Odyssey, Cassini, Galileo, LCROSS, Lunar Reconnaissance Orbiter, Mars Exploration Rover, Mars Express, Magellan, Mars Global Surveyor, Mars Pathfinder, Mars Reconnaissance Orbiter, MESSENGER, Phoe nix, Viking Lander, Viking Orbiter, and Voyager. The Atlas utilizes the UPC to translate mission-specific coordinate systems into a unified coordinate system, allowing the end user to query across missions of similar targets. If desired, the end user can also use a mission-specific view of the Atlas. The mission-specific views rely on the same code base. This application is a major improvement over the initial version of the Planetary Image Atlas. It is a multi-mission search engine. This tool includes both basic and advanced search capabilities, providing a product search tool to interrogate the collection of planetary images. This tool lets the end user query information about each image, and ignores the data that the user has no interest in. Users can reduce the number of images to look at by defining an area of interest with latitude and longitude ranges.

Research on image retrieval using deep convolutional neural network combining L1 regularization and PRelu activation function

NASA Astrophysics Data System (ADS)

QingJie, Wei; WenBin, Wang

2017-06-01

In this paper, the image retrieval using deep convolutional neural network combined with regularization and PRelu activation function is studied, and improves image retrieval accuracy. Deep convolutional neural network can not only simulate the process of human brain to receive and transmit information, but also contains a convolution operation, which is very suitable for processing images. Using deep convolutional neural network is better than direct extraction of image visual features for image retrieval. However, the structure of deep convolutional neural network is complex, and it is easy to over-fitting and reduces the accuracy of image retrieval. In this paper, we combine L1 regularization and PRelu activation function to construct a deep convolutional neural network to prevent over-fitting of the network and improve the accuracy of image retrieval

The Digital Fish Library: Using MRI to Digitize, Database, and Document the Morphological Diversity of Fish

PubMed Central

Berquist, Rachel M.; Gledhill, Kristen M.; Peterson, Matthew W.; Doan, Allyson H.; Baxter, Gregory T.; Yopak, Kara E.; Kang, Ning; Walker, H. J.; Hastings, Philip A.; Frank, Lawrence R.

2012-01-01

Museum fish collections possess a wealth of anatomical and morphological data that are essential for documenting and understanding biodiversity. Obtaining access to specimens for research, however, is not always practical and frequently conflicts with the need to maintain the physical integrity of specimens and the collection as a whole. Non-invasive three-dimensional (3D) digital imaging therefore serves a critical role in facilitating the digitization of these specimens for anatomical and morphological analysis as well as facilitating an efficient method for online storage and sharing of this imaging data. Here we describe the development of the Digital Fish Library (DFL, http://www.digitalfishlibrary.org), an online digital archive of high-resolution, high-contrast, magnetic resonance imaging (MRI) scans of the soft tissue anatomy of an array of fishes preserved in the Marine Vertebrate Collection of Scripps Institution of Oceanography. We have imaged and uploaded MRI data for over 300 marine and freshwater species, developed a data archival and retrieval system with a web-based image analysis and visualization tool, and integrated these into the public DFL website to disseminate data and associated metadata freely over the web. We show that MRI is a rapid and powerful method for accurately depicting the in-situ soft-tissue anatomy of preserved fishes in sufficient detail for large-scale comparative digital morphology. However these 3D volumetric data require a sophisticated computational and archival infrastructure in order to be broadly accessible to researchers and educators. PMID:22493695

The Digital Fish Library: using MRI to digitize, database, and document the morphological diversity of fish.

PubMed

Berquist, Rachel M; Gledhill, Kristen M; Peterson, Matthew W; Doan, Allyson H; Baxter, Gregory T; Yopak, Kara E; Kang, Ning; Walker, H J; Hastings, Philip A; Frank, Lawrence R

2012-01-01

Museum fish collections possess a wealth of anatomical and morphological data that are essential for documenting and understanding biodiversity. Obtaining access to specimens for research, however, is not always practical and frequently conflicts with the need to maintain the physical integrity of specimens and the collection as a whole. Non-invasive three-dimensional (3D) digital imaging therefore serves a critical role in facilitating the digitization of these specimens for anatomical and morphological analysis as well as facilitating an efficient method for online storage and sharing of this imaging data. Here we describe the development of the Digital Fish Library (DFL, http://www.digitalfishlibrary.org), an online digital archive of high-resolution, high-contrast, magnetic resonance imaging (MRI) scans of the soft tissue anatomy of an array of fishes preserved in the Marine Vertebrate Collection of Scripps Institution of Oceanography. We have imaged and uploaded MRI data for over 300 marine and freshwater species, developed a data archival and retrieval system with a web-based image analysis and visualization tool, and integrated these into the public DFL website to disseminate data and associated metadata freely over the web. We show that MRI is a rapid and powerful method for accurately depicting the in-situ soft-tissue anatomy of preserved fishes in sufficient detail for large-scale comparative digital morphology. However these 3D volumetric data require a sophisticated computational and archival infrastructure in order to be broadly accessible to researchers and educators.

RSAT 2018: regulatory sequence analysis tools 20th anniversary.

PubMed

Nguyen, Nga Thi Thuy; Contreras-Moreira, Bruno; Castro-Mondragon, Jaime A; Santana-Garcia, Walter; Ossio, Raul; Robles-Espinoza, Carla Daniela; Bahin, Mathieu; Collombet, Samuel; Vincens, Pierre; Thieffry, Denis; van Helden, Jacques; Medina-Rivera, Alejandra; Thomas-Chollier, Morgane

2018-05-02

RSAT (Regulatory Sequence Analysis Tools) is a suite of modular tools for the detection and the analysis of cis-regulatory elements in genome sequences. Its main applications are (i) motif discovery, including from genome-wide datasets like ChIP-seq/ATAC-seq, (ii) motif scanning, (iii) motif analysis (quality assessment, comparisons and clustering), (iv) analysis of regulatory variations, (v) comparative genomics. Six public servers jointly support 10 000 genomes from all kingdoms. Six novel or refactored programs have been added since the 2015 NAR Web Software Issue, including updated programs to analyse regulatory variants (retrieve-variation-seq, variation-scan, convert-variations), along with tools to extract sequences from a list of coordinates (retrieve-seq-bed), to select motifs from motif collections (retrieve-matrix), and to extract orthologs based on Ensembl Compara (get-orthologs-compara). Three use cases illustrate the integration of new and refactored tools to the suite. This Anniversary update gives a 20-year perspective on the software suite. RSAT is well-documented and available through Web sites, SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services, virtual machines and stand-alone programs at http://www.rsat.eu/.

Combining textual and visual information for image retrieval in the medical domain.

PubMed

Gkoufas, Yiannis; Morou, Anna; Kalamboukis, Theodore

2011-01-01

In this article we have assembled the experience obtained from our participation in the imageCLEF evaluation task over the past two years. Exploitation on the use of linear combinations for image retrieval has been attempted by combining visual and textual sources of images. From our experiments we conclude that a mixed retrieval technique that applies both textual and visual retrieval in an interchangeably repeated manner improves the performance while overcoming the scalability limitations of visual retrieval. In particular, the mean average precision (MAP) has increased from 0.01 to 0.15 and 0.087 for 2009 and 2010 data, respectively, when content-based image retrieval (CBIR) is performed on the top 1000 results from textual retrieval based on natural language processing (NLP).

An Electronic Tree Inventory for Arboriculture Management

NASA Astrophysics Data System (ADS)

Tait, Roger J.; Allen, Tony J.; Sherkat, Nasser; Bellett-Travers, Marcus D.

The integration of Global Positioning System (GPS) technology into mobile devices provides them with an awareness of their physical location. This geospatial context can be employed in a wide range of applications including locating nearby places of interest as well as guiding emergency services to incidents. In this research, a GPS-enabled Personal Digital Assistant (PDA) is used to create a computerised tree inventory for the management of arboriculture. Using the General Packet Radio Service (GPRS), GPS information and arboreal image data are sent to a web-server. An office-based PC running customised Geographical Information Software (GIS) then automatically retrieves the GPS tagged image data for display and analysis purposes. The resulting application allows an expert user to view the condition of individual trees in greater detail than is possible using remotely sensed imagery.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

PubMed

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming distance using the learned binary representation. A boosting algorithm is presented to efficiently learn the distance function. We evaluate the proposed algorithm on a mammographic image reference library with an Interactive Search-Assisted Decision Support (ISADS) system and on the medical image data set from ImageCLEF. Our results show that the boosting framework compares favorably to state-of-the-art approaches for distance metric learning in retrieval accuracy, with much lower computational cost. Additional evaluation with the COREL collection shows that our algorithm works well for regular image data sets.

Deeply learnt hashing forests for content based image retrieval in prostate MR images

NASA Astrophysics Data System (ADS)

Shah, Amit; Conjeti, Sailesh; Navab, Nassir; Katouzian, Amin

2016-03-01

Deluge in the size and heterogeneity of medical image databases necessitates the need for content based retrieval systems for their efficient organization. In this paper, we propose such a system to retrieve prostate MR images which share similarities in appearance and content with a query image. We introduce deeply learnt hashing forests (DL-HF) for this image retrieval task. DL-HF effectively leverages the semantic descriptiveness of deep learnt Convolutional Neural Networks. This is used in conjunction with hashing forests which are unsupervised random forests. DL-HF hierarchically parses the deep-learnt feature space to encode subspaces with compact binary code words. We propose a similarity preserving feature descriptor called Parts Histogram which is derived from DL-HF. Correlation defined on this descriptor is used as a similarity metric for retrieval from the database. Validations on publicly available multi-center prostate MR image database established the validity of the proposed approach. The proposed method is fully-automated without any user-interaction and is not dependent on any external image standardization like image normalization and registration. This image retrieval method is generalizable and is well-suited for retrieval in heterogeneous databases other imaging modalities and anatomies.

A new method of content based medical image retrieval and its applications to CT imaging sign retrieval.

PubMed

Ma, Ling; Liu, Xiabi; Gao, Yan; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu

2017-02-01

This paper proposes a new method of content based medical image retrieval through considering fused, context-sensitive similarity. Firstly, we fuse the semantic and visual similarities between the query image and each image in the database as their pairwise similarities. Then, we construct a weighted graph whose nodes represent the images and edges measure their pairwise similarities. By using the shortest path algorithm over the weighted graph, we obtain a new similarity measure, context-sensitive similarity measure, between the query image and each database image to complete the retrieval process. Actually, we use the fused pairwise similarity to narrow down the semantic gap for obtaining a more accurate pairwise similarity measure, and spread it on the intrinsic data manifold to achieve the context-sensitive similarity for a better retrieval performance. The proposed method has been evaluated on the retrieval of the Common CT Imaging Signs of Lung Diseases (CISLs) and achieved not only better retrieval results but also the satisfactory computation efficiency. Copyright © 2017 Elsevier Inc. All rights reserved.

Developer Network

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

2012-08-21

NREL's Developer Network, developer.nrel.gov, provides data that users can access to provide data to their own analyses, mobile and web applications. Developers can retrieve the data through a Web services API (application programming interface). The Developer Network handles overhead of serving up web services such as key management, authentication, analytics, reporting, documentation standards, and throttling in a common architecture, while allowing web services and APIs to be maintained and managed independently.

Scalable ranked retrieval using document images

NASA Astrophysics Data System (ADS)

Jain, Rajiv; Oard, Douglas W.; Doermann, David

2013-12-01

Despite the explosion of text on the Internet, hard copy documents that have been scanned as images still play a significant role for some tasks. The best method to perform ranked retrieval on a large corpus of document images, however, remains an open research question. The most common approach has been to perform text retrieval using terms generated by optical character recognition. This paper, by contrast, examines whether a scalable segmentation-free image retrieval algorithm, which matches sub-images containing text or graphical objects, can provide additional benefit in satisfying a user's information needs on a large, real world dataset. Results on 7 million scanned pages from the CDIP v1.0 test collection show that content based image retrieval finds a substantial number of documents that text retrieval misses, and that when used as a basis for relevance feedback can yield improvements in retrieval effectiveness.

Information Architecture for the Web: The IA Matrix Approach to Designing Children's Portals.

ERIC Educational Resources Information Center

Large, Andrew; Beheshti, Jamshid; Cole, Charles

2002-01-01

Presents a matrix that can serve as a tool for designing the information architecture of a Web portal in a logical and systematic manner. Highlights include interfaces; metaphors; navigation; interaction; information retrieval; and an example of a children's Web portal to provide access to museum information. (Author/LRW)

On the Nets. Comparing Web Browsers: Mosaic, Cello, Netscape, WinWeb and InternetWorks Life.

ERIC Educational Resources Information Center

Notess, Greg R.

1995-01-01

World Wide Web browsers are compared by speed, setup, hypertext transport protocol (HTTP) handling, management of file transfer protocol (FTP), telnet, gopher, and wide area information server (WAIS); bookmark options; and communication functions. Netscape has the most features, the fastest retrieval, sophisticated bookmark capabilities. (JMV)

A Semiotic Analysis of Icons on the World Wide Web.

ERIC Educational Resources Information Center

Ma, Yan

The World Wide Web allows users to interact with a graphic interface to search information in a hypermedia and multimedia environment. Graphics serve as reference points on the World Wide Web for searching and retrieving information. This study analyzed the culturally constructed syntax patterns, or codes, embedded in the icons of library…

Comprehensive Analysis of Semantic Web Reasoners and Tools: A Survey

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2017-01-01

Ontologies are emerging as best representation techniques for knowledge based context domains. The continuing need for interoperation, collaboration and effective information retrieval has lead to the creation of semantic web with the help of tools and reasoners which manages personalized information. The future of semantic web lies in an ontology…

Visits, Hits, Caching and Counting on the World Wide Web: Old Wine in New Bottles?

ERIC Educational Resources Information Center

Berthon, Pierre; Pitt, Leyland; Prendergast, Gerard

1997-01-01

Although web browser caching speeds up retrieval, reduces network traffic, and decreases the load on servers and browser's computers, an unintended consequence for marketing research is that Web servers undercount hits. This article explores counting problems, caching, proxy servers, trawler software and presents a series of correction factors…

Electronic Photography

NASA Technical Reports Server (NTRS)

Payne, Meredith Lindsay

1995-01-01

The main objective was to assist in the production of electronic images in the Electronic Photography Lab (EPL). The EPL is a new facility serving the electronic photographic needs of the Langley community. The purpose of the Electronic Photography lab is to provide Langley with access to digital imaging technology. Although the EPL has been in operation for less than one year, almost 1,000 images have been produced. The decision to establish the lab was made after careful determination of the centers needs for electronic photography. The LaRC community requires electronic photography for the production of electronic printing, Web sites, desktop publications, and its increased enhancement capabilities. In addition to general use, other considerations went into the planning of the EPL. For example, electronic photography is much less of a burden on the environment compared to conventional photography. Also, the possibilities of an on-line database and retrieval system could make locating past work more efficient. Finally, information in an electronic image is quantified, making measurements and calculations easier for the researcher.

Broadband Phase Retrieval for Image-Based Wavefront Sensing

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A focus-diverse phase-retrieval algorithm has been shown to perform adequately for the purpose of image-based wavefront sensing when (1) broadband light (typically spanning the visible spectrum) is used in forming the images by use of an optical system under test and (2) the assumption of monochromaticity is applied to the broadband image data. Heretofore, it had been assumed that in order to obtain adequate performance, it is necessary to use narrowband or monochromatic light. Some background information, including definitions of terms and a brief description of pertinent aspects of image-based phase retrieval, is prerequisite to a meaningful summary of the present development. Phase retrieval is a general term used in optics to denote estimation of optical imperfections or aberrations of an optical system under test. The term image-based wavefront sensing refers to a general class of algorithms that recover optical phase information, and phase-retrieval algorithms constitute a subset of this class. In phase retrieval, one utilizes the measured response of the optical system under test to produce a phase estimate. The optical response of the system is defined as the image of a point-source object, which could be a star or a laboratory point source. The phase-retrieval problem is characterized as image-based in the sense that a charge-coupled-device camera, preferably of scientific imaging quality, is used to collect image data where the optical system would normally form an image. In a variant of phase retrieval, denoted phase-diverse phase retrieval [which can include focus-diverse phase retrieval (in which various defocus planes are used)], an additional known aberration (or an equivalent diversity function) is superimposed as an aid in estimating unknown aberrations by use of an image-based wavefront-sensing algorithm. Image-based phase-retrieval differs from such other wavefront-sensing methods, such as interferometry, shearing interferometry, curvature wavefront sensing, and Shack-Hartmann sensing, all of which entail disadvantages in comparison with image-based methods. The main disadvantages of these non-image based methods are complexity of test equipment and the need for a wavefront reference.

Improved image retrieval based on fuzzy colour feature vector

NASA Astrophysics Data System (ADS)

Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

2013-03-01

One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

Kingfisher: a system for remote sensing image database management

NASA Astrophysics Data System (ADS)

Bruzzo, Michele; Giordano, Ferdinando; Dellepiane, Silvana G.

2003-04-01

At present retrieval methods in remote sensing image database are mainly based on spatial-temporal information. The increasing amount of images to be collected by the ground station of earth observing systems emphasizes the need for database management with intelligent data retrieval capabilities. The purpose of the proposed method is to realize a new content based retrieval system for remote sensing images database with an innovative search tool based on image similarity. This methodology is quite innovative for this application, at present many systems exist for photographic images, as for example QBIC and IKONA, but they are not able to extract and describe properly remote image content. The target database is set by an archive of images originated from an X-SAR sensor (spaceborne mission, 1994). The best content descriptors, mainly texture parameters, guarantees high retrieval performances and can be extracted without losses independently of image resolution. The latter property allows DBMS (Database Management System) to process low amount of information, as in the case of quick-look images, improving time performance and memory access without reducing retrieval accuracy. The matching technique has been designed to enable image management (database population and retrieval) independently of dimensions (width and height). Local and global content descriptors are compared, during retrieval phase, with the query image and results seem to be very encouraging.

High Resolution Trajectory-Based Smoke Forecasts Using VIIRS Aerosol Optical Depth and NUCAPS Carbon Monoxide Retrievals

NASA Astrophysics Data System (ADS)

Pierce, R. B.; Smith, N.; Barnet, C.; Barnet, C. D.; Kondragunta, S.; Davies, J. E.; Strabala, K.

2016-12-01

We use Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Aerosol Optical Depth (AOD) and combined Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) NOAA-Unique CrIS-ATMS Processing System (NUCAPS) carbon monoxide (CO) retrievals to initialize trajectory-based, high spatial resolution North American smoke dispersion forecasts during the May 2016 Fort McMurray wildfire in northern Alberta and the July 2016 Soberanes Fire in Northern California. These two case studies illustrate how long range transport of wild fire smoke can adversely impact surface air quality thousands of kilometers downwind and how local topographic flow can lead to complex transport patterns near the wildfire source region. The NUCAPS CO retrievals are shown to complement the high resolution VIIRS AOD retrievals by providing retrievals in partially cloudy scenes and also providing information on the vertical distribution of the wildfire smoke. This work addresses the need for low latency, web-based, high resolution forecasts of smoke dispersion for use by NWS Incident Meteorologists (IMET) to support on-site decision support services for fire incident management teams. The primary user community for the IDEA-I smoke forecasts is the Western regions of the NWS and US EPA due to the significant impacts of wildfires in these regions. Secondary users include Alaskan NWS offices and Western State and Local air quality management agencies such as the Western Regional Air Partnership (WRAP).

An object-oriented programming system for the integration of internet-based bioinformatics resources.

PubMed

Beveridge, Allan

2006-01-01

The Internet consists of a vast inhomogeneous reservoir of data. Developing software that can integrate a wide variety of different data sources is a major challenge that must be addressed for the realisation of the full potential of the Internet as a scientific research tool. This article presents a semi-automated object-oriented programming system for integrating web-based resources. We demonstrate that the current Internet standards (HTML, CGI [common gateway interface], Java, etc.) can be exploited to develop a data retrieval system that scans existing web interfaces and then uses a set of rules to generate new Java code that can automatically retrieve data from the Web. The validity of the software has been demonstrated by testing it on several biological databases. We also examine the current limitations of the Internet and discuss the need for the development of universal standards for web-based data.

Brain CT image similarity retrieval method based on uncertain location graph.

PubMed

Pan, Haiwei; Li, Pengyuan; Li, Qing; Han, Qilong; Feng, Xiaoning; Gao, Linlin

2014-03-01

A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases. However, the similarity retrieval for brain CT images requires much higher accuracy than the general images. In this paper, a new model of uncertain location graph (ULG) is presented for brain CT image modeling and similarity retrieval. According to the characteristics of brain CT image, we propose a novel method to model brain CT image to ULG based on brain CT image texture. Then, a scheme for ULG similarity retrieval is introduced. Furthermore, an effective index structure is applied to reduce the searching time. Experimental results reveal that our method functions well on brain CT images similarity retrieval with higher accuracy and efficiency.

Leveraging search and content exploration by exploiting context in folksonomy systems

NASA Astrophysics Data System (ADS)

Abel, Fabian; Baldoni, Matteo; Baroglio, Cristina; Henze, Nicola; Kawase, Ricardo; Krause, Daniel; Patti, Viviana

2010-04-01

With the advent of Web 2.0 tagging became a popular feature in social media systems. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. In the last years several researchers analyzed the impact of tags on information retrieval. Most works focused on tags only and ignored context information. In this article we present context-aware approaches for learning semantics and improve personalized information retrieval in tagging systems. We investigate how explorative search, initialized by clicking on tags, can be enhanced with automatically produced context information so that search results better fit to the actual information needs of the users. We introduce the SocialHITS algorithm and present an experiment where we compare different algorithms for ranking users, tags, and resources in a contextualized way. We showcase our approaches in the domain of images and present the TagMe! system that enables users to explore and tag Flickr pictures. In TagMe! we further demonstrate how advanced context information can easily be generated: TagMe! allows users to attach tag assignments to a specific area within an image and to categorize tag assignments. In our corresponding evaluation we show that those additional facets of tag assignments gain valuable semantics, which can be applied to improve existing search and ranking algorithms significantly.

Comparing the quality of accessing medical literature using content-based visual and textual information retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Kalpathy-Cramer, Jayashree; Kahn, Charles E., Jr.; Hersh, William

2009-02-01

Content-based visual information (or image) retrieval (CBIR) has been an extremely active research domain within medical imaging over the past ten years, with the goal of improving the management of visual medical information. Many technical solutions have been proposed, and application scenarios for image retrieval as well as image classification have been set up. However, in contrast to medical information retrieval using textual methods, visual retrieval has only rarely been applied in clinical practice. This is despite the large amount and variety of visual information produced in hospitals every day. This information overload imposes a significant burden upon clinicians, and CBIR technologies have the potential to help the situation. However, in order for CBIR to become an accepted clinical tool, it must demonstrate a higher level of technical maturity than it has to date. Since 2004, the ImageCLEF benchmark has included a task for the comparison of visual information retrieval algorithms for medical applications. In 2005, a task for medical image classification was introduced and both tasks have been run successfully for the past four years. These benchmarks allow an annual comparison of visual retrieval techniques based on the same data sets and the same query tasks, enabling the meaningful comparison of various retrieval techniques. The datasets used from 2004-2007 contained images and annotations from medical teaching files. In 2008, however, the dataset used was made up of 67,000 images (along with their associated figure captions and the full text of their corresponding articles) from two Radiological Society of North America (RSNA) scientific journals. This article describes the results of the medical image retrieval task of the ImageCLEF 2008 evaluation campaign. We compare the retrieval results of both visual and textual information retrieval systems from 15 research groups on the aforementioned data set. The results show clearly that, currently, visual retrieval alone does not achieve the performance necessary for real-world clinical applications. Most of the common visual retrieval techniques have a MAP (Mean Average Precision) of around 2-3%, which is much lower than that achieved using textual retrieval (MAP=29%). Advanced machine learning techniques, together with good training data, have been shown to improve the performance of visual retrieval systems in the past. Multimodal retrieval (basing retrieval on both visual and textual information) can achieve better results than purely visual, but only when carefully applied. In many cases, multimodal retrieval systems performed even worse than purely textual retrieval systems. On the other hand, some multimodal retrieval systems demonstrated significantly increased early precision, which has been shown to be a desirable behavior in real-world systems.

Globe Teachers Guide and Photographic Data on the Web

NASA Technical Reports Server (NTRS)

Kowal, Dan

2004-01-01

The task of managing the GLOBE Online Teacher s Guide during this time period focused on transforming the technology behind the delivery system of this document. The web application transformed from a flat file retrieval system to a dynamic database access approach. The new methodology utilizes Java Server Pages (JSP) on the front-end and an Oracle relational database on the backend. This new approach allows users of the web site, mainly teachers, to access content efficiently by grade level and/or by investigation or educational concept area. Moreover, teachers can gain easier access to data sheets and lab and field guides. The new online guide also included updated content for all GLOBE protocols. The GLOBE web management team was given documentation for maintaining the new application. Instructions for modifying the JSP templates and managing database content were included in this document. It was delivered to the team by the end of October, 2003. The National Geophysical Data Center (NGDC) continued to manage the school study site photos on the GLOBE website. 333 study site photo images were added to the GLOBE database and posted on the web during this same time period for 64 schools. Documentation for processing study site photos was also delivered to the new GLOBE web management team. Lastly, assistance was provided in transferring reference applications such as the Cloud and LandSat quizzes and Earth Systems Online Poster from NGDC servers to GLOBE servers along with documentation for maintaining these applications.

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

PubMed Central

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-01-01

Background DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. Results GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. Conclusion GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at . PMID:19728865

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

PubMed

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-09-03

DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at http://cgs.pharm.kyoto-u.ac.jp/services/network.

Medical image retrieval system using multiple features from 3D ROIs

NASA Astrophysics Data System (ADS)

Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

2012-02-01

Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

PubMed

Ashraf, Rehan; Ahmed, Mudassar; Jabbar, Sohail; Khalid, Shehzad; Ahmad, Awais; Din, Sadia; Jeon, Gwangil

2018-01-25

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance. The color, shape and texture are the examples of low-level image features. The feature plays a significant role in image processing. The powerful representation of an image is known as feature vector and feature extraction techniques are applied to get features that will be useful in classifying and recognition of images. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. In this paper, we are going to discuss various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique will be better. The effectiveness of the CBIR approach is fundamentally based on feature extraction. In image processing errands like object recognition and image retrieval feature descriptor is an immense among the most essential step. The main idea of CBIR is that it can search related images to an image passed as query from a dataset got by using distance metrics. The proposed method is explained for image retrieval constructed on YCbCr color with canny edge histogram and discrete wavelet transform. The combination of edge of histogram and discrete wavelet transform increase the performance of image retrieval framework for content based search. The execution of different wavelets is additionally contrasted with discover the suitability of specific wavelet work for image retrieval. The proposed algorithm is prepared and tried to implement for Wang image database. For Image Retrieval Purpose, Artificial Neural Networks (ANN) is used and applied on standard dataset in CBIR domain. The execution of the recommended descriptors is assessed by computing both Precision and Recall values and compared with different other proposed methods with demonstrate the predominance of our method. The efficiency and effectiveness of the proposed approach outperforms the existing research in term of average precision and recall values.

Evaluating performance of biomedical image retrieval systems – an overview of the medical image retrieval task at ImageCLEF 2004–2013

PubMed Central

Kalpathy-Cramer, Jayashree; de Herrera, Alba García Seco; Demner-Fushman, Dina; Antani, Sameer; Bedrick, Steven; Müller, Henning

2014-01-01

Medical image retrieval and classification have been extremely active research topics over the past 15 years. With the ImageCLEF benchmark in medical image retrieval and classification a standard test bed was created that allows researchers to compare their approaches and ideas on increasingly large and varied data sets including generated ground truth. This article describes the lessons learned in ten evaluations campaigns. A detailed analysis of the data also highlights the value of the resources created. PMID:24746250

Multiple Object Retrieval in Image Databases Using Hierarchical Segmentation Tree

ERIC Educational Resources Information Center

Chen, Wei-Bang

2012-01-01

The purpose of this research is to develop a new visual information analysis, representation, and retrieval framework for automatic discovery of salient objects of user's interest in large-scale image databases. In particular, this dissertation describes a content-based image retrieval framework which supports multiple-object retrieval. The…

E-Referencer: Transforming Boolean OPACs to Web Search Engines.

ERIC Educational Resources Information Center

Khoo, Christopher S. G.; Poo, Danny C. C.; Toh, Teck-Kang; Hong, Glenn

E-Referencer is an expert intermediary system for searching library online public access catalogs (OPACs) on the World Wide Web. It is implemented as a proxy server that mediates the interaction between the user and Boolean OPACs. It transforms a Boolean OPAC into a retrieval system with many of the search capabilities of Web search engines.…

Users' Perceptions of the Web As Revealed by Transaction Log Analysis.

ERIC Educational Resources Information Center

Moukdad, Haidar; Large, Andrew

2001-01-01

Describes the results of a transaction log analysis of a Web search engine, WebCrawler, to analyze user's queries for information retrieval. Results suggest most users do not employ advanced search features, and the linguistic structure often resembles a human-human communication model that is not always successful in human-computer communication.…

Dancing with the Web: Students Bring Meaning to the Semantic Web

ERIC Educational Resources Information Center

Brooks, Pauline

2012-01-01

This article will discuss the issues concerning the storage, retrieval and use of multimedia technology in dance, and how semantic web technologies can support those requirements. It will identify the key aims and outcomes of four international telematic dance projects, and review the use of reflective practice to engage students in their learning…

A WWW-Based Archive and Retrieval System for Multimedia

NASA Technical Reports Server (NTRS)

Hyon, J.; Sorensen, S.; Martin, M.; Kawasaki, K.; Takacs, M.

1996-01-01

This paper describes the Data Distribution Laboratory (DDL) and discusses issues involved in building multimedia CD-ROMs. It describes the modeling philosophy for cataloging multimedia products and the worldwide-web (WWW)-based multimedia archive and retrieval system (Webcat) built on that model.

Theoretical and Empirical Comparison of Big Data Image Processing with Apache Hadoop and Sun Grid Engine

PubMed Central

Bao, Shunxing; Weitendorf, Frederick D.; Plassard, Andrew J.; Huo, Yuankai; Gokhale, Aniruddha; Landman, Bennett A.

2016-01-01

The field of big data is generally concerned with the scale of processing at which traditional computational paradigms break down. In medical imaging, traditional large scale processing uses a cluster computer that combines a group of workstation nodes into a functional unit that is controlled by a job scheduler. Typically, a shared-storage network file system (NFS) is used to host imaging data. However, data transfer from storage to processing nodes can saturate network bandwidth when data is frequently uploaded/retrieved from the NFS, e.g., “short” processing times and/or “large” datasets. Recently, an alternative approach using Hadoop and HBase was presented for medical imaging to enable co-location of data storage and computation while minimizing data transfer. The benefits of using such a framework must be formally evaluated against a traditional approach to characterize the point at which simply “large scale” processing transitions into “big data” and necessitates alternative computational frameworks. The proposed Hadoop system was implemented on a production lab-cluster alongside a standard Sun Grid Engine (SGE). Theoretical models for wall-clock time and resource time for both approaches are introduced and validated. To provide real example data, three T1 image archives were retrieved from a university secure, shared web database and used to empirically assess computational performance under three configurations of cluster hardware (using 72, 109, or 209 CPU cores) with differing job lengths. Empirical results match the theoretical models. Based on these data, a comparative analysis is presented for when the Hadoop framework will be relevant and non-relevant for medical imaging. PMID:28736473

Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining

PubMed Central

Sadesh, S.; Suganthe, R. C.

2015-01-01

Web with tremendous volume of information retrieves result for user related queries. With the rapid growth of web page recommendation, results retrieved based on data mining techniques did not offer higher performance filtering rate because relationships between user profile and queries were not analyzed in an extensive manner. At the same time, existing user profile based prediction in web data mining is not exhaustive in producing personalized result rate. To improve the query result rate on dynamics of user behavior over time, Hamilton Filtered Regime Switching User Query Probability (HFRS-UQP) framework is proposed. HFRS-UQP framework is split into two processes, where filtering and switching are carried out. The data mining based filtering in our research work uses the Hamilton Filtering framework to filter user result based on personalized information on automatic updated profiles through search engine. Maximized result is fetched, that is, filtered out with respect to user behavior profiles. The switching performs accurate filtering updated profiles using regime switching. The updating in profile change (i.e., switches) regime in HFRS-UQP framework identifies the second- and higher-order association of query result on the updated profiles. Experiment is conducted on factors such as personalized information search retrieval rate, filtering efficiency, and precision ratio. PMID:26221626

Development of a web-based video management and application processing system

NASA Astrophysics Data System (ADS)

Chan, Shermann S.; Wu, Yi; Li, Qing; Zhuang, Yueting

2001-07-01

How to facilitate efficient video manipulation and access in a web-based environment is becoming a popular trend for video applications. In this paper, we present a web-oriented video management and application processing system, based on our previous work on multimedia database and content-based retrieval. In particular, we extend the VideoMAP architecture with specific web-oriented mechanisms, which include: (1) Concurrency control facilities for the editing of video data among different types of users, such as Video Administrator, Video Producer, Video Editor, and Video Query Client; different users are assigned various priority levels for different operations on the database. (2) Versatile video retrieval mechanism which employs a hybrid approach by integrating a query-based (database) mechanism with content- based retrieval (CBR) functions; its specific language (CAROL/ST with CBR) supports spatio-temporal semantics of video objects, and also offers an improved mechanism to describe visual content of videos by content-based analysis method. (3) Query profiling database which records the `histories' of various clients' query activities; such profiles can be used to provide the default query template when a similar query is encountered by the same kind of users. An experimental prototype system is being developed based on the existing VideoMAP prototype system, using Java and VC++ on the PC platform.

An automatic method for retrieving and indexing catalogues of biomedical courses.

PubMed

Maojo, Victor; de la Calle, Guillermo; García-Remesal, Miguel; Bankauskaite, Vaida; Crespo, Jose

2008-11-06

Although there is wide information about Biomedical Informatics education and courses in different Websites, information is usually not exhaustive and difficult to update. We propose a new methodology based on information retrieval techniques for extracting, indexing and retrieving automatically information about educational offers. A web application has been developed to make available such information in an inventory of courses and educational offers.

Near-Real-Time Satellite Cloud Products for Icing Detection and Aviation Weather over the USA

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Smith, William L., Jr.; Nguyen, Louis; Murray, J. J.; Heck, Patrick W.; Khaiyer, Mandana M.

2003-01-01

A set of physically based retrieval algorithms has been developed to derive from multispectral satellite imagery a variety of cloud properties that can be used to diagnose icing conditions when upper-level clouds are absent. The algorithms are being applied in near-real time to the Geostationary Operational Environmental Satellite (GOES) data over Florida, the Southern Great Plains, and the midwestern USA. The products are available in image and digital formats on the world-wide web. The analysis system is being upgraded to analyze GOES data over the CONUS. Validation, 24-hour processing, and operational issues are discussed.

Understanding human quality judgment in assessing online forum contents for thread retrieval purpose

NASA Astrophysics Data System (ADS)

Ismail, Zuriati; Salim, Naomie; Huspi, Sharin Hazlin

2017-10-01

Compared to traditional materials or journals, user-generated contents are not peer-reviewed. Lack of quality control and the explosive growth of web contents make the task of finding quality information on the web especially critical. The existence of new facilities for producing web contents such as forum makes this issue more significant. This study focuses on online forums threads or discussion, where the forums contain valuable human-generated information in a form of discussions. Due to the unique structure of the online forum pages, special techniques are required to organize and search for information in these forums. Quality biased retrieval is a retrieval approach that search for relevant document and prioritized higher quality documents. Despite major concern of quality content and recent development of quality biased retrieval, there is an urgent need to understand how quality content is being judged, for retrieval and performance evaluation purposes. Furthermore, even though there are various studies on the quality of information, there is no standard framework that has been established. The primary aim of this paper is to contribute to the understanding of human quality judgment in assessing online forum contents. The foundation of this study is to compare and evaluate different frameworks (for quality biased retrieval and information quality). This led to the finding that many quality dimensions are redundant and some dimensions are understood differently between different studies. We conducted a survey on crowdsourcing community to measure the importance of each quality dimensions found in various frameworks. Accuracy and ease of understanding are among top important dimensions while threads popularity and contents manipulability are among least important dimensions. This finding is beneficial in evaluating contents of online forum.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Data augmentation-assisted deep learning of hand-drawn partially colored sketches for visual search

PubMed Central

Muhammad, Khan; Baik, Sung Wook

2017-01-01

In recent years, image databases are growing at exponential rates, making their management, indexing, and retrieval, very challenging. Typical image retrieval systems rely on sample images as queries. However, in the absence of sample query images, hand-drawn sketches are also used. The recent adoption of touch screen input devices makes it very convenient to quickly draw shaded sketches of objects to be used for querying image databases. This paper presents a mechanism to provide access to visual information based on users’ hand-drawn partially colored sketches using touch screen devices. A key challenge for sketch-based image retrieval systems is to cope with the inherent ambiguity in sketches due to the lack of colors, textures, shading, and drawing imperfections. To cope with these issues, we propose to fine-tune a deep convolutional neural network (CNN) using augmented dataset to extract features from partially colored hand-drawn sketches for query specification in a sketch-based image retrieval framework. The large augmented dataset contains natural images, edge maps, hand-drawn sketches, de-colorized, and de-texturized images which allow CNN to effectively model visual contents presented to it in a variety of forms. The deep features extracted from CNN allow retrieval of images using both sketches and full color images as queries. We also evaluated the role of partial coloring or shading in sketches to improve the retrieval performance. The proposed method is tested on two large datasets for sketch recognition and sketch-based image retrieval and achieved better classification and retrieval performance than many existing methods. PMID:28859140

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Alkemio: association of chemicals with biomedical topics by text and data mining

PubMed Central

Gijón-Correas, José A.; Andrade-Navarro, Miguel A.; Fontaine, Jean F.

2014-01-01

The PubMed® database of biomedical citations allows the retrieval of scientific articles studying the function of chemicals in biology and medicine. Mining millions of available citations to search reported associations between chemicals and topics of interest would require substantial human time. We have implemented the Alkemio text mining web tool and SOAP web service to help in this task. The tool uses biomedical articles discussing chemicals (including drugs), predicts their relatedness to the query topic with a naïve Bayesian classifier and ranks all chemicals by P-values computed from random simulations. Benchmarks on seven human pathways showed good retrieval performance (areas under the receiver operating characteristic curves ranged from 73.6 to 94.5%). Comparison with existing tools to retrieve chemicals associated to eight diseases showed the higher precision and recall of Alkemio when considering the top 10 candidate chemicals. Alkemio is a high performing web tool ranking chemicals for any biomedical topics and it is free to non-commercial users. Availability: http://cbdm.mdc-berlin.de/∼medlineranker/cms/alkemio. PMID:24838570

Query-Structure Based Web Page Indexing

DTIC Science & Technology

2012-11-01

the massive amount of data present on the web. In our third participation in the web track at TREC 2012, we explore the idea of building an...the ad-hoc and diversity task. 1 INTRODUCTION The rapid growth and massive quantities of data on the Internet have increased the importance and...complexity of information retrieval systems. The amount and the diversity of the web data introduce shortcomings in the way search engines rank their

Beyond Information Retrieval: Ways To Provide Content in Context.

ERIC Educational Resources Information Center

Wiley, Deborah Lynne

1998-01-01

Provides an overview of information retrieval from mainframe systems to Web search engines; discusses collaborative filtering, data extraction, data visualization, agent technology, pattern recognition, classification and clustering, and virtual communities. Argues that rather than huge data-storage centers and proprietary software, we need…

Mobile object retrieval in server-based image databases

NASA Astrophysics Data System (ADS)

Manger, D.; Pagel, F.; Widak, H.

2013-05-01

The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.

Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

PubMed

Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

2014-02-01

Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics.

PubMed

Sharma, Harshita; Alekseychuk, Alexander; Leskovsky, Peter; Hellwich, Olaf; Anand, R S; Zerbe, Norman; Hufnagl, Peter

2012-10-04

Computer-based analysis of digitalized histological images has been gaining increasing attention, due to their extensive use in research and routine practice. The article aims to contribute towards the description and retrieval of histological images by employing a structural method using graphs. Due to their expressive ability, graphs are considered as a powerful and versatile representation formalism and have obtained a growing consideration especially by the image processing and computer vision community. The article describes a novel method for determining similarity between histological images through graph-theoretic description and matching, for the purpose of content-based retrieval. A higher order (region-based) graph-based representation of breast biopsy images has been attained and a tree-search based inexact graph matching technique has been employed that facilitates the automatic retrieval of images structurally similar to a given image from large databases. The results obtained and evaluation performed demonstrate the effectiveness and superiority of graph-based image retrieval over a common histogram-based technique. The employed graph matching complexity has been reduced compared to the state-of-the-art optimal inexact matching methods by applying a pre-requisite criterion for matching of nodes and a sophisticated design of the estimation function, especially the prognosis function. The proposed method is suitable for the retrieval of similar histological images, as suggested by the experimental and evaluation results obtained in the study. It is intended for the use in Content Based Image Retrieval (CBIR)-requiring applications in the areas of medical diagnostics and research, and can also be generalized for retrieval of different types of complex images. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1224798882787923.

Determining similarity in histological images using graph-theoretic description and matching methods for content-based image retrieval in medical diagnostics

PubMed Central

2012-01-01

Background Computer-based analysis of digitalized histological images has been gaining increasing attention, due to their extensive use in research and routine practice. The article aims to contribute towards the description and retrieval of histological images by employing a structural method using graphs. Due to their expressive ability, graphs are considered as a powerful and versatile representation formalism and have obtained a growing consideration especially by the image processing and computer vision community. Methods The article describes a novel method for determining similarity between histological images through graph-theoretic description and matching, for the purpose of content-based retrieval. A higher order (region-based) graph-based representation of breast biopsy images has been attained and a tree-search based inexact graph matching technique has been employed that facilitates the automatic retrieval of images structurally similar to a given image from large databases. Results The results obtained and evaluation performed demonstrate the effectiveness and superiority of graph-based image retrieval over a common histogram-based technique. The employed graph matching complexity has been reduced compared to the state-of-the-art optimal inexact matching methods by applying a pre-requisite criterion for matching of nodes and a sophisticated design of the estimation function, especially the prognosis function. Conclusion The proposed method is suitable for the retrieval of similar histological images, as suggested by the experimental and evaluation results obtained in the study. It is intended for the use in Content Based Image Retrieval (CBIR)-requiring applications in the areas of medical diagnostics and research, and can also be generalized for retrieval of different types of complex images. Virtual Slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1224798882787923. PMID:23035717

Global polar geospatial information service retrieval based on search engine and ontology reasoning

USGS Publications Warehouse

Chen, Nengcheng; E, Dongcheng; Di, Liping; Gong, Jianya; Chen, Zeqiang

2007-01-01

In order to improve the access precision of polar geospatial information service on web, a new methodology for retrieving global spatial information services based on geospatial service search and ontology reasoning is proposed, the geospatial service search is implemented to find the coarse service from web, the ontology reasoning is designed to find the refined service from the coarse service. The proposed framework includes standardized distributed geospatial web services, a geospatial service search engine, an extended UDDI registry, and a multi-protocol geospatial information service client. Some key technologies addressed include service discovery based on search engine and service ontology modeling and reasoning in the Antarctic geospatial context. Finally, an Antarctica multi protocol OWS portal prototype based on the proposed methodology is introduced.

A brief introduction to web-based genome browsers.

PubMed

Wang, Jun; Kong, Lei; Gao, Ge; Luo, Jingchu

2013-03-01

Genome browser provides a graphical interface for users to browse, search, retrieve and analyze genomic sequence and annotation data. Web-based genome browsers can be classified into general genome browsers with multiple species and species-specific genome browsers. In this review, we attempt to give an overview for the main functions and features of web-based genome browsers, covering data visualization, retrieval, analysis and customization. To give a brief introduction to the multiple-species genome browser, we describe the user interface and main functions of the Ensembl and UCSC genome browsers using the human alpha-globin gene cluster as an example. We further use the MSU and the Rice-Map genome browsers to show some special features of species-specific genome browser, taking a rice transcription factor gene OsSPL14 as an example.

A content-based image retrieval method for optical colonoscopy images based on image recognition techniques

NASA Astrophysics Data System (ADS)

Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro

2015-03-01

This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.

Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

NASA Astrophysics Data System (ADS)

Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang

2017-12-01

In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.

Document image database indexing with pictorial dictionary

NASA Astrophysics Data System (ADS)

Akbari, Mohammad; Azimi, Reza

2010-02-01

In this paper we introduce a new approach for information retrieval from Persian document image database without using Optical Character Recognition (OCR).At first an attribute called subword upper contour label is defined then, a pictorial dictionary is constructed based on this attribute for the subwords. By this approach we address two issues in document image retrieval: keyword spotting and retrieval according to the document similarities. The proposed methods have been evaluated on a Persian document image database. The results have proved the ability of this approach in document image information retrieval.

Comparing features sets for content-based image retrieval in a medical-case database

NASA Astrophysics Data System (ADS)

Muller, Henning; Rosset, Antoine; Vallee, Jean-Paul; Geissbuhler, Antoine

2004-04-01

Content-based image retrieval systems (CBIRSs) have frequently been proposed for the use in medical image databases and PACS. Still, only few systems were developed and used in a real clinical environment. It rather seems that medical professionals define their needs and computer scientists develop systems based on data sets they receive with little or no interaction between the two groups. A first study on the diagnostic use of medical image retrieval also shows an improvement in diagnostics when using CBIRSs which underlines the potential importance of this technique. This article explains the use of an open source image retrieval system (GIFT - GNU Image Finding Tool) for the retrieval of medical images in the medical case database system CasImage that is used in daily, clinical routine in the university hospitals of Geneva. Although the base system of GIFT shows an unsatisfactory performance, already little changes in the feature space show to significantly improve the retrieval results. The performance of variations in feature space with respect to color (gray level) quantizations and changes in texture analysis (Gabor filters) is compared. Whereas stock photography relies mainly on colors for retrieval, medical images need a large number of gray levels for successful retrieval, especially when executing feedback queries. The results also show that a too fine granularity in the gray levels lowers the retrieval quality, especially with single-image queries. For the evaluation of the retrieval peformance, a subset of the entire case database of more than 40,000 images is taken with a total of 3752 images. Ground truth was generated by a user who defined the expected query result of a perfect system by selecting images relevant to a given query image. The results show that a smaller number of gray levels (32 - 64) leads to a better retrieval performance, especially when using relevance feedback. The use of more scales and directions for the Gabor filters in the texture analysis also leads to improved results but response time is going up equally due to the larger feature space. CBIRSs can be of great use in managing large medical image databases. They allow to find images that might otherwise be lost for research and publications. They also give students students the possibility to navigate within large image repositories. In the future, CBIR might also become more important in case-based reasoning and evidence-based medicine to support the diagnostics because first studies show good results.

Estimation of chromatic errors from broadband images for high contrast imaging

NASA Astrophysics Data System (ADS)

Sirbu, Dan; Belikov, Ruslan

2015-09-01

Usage of an internal coronagraph with an adaptive optical system for wavefront correction for direct imaging of exoplanets is currently being considered for many mission concepts, including as an instrument addition to the WFIRST-AFTA mission to follow the James Web Space Telescope. The main technical challenge associated with direct imaging of exoplanets with an internal coronagraph is to effectively control both the diffraction and scattered light from the star so that the dim planetary companion can be seen. For the deformable mirror (DM) to recover a dark hole region with sufficiently high contrast in the image plane, wavefront errors are usually estimated using probes on the DM. To date, most broadband lab demonstrations use narrowband filters to estimate the chromaticity of the wavefront error, but this reduces the photon flux per filter and requires a filter system. Here, we propose a method to estimate the chromaticity of wavefront errors using only a broadband image. This is achieved by using special DM probes that have sufficient chromatic diversity. As a case example, we simulate the retrieval of the spectrum of the central wavelength from broadband images for a simple shaped- pupil coronagraph with a conjugate DM and compute the resulting estimation error.

Supervised graph hashing for histopathology image retrieval and classification.

PubMed

Shi, Xiaoshuang; Xing, Fuyong; Xu, KaiDi; Xie, Yuanpu; Su, Hai; Yang, Lin

2017-12-01

In pathology image analysis, morphological characteristics of cells are critical to grade many diseases. With the development of cell detection and segmentation techniques, it is possible to extract cell-level information for further analysis in pathology images. However, it is challenging to conduct efficient analysis of cell-level information on a large-scale image dataset because each image usually contains hundreds or thousands of cells. In this paper, we propose a novel image retrieval based framework for large-scale pathology image analysis. For each image, we encode each cell into binary codes to generate image representation using a novel graph based hashing model and then conduct image retrieval by applying a group-to-group matching method to similarity measurement. In order to improve both computational efficiency and memory requirement, we further introduce matrix factorization into the hashing model for scalable image retrieval. The proposed framework is extensively validated with thousands of lung cancer images, and it achieves 97.98% classification accuracy and 97.50% retrieval precision with all cells of each query image used. Copyright © 2017 Elsevier B.V. All rights reserved.

On combining image-based and ontological semantic dissimilarities for medical image retrieval applications

PubMed Central

Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F.; Rubin, Daniel L.

2014-01-01

Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic “soft” prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs of images on a 25-images dataset, and evaluation relative to the diagnoses of the retrieved images on a 72-images dataset. A normalized discounted cumulative gain (NDCG) score of more than 0.92 was obtained with the first protocol, while AUC scores of more than 0.77 were obtained with the second protocol. This automatical approach could provide real-time decision support to radiologists by showing them similar images with associated diagnoses and, where available, responses to therapies. PMID:25036769

Table Extraction from Web Pages Using Conditional Random Fields to Extract Toponym Related Data

NASA Astrophysics Data System (ADS)

Luthfi Hanifah, Hayyu'; Akbar, Saiful

2017-01-01

Table is one of the ways to visualize information on web pages. The abundant number of web pages that compose the World Wide Web has been the motivation of information extraction and information retrieval research, including the research for table extraction. Besides, there is a need for a system which is designed to specifically handle location-related information. Based on this background, this research is conducted to provide a way to extract location-related data from web tables so that it can be used in the development of Geographic Information Retrieval (GIR) system. The location-related data will be identified by the toponym (location name). In this research, a rule-based approach with gazetteer is used to recognize toponym from web table. Meanwhile, to extract data from a table, a combination of rule-based approach and statistical-based approach is used. On the statistical-based approach, Conditional Random Fields (CRF) model is used to understand the schema of the table. The result of table extraction is presented on JSON format. If a web table contains toponym, a field will be added on the JSON document to store the toponym values. This field can be used to index the table data in accordance to the toponym, which then can be used in the development of GIR system.

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

Improving data management and dissemination in web based information systems by semantic enrichment of descriptive data aspects

NASA Astrophysics Data System (ADS)

Gebhardt, Steffen; Wehrmann, Thilo; Klinger, Verena; Schettler, Ingo; Huth, Juliane; Künzer, Claudia; Dech, Stefan

2010-10-01

The German-Vietnamese water-related information system for the Mekong Delta (WISDOM) project supports business processes in Integrated Water Resources Management in Vietnam. Multiple disciplines bring together earth and ground based observation themes, such as environmental monitoring, water management, demographics, economy, information technology, and infrastructural systems. This paper introduces the components of the web-based WISDOM system including data, logic and presentation tier. It focuses on the data models upon which the database management system is built, including techniques for tagging or linking metadata with the stored information. The model also uses ordered groupings of spatial, thematic and temporal reference objects to semantically tag datasets to enable fast data retrieval, such as finding all data in a specific administrative unit belonging to a specific theme. A spatial database extension is employed by the PostgreSQL database. This object-oriented database was chosen over a relational database to tag spatial objects to tabular data, improving the retrieval of census and observational data at regional, provincial, and local areas. While the spatial database hinders processing raster data, a "work-around" was built into WISDOM to permit efficient management of both raster and vector data. The data model also incorporates styling aspects of the spatial datasets through styled layer descriptions (SLD) and web mapping service (WMS) layer specifications, allowing retrieval of rendered maps. Metadata elements of the spatial data are based on the ISO19115 standard. XML structured information of the SLD and metadata are stored in an XML database. The data models and the data management system are robust for managing the large quantity of spatial objects, sensor observations, census and document data. The operational WISDOM information system prototype contains modules for data management, automatic data integration, and web services for data retrieval, analysis, and distribution. The graphical user interfaces facilitate metadata cataloguing, data warehousing, web sensor data analysis and thematic mapping.

Web Conversations About Complementary and Alternative Medicines and Cancer: Content and Sentiment Analysis.

PubMed

Mazzocut, Mauro; Truccolo, Ivana; Antonini, Marialuisa; Rinaldi, Fabio; Omero, Paolo; Ferrarin, Emanuela; De Paoli, Paolo; Tasso, Carlo

2016-06-16

The use of complementary and alternative medicine (CAM) among cancer patients is widespread and mostly self-administrated. Today, one of the most relevant topics is the nondisclosure of CAM use to doctors. This general lack of communication exposes patients to dangerous behaviors and to less reliable information channels, such as the Web. The Italian context scarcely differs from this trend. Today, we are able to mine and analyze systematically the unstructured information available in the Web, to get an insight of people's opinions, beliefs, and rumors concerning health topics. Our aim was to analyze Italian Web conversations about CAM, identifying the most relevant Web sources, therapies, and diseases and measure the related sentiment. Data have been collected using the Web Intelligence tool ifMONITOR. The workflow consisted of 6 phases: (1) eligibility criteria definition for the ifMONITOR search profile; (2) creation of a CAM terminology database; (3) generic Web search and automatic filtering, the results have been manually revised to refine the search profile, and stored in the ifMONITOR database; (4) automatic classification using the CAM database terms; (5) selection of the final sample and manual sentiment analysis using a 1-5 score range; (6) manual indexing of the Web sources and CAM therapies type retrieved. Descriptive univariate statistics were computed for each item: absolute frequency, percentage, central tendency (mean sentiment score [MSS]), and variability (standard variation σ). Overall, 212 Web sources, 423 Web documents, and 868 opinions have been retrieved. The overall sentiment measured tends to a good score (3.6 of 5). Quite a high polarization in the opinions of the conversation partaking emerged from standard variation analysis (σ≥1). In total, 126 of 212 (59.4%) Web sources retrieved were nonhealth-related. Facebook (89; 21%) and Yahoo Answers (41; 9.7%) were the most relevant. In total, 94 CAM therapies have been retrieved. Most belong to the "biologically based therapies or nutrition" category: 339 of 868 opinions (39.1%), showing an MSS of 3.9 (σ=0.83). Within nutrition, "diets" collected 154 opinions (18.4%) with an MSS of 3.8 (σ=0.87); "food as CAM" overall collected 112 opinions (12.8%) with a MSS of 4 (σ=0.68). Excluding diets and food, the most discussed CAM therapy is the controversial Italian "Di Bella multitherapy" with 102 opinions (11.8%) with an MSS of 3.4 (σ=1.21). Breast cancer was the most mentioned disease: 81 opinions of 868. Conversations about CAM and cancer are ubiquitous. There is a great concern about the biologically based therapies, perceived as harmless and useful, under-rating all risks related to dangerous interactions or malnutrition. Our results can be useful to doctors to be aware of the implications of these beliefs for the clinical practice. Web conversation exploitation could be a strategy to gain insights of people's perspective for other controversial topics.

Design and implementation of CUAHSI WaterML and WaterOneFlow Web Services

NASA Astrophysics Data System (ADS)

Valentine, D. W.; Zaslavsky, I.; Whitenack, T.; Maidment, D.

2007-12-01

WaterOneFlow is a term for a group of web services created by and for the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) community. CUAHSI web services facilitate the retrieval of hydrologic observations information from online data sources using the SOAP protocol. CUAHSI Water Markup Language (below referred to as WaterML) is an XML schema defining the format of messages returned by the WaterOneFlow web services. \

Extraction and labeling high-resolution images from PDF documents

NASA Astrophysics Data System (ADS)

Chachra, Suchet K.; Xue, Zhiyun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Accuracy of content-based image retrieval is affected by image resolution among other factors. Higher resolution images enable extraction of image features that more accurately represent the image content. In order to improve the relevance of search results for our biomedical image search engine, Open-I, we have developed techniques to extract and label high-resolution versions of figures from biomedical articles supplied in the PDF format. Open-I uses the open-access subset of biomedical articles from the PubMed Central repository hosted by the National Library of Medicine. Articles are available in XML and in publisher supplied PDF formats. As these PDF documents contain little or no meta-data to identify the embedded images, the task includes labeling images according to their figure number in the article after they have been successfully extracted. For this purpose we use the labeled small size images provided with the XML web version of the article. This paper describes the image extraction process and two alternative approaches to perform image labeling that measure the similarity between two images based upon the image intensity projection on the coordinate axes and similarity based upon the normalized cross-correlation between the intensities of two images. Using image identification based on image intensity projection, we were able to achieve a precision of 92.84% and a recall of 82.18% in labeling of the extracted images.

Optical image transformation and encryption by phase-retrieval-based double random-phase encoding and compressive ghost imaging

NASA Astrophysics Data System (ADS)

Yuan, Sheng; Yang, Yangrui; Liu, Xuemei; Zhou, Xin; Wei, Zhenzhuo

2018-01-01

An optical image transformation and encryption scheme is proposed based on double random-phase encoding (DRPE) and compressive ghost imaging (CGI) techniques. In this scheme, a secret image is first transformed into a binary image with the phase-retrieval-based DRPE technique, and then encoded by a series of random amplitude patterns according to the ghost imaging (GI) principle. Compressive sensing, corrosion and expansion operations are implemented to retrieve the secret image in the decryption process. This encryption scheme takes the advantage of complementary capabilities offered by the phase-retrieval-based DRPE and GI-based encryption techniques. That is the phase-retrieval-based DRPE is used to overcome the blurring defect of the decrypted image in the GI-based encryption, and the CGI not only reduces the data amount of the ciphertext, but also enhances the security of DRPE. Computer simulation results are presented to verify the performance of the proposed encryption scheme.

Optically secured information retrieval using two authenticated phase-only masks.

PubMed

Wang, Xiaogang; Chen, Wen; Mei, Shengtao; Chen, Xudong

2015-10-23

We propose an algorithm for jointly designing two phase-only masks (POMs) that allow for the encryption and noise-free retrieval of triple images. The images required for optical retrieval are first stored in quick-response (QR) codes for noise-free retrieval and flexible readout. Two sparse POMs are respectively calculated from two different images used as references for authentication based on modified Gerchberg-Saxton algorithm (GSA) and pixel extraction, and are then used as support constraints in a modified double-phase retrieval algorithm (MPRA), together with the above-mentioned QR codes. No visible information about the target images or the reference images can be obtained from each of these authenticated POMs. This approach allows users to authenticate the two POMs used for image reconstruction without visual observation of the reference images. It also allows user to friendly access and readout with mobile devices.

Optically secured information retrieval using two authenticated phase-only masks

PubMed Central

Wang, Xiaogang; Chen, Wen; Mei, Shengtao; Chen, Xudong

2015-01-01

We propose an algorithm for jointly designing two phase-only masks (POMs) that allow for the encryption and noise-free retrieval of triple images. The images required for optical retrieval are first stored in quick-response (QR) codes for noise-free retrieval and flexible readout. Two sparse POMs are respectively calculated from two different images used as references for authentication based on modified Gerchberg-Saxton algorithm (GSA) and pixel extraction, and are then used as support constraints in a modified double-phase retrieval algorithm (MPRA), together with the above-mentioned QR codes. No visible information about the target images or the reference images can be obtained from each of these authenticated POMs. This approach allows users to authenticate the two POMs used for image reconstruction without visual observation of the reference images. It also allows user to friendly access and readout with mobile devices. PMID:26494213

Optically secured information retrieval using two authenticated phase-only masks

NASA Astrophysics Data System (ADS)

Wang, Xiaogang; Chen, Wen; Mei, Shengtao; Chen, Xudong

2015-10-01

We propose an algorithm for jointly designing two phase-only masks (POMs) that allow for the encryption and noise-free retrieval of triple images. The images required for optical retrieval are first stored in quick-response (QR) codes for noise-free retrieval and flexible readout. Two sparse POMs are respectively calculated from two different images used as references for authentication based on modified Gerchberg-Saxton algorithm (GSA) and pixel extraction, and are then used as support constraints in a modified double-phase retrieval algorithm (MPRA), together with the above-mentioned QR codes. No visible information about the target images or the reference images can be obtained from each of these authenticated POMs. This approach allows users to authenticate the two POMs used for image reconstruction without visual observation of the reference images. It also allows user to friendly access and readout with mobile devices.

Access to MISR Aerosol Data and Imagery for the GoMACCS Field Study

NASA Astrophysics Data System (ADS)

Ritchey, N.; Watkinson, T.; Davis, J.; Walter, J.; Protack, S.; Matthews, J.; Smyth, M.; Rheingans, B.; Gaitley, B.; Ferebee, M.; Haberer, S.

2006-12-01

NASA Langley Atmospheric Science Data Center (ASDC) and NASA Jet Propulsion Laboratory (JPL) Multi- angle Imaging SpectroRadiometer (MISR) teams collaborated to provide special data products and images in an innovative approach for the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS) field campaign. GoMACCS was an intensive field study focused on providing a better understanding of the sources and atmospheric processes responsible for the formation and distribution of ozone and aerosols in the atmosphere and the influence that these species have on the radiative forcing of regional and global climate, as well as their impact on human health and regional haze. The study area encompassed Texas and the northwestern Gulf of Mexico. Numerous U. S. Government agencies, universities and commercial entities participated in the field campaign which occurred August through September 2006. Aerosol and meteorological measurements were provided by a network of instruments on land, buoys and ships, by airborne in situ and remote instruments, and by satellite retrievals. MISR's role in GoMACCS was to provide satellite retrievals of aerosols and cloud properties and imagery as quickly as possible after data acquisition. The diverse group of scientific participants created unique opportunities for ASDC and MISR to develop special data products and images that were easily accessible by all participants. Examples of the data products, images and access methods as well as the data and imagery flow will be presented. Additional information about ASDC and MISR is available from the following web sites, http://eosweb.larc.nasa.gov and http://www-misr.jpl.nasa.gov/.

Content-Based Medical Image Retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Deserno, Thomas M.

This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

High resolution satellite image indexing and retrieval using SURF features and bag of visual words

NASA Astrophysics Data System (ADS)

Bouteldja, Samia; Kourgli, Assia

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Latent Semantic Analysis as a Method of Content-Based Image Retrieval in Medical Applications

ERIC Educational Resources Information Center

Makovoz, Gennadiy

2010-01-01

The research investigated whether a Latent Semantic Analysis (LSA)-based approach to image retrieval can map pixel intensity into a smaller concept space with good accuracy and reasonable computational cost. From a large set of M computed tomography (CT) images, a retrieval query found all images for a particular patient based on semantic…

A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations

PubMed Central

Kurtz, Camille; Beaulieu, Christopher F.; Napel, Sandy; Rubin, Daniel L.

2014-01-01

Computer-assisted image retrieval applications could assist radiologist interpretations by identifying similar images in large archives as a means to providing decision support. However, the semantic gap between low-level image features and their high level semantics may impair the system performances. Indeed, it can be challenging to comprehensively characterize the images using low-level imaging features to fully capture the visual appearance of diseases on images, and recently the use of semantic terms has been advocated to provide semantic descriptions of the visual contents of images. However, most of the existing image retrieval strategies do not consider the intrinsic properties of these terms during the comparison of the images beyond treating them as simple binary (presence/absence) features. We propose a new framework that includes semantic features in images and that enables retrieval of similar images in large databases based on their semantic relations. It is based on two main steps: (1) annotation of the images with semantic terms extracted from an ontology, and (2) evaluation of the similarity of image pairs by computing the similarity between the terms using the Hierarchical Semantic-Based Distance (HSBD) coupled to an ontological measure. The combination of these two steps provides a means of capturing the semantic correlations among the terms used to characterize the images that can be considered as a potential solution to deal with the semantic gap problem. We validate this approach in the context of the retrieval and the classification of 2D regions of interest (ROIs) extracted from computed tomographic (CT) images of the liver. Under this framework, retrieval accuracy of more than 0.96 was obtained on a 30-images dataset using the Normalized Discounted Cumulative Gain (NDCG) index that is a standard technique used to measure the effectiveness of information retrieval algorithms when a separate reference standard is available. Classification results of more than 95% were obtained on a 77-images dataset. For comparison purpose, the use of the Earth Mover's Distance (EMD), which is an alternative distance metric that considers all the existing relations among the terms, led to results retrieval accuracy of 0.95 and classification results of 93% with a higher computational cost. The results provided by the presented framework are competitive with the state-of-the-art and emphasize the usefulness of the proposed methodology for radiology image retrieval and classification. PMID:24632078

Indexing and Metatag Schemes for Web-Based Information Retrieval.

ERIC Educational Resources Information Center

Torok, Andrew G.

This paper reviews indexing theory and suggests that information retrieval can be significantly improved by applying basic indexing criteria. Indexing practices are described, including the three main types of indexes: pre-coordinate, post-coordinate, and variants of both. Design features of indexes are summarized, including accuracy, consistency,…

Quantification of signal detection performance degradation induced by phase-retrieval in propagation-based x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

Chou, Cheng-Ying; Anastasio, Mark A.

2016-04-01

In propagation-based X-ray phase-contrast (PB XPC) imaging, the measured image contains a mixture of absorption- and phase-contrast. To obtain separate images of the projected absorption and phase (i.e., refractive) properties of a sample, phase retrieval methods can be employed. It has been suggested that phase-retrieval can always improve image quality in PB XPC imaging. However, when objective (task-based) measures of image quality are employed, this is not necessarily true and phase retrieval can be detrimental. In this work, signal detection theory is utilized to quantify the performance of a Hotelling observer (HO) for detecting a known signal in a known background. Two cases are considered. In the first case, the HO acts directly on the measured intensity data. In the second case, the HO acts on either the retrieved phase or absorption image. We demonstrate that the performance of the HO is superior when acting on the measured intensity data. The loss of task-specific information induced by phase-retrieval is quantified by computing the efficiency of the HO as the ratio of the test statistic signal-to-noise ratio (SNR) for the two cases. The effect of the system geometry on this efficiency is systematically investigated. Our findings confirm that phase-retrieval can impair signal detection performance in XPC imaging.

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE PAGES

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

2014-12-01

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

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

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Design and evaluation of web-based image transmission and display with different protocols

NASA Astrophysics Data System (ADS)

Tan, Bin; Chen, Kuangyi; Zheng, Xichuan; Zhang, Jianguo

2011-03-01

There are many Web-based image accessing technologies used in medical imaging area, such as component-based (ActiveX Control) thick client Web display, Zerofootprint thin client Web viewer (or called server side processing Web viewer), Flash Rich Internet Application(RIA) ,or HTML5 based Web display. Different Web display methods have different peformance in different network environment. In this presenation, we give an evaluation on two developed Web based image display systems. The first one is used for thin client Web display. It works between a PACS Web server with WADO interface and thin client. The PACS Web server provides JPEG format images to HTML pages. The second one is for thick client Web display. It works between a PACS Web server with WADO interface and thick client running in browsers containing ActiveX control, Flash RIA program or HTML5 scripts. The PACS Web server provides native DICOM format images or JPIP stream for theses clients.

Real People Don't Do Boolean: How To Teach End Users To Find High-Quality Information on the Internet.

ERIC Educational Resources Information Center

Vine, Rita

2001-01-01

Explains how to train users in effective Web searching. Discusses challenges of teaching Web information retrieval; a framework for information searching; choosing the right search tools for users; the seven-step lesson planning process; tips for delivering group Internet training; and things that help people work faster and smarter on the Web.…

Reliability, Validity, and Usability of Data Extraction Programs for Single-Case Research Designs.

PubMed

Moeyaert, Mariola; Maggin, Daniel; Verkuilen, Jay

2016-11-01

Single-case experimental designs (SCEDs) have been increasingly used in recent years to inform the development and validation of effective interventions in the behavioral sciences. An important aspect of this work has been the extension of meta-analytic and other statistical innovations to SCED data. Standard practice within SCED methods is to display data graphically, which requires subsequent users to extract the data, either manually or using data extraction programs. Previous research has examined issues of reliability and validity of data extraction programs in the past, but typically at an aggregate level. Little is known, however, about the coding of individual data points. We focused on four different software programs that can be used for this purpose (i.e., Ungraph, DataThief, WebPlotDigitizer, and XYit), and examined the reliability of numeric coding, the validity compared with real data, and overall program usability. This study indicates that the reliability and validity of the retrieved data are independent of the specific software program, but are dependent on the individual single-case study graphs. Differences were found in program usability in terms of user friendliness, data retrieval time, and license costs. Ungraph and WebPlotDigitizer received the highest usability scores. DataThief was perceived as unacceptable and the time needed to retrieve the data was double that of the other three programs. WebPlotDigitizer was the only program free to use. As a consequence, WebPlotDigitizer turned out to be the best option in terms of usability, time to retrieve the data, and costs, although the usability scores of Ungraph were also strong. © The Author(s) 2016.

BioPartsBuilder: a synthetic biology tool for combinatorial assembly of biological parts.

PubMed

Yang, Kun; Stracquadanio, Giovanni; Luo, Jingchuan; Boeke, Jef D; Bader, Joel S

2016-03-15

Combinatorial assembly of DNA elements is an efficient method for building large-scale synthetic pathways from standardized, reusable components. These methods are particularly useful because they enable assembly of multiple DNA fragments in one reaction, at the cost of requiring that each fragment satisfies design constraints. We developed BioPartsBuilder as a biologist-friendly web tool to design biological parts that are compatible with DNA combinatorial assembly methods, such as Golden Gate and related methods. It retrieves biological sequences, enforces compliance with assembly design standards and provides a fabrication plan for each fragment. BioPartsBuilder is accessible at http://public.biopartsbuilder.org and an Amazon Web Services image is available from the AWS Market Place (AMI ID: ami-508acf38). Source code is released under the MIT license, and available for download at https://github.com/baderzone/biopartsbuilder joel.bader@jhu.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Microsoft Research at TREC 2009. Web and Relevance Feedback Tracks

DTIC Science & Technology

2009-11-01

Information Processing Systems, pages 193–200, 2006. [2] J . M. Kleinberg. Authoritative sources in a hyperlinked environment. In Proc. of the 9th...Walker, S. Jones, M. Hancock-Beaulieu, and M. Gatford. Okapi at TREC-3. In Proc. of the 3rd Text REtrieval Conference, 1994. [8] J . J . Rocchio. Relevance...feedback in information retrieval. In Gerard Salton , editor, The SMART Retrieval System - Experiments in Automatic Document Processing. Prentice Hall

The Impact of Positive, Negative and Topical Relevance Feedback

DTIC Science & Technology

2008-11-01

the Netherlands Organization for Scientific Research (NWO, grant # 612.066.513). REFERENCES [1] Y. K. Chang, C. Cirillo, and J . Razon. Evaluation of...feedback retrieval using modified freezing, residual collection and test and control groups. In G. Salton , editor, The SMART retrieval system...information retrieval. In Proceedings SI- GIR 2004, pages 178–185. ACM Press, New York NY, 2004. [3] R. Kaptein and J . Kamps. Web directories as topical context

Bat-Inspired Algorithm Based Query Expansion for Medical Web Information Retrieval.

PubMed

Khennak, Ilyes; Drias, Habiba

2017-02-01

With the increasing amount of medical data available on the Web, looking for health information has become one of the most widely searched topics on the Internet. Patients and people of several backgrounds are now using Web search engines to acquire medical information, including information about a specific disease, medical treatment or professional advice. Nonetheless, due to a lack of medical knowledge, many laypeople have difficulties in forming appropriate queries to articulate their inquiries, which deem their search queries to be imprecise due the use of unclear keywords. The use of these ambiguous and vague queries to describe the patients' needs has resulted in a failure of Web search engines to retrieve accurate and relevant information. One of the most natural and promising method to overcome this drawback is Query Expansion. In this paper, an original approach based on Bat Algorithm is proposed to improve the retrieval effectiveness of query expansion in medical field. In contrast to the existing literature, the proposed approach uses Bat Algorithm to find the best expanded query among a set of expanded query candidates, while maintaining low computational complexity. Moreover, this new approach allows the determination of the length of the expanded query empirically. Numerical results on MEDLINE, the on-line medical information database, show that the proposed approach is more effective and efficient compared to the baseline.

Characterizing region of interest in image using MPEG-7 visual descriptors

NASA Astrophysics Data System (ADS)

Ryu, Min-Sung; Park, Soo-Jun; Won, Chee Sun

2005-08-01

In this paper, we propose a region-based image retrieval system using EHD (Edge Histogram Descriptor) and CLD (Color Layout Descriptor) of MPEG-7 descriptors. The combined descriptor can efficiently describe edge and color features in terms of sub-image regions. That is, the basic unit for the selection of the region-of-interest (ROI) in the image is the sub-image block of the EHD, which corresponds to 16 (i.e., 4x4) non-overlapping image blocks in the image space. This implies that, to have a one-to-one region correspondence between EHD and CLD, we need to take an 8x8 inverse DCT (IDCT) for the CLD. Experimental results show that the proposed retrieval scheme can be used for image retrieval with the ROI based image retrieval for MPEG-7 indexed images.

Storage and Retrieval of Large RDF Graph Using Hadoop and MapReduce

NASA Astrophysics Data System (ADS)

Farhan Husain, Mohammad; Doshi, Pankil; Khan, Latifur; Thuraisingham, Bhavani

Handling huge amount of data scalably is a matter of concern for a long time. Same is true for semantic web data. Current semantic web frameworks lack this ability. In this paper, we describe a framework that we built using Hadoop to store and retrieve large number of RDF triples. We describe our schema to store RDF data in Hadoop Distribute File System. We also present our algorithms to answer a SPARQL query. We make use of Hadoop's MapReduce framework to actually answer the queries. Our results reveal that we can store huge amount of semantic web data in Hadoop clusters built mostly by cheap commodity class hardware and still can answer queries fast enough. We conclude that ours is a scalable framework, able to handle large amount of RDF data efficiently.

Retrieval of bilingual autobiographical memories: effects of cue language and cue imageability.

PubMed

Mortensen, Linda; Berntsen, Dorthe; Bohn, Ocke-Schwen

2015-01-01

An important issue in theories of bilingual autobiographical memory is whether linguistically encoded memories are represented in language-specific stores or in a common language-independent store. Previous research has found that autobiographical memory retrieval is facilitated when the language of the cue is the same as the language of encoding, consistent with language-specific memory stores. The present study examined whether this language congruency effect is influenced by cue imageability. Danish-English bilinguals retrieved autobiographical memories in response to Danish and English high- or low-imageability cues. Retrieval latencies were shorter to Danish than English cues and shorter to high- than low-imageability cues. Importantly, the cue language effect was stronger for low-than high-imageability cues. To examine the relationship between cue language and the language of internal retrieval, participants identified the language in which the memories were internally retrieved. More memories were retrieved when the cue language was the same as the internal language than when the cue was in the other language, and more memories were identified as being internally retrieved in Danish than English, regardless of the cue language. These results provide further evidence for language congruency effects in bilingual memory and suggest that this effect is influenced by cue imageability.

Web survey data collection and retrieval to plan teleradiology implementation

NASA Astrophysics Data System (ADS)

Alaoui, Adil; Collmann, Jeff R.; Johnson, Jeffrey A.; Lindisch, David; Nguyen, Dan; Mun, Seong K.

2003-05-01

This case study details the experience of system engineers of the Imaging Science and Information Systems Center, Georgetown University Medical Center (ISIS) and radiologists from the department of Radiology in the implementation of a new Teleradiology system. The Teleradiology system enables radiologists to view medical images from remote sites under those circumstances where a resident radiologist needs assistance in evaluating the images after hours and during weekends; it also enables clinicians access to patients" medical images from different workstations within the hospital. The Implementation of the Teleradiology project was preceded by an evaluation phase to perform testing, gather users feedback using a web site and collect information that helped eliminate system bugs, complete recommendations regarding minimum hardware configuration and bandwidth and enhance system"s functions, this phase included a survey-based system assessment of computer configurations, Internet connections, problem identification, and recommendations for improvement, and a testing period with 2 radiologists and ISIS engineers; The second phase was designed to launch the system and make it available to all attending radiologists in the department. To accomplish the first phase of the project a web site was designed and ASP pages were created to enable users to securely logon and enter feedback and recommendations into an SQL database. This efficient, accurate data flow alleviated networking, software and hardware problems. Corrective recommendations were immediately forwarded to the software vendor. The vendor responded with software updates that better met the needs of the radiologists. The ISIS Center completed recommendations for minimum hardware and bandwidth requirements. This experience illustrates that the approach used in collecting the data and facilitating the teamwork between the system engineers and radiologists was instrumental in the project"s success. Major problems with the Teleradiology system were discovered and remedied early by linking the actual practice experience of the physicians to the system improvements.

Development of a web database portfolio system with PACS connectivity for undergraduate health education and continuing professional development.

PubMed

Ng, Curtise K C; White, Peter; McKay, Janice C

2009-04-01

Increasingly, the use of web database portfolio systems is noted in medical and health education, and for continuing professional development (CPD). However, the functions of existing systems are not always aligned with the corresponding pedagogy and hence reflection is often lost. This paper presents the development of a tailored web database portfolio system with Picture Archiving and Communication System (PACS) connectivity, which is based on the portfolio pedagogy. Following a pre-determined portfolio framework, a system model with the components of web, database and mail servers, server side scripts, and a Query/Retrieve (Q/R) broker for conversion between Hypertext Transfer Protocol (HTTP) requests and Q/R service class of Digital Imaging and Communication in Medicine (DICOM) standard, is proposed. The system was piloted with seventy-seven volunteers. A tailored web database portfolio system (http://radep.hti.polyu.edu.hk) was developed. Technological arrangements for reinforcing portfolio pedagogy include popup windows (reminders) with guidelines and probing questions of 'collect', 'select' and 'reflect' on evidence of development/experience, limitation in the number of files (evidence) to be uploaded, the 'Evidence Insertion' functionality to link the individual uploaded artifacts with reflective writing, capability to accommodate diversity of contents and convenient interfaces for reviewing portfolios and communication. Evidence to date suggests the system supports users to build their portfolios with sound hypertext reflection under a facilitator's guidance, and with reviewers to monitor students' progress providing feedback and comments online in a programme-wide situation.

The aware toolbox for the detection of law infringements on web pages

NASA Astrophysics Data System (ADS)

Shahab, Asif; Kieninger, Thomas; Dengel, Andreas

2010-01-01

In the project Aware we aim to develop an automatic assistant for the detection of law infringements on web pages. The motivation for this project is that many authors of web pages are at some points infringing copyrightor other laws, mostly without being aware of that fact, and are more and more often confronted with costly legal warnings. As the legal environment is constantly changing, an important requirement of Aware is that the domain knowledge can be maintained (and initially defined) by numerous legal experts remotely working without further assistance of the computer scientists. Consequently, the software platform was chosen to be a web-based generic toolbox that can be configured to suit individual analysis experts, definitions of analysis flow, information gathering and report generation. The report generated by the system summarizes all critical elements of a given web page and provides case specific hints to the page author and thus forms a new type of service. Regarding the analysis subsystems, Aware mainly builds on existing state-of-the-art technologies. Their usability has been evaluated for each intended task. In order to control the heterogeneous analysis components and to gather the information, a lightweight scripting shell has been developed. This paper describes the analysis technologies, ranging from text based information extraction, over optical character recognition and phonetic fuzzy string matching to a set of image analysis and retrieval tools; as well as the scripting language to define the analysis flow.

Large-scale retrieval for medical image analytics: A comprehensive review.

PubMed

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Online Islamic Organizations and Measuring Web Effectiveness

DTIC Science & Technology

2004-12-01

Internet Research 13 (2003) : 17-26. Retrived from ProQuest online database on 15 May 2004. Lee, Jae-Kwan. “A model for monitoring public sector...Web site strategy.” Internet Research : Electronic Networking Applications and Policy 13 (2003) : 259-266. Retrieved from Emerad online database on

Content-based cell pathology image retrieval by combining different features

NASA Astrophysics Data System (ADS)

Zhou, Guangquan; Jiang, Lu; Luo, Limin; Bao, Xudong; Shu, Huazhong

2004-04-01

Content Based Color Cell Pathology Image Retrieval is one of the newest computer image processing applications in medicine. Recently, some algorithms have been developed to achieve this goal. Because of the particularity of cell pathology images, the result of the image retrieval based on single characteristic is not satisfactory. A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed. Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation and mathematics morphology. The features that include color, texture and morphologic features are extracted from single leukocyte to represent main attribute in the search query. The features are then normalized because the numerical value range and physical meaning of extracted features are different. Finally, the relevance feedback system is introduced. So that the system can automatically adjust the weights of different features and improve the results of retrieval system according to the feedback information. Retrieval results using the proposed method fit closely with human perception and are better than those obtained with the methods based on single feature.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

ERIC Educational Resources Information Center

Wang, James Z.; Du, Yanping

Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

Automated semantic indexing of figure captions to improve radiology image retrieval.

PubMed

Kahn, Charles E; Rubin, Daniel L

2009-01-01

We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Estimated precision was 0.897 (95% confidence interval, 0.857-0.937). Estimated recall was 0.930 (95% confidence interval, 0.838-1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval.

[Security specifications for electronic medical records on the Internet].

PubMed

Mocanu, Mihai; Mocanu, Carmen

2007-01-01

The extension for the Web applications of the Electronic Medical Record seems both interesting and promising. Correlated with the expansion of Internet in our country, it allows the interconnection of physicians of different specialties and their collaboration for better treatment of patients. In this respect, the ophthalmologic medical applications consider the increased possibilities for monitoring chronic ocular diseases and for the identification of some elements for early diagnosis and risk factors supervision. We emphasize in this survey some possible solutions to the problems of interconnecting medical information systems to the Internet: the achievement of interoperability within medical organizations through the use of open standards, the automated input and processing for ocular imaging, the use of data reduction techniques in order to increase the speed of image retrieval in large databases, and, last but not least, the resolution of security and confidentiality problems in medical databases.

Coral disease and health workshop: Coral Histopathology II, July 12-14, 2005

USGS Publications Warehouse

Galloway, S.B.; Woodley, Cheryl M.; McLaughlin, S.M.; Work, Thierry M.; Bochsler, V.S.; Meteyer, Carol U.; Sileo, Louis; Peters, E.C.; Kramarsky-Winters, E.; Morado, J. Frank; Parnell, P.G.; Rotstein, D.S.; Harely, R.A.; Reynolds, T.L.

2005-01-01

An exciting highlight of this meeting was provided by Professor Robert Ogilvie (MUSC Department of Cell Biology and Anatomy) when he introduced participants to a new digital technology that is revolutionizing histology and histopathology in the medical field. The Virtual Slide technology creates digital images of histological tissue sections by computer scanning actual slides in high definition and storing the images for retrieval and viewing. Virtual slides now allow any investigator with access to a computer and the web to view, search, annotate and comment on the same tissue sections in real time. Medical and veterinary slide libraries across the country are being converted into virtual slides to enhance biomedical education, research and diagnosis. The coral health and disease researchers at this workshop deem virtual slides as a significant way to increase capabilities in coral histology and a means for pathology consultations on coral disease cases on a global scale. 

Designing an information search interface for younger and older adults.

PubMed

Pak, Richard; Price, Margaux M

2008-08-01

The present study examined Web-based information retrieval as a function of age for two information organization schemes: hierarchical organization and one organized around tags or keywords. Older adults' performance in information retrieval tasks has traditionally been lower compared with younger adults'. The current study examined the degree to which information organization moderated age-related performance differences on an information retrieval task. The theory of fluid and crystallized intelligence may provide insight into different kinds of information architectures that may reduce age-related differences in computer-based information retrieval performance. Fifty younger (18-23 years of age) and 50 older (55-76 years of age) participants browsed a Web site for answers to specific questions. Half of the participants browsed the hierarchically organized system (taxonomy), which maintained a one-to-one relationship between menu link and page, whereas the other half browsed the tag-based interface, with a many-to-one relationship between menu and page. This difference was expected to interact with age-related differences in fluid and crystallized intelligence. Age-related differences in information retrieval performance persisted; however, a tag-based retrieval interface reduced age-related differences, as compared with a taxonomical interface. Cognitive aging theory can lead to interface interventions that reduce age-related differences in performance with technology. In an information retrieval paradigm, older adults may be able to leverage their increased crystallized intelligence to offset fluid intelligence declines in a computer-based information search task. More research is necessary, but the results suggest that information retrieval interfaces organized around keywords may reduce age-related differences in performance.

WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions

PubMed Central

Karr, Jonathan R.; Phillips, Nolan C.; Covert, Markus W.

2014-01-01

Mechanistic ‘whole-cell’ models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. Database URL: http://www.wholecellsimdb.org Source code repository URL: http://github.com/CovertLab/WholeCellSimDB PMID:25231498

Alkemio: association of chemicals with biomedical topics by text and data mining.

PubMed

Gijón-Correas, José A; Andrade-Navarro, Miguel A; Fontaine, Jean F

2014-07-01

The PubMed® database of biomedical citations allows the retrieval of scientific articles studying the function of chemicals in biology and medicine. Mining millions of available citations to search reported associations between chemicals and topics of interest would require substantial human time. We have implemented the Alkemio text mining web tool and SOAP web service to help in this task. The tool uses biomedical articles discussing chemicals (including drugs), predicts their relatedness to the query topic with a naïve Bayesian classifier and ranks all chemicals by P-values computed from random simulations. Benchmarks on seven human pathways showed good retrieval performance (areas under the receiver operating characteristic curves ranged from 73.6 to 94.5%). Comparison with existing tools to retrieve chemicals associated to eight diseases showed the higher precision and recall of Alkemio when considering the top 10 candidate chemicals. Alkemio is a high performing web tool ranking chemicals for any biomedical topics and it is free to non-commercial users. http://cbdm.mdc-berlin.de/∼medlineranker/cms/alkemio. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A concept-based interactive biomedical image retrieval approach using visualness and spatial information

NASA Astrophysics Data System (ADS)

Rahman, Md M.; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.

2015-03-01

This paper presents a novel approach to biomedical image retrieval by mapping image regions to local concepts and represent images in a weighted entropy-based concept feature space. The term concept refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist user in interactively select a Region-Of-Interest (ROI) and search for similar image ROIs. Further, a spatial verification step is used as a post-processing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval, is validated through experiments on a data set of 450 lung CT images extracted from journal articles from four different collections.

Development of a 3D WebGIS System for Retrieving and Visualizing CityGML Data Based on their Geometric and Semantic Characteristics by Using Free and Open Source Technology

NASA Astrophysics Data System (ADS)

Pispidikis, I.; Dimopoulou, E.

2016-10-01

CityGML is considered as an optimal standard for representing 3D city models. However, international experience has shown that visualization of the latter is quite difficult to be implemented on the web, due to the large size of data and the complexity of CityGML. As a result, in the context of this paper, a 3D WebGIS application is developed in order to successfully retrieve and visualize CityGML data in accordance with their respective geometric and semantic characteristics. Furthermore, the available web technologies and the architecture of WebGIS systems are investigated, as provided by international experience, in order to be utilized in the most appropriate way for the purposes of this paper. Specifically, a PostgreSQL/ PostGIS Database is used, in compliance with the 3DCityDB schema. At Server tier, Apache HTTP Server and GeoServer are utilized, while a Server Side programming language PHP is used. At Client tier, which implemented the interface of the application, the following technologies were used: JQuery, AJAX, JavaScript, HTML5, WebGL and Ol3-Cesium. Finally, it is worth mentioning that the application's primary objectives are a user-friendly interface and a fully open source development.

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

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

Scalability of Findability: Decentralized Search and Retrieval in Large Information Networks

ERIC Educational Resources Information Center

Ke, Weimao

2010-01-01

Amid the rapid growth of information today is the increasing challenge for people to survive and navigate its magnitude. Dynamics and heterogeneity of large information spaces such as the Web challenge information retrieval in these environments. Collection of information in advance and centralization of IR operations are hardly possible because…

An Assistant for Loading Learning Object Metadata: An Ontology Based Approach

ERIC Educational Resources Information Center

Casali, Ana; Deco, Claudia; Romano, Agustín; Tomé, Guillermo

2013-01-01

In the last years, the development of different Repositories of Learning Objects has been increased. Users can retrieve these resources for reuse and personalization through searches in web repositories. The importance of high quality metadata is key for a successful retrieval. Learning Objects are described with metadata usually in the standard…

Chinese Brush Calligraphy Character Retrieval and Learning

ERIC Educational Resources Information Center

Zhuang, Yueting; Zhang, Xiafen; Lu, Weiming; Wu, Fei

2007-01-01

Chinese brush calligraphy is a valuable civilization legacy and a high art of scholarship. It is still popular in Chinese banners, newspaper mastheads, university names, and celebration gifts. There are Web sites that try to help people enjoy and learn Chinese calligraphy. However, there lacks advanced services such as content-based retrieval or…

Enhancing Retrieval with Hyperlinks: A General Model Based on Propositional Argumentation Systems.

ERIC Educational Resources Information Center

Picard, Justin; Savoy, Jacques

2003-01-01

Discusses the use of hyperlinks for improving information retrieval on the World Wide Web and proposes a general model for using hyperlinks based on Probabilistic Argumentation Systems. Topics include propositional logic, knowledge, and uncertainty; assumptions; using hyperlinks to modify document score and rank; and estimating the popularity of a…

[Digital teaching archive. Concept, implementation, and experiences in a university setting].

PubMed

Trumm, C; Dugas, M; Wirth, S; Treitl, M; Lucke, A; Küttner, B; Pander, E; Clevert, D-A; Glaser, C; Reiser, M

2005-08-01

Film-based teaching files require a substantial investment in human, logistic, and financial resources. The combination of computer and network technology facilitates the workflow integration of distributing radiologic teaching cases within an institution (intranet) or via the World Wide Web (Internet). A digital teaching file (DTF) should include the following basic functions: image import from different sources and of different formats, editing of imported images, uniform case classification, quality control (peer review), a controlled access of different user groups (in-house and external), and an efficient retrieval strategy. The portable network graphics image format (PNG) is especially suitable for DTFs because of several features: pixel support, 2D-interlacing, gamma correction, and lossless compression. The American College of Radiology (ACR) "Index for Radiological Diagnoses" is hierarchically organized and thus an ideal classification system for a DTF. Computer-based training (CBT) in radiology is described in numerous publications, from supplementing traditional learning methods to certified education via the Internet. Attractiveness of a CBT application can be increased by integration of graphical and interactive elements but makes workflow integration of daily case input more difficult. Our DTF was built with established Internet instruments and integrated into a heterogeneous PACS/RIS environment. It facilitates a quick transfer (DICOM_Send) of selected images at the time of interpretation to the DTF and access to the DTF application at any time anywhere within the university hospital intranet employing a standard web browser. A DTF is a small but important building block in an institutional strategy of knowledge management.

Compressed domain indexing of losslessly compressed images

NASA Astrophysics Data System (ADS)

Schaefer, Gerald

2001-12-01

Image retrieval and image compression have been pursued separately in the past. Only little research has been done on a synthesis of the two by allowing image retrieval to be performed directly in the compressed domain of images without the need to uncompress them first. In this paper methods for image retrieval in the compressed domain of losslessly compressed images are introduced. While most image compression techniques are lossy, i.e. discard visually less significant information, lossless techniques are still required in fields like medical imaging or in situations where images must not be changed due to legal reasons. The algorithms in this paper are based on predictive coding methods where a pixel is encoded based on the pixel values of its (already encoded) neighborhood. The first method is based on an understanding that predictively coded data is itself indexable and represents a textural description of the image. The second method operates directly on the entropy encoded data by comparing codebooks of images. Experiments show good image retrieval results for both approaches.

Linear information retrieval method in X-ray grating-based phase contrast imaging and its interchangeability with tomographic reconstruction

NASA Astrophysics Data System (ADS)

Wu, Z.; Gao, K.; Wang, Z. L.; Shao, Q. G.; Hu, R. F.; Wei, C. X.; Zan, G. B.; Wali, F.; Luo, R. H.; Zhu, P. P.; Tian, Y. C.

2017-06-01

In X-ray grating-based phase contrast imaging, information retrieval is necessary for quantitative research, especially for phase tomography. However, numerous and repetitive processes have to be performed for tomographic reconstruction. In this paper, we report a novel information retrieval method, which enables retrieving phase and absorption information by means of a linear combination of two mutually conjugate images. Thanks to the distributive law of the multiplication as well as the commutative law and associative law of the addition, the information retrieval can be performed after tomographic reconstruction, thus simplifying the information retrieval procedure dramatically. The theoretical model of this method is established in both parallel beam geometry for Talbot interferometer and fan beam geometry for Talbot-Lau interferometer. Numerical experiments are also performed to confirm the feasibility and validity of the proposed method. In addition, we discuss its possibility in cone beam geometry and its advantages compared with other methods. Moreover, this method can also be employed in other differential phase contrast imaging methods, such as diffraction enhanced imaging, non-interferometric imaging, and edge illumination.

Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu

2017-07-01

In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content-based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate, and fast retrieval method for a breast histopathological image. Specifically, the method presents a local statistical feature of nuclei for morphology and distribution of nuclei, and employs the Gabor feature to describe the texture information. The latent Dirichlet allocation model is utilized for high-level semantic mining. Locality-sensitive hashing is used to speed up the search. Experiments on a WSI database with more than 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, and WSI archiving and management.

A data colocation grid framework for big data medical image processing: backend design

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop and HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design.

PubMed

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design

PubMed Central

Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-01-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework’s performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available. PMID:29887668

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

A similarity learning approach to content-based image retrieval: application to digital mammography.

PubMed

El-Naqa, Issam; Yang, Yongyi; Galatsanos, Nikolas P; Nishikawa, Robert M; Wernick, Miles N

2004-10-01

In this paper, we describe an approach to content-based retrieval of medical images from a database, and provide a preliminary demonstration of our approach as applied to retrieval of digital mammograms. Content-based image retrieval (CBIR) refers to the retrieval of images from a database using information derived from the images themselves, rather than solely from accompanying text indices. In the medical-imaging context, the ultimate aim of CBIR is to provide radiologists with a diagnostic aid in the form of a display of relevant past cases, along with proven pathology and other suitable information. CBIR may also be useful as a training tool for medical students and residents. The goal of information retrieval is to recall from a database information that is relevant to the user's query. The most challenging aspect of CBIR is the definition of relevance (similarity), which is used to guide the retrieval machine. In this paper, we pursue a new approach, in which similarity is learned from training examples provided by human observers. Specifically, we explore the use of neural networks and support vector machines to predict the user's notion of similarity. Within this framework we propose using a hierarchal learning approach, which consists of a cascade of a binary classifier and a regression module to optimize retrieval effectiveness and efficiency. We also explore how to incorporate online human interaction to achieve relevance feedback in this learning framework. Our experiments are based on a database consisting of 76 mammograms, all of which contain clustered microcalcifications (MCs). Our goal is to retrieve mammogram images containing similar MC clusters to that in a query. The performance of the retrieval system is evaluated using precision-recall curves computed using a cross-validation procedure. Our experimental results demonstrate that: 1) the learning framework can accurately predict the perceptual similarity reported by human observers, thereby serving as a basis for CBIR; 2) the learning-based framework can significantly outperform a simple distance-based similarity metric; 3) the use of the hierarchical two-stage network can improve retrieval performance; and 4) relevance feedback can be effectively incorporated into this learning framework to achieve improvement in retrieval precision based on online interaction with users; and 5) the retrieved images by the network can have predicting value for the disease condition of the query.

Medical Image Retrieval: A Multimodal Approach

PubMed Central

Cao, Yu; Steffey, Shawn; He, Jianbiao; Xiao, Degui; Tao, Cui; Chen, Ping; Müller, Henning

2014-01-01

Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical practice and research. While substantial progress has been made in different areas of content-based image retrieval (CBIR) research, direct applications of existing CBIR techniques to the medical images produced unsatisfactory results, because of the unique characteristics of medical images. In this paper, we develop a new multimodal medical image retrieval approach based on the recent advances in the statistical graphic model and deep learning. Specifically, we first investigate a new extended probabilistic Latent Semantic Analysis model to integrate the visual and textual information from medical images to bridge the semantic gap. We then develop a new deep Boltzmann machine-based multimodal learning model to learn the joint density model from multimodal information in order to derive the missing modality. Experimental results with large volume of real-world medical images have shown that our new approach is a promising solution for the next-generation medical imaging indexing and retrieval system. PMID:26309389

Web Conversations About Complementary and Alternative Medicines and Cancer: Content and Sentiment Analysis

PubMed Central

Truccolo, Ivana; Antonini, Marialuisa; Rinaldi, Fabio; Omero, Paolo; Ferrarin, Emanuela; De Paoli, Paolo; Tasso, Carlo

2016-01-01

Background The use of complementary and alternative medicine (CAM) among cancer patients is widespread and mostly self-administrated. Today, one of the most relevant topics is the nondisclosure of CAM use to doctors. This general lack of communication exposes patients to dangerous behaviors and to less reliable information channels, such as the Web. The Italian context scarcely differs from this trend. Today, we are able to mine and analyze systematically the unstructured information available in the Web, to get an insight of people’s opinions, beliefs, and rumors concerning health topics. Objective Our aim was to analyze Italian Web conversations about CAM, identifying the most relevant Web sources, therapies, and diseases and measure the related sentiment. Methods Data have been collected using the Web Intelligence tool ifMONITOR. The workflow consisted of 6 phases: (1) eligibility criteria definition for the ifMONITOR search profile; (2) creation of a CAM terminology database; (3) generic Web search and automatic filtering, the results have been manually revised to refine the search profile, and stored in the ifMONITOR database; (4) automatic classification using the CAM database terms; (5) selection of the final sample and manual sentiment analysis using a 1-5 score range; (6) manual indexing of the Web sources and CAM therapies type retrieved. Descriptive univariate statistics were computed for each item: absolute frequency, percentage, central tendency (mean sentiment score [MSS]), and variability (standard variation σ). Results Overall, 212 Web sources, 423 Web documents, and 868 opinions have been retrieved. The overall sentiment measured tends to a good score (3.6 of 5). Quite a high polarization in the opinions of the conversation partaking emerged from standard variation analysis (σ≥1). In total, 126 of 212 (59.4%) Web sources retrieved were nonhealth-related. Facebook (89; 21%) and Yahoo Answers (41; 9.7%) were the most relevant. In total, 94 CAM therapies have been retrieved. Most belong to the “biologically based therapies or nutrition” category: 339 of 868 opinions (39.1%), showing an MSS of 3.9 (σ=0.83). Within nutrition, “diets” collected 154 opinions (18.4%) with an MSS of 3.8 (σ=0.87); “food as CAM” overall collected 112 opinions (12.8%) with a MSS of 4 (σ=0.68). Excluding diets and food, the most discussed CAM therapy is the controversial Italian “Di Bella multitherapy” with 102 opinions (11.8%) with an MSS of 3.4 (σ=1.21). Breast cancer was the most mentioned disease: 81 opinions of 868. Conclusions Conversations about CAM and cancer are ubiquitous. There is a great concern about the biologically based therapies, perceived as harmless and useful, under-rating all risks related to dangerous interactions or malnutrition. Our results can be useful to doctors to be aware of the implications of these beliefs for the clinical practice. Web conversation exploitation could be a strategy to gain insights of people’s perspective for other controversial topics. PMID:27311444

Comparisons of citations in Web of Science, Scopus, and Google Scholar for articles published in general medical journals.

PubMed

Kulkarni, Abhaya V; Aziz, Brittany; Shams, Iffat; Busse, Jason W

2009-09-09

Until recently, Web of Science was the only database available to track citation counts for published articles. Other databases are now available, but their relative performance has not been established. To compare the citation count profiles of articles published in general medical journals among the citation databases of Web of Science, Scopus, and Google Scholar. Cohort study of 328 articles published in JAMA, Lancet, or the New England Journal of Medicine between October 1, 1999, and March 31, 2000. Total citation counts for each article up to June 2008 were retrieved from Web of Science, Scopus, and Google Scholar. Article characteristics were analyzed in linear regression models to determine interaction with the databases. Number of citations received by an article since publication and article characteristics associated with citation in databases. Google Scholar and Scopus retrieved more citations per article with a median of 160 (interquartile range [IQR], 83 to 324) and 149 (IQR, 78 to 289), respectively, than Web of Science (median, 122; IQR, 66 to 241) (P < .001 for both comparisons). Compared with Web of Science, Scopus retrieved more citations from non-English-language sources (median, 10.2% vs 4.1%) and reviews (30.8% vs 18.2%), and fewer citations from articles (57.2% vs 70.5%), editorials (2.1% vs 5.9%), and letters (0.8% vs 2.6%) (all P < .001). On a log(10)-transformed scale, fewer citations were found in Google Scholar to articles with declared industry funding (nonstandardized regression coefficient, -0.09; 95% confidence interval [CI], -0.15 to -0.03), reporting a study of a drug or medical device (-0.05; 95% CI, -0.11 to 0.01), or with group authorship (-0.29; 95% CI, -0.35 to -0.23). In multivariable analysis, group authorship was the only characteristic that differed among the databases; Google Scholar had significantly fewer citations to group-authored articles (-0.30; 95% CI, -0.36 to -0.23) compared with Web of Science. Web of Science, Scopus, and Google Scholar produced quantitatively and qualitatively different citation counts for articles published in 3 general medical journals.

A memory learning framework for effective image retrieval.

PubMed

Han, Junwei; Ngan, King N; Li, Mingjing; Zhang, Hong-Jiang

2005-04-01

Most current content-based image retrieval systems are still incapable of providing users with their desired results. The major difficulty lies in the gap between low-level image features and high-level image semantics. To address the problem, this study reports a framework for effective image retrieval by employing a novel idea of memory learning. It forms a knowledge memory model to store the semantic information by simply accumulating user-provided interactions. A learning strategy is then applied to predict the semantic relationships among images according to the memorized knowledge. Image queries are finally performed based on a seamless combination of low-level features and learned semantics. One important advantage of our framework is its ability to efficiently annotate images and also propagate the keyword annotation from the labeled images to unlabeled images. The presented algorithm has been integrated into a practical image retrieval system. Experiments on a collection of 10,000 general-purpose images demonstrate the effectiveness of the proposed framework.

Natural texture retrieval based on perceptual similarity measurement

NASA Astrophysics Data System (ADS)

Gao, Ying; Dong, Junyu; Lou, Jianwen; Qi, Lin; Liu, Jun

2018-04-01

A typical texture retrieval system performs feature comparison and might not be able to make human-like judgments of image similarity. Meanwhile, it is commonly known that perceptual texture similarity is difficult to be described by traditional image features. In this paper, we propose a new texture retrieval scheme based on texture perceptual similarity. The key of the proposed scheme is that prediction of perceptual similarity is performed by learning a non-linear mapping from image features space to perceptual texture space by using Random Forest. We test the method on natural texture dataset and apply it on a new wallpapers dataset. Experimental results demonstrate that the proposed texture retrieval scheme with perceptual similarity improves the retrieval performance over traditional image features.

Complex amplitude reconstruction by iterative amplitude-phase retrieval algorithm with reference

NASA Astrophysics Data System (ADS)

Shen, Cheng; Guo, Cheng; Tan, Jiubin; Liu, Shutian; Liu, Zhengjun

2018-06-01

Multi-image iterative phase retrieval methods have been successfully applied in plenty of research fields due to their simple but efficient implementation. However, there is a mismatch between the measurement of the first long imaging distance and the sequential interval. In this paper, an amplitude-phase retrieval algorithm with reference is put forward without additional measurements or priori knowledge. It gets rid of measuring the first imaging distance. With a designed update formula, it significantly raises the convergence speed and the reconstruction fidelity, especially in phase retrieval. Its superiority over the original amplitude-phase retrieval (APR) method is validated by numerical analysis and experiments. Furthermore, it provides a conceptual design of a compact holographic image sensor, which can achieve numerical refocusing easily.

Comparison of the effectiveness of alternative feature sets in shape retrieval of multicomponent images

NASA Astrophysics Data System (ADS)

Eakins, John P.; Edwards, Jonathan D.; Riley, K. Jonathan; Rosin, Paul L.

2001-01-01

Many different kinds of features have been used as the basis for shape retrieval from image databases. This paper investigates the relative effectiveness of several types of global shape feature, both singly and in combination. The features compared include well-established descriptors such as Fourier coefficients and moment invariants, as well as recently-proposed measures of triangularity and ellipticity. Experiments were conducted within the framework of the ARTISAN shape retrieval system, and retrieval effectiveness assessed on a database of over 10,000 images, using 24 queries and associated ground truth supplied by the UK Patent Office . Our experiments revealed only minor differences in retrieval effectiveness between different measures, suggesting that a wide variety of shape feature combinations can provide adequate discriminating power for effective shape retrieval in multi-component image collections such as trademark registries. Marked differences between measures were observed for some individual queries, suggesting that there could be considerable scope for improving retrieval effectiveness by providing users with an improved framework for searching multi-dimensional feature space.

Comparison of the effectiveness of alternative feature sets in shape retrieval of multicomponent images

NASA Astrophysics Data System (ADS)

Eakins, John P.; Edwards, Jonathan D.; Riley, K. Jonathan; Rosin, Paul L.

2000-12-01

Many different kinds of features have been used as the basis for shape retrieval from image databases. This paper investigates the relative effectiveness of several types of global shape feature, both singly and in combination. The features compared include well-established descriptors such as Fourier coefficients and moment invariants, as well as recently-proposed measures of triangularity and ellipticity. Experiments were conducted within the framework of the ARTISAN shape retrieval system, and retrieval effectiveness assessed on a database of over 10,000 images, using 24 queries and associated ground truth supplied by the UK Patent Office . Our experiments revealed only minor differences in retrieval effectiveness between different measures, suggesting that a wide variety of shape feature combinations can provide adequate discriminating power for effective shape retrieval in multi-component image collections such as trademark registries. Marked differences between measures were observed for some individual queries, suggesting that there could be considerable scope for improving retrieval effectiveness by providing users with an improved framework for searching multi-dimensional feature space.

Leveraging Terminologies for Retrieval of Radiology Reports with Critical Imaging Findings

PubMed Central

Warden, Graham I.; Lacson, Ronilda; Khorasani, Ramin

2011-01-01

Introduction: Communication of critical imaging findings is an important component of medical quality and safety. A fundamental challenge includes retrieval of radiology reports that contain these findings. This study describes the expressiveness and coverage of existing medical terminologies for critical imaging findings and evaluates radiology report retrieval using each terminology. Methods: Four terminologies were evaluated: National Cancer Institute Thesaurus (NCIT), Radiology Lexicon (RadLex), Systemized Nomenclature of Medicine (SNOMED-CT), and International Classification of Diseases (ICD-9-CM). Concepts in each terminology were identified for 10 critical imaging findings. Three findings were subsequently selected to evaluate document retrieval. Results: SNOMED-CT consistently demonstrated the highest number of overall terms (mean=22) for each of ten critical findings. However, retrieval rate and precision varied between terminologies for the three findings evaluated. Conclusion: No single terminology is optimal for retrieving radiology reports with critical findings. The expressiveness of a terminology does not consistently correlate with radiology report retrieval. PMID:22195212

Near real time water quality monitoring of Chivero and Manyame lakes of Zimbabwe

NASA Astrophysics Data System (ADS)

Muchini, Ronald; Gumindoga, Webster; Togarepi, Sydney; Pinias Masarira, Tarirai; Dube, Timothy

2018-05-01

Zimbabwe's water resources are under pressure from both point and non-point sources of pollution hence the need for regular and synoptic assessment. In-situ and laboratory based methods of water quality monitoring are point based and do not provide a synoptic coverage of the lakes. This paper presents novel methods for retrieving water quality parameters in Chivero and Manyame lakes, Zimbabwe, from remotely sensed imagery. Remotely sensed derived water quality parameters are further validated using in-situ data. It also presents an application for automated retrieval of those parameters developed in VB6, as well as a web portal for disseminating the water quality information to relevant stakeholders. The web portal is developed, using Geoserver, open layers and HTML. Results show the spatial variation of water quality and an automated remote sensing and GIS system with a web front end to disseminate water quality information.

New Quality Metrics for Web Search Results

NASA Astrophysics Data System (ADS)

Metaxas, Panagiotis Takis; Ivanova, Lilia; Mustafaraj, Eni

Web search results enjoy an increasing importance in our daily lives. But what can be said about their quality, especially when querying a controversial issue? The traditional information retrieval metrics of precision and recall do not provide much insight in the case of web information retrieval. In this paper we examine new ways of evaluating quality in search results: coverage and independence. We give examples on how these new metrics can be calculated and what their values reveal regarding the two major search engines, Google and Yahoo. We have found evidence of low coverage for commercial and medical controversial queries, and high coverage for a political query that is highly contested. Given the fact that search engines are unwilling to tune their search results manually, except in a few cases that have become the source of bad publicity, low coverage and independence reveal the efforts of dedicated groups to manipulate the search results.

Intelligent retrieval of medical images from the Internet

NASA Astrophysics Data System (ADS)

Tang, Yau-Kuo; Chiang, Ted T.

1996-05-01

The object of this study is using Internet resources to provide a cost-effective, user-friendly method to access the medical image archive system and to provide an easy method for the user to identify the images required. This paper describes the prototype system architecture, the implementation, and results. In the study, we prototype the Intelligent Medical Image Retrieval (IMIR) system as a Hypertext Transport Prototype server and provide Hypertext Markup Language forms for user, as an Internet client, using browser to enter image retrieval criteria for review. We are developing the intelligent retrieval engine, with the capability to map the free text search criteria to the standard terminology used for medical image identification. We evaluate retrieved records based on the number of the free text entries matched and their relevance level to the standard terminology. We are in the integration and testing phase. We have collected only a few different types of images for testing and have trained a few phrases to map the free text to the standard medical terminology. Nevertheless, we are able to demonstrate the IMIR's ability to search, retrieve, and review medical images from the archives using general Internet browser. The prototype also uncovered potential problems in performance, security, and accuracy. Additional studies and enhancements will make the system clinically operational.

Automated Semantic Indexing of Figure Captions to Improve Radiology Image Retrieval

PubMed Central

Kahn, Charles E.; Rubin, Daniel L.

2009-01-01

Objective We explored automated concept-based indexing of unstructured figure captions to improve retrieval of images from radiology journals. Design The MetaMap Transfer program (MMTx) was used to map the text of 84,846 figure captions from 9,004 peer-reviewed, English-language articles to concepts in three controlled vocabularies from the UMLS Metathesaurus, version 2006AA. Sampling procedures were used to estimate the standard information-retrieval metrics of precision and recall, and to evaluate the degree to which concept-based retrieval improved image retrieval. Measurements Precision was estimated based on a sample of 250 concepts. Recall was estimated based on a sample of 40 concepts. The authors measured the impact of concept-based retrieval to improve upon keyword-based retrieval in a random sample of 10,000 search queries issued by users of a radiology image search engine. Results Estimated precision was 0.897 (95% confidence interval, 0.857–0.937). Estimated recall was 0.930 (95% confidence interval, 0.838–1.000). In 5,535 of 10,000 search queries (55%), concept-based retrieval found results not identified by simple keyword matching; in 2,086 searches (21%), more than 75% of the results were found by concept-based search alone. Conclusion Concept-based indexing of radiology journal figure captions achieved very high precision and recall, and significantly improved image retrieval. PMID:19261938

User-oriented evaluation of a medical image retrieval system for radiologists.

PubMed

Markonis, Dimitrios; Holzer, Markus; Baroz, Frederic; De Castaneda, Rafael Luis Ruiz; Boyer, Célia; Langs, Georg; Müller, Henning

2015-10-01

This article reports the user-oriented evaluation of a text- and content-based medical image retrieval system. User tests with radiologists using a search system for images in the medical literature are presented. The goal of the tests is to assess the usability of the system, identify system and interface aspects that need improvement and useful additions. Another objective is to investigate the system's added value to radiology information retrieval. The study provides an insight into required specifications and potential shortcomings of medical image retrieval systems through a concrete methodology for conducting user tests. User tests with a working image retrieval system of images from the biomedical literature were performed in an iterative manner, where each iteration had the participants perform radiology information seeking tasks and then refining the system as well as the user study design itself. During these tasks the interaction of the users with the system was monitored, usability aspects were measured, retrieval success rates recorded and feedback was collected through survey forms. In total, 16 radiologists participated in the user tests. The success rates in finding relevant information were on average 87% and 78% for image and case retrieval tasks, respectively. The average time for a successful search was below 3 min in both cases. Users felt quickly comfortable with the novel techniques and tools (after 5 to 15 min), such as content-based image retrieval and relevance feedback. User satisfaction measures show a very positive attitude toward the system's functionalities while the user feedback helped identifying the system's weak points. The participants proposed several potentially useful new functionalities, such as filtering by imaging modality and search for articles using image examples. The iterative character of the evaluation helped to obtain diverse and detailed feedback on all system aspects. Radiologists are quickly familiar with the functionalities but have several comments on desired functionalities. The analysis of the results can potentially assist system refinement for future medical information retrieval systems. Moreover, the methodology presented as well as the discussion on the limitations and challenges of such studies can be useful for user-oriented medical image retrieval evaluation, as user-oriented evaluation of interactive system is still only rarely performed. Such interactive evaluations can be limited in effort if done iteratively and can give many insights for developing better systems. Copyright © 2015. Published by Elsevier Ireland Ltd.

Using Context to Assist in Personal File Retrieval

DTIC Science & Technology

2006-08-25

of this work, filled in many of the gaps in my knowledge , and helped steer me toward solutions. Anind Dey was also invaluable in helping me design...like a personal assistant. Unfortunately, we are far from this ideal today. In fact, information management is one of the largest problems in...world wide web The world wide web is, perhaps, the largest distributed naming system in existence. To help manage this namespace, the web combines a

Generating region proposals for histopathological whole slide image retrieval.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu; Shi, Jun

2018-06-01

Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels. This paper presents a novel unsupervised region proposing method for histopathological WSI based on Selective Search. Specifically, the WSI is over-segmented into regions which are hierarchically merged until the WSI becomes a single region. Nucleus-oriented similarity measures for region mergence and Nucleus-Cytoplasm color space for histopathological image are specially defined to generate accurate region proposals. Additionally, we propose a new semi-supervised hashing method for image retrieval. The semantic features of images are extracted with Latent Dirichlet Allocation and transformed into binary hashing codes with Supervised Hashing. The methods are tested on a large-scale multi-class database of breast histopathological WSIs. The results demonstrate that for one WSI, our region proposing method can generate 7.3 thousand contoured regions which fit well with 95.8% of the ROIs annotated by pathologists. The proposed hashing method can retrieve a query image among 136 thousand images in 0.29 s and reach precision of 91% with only 10% of images labeled. The unsupervised region proposing method can generate regions as predictions of lesions in histopathological WSI. The region proposals can also serve as the training samples to train machine-learning models for image retrieval. The proposed hashing method can achieve fast and precise image retrieval with small amount of labels. Furthermore, the proposed methods can be potentially applied in online computer-aided-diagnosis systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Phase retrieval by coherent modulation imaging.

PubMed

Zhang, Fucai; Chen, Bo; Morrison, Graeme R; Vila-Comamala, Joan; Guizar-Sicairos, Manuel; Robinson, Ian K

2016-11-18

Phase retrieval is a long-standing problem in imaging when only the intensity of the wavefield can be recorded. Coherent diffraction imaging is a lensless technique that uses iterative algorithms to recover amplitude and phase contrast images from diffraction intensity data. For general samples, phase retrieval from a single-diffraction pattern has been an algorithmic and experimental challenge. Here we report a method of phase retrieval that uses a known modulation of the sample exit wave. This coherent modulation imaging method removes inherent ambiguities of coherent diffraction imaging and uses a reliable, rapidly converging iterative algorithm involving three planes. It works for extended samples, does not require tight support for convergence and relaxes dynamic range requirements on the detector. Coherent modulation imaging provides a robust method for imaging in materials and biological science, while its single-shot capability will benefit the investigation of dynamical processes with pulsed sources, such as X-ray free-electron lasers.

Use of ebRIM-based CSW with sensor observation services for registry and discovery of remote-sensing observations

NASA Astrophysics Data System (ADS)

Chen, Nengcheng; Di, Liping; Yu, Genong; Gong, Jianya; Wei, Yaxing

2009-02-01

Recent advances in Sensor Web geospatial data capture, such as high-resolution in satellite imagery and Web-ready data processing and modeling technologies, have led to the generation of large numbers of datasets from real-time or near real-time observations and measurements. Finding which sensor or data complies with criteria such as specific times, locations, and scales has become a bottleneck for Sensor Web-based applications, especially remote-sensing observations. In this paper, an architecture for use of the integration Sensor Observation Service (SOS) with the Open Geospatial Consortium (OGC) Catalogue Service-Web profile (CSW) is put forward. The architecture consists of a distributed geospatial sensor observation service, a geospatial catalogue service based on the ebXML Registry Information Model (ebRIM), SOS search and registry middleware, and a geospatial sensor portal. The SOS search and registry middleware finds the potential SOS, generating data granule information and inserting the records into CSW. The contents and sequence of the services, the available observations, and the metadata of the observations registry are described. A prototype system is designed and implemented using the service middleware technology and a standard interface and protocol. The feasibility and the response time of registry and retrieval of observations are evaluated using a realistic Earth Observing-1 (EO-1) SOS scenario. Extracting information from SOS requires the same execution time as record generation for CSW. The average data retrieval response time in SOS+CSW mode is 17.6% of that of the SOS-alone mode. The proposed architecture has the more advantages of SOS search and observation data retrieval than the existing sensor Web enabled systems.

Query Enhancement with Topic Detection and Disambiguation for Robust Retrieval

ERIC Educational Resources Information Center

Zhang, Hui

2013-01-01

With the rapid increase in the amount of available information, people nowadays rely heavily on information retrieval (IR) systems such as web search engine to fulfill their information needs. However, due to the lack of domain knowledge and the limitation of natural language such as synonyms and polysemes, many system users cannot formulate their…

Exploiting LCSH, LCC, and DDC To Retrieve Networked Resources: Issues and Challenges.

ERIC Educational Resources Information Center

Chan, Lois Mai

This paper examines how the nature of the World Wide Web and characteristics of networked resources affect subject access and analyzes the requirements of effective indexing and retrieval tools. The current and potential uses of existing tools and possible courses of future development are explored in the context of recent research. The first…

Using Metadata To Improve Organization and Information Retrieval on the WWW.

ERIC Educational Resources Information Center

Doan, Bich-Lien; Beigbeder, Michel; Girardot, Jean-Jacques; Jaillon, Philippe

The growing volume of heterogeneous and distributed information on the World Wide Web has made it increasingly difficult for existing tools to retrieve relevant information. To improve the performance of these tools, this paper suggests how to handle two aspects of the problem. The first aspect concerns a better representation and description of…

Identify, Organize, and Retrieve Items Using Zotero

ERIC Educational Resources Information Center

Clark, Brian; Stierman, John

2009-01-01

Librarians build collections. To do this they use tools that help them identify, organize, and retrieve items for the collection. Zotero (zoh-TAIR-oh) is such a tool that helps the user build a library of useful books, articles, web sites, blogs, etc., discovered while surfing online. A visit to Zotero's homepage, www.zotero.org, shows a number of…

An Empirical Comparison of Visualization Tools To Assist Information Retrieval on the Web.

ERIC Educational Resources Information Center

Heo, Misook; Hirtle, Stephen C.

2001-01-01

Discusses problems with navigation in hypertext systems, including cognitive overload, and describes a study that tested information visualization techniques to see which best represented the underlying structure of Web space. Considers the effects of visualization techniques on user performance on information searching tasks and the effects of…

Documenting historical data and accessing it on the World Wide Web

Treesearch

Malchus B. Baker; Daniel P. Huebner; Peter F. Ffolliott

2000-01-01

New computer technologies facilitate the storage, retrieval, and summarization of watershed-based data sets on the World Wide Web. These data sets are used by researchers when testing and validating predictive models, managers when planning and implementing watershed management practices, educators when learning about hydrologic processes, and decisionmakers when...

Searching to Translate and Translating to Search: When Information Retrieval Meets Machine Translation

ERIC Educational Resources Information Center

Ture, Ferhan

2013-01-01

With the adoption of web services in daily life, people have access to tremendous amounts of information, beyond any human's reading and comprehension capabilities. As a result, search technologies have become a fundamental tool for accessing information. Furthermore, the web contains information in multiple languages, introducing another barrier…

Enriching the Web of Data with Educational Information Using We-Share

ERIC Educational Resources Information Center

Ruiz-Calleja, Adolfo; Asensio-Pérez, Juan I.; Vega-Gorgojo, Guillermo; Gómez-Sánchez, Eduardo; Bote-Lorenzo, Miguel L.; Alario-Hoyos, Carlos

2017-01-01

This paper presents We-Share, a social annotation application that enables educators to publish and retrieve information about educational ICT tools. As a distinctive characteristic, We-Share provides educators data about educational tools already available on the Web of Data while allowing them to enrich such data with their experience using…

Creating a Web Site for Advocacy

ERIC Educational Resources Information Center

Erwin, Heather; Valley, Julia

2005-01-01

Because a mounting number of personnel, both young and old, continuously retrieve, seek out, communicate, assemble, and distribute information by way of the World Wide Web (WWW), it is vital for physical education teachers and other health/wellness promoters to tap into this source to advocate for their quality programs (Shiffett et al., 2001).…

World-Wide Web: The Information Universe.

ERIC Educational Resources Information Center

Berners-Lee, Tim; And Others

1992-01-01

Describes the World-Wide Web (W3) project, which is designed to create a global information universe using techniques of hypertext, information retrieval, and wide area networking. Discussion covers the W3 data model, W3 architecture, the document naming scheme, protocols, document formats, comparison with other systems, experience with the W3…

A comparative study for chest radiograph image retrieval using binary texture and deep learning classification.

PubMed

Anavi, Yaron; Kogan, Ilya; Gelbart, Elad; Geva, Ofer; Greenspan, Hayit

2015-08-01

In this work various approaches are investigated for X-ray image retrieval and specifically chest pathology retrieval. Given a query image taken from a data set of 443 images, the objective is to rank images according to similarity. Different features, including binary features, texture features, and deep learning (CNN) features are examined. In addition, two approaches are investigated for the retrieval task. One approach is based on the distance of image descriptors using the above features (hereon termed the "descriptor"-based approach); the second approach ("classification"-based approach) is based on a probability descriptor, generated by a pair-wise classification of each two classes (pathologies) and their decision values using an SVM classifier. Best results are achieved using deep learning features in a classification scheme.

A novel content-based medical image retrieval method based on query topic dependent image features (QTDIF)

NASA Astrophysics Data System (ADS)

Xiong, Wei; Qiu, Bo; Tian, Qi; Mueller, Henning; Xu, Changsheng

2005-04-01

Medical image retrieval is still mainly a research domain with a large variety of applications and techniques. With the ImageCLEF 2004 benchmark, an evaluation framework has been created that includes a database, query topics and ground truth data. Eleven systems (with a total of more than 50 runs) compared their performance in various configurations. The results show that there is not any one feature that performs well on all query tasks. Key to successful retrieval is rather the selection of features and feature weights based on a specific set of input features, thus on the query task. In this paper we propose a novel method based on query topic dependent image features (QTDIF) for content-based medical image retrieval. These feature sets are designed to capture both inter-category and intra-category statistical variations to achieve good retrieval performance in terms of recall and precision. We have used Gaussian Mixture Models (GMM) and blob representation to model medical images and construct the proposed novel QTDIF for CBIR. Finally, trained multi-class support vector machines (SVM) are used for image similarity ranking. The proposed methods have been tested over the Casimage database with around 9000 images, for the given 26 image topics, used for imageCLEF 2004. The retrieval performance has been compared with the medGIFT system, which is based on the GNU Image Finding Tool (GIFT). The experimental results show that the proposed QTDIF-based CBIR can provide significantly better performance than systems based general features only.

MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

2011-09-01

Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

Desktop Access to Full-Text NACA and NASA Reports: Systems Developed by NASA Langley Technical Library

NASA Technical Reports Server (NTRS)

Ambur, Manjula Y.; Adams, David L.; Trinidad, P. Paul

1997-01-01

NASA Langley Technical Library has been involved in developing systems for full-text information delivery of NACA/NASA technical reports since 1991. This paper will describe the two prototypes it has developed and the present production system configuration. The prototype systems are a NACA CD-ROM of thirty-three classic paper NACA reports and a network-based Full-text Electronic Reports Documents System (FEDS) constructed from both paper and electronic formats of NACA and NASA reports. The production system is the DigiDoc System (DIGItal Documents) presently being developed based on the experiences gained from the two prototypes. DigiDoc configuration integrates the on-line catalog database World Wide Web interface and PDF technology to provide a powerful and flexible search and retrieval system. It describes in detail significant achievements and lessons learned in terms of data conversion, storage technologies, full-text searching and retrieval, and image databases. The conclusions from the experiences of digitization and full- text access and future plans for DigiDoc system implementation are discussed.

Measuring and Predicting Tag Importance for Image Retrieval.

PubMed

Li, Shangwen; Purushotham, Sanjay; Chen, Chen; Ren, Yuzhuo; Kuo, C-C Jay

2017-12-01

Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature.

PubMed

Perez-Rey, David; Jimenez-Castellanos, Ana; Garcia-Remesal, Miguel; Crespo, Jose; Maojo, Victor

2012-04-05

Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

PubMed Central

2012-01-01

Background Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs). In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i) load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA), (ii) identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH), automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii) generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard PubMed interface. It has been tested on a public dataset of HL7-CDA documents, returning significantly fewer citations since queries are focused on characteristics identified within the EHR. For instance, compared with more than 200,000 citations retrieved by breast neoplasm, fewer than ten citations were retrieved when ten patient features were added using CDAPubMed. This is an open source tool that can be freely used for non-profit purposes and integrated with other existing systems. PMID:22480327

Enhancing navigation in biomedical databases by community voting and database-driven text classification

PubMed Central

Duchrow, Timo; Shtatland, Timur; Guettler, Daniel; Pivovarov, Misha; Kramer, Stefan; Weissleder, Ralph

2009-01-01

Background The breadth of biological databases and their information content continues to increase exponentially. Unfortunately, our ability to query such sources is still often suboptimal. Here, we introduce and apply community voting, database-driven text classification, and visual aids as a means to incorporate distributed expert knowledge, to automatically classify database entries and to efficiently retrieve them. Results Using a previously developed peptide database as an example, we compared several machine learning algorithms in their ability to classify abstracts of published literature results into categories relevant to peptide research, such as related or not related to cancer, angiogenesis, molecular imaging, etc. Ensembles of bagged decision trees met the requirements of our application best. No other algorithm consistently performed better in comparative testing. Moreover, we show that the algorithm produces meaningful class probability estimates, which can be used to visualize the confidence of automatic classification during the retrieval process. To allow viewing long lists of search results enriched by automatic classifications, we added a dynamic heat map to the web interface. We take advantage of community knowledge by enabling users to cast votes in Web 2.0 style in order to correct automated classification errors, which triggers reclassification of all entries. We used a novel framework in which the database "drives" the entire vote aggregation and reclassification process to increase speed while conserving computational resources and keeping the method scalable. In our experiments, we simulate community voting by adding various levels of noise to nearly perfectly labelled instances, and show that, under such conditions, classification can be improved significantly. Conclusion Using PepBank as a model database, we show how to build a classification-aided retrieval system that gathers training data from the community, is completely controlled by the database, scales well with concurrent change events, and can be adapted to add text classification capability to other biomedical databases. The system can be accessed at . PMID:19799796

A novel 3D shape descriptor for automatic retrieval of anatomical structures from medical images

NASA Astrophysics Data System (ADS)

Nunes, Fátima L. S.; Bergamasco, Leila C. C.; Delmondes, Pedro H.; Valverde, Miguel A. G.; Jackowski, Marcel P.

2017-03-01

Content-based image retrieval (CBIR) aims at retrieving from a database objects that are similar to an object provided by a query, by taking into consideration a set of extracted features. While CBIR has been widely applied in the two-dimensional image domain, the retrieval of3D objects from medical image datasets using CBIR remains to be explored. In this context, the development of descriptors that can capture information specific to organs or structures is desirable. In this work, we focus on the retrieval of two anatomical structures commonly imaged by Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) techniques, the left ventricle of the heart and blood vessels. Towards this aim, we developed the Area-Distance Local Descriptor (ADLD), a novel 3D local shape descriptor that employs mesh geometry information, namely facet area and distance from centroid to surface, to identify shape changes. Because ADLD only considers surface meshes extracted from volumetric medical images, it substantially diminishes the amount of data to be analyzed. A 90% precision rate was obtained when retrieving both convex (left ventricle) and non-convex structures (blood vessels), allowing for detection of abnormalities associated with changes in shape. Thus, ADLD has the potential to aid in the diagnosis of a wide range of vascular and cardiac diseases.

Source Update Capture in Information Agents

NASA Technical Reports Server (NTRS)

Ashish, Naveen; Kulkarni, Deepak; Wang, Yao

2003-01-01

In this paper we present strategies for successfully capturing updates at Web sources. Web-based information agents provide integrated access to autonomous Web sources that can get updated. For many information agent applications we are interested in knowing when a Web source to which the application provides access, has been updated. We may also be interested in capturing all the updates at a Web source over a period of time i.e., detecting the updates and, for each update retrieving and storing the new version of data. Previous work on update and change detection by polling does not adequately address this problem. We present strategies for intelligently polling a Web source for efficiently capturing changes at the source.

Comparison of k-means related clustering methods for nuclear medicine images segmentation

NASA Astrophysics Data System (ADS)

Borys, Damian; Bzowski, Pawel; Danch-Wierzchowska, Marta; Psiuk-Maksymowicz, Krzysztof

2017-03-01

In this paper, we evaluate the performance of SURF descriptor for high resolution satellite imagery (HRSI) retrieval through a BoVW model on a land-use/land-cover (LULC) dataset. Local feature approaches such as SIFT and SURF descriptors can deal with a large variation of scale, rotation and illumination of the images, providing, therefore, a better discriminative power and retrieval efficiency than global features, especially for HRSI which contain a great range of objects and spatial patterns. Moreover, we combine SURF and color features to improve the retrieval accuracy, and we propose to learn a category-specific dictionary for each image category which results in a more discriminative image representation and boosts the image retrieval performance.

Creating & using specimen images for collection documentation, research, teaching and outreach

NASA Astrophysics Data System (ADS)

Demouthe, J. F.

2012-12-01

In this age of digital media, there are many opportunities for use of good images of specimens. On-line resources such as institutional web sites and global sites such as PaleoNet and the Paleobiology Database provide venues for collection information and images. Pictures can also be made available to the general public through popular media sites such as Flickr and Facebook, where they can be retrieved and used by teachers, students, and the general public. The number of requests for specimen loans can be drastically reduced by offering the scientific community access to data and specimen images using the internet. This is an important consideration in these days of limited support budgets, since it reduces the amount of staff time necessary for giving researchers and educators access to collections. It also saves wear and tear on the specimens themselves. Many institutions now limit or refuse to send specimens out of their own countries because of the risks involved in going through security and customs. The internet can bridge political boundaries, allowing everyone equal access to collections. In order to develop photographic documentation of a collection, thoughtful preparation will make the process easier and more efficient. Acquire the necessary equipment, establish standards for images, and develop a simple workflow design. Manage images in the camera, and produce the best possible results, rather than relying on time-consuming editing after the fact. It is extremely important that the images of each specimen be of the highest quality and resolution. Poor quality, low resolution photos are not good for anything, and will often have to be retaken when another need arises. Repeating the photography process involves more handling of specimens and more staff time. Once good photos exist, smaller versions can be created for use on the web. The originals can be archived and used for publication and other purposes.

Selecting relevant 3D image features of margin sharpness and texture for lung nodule retrieval.

PubMed

Ferreira, José Raniery; de Azevedo-Marques, Paulo Mazzoncini; Oliveira, Marcelo Costa

2017-03-01

Lung cancer is the leading cause of cancer-related deaths in the world. Its diagnosis is a challenge task to specialists due to several aspects on the classification of lung nodules. Therefore, it is important to integrate content-based image retrieval methods on the lung nodule classification process, since they are capable of retrieving similar cases from databases that were previously diagnosed. However, this mechanism depends on extracting relevant image features in order to obtain high efficiency. The goal of this paper is to perform the selection of 3D image features of margin sharpness and texture that can be relevant on the retrieval of similar cancerous and benign lung nodules. A total of 48 3D image attributes were extracted from the nodule volume. Border sharpness features were extracted from perpendicular lines drawn over the lesion boundary. Second-order texture features were extracted from a cooccurrence matrix. Relevant features were selected by a correlation-based method and a statistical significance analysis. Retrieval performance was assessed according to the nodule's potential malignancy on the 10 most similar cases and by the parameters of precision and recall. Statistical significant features reduced retrieval performance. Correlation-based method selected 2 margin sharpness attributes and 6 texture attributes and obtained higher precision compared to all 48 extracted features on similar nodule retrieval. Feature space dimensionality reduction of 83 % obtained higher retrieval performance and presented to be a computationaly low cost method of retrieving similar nodules for the diagnosis of lung cancer.

Fast perceptual image hash based on cascade algorithm

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly; Yavtushenko, Evgeniya

2017-09-01

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. Image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

A Novel Image Retrieval Based on Visual Words Integration of SIFT and SURF

PubMed Central

Ali, Nouman; Bajwa, Khalid Bashir; Sablatnig, Robert; Chatzichristofis, Savvas A.; Iqbal, Zeshan; Rashid, Muhammad; Habib, Hafiz Adnan

2016-01-01

With the recent evolution of technology, the number of image archives has increased exponentially. In Content-Based Image Retrieval (CBIR), high-level visual information is represented in the form of low-level features. The semantic gap between the low-level features and the high-level image concepts is an open research problem. In this paper, we present a novel visual words integration of Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF). The two local features representations are selected for image retrieval because SIFT is more robust to the change in scale and rotation, while SURF is robust to changes in illumination. The visual words integration of SIFT and SURF adds the robustness of both features to image retrieval. The qualitative and quantitative comparisons conducted on Corel-1000, Corel-1500, Corel-2000, Oliva and Torralba and Ground Truth image benchmarks demonstrate the effectiveness of the proposed visual words integration. PMID:27315101

Chinese Herbal Medicine Image Recognition and Retrieval by Convolutional Neural Network

PubMed Central

Sun, Xin; Qian, Huinan

2016-01-01

Chinese herbal medicine image recognition and retrieval have great potential of practical applications. Several previous studies have focused on the recognition with hand-crafted image features, but there are two limitations in them. Firstly, most of these hand-crafted features are low-level image representation, which is easily affected by noise and background. Secondly, the medicine images are very clean without any backgrounds, which makes it difficult to use in practical applications. Therefore, designing high-level image representation for recognition and retrieval in real world medicine images is facing a great challenge. Inspired by the recent progress of deep learning in computer vision, we realize that deep learning methods may provide robust medicine image representation. In this paper, we propose to use the Convolutional Neural Network (CNN) for Chinese herbal medicine image recognition and retrieval. For the recognition problem, we use the softmax loss to optimize the recognition network; then for the retrieval problem, we fine-tune the recognition network by adding a triplet loss to search for the most similar medicine images. To evaluate our method, we construct a public database of herbal medicine images with cluttered backgrounds, which has in total 5523 images with 95 popular Chinese medicine categories. Experimental results show that our method can achieve the average recognition precision of 71% and the average retrieval precision of 53% over all the 95 medicine categories, which are quite promising given the fact that the real world images have multiple pieces of occluded herbal and cluttered backgrounds. Besides, our proposed method achieves the state-of-the-art performance by improving previous studies with a large margin. PMID:27258404

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval.

PubMed

Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R

2015-10-01

This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval

PubMed Central

Rahman, Md. Mahmudur; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.

2015-01-01

Abstract. This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term “concept” refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature. PMID:26730398

Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

ERIC Educational Resources Information Center

Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

2000-01-01

These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

Effects of Internal and External Vividness on Hippocampal Connectivity during Memory Retrieval

PubMed Central

Ford, Jaclyn H.; Kensinger, Elizabeth A.

2016-01-01

Successful memory for an image can be supported by retrieval of one’s personal reaction to the image (i.e., internal vividness), as well as retrieval of the specific details of the image itself (i.e., external vividness). Prior research suggests that memory vividness relies on regions within the medial temporal lobe, particularly the hippocampus, but it is unclear whether internal and external vividness are supported by the hippocampus in a similar way. To address this open question, the current study examined hippocampal connectivity associated with enhanced internal and external vividness ratings during retrieval. Participants encoded complex visual images paired with verbal titles. During a scanned retrieval session, they were presented with the titles and asked whether each had been seen with an image during encoding. Following retrieval of each image, participants were asked to rate internal and external vividness. Increased hippocampal activity was associated with higher vividness ratings for both scales, supporting prior evidence implicating the hippocampus in retrieval of memory detail. However, different patterns of hippocampal connectivity related to enhanced external and internal vividness. Further, hippocampal connectivity with medial prefrontal regions was associated with increased ratings of internal vividness, but with decreased ratings of external vividness. These findings suggest that the hippocampus may contribute to increased internal and external vividness via distinct mechanisms and that external and internal vividness of memories should be considered as separable measures. PMID:26778653

Where's My Data - WMD

NASA Technical Reports Server (NTRS)

Quach, William L.; Sesplaukis, Tadas; Owen-Mankovich, Kyran J.; Nakamura, Lori L.

2012-01-01

WMD provides a centralized interface to access data stored in the Mission Data Processing and Control System (MPCS) GDS (Ground Data Systems) databases during MSL (Mars Science Laboratory) Testbeds and ATLO (Assembly, Test, and Launch Operations) test sessions. The MSL project organizes its data based on venue (Testbed, ATLO, Ops), with each venue's data stored on a separate database, making it cumbersome for users to access data across the various venues. WMD allows sessions to be retrieved through a Web-based search using several criteria: host name, session start date, or session ID number. Sessions matching the search criteria will be displayed and users can then select a session to obtain and analyze the associated data. The uniqueness of this software comes from its collection of data retrieval and analysis features provided through a single interface. This allows users to obtain their data and perform the necessary analysis without having to worry about where and how to get the data, which may be stored in various locations. Additionally, this software is a Web application that only requires a standard browser without additional plug-ins, providing a cross-platform, lightweight solution for users to retrieve and analyze their data. This software solves the problem of efficiently and easily finding and retrieving data from thousands of MSL Testbed and ATLO sessions. WMD allows the user to retrieve their session in as little as one mouse click, and then to quickly retrieve additional data associated with the session.

Java and its future in biomedical computing.

PubMed Central

Rodgers, R P

1996-01-01

Java, a new object-oriented computing language related to C++, is receiving considerable attention due to its use in creating network-sharable, platform-independent software modules (known as "applets") that can be used with the World Wide Web. The Web has rapidly become the most commonly used information-retrieval tool associated with the global computer network known as the Internet, and Java has the potential to further accelerate the Web's application to medical problems. Java's potentially wide acceptance due to its Web association and its own technical merits also suggests that it may become a popular language for non-Web-based, object-oriented computing. PMID:8880677

Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

NASA Technical Reports Server (NTRS)

Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

2016-01-01

The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions.

PubMed

Karr, Jonathan R; Phillips, Nolan C; Covert, Markus W

2014-01-01

Mechanistic 'whole-cell' models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. http://www.wholecellsimdb.org SOURCE CODE REPOSITORY: URL: http://github.com/CovertLab/WholeCellSimDB. © The Author(s) 2014. Published by Oxford University Press.

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

PubMed Central

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods. PMID:24349277

Toward a standard reference database for computer-aided mammography

NASA Astrophysics Data System (ADS)

Oliveira, Júlia E. E.; Gueld, Mark O.; de A. Araújo, Arnaldo; Ott, Bastian; Deserno, Thomas M.

2008-03-01

Because of the lack of mammography databases with a large amount of codified images and identified characteristics like pathology, type of breast tissue, and abnormality, there is a problem for the development of robust systems for computer-aided diagnosis. Integrated to the Image Retrieval in Medical Applications (IRMA) project, we present an available mammography database developed from the union of: The Mammographic Image Analysis Society Digital Mammogram Database (MIAS), The Digital Database for Screening Mammography (DDSM), the Lawrence Livermore National Laboratory (LLNL), and routine images from the Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen. Using the IRMA code, standardized coding of tissue type, tumor staging, and lesion description was developed according to the American College of Radiology (ACR) tissue codes and the ACR breast imaging reporting and data system (BI-RADS). The import was done automatically using scripts for image download, file format conversion, file name, web page and information file browsing. Disregarding the resolution, this resulted in a total of 10,509 reference images, and 6,767 images are associated with an IRMA contour information feature file. In accordance to the respective license agreements, the database will be made freely available for research purposes, and may be used for image based evaluation campaigns such as the Cross Language Evaluation Forum (CLEF). We have also shown that it can be extended easily with further cases imported from a picture archiving and communication system (PACS).

Complex Event Processing for Content-Based Text, Image, and Video Retrieval

DTIC Science & Technology

2016-06-01

NY): Wiley- Interscience; 2000. Feldman R, Sanger J. The text mining handbook: advanced approaches in analyzing unstructured data. New York (NY...ARL-TR-7705 ● JUNE 2016 US Army Research Laboratory Complex Event Processing for Content-Based Text , Image, and Video Retrieval...ARL-TR-7705 ● JUNE 2016 US Army Research Laboratory Complex Event Processing for Content-Based Text , Image, and Video Retrieval

On-demand server-side image processing for web-based DICOM image display

NASA Astrophysics Data System (ADS)

Sakusabe, Takaya; Kimura, Michio; Onogi, Yuzo

2000-04-01

Low cost image delivery is needed in modern networked hospitals. If a hospital has hundreds of clients, cost of client systems is a big problem. Naturally, a Web-based system is the most effective solution. But a Web browser could not display medical images with certain image processing such as a lookup table transformation. We developed a Web-based medical image display system using Web browser and on-demand server-side image processing. All images displayed on a Web page are generated from DICOM files on a server, delivered on-demand. User interaction on the Web page is handled by a client-side scripting technology such as JavaScript. This combination makes a look-and-feel of an imaging workstation not only for its functionality but also for its speed. Real time update of images with tracing mouse motion is achieved on Web browser without any client-side image processing which may be done by client-side plug-in technology such as Java Applets or ActiveX. We tested performance of the system in three cases. Single client, small number of clients in a fast speed network, and large number of clients in a normal speed network. The result shows that there are very slight overhead for communication and very scalable in number of clients.

Diversification of visual media retrieval results using saliency detection

NASA Astrophysics Data System (ADS)

Muratov, Oleg; Boato, Giulia; De Natale, Franesco G. B.

2013-03-01

Diversification of retrieval results allows for better and faster search. Recently there has been proposed different methods for diversification of image retrieval results mainly utilizing text information and techniques imported from natural language processing domain. However, images contain visual information that is impossible to describe in text and the use of visual features is inevitable. Visual saliency is information about the main object of an image implicitly included by humans while creating visual content. For this reason it is naturally to exploit this information for the task of diversification of the content. In this work we study whether visual saliency can be used for the task of diversification and propose a method for re-ranking image retrieval results using saliency. The evaluation has shown that the use of saliency information results in higher diversity of retrieval results.

Content Based Lecture Video Retrieval Using Speech and Video Text Information

ERIC Educational Resources Information Center

Yang, Haojin; Meinel, Christoph

2014-01-01

In the last decade e-lecturing has become more and more popular. The amount of lecture video data on the "World Wide Web" (WWW) is growing rapidly. Therefore, a more efficient method for video retrieval in WWW or within large lecture video archives is urgently needed. This paper presents an approach for automated video indexing and video…

ASIST 2001. Information in a Networked World: Harnessing the Flow. Part III: Poster Presentations.

ERIC Educational Resources Information Center

Proceedings of the ASIST Annual Meeting, 2001

2001-01-01

Topics of Poster Presentations include: electronic preprints; intranets; poster session abstracts; metadata; information retrieval; watermark images; video games; distributed information retrieval; subject domain knowledge; data mining; information theory; course development; historians' use of pictorial images; information retrieval software;…

Enhanced Information Retrieval Using AJAX

NASA Astrophysics Data System (ADS)

Kachhwaha, Rajendra; Rajvanshi, Nitin

2010-11-01

Information Retrieval deals with the representation, storage, organization of, and access to information items. The representation and organization of information items should provide the user with easy access to the information with the rapid development of Internet, large amounts of digitally stored information is readily available on the World Wide Web. This information is so huge that it becomes increasingly difficult and time consuming for the users to find the information relevant to their needs. The explosive growth of information on the Internet has greatly increased the need for information retrieval systems. However, most of the search engines are using conventional information retrieval systems. An information system needs to implement sophisticated pattern matching tools to determine contents at a faster rate. AJAX has recently emerged as the new tool such the of information retrieval process of information retrieval can become fast and information reaches the use at a faster pace as compared to conventional retrieval systems.

Web Based Data Access to the World Data Center for Climate

NASA Astrophysics Data System (ADS)

Toussaint, F.; Lautenschlager, M.

2006-12-01

The World Data Center for Climate (WDC-Climate, www.wdc-climate.de) is hosted by the Model &Data Group (M&D) of the Max Planck Institute for Meteorology. The M&D department is financed by the German government and uses the computers and mass storage facilities of the German Climate Computing Centre (Deutsches Klimarechenzentrum, DKRZ). The WDC-Climate provides web access to 200 Terabytes of climate data; the total mass storage archive contains nearly 4 Petabytes. Although the majority of the datasets concern model output data, some satellite and observational data are accessible as well. The underlying relational database is distributed on five servers. The CERA relational data model is used to integrate catalogue data and mass data. The flexibility of the model allows to store and access very different types of data and metadata. The CERA metadata catalogue provides easy access to the content of the CERA database as well as to other data in the web. Visit ceramodel.wdc-climate.de for additional information on the CERA data model. The majority of the users access data via the CERA metadata catalogue, which is open without registration. However, prior to retrieving data user are required to check in and apply for a userid and password. The CERA metadata catalogue is servlet based. So it is accessible worldwide through any web browser at cera.wdc-climate.de. In addition to data and metadata access by the web catalogue, WDC-Climate offers a number of other forms of web based data access. All metadata are available via http request as xml files in various metadata formats (ISO, DC, etc., see wini.wdc-climate.de) which allows for easy data interchange with other catalogues. Model data can be retrieved in GRIB, ASCII, NetCDF, and binary (IEEE) format. WDC-Climate serves as data centre for various projects. Since xml files are accessible by http, the integration of data into applications of different projects is very easy. Projects supported by WDC-Climate are e.g. CEOP, IPCC, and CARIBIC. A script tool for data download (jblob) is offered on the web page, to make retrieval of huge data quantities more comfortable.

X-Ray Phase Imaging for Breast Cancer Detection

DTIC Science & Technology

2010-09-01

regularization seeks the minimum- norm , least squares solution for phase retrieval. The retrieval result with Tikhonov regularization is still unsatisfactory...of norm , that can effectively reflect the accuracy of the retrieved data as an image, if ‖δ Ik+1−δ Ik‖ is less than a predefined threshold value β...pointed out that the proper norm for images is the total variation (TV) norm , which is the L1 norm of the gradient of the image function, and not the

Determining the Navigational Aids Use on the Internet: The Information Technologies Teacher Candidates' Case

ERIC Educational Resources Information Center

Kuzu, Abdullah; Firat, Mehmet

2010-01-01

The Internet users who fail to cope with navigation may generally face various problems such as disorientation, distraction, low motivation and abandonment of information retrieval. Therefore, navigational aids are frequently used in today's Web browsers and Web sites to help users navigate on the Internet. However, it is asserted that…

The Impact of Subject Indexes on Semantic Indeterminacy in Enterprise Document Retrieval

ERIC Educational Resources Information Center

Schymik, Gregory

2012-01-01

Ample evidence exists to support the conclusion that enterprise search is failing its users. This failure is costing corporate America billions of dollars every year. Most enterprise search engines are built using web search engines as their foundations. These search engines are optimized for web use and are inadequate when used inside the…

Maintaining a News Perspective Remotely through Online Information Retrieval: Task-Based Web Experiences of Foreign News Correspondents

ERIC Educational Resources Information Center

Lin, Kuanyuh Tony

2009-01-01

A two-stage mixed methods approach was used to examine how foreign correspondents stationed in the United States use World Wide Web technology to maintain their news perspectives remotely. Despite emerging technology playing an increasingly significant role in the production of international journalism, the subject under investigation has been…

QUT Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents

DTIC Science & Technology

2012-11-01

zero for the QUTParaTQEg1 sys- tem (and the best performance across all participants was non-zero), included: 1. Topic 157: The beatles rock band 2...Topic 162: dnr 3. Topic 163: arkansas 5 4. Topic 167: barbados 5. Topic 170: scooters 6. Topic 179: black history 7. Topic 188: internet phone service

SIFT Meets CNN: A Decade Survey of Instance Retrieval.

PubMed

Zheng, Liang; Yang, Yi; Tian, Qi

2018-05-01

In the early days, content-based image retrieval (CBIR) was studied with global features. Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively studied for over a decade due to the advantage of SIFT in dealing with image transformations. Recently, image representations based on the convolutional neural network (CNN) have attracted increasing interest in the community and demonstrated impressive performance. Given this time of rapid evolution, this article provides a comprehensive survey of instance retrieval over the last decade. Two broad categories, SIFT-based and CNN-based methods, are presented. For the former, according to the codebook size, we organize the literature into using large/medium-sized/small codebooks. For the latter, we discuss three lines of methods, i.e., using pre-trained or fine-tuned CNN models, and hybrid methods. The first two perform a single-pass of an image to the network, while the last category employs a patch-based feature extraction scheme. This survey presents milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods. After analyzing and comparing retrieval performance of different categories on several datasets, we discuss promising directions towards generic and specialized instance retrieval.

Design of Content Based Image Retrieval Scheme for Diabetic Retinopathy Images using Harmony Search Algorithm.

PubMed

Sivakamasundari, J; Natarajan, V

2015-01-01

Diabetic Retinopathy (DR) is a disorder that affects the structure of retinal blood vessels due to long-standing diabetes mellitus. Automated segmentation of blood vessel is vital for periodic screening and timely diagnosis. An attempt has been made to generate continuous retinal vasculature for the design of Content Based Image Retrieval (CBIR) application. The typical normal and abnormal retinal images are preprocessed to improve the vessel contrast. The blood vessels are segmented using evolutionary based Harmony Search Algorithm (HSA) combined with Otsu Multilevel Thresholding (MLT) method by best objective functions. The segmentation results are validated with corresponding ground truth images using binary similarity measures. The statistical, textural and structural features are obtained from the segmented images of normal and DR affected retina and are analyzed. CBIR in medical image retrieval applications are used to assist physicians in clinical decision-support techniques and research fields. A CBIR system is developed using HSA based Otsu MLT segmentation technique and the features obtained from the segmented images. Similarity matching is carried out between the features of query and database images using Euclidean Distance measure. Similar images are ranked and retrieved. The retrieval performance of CBIR system is evaluated in terms of precision and recall. The CBIR systems developed using HSA based Otsu MLT and conventional Otsu MLT methods are compared. The retrieval performance such as precision and recall are found to be 96% and 58% for CBIR system using HSA based Otsu MLT segmentation. This automated CBIR system could be recommended for use in computer assisted diagnosis for diabetic retinopathy screening.

Virtual Patients on the Semantic Web: A Proof-of-Application Study

PubMed Central

Dafli, Eleni; Antoniou, Panagiotis; Ioannidis, Lazaros; Dombros, Nicholas; Topps, David

2015-01-01

Background Virtual patients are interactive computer simulations that are increasingly used as learning activities in modern health care education, especially in teaching clinical decision making. A key challenge is how to retrieve and repurpose virtual patients as unique types of educational resources between different platforms because of the lack of standardized content-retrieving and repurposing mechanisms. Semantic Web technologies provide the capability, through structured information, for easy retrieval, reuse, repurposing, and exchange of virtual patients between different systems. Objective An attempt to address this challenge has been made through the mEducator Best Practice Network, which provisioned frameworks for the discovery, retrieval, sharing, and reuse of medical educational resources. We have extended the OpenLabyrinth virtual patient authoring and deployment platform to facilitate the repurposing and retrieval of existing virtual patient material. Methods A standalone Web distribution and Web interface, which contains an extension for the OpenLabyrinth virtual patient authoring system, was implemented. This extension was designed to semantically annotate virtual patients to facilitate intelligent searches, complex queries, and easy exchange between institutions. The OpenLabyrinth extension enables OpenLabyrinth authors to integrate and share virtual patient case metadata within the mEducator3.0 network. Evaluation included 3 successive steps: (1) expert reviews; (2) evaluation of the ability of health care professionals and medical students to create, share, and exchange virtual patients through specific scenarios in extended OpenLabyrinth (OLabX); and (3) evaluation of the repurposed learning objects that emerged from the procedure. Results We evaluated 30 repurposed virtual patient cases. The evaluation, with a total of 98 participants, demonstrated the system’s main strength: the core repurposing capacity. The extensive metadata schema presentation facilitated user exploration and filtering of resources. Usability weaknesses were primarily related to standard computer applications’ ease of use provisions. Most evaluators provided positive feedback regarding educational experiences on both content and system usability. Evaluation results replicated across several independent evaluation events. Conclusions The OpenLabyrinth extension, as part of the semantic mEducator3.0 approach, is a virtual patient sharing approach that builds on a collection of Semantic Web services and federates existing sources of clinical and educational data. It is an effective sharing tool for virtual patients and has been merged into the next version of the app (OpenLabyrinth 3.3). Such tool extensions may enhance the medical education arsenal with capacities of creating simulation/game-based learning episodes, massive open online courses, curricular transformations, and a future robust infrastructure for enabling mobile learning. PMID:25616272

Virtual patients on the semantic Web: a proof-of-application study.

PubMed

Dafli, Eleni; Antoniou, Panagiotis; Ioannidis, Lazaros; Dombros, Nicholas; Topps, David; Bamidis, Panagiotis D

2015-01-22

Virtual patients are interactive computer simulations that are increasingly used as learning activities in modern health care education, especially in teaching clinical decision making. A key challenge is how to retrieve and repurpose virtual patients as unique types of educational resources between different platforms because of the lack of standardized content-retrieving and repurposing mechanisms. Semantic Web technologies provide the capability, through structured information, for easy retrieval, reuse, repurposing, and exchange of virtual patients between different systems. An attempt to address this challenge has been made through the mEducator Best Practice Network, which provisioned frameworks for the discovery, retrieval, sharing, and reuse of medical educational resources. We have extended the OpenLabyrinth virtual patient authoring and deployment platform to facilitate the repurposing and retrieval of existing virtual patient material. A standalone Web distribution and Web interface, which contains an extension for the OpenLabyrinth virtual patient authoring system, was implemented. This extension was designed to semantically annotate virtual patients to facilitate intelligent searches, complex queries, and easy exchange between institutions. The OpenLabyrinth extension enables OpenLabyrinth authors to integrate and share virtual patient case metadata within the mEducator3.0 network. Evaluation included 3 successive steps: (1) expert reviews; (2) evaluation of the ability of health care professionals and medical students to create, share, and exchange virtual patients through specific scenarios in extended OpenLabyrinth (OLabX); and (3) evaluation of the repurposed learning objects that emerged from the procedure. We evaluated 30 repurposed virtual patient cases. The evaluation, with a total of 98 participants, demonstrated the system's main strength: the core repurposing capacity. The extensive metadata schema presentation facilitated user exploration and filtering of resources. Usability weaknesses were primarily related to standard computer applications' ease of use provisions. Most evaluators provided positive feedback regarding educational experiences on both content and system usability. Evaluation results replicated across several independent evaluation events. The OpenLabyrinth extension, as part of the semantic mEducator3.0 approach, is a virtual patient sharing approach that builds on a collection of Semantic Web services and federates existing sources of clinical and educational data. It is an effective sharing tool for virtual patients and has been merged into the next version of the app (OpenLabyrinth 3.3). Such tool extensions may enhance the medical education arsenal with capacities of creating simulation/game-based learning episodes, massive open online courses, curricular transformations, and a future robust infrastructure for enabling mobile learning.

Two-dimensional thermography image retrieval from zig-zag scanned data with TZ-SCAN

NASA Astrophysics Data System (ADS)

Okumura, Hiroshi; Yamasaki, Ryohei; Arai, Kohei

2008-10-01

TZ-SCAN is a simple and low cost thermal imaging device which consists of a single point radiation thermometer on a tripod with a pan-tilt rotator, a DC motor controller board with a USB interface, and a laptop computer for rotator control, data acquisition, and data processing. TZ-SCAN acquires a series of zig-zag scanned data and stores the data as CSV file. A 2-D thermal distribution image can be retrieved by using the second quefrency peak calculated from TZ-SCAN data. An experiment is conducted to confirm the validity of the thermal retrieval algorithm. The experimental result shows efficient accuracy for 2-D thermal distribution image retrieval.

The Influence of Spatial Resolutions on the Retrieval Accuracy of Sea Surface Wind Speed with Cross-polarized C-band SAR images

NASA Astrophysics Data System (ADS)

Zhang, K.; Han, B.; Mansaray, L. R.; Xu, X.; Guo, Q.; Jingfeng, H.

2017-12-01

Synthetic aperture radar (SAR) instruments on board satellites are valuable for high-resolution wind field mapping, especially for coastal studies. Since the launch of Sentinel-1A on April 3, 2014, followed by Sentinel-1B on April 25, 2016, large amount of C-band SAR data have been added to a growing accumulation of SAR datasets (ERS-1/2, RADARSAT-1/2, ENVISAT). These new developments are of great significance for a wide range of applications in coastal sea areas, especially for high spatial resolution wind resource assessment, in which the accuracy of retrieved wind fields is extremely crucial. Recently, it is reported that wind speeds can also be retrieved from C-band cross-polarized SAR images, which is an important complement to wind speed retrieval from co-polarization. However, there is no consensus on the optimal resolution for wind speed retrieval from cross-polarized SAR images. This paper presents a comparison strategy for investigating the influence of spatial resolutions on sea surface wind speed retrieval accuracy with cross-polarized SAR images. Firstly, for wind speeds retrieved from VV-polarized images, the optimal geophysical C-band model (CMOD) function was selected among four CMOD functions. Secondly, the most suitable C-band cross-polarized ocean (C-2PO) model was selected between two C-2POs for the VH-polarized image dataset. Then, the VH-wind speeds retrieved by the selected C-2PO were compared with the VV-polarized sea surface wind speeds retrieved using the optimal CMOD, which served as reference, at different spatial resolutions. Results show that the VH-polarized wind speed retrieval accuracy increases rapidly with the decrease in spatial resolutions from 100 m to 1000 m, with a drop in RMSE of 42%. However, the improvement in wind speed retrieval accuracy levels off with spatial resolutions decreasing from 1000 m to 5000 m. This demonstrates that the pixel spacing of 1 km may be the compromising choice for the tradeoff between the spatial resolution and wind speed retrieval accuracy with cross-polarized images obtained from RADASAT-2 fine quad polarization mode. Figs. 1 illustrate the variation of the following statistical parameters: Bias, Corr, R2, RMSE and STD as a function of spatial resolution.

Gram-Schmidt orthonormalization for retrieval of amplitude images under sinusoidal patterns of illumination

USDA-ARS?s Scientific Manuscript database

Structured illumination using sinusoidal patterns has been utilized for optical imaging of biological tissues in biomedical research and, of horticultural products. Implementation of structured-illumination imaging relies on retrieval of amplitude images, which is conventionally achieved by a phase-...

Feature hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

Display gamma is an important factor in Web image viewing

NASA Astrophysics Data System (ADS)

Zhang, Xuemei; Lavin, Yingmei; Silverstein, D. Amnon

2001-06-01

We conducted a perceptual image preference experiment over the web to find our (1) if typical computer users have significant variations in their display gamma settings, and (2) if so, do the gamma settings have significant perceptual effect on the appearance of images in their web browsers. The digital image renderings used were found to have preferred tone characteristics from a previous lab- controlled experiment. They were rendered with 4 different gamma settings. The subjects were asked to view the images over the web, with their own computer equipment and web browsers. The subjects werewe asked to view the images over the web, with their own computer equipment and web browsers. The subjects made pair-wise subjective preference judgements on which rendering they liked bets for each image. Each subject's display gamma setting was estimated using a 'gamma estimator' tool, implemented as a Java applet. The results indicated that (1) the user's gamma settings, as estimated in the experiment, span a wide range from about 1.8 to about 3.0; (2) the subjects preferred images that werewe rendered with a 'correct' gamma value matching their display setting. Subjects disliked images rendered with a gamma value not matching their displays'. This indicates that display gamma estimation is a perceptually significant factor in web image optimization.

Interactive content-based image retrieval (CBIR) computer-aided diagnosis (CADx) system for ultrasound breast masses using relevance feedback

NASA Astrophysics Data System (ADS)

Cho, Hyun-chong; Hadjiiski, Lubomir; Sahiner, Berkman; Chan, Heang-Ping; Paramagul, Chintana; Helvie, Mark; Nees, Alexis V.

2012-03-01

We designed a Content-Based Image Retrieval (CBIR) Computer-Aided Diagnosis (CADx) system to assist radiologists in characterizing masses on ultrasound images. The CADx system retrieves masses that are similar to a query mass from a reference library based on computer-extracted features that describe texture, width-to-height ratio, and posterior shadowing of a mass. Retrieval is performed with k nearest neighbor (k-NN) method using Euclidean distance similarity measure and Rocchio relevance feedback algorithm (RRF). In this study, we evaluated the similarity between the query and the retrieved masses with relevance feedback using our interactive CBIR CADx system. The similarity assessment and feedback were provided by experienced radiologists' visual judgment. For training the RRF parameters, similarities of 1891 image pairs obtained from 62 masses were rated by 3 MQSA radiologists using a 9-point scale (9=most similar). A leave-one-out method was used in training. For each query mass, 5 most similar masses were retrieved from the reference library using radiologists' similarity ratings, which were then used by RRF to retrieve another 5 masses for the same query. The best RRF parameters were chosen based on three simulated observer experiments, each of which used one of the radiologists' ratings for retrieval and relevance feedback. For testing, 100 independent query masses on 100 images and 121 reference masses on 230 images were collected. Three radiologists rated the similarity between the query and the computer-retrieved masses. Average similarity ratings without and with RRF were 5.39 and 5.64 on the training set and 5.78 and 6.02 on the test set, respectively. The average Az values without and with RRF were 0.86+/-0.03 and 0.87+/-0.03 on the training set and 0.91+/-0.03 and 0.90+/-0.03 on the test set, respectively. This study demonstrated that RRF improved the similarity of the retrieved masses.

Retrieval of land cover information under thin fog in Landsat TM image

NASA Astrophysics Data System (ADS)

Wei, Yuchun

2008-04-01

Thin fog, which often appears in remote sensing image of subtropical climate region, has resulted in the low image quantity and bad image mapping. Therefore, it is necessary to develop the image processing method to retrieve land cover information under thin fog. In this paper, the Landsat TM image near the Taihu Lake that is in the subtropical climate zone of China was used as an example, and the workflow and method used to retrieve the land cover information under thin fog have been built based on ENVI software and a single TM image. The basic step covers three parts: 1) isolating the thin fog area in image according to the spectral difference of different bands; 2) retrieving the visible band information of different land cover types under thin fog from the near-infrared bands according to the relationships between near-infrared bands and visible bands of different land cover types in the area without fog; 3) image post-process. The result showed that the method in the paper is easy and suitable, and can be used to improve the quantity of TM image mapping more effectively.

Autobiographical memory specificity in response to verbal and pictorial cues in clinical depression.

PubMed

Ridout, Nathan; Dritschel, Barbara; Matthews, Keith; O'Carroll, Ronan

2016-06-01

Depressed individuals have been consistently shown to exhibit problems in accessing specific memories of events from their past and instead tend to retrieve categorical summaries of events. The majority of studies examining autobiographical memory changes associated with psychopathology have tended to use word cues, but only one study to date has used images (with PTSD patients). to determine if using images to cue autobiographical memories would reduce the memory specificity deficit exhibited by patients with depression in comparison to healthy controls. Twenty-five clinically depressed patients and twenty-five healthy controls were assessed on two versions of the autobiographical memory test; cued with emotional words and images. Depressed patients retrieved significantly fewer specific memories, and a greater number of categorical, than did the controls. Controls retrieved a greater proportion of specific memories to images compared to words, whereas depressed patients retrieved a similar proportion of specific memories to both images and words. no information about the presence and severity of past trauma was collected. results suggest that the overgeneral memory style in depression generalises from verbal to pictorial cues. This is important because retrieval to images may provide a more ecologically valid test of everyday memory experiences than word-cued retrieval.. Copyright © 2016 Elsevier Ltd. All rights reserved.

Observations from the GOES Space Environment Monitor and Solar X-ray Imager are now available in a whole new way!

NASA Astrophysics Data System (ADS)

Wilkinson, D. C.

2012-12-01

NOAA's Geosynchronous Operational Environmental Satellites (GOES) have been observing the environment in near-earth-space for over 37 years. Those data are down-linked and processed by the Space Weather Prediction Center (SWPC) and form the cornerstone of their alert and forecast services. At the close of each UT day these data are ingested by the National Geophysical Data Center (NGDC) where they are merged into the national archive and made available to the user community in a uniform manner. In 2012 NGDC unveiled a RESTful web service for accessing these data. What does this mean? Users can now build a web-like URL using simple predefined constructs that allows their browser or custom software to directly access the relational archives and bundle the requested data into a variety of popular formats. The user can select precisely the data they need and the results are delivered immediately. NGDC understands that many users are perfectly happy retrieving data via pre-generated files and will continue to provide internally documented NetCDF and CSV files far into the future.

Observations from the GOES Space Environment Monitor and Solar X-ray Imager are now available in a whole new way!

NASA Astrophysics Data System (ADS)

Wilkinson, D. C.

2013-12-01

NOAA's Geosynchronous Operational Environmental Satellites (GOES) have been observing the environment in near-earth-space for over 37 years. Those data are down-linked and processed by the Space Weather Prediction Center (SWPC) and form the cornerstone of their alert and forecast services. At the close of each UT day these data are ingested by the National Geophysical Data Center (NGDC) where they are merged into the national archive and made available to the user community in a uniform manner. In 2012 NGDC unveiled a RESTful web service for accessing these data. What does this mean? Users can now build a web-like URL using simple predefined constructs that allows their browser or custom software to directly access the relational archives and bundle the requested data into a variety of popular formats. The user can select precisely the data they need and the results are delivered immediately. NGDC understands that many users are perfectly happy retrieving data via pre-generated files and will continue to provide internally documented NetCDF and CSV files far into the future.

The Department of Defense and the Power of Cloud Computing: Weighing Acceptable Cost Versus Acceptable Risk

DTIC Science & Technology

2016-04-01

the DOD will put DOD systems and data at a risk level comparable to that of their neighbors in the cloud. Just as a user browses a Web page on the...proxy servers for controlling user access to Web pages, and large-scale storage for data management. Each of these devices allows access to the...user to develop applications. Acunetics.com describes Web applications as “computer programs allowing Website visitors to submit and retrieve data

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

Casella, R.

RESTful (REpresentational State Transfer) web services are an alternative implementation to SOAP/RPC web services in a client/server model. BNLs IT Division has started deploying RESTful Web Services for enterprise data retrieval and manipulation. Data is currently used by system administrators for tracking configuration information and as it is expanded will be used by Cyber Security for vulnerability management and as an aid to cyber investigations. This talk will describe the implementation and outstanding issues as well as some of the reasons for choosing RESTful over SOAP/RPC and future directions.

Combination of image descriptors for the exploration of cultural photographic collections

NASA Astrophysics Data System (ADS)

Bhowmik, Neelanjan; Gouet-Brunet, Valérie; Bloch, Gabriel; Besson, Sylvain

2017-01-01

The rapid growth of image digitization and collections in recent years makes it challenging and burdensome to organize, categorize, and retrieve similar images from voluminous collections. Content-based image retrieval (CBIR) is immensely convenient in this context. A considerable number of local feature detectors and descriptors are present in the literature of CBIR. We propose a model to anticipate the best feature combinations for image retrieval-related applications. Several spatial complementarity criteria of local feature detectors are analyzed and then engaged in a regression framework to find the optimal combination of detectors for a given dataset and are better adapted for each given image; the proposed model is also useful to optimally fix some other parameters, such as the k in k-nearest neighbor retrieval. Three public datasets of various contents and sizes are employed to evaluate the proposal, which is legitimized by improving the quality of retrieval notably facing classical approaches. Finally, the proposed image search engine is applied to the cultural photographic collections of a French museum, where it demonstrates its added value for the exploration and promotion of these contents at different levels from their archiving up to their exhibition in or ex situ.

Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images

PubMed Central

Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro; Aoki, Hiroshi; Takeuchi, Ken; Suzuki, Yasuo

2017-01-01

Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical colonoscopy examinations are particularly important for detecting cancers at early stages while still treatable. However, diagnostic accuracy is highly dependent on both the experience and knowledge of the medical doctor. Moreover, it is extremely difficult, even for specialist doctors, to detect the early stages of cancer when obscured by inflammations of the colonic mucosa due to intractable inflammatory bowel diseases, such as ulcerative colitis. Thus, to assist the UC diagnosis, it is necessary to develop a new technology that can retrieve similar cases of diagnostic target image from cases in the past that stored the diagnosed images with various symptoms of colonic mucosa. In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multiscale objects. The proposed method can retrieve similar colonoscopy images despite varying visible sizes of the target objects. Through three experiments conducted with real clinical colonoscopy images, we demonstrate that the method is able to retrieve objects of any visible size and any location at a high level of accuracy. PMID:28255295

Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images.

PubMed

Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro; Aoki, Hiroshi; Takeuchi, Ken; Suzuki, Yasuo

2017-01-01

Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical colonoscopy examinations are particularly important for detecting cancers at early stages while still treatable. However, diagnostic accuracy is highly dependent on both the experience and knowledge of the medical doctor. Moreover, it is extremely difficult, even for specialist doctors, to detect the early stages of cancer when obscured by inflammations of the colonic mucosa due to intractable inflammatory bowel diseases, such as ulcerative colitis. Thus, to assist the UC diagnosis, it is necessary to develop a new technology that can retrieve similar cases of diagnostic target image from cases in the past that stored the diagnosed images with various symptoms of colonic mucosa. In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multiscale objects. The proposed method can retrieve similar colonoscopy images despite varying visible sizes of the target objects. Through three experiments conducted with real clinical colonoscopy images, we demonstrate that the method is able to retrieve objects of any visible size and any location at a high level of accuracy.

Phase retrieval by coherent modulation imaging

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

Zhang, Fucai; Chen, Bo; Morrison, Graeme R.

Phase retrieval is a long-standing problem in imaging when only the intensity of the wavefield can be recorded. Coherent diffraction imaging (CDI) is a lensless technique that uses iterative algorithms to recover amplitude and phase contrast images from diffraction intensity data. For general samples, phase retrieval from a single diffraction pattern has been an algorithmic and experimental challenge. Here we report a method of phase retrieval that uses a known modulation of the sample exit-wave. This coherent modulation imaging (CMI) method removes inherent ambiguities of CDI and uses a reliable, rapidly converging iterative algorithm involving three planes. It works formore » extended samples, does not require tight support for convergence, and relaxes dynamic range requirements on the detector. CMI provides a robust method for imaging in materials and biological science, while its single-shot capability will benefit the investigation of dynamical processes with pulsed sources, such as X-ray free electron laser.« less

Phase retrieval by coherent modulation imaging

DOE PAGES

Zhang, Fucai; Chen, Bo; Morrison, Graeme R.; ...

2016-11-18

Phase retrieval is a long-standing problem in imaging when only the intensity of the wavefield can be recorded. Coherent diffraction imaging (CDI) is a lensless technique that uses iterative algorithms to recover amplitude and phase contrast images from diffraction intensity data. For general samples, phase retrieval from a single diffraction pattern has been an algorithmic and experimental challenge. Here we report a method of phase retrieval that uses a known modulation of the sample exit-wave. This coherent modulation imaging (CMI) method removes inherent ambiguities of CDI and uses a reliable, rapidly converging iterative algorithm involving three planes. It works formore » extended samples, does not require tight support for convergence, and relaxes dynamic range requirements on the detector. CMI provides a robust method for imaging in materials and biological science, while its single-shot capability will benefit the investigation of dynamical processes with pulsed sources, such as X-ray free electron laser.« less

Empowering schoolchildren to do astronomical science with images

NASA Astrophysics Data System (ADS)

Raeside, L.; Busschots, B.; O'Cinneide, E.; Foy, S.; Keating, J. G.

2005-06-01

In 1991 the TIE (Telescopes in Education) Foundation provided schoolchildren with the ability to access professional observatory telescopes remotely. TIE has raised the profile of astronomy and science among schoolchildren. Since the initiation of this facility the TIE Foundation have spread their reach from one telescope in the US to many telescopes and many schools across the globe. The VTIE (Virtual Telescopes in Education) project was launched in 2001 to build on the success of TIE. The VTIE VLE (Virtual Learning Environment) provides a Web portal through which pupils can create a scientific proposal, retrieve astronomical images, and produce a scientific paper summarizing their learning experiences of the VTIE scientific process. Since the completion of the first formative evaluations of VTIE (which involved over 250 schoolchildren) it has been observed that the participating schoolchildren have had difficulty completing and understanding the practical imaging aspects of astronomical science. Our experimental observations have revealed that the imaging tools currently available to astronomers have not ported well to schools. The VTIE imaging tools developed during our research will provide schoolchildren with the ability to store, acquire, manipulate and analyze images within the VTIE VLE. It is hypothesized herein that the provision of exclusively child-centered imaging software components will improve greatly the children's empowerment within the VTIE scientific process. Consequentially the addition of fully integrated child-centered imaging tools will contribute positively to the overall VTIE goal to promote science among schoolchildren.

Video and image retrieval beyond the cognitive level: the needs and possibilities

NASA Astrophysics Data System (ADS)

Hanjalic, Alan

2000-12-01

The worldwide research efforts in the are of image and video retrieval have concentrated so far on increasing the efficiency and reliability of extracting the elements of image and video semantics and so on improving the search and retrieval performance at the cognitive level of content abstraction. At this abstraction level, the user is searching for 'factual' or 'objective' content such as image showing a panorama of San Francisco, an outdoor or an indoor image, a broadcast news report on a defined topic, a movie dialog between the actors A and B or the parts of a basketball game showing fast breaks, steals and scores. These efforts, however, do not address the retrieval applications at the so-called affective level of content abstraction where the 'ground truth' is not strictly defined. Such applications are, for instance, those where subjectivity of the user plays the major role, e.g. the task of retrieving all images that the user 'likes most', and those that are based on 'recognizing emotions' in audiovisual data. Typical examples are searching for all images that 'radiate happiness', identifying all 'sad' movie fragments and looking for the 'romantic landscapes', 'sentimental' movie segments, 'movie highlights' or 'most exciting' moments of a sport event. This paper discusses the needs and possibilities for widening the current scope of research in the area of image and video search and retrieval in order to enable applications at the affective level of content abstraction.

Video and image retrieval beyond the cognitive level: the needs and possibilities

NASA Astrophysics Data System (ADS)

Hanjalic, Alan

2001-01-01

The worldwide research efforts in the are of image and video retrieval have concentrated so far on increasing the efficiency and reliability of extracting the elements of image and video semantics and so on improving the search and retrieval performance at the cognitive level of content abstraction. At this abstraction level, the user is searching for 'factual' or 'objective' content such as image showing a panorama of San Francisco, an outdoor or an indoor image, a broadcast news report on a defined topic, a movie dialog between the actors A and B or the parts of a basketball game showing fast breaks, steals and scores. These efforts, however, do not address the retrieval applications at the so-called affective level of content abstraction where the 'ground truth' is not strictly defined. Such applications are, for instance, those where subjectivity of the user plays the major role, e.g. the task of retrieving all images that the user 'likes most', and those that are based on 'recognizing emotions' in audiovisual data. Typical examples are searching for all images that 'radiate happiness', identifying all 'sad' movie fragments and looking for the 'romantic landscapes', 'sentimental' movie segments, 'movie highlights' or 'most exciting' moments of a sport event. This paper discusses the needs and possibilities for widening the current scope of research in the area of image and video search and retrieval in order to enable applications at the affective level of content abstraction.

A PDA study management tool (SMT) utilizing wireless broadband and full DICOM viewing capability

NASA Astrophysics Data System (ADS)

Documet, Jorge; Liu, Brent; Zhou, Zheng; Huang, H. K.; Documet, Luis

2007-03-01

During the last 4 years IPI (Image Processing and Informatics) Laboratory has been developing a web-based Study Management Tool (SMT) application that allows Radiologists, Film librarians and PACS-related (Picture Archiving and Communication System) users to dynamically and remotely perform Query/Retrieve operations in a PACS network. The users utilizing a regular PDA (Personal Digital Assistant) can remotely query a PACS archive to distribute any study to an existing DICOM (Digital Imaging and Communications in Medicine) node. This application which has proven to be convenient to manage the Study Workflow [1, 2] has been extended to include a DICOM viewing capability in the PDA. With this new feature, users can take a quick view of DICOM images providing them mobility and convenience at the same time. In addition, we are extending this application to Metropolitan-Area Wireless Broadband Networks. This feature requires Smart Phones that are capable of working as a PDA and have access to Broadband Wireless Services. With the extended application to wireless broadband technology and the preview of DICOM images, the Study Management Tool becomes an even more powerful tool for clinical workflow management.

Architecture of portable electronic medical records system integrated with streaming media.

PubMed

Chen, Wei; Shih, Chien-Chou

2012-02-01

Due to increasing occurrence of accidents and illness during business trips, travel, or overseas studies, the requirement for portable EMR (Electronic Medical Records) has increased. This study proposes integrating streaming media technology into the EMR system to facilitate referrals, contracted laboratories, and disease notification among hospitals. The current study encoded static and dynamic medical images of patients into a streaming video format and stored them in a Flash Media Server (FMS). Based on the Taiwan Electronic Medical Record Template (TMT) standard, EMR records can be converted into XML documents and used to integrate description fields with embedded streaming videos. This investigation implemented a web-based portable EMR interchanging system using streaming media techniques to expedite exchanging medical image information among hospitals. The proposed architecture of the portable EMR retrieval system not only provides local hospital users the ability to acquire EMR text files from a previous hospital, but also helps access static and dynamic medical images as reference for clinical diagnosis and treatment. The proposed method protects property rights of medical images through information security mechanisms of the Medical Record Interchange Service Center and Health Certificate Authorization to facilitate proper, efficient, and continuous treatment of patients.

Ontology-oriented retrieval of putative microRNAs in Vitis vinifera via GrapeMiRNA: a web database of de novo predicted grape microRNAs.

PubMed

Lazzari, Barbara; Caprera, Andrea; Cestaro, Alessandro; Merelli, Ivan; Del Corvo, Marcello; Fontana, Paolo; Milanesi, Luciano; Velasco, Riccardo; Stella, Alessandra

2009-06-29

Two complete genome sequences are available for Vitis vinifera Pinot noir. Based on the sequence and gene predictions produced by the IASMA, we performed an in silico detection of putative microRNA genes and of their targets, and collected the most reliable microRNA predictions in a web database. The application is available at http://www.itb.cnr.it/ptp/grapemirna/. The program FindMiRNA was used to detect putative microRNA genes in the grape genome. A very high number of predictions was retrieved, calling for validation. Nine parameters were calculated and, based on the grape microRNAs dataset available at miRBase, thresholds were defined and applied to FindMiRNA predictions having targets in gene exons. In the resulting subset, predictions were ranked according to precursor positions and sequence similarity, and to target identity. To further validate FindMiRNA predictions, comparisons to the Arabidopsis genome, to the grape Genoscope genome, and to the grape EST collection were performed. Results were stored in a MySQL database and a web interface was prepared to query the database and retrieve predictions of interest. The GrapeMiRNA database encompasses 5,778 microRNA predictions spanning the whole grape genome. Predictions are integrated with information that can be of use in selection procedures. Tools added in the web interface also allow to inspect predictions according to gene ontology classes and metabolic pathways of targets. The GrapeMiRNA database can be of help in selecting candidate microRNA genes to be validated.

Requirements for benchmarking personal image retrieval systems

NASA Astrophysics Data System (ADS)

Bouguet, Jean-Yves; Dulong, Carole; Kozintsev, Igor; Wu, Yi

2006-01-01

It is now common to have accumulated tens of thousands of personal ictures. Efficient access to that many pictures can only be done with a robust image retrieval system. This application is of high interest to Intel processor architects. It is highly compute intensive, and could motivate end users to upgrade their personal computers to the next generations of processors. A key question is how to assess the robustness of a personal image retrieval system. Personal image databases are very different from digital libraries that have been used by many Content Based Image Retrieval Systems.1 For example a personal image database has a lot of pictures of people, but a small set of different people typically family, relatives, and friends. Pictures are taken in a limited set of places like home, work, school, and vacation destination. The most frequent queries are searched for people, and for places. These attributes, and many others affect how a personal image retrieval system should be benchmarked, and benchmarks need to be different from existing ones based on art images, or medical images for examples. The attributes of the data set do not change the list of components needed for the benchmarking of such systems as specified in2: - data sets - query tasks - ground truth - evaluation measures - benchmarking events. This paper proposed a way to build these components to be representative of personal image databases, and of the corresponding usage models.

Effects of internal and external vividness on hippocampal connectivity during memory retrieval.

PubMed

Ford, Jaclyn H; Kensinger, Elizabeth A

2016-10-01

Successful memory for an image can be supported by retrieval of one's personal reaction to the image (i.e., internal vividness), as well as retrieval of the specific details of the image itself (i.e., external vividness). Prior research suggests that memory vividness relies on regions within the medial temporal lobe, particularly the hippocampus, but it is unclear whether internal and external vividness are supported by the hippocampus in a similar way. To address this open question, the current study examined hippocampal connectivity associated with enhanced internal and external vividness ratings during retrieval. Participants encoded complex visual images paired with verbal titles. During a scanned retrieval session, they were presented with the titles and asked whether each had been seen with an image during encoding. Following retrieval of each image, participants were asked to rate internal and external vividness. Increased hippocampal activity was associated with higher vividness ratings for both scales, supporting prior evidence implicating the hippocampus in retrieval of memory detail. However, different patterns of hippocampal connectivity related to enhanced external and internal vividness. Further, hippocampal connectivity with medial prefrontal regions was associated with increased ratings of internal vividness, but with decreased ratings of external vividness. These findings suggest that the hippocampus may contribute to increased internal and external vividness via distinct mechanisms and that external and internal vividness of memories should be considered as separable measures. Copyright © 2016 Elsevier Inc. All rights reserved.

Image Location Estimation by Salient Region Matching.

PubMed

Qian, Xueming; Zhao, Yisi; Han, Junwei

2015-11-01

Nowadays, locations of images have been widely used in many application scenarios for large geo-tagged image corpora. As to images which are not geographically tagged, we estimate their locations with the help of the large geo-tagged image set by content-based image retrieval. In this paper, we exploit spatial information of useful visual words to improve image location estimation (or content-based image retrieval performances). We proposed to generate visual word groups by mean-shift clustering. To improve the retrieval performance, spatial constraint is utilized to code the relative position of visual words. We proposed to generate a position descriptor for each visual word and build fast indexing structure for visual word groups. Experiments show the effectiveness of our proposed approach.

Internet printing

NASA Astrophysics Data System (ADS)

Rahgozar, M. Armon; Hastings, Tom; McCue, Daniel L.

1997-04-01

The Internet is rapidly changing the traditional means of creation, distribution and retrieval of information. Today, information publishers leverage the capabilities provided by Internet technologies to rapidly communicate information to a much wider audience in unique customized ways. As a result, the volume of published content has been astronomically increasing. This, in addition to the ease of distribution afforded by the Internet has resulted in more and more documents being printed. This paper introduces several axes along which Internet printing may be examined and addresses some of the technological challenges that lay ahead. Some of these axes include: (1) submission--the use of the Internet protocols for selecting printers and submitting documents for print, (2) administration--the management and monitoring of printing engines and other print resources via Web pages, and (3) formats--printing document formats whose spectrum now includes HTML documents with simple text, layout-enhanced documents with Style Sheets, documents that contain audio, graphics and other active objects as well as the existing desktop and PDL formats. The format axis of the Internet Printing becomes even more exciting when one considers that the Web documents are inherently compound and the traversal into the various pieces may uncover various formats. The paper also examines some imaging specific issues that are paramount to Internet Printing. These include formats and structures for representing raster documents and images, compression, fonts rendering and color spaces.

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

PubMed

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

1995-11-01

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

Structure function monitor

DOEpatents

McGraw, John T [Placitas, NM; Zimmer, Peter C [Albuquerque, NM; Ackermann, Mark R [Albuquerque, NM

2012-01-24

Methods and apparatus for a structure function monitor provide for generation of parameters characterizing a refractive medium. In an embodiment, a structure function monitor acquires images of a pupil plane and an image plane and, from these images, retrieves the phase over an aperture, unwraps the retrieved phase, and analyzes the unwrapped retrieved phase. In an embodiment, analysis yields atmospheric parameters measured at spatial scales from zero to the diameter of a telescope used to collect light from a source.

Content Based Image Retrieval based on Wavelet Transform coefficients distribution

PubMed Central

Lamard, Mathieu; Cazuguel, Guy; Quellec, Gwénolé; Bekri, Lynda; Roux, Christian; Cochener, Béatrice

2007-01-01

In this paper we propose a content based image retrieval method for diagnosis aid in medical fields. We characterize images without extracting significant features by using distribution of coefficients obtained by building signatures from the distribution of wavelet transform. The research is carried out by computing signature distances between the query and database images. Several signatures are proposed; they use a model of wavelet coefficient distribution. To enhance results, a weighted distance between signatures is used and an adapted wavelet base is proposed. Retrieval efficiency is given for different databases including a diabetic retinopathy, a mammography and a face database. Results are promising: the retrieval efficiency is higher than 95% for some cases using an optimization process. PMID:18003013

Experimental Studies on a Compact Storage Scheme for Wavelet-based Multiresolution Subregion Retrieval

NASA Technical Reports Server (NTRS)

Poulakidas, A.; Srinivasan, A.; Egecioglu, O.; Ibarra, O.; Yang, T.

1996-01-01

Wavelet transforms, when combined with quantization and a suitable encoding, can be used to compress images effectively. In order to use them for image library systems, a compact storage scheme for quantized coefficient wavelet data must be developed with a support for fast subregion retrieval. We have designed such a scheme and in this paper we provide experimental studies to demonstrate that it achieves good image compression ratios, while providing a natural indexing mechanism that facilitates fast retrieval of portions of the image at various resolutions.

PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization.

PubMed

Dogrusoz, U; Erson, E Z; Giral, E; Demir, E; Babur, O; Cetintas, A; Colak, R

2006-02-01

Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

PubMed Central

Das, Ravi K.; Gale, Grace; Hennessy, Vanessa; Kamboj, Sunjeev K.

2018-01-01

Maladaptive reward memories (MRMs) can become unstable following retrieval under certain conditions, allowing their modification by subsequent new learning. However, robust (well-rehearsed) and chronologically old MRMs, such as those underlying substance use disorders, do not destabilize easily when retrieved. A key determinate of memory destabilization during retrieval is prediction error (PE). We describe a retrieval procedure for alcohol MRMs in hazardous drinkers that specifically aims to maximize the generation of PE and therefore the likelihood of MRM destabilization. The procedure requires explicitly generating the expectancy of alcohol consumption and then violating this expectancy (withholding alcohol) following the presentation of a brief set of prototypical alcohol cue images (retrieval + PE). Control procedures involve presenting the same cue images, but allow alcohol to be consumed, generating minimal PE (retrieval-no PE) or generate PE without retrieval of alcohol MRMs, by presenting orange juice cues (no retrieval + PE). Subsequently, we describe a multisensory disgust-based counterconditioning procedure to probe MRM destabilization by re-writing alcohol cue-reward associations prior to reconsolidation. This procedure pairs alcohol cues with images invoking pathogen disgust and an extremely bitter-tasting solution (denatonium benzoate), generating gustatory disgust. Following retrieval + PE, but not no retrieval + PE or retrieval-no PE, counterconditioning produces evidence of MRM rewriting as indexed by lasting reductions in alcohol cue valuation, attentional capture, and alcohol craving. PMID:29364255

Propagation based phase retrieval of simulated intensity measurements using artificial neural networks

NASA Astrophysics Data System (ADS)

Kemp, Z. D. C.

2018-04-01

Determining the phase of a wave from intensity measurements has many applications in fields such as electron microscopy, visible light optics, and medical imaging. Propagation based phase retrieval, where the phase is obtained from defocused images, has shown significant promise. There are, however, limitations in the accuracy of the retrieved phase arising from such methods. Sources of error include shot noise, image misalignment, and diffraction artifacts. We explore the use of artificial neural networks (ANNs) to improve the accuracy of propagation based phase retrieval algorithms applied to simulated intensity measurements. We employ a phase retrieval algorithm based on the transport-of-intensity equation to obtain the phase from simulated micrographs of procedurally generated specimens. We then train an ANN with pairs of retrieved and exact phases, and use the trained ANN to process a test set of retrieved phase maps. The total error in the phase is significantly reduced using this method. We also discuss a variety of potential extensions to this work.

Inter-Comparison of GOES-8 Imager and Sounder Skin Temperature Retrievals

NASA Technical Reports Server (NTRS)

Haines, Stephanie L.; Suggs, Ronnie J.; Jedlovec, Gary J.; Arnold, James E. (Technical Monitor)

2001-01-01

Skin temperature (ST) retrievals derived from geostationary satellite observations have both high temporal and spatial resolutions and are therefore useful for applications such as assimilation into mesoscale forecast models, nowcasting, and diagnostic studies. Our retrieval method uses a Physical Split Window technique requiring at least two channels within the longwave infrared window. On current GOES satellites, including GOES-11, there are two Imager channels within the required spectral interval. However, beginning with the GOES-M satellite the 12-um channel will be removed, leaving only one longwave channel. The Sounder instrument will continue to have three channels within the longwave window, and therefore ST retrievals will be derived from Sounder measurements. This research compares retrievals from the two instruments and evaluates the effects of the spatial resolution and sensor calibration differences on the retrievals. Both Imager and Sounder retrievals are compared to ground-truth data to evaluate the overall accuracy of the technique. An analysis of GOES-8 and GOES-11 intercomparisons is also presented.

Content-based image retrieval from a database of fracture images

NASA Astrophysics Data System (ADS)

Müller, Henning; Do Hoang, Phuong Anh; Depeursinge, Adrien; Hoffmeyer, Pierre; Stern, Richard; Lovis, Christian; Geissbuhler, Antoine

2007-03-01

This article describes the use of a medical image retrieval system on a database of 16'000 fractures, selected from surgical routine over several years. Image retrieval has been a very active domain of research for several years. It was frequently proposed for the medical domain, but only few running systems were ever tested in clinical routine. For the planning of surgical interventions after fractures, x-ray images play an important role. The fractures are classified according to exact fracture location, plus whether and to which degree the fracture is damaging articulations to see how complicated a reparation will be. Several classification systems for fractures exist and the classification plus the experience of the surgeon lead in the end to the choice of surgical technique (screw, metal plate, ...). This choice is strongly influenced by the experience and knowledge of the surgeons with respect to a certain technique. Goal of this article is to describe a prototype that supplies similar cases to an example to help treatment planning and find the most appropriate technique for a surgical intervention. Our database contains over 16'000 fracture images before and after a surgical intervention. We use an image retrieval system (GNU Image Finding Tool, GIFT) to find cases/images similar to an example case currently under observation. Problems encountered are varying illumination of images as well as strong anatomic differences between patients. Regions of interest are usually small and the retrieval system needs to focus on this region. Results show that GIFT is capable of supplying similar cases, particularly when using relevance feedback, on such a large database. Usual image retrieval is based on a single image as search target but for this application we have to select images by case as similar cases need to be found and not images. A few false positive cases often remain in the results but they can be sorted out quickly by the surgeons. Image retrieval can well be used for the planning of operations by supplying similar cases. A variety of challenges has been identified and partly solved (varying luminosity, small region of interested, case-based instead of image-based). This article mainly presents a case study to identify potential benefits and problems. Several steps for improving the system have been identified as well and will be described at the end of the paper.

[A solution for display and processing of DICOM images in web PACS].

PubMed

Xue, Wei-jing; Lu, Wen; Wang, Hai-yang; Meng, Jian

2009-03-01

Use the technique of Java Applet to realize the supporting of DICOM image in ordinary Web browser, thereby to expand the processing function of medical image. First analyze the format of DICOM file and design a class which can acquire the pixels, then design two Applet classes, of which one is used to disposal the DICOM image, the other is used to display DICOM image that have been disposaled in the first Applet. They all embedded in the View page, and they communicate by Applet Context object. The method designed in this paper can make users display and process DICOM images directly by using ordinary Web browser, which makes Web PACS not only have the advantages of B/S model, but also have the advantages of the C/S model. Java Applet is the key for expanding the Web browser's function in Web PACS, which provides a guideline to sharing of medical images.

Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses.

PubMed

Falagas, Matthew E; Pitsouni, Eleni I; Malietzis, George A; Pappas, Georgios

2008-02-01

The evolution of the electronic age has led to the development of numerous medical databases on the World Wide Web, offering search facilities on a particular subject and the ability to perform citation analysis. We compared the content coverage and practical utility of PubMed, Scopus, Web of Science, and Google Scholar. The official Web pages of the databases were used to extract information on the range of journals covered, search facilities and restrictions, and update frequency. We used the example of a keyword search to evaluate the usefulness of these databases in biomedical information retrieval and a specific published article to evaluate their utility in performing citation analysis. All databases were practical in use and offered numerous search facilities. PubMed and Google Scholar are accessed for free. The keyword search with PubMed offers optimal update frequency and includes online early articles; other databases can rate articles by number of citations, as an index of importance. For citation analysis, Scopus offers about 20% more coverage than Web of Science, whereas Google Scholar offers results of inconsistent accuracy. PubMed remains an optimal tool in biomedical electronic research. Scopus covers a wider journal range, of help both in keyword searching and citation analysis, but it is currently limited to recent articles (published after 1995) compared with Web of Science. Google Scholar, as for the Web in general, can help in the retrieval of even the most obscure information but its use is marred by inadequate, less often updated, citation information.

The potential of the internet.

PubMed

Coleman, Jamie J; McDowell, Sarah E

2012-06-01

The internet and the World Wide Web have changed the ways that we function. As technologies grow and adapt, there is a huge potential for the internet to affect drug research and development, as well as many other aspects of clinical pharmacology. We review some of the areas of interest to date and discuss some of the potential areas in which internet-based technology can be exploited. Information retrieval from the web by health-care professionals is common, and bringing evidence-based medicine to the bedside affects the care of patients. As a primary research tool the web can provide a vast array of information in generating new ideas or exploring previous research findings. This has facilitated systematic reviewing, for example. The content of the web has become a subject of research in its own right. The web is also widely used as a research facilitator, including enhancement of communication between collaborators, provision of online research tools (such as questionnaires, management of large scale multicentre trials, registration of clinical trials) and distribution of information. Problems include information overload, ignorance of early data that are not indexed in databases, difficulties in keeping web sites up to date and assessing the validity of information retrieved. Some web-based activities are viewed with suspicion, including analysis by pharmaceutical companies of drug information to facilitate direct-to-consumer advertising of novel pharmaceuticals. Use of these technologies will continue to expand in often unexpected ways. Clinical pharmacologists must embrace internet technology and include it as a key priority in their research agenda. © 2012 The Authors. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.

SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs

PubMed Central

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2017-01-01

Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches. PMID:28771497

Effectiveness of image features and similarity measures in cluster-based approaches for content-based image retrieval

NASA Astrophysics Data System (ADS)

Du, Hongbo; Al-Jubouri, Hanan; Sellahewa, Harin

2014-05-01

Content-based image retrieval is an automatic process of retrieving images according to image visual contents instead of textual annotations. It has many areas of application from automatic image annotation and archive, image classification and categorization to homeland security and law enforcement. The key issues affecting the performance of such retrieval systems include sensible image features that can effectively capture the right amount of visual contents and suitable similarity measures to find similar and relevant images ranked in a meaningful order. Many different approaches, methods and techniques have been developed as a result of very intensive research in the past two decades. Among many existing approaches, is a cluster-based approach where clustering methods are used to group local feature descriptors into homogeneous regions, and search is conducted by comparing the regions of the query image against those of the stored images. This paper serves as a review of works in this area. The paper will first summarize the existing work reported in the literature and then present the authors' own investigations in this field. The paper intends to highlight not only achievements made by recent research but also challenges and difficulties still remaining in this area.

Image Retrieval by Color Semantics with Incomplete Knowledge.

ERIC Educational Resources Information Center

Corridoni, Jacopo M.; Del Bimbo, Alberto; Vicario, Enrico

1998-01-01

Presents a system which supports image retrieval by high-level chromatic contents, the sensations that color accordances generate on the observer. Surveys Itten's theory of color semantics and discusses image description and query specification. Presents examples of visual querying. (AEF)

Automatic visibility retrieval from thermal camera images

NASA Astrophysics Data System (ADS)

Dizerens, Céline; Ott, Beat; Wellig, Peter; Wunderle, Stefan

2017-10-01

This study presents an automatic visibility retrieval of a FLIR A320 Stationary Thermal Imager installed on a measurement tower on the mountain Lagern located in the Swiss Jura Mountains. Our visibility retrieval makes use of edges that are automatically detected from thermal camera images. Predefined target regions, such as mountain silhouettes or buildings with high thermal differences to the surroundings, are used to derive the maximum visibility distance that is detectable in the image. To allow a stable, automatic processing, our procedure additionally removes noise in the image and includes automatic image alignment to correct small shifts of the camera. We present a detailed analysis of visibility derived from more than 24000 thermal images of the years 2015 and 2016 by comparing them to (1) visibility derived from a panoramic camera image (VISrange), (2) measurements of a forward-scatter visibility meter (Vaisala FD12 working in the NIR spectra), and (3) modeled visibility values using the Thermal Range Model TRM4. Atmospheric conditions, mainly water vapor from European Center for Medium Weather Forecast (ECMWF), were considered to calculate the extinction coefficients using MODTRAN. The automatic visibility retrieval based on FLIR A320 images is often in good agreement with the retrieval from the systems working in different spectral ranges. However, some significant differences were detected as well, depending on weather conditions, thermal differences of the monitored landscape, and defined target size.

Improving information retrieval with multiple health terminologies in a quality-controlled gateway.

PubMed

Soualmia, Lina F; Sakji, Saoussen; Letord, Catherine; Rollin, Laetitia; Massari, Philippe; Darmoni, Stéfan J

2013-01-01

The Catalog and Index of French-language Health Internet resources (CISMeF) is a quality-controlled health gateway, primarily for Web resources in French (n=89,751). Recently, we achieved a major improvement in the structure of the catalogue by setting-up multiple terminologies, based on twelve health terminologies available in French, to overcome the potential weakness of the MeSH thesaurus, which is the main and pivotal terminology we use for indexing and retrieval since 1995. The main aim of this study was to estimate the added-value of exploiting several terminologies and their semantic relationships to improve Web resource indexing and retrieval in CISMeF, in order to provide additional health resources which meet the users' expectations. Twelve terminologies were integrated into the CISMeF information system to set up multiple-terminologies indexing and retrieval. The same sets of thirty queries were run: (i) by exploiting the hierarchical structure of the MeSH, and (ii) by exploiting the additional twelve terminologies and their semantic links. The two search modes were evaluated and compared. The overall coverage of the multiple-terminologies search mode was improved by comparison to the coverage of using the MeSH (16,283 vs. 14,159) (+15%). These additional findings were estimated at 56.6% relevant results, 24.7% intermediate results and 18.7% irrelevant. The multiple-terminologies approach improved information retrieval. These results suggest that integrating additional health terminologies was able to improve recall. Since performing the study, 21 other terminologies have been added which should enable us to make broader studies in multiple-terminologies information retrieval.

A web-based solution for 3D medical image visualization

NASA Astrophysics Data System (ADS)

Hou, Xiaoshuai; Sun, Jianyong; Zhang, Jianguo

2015-03-01

In this presentation, we present a web-based 3D medical image visualization solution which enables interactive large medical image data processing and visualization over the web platform. To improve the efficiency of our solution, we adopt GPU accelerated techniques to process images on the server side while rapidly transferring images to the HTML5 supported web browser on the client side. Compared to traditional local visualization solution, our solution doesn't require the users to install extra software or download the whole volume dataset from PACS server. By designing this web-based solution, it is feasible for users to access the 3D medical image visualization service wherever the internet is available.

Semantics of User Interface for Image Retrieval: Possibility Theory and Learning Techniques.

ERIC Educational Resources Information Center

Crehange, M.; And Others

1989-01-01

Discusses the need for a rich semantics for the user interface in interactive image retrieval and presents two methods for building such interfaces: possibility theory applied to fuzzy data retrieval, and a machine learning technique applied to learning the user's deep need. Prototypes developed using videodisks and knowledge-based software are…

QMachine: commodity supercomputing in web browsers.

PubMed

Wilkinson, Sean R; Almeida, Jonas S

2014-06-09

Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics' "Big Data" from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine. QM is an open-sourced, publicly available web service that acts as a messaging system for posting tasks and retrieving results over HTTP. The illustrative application described here distributes the analyses of 20 Streptococcus pneumoniae genomes for shared suffixes. Because all analytical and data retrieval tasks are executed by volunteer machines, few server resources are required. Any modern web browser can submit those tasks and/or volunteer to execute them without installing any extra plugins or programs. A client library provides high-level distribution templates including MapReduce. This stark departure from the current reliance on expensive server hardware running "download and install" software has already gathered substantial community interest, as QM received more than 2.2 million API calls from 87 countries in 12 months. QM was found adequate to deliver the sort of scalable bioinformatics solutions that computation- and data-intensive workflows require. Paradoxically, the sandboxed execution of code by web browsers was also found to enable them, as compute nodes, to address critical privacy concerns that characterize biomedical environments.

MyFreePACS: a free web-based radiology image storage and viewing tool.

PubMed

de Regt, David; Weinberger, Ed

2004-08-01

We developed an easy-to-use method for central storage and subsequent viewing of radiology images for use on any PC equipped with Internet Explorer. We developed MyFreePACS, a program that uses a DICOM server to receive and store images and transmit them over the Web to the MyFreePACS Web client. The MyFreePACS Web client is a Web page that uses an ActiveX control for viewing and manipulating images. The client contains many of the tools found in modern image viewing stations including 3D localization and multiplanar reformation. The system is built entirely with free components and is freely available for download and installation from the Web at www.myfreepacs.com.

Retrieve polarization aberration from image degradation: a new measurement method in DUV lithography

NASA Astrophysics Data System (ADS)

Xiang, Zhongbo; Li, Yanqiu

2017-10-01

Detailed knowledge of polarization aberration (PA) of projection lens in higher-NA DUV lithographic imaging is necessary due to its impact to imaging degradations, and precise measurement of PA is conductive to computational lithography techniques such as RET and OPC. Current in situ measurement method of PA thorough the detection of degradations of aerial images need to do linear approximation and apply the assumption of 3-beam/2-beam interference condition. The former approximation neglects the coupling effect of the PA coefficients, which would significantly influence the accuracy of PA retrieving. The latter assumption restricts the feasible pitch of test masks in higher-NA system, conflicts with the Kirhhoff diffraction model of test mask used in retrieving model, and introduces 3D mask effect as a source of retrieving error. In this paper, a new in situ measurement method of PA is proposed. It establishes the analytical quadratic relation between the PA coefficients and the degradations of aerial images of one-dimensional dense lines in coherent illumination through vector aerial imaging, which does not rely on the assumption of 3-beam/2- beam interference and linear approximation. In this case, the retrieval of PA from image degradation can be convert from the nonlinear system of m-quadratic equations to a multi-objective quadratic optimization problem, and finally be solved by nonlinear least square method. Some preliminary simulation results are given to demonstrate the correctness and accuracy of the new PA retrieving model.

Precise and Efficient Retrieval of Captioned Images: The MARIE Project.

ERIC Educational Resources Information Center

Rowe, Neil C.

1999-01-01

The MARIE project explores knowledge-based information retrieval of captioned images of the kind found in picture libraries and on the Internet. MARIE's five-part approach exploits the idea that images are easier to understand with context, especially descriptive text near them, but it also does image analysis. Experiments show MARIE prototypes…

Novel Algorithm for Classification of Medical Images

NASA Astrophysics Data System (ADS)

Bhushan, Bharat; Juneja, Monika

2010-11-01

Content-based image retrieval (CBIR) methods in medical image databases have been designed to support specific tasks, such as retrieval of medical images. These methods cannot be transferred to other medical applications since different imaging modalities require different types of processing. To enable content-based queries in diverse collections of medical images, the retrieval system must be familiar with the current Image class prior to the query processing. Further, almost all of them deal with the DICOM imaging format. In this paper a novel algorithm based on energy information obtained from wavelet transform for the classification of medical images according to their modalities is described. For this two types of wavelets have been used and have been shown that energy obtained in either case is quite distinct for each of the body part. This technique can be successfully applied to different image formats. The results are shown for JPEG imaging format.

Landmark Image Retrieval by Jointing Feature Refinement and Multimodal Classifier Learning.

PubMed

Zhang, Xiaoming; Wang, Senzhang; Li, Zhoujun; Ma, Shuai; Xiaoming Zhang; Senzhang Wang; Zhoujun Li; Shuai Ma; Ma, Shuai; Zhang, Xiaoming; Wang, Senzhang; Li, Zhoujun

2018-06-01

Landmark retrieval is to return a set of images with their landmarks similar to those of the query images. Existing studies on landmark retrieval focus on exploiting the geometries of landmarks for visual similarity matches. However, the visual content of social images is of large diversity in many landmarks, and also some images share common patterns over different landmarks. On the other side, it has been observed that social images usually contain multimodal contents, i.e., visual content and text tags, and each landmark has the unique characteristic of both visual content and text content. Therefore, the approaches based on similarity matching may not be effective in this environment. In this paper, we investigate whether the geographical correlation among the visual content and the text content could be exploited for landmark retrieval. In particular, we propose an effective multimodal landmark classification paradigm to leverage the multimodal contents of social image for landmark retrieval, which integrates feature refinement and landmark classifier with multimodal contents by a joint model. The geo-tagged images are automatically labeled for classifier learning. Visual features are refined based on low rank matrix recovery, and multimodal classification combined with group sparse is learned from the automatically labeled images. Finally, candidate images are ranked by combining classification result and semantic consistence measuring between the visual content and text content. Experiments on real-world datasets demonstrate the superiority of the proposed approach as compared to existing methods.

Three-dimensional spatiotemporal features for fast content-based retrieval of focal liver lesions.

PubMed

Roy, Sharmili; Chi, Yanling; Liu, Jimin; Venkatesh, Sudhakar K; Brown, Michael S

2014-11-01

Content-based image retrieval systems for 3-D medical datasets still largely rely on 2-D image-based features extracted from a few representative slices of the image stack. Most 2 -D features that are currently used in the literature not only model a 3-D tumor incompletely but are also highly expensive in terms of computation time, especially for high-resolution datasets. Radiologist-specified semantic labels are sometimes used along with image-based 2-D features to improve the retrieval performance. Since radiological labels show large interuser variability, are often unstructured, and require user interaction, their use as lesion characterizing features is highly subjective, tedious, and slow. In this paper, we propose a 3-D image-based spatiotemporal feature extraction framework for fast content-based retrieval of focal liver lesions. All the features are computer generated and are extracted from four-phase abdominal CT images. Retrieval performance and query processing times for the proposed framework is evaluated on a database of 44 hepatic lesions comprising of five pathological types. Bull's eye percentage score above 85% is achieved for three out of the five lesion pathologies and for 98% of query lesions, at least one same type of lesion is ranked among the top two retrieved results. Experiments show that the proposed system's query processing is more than 20 times faster than other already published systems that use 2-D features. With fast computation time and high retrieval accuracy, the proposed system has the potential to be used as an assistant to radiologists for routine hepatic tumor diagnosis.

Interactive radiographic image retrieval system.

PubMed

Kundu, Malay Kumar; Chowdhury, Manish; Das, Sudeb

2017-02-01

Content based medical image retrieval (CBMIR) systems enable fast diagnosis through quantitative assessment of the visual information and is an active research topic over the past few decades. Most of the state-of-the-art CBMIR systems suffer from various problems: computationally expensive due to the usage of high dimensional feature vectors and complex classifier/clustering schemes. Inability to properly handle the "semantic gap" and the high intra-class versus inter-class variability problem of the medical image database (like radiographic image database). This yields an exigent demand for developing highly effective and computationally efficient retrieval system. We propose a novel interactive two-stage CBMIR system for diverse collection of medical radiographic images. Initially, Pulse Coupled Neural Network based shape features are used to find out the most probable (similar) image classes using a novel "similarity positional score" mechanism. This is followed by retrieval using Non-subsampled Contourlet Transform based texture features considering only the images of the pre-identified classes. Maximal information compression index is used for unsupervised feature selection to achieve better results. To reduce the semantic gap problem, the proposed system uses a novel fuzzy index based relevance feedback mechanism by incorporating subjectivity of human perception in an analytic manner. Extensive experiments were carried out to evaluate the effectiveness of the proposed CBMIR system on a subset of Image Retrieval in Medical Applications (IRMA)-2009 database consisting of 10,902 labeled radiographic images of 57 different modalities. We obtained overall average precision of around 98% after only 2-3 iterations of relevance feedback mechanism. We assessed the results by comparisons with some of the state-of-the-art CBMIR systems for radiographic images. Unlike most of the existing CBMIR systems, in the proposed two-stage hierarchical framework, main importance is given on constructing efficient and compact feature vector representation, search-space reduction and handling the "semantic gap" problem effectively, without compromising the retrieval performance. Experimental results and comparisons show that the proposed system performs efficiently in the radiographic medical image retrieval field. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

WEB-IS2: Next Generation Web Services Using Amira Visualization Package

NASA Astrophysics Data System (ADS)

Yang, X.; Wang, Y.; Bollig, E. F.; Kadlec, B. J.; Garbow, Z. A.; Yuen, D. A.; Erlebacher, G.

2003-12-01

Amira (www.amiravis.com) is a powerful 3-D visualization package and has been employed recently by the science and engineering communities to gain insight into their data. We present a new web-based interface to Amira, packaged in a Java applet. We have developed a module called WEB-IS/Amira (WEB-IS2), which provides web-based access to Amira. This tool allows earth scientists to manipulate Amira controls remotely and to analyze, render and view large datasets over the internet, without regard for time or location. This could have important ramifications for GRID computing. The design of our implementation will soon allow multiple users to visually collaborate by manipulating a single dataset through a variety of client devices. These clients will only require a browser capable of displaying Java applets. As the deluge of data continues, innovative solutions that maximize ease of use without sacrificing efficiency or flexibility will continue to gain in importance, particularly in the Earth sciences. Major initiatives, such as Earthscope (http://www.earthscope.org), which will generate at least a terabyte of data daily, stand to profit enormously by a system such as WEB-IS/Amira (WEB-IS2). We discuss our use of SOAP (Livingston, D., Advanced SOAP for Web development, Prentice Hall, 2002), a novel 2-way communication protocol, as a means of providing remote commands, and efficient point-to-point transfer of binary image data. We will present our initial experiences with the use of Naradabrokering (www.naradabrokering.org) as a means to decouple clients and servers. Information is submitted to the system as a published item, while it is retrieved through a subscription mechanisms, via what is known as "topics". These topic headers, their contents, and the list of subscribers are automatically tracked by Naradabrokering. This novel approach promises a high degree of fault tolerance, flexibility with respect to client diversity, and language independence for the services (Erlebacher, G., Yuen, D.A., and F. Dubuffet, Current trends and demands in visualization in the geosciences, Electron. Geosciences, 4, 2001).

Automatic classification and detection of clinically relevant images for diabetic retinopathy

NASA Astrophysics Data System (ADS)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Modelling Subjectivity in Visual Perception of Orientation for Image Retrieval.

ERIC Educational Resources Information Center

Sanchez, D.; Chamorro-Martinez, J.; Vila, M. A.

2003-01-01

Discussion of multimedia libraries and the need for storage, indexing, and retrieval techniques focuses on the combination of computer vision and data mining techniques to model high-level concepts for image retrieval based on perceptual features of the human visual system. Uses fuzzy set theory to measure users' assessments and to capture users'…

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

PubMed

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

Information Retrieval and Graph Analysis Approaches for Book Recommendation.

PubMed

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

Information Retrieval and Graph Analysis Approaches for Book Recommendation

PubMed Central

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments. PMID:26504899

Mapping the Themes, Impact, and Cohesion of Creativity Research over the Last 25 Years

ERIC Educational Resources Information Center

Williams, Rich; Runco, Mark A.; Berlow, Eric

2016-01-01

This article describes the themes found in the past 25 years of creativity research. Computational methods and network analysis were used to map keyword theme development across ~1,400 documents and ~5,000 unique keywords from 1990 (the first year keywords are available in Web of Science) to 2015. Data were retrieved from Web of Science using the…

A World Wide Web Human Dimensions Framework and Database for Wildlife and Forest Planning

Treesearch

Michael A. Tarrant; Alan D. Bright; H. Ken Cordell

1999-01-01

The paper describes a human dimensions framework(HDF) for application in wildlife and forest planning. The HDF is delivered via the world wide web and retrieves data on-line from the Social, Economic, Environmental, Leisure, and Attitudes (SEELA) database. The proposed HDF is guided by ten fundamental HD principles, and is applied to wildlife and forest planning using...

A graph-based approach for the retrieval of multi-modality medical images.

PubMed

Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

2014-02-01

In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state-of-the-art methods such as visual words using the scale- invariant feature transform (SIFT) and relational matrices representing the spatial arrangements of objects. Copyright © 2013 Elsevier B.V. All rights reserved.

Visualizing and improving the robustness of phase retrieval algorithms

DOE PAGES

Tripathi, Ashish; Leyffer, Sven; Munson, Todd; ...

2015-06-01

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

Visualizing and improving the robustness of phase retrieval algorithms

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

Tripathi, Ashish; Leyffer, Sven; Munson, Todd

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

A flower image retrieval method based on ROI feature.

PubMed

Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

2004-07-01

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

Cross-Modal Retrieval With CNN Visual Features: A New Baseline.

PubMed

Wei, Yunchao; Zhao, Yao; Lu, Canyi; Wei, Shikui; Liu, Luoqi; Zhu, Zhenfeng; Yan, Shuicheng

2017-02-01

Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than one million images from 1000 object categories, as a generic image representation to tackle cross-modal retrieval. To further enhance the representational ability of CNN visual features, based on the pretrained CNN model on ImageNet, a fine-tuning step is performed by using the open source Caffe CNN library for each target data set. Besides, we propose a deep semantic matching method to address the cross-modal retrieval problem with respect to samples which are annotated with one or multiple labels. Extensive experiments on five popular publicly available data sets well demonstrate the superiority of CNN visual features for cross-modal retrieval.

A Integrated Service Platform for Remote Sensing Image 3D Interpretation and Draughting based on HTML5

NASA Astrophysics Data System (ADS)

LIU, Yiping; XU, Qing; ZhANG, Heng; LV, Liang; LU, Wanjie; WANG, Dandi

2016-11-01

The purpose of this paper is to solve the problems of the traditional single system for interpretation and draughting such as inconsistent standards, single function, dependence on plug-ins, closed system and low integration level. On the basis of the comprehensive analysis of the target elements composition, map representation and similar system features, a 3D interpretation and draughting integrated service platform for multi-source, multi-scale and multi-resolution geospatial objects is established based on HTML5 and WebGL, which not only integrates object recognition, access, retrieval, three-dimensional display and test evaluation but also achieves collection, transfer, storage, refreshing and maintenance of data about Geospatial Objects and shows value in certain prospects and potential for growth.

Using Sensor Web Processes and Protocols to Assimilate Satellite Data into a Forecast Model

NASA Technical Reports Server (NTRS)

Goodman, H. Michael; Conover, Helen; Zavodsky, Bradley; Maskey, Manil; Jedlovec, Gary; Regner, Kathryn; Li, Xiang; Lu, Jessica; Botts, Mike; Berthiau, Gregoire

2008-01-01

The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

Image acquisition context: procedure description attributes for clinically relevant indexing and selective retrieval of biomedical images.

PubMed

Bidgood, W D; Bray, B; Brown, N; Mori, A R; Spackman, K A; Golichowski, A; Jones, R H; Korman, L; Dove, B; Hildebrand, L; Berg, M

1999-01-01

To support clinically relevant indexing of biomedical images and image-related information based on the attributes of image acquisition procedures and the judgments (observations) expressed by observers in the process of image interpretation. The authors introduce the notion of "image acquisition context," the set of attributes that describe image acquisition procedures, and present a standards-based strategy for utilizing the attributes of image acquisition context as indexing and retrieval keys for digital image libraries. The authors' indexing strategy is based on an interdependent message/terminology architecture that combines the Digital Imaging and Communication in Medicine (DICOM) standard, the SNOMED (Systematized Nomenclature of Human and Veterinary Medicine) vocabulary, and the SNOMED DICOM microglossary. The SNOMED DICOM microglossary provides context-dependent mapping of terminology to DICOM data elements. The capability of embedding standard coded descriptors in DICOM image headers and image-interpretation reports improves the potential for selective retrieval of image-related information. This favorably affects information management in digital libraries.

Searching for Images: The Analysis of Users' Queries for Image Retrieval in American History.

ERIC Educational Resources Information Center

Choi, Youngok; Rasmussen, Edie M.

2003-01-01

Studied users' queries for visual information in American history to identify the image attributes important for retrieval and the characteristics of users' queries for digital images, based on queries from 38 faculty and graduate students. Results of pre- and post-test questionnaires and interviews suggest principle categories of search terms.…

Image selection system. [computerized data storage and retrieval system

NASA Technical Reports Server (NTRS)

Knutson, M. A.; Hurd, D.; Hubble, L.; Kroeck, R. M.

1974-01-01

An image selection (ISS) was developed for the NASA-Ames Research Center Earth Resources Aircraft Project. The ISS is an interactive, graphics oriented, computer retrieval system for aerial imagery. An analysis of user coverage requests and retrieval strategies is presented, followed by a complete system description. Data base structure, retrieval processors, command language, interactive display options, file structures, and the system's capability to manage sets of selected imagery are described. A detailed example of an area coverage request is graphically presented.

Digitizing Olin Eggen's Card Database

NASA Astrophysics Data System (ADS)

Crast, J.; Silvis, G.

2017-06-01

The goal of the Eggen Card Database Project is to recover as many of the photometric observations from Olin Eggen's Card Database as possible and preserve these observations, in digital forms that are accessible by anyone. Any observations of interest to the AAVSO will be added to the AAVSO International Database (AID). Given to the AAVSO on long-term loan by the Cerro Tololo Inter-American Observatory, the database is a collection of over 78,000 index cards holding all Eggen's observations made between 1960 and 1990. The cards were electronically scanned and the resulting 108,000 card images have been published as a series of 2,216 PDF files, which are available from the AAVSO web site. The same images are also stored in an AAVSO online database where they are indexed by star name and card content. These images can be viewed using the eggen card portal online tool. Eggen made observations using filter bands from five different photometric systems. He documented these observations using 15 different data recording formats. Each format represents a combination of filter magnitudes and color indexes. These observations are being transcribed onto spreadsheets, from which observations of value to the AAVSO are added to the AID. A total of 506 U, B, V, R, and I observations were added to the AID for the variable stars S Car and l Car. We would like the reader to search through the card database using the eggen card portal for stars of particular interest. If such stars are found and retrieval of the observations is desired, e-mail the authors, and we will be happy to help retrieve those data for the reader.

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

2013-01-01

Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

Image retrieval for identifying house plants

NASA Astrophysics Data System (ADS)

Kebapci, Hanife; Yanikoglu, Berrin; Unal, Gozde

2010-02-01

We present a content-based image retrieval system for plant identification which is intended for providing users with a simple method to locate information about their house plants. A plant image consists of a collection of overlapping leaves and possibly flowers, which makes the problem challenging. We studied the suitability of various well-known color, texture and shape features for this problem, as well as introducing some new ones. The features are extracted from the general plant region that is segmented from the background using the max-flow min-cut technique. Results on a database of 132 different plant images show promise (in about 72% of the queries, the correct plant image is retrieved among the top-15 results).

Evaluation of contents-based image retrieval methods for a database of logos on drug tablets

NASA Astrophysics Data System (ADS)

Geradts, Zeno J.; Hardy, Huub; Poortman, Anneke; Bijhold, Jurrien

2001-02-01

In this research an evaluation has been made of the different ways of contents based image retrieval of logos of drug tablets. On a database of 432 illicitly produced tablets (mostly containing MDMA), we have compared different retrieval methods. Two of these methods were available from commercial packages, QBIC and Imatch, where the implementation of the contents based image retrieval methods are not exactly known. We compared the results for this database with the MPEG-7 shape comparison methods, which are the contour-shape, bounding box and region-based shape methods. In addition, we have tested the log polar method that is available from our own research.

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

NASA Astrophysics Data System (ADS)

Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

Toward privacy-preserving JPEG image retrieval

NASA Astrophysics Data System (ADS)

Cheng, Hang; Wang, Jingyue; Wang, Meiqing; Zhong, Shangping

2017-07-01

This paper proposes a privacy-preserving retrieval scheme for JPEG images based on local variance. Three parties are involved in the scheme: the content owner, the server, and the authorized user. The content owner encrypts JPEG images for privacy protection by jointly using permutation cipher and stream cipher, and then, the encrypted versions are uploaded to the server. With an encrypted query image provided by an authorized user, the server may extract blockwise local variances in different directions without knowing the plaintext content. After that, it can calculate the similarity between the encrypted query image and each encrypted database image by a local variance-based feature comparison mechanism. The authorized user with the encryption key can decrypt the returned encrypted images with plaintext content similar to the query image. The experimental results show that the proposed scheme not only provides effective privacy-preserving retrieval service but also ensures both format compliance and file size preservation for encrypted JPEG images.

Current Development at the Southern California Earthquake Data Center (SCEDC)

NASA Astrophysics Data System (ADS)

Appel, V. L.; Clayton, R. W.

2005-12-01

Over the past year, the SCEDC completed or is near completion of three featured projects: Station Information System (SIS) Development: The SIS will provide users with an interface into complete and accurate station metadata for all current and historic data at the SCEDC. The goal of this project is to develop a system that can interact with a single database source to enter, update and retrieve station metadata easily and efficiently. The system will provide accurate station/channel information for active stations to the SCSN real-time processing system, as will as station/channel information for stations that have parametric data at the SCEDC i.e., for users retrieving data via STP. Additionally, the SIS will supply information required to generate dataless SEED and COSMOS V0 volumes and allow stations to be added to the system with a minimum, but incomplete set of information using predefined defaults that can be easily updated as more information becomes available. Finally, the system will facilitate statewide metadata exchange for both real-time processing and provide a common approach to CISN historic station metadata. Moment Tensor Solutions: The SCEDC is currently archiving and delivering Moment Magnitudes and Moment Tensor Solutions (MTS) produced by the SCSN in real-time and post-processing solutions for events spanning back to 1999. The automatic MTS runs on all local events with magnitudes > 3.0, and all regional events > 3.5. The distributed solution automatically creates links from all USGS Simpson Maps to a text e-mail summary solution, creates a .gif image of the solution, and updates the moment tensor database tables at the SCEDC. Searchable Scanned Waveforms Site: The Caltech Seismological Lab has made available 12,223 scanned images of pre-digital analog recordings of major earthquakes recorded in Southern California between 1962 and 1992 at http://www.data.scec.org/research/scans/. The SCEDC has developed a searchable web interface that allows users to search the available files, select multiple files for download and then retrieve a zipped file containing the results. Scanned images of paper records for M>3.5 southern California earthquakes and several significant teleseisms are available for download via the SCEDC through this search tool.

Recognition of pornographic web pages by classifying texts and images.

PubMed

Hu, Weiming; Wu, Ou; Chen, Zhouyao; Fu, Zhouyu; Maybank, Steve

2007-06-01

With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can be easily accessed. It is important to recognize such unsuitable, offensive, or pornographic Web pages. In this paper, a novel framework for recognizing pornographic Web pages is described. A C4.5 decision tree is used to divide Web pages, according to content representations, into continuous text pages, discrete text pages, and image pages. These three categories of Web pages are handled, respectively, by a continuous text classifier, a discrete text classifier, and an algorithm that fuses the results from the image classifier and the discrete text classifier. In the continuous text classifier, statistical and semantic features are used to recognize pornographic texts. In the discrete text classifier, the naive Bayes rule is used to calculate the probability that a discrete text is pornographic. In the image classifier, the object's contour-based features are extracted to recognize pornographic images. In the text and image fusion algorithm, the Bayes theory is used to combine the recognition results from images and texts. Experimental results demonstrate that the continuous text classifier outperforms the traditional keyword-statistics-based classifier, the contour-based image classifier outperforms the traditional skin-region-based image classifier, the results obtained by our fusion algorithm outperform those by either of the individual classifiers, and our framework can be adapted to different categories of Web pages.

Multi-clues image retrieval based on improved color invariants

NASA Astrophysics Data System (ADS)

Liu, Liu; Li, Jian-Xun

2012-05-01

At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

Multi-instance learning based on instance consistency for image retrieval

NASA Astrophysics Data System (ADS)

Zhang, Miao; Wu, Zhize; Wan, Shouhong; Yue, Lihua; Yin, Bangjie

2017-07-01

Multiple-instance learning (MIL) has been successfully utilized in image retrieval. Existing approaches cannot select positive instances correctly from positive bags which may result in a low accuracy. In this paper, we propose a new image retrieval approach called multiple instance learning based on instance-consistency (MILIC) to mitigate such issue. First, we select potential positive instances effectively in each positive bag by ranking instance-consistency (IC) values of instances. Then, we design a feature representation scheme, which can represent the relationship among bags and instances, based on potential positive instances to convert a bag into a single instance. Finally, we can use a standard single-instance learning strategy, such as the support vector machine, for performing object-based image retrieval. Experimental results on two challenging data sets show the effectiveness of our proposal in terms of accuracy and run time.

Quality of the written radiology report: a review of the literature.

PubMed

Pool, Felicity; Goergen, Stacy

2010-08-01

A literature review was carried out, guided by the question, What are the important elements of a high-quality radiology written report? Two papers known to the authors were used as a basis for 5 PubMed search strategies. Exclusion criteria were applied to retrieved citations. Reference lists of retrieved citations were scanned for additional relevant papers and exclusion criteria applied to these. Web sites of professional radiology organizations were scanned for guidelines relating to the written radiology report. Retrieved guidelines were appraised using the Appraisal of Guidelines for Research & Evaluation instrument. Methodologies of retrieved papers were not suitable for conventional appraisal, and an evidence table was constructed. The search strategy identified 25 published papers and 4 guidelines. Published study methodologies included 1 randomized controlled trial; 1 before-and-after study of interventions; 10 observational studies, audits, or analyses; 12 surveys; and 1 narrative review of the literature. Existing guidelines have a number of weaknesses with regard to scope and purpose, methods of development, stakeholder consultation, and editorial independence and applicability. There is a major gap in published studies relating to testing of interventions to improve report quality using conventional randomized controlled trial methods. Published studies and guidelines generally support report content, including clinical history, examination quality, description of findings, comparison, and diagnosis. Important report attributes include accuracy, clarity, and certainty. There is wide variation in the language used to describe imaging findings and diagnostic certainty. Survey participants strongly preferred reports with structured or itemized formats, but few studies exist regarding the effect of report structure on quality. Copyright 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Hypertext Image Retrieval: The Evolution of an Application.

ERIC Educational Resources Information Center

Roberts, G. Louis; Kenney, Carol E.

1991-01-01

Describes the development and implementation of a full-text image retrieval system at the Boeing Commercial Airplane Group. The conversion of card formats to a microcomputer-based system using HyperCard is described; the online system architecture is explained; and future plans are discussed, including conversion to digital images. (LRW)

Millimeter-wave Imaging Radiometer (MIR) data processing and development of water vapor retrieval algorithms

NASA Technical Reports Server (NTRS)

Chang, L. Aron

1995-01-01

This document describes the progress of the task of the Millimeter-wave Imaging Radiometer (MIR) data processing and the development of water vapor retrieval algorithms, for the second six-month performing period. Aircraft MIR data from two 1995 field experiments were collected and processed with a revised data processing software. Two revised versions of water vapor retrieval algorithm were developed, one for the execution of retrieval on a supercomputer platform, and one for using pressure as the vertical coordinate. Two implementations of incorporating products from other sensors into the water vapor retrieval system, one from the Special Sensor Microwave Imager (SSM/I), the other from the High-resolution Interferometer Sounder (HIS). Water vapor retrievals were performed for both airborne MIR data and spaceborne SSM/T-2 data, during field experiments of TOGA/COARE, CAMEX-1, and CAMEX-2. The climatology of water vapor during TOGA/COARE was examined by SSM/T-2 soundings and conventional rawinsonde.

SU-D-BRD-02: A Web-Based Image Processing and Plan Evaluation Platform (WIPPEP) for Future Cloud-Based Radiotherapy

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

Chai, X; Liu, L; Xing, L

Purpose: Visualization and processing of medical images and radiation treatment plan evaluation have traditionally been constrained to local workstations with limited computation power and ability of data sharing and software update. We present a web-based image processing and planning evaluation platform (WIPPEP) for radiotherapy applications with high efficiency, ubiquitous web access, and real-time data sharing. Methods: This software platform consists of three parts: web server, image server and computation server. Each independent server communicates with each other through HTTP requests. The web server is the key component that provides visualizations and user interface through front-end web browsers and relay informationmore » to the backend to process user requests. The image server serves as a PACS system. The computation server performs the actual image processing and dose calculation. The web server backend is developed using Java Servlets and the frontend is developed using HTML5, Javascript, and jQuery. The image server is based on open source DCME4CHEE PACS system. The computation server can be written in any programming language as long as it can send/receive HTTP requests. Our computation server was implemented in Delphi, Python and PHP, which can process data directly or via a C++ program DLL. Results: This software platform is running on a 32-core CPU server virtually hosting the web server, image server, and computation servers separately. Users can visit our internal website with Chrome browser, select a specific patient, visualize image and RT structures belonging to this patient and perform image segmentation running Delphi computation server and Monte Carlo dose calculation on Python or PHP computation server. Conclusion: We have developed a webbased image processing and plan evaluation platform prototype for radiotherapy. This system has clearly demonstrated the feasibility of performing image processing and plan evaluation platform through a web browser and exhibited potential for future cloud based radiotherapy.« less

Stratification-Based Outlier Detection over the Deep Web.

PubMed

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

Description and testing of the Geo Data Portal: Data integration framework and Web processing services for environmental science collaboration

USGS Publications Warehouse

Blodgett, David L.; Booth, Nathaniel L.; Kunicki, Thomas C.; Walker, Jordan I.; Viger, Roland J.

2011-01-01

Interest in sharing interdisciplinary environmental modeling results and related data is increasing among scientists. The U.S. Geological Survey Geo Data Portal project enables data sharing by assembling open-standard Web services into an integrated data retrieval and analysis Web application design methodology that streamlines time-consuming and resource-intensive data management tasks. Data-serving Web services allow Web-based processing services to access Internet-available data sources. The Web processing services developed for the project create commonly needed derivatives of data in numerous formats. Coordinate reference system manipulation and spatial statistics calculation components implemented for the Web processing services were confirmed using ArcGIS 9.3.1, a geographic information science software package. Outcomes of the Geo Data Portal project support the rapid development of user interfaces for accessing and manipulating environmental data.

Stratification-Based Outlier Detection over the Deep Web

PubMed Central

Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S.; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

2016-01-01

For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

Surfing for suicide methods and help: content analysis of websites retrieved with search engines in Austria and the United States.

PubMed

Till, Benedikt; Niederkrotenthaler, Thomas

2014-08-01

The Internet provides a variety of resources for individuals searching for suicide-related information. Structured content-analytic approaches to assess intercultural differences in web contents retrieved with method-related and help-related searches are scarce. We used the 2 most popular search engines (Google and Yahoo/Bing) to retrieve US-American and Austrian search results for the term suicide, method-related search terms (e.g., suicide methods, how to kill yourself, painless suicide, how to hang yourself), and help-related terms (e.g., suicidal thoughts, suicide help) on February 11, 2013. In total, 396 websites retrieved with US search engines and 335 websites from Austrian searches were analyzed with content analysis on the basis of current media guidelines for suicide reporting. We assessed the quality of websites and compared findings across search terms and between the United States and Austria. In both countries, protective outweighed harmful website characteristics by approximately 2:1. Websites retrieved with method-related search terms (e.g., how to hang yourself) contained more harmful (United States: P < .001, Austria: P < .05) and fewer protective characteristics (United States: P < .001, Austria: P < .001) compared to the term suicide. Help-related search terms (e.g., suicidal thoughts) yielded more websites with protective characteristics (United States: P = .07, Austria: P < .01). Websites retrieved with U.S. search engines generally had more protective characteristics (P < .001) than searches with Austrian search engines. Resources with harmful characteristics were better ranked than those with protective characteristics (United States: P < .01, Austria: P < .05). The quality of suicide-related websites obtained depends on the search terms used. Preventive efforts to improve the ranking of preventive web content, particularly regarding method-related search terms, seem necessary. © Copyright 2014 Physicians Postgraduate Press, Inc.

Intelligent distributed medical image management

NASA Astrophysics Data System (ADS)

Garcia, Hong-Mei C.; Yun, David Y.

1995-05-01

The rapid advancements in high performance global communication have accelerated cooperative image-based medical services to a new frontier. Traditional image-based medical services such as radiology and diagnostic consultation can now fully utilize multimedia technologies in order to provide novel services, including remote cooperative medical triage, distributed virtual simulation of operations, as well as cross-country collaborative medical research and training. Fast (efficient) and easy (flexible) retrieval of relevant images remains a critical requirement for the provision of remote medical services. This paper describes the database system requirements, identifies technological building blocks for meeting the requirements, and presents a system architecture for our target image database system, MISSION-DBS, which has been designed to fulfill the goals of Project MISSION (medical imaging support via satellite integrated optical network) -- an experimental high performance gigabit satellite communication network with access to remote supercomputing power, medical image databases, and 3D visualization capabilities in addition to medical expertise anywhere and anytime around the country. The MISSION-DBS design employs a synergistic fusion of techniques in distributed databases (DDB) and artificial intelligence (AI) for storing, migrating, accessing, and exploring images. The efficient storage and retrieval of voluminous image information is achieved by integrating DDB modeling and AI techniques for image processing while the flexible retrieval mechanisms are accomplished by combining attribute- based and content-based retrievals.

Content-based retrieval of historical Ottoman documents stored as textual images.

PubMed

Saykol, Ediz; Sinop, Ali Kemal; Güdükbay, Ugur; Ulusoy, Ozgür; Cetin, A Enis

2004-03-01

There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a framework for content-based retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domain based on angular and distance span of shapes are used to extract the symbols. In order to make content-based retrieval in historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in textual images. The querying process does not require decompression of images. The new content-based retrieval framework is also applicable to many other document archives using different scripts.

TRECVID: the utility of a content-based video retrieval evaluation

NASA Astrophysics Data System (ADS)

Hauptmann, Alexander G.

2006-01-01

TRECVID, an annual retrieval evaluation benchmark organized by NIST, encourages research in information retrieval from digital video. TRECVID benchmarking covers both interactive and manual searching by end users, as well as the benchmarking of some supporting technologies including shot boundary detection, extraction of semantic features, and the automatic segmentation of TV news broadcasts. Evaluations done in the context of the TRECVID benchmarks show that generally, speech transcripts and annotations provide the single most important clue for successful retrieval. However, automatically finding the individual images is still a tremendous and unsolved challenge. The evaluations repeatedly found that none of the multimedia analysis and retrieval techniques provide a significant benefit over retrieval using only textual information such as from automatic speech recognition transcripts or closed captions. In interactive systems, we do find significant differences among the top systems, indicating that interfaces can make a huge difference for effective video/image search. For interactive tasks efficient interfaces require few key clicks, but display large numbers of images for visual inspection by the user. The text search finds the right context region in the video in general, but to select specific relevant images we need good interfaces to easily browse the storyboard pictures. In general, TRECVID has motivated the video retrieval community to be honest about what we don't know how to do well (sometimes through painful failures), and has focused us to work on the actual task of video retrieval, as opposed to flashy demos based on technological capabilities.

Satellite retrievals of Karenia brevis harmful algal blooms in the West Florida shelf using neural networks and impacts of temporal variabilities

NASA Astrophysics Data System (ADS)

El-Habashi, Ahmed; Duran, Claudia M.; Lovko, Vincent; Tomlinson, Michelle C.; Stumpf, Richard P.; Ahmed, Sam

2017-07-01

We apply a neural network (NN) technique to detect/track Karenia brevis harmful algal blooms (KB HABs) plaguing West Florida shelf (WFS) coasts from Visible-Infrared Imaging Radiometer Suite (VIIRS) satellite observations. Previously KB HABs detection primarily relied on the Moderate Resolution Imaging Spectroradiometer Aqua (MODIS-A) satellite, depending on its remote sensing reflectance signal at the 678-nm chlorophyll fluorescence band (Rrs678) needed for normalized fluorescence height and related red band difference retrieval algorithms. VIIRS, MODIS-A's successor, does not have a 678-nm channel. Instead, our NN uses Rrs at 486-, 551-, and 671-nm VIIRS channels to retrieve phytoplankton absorption at 443 nm (a). The retrieved a images are next filtered by applying limits, defined by (i) low Rrs551-nm backscatter and (ii) a minimum a value associated with KB HABs. The filtered residual images are then converted to show chlorophyll-a concentrations [Chla] and KB cell counts. VIIRS retrievals using our NN and five other retrieval algorithms were compared and evaluated against numerous in situ measurements made over the four-year 2012 to 2016 period, for which VIIRS data are available. These comparisons confirm the viability and higher retrieval accuracies of the NN technique, when combined with the filtering constraints, for effective detection of KB HABs. Analysis of these results as well as sequential satellite observations and recent field measurements underline the importance of short-term temporal variabilities on retrieval accuracies.

Dictionary Pruning with Visual Word Significance for Medical Image Retrieval

PubMed Central

Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G.; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

2016-01-01

Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency. PMID:27688597

Dictionary Pruning with Visual Word Significance for Medical Image Retrieval.

PubMed

Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

2016-02-12

Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency.

Optimisation of sea surface current retrieval using a maximum cross correlation technique on modelled sea surface temperature

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Eriksson, Leif; Carvajal, Gisela

2017-04-01

Using sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real time implementation has not been possible. Validation studies are too region-specific or uncertain, due to the errors induced by the images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the three parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of Western Europe, and the best of nine settings and eight temporal resolutions are determined. For all regions, tracking a small 5 km pattern from the first image over a large 30 km region around its original location on a second image, separated from the first image by 6 to 9 hours returned the most accurate results. Moreover, for all regions, the problem is not inaccurate results but missing results, where the velocity is too low to be picked by the retrieval. The results are consistent both with limitations caused by ocean surface current dynamics and with the available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible now, for search and rescue operations, pollution confinement or even for more energy efficient and comfortable ship navigation.

Data Archival and Retrieval Enhancement (DARE) Metadata Modeling and Its User Interface

NASA Technical Reports Server (NTRS)

Hyon, Jason J.; Borgen, Rosana B.

1996-01-01

The Defense Nuclear Agency (DNA) has acquired terabytes of valuable data which need to be archived and effectively distributed to the entire nuclear weapons effects community and others...This paper describes the DARE (Data Archival and Retrieval Enhancement) metadata model and explains how it is used as a source for generating HyperText Markup Language (HTML)or Standard Generalized Markup Language (SGML) documents for access through web browsers such as Netscape.

PubMed Interact: an Interactive Search Application for MEDLINE/PubMed

PubMed Central

Muin, Michael; Fontelo, Paul; Ackerman, Michael

2006-01-01

Online search and retrieval systems are important resources for medical literature research. Progressive Web 2.0 technologies provide opportunities to improve search strategies and user experience. Using PHP, Document Object Model (DOM) manipulation and Asynchronous JavaScript and XML (Ajax), PubMed Interact allows greater functionality so users can refine search parameters with ease and interact with the search results to retrieve and display relevant information and related articles. PMID:17238658

Developing a Philippine Cancer Grid. Part 1: Building a Prototype for a Data Retrieval System for Breast Cancer Research Using Medical Ontologies

NASA Astrophysics Data System (ADS)

Coronel, Andrei D.; Saldana, Rafael P.

Cancer is a leading cause of morbidity and mortality in the Philippines. Developed within the context of a Philippine Cancer Grid, the present study used web development technologies such as PHP, MySQL, and Apache server to build a prototype data retrieval system for breast cancer research that incorporates medical ontologies from the Unified Medical Language System (UMLS).

A service protocol for post-processing of medical images on the mobile device

NASA Astrophysics Data System (ADS)

He, Longjun; Ming, Xing; Xu, Lang; Liu, Qian

2014-03-01

With computing capability and display size growing, the mobile device has been used as a tool to help clinicians view patient information and medical images anywhere and anytime. It is uneasy and time-consuming for transferring medical images with large data size from picture archiving and communication system to mobile client, since the wireless network is unstable and limited by bandwidth. Besides, limited by computing capability, memory and power endurance, it is hard to provide a satisfactory quality of experience for radiologists to handle some complex post-processing of medical images on the mobile device, such as real-time direct interactive three-dimensional visualization. In this work, remote rendering technology is employed to implement the post-processing of medical images instead of local rendering, and a service protocol is developed to standardize the communication between the render server and mobile client. In order to make mobile devices with different platforms be able to access post-processing of medical images, the Extensible Markup Language is taken to describe this protocol, which contains four main parts: user authentication, medical image query/ retrieval, 2D post-processing (e.g. window leveling, pixel values obtained) and 3D post-processing (e.g. maximum intensity projection, multi-planar reconstruction, curved planar reformation and direct volume rendering). And then an instance is implemented to verify the protocol. This instance can support the mobile device access post-processing of medical image services on the render server via a client application or on the web page.

QMachine: commodity supercomputing in web browsers

PubMed Central

2014-01-01

Background Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics’ “Big Data” from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine. Results QM is an open-sourced, publicly available web service that acts as a messaging system for posting tasks and retrieving results over HTTP. The illustrative application described here distributes the analyses of 20 Streptococcus pneumoniae genomes for shared suffixes. Because all analytical and data retrieval tasks are executed by volunteer machines, few server resources are required. Any modern web browser can submit those tasks and/or volunteer to execute them without installing any extra plugins or programs. A client library provides high-level distribution templates including MapReduce. This stark departure from the current reliance on expensive server hardware running “download and install” software has already gathered substantial community interest, as QM received more than 2.2 million API calls from 87 countries in 12 months. Conclusions QM was found adequate to deliver the sort of scalable bioinformatics solutions that computation- and data-intensive workflows require. Paradoxically, the sandboxed execution of code by web browsers was also found to enable them, as compute nodes, to address critical privacy concerns that characterize biomedical environments. PMID:24913605

Occam's razor: supporting visual query expression for content-based image queries

NASA Astrophysics Data System (ADS)

Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.

2005-01-01

This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).

Occam"s razor: supporting visual query expression for content-based image queries

NASA Astrophysics Data System (ADS)

Venters, Colin C.; Hartley, Richard J.; Hewitt, William T.

2004-12-01

This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).

CerebralWeb: a Cytoscape.js plug-in to visualize networks stratified by subcellular localization.

PubMed

Frias, Silvia; Bryan, Kenneth; Brinkman, Fiona S L; Lynn, David J

2015-01-01

CerebralWeb is a light-weight JavaScript plug-in that extends Cytoscape.js to enable fast and interactive visualization of molecular interaction networks stratified based on subcellular localization or other user-supplied annotation. The application is designed to be easily integrated into any website and is configurable to support customized network visualization. CerebralWeb also supports the automatic retrieval of Cerebral-compatible localizations for human, mouse and bovine genes via a web service and enables the automated parsing of Cytoscape compatible XGMML network files. CerebralWeb currently supports embedded network visualization on the InnateDB (www.innatedb.com) and Allergy and Asthma Portal (allergen.innatedb.com) database and analysis resources. Database tool URL: http://www.innatedb.com/CerebralWeb © The Author(s) 2015. Published by Oxford University Press.

Learning About The Internet Bibliography And Beginner’s Guide

DTIC Science & Technology

1994-01-01

are eight parts to this document, all beginning with the acadlist. Strangelove, Michael, comp. "Directory of Electronic Journals and Newsletters/X^l...WEB World Wide Web (WWW) is a tool that merges the techniques of information retrieval and hypertext to make an easy but powerful global information...data and changes in theories . Sometimes, conversation helps to clarify articles, illuminate new perceptions of theories , and sustain us through our

OntoTrader: An Ontological Web Trading Agent Approach for Environmental Information Retrieval

PubMed Central

Iribarne, Luis; Padilla, Nicolás; Ayala, Rosa; Asensio, José A.; Criado, Javier

2014-01-01

Modern Web-based Information Systems (WIS) are becoming increasingly necessary to provide support for users who are in different places with different types of information, by facilitating their access to the information, decision making, workgroups, and so forth. Design of these systems requires the use of standardized methods and techniques that enable a common vocabulary to be defined to represent the underlying knowledge. Thus, mediation elements such as traders enrich the interoperability of web components in open distributed systems. These traders must operate with other third-party traders and/or agents in the system, which must also use a common vocabulary for communication between them. This paper presents the OntoTrader architecture, an Ontological Web Trading agent based on the OMG ODP trading standard. It also presents the ontology needed by some system agents to communicate with the trading agent and the behavioral framework for the SOLERES OntoTrader agent, an Environmental Management Information System (EMIS). This framework implements a “Query-Searching/Recovering-Response” information retrieval model using a trading service, SPARQL notation, and the JADE platform. The paper also presents reflection, delegation and, federation mediation models and describes formalization, an experimental testing environment in three scenarios, and a tool which allows our proposal to be evaluated and validated. PMID:24977211

[A systematic evaluation of application of the web-based cancer database].

PubMed

Huang, Tingting; Liu, Jialin; Li, Yong; Zhang, Rui

2013-10-01

In order to support the theory and practice of the web-based cancer database development in China, we applied a systematic evaluation to assess the development condition of the web-based cancer databases at home and abroad. We performed computer-based retrieval of the Ovid-MEDLINE, Springerlink, EBSCOhost, Wiley Online Library and CNKI databases, the papers of which were published between Jan. 1995 and Dec. 2011, and retrieved the references of these papers by hand. We selected qualified papers according to the pre-established inclusion and exclusion criteria, and carried out information extraction and analysis of the papers. Eventually, searching the online database, we obtained 1244 papers, and checking the reference lists, we found other 19 articles. Thirty-one articles met the inclusion and exclusion criteria and we extracted the proofs and assessed them. Analyzing these evidences showed that the U.S.A. counted for 26% in the first place. Thirty-nine percent of these web-based cancer databases are comprehensive cancer databases. As for single cancer databases, breast cancer and prostatic cancer are on the top, both counting for 10% respectively. Thirty-two percent of the cancer database are associated with cancer gene information. For the technical applications, MySQL and PHP applied most widely, nearly 23% each.

OntoTrader: an ontological Web trading agent approach for environmental information retrieval.

PubMed

Iribarne, Luis; Padilla, Nicolás; Ayala, Rosa; Asensio, José A; Criado, Javier

2014-01-01

Modern Web-based Information Systems (WIS) are becoming increasingly necessary to provide support for users who are in different places with different types of information, by facilitating their access to the information, decision making, workgroups, and so forth. Design of these systems requires the use of standardized methods and techniques that enable a common vocabulary to be defined to represent the underlying knowledge. Thus, mediation elements such as traders enrich the interoperability of web components in open distributed systems. These traders must operate with other third-party traders and/or agents in the system, which must also use a common vocabulary for communication between them. This paper presents the OntoTrader architecture, an Ontological Web Trading agent based on the OMG ODP trading standard. It also presents the ontology needed by some system agents to communicate with the trading agent and the behavioral framework for the SOLERES OntoTrader agent, an Environmental Management Information System (EMIS). This framework implements a "Query-Searching/Recovering-Response" information retrieval model using a trading service, SPARQL notation, and the JADE platform. The paper also presents reflection, delegation and, federation mediation models and describes formalization, an experimental testing environment in three scenarios, and a tool which allows our proposal to be evaluated and validated.

Similarity estimation for reference image retrieval in mammograms using convolutional neural network

NASA Astrophysics Data System (ADS)

Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

2018-02-01

Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

Interagency Testing Committee

EPA Pesticide Factsheets

The ITC's web site is a dynamic interactive vehicle that enables industry to electronically submit unpublished data and for the public (including industry) to retrieve these data and other information created or reviewed by the ITC.

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data Via Hyrax Server Data Server

NASA Technical Reports Server (NTRS)

Habermann, Ted; Gallagher, James; Jelenak, Aleksandar; Potter, Nathan; Lee, Joe; Yang, Kent

2017-01-01

This study explored three candidate architectures with different types of objects and access paths for serving NASA Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the study were: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and netCDF4 data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3). Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.We will describe the three architectures and the use cases along with performance results and recommendations for further work.

CropEx Web-Based Agricultural Monitoring and Decision Support

NASA Technical Reports Server (NTRS)

Harvey. Craig; Lawhead, Joel

2011-01-01

CropEx is a Web-based agricultural Decision Support System (DSS) that monitors changes in crop health over time. It is designed to be used by a wide range of both public and private organizations, including individual producers and regional government offices with a vested interest in tracking vegetation health. The database and data management system automatically retrieve and ingest data for the area of interest. Another stores results of the processing and supports the DSS. The processing engine will allow server-side analysis of imagery with support for image sub-setting and a set of core raster operations for image classification, creation of vegetation indices, and change detection. The system includes the Web-based (CropEx) interface, data ingestion system, server-side processing engine, and a database processing engine. It contains a Web-based interface that has multi-tiered security profiles for multiple users. The interface provides the ability to identify areas of interest to specific users, user profiles, and methods of processing and data types for selected or created areas of interest. A compilation of programs is used to ingest available data into the system, classify that data, profile that data for quality, and make data available for the processing engine immediately upon the data s availability to the system (near real time). The processing engine consists of methods and algorithms used to process the data in a real-time fashion without copying, storing, or moving the raw data. The engine makes results available to the database processing engine for storage and further manipulation. The database processing engine ingests data from the image processing engine, distills those results into numerical indices, and stores each index for an area of interest. This process happens each time new data is ingested and processed for the area of interest, and upon subsequent database entries, the database processing engine qualifies each value for each area of interest and conducts a logical processing of results indicating when and where thresholds are exceeded. Reports are provided at regular, operator-determined intervals that include variances from thresholds and links to view raw data for verification, if necessary. The technology and method of development allow the code base to easily be modified for varied use in the real-time and near-real-time processing environments. In addition, the final product will be demonstrated as a means for rapid draft assessment of imagery.

A new image representation for compact and secure communication

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

Prasad, Lakshman; Skourikhine, A. N.

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

Surface retrievals from Hyperion EO1 using a new, fast, 1D-Var based retrieval code

NASA Astrophysics Data System (ADS)

Thelen, Jean-Claude; Havemann, Stephan; Wong, Gerald

2015-05-01

We have developed a new algorithm for the simultaneous retrieval of the atmospheric profiles (temperature, humidity, ozone and aerosol) and the surface reflectance from hyperspectral radiance measurements obtained from air/space-borne, hyperspectral imagers such as Hyperion EO-1. The new scheme, proposed here, consists of a fast radiative transfer code, based on empirical orthogonal functions (EOFs), in conjunction with a 1D-Var retrieval scheme. The inclusion of an 'exact' scattering code based on spherical harmonics, allows for an accurate treatment of Rayleigh scattering and scattering by aerosols, water droplets and ice-crystals, thus making it possible to also retrieve cloud and aerosol optical properties, although here we will concentrate on non-cloudy scenes. We successfully tested this new approach using hyperspectral images taken by Hyperion EO-1, an experimental pushbroom imaging spectrometer operated by NASA.

MARs Color Imager (MARCI) Daily Global Ozone Column Mapping from the Mars Reconnaissance Orbiter (MRO): A Survey of 2006-2010 Results

NASA Astrophysics Data System (ADS)

Clancy, R. T.; Wolff, M. J.; Malin, M. C.; Cantor, B. A.

2010-12-01

MARCI UV band imaging photometry within (260nm) and outside (320nm) the Hartley ozone band absorption supports daily global mapping of Mars ozone column abundances. Key retrieval issues include accurate UV radiometric calibrations, detailed specifications of surface and atmospheric background reflectance (surface albedo, atmospheric Raleigh and dust scattering/absorption), and simultaneous cloud retrievals. The implementation of accurate radiative transfer (RT) treatments of these processes has been accomplished (Wolff et al., 2010) such that daily global mapping retrievals for Mars ozone columns have been completed for the 2006-2010 period of MARCI global imaging. Ozone retrievals are most accurate for high column abundances associated with mid-to-high latitude regions during fall, winter, and spring seasons. We present a survey of these MARCI ozone column retrievals versus season, latitude, longitude, and year.

Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

2018-03-01

An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and <0.5 km, respectively. At RSP's footprint scale ( 323 m), mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

WebMedSA: a web-based framework for segmenting and annotating medical images using biomedical ontologies

NASA Astrophysics Data System (ADS)

Vega, Francisco; Pérez, Wilson; Tello, Andrés.; Saquicela, Victor; Espinoza, Mauricio; Solano-Quinde, Lizandro; Vidal, Maria-Esther; La Cruz, Alexandra

2015-12-01

Advances in medical imaging have fostered medical diagnosis based on digital images. Consequently, the number of studies by medical images diagnosis increases, thus, collaborative work and tele-radiology systems are required to effectively scale up to this diagnosis trend. We tackle the problem of the collaborative access of medical images, and present WebMedSA, a framework to manage large datasets of medical images. WebMedSA relies on a PACS and supports the ontological annotation, as well as segmentation and visualization of the images based on their semantic description. Ontological annotations can be performed directly on the volumetric image or at different image planes (e.g., axial, coronal, or sagittal); furthermore, annotations can be complemented after applying a segmentation technique. WebMedSA is based on three main steps: (1) RDF-ization process for extracting, anonymizing, and serializing metadata comprised in DICOM medical images into RDF/XML; (2) Integration of different biomedical ontologies (using L-MOM library), making this approach ontology independent; and (3) segmentation and visualization of annotated data which is further used to generate new annotations according to expert knowledge, and validation. Initial user evaluations suggest that WebMedSA facilitates the exchange of knowledge between radiologists, and provides the basis for collaborative work among them.

SU-E-T-220: A Web-Based Research System for Outcome Analysis of NSCLC Treated with SABR.

PubMed

Le, A; Yang, Y; Michalski, D; Heron, D; Huq, M

2012-06-01

To establish a web-based software system, an electronic patient record (ePR), to consolidate and evaluate clinical data, dose delivery and treatment outcomes for non small cell lung cancer (NSCLC) patients treated with hypofractionated stereotactic ablative radiation therapy (SABR) across institutions. The new trend of information technology in medical imaging and informatics is towards the development of an electronic patient record (ePR), in which all health and medical information of each patient are organized under the patient's name and identification number. The system has been developed using the Wamp Server, a package of Apache web server, PHP and MySQL database to facilitate patient data input and management, and evaluation of patient clinical data and dose delivery across institution using web technology. The data of each patient to be recorded in the database include pre-treatment clinical data, treatment plan in DICOM-RT format and follow-up data. The pre-treatment data include demographics data, pathology condition, cancer staging. The follow-up data include the survival status, local tumor control condition and toxicity. The clinical data are entered to the system through the web page while the treatment plan data will be imported from the treatment planning system (TPS) using DICOM communication. The collection of data of NSCLC patients treated with SABR stored in the ePR is always accessible and can be retrieved and processed in the future. The core of the ePR is the database which integrates all patient data in one location. The web-based DICOM RT ePR system utilizes the current state-of-the-art medical informatics approach to investigate the combination and consolidation of patient data and outcome results. This will allow clinically-driven data mining for dose distributions and resulting treatment outcome in connection with biological modeling of the treatment parameters to quantify the efficacy of SABR in treating NSCLC patients. © 2012 American Association of Physicists in Medicine.

A selective deficit in imageable concepts: a window to the organization of the conceptual system

PubMed Central

Gvion, Aviah; Friedmann, Naama

2013-01-01

Nissim, a 64 years old Hebrew-speaking man who sustained an ischemic infarct in the left occipital lobe, exhibited an intriguing pattern. He could hold a deep and fluent conversation about abstract and complex issues, such as the social risks in unemployment, but failed to retrieve imageable words such as ball, spoon, carrot, or giraffe. A detailed study of the words he could and could not retrieve, in tasks of picture naming, tactile naming, and naming to definition, indicated that whereas he was able to retrieve abstract words, he had severe difficulties when trying to retrieve imageable words. The same dissociation also applied for proper names—he could retrieve names of people who have no visual image attached to their representation (such as the son of the biblical Abraham), but could not name people who had a visual image (such as his own son, or Barack Obama). When he tried to produce imageable words, he mainly produced perseverations and empty speech, and some semantic paraphasias. He did not produce perseverations when he tried to retrieve abstract words. This suggests that perseverations may occur when the phonological production system produces a word without proper activation in the semantic lexicon. Nissim evinced a similar dissociation in comprehension—he could understand abstract words and sentences but failed to understand sentences with imageable words, and to match spoken imageable words to pictures or to semantically related imageable words. He was able to understand proverbs with imageable literal meaning but abstract figurative meaning. His comprehension was impaired also in tasks of semantic associations of pictures, pointing to a conceptual, rather than lexical source of the deficit. His visual perception as well as his phonological input and output lexicons and buffers (assessed by auditory lexical decision, word and sentence repetition, and writing to dictation) were intact, supporting a selective conceptual system impairment. He was able to retrieve gestures for objects and pictures he saw, indicating that his access to concepts often sufficed for the activation of the motoric information but did not suffice for access to the entry in the semantic lexicon. These results show that imageable concepts can be selectively impaired, and shed light on the organization of conceptual-semantic system. PMID:23785321